Ethereum_time_series.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# Practicing Time series\n",
        "\n",
        "* Predict the ethereum prices based on previous data"
      ],
      "metadata": {
        "id": "WdIUF_pSc6IE"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "0g0MxM-3UC1Q",
        "outputId": "953c4ff6-2f88-4636-8be2-d3d79cbddb31"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         Date        Open        High         Low       Close   Adj Close  \\\n",
              "0  2017-11-09  308.644989  329.451996  307.056000  320.884003  320.884003   \n",
              "1  2017-11-10  320.670990  324.717987  294.541992  299.252991  299.252991   \n",
              "2  2017-11-11  298.585999  319.453003  298.191986  314.681000  314.681000   \n",
              "3  2017-11-12  314.690002  319.153015  298.513000  307.907990  307.907990   \n",
              "4  2017-11-13  307.024994  328.415009  307.024994  316.716003  316.716003   \n",
              "\n",
              "         Volume  \n",
              "0  8.932500e+08  \n",
              "1  8.859860e+08  \n",
              "2  8.423010e+08  \n",
              "3  1.613480e+09  \n",
              "4  1.041890e+09  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-439a4a7b-cbb4-46fb-945e-bb3ceb274afe\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</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",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2017-11-09</td>\n",
              "      <td>308.644989</td>\n",
              "      <td>329.451996</td>\n",
              "      <td>307.056000</td>\n",
              "      <td>320.884003</td>\n",
              "      <td>320.884003</td>\n",
              "      <td>8.932500e+08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2017-11-10</td>\n",
              "      <td>320.670990</td>\n",
              "      <td>324.717987</td>\n",
              "      <td>294.541992</td>\n",
              "      <td>299.252991</td>\n",
              "      <td>299.252991</td>\n",
              "      <td>8.859860e+08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2017-11-11</td>\n",
              "      <td>298.585999</td>\n",
              "      <td>319.453003</td>\n",
              "      <td>298.191986</td>\n",
              "      <td>314.681000</td>\n",
              "      <td>314.681000</td>\n",
              "      <td>8.423010e+08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2017-11-12</td>\n",
              "      <td>314.690002</td>\n",
              "      <td>319.153015</td>\n",
              "      <td>298.513000</td>\n",
              "      <td>307.907990</td>\n",
              "      <td>307.907990</td>\n",
              "      <td>1.613480e+09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2017-11-13</td>\n",
              "      <td>307.024994</td>\n",
              "      <td>328.415009</td>\n",
              "      <td>307.024994</td>\n",
              "      <td>316.716003</td>\n",
              "      <td>316.716003</td>\n",
              "      <td>1.041890e+09</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-439a4a7b-cbb4-46fb-945e-bb3ceb274afe')\"\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-439a4a7b-cbb4-46fb-945e-bb3ceb274afe 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-439a4a7b-cbb4-46fb-945e-bb3ceb274afe');\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-e384f0c9-9190-4dd0-853f-f7e3c1f6940a\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-e384f0c9-9190-4dd0-853f-f7e3c1f6940a')\"\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-e384f0c9-9190-4dd0-853f-f7e3c1f6940a button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 59
        }
      ],
      "source": [
        "import pandas as pd\n",
        "\n",
        "eth_df = pd.read_csv('ETH-USD.csv')\n",
        "eth_df.head()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "eth_df['Date'].min()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "d2fXjX1RK3s-",
        "outputId": "a7adc1e8-7226-4979-c3d1-61fa5cf86494"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'2017-11-09'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 60
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "eth_df['Date'].max()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "RPyegmioLUZN",
        "outputId": "6248faf9-b58d-4366-9c22-4343044aa3b1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'2023-12-21'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "btc_df = pd.read_csv('BTC-USD.csv')\n",
        "btc_df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "OIcuK7CXLXR3",
        "outputId": "70ae3cec-a8fc-4682-f965-c4ab825fa4b5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         Date        Open        High         Low       Close   Adj Close  \\\n",
              "0  2014-09-17  465.864014  468.174011  452.421997  457.334015  457.334015   \n",
              "1  2014-09-18  456.859985  456.859985  413.104004  424.440002  424.440002   \n",
              "2  2014-09-19  424.102997  427.834991  384.532013  394.795990  394.795990   \n",
              "3  2014-09-20  394.673004  423.295990  389.882996  408.903992  408.903992   \n",
              "4  2014-09-21  408.084991  412.425995  393.181000  398.821014  398.821014   \n",
              "\n",
              "       Volume  \n",
              "0  21056800.0  \n",
              "1  34483200.0  \n",
              "2  37919700.0  \n",
              "3  36863600.0  \n",
              "4  26580100.0  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-52cf69d0-d228-40d1-8dc1-9899bc74967f\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</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",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2014-09-17</td>\n",
              "      <td>465.864014</td>\n",
              "      <td>468.174011</td>\n",
              "      <td>452.421997</td>\n",
              "      <td>457.334015</td>\n",
              "      <td>457.334015</td>\n",
              "      <td>21056800.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2014-09-18</td>\n",
              "      <td>456.859985</td>\n",
              "      <td>456.859985</td>\n",
              "      <td>413.104004</td>\n",
              "      <td>424.440002</td>\n",
              "      <td>424.440002</td>\n",
              "      <td>34483200.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2014-09-19</td>\n",
              "      <td>424.102997</td>\n",
              "      <td>427.834991</td>\n",
              "      <td>384.532013</td>\n",
              "      <td>394.795990</td>\n",
              "      <td>394.795990</td>\n",
              "      <td>37919700.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2014-09-20</td>\n",
              "      <td>394.673004</td>\n",
              "      <td>423.295990</td>\n",
              "      <td>389.882996</td>\n",
              "      <td>408.903992</td>\n",
              "      <td>408.903992</td>\n",
              "      <td>36863600.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2014-09-21</td>\n",
              "      <td>408.084991</td>\n",
              "      <td>412.425995</td>\n",
              "      <td>393.181000</td>\n",
              "      <td>398.821014</td>\n",
              "      <td>398.821014</td>\n",
              "      <td>26580100.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-52cf69d0-d228-40d1-8dc1-9899bc74967f')\"\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-52cf69d0-d228-40d1-8dc1-9899bc74967f 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-52cf69d0-d228-40d1-8dc1-9899bc74967f');\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-7f297e9c-628e-47ca-9b4f-98cfc7da48b2\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-7f297e9c-628e-47ca-9b4f-98cfc7da48b2')\"\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-7f297e9c-628e-47ca-9b4f-98cfc7da48b2 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 62
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "btc_df[\"Date\"].min()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "Tx5-00MILaNI",
        "outputId": "de8d4a13-7c88-4f77-ecbb-5c3fd448a3fb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'2014-09-17'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 63
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "btc_df[\"Date\"].max()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "S2TAuKpvLnjz",
        "outputId": "e7fbce0e-0eca-4ccf-b290-2c3fdfd856fd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'2023-12-21'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 64
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# remove all rows before 2017-11-09\n",
        "btc_df = btc_df[btc_df['Date'] >= '2017-11-09']\n",
        "btc_df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "GCq-ohrtLrYW",
        "outputId": "add97b73-dc86-4b42-96e2-fca3c5c6958c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            Date          Open          High           Low         Close  \\\n",
              "1149  2017-11-09   7446.830078   7446.830078   7101.520020   7143.580078   \n",
              "1150  2017-11-10   7173.729980   7312.000000   6436.870117   6618.140137   \n",
              "1151  2017-11-11   6618.609863   6873.149902   6204.220215   6357.600098   \n",
              "1152  2017-11-12   6295.450195   6625.049805   5519.009766   5950.069824   \n",
              "1153  2017-11-13   5938.250000   6811.189941   5844.290039   6559.490234   \n",
              "...          ...           ...           ...           ...           ...   \n",
              "3378  2023-12-17  42236.109375  42359.496094  41274.542969  41364.664063   \n",
              "3379  2023-12-18  41348.203125  42720.296875  40530.257813  42623.539063   \n",
              "3380  2023-12-19  42641.511719  43354.296875  41826.335938  42270.527344   \n",
              "3381  2023-12-20           NaN           NaN           NaN           NaN   \n",
              "3382  2023-12-21  43648.125000  43725.050781  43355.367188  43504.792969   \n",
              "\n",
              "         Adj Close        Volume  \n",
              "1149   7143.580078  3.226250e+09  \n",
              "1150   6618.140137  5.208250e+09  \n",
              "1151   6357.600098  4.908680e+09  \n",
              "1152   5950.069824  8.957350e+09  \n",
              "1153   6559.490234  6.263250e+09  \n",
              "...            ...           ...  \n",
              "3378  41364.664063  1.667870e+10  \n",
              "3379  42623.539063  2.522464e+10  \n",
              "3380  42270.527344  2.317100e+10  \n",
              "3381           NaN           NaN  \n",
              "3382  43504.792969  2.910162e+10  \n",
              "\n",
              "[2234 rows x 7 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-752b9f8d-9990-4d75-a2ef-24544a77b5d0\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</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",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1149</th>\n",
              "      <td>2017-11-09</td>\n",
              "      <td>7446.830078</td>\n",
              "      <td>7446.830078</td>\n",
              "      <td>7101.520020</td>\n",
              "      <td>7143.580078</td>\n",
              "      <td>7143.580078</td>\n",
              "      <td>3.226250e+09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1150</th>\n",
              "      <td>2017-11-10</td>\n",
              "      <td>7173.729980</td>\n",
              "      <td>7312.000000</td>\n",
              "      <td>6436.870117</td>\n",
              "      <td>6618.140137</td>\n",
              "      <td>6618.140137</td>\n",
              "      <td>5.208250e+09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1151</th>\n",
              "      <td>2017-11-11</td>\n",
              "      <td>6618.609863</td>\n",
              "      <td>6873.149902</td>\n",
              "      <td>6204.220215</td>\n",
              "      <td>6357.600098</td>\n",
              "      <td>6357.600098</td>\n",
              "      <td>4.908680e+09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1152</th>\n",
              "      <td>2017-11-12</td>\n",
              "      <td>6295.450195</td>\n",
              "      <td>6625.049805</td>\n",
              "      <td>5519.009766</td>\n",
              "      <td>5950.069824</td>\n",
              "      <td>5950.069824</td>\n",
              "      <td>8.957350e+09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1153</th>\n",
              "      <td>2017-11-13</td>\n",
              "      <td>5938.250000</td>\n",
              "      <td>6811.189941</td>\n",
              "      <td>5844.290039</td>\n",
              "      <td>6559.490234</td>\n",
              "      <td>6559.490234</td>\n",
              "      <td>6.263250e+09</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",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3378</th>\n",
              "      <td>2023-12-17</td>\n",
              "      <td>42236.109375</td>\n",
              "      <td>42359.496094</td>\n",
              "      <td>41274.542969</td>\n",
              "      <td>41364.664063</td>\n",
              "      <td>41364.664063</td>\n",
              "      <td>1.667870e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3379</th>\n",
              "      <td>2023-12-18</td>\n",
              "      <td>41348.203125</td>\n",
              "      <td>42720.296875</td>\n",
              "      <td>40530.257813</td>\n",
              "      <td>42623.539063</td>\n",
              "      <td>42623.539063</td>\n",
              "      <td>2.522464e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3380</th>\n",
              "      <td>2023-12-19</td>\n",
              "      <td>42641.511719</td>\n",
              "      <td>43354.296875</td>\n",
              "      <td>41826.335938</td>\n",
              "      <td>42270.527344</td>\n",
              "      <td>42270.527344</td>\n",
              "      <td>2.317100e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3381</th>\n",
              "      <td>2023-12-20</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3382</th>\n",
              "      <td>2023-12-21</td>\n",
              "      <td>43648.125000</td>\n",
              "      <td>43725.050781</td>\n",
              "      <td>43355.367188</td>\n",
              "      <td>43504.792969</td>\n",
              "      <td>43504.792969</td>\n",
              "      <td>2.910162e+10</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2234 rows × 7 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-752b9f8d-9990-4d75-a2ef-24544a77b5d0')\"\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-752b9f8d-9990-4d75-a2ef-24544a77b5d0 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-752b9f8d-9990-4d75-a2ef-24544a77b5d0');\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-eed120ac-3bb0-482f-82cf-34d330abacd5\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-eed120ac-3bb0-482f-82cf-34d330abacd5')\"\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-eed120ac-3bb0-482f-82cf-34d330abacd5 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_481982f3-e770-4d19-8cc6-8629323c15c2\">\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('btc_df')\"\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_481982f3-e770-4d19-8cc6-8629323c15c2 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('btc_df');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 65
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# set the index of eth_df to date col\n",
        "eth_df = eth_df.set_index('Date')\n",
        "eth_df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "id": "72CRo0SmMTFB",
        "outputId": "97494a81-00fb-44a2-acaa-ac345a897405"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                  Open        High         Low       Close   Adj Close  \\\n",
              "Date                                                                     \n",
              "2017-11-09  308.644989  329.451996  307.056000  320.884003  320.884003   \n",
              "2017-11-10  320.670990  324.717987  294.541992  299.252991  299.252991   \n",
              "2017-11-11  298.585999  319.453003  298.191986  314.681000  314.681000   \n",
              "2017-11-12  314.690002  319.153015  298.513000  307.907990  307.907990   \n",
              "2017-11-13  307.024994  328.415009  307.024994  316.716003  316.716003   \n",
              "\n",
              "                  Volume  \n",
              "Date                      \n",
              "2017-11-09  8.932500e+08  \n",
              "2017-11-10  8.859860e+08  \n",
              "2017-11-11  8.423010e+08  \n",
              "2017-11-12  1.613480e+09  \n",
              "2017-11-13  1.041890e+09  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-1003bfe2-37f6-4e31-91c8-5e01a06e56b9\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>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>2017-11-09</th>\n",
              "      <td>308.644989</td>\n",
              "      <td>329.451996</td>\n",
              "      <td>307.056000</td>\n",
              "      <td>320.884003</td>\n",
              "      <td>320.884003</td>\n",
              "      <td>8.932500e+08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-10</th>\n",
              "      <td>320.670990</td>\n",
              "      <td>324.717987</td>\n",
              "      <td>294.541992</td>\n",
              "      <td>299.252991</td>\n",
              "      <td>299.252991</td>\n",
              "      <td>8.859860e+08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-11</th>\n",
              "      <td>298.585999</td>\n",
              "      <td>319.453003</td>\n",
              "      <td>298.191986</td>\n",
              "      <td>314.681000</td>\n",
              "      <td>314.681000</td>\n",
              "      <td>8.423010e+08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-12</th>\n",
              "      <td>314.690002</td>\n",
              "      <td>319.153015</td>\n",
              "      <td>298.513000</td>\n",
              "      <td>307.907990</td>\n",
              "      <td>307.907990</td>\n",
              "      <td>1.613480e+09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-13</th>\n",
              "      <td>307.024994</td>\n",
              "      <td>328.415009</td>\n",
              "      <td>307.024994</td>\n",
              "      <td>316.716003</td>\n",
              "      <td>316.716003</td>\n",
              "      <td>1.041890e+09</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-1003bfe2-37f6-4e31-91c8-5e01a06e56b9')\"\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-1003bfe2-37f6-4e31-91c8-5e01a06e56b9 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-1003bfe2-37f6-4e31-91c8-5e01a06e56b9');\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-5430ee77-1389-4106-a062-b2031c4c900b\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-5430ee77-1389-4106-a062-b2031c4c900b')\"\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-5430ee77-1389-4106-a062-b2031c4c900b button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 66
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# drop all columns excepty close\n",
        "eth_df = eth_df.drop(columns=['Open', 'High', 'Low', 'Adj Close', 'Volume'])\n"
      ],
      "metadata": {
        "id": "NvtvmvyrOO9g"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "eth_df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "id": "JZ9IbKr7OYBe",
        "outputId": "bf9dce50-41a9-4663-e33f-203a7e99d9fb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                  Close\n",
              "Date                   \n",
              "2017-11-09   320.884003\n",
              "2017-11-10   299.252991\n",
              "2017-11-11   314.681000\n",
              "2017-11-12   307.907990\n",
              "2017-11-13   316.716003\n",
              "...                 ...\n",
              "2023-12-17  2196.481201\n",
              "2023-12-18  2217.273438\n",
              "2023-12-19  2177.872559\n",
              "2023-12-20          NaN\n",
              "2023-12-21  2192.711426\n",
              "\n",
              "[2234 rows x 1 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-a3605f5e-3ae1-4eb4-8799-d0e43f867ab7\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Close</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2017-11-09</th>\n",
              "      <td>320.884003</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-10</th>\n",
              "      <td>299.252991</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-11</th>\n",
              "      <td>314.681000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-12</th>\n",
              "      <td>307.907990</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-13</th>\n",
              "      <td>316.716003</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2023-12-17</th>\n",
              "      <td>2196.481201</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2023-12-18</th>\n",
              "      <td>2217.273438</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2023-12-19</th>\n",
              "      <td>2177.872559</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2023-12-20</th>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2023-12-21</th>\n",
              "      <td>2192.711426</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2234 rows × 1 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-a3605f5e-3ae1-4eb4-8799-d0e43f867ab7')\"\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-a3605f5e-3ae1-4eb4-8799-d0e43f867ab7 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-a3605f5e-3ae1-4eb4-8799-d0e43f867ab7');\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-598ab503-8fbc-45eb-8cd2-c67b7f0d7020\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-598ab503-8fbc-45eb-8cd2-c67b7f0d7020')\"\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-598ab503-8fbc-45eb-8cd2-c67b7f0d7020 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_9c5c0853-1ba3-4854-a26f-01dfb59f51c1\">\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('eth_df')\"\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_9c5c0853-1ba3-4854-a26f-01dfb59f51c1 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('eth_df');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 68
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# add the btc_df to the eth_df only include the close price of both\n",
        "# eth_df = eth_df.join(btc_df['Date'])\n",
        "# eth_df"
      ],
      "metadata": {
        "id": "KHc4O_VYM2bS"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "btc_df = btc_df.drop(columns=['Open', 'High', 'Low', 'Adj Close', 'Volume'])\n"
      ],
      "metadata": {
        "id": "XhKqiZL2PD29"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "btc_df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "yld3UNa9PHZA",
        "outputId": "1267213b-4571-4524-a25a-5332ed0ce9ef"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            Date         Close\n",
              "1149  2017-11-09   7143.580078\n",
              "1150  2017-11-10   6618.140137\n",
              "1151  2017-11-11   6357.600098\n",
              "1152  2017-11-12   5950.069824\n",
              "1153  2017-11-13   6559.490234\n",
              "...          ...           ...\n",
              "3378  2023-12-17  41364.664063\n",
              "3379  2023-12-18  42623.539063\n",
              "3380  2023-12-19  42270.527344\n",
              "3381  2023-12-20           NaN\n",
              "3382  2023-12-21  43504.792969\n",
              "\n",
              "[2234 rows x 2 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-7b83ba97-1cb2-48af-807e-753425296cbd\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Close</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1149</th>\n",
              "      <td>2017-11-09</td>\n",
              "      <td>7143.580078</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1150</th>\n",
              "      <td>2017-11-10</td>\n",
              "      <td>6618.140137</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1151</th>\n",
              "      <td>2017-11-11</td>\n",
              "      <td>6357.600098</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1152</th>\n",
              "      <td>2017-11-12</td>\n",
              "      <td>5950.069824</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1153</th>\n",
              "      <td>2017-11-13</td>\n",
              "      <td>6559.490234</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3378</th>\n",
              "      <td>2023-12-17</td>\n",
              "      <td>41364.664063</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3379</th>\n",
              "      <td>2023-12-18</td>\n",
              "      <td>42623.539063</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3380</th>\n",
              "      <td>2023-12-19</td>\n",
              "      <td>42270.527344</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3381</th>\n",
              "      <td>2023-12-20</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3382</th>\n",
              "      <td>2023-12-21</td>\n",
              "      <td>43504.792969</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2234 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-7b83ba97-1cb2-48af-807e-753425296cbd')\"\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-7b83ba97-1cb2-48af-807e-753425296cbd 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-7b83ba97-1cb2-48af-807e-753425296cbd');\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-f88dcdf0-106d-4804-b081-2cb021c44e62\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-f88dcdf0-106d-4804-b081-2cb021c44e62')\"\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-f88dcdf0-106d-4804-b081-2cb021c44e62 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_9083d180-59f3-4239-bb04-d3273ed9d2f3\">\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('btc_df')\"\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_9083d180-59f3-4239-bb04-d3273ed9d2f3 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('btc_df');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 71
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# set the index of eth_df to date col\n",
        "btc_df = btc_df.set_index('Date')\n",
        "btc_df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "id": "WNN8VdyVPK5O",
        "outputId": "e5c5dd52-1810-46c1-82b4-f1207222b2a0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                  Close\n",
              "Date                   \n",
              "2017-11-09  7143.580078\n",
              "2017-11-10  6618.140137\n",
              "2017-11-11  6357.600098\n",
              "2017-11-12  5950.069824\n",
              "2017-11-13  6559.490234"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-ddf7a56b-4261-45bb-b353-4e0172a76970\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Close</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2017-11-09</th>\n",
              "      <td>7143.580078</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-10</th>\n",
              "      <td>6618.140137</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-11</th>\n",
              "      <td>6357.600098</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-12</th>\n",
              "      <td>5950.069824</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-13</th>\n",
              "      <td>6559.490234</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ddf7a56b-4261-45bb-b353-4e0172a76970')\"\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-ddf7a56b-4261-45bb-b353-4e0172a76970 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-ddf7a56b-4261-45bb-b353-4e0172a76970');\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-d5346cd9-5158-40e3-985e-e676ca657293\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-d5346cd9-5158-40e3-985e-e676ca657293')\"\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-d5346cd9-5158-40e3-985e-e676ca657293 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 72
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# join btc_df and eth df\n",
        "combined_df = eth_df.join(btc_df['Close'], lsuffix='_eth', rsuffix='_btc')\n",
        "combined_df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "id": "uJX84G1xPMyU",
        "outputId": "1eab34bc-6c60-473a-d56a-a72052edc645"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              Close_eth     Close_btc\n",
              "Date                                 \n",
              "2017-11-09   320.884003   7143.580078\n",
              "2017-11-10   299.252991   6618.140137\n",
              "2017-11-11   314.681000   6357.600098\n",
              "2017-11-12   307.907990   5950.069824\n",
              "2017-11-13   316.716003   6559.490234\n",
              "...                 ...           ...\n",
              "2023-12-17  2196.481201  41364.664063\n",
              "2023-12-18  2217.273438  42623.539063\n",
              "2023-12-19  2177.872559  42270.527344\n",
              "2023-12-20          NaN           NaN\n",
              "2023-12-21  2192.711426  43504.792969\n",
              "\n",
              "[2234 rows x 2 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-45009f37-ead1-48ae-825d-4c10a31b3767\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Close_eth</th>\n",
              "      <th>Close_btc</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>2017-11-09</th>\n",
              "      <td>320.884003</td>\n",
              "      <td>7143.580078</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-10</th>\n",
              "      <td>299.252991</td>\n",
              "      <td>6618.140137</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-11</th>\n",
              "      <td>314.681000</td>\n",
              "      <td>6357.600098</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-12</th>\n",
              "      <td>307.907990</td>\n",
              "      <td>5950.069824</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-13</th>\n",
              "      <td>316.716003</td>\n",
              "      <td>6559.490234</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2023-12-17</th>\n",
              "      <td>2196.481201</td>\n",
              "      <td>41364.664063</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2023-12-18</th>\n",
              "      <td>2217.273438</td>\n",
              "      <td>42623.539063</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2023-12-19</th>\n",
              "      <td>2177.872559</td>\n",
              "      <td>42270.527344</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2023-12-20</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2023-12-21</th>\n",
              "      <td>2192.711426</td>\n",
              "      <td>43504.792969</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2234 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-45009f37-ead1-48ae-825d-4c10a31b3767')\"\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-45009f37-ead1-48ae-825d-4c10a31b3767 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-45009f37-ead1-48ae-825d-4c10a31b3767');\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-8d87fde3-e9a3-429f-ac9e-dd4ba062b214\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-8d87fde3-e9a3-429f-ac9e-dd4ba062b214')\"\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-8d87fde3-e9a3-429f-ac9e-dd4ba062b214 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_0cb79e1f-c019-4919-9ba1-ddbeec0bbb13\">\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('combined_df')\"\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_0cb79e1f-c019-4919-9ba1-ddbeec0bbb13 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('combined_df');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 74
        }
      ]
    },
    {
      "source": [
        "combined_df = eth_df.join(btc_df['Close'], lsuffix='_eth', rsuffix='_btc')"
      ],
      "cell_type": "code",
      "metadata": {
        "id": "SL98NmXWPgLg"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "combined_df.plot(figsize=(10, 7))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 636
        },
        "id": "5DdfQlvtPzj3",
        "outputId": "a76a32a7-65e8-4de4-c165-af7b6fb61a3f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: xlabel='Date'>"
            ]
          },
          "metadata": {},
          "execution_count": 75
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x700 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "HORIZON = 1\n",
        "WINDOW_SIZE = 7"
      ],
      "metadata": {
        "id": "ivu5UEUiPxWe"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Make a copy of the Bitcoin historical data with block reward feature\n",
        "# bitcoin_prices_windowed = bitcoin_prices_block.copy()\n",
        "\n",
        "# # Add windowed columns\n",
        "# for i in range(WINDOW_SIZE): # Shift values for each step in WINDOW_SIZE\n",
        "#   bitcoin_prices_windowed[f\"Price-{i+1}\"] = bitcoin_prices_windowed[\"Price\"].shift(periods=i+1)\n",
        "# bitcoin_prices_windowed.head(10)"
      ],
      "metadata": {
        "id": "Qyy6tXcCQboe"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "eth_prices_windowed = combined_df.copy()\n",
        "\n",
        "# Add windowed columns\n",
        "for i in range(WINDOW_SIZE):\n",
        "  eth_prices_windowed[f\"Price-{i+1}\"] = eth_prices_windowed[\"Close_eth\"].shift(periods=i+1)\n",
        "eth_prices_windowed.head(10)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 394
        },
        "id": "cvzLIbZAQdLv",
        "outputId": "e28f7391-0212-4bdc-d357-9444dd0cdc21"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             Close_eth    Close_btc     Price-1     Price-2     Price-3  \\\n",
              "Date                                                                      \n",
              "2017-11-09  320.884003  7143.580078         NaN         NaN         NaN   \n",
              "2017-11-10  299.252991  6618.140137  320.884003         NaN         NaN   \n",
              "2017-11-11  314.681000  6357.600098  299.252991  320.884003         NaN   \n",
              "2017-11-12  307.907990  5950.069824  314.681000  299.252991  320.884003   \n",
              "2017-11-13  316.716003  6559.490234  307.907990  314.681000  299.252991   \n",
              "2017-11-14  337.631012  6635.750000  316.716003  307.907990  314.681000   \n",
              "2017-11-15  333.356995  7315.540039  337.631012  316.716003  307.907990   \n",
              "2017-11-16  330.924011  7871.689941  333.356995  337.631012  316.716003   \n",
              "2017-11-17  332.394012  7708.990234  330.924011  333.356995  337.631012   \n",
              "2017-11-18  347.612000  7790.149902  332.394012  330.924011  333.356995   \n",
              "\n",
              "               Price-4     Price-5     Price-6     Price-7  \n",
              "Date                                                        \n",
              "2017-11-09         NaN         NaN         NaN         NaN  \n",
              "2017-11-10         NaN         NaN         NaN         NaN  \n",
              "2017-11-11         NaN         NaN         NaN         NaN  \n",
              "2017-11-12         NaN         NaN         NaN         NaN  \n",
              "2017-11-13  320.884003         NaN         NaN         NaN  \n",
              "2017-11-14  299.252991  320.884003         NaN         NaN  \n",
              "2017-11-15  314.681000  299.252991  320.884003         NaN  \n",
              "2017-11-16  307.907990  314.681000  299.252991  320.884003  \n",
              "2017-11-17  316.716003  307.907990  314.681000  299.252991  \n",
              "2017-11-18  337.631012  316.716003  307.907990  314.681000  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-b087fd3a-2c37-4456-bd53-f5fa37431beb\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Close_eth</th>\n",
              "      <th>Close_btc</th>\n",
              "      <th>Price-1</th>\n",
              "      <th>Price-2</th>\n",
              "      <th>Price-3</th>\n",
              "      <th>Price-4</th>\n",
              "      <th>Price-5</th>\n",
              "      <th>Price-6</th>\n",
              "      <th>Price-7</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2017-11-09</th>\n",
              "      <td>320.884003</td>\n",
              "      <td>7143.580078</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-10</th>\n",
              "      <td>299.252991</td>\n",
              "      <td>6618.140137</td>\n",
              "      <td>320.884003</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-11</th>\n",
              "      <td>314.681000</td>\n",
              "      <td>6357.600098</td>\n",
              "      <td>299.252991</td>\n",
              "      <td>320.884003</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-12</th>\n",
              "      <td>307.907990</td>\n",
              "      <td>5950.069824</td>\n",
              "      <td>314.681000</td>\n",
              "      <td>299.252991</td>\n",
              "      <td>320.884003</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-13</th>\n",
              "      <td>316.716003</td>\n",
              "      <td>6559.490234</td>\n",
              "      <td>307.907990</td>\n",
              "      <td>314.681000</td>\n",
              "      <td>299.252991</td>\n",
              "      <td>320.884003</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-14</th>\n",
              "      <td>337.631012</td>\n",
              "      <td>6635.750000</td>\n",
              "      <td>316.716003</td>\n",
              "      <td>307.907990</td>\n",
              "      <td>314.681000</td>\n",
              "      <td>299.252991</td>\n",
              "      <td>320.884003</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-15</th>\n",
              "      <td>333.356995</td>\n",
              "      <td>7315.540039</td>\n",
              "      <td>337.631012</td>\n",
              "      <td>316.716003</td>\n",
              "      <td>307.907990</td>\n",
              "      <td>314.681000</td>\n",
              "      <td>299.252991</td>\n",
              "      <td>320.884003</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-16</th>\n",
              "      <td>330.924011</td>\n",
              "      <td>7871.689941</td>\n",
              "      <td>333.356995</td>\n",
              "      <td>337.631012</td>\n",
              "      <td>316.716003</td>\n",
              "      <td>307.907990</td>\n",
              "      <td>314.681000</td>\n",
              "      <td>299.252991</td>\n",
              "      <td>320.884003</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-17</th>\n",
              "      <td>332.394012</td>\n",
              "      <td>7708.990234</td>\n",
              "      <td>330.924011</td>\n",
              "      <td>333.356995</td>\n",
              "      <td>337.631012</td>\n",
              "      <td>316.716003</td>\n",
              "      <td>307.907990</td>\n",
              "      <td>314.681000</td>\n",
              "      <td>299.252991</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-18</th>\n",
              "      <td>347.612000</td>\n",
              "      <td>7790.149902</td>\n",
              "      <td>332.394012</td>\n",
              "      <td>330.924011</td>\n",
              "      <td>333.356995</td>\n",
              "      <td>337.631012</td>\n",
              "      <td>316.716003</td>\n",
              "      <td>307.907990</td>\n",
              "      <td>314.681000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b087fd3a-2c37-4456-bd53-f5fa37431beb')\"\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-b087fd3a-2c37-4456-bd53-f5fa37431beb 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-b087fd3a-2c37-4456-bd53-f5fa37431beb');\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-5a64704b-eb7e-4537-b183-283f97920992\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-5a64704b-eb7e-4537-b183-283f97920992')\"\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-5a64704b-eb7e-4537-b183-283f97920992 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 80
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "# Let's create X & y, remove the NaN's and convert to float32 to prevent TensorFlow errors\n",
        "X = eth_prices_windowed.dropna().drop(\"Close_eth\", axis=1).astype(np.float32)\n",
        "y = eth_prices_windowed.dropna()[\"Close_eth\"].astype(np.float32)\n",
        "X.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "id": "Egj4qmEUQx1X",
        "outputId": "6b8adc94-7e44-4f84-9559-ff3a442cf65a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              Close_btc     Price-1     Price-2     Price-3     Price-4  \\\n",
              "Date                                                                      \n",
              "2017-11-16  7871.689941  333.356995  337.631012  316.716003  307.907990   \n",
              "2017-11-17  7708.990234  330.924011  333.356995  337.631012  316.716003   \n",
              "2017-11-18  7790.149902  332.394012  330.924011  333.356995  337.631012   \n",
              "2017-11-19  8036.490234  347.612000  332.394012  330.924011  333.356995   \n",
              "2017-11-20  8200.639648  354.385986  347.612000  332.394012  330.924011   \n",
              "\n",
              "               Price-5     Price-6     Price-7  \n",
              "Date                                            \n",
              "2017-11-16  314.681000  299.252991  320.884003  \n",
              "2017-11-17  307.907990  314.681000  299.252991  \n",
              "2017-11-18  316.716003  307.907990  314.681000  \n",
              "2017-11-19  337.631012  316.716003  307.907990  \n",
              "2017-11-20  333.356995  337.631012  316.716003  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-c6f3e8f2-c1ea-4fbe-a68b-1dd5c69ddcd1\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Close_btc</th>\n",
              "      <th>Price-1</th>\n",
              "      <th>Price-2</th>\n",
              "      <th>Price-3</th>\n",
              "      <th>Price-4</th>\n",
              "      <th>Price-5</th>\n",
              "      <th>Price-6</th>\n",
              "      <th>Price-7</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2017-11-16</th>\n",
              "      <td>7871.689941</td>\n",
              "      <td>333.356995</td>\n",
              "      <td>337.631012</td>\n",
              "      <td>316.716003</td>\n",
              "      <td>307.907990</td>\n",
              "      <td>314.681000</td>\n",
              "      <td>299.252991</td>\n",
              "      <td>320.884003</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-17</th>\n",
              "      <td>7708.990234</td>\n",
              "      <td>330.924011</td>\n",
              "      <td>333.356995</td>\n",
              "      <td>337.631012</td>\n",
              "      <td>316.716003</td>\n",
              "      <td>307.907990</td>\n",
              "      <td>314.681000</td>\n",
              "      <td>299.252991</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-18</th>\n",
              "      <td>7790.149902</td>\n",
              "      <td>332.394012</td>\n",
              "      <td>330.924011</td>\n",
              "      <td>333.356995</td>\n",
              "      <td>337.631012</td>\n",
              "      <td>316.716003</td>\n",
              "      <td>307.907990</td>\n",
              "      <td>314.681000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-19</th>\n",
              "      <td>8036.490234</td>\n",
              "      <td>347.612000</td>\n",
              "      <td>332.394012</td>\n",
              "      <td>330.924011</td>\n",
              "      <td>333.356995</td>\n",
              "      <td>337.631012</td>\n",
              "      <td>316.716003</td>\n",
              "      <td>307.907990</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-20</th>\n",
              "      <td>8200.639648</td>\n",
              "      <td>354.385986</td>\n",
              "      <td>347.612000</td>\n",
              "      <td>332.394012</td>\n",
              "      <td>330.924011</td>\n",
              "      <td>333.356995</td>\n",
              "      <td>337.631012</td>\n",
              "      <td>316.716003</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c6f3e8f2-c1ea-4fbe-a68b-1dd5c69ddcd1')\"\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-c6f3e8f2-c1ea-4fbe-a68b-1dd5c69ddcd1 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-c6f3e8f2-c1ea-4fbe-a68b-1dd5c69ddcd1');\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-2133bbf4-9f58-4dca-99f8-ed036648582a\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-2133bbf4-9f58-4dca-99f8-ed036648582a')\"\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-2133bbf4-9f58-4dca-99f8-ed036648582a button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 82
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rs_RoqQqRI3D",
        "outputId": "37014eea-5fc7-45d1-f50a-e6889988b4bc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Date\n",
              "2017-11-16    330.924011\n",
              "2017-11-17    332.394012\n",
              "2017-11-18    347.612000\n",
              "2017-11-19    354.385986\n",
              "2017-11-20    366.730011\n",
              "Name: Close_eth, dtype: float32"
            ]
          },
          "metadata": {},
          "execution_count": 83
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Make train and test sets\n",
        "split_size = int(len(X) * 0.8)\n",
        "X_train, y_train = X[:split_size], y[:split_size]\n",
        "X_test, y_test = X[split_size:], y[split_size:]\n",
        "len(X_train), len(y_train), len(X_test), len(y_test)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-1aXiFOGRM32",
        "outputId": "4a933f21-f075-483b-e397-355e8059155e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1780, 1780, 445, 445)"
            ]
          },
          "metadata": {},
          "execution_count": 84
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import tensorflow as tf\n",
        "\n",
        "tf.random.set_seed(42)\n",
        "\n",
        "# Make multivariate time series model\n",
        "model_6 = tf.keras.Sequential([\n",
        "  tf.keras.layers.Dense(128, activation=\"relu\"),\n",
        "  # layers.Dense(128, activation=\"relu\"), # adding an extra layer here should lead to beating the naive model\n",
        "  tf.keras.layers.Dense(HORIZON)\n",
        "], name=\"model_6_dense_multivariate\")\n",
        "\n",
        "# Compile\n",
        "model_6.compile(loss=\"mae\",\n",
        "                optimizer=tf.keras.optimizers.Adam(),\n",
        "                metrics=[\"mae\"])\n",
        "\n",
        "# Fit\n",
        "model_6.fit(X_train,\n",
        "            y_train,\n",
        "            epochs=100,\n",
        "            batch_size=128,\n",
        "            validation_data=(X_test, y_test),\n",
        "            # callbacks=[create_model_checkpoint(model_name=model_6.name)]\n",
        "            )"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XVPjJO5ERRbQ",
        "outputId": "6bf04ff8-720d-475a-befb-b1628fb95f8f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/100\n",
            "14/14 [==============================] - 2s 59ms/step - loss: 341.6541 - mae: 341.6541 - val_loss: 129.9708 - val_mae: 129.9708\n",
            "Epoch 2/100\n",
            "14/14 [==============================] - 0s 20ms/step - loss: 182.7340 - mae: 182.7340 - val_loss: 50.9489 - val_mae: 50.9489\n",
            "Epoch 3/100\n",
            "14/14 [==============================] - 0s 10ms/step - loss: 83.7554 - mae: 83.7554 - val_loss: 64.0891 - val_mae: 64.0891\n",
            "Epoch 4/100\n",
            "14/14 [==============================] - 0s 5ms/step - loss: 75.6871 - mae: 75.6871 - val_loss: 66.7740 - val_mae: 66.7740\n",
            "Epoch 5/100\n",
            "14/14 [==============================] - 0s 5ms/step - loss: 68.6121 - mae: 68.6121 - val_loss: 68.8425 - val_mae: 68.8425\n",
            "Epoch 6/100\n",
            "14/14 [==============================] - 0s 5ms/step - loss: 73.2057 - mae: 73.2057 - val_loss: 58.2086 - val_mae: 58.2086\n",
            "Epoch 7/100\n",
            "14/14 [==============================] - 0s 5ms/step - loss: 75.0484 - mae: 75.0484 - val_loss: 85.3666 - val_mae: 85.3666\n",
            "Epoch 8/100\n",
            "14/14 [==============================] - 0s 4ms/step - loss: 66.4195 - mae: 66.4195 - val_loss: 46.7859 - val_mae: 46.7859\n",
            "Epoch 9/100\n",
            "14/14 [==============================] - 0s 5ms/step - loss: 60.5485 - mae: 60.5485 - val_loss: 54.8694 - val_mae: 54.8694\n",
            "Epoch 10/100\n",
            "14/14 [==============================] - 0s 6ms/step - loss: 61.9998 - mae: 61.9998 - val_loss: 51.1667 - val_mae: 51.1667\n",
            "Epoch 11/100\n",
            "14/14 [==============================] - 0s 4ms/step - loss: 68.2234 - mae: 68.2234 - val_loss: 60.9694 - val_mae: 60.9694\n",
            "Epoch 12/100\n",
            "14/14 [==============================] - 0s 4ms/step - loss: 64.6762 - mae: 64.6762 - val_loss: 58.1481 - val_mae: 58.1481\n",
            "Epoch 13/100\n",
            "14/14 [==============================] - 0s 4ms/step - loss: 57.3152 - mae: 57.3152 - val_loss: 41.3237 - val_mae: 41.3237\n",
            "Epoch 14/100\n",
            "14/14 [==============================] - 0s 5ms/step - loss: 56.9302 - mae: 56.9302 - val_loss: 89.7612 - val_mae: 89.7612\n",
            "Epoch 15/100\n",
            "14/14 [==============================] - 0s 5ms/step - loss: 56.6305 - mae: 56.6305 - val_loss: 53.2882 - val_mae: 53.2882\n",
            "Epoch 16/100\n",
            "14/14 [==============================] - 0s 6ms/step - loss: 52.9197 - mae: 52.9197 - val_loss: 68.5138 - val_mae: 68.5138\n",
            "Epoch 17/100\n",
            "14/14 [==============================] - 0s 4ms/step - loss: 54.0553 - mae: 54.0553 - val_loss: 48.6482 - val_mae: 48.6482\n",
            "Epoch 18/100\n",
            "14/14 [==============================] - 0s 4ms/step - loss: 57.9603 - mae: 57.9603 - val_loss: 60.4310 - val_mae: 60.4310\n",
            "Epoch 19/100\n",
            "14/14 [==============================] - 0s 4ms/step - loss: 55.3502 - mae: 55.3502 - val_loss: 75.8690 - val_mae: 75.8690\n",
            "Epoch 20/100\n",
            "14/14 [==============================] - 0s 5ms/step - loss: 52.0585 - mae: 52.0585 - val_loss: 55.4363 - val_mae: 55.4363\n",
            "Epoch 21/100\n",
            "14/14 [==============================] - 0s 5ms/step - loss: 49.5464 - mae: 49.5464 - val_loss: 49.4664 - val_mae: 49.4664\n",
            "Epoch 22/100\n",
            "14/14 [==============================] - 0s 5ms/step - loss: 48.8311 - mae: 48.8311 - val_loss: 38.5453 - val_mae: 38.5453\n",
            "Epoch 23/100\n",
            "14/14 [==============================] - 0s 6ms/step - loss: 51.5830 - mae: 51.5830 - val_loss: 58.2197 - val_mae: 58.2197\n",
            "Epoch 24/100\n",
            "14/14 [==============================] - 0s 5ms/step - loss: 50.2858 - mae: 50.2858 - val_loss: 59.5119 - val_mae: 59.5119\n",
            "Epoch 25/100\n",
            "14/14 [==============================] - 0s 5ms/step - loss: 52.7855 - mae: 52.7855 - val_loss: 67.8855 - val_mae: 67.8855\n",
            "Epoch 26/100\n",
            "14/14 [==============================] - 0s 6ms/step - loss: 53.5215 - mae: 53.5215 - val_loss: 40.2436 - val_mae: 40.2436\n",
            "Epoch 27/100\n",
            "14/14 [==============================] - 0s 5ms/step - loss: 52.3716 - mae: 52.3716 - val_loss: 42.8047 - val_mae: 42.8047\n",
            "Epoch 28/100\n",
            "14/14 [==============================] - 0s 7ms/step - loss: 47.0027 - mae: 47.0027 - val_loss: 35.5761 - val_mae: 35.5761\n",
            "Epoch 29/100\n",
            "14/14 [==============================] - 0s 6ms/step - loss: 48.6677 - mae: 48.6677 - val_loss: 46.7150 - val_mae: 46.7150\n",
            "Epoch 30/100\n",
            "14/14 [==============================] - 0s 6ms/step - loss: 54.3069 - mae: 54.3069 - val_loss: 108.8512 - val_mae: 108.8512\n",
            "Epoch 31/100\n",
            "14/14 [==============================] - 0s 7ms/step - loss: 54.9534 - mae: 54.9534 - val_loss: 50.9831 - val_mae: 50.9831\n",
            "Epoch 32/100\n",
            "14/14 [==============================] - 0s 5ms/step - loss: 44.6217 - mae: 44.6217 - val_loss: 36.7969 - val_mae: 36.7969\n",
            "Epoch 33/100\n",
            "14/14 [==============================] - 0s 7ms/step - loss: 44.9853 - mae: 44.9853 - val_loss: 42.0187 - val_mae: 42.0187\n",
            "Epoch 34/100\n",
            "14/14 [==============================] - 0s 6ms/step - loss: 45.8810 - mae: 45.8810 - val_loss: 41.0239 - val_mae: 41.0239\n",
            "Epoch 35/100\n",
            "14/14 [==============================] - 0s 6ms/step - loss: 47.9436 - mae: 47.9436 - val_loss: 34.1665 - val_mae: 34.1665\n",
            "Epoch 36/100\n",
            "14/14 [==============================] - 0s 6ms/step - loss: 48.2945 - mae: 48.2945 - val_loss: 34.4243 - val_mae: 34.4243\n",
            "Epoch 37/100\n",
            "14/14 [==============================] - 0s 5ms/step - loss: 47.5099 - mae: 47.5099 - val_loss: 57.2836 - val_mae: 57.2836\n",
            "Epoch 38/100\n",
            "14/14 [==============================] - 0s 6ms/step - loss: 45.9302 - mae: 45.9302 - val_loss: 51.2039 - val_mae: 51.2039\n",
            "Epoch 39/100\n",
            "14/14 [==============================] - 0s 6ms/step - loss: 49.5805 - mae: 49.5805 - val_loss: 43.8619 - val_mae: 43.8619\n",
            "Epoch 40/100\n",
            "14/14 [==============================] - 0s 7ms/step - loss: 44.1561 - mae: 44.1561 - val_loss: 37.1164 - val_mae: 37.1164\n",
            "Epoch 41/100\n",
            "14/14 [==============================] - 0s 5ms/step - loss: 47.8498 - mae: 47.8498 - val_loss: 108.1959 - val_mae: 108.1959\n",
            "Epoch 42/100\n",
            "14/14 [==============================] - 0s 6ms/step - loss: 52.5430 - mae: 52.5430 - val_loss: 34.3587 - val_mae: 34.3587\n",
            "Epoch 43/100\n",
            "14/14 [==============================] - 0s 7ms/step - loss: 45.3232 - mae: 45.3232 - val_loss: 39.1481 - val_mae: 39.1481\n",
            "Epoch 44/100\n",
            "14/14 [==============================] - 0s 6ms/step - loss: 46.8623 - mae: 46.8623 - val_loss: 71.9976 - val_mae: 71.9976\n",
            "Epoch 45/100\n",
            "14/14 [==============================] - 0s 6ms/step - loss: 45.9864 - mae: 45.9864 - val_loss: 43.7316 - val_mae: 43.7316\n",
            "Epoch 46/100\n",
            "14/14 [==============================] - 0s 8ms/step - loss: 51.7317 - mae: 51.7317 - val_loss: 45.1137 - val_mae: 45.1137\n",
            "Epoch 47/100\n",
            "14/14 [==============================] - 0s 6ms/step - loss: 44.8971 - mae: 44.8971 - val_loss: 39.6768 - val_mae: 39.6768\n",
            "Epoch 48/100\n",
            "14/14 [==============================] - 0s 5ms/step - loss: 42.6340 - mae: 42.6340 - val_loss: 60.4995 - val_mae: 60.4995\n",
            "Epoch 49/100\n",
            "14/14 [==============================] - 0s 5ms/step - loss: 47.4533 - mae: 47.4533 - val_loss: 37.1583 - val_mae: 37.1583\n",
            "Epoch 50/100\n",
            "14/14 [==============================] - 0s 6ms/step - loss: 43.2019 - mae: 43.2019 - val_loss: 33.8308 - val_mae: 33.8308\n",
            "Epoch 51/100\n",
            "14/14 [==============================] - 0s 6ms/step - loss: 49.7805 - mae: 49.7805 - val_loss: 33.0026 - val_mae: 33.0026\n",
            "Epoch 52/100\n",
            "14/14 [==============================] - 0s 4ms/step - loss: 42.9237 - mae: 42.9237 - val_loss: 46.8258 - val_mae: 46.8258\n",
            "Epoch 53/100\n",
            "14/14 [==============================] - 0s 6ms/step - loss: 47.4528 - mae: 47.4528 - val_loss: 85.3433 - val_mae: 85.3433\n",
            "Epoch 54/100\n",
            "14/14 [==============================] - 0s 4ms/step - loss: 48.7057 - mae: 48.7057 - val_loss: 54.7597 - val_mae: 54.7597\n",
            "Epoch 55/100\n",
            "14/14 [==============================] - 0s 6ms/step - loss: 43.2956 - mae: 43.2956 - val_loss: 32.7215 - val_mae: 32.7215\n",
            "Epoch 56/100\n",
            "14/14 [==============================] - 0s 4ms/step - loss: 44.8798 - mae: 44.8798 - val_loss: 33.5859 - val_mae: 33.5859\n",
            "Epoch 57/100\n",
            "14/14 [==============================] - 0s 5ms/step - loss: 43.1187 - mae: 43.1187 - val_loss: 46.7540 - val_mae: 46.7540\n",
            "Epoch 58/100\n",
            "14/14 [==============================] - 0s 4ms/step - loss: 43.9746 - mae: 43.9746 - val_loss: 42.3961 - val_mae: 42.3961\n",
            "Epoch 59/100\n",
            "14/14 [==============================] - 0s 5ms/step - loss: 44.7242 - mae: 44.7242 - val_loss: 46.0423 - val_mae: 46.0423\n",
            "Epoch 60/100\n",
            "14/14 [==============================] - 0s 4ms/step - loss: 42.6391 - mae: 42.6391 - val_loss: 42.8591 - val_mae: 42.8591\n",
            "Epoch 61/100\n",
            "14/14 [==============================] - 0s 6ms/step - loss: 42.8648 - mae: 42.8648 - val_loss: 40.3694 - val_mae: 40.3694\n",
            "Epoch 62/100\n",
            "14/14 [==============================] - 0s 6ms/step - loss: 42.1968 - mae: 42.1968 - val_loss: 37.9947 - val_mae: 37.9947\n",
            "Epoch 63/100\n",
            "14/14 [==============================] - 0s 7ms/step - loss: 44.7948 - mae: 44.7948 - val_loss: 33.0213 - val_mae: 33.0213\n",
            "Epoch 64/100\n",
            "14/14 [==============================] - 0s 10ms/step - loss: 44.9658 - mae: 44.9658 - val_loss: 33.1613 - val_mae: 33.1613\n",
            "Epoch 65/100\n",
            "14/14 [==============================] - 0s 9ms/step - loss: 44.8507 - mae: 44.8507 - val_loss: 40.8279 - val_mae: 40.8279\n",
            "Epoch 66/100\n",
            "14/14 [==============================] - 0s 8ms/step - loss: 45.6400 - mae: 45.6400 - val_loss: 48.2501 - val_mae: 48.2501\n",
            "Epoch 67/100\n",
            "14/14 [==============================] - 0s 9ms/step - loss: 47.3133 - mae: 47.3133 - val_loss: 33.0570 - val_mae: 33.0570\n",
            "Epoch 68/100\n",
            "14/14 [==============================] - 0s 9ms/step - loss: 42.4117 - mae: 42.4117 - val_loss: 44.6203 - val_mae: 44.6203\n",
            "Epoch 69/100\n",
            "14/14 [==============================] - 0s 9ms/step - loss: 42.6501 - mae: 42.6501 - val_loss: 39.9083 - val_mae: 39.9083\n",
            "Epoch 70/100\n",
            "14/14 [==============================] - 0s 9ms/step - loss: 41.6120 - mae: 41.6120 - val_loss: 36.2694 - val_mae: 36.2694\n",
            "Epoch 71/100\n",
            "14/14 [==============================] - 0s 10ms/step - loss: 42.1529 - mae: 42.1529 - val_loss: 52.1883 - val_mae: 52.1883\n",
            "Epoch 72/100\n",
            "14/14 [==============================] - 0s 8ms/step - loss: 45.8433 - mae: 45.8433 - val_loss: 32.3893 - val_mae: 32.3893\n",
            "Epoch 73/100\n",
            "14/14 [==============================] - 0s 9ms/step - loss: 51.9416 - mae: 51.9416 - val_loss: 97.0949 - val_mae: 97.0949\n",
            "Epoch 74/100\n",
            "14/14 [==============================] - 0s 9ms/step - loss: 51.2764 - mae: 51.2764 - val_loss: 74.6007 - val_mae: 74.6007\n",
            "Epoch 75/100\n",
            "14/14 [==============================] - 0s 9ms/step - loss: 45.4889 - mae: 45.4889 - val_loss: 47.9686 - val_mae: 47.9686\n",
            "Epoch 76/100\n",
            "14/14 [==============================] - 0s 7ms/step - loss: 44.7583 - mae: 44.7583 - val_loss: 70.8077 - val_mae: 70.8077\n",
            "Epoch 77/100\n",
            "14/14 [==============================] - 0s 9ms/step - loss: 45.6509 - mae: 45.6509 - val_loss: 82.8334 - val_mae: 82.8334\n",
            "Epoch 78/100\n",
            "14/14 [==============================] - 0s 8ms/step - loss: 46.5713 - mae: 46.5713 - val_loss: 34.3245 - val_mae: 34.3245\n",
            "Epoch 79/100\n",
            "14/14 [==============================] - 0s 9ms/step - loss: 45.3993 - mae: 45.3993 - val_loss: 32.8014 - val_mae: 32.8014\n",
            "Epoch 80/100\n",
            "14/14 [==============================] - 0s 9ms/step - loss: 45.8662 - mae: 45.8662 - val_loss: 32.7780 - val_mae: 32.7780\n",
            "Epoch 81/100\n",
            "14/14 [==============================] - 0s 8ms/step - loss: 42.4692 - mae: 42.4692 - val_loss: 33.1282 - val_mae: 33.1282\n",
            "Epoch 82/100\n",
            "14/14 [==============================] - 0s 8ms/step - loss: 42.0702 - mae: 42.0702 - val_loss: 39.2484 - val_mae: 39.2484\n",
            "Epoch 83/100\n",
            "14/14 [==============================] - 0s 8ms/step - loss: 42.8679 - mae: 42.8679 - val_loss: 53.2651 - val_mae: 53.2651\n",
            "Epoch 84/100\n",
            "14/14 [==============================] - 0s 7ms/step - loss: 50.9396 - mae: 50.9396 - val_loss: 39.0239 - val_mae: 39.0239\n",
            "Epoch 85/100\n",
            "14/14 [==============================] - 0s 11ms/step - loss: 43.1740 - mae: 43.1740 - val_loss: 42.4270 - val_mae: 42.4270\n",
            "Epoch 86/100\n",
            "14/14 [==============================] - 0s 10ms/step - loss: 44.3014 - mae: 44.3014 - val_loss: 39.4996 - val_mae: 39.4996\n",
            "Epoch 87/100\n",
            "14/14 [==============================] - 0s 10ms/step - loss: 41.7333 - mae: 41.7333 - val_loss: 45.3759 - val_mae: 45.3759\n",
            "Epoch 88/100\n",
            "14/14 [==============================] - 0s 8ms/step - loss: 41.7372 - mae: 41.7372 - val_loss: 35.6301 - val_mae: 35.6301\n",
            "Epoch 89/100\n",
            "14/14 [==============================] - 0s 9ms/step - loss: 47.9762 - mae: 47.9762 - val_loss: 38.6003 - val_mae: 38.6003\n",
            "Epoch 90/100\n",
            "14/14 [==============================] - 0s 8ms/step - loss: 48.4059 - mae: 48.4059 - val_loss: 35.1692 - val_mae: 35.1692\n",
            "Epoch 91/100\n",
            "14/14 [==============================] - 0s 8ms/step - loss: 49.8436 - mae: 49.8436 - val_loss: 52.4757 - val_mae: 52.4757\n",
            "Epoch 92/100\n",
            "14/14 [==============================] - 0s 9ms/step - loss: 60.6342 - mae: 60.6342 - val_loss: 106.6301 - val_mae: 106.6301\n",
            "Epoch 93/100\n",
            "14/14 [==============================] - 0s 7ms/step - loss: 56.1501 - mae: 56.1501 - val_loss: 61.2923 - val_mae: 61.2923\n",
            "Epoch 94/100\n",
            "14/14 [==============================] - 0s 7ms/step - loss: 48.1889 - mae: 48.1889 - val_loss: 39.7725 - val_mae: 39.7725\n",
            "Epoch 95/100\n",
            "14/14 [==============================] - 0s 5ms/step - loss: 42.4560 - mae: 42.4560 - val_loss: 35.3586 - val_mae: 35.3586\n",
            "Epoch 96/100\n",
            "14/14 [==============================] - 0s 6ms/step - loss: 43.3329 - mae: 43.3329 - val_loss: 65.3759 - val_mae: 65.3759\n",
            "Epoch 97/100\n",
            "14/14 [==============================] - 0s 5ms/step - loss: 44.9740 - mae: 44.9740 - val_loss: 47.9588 - val_mae: 47.9588\n",
            "Epoch 98/100\n",
            "14/14 [==============================] - 0s 6ms/step - loss: 42.5153 - mae: 42.5153 - val_loss: 33.2190 - val_mae: 33.2190\n",
            "Epoch 99/100\n",
            "14/14 [==============================] - 0s 6ms/step - loss: 42.5109 - mae: 42.5109 - val_loss: 67.0128 - val_mae: 67.0128\n",
            "Epoch 100/100\n",
            "14/14 [==============================] - 0s 5ms/step - loss: 43.1319 - mae: 43.1319 - val_loss: 37.9323 - val_mae: 37.9323\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<keras.src.callbacks.History at 0x78ea78326530>"
            ]
          },
          "metadata": {},
          "execution_count": 88
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model_6.summary()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "J5fu1X9TRrw7",
        "outputId": "a90de731-ab6c-49d5-9f83-4834d3f54b7a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"model_6_dense_multivariate\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " dense (Dense)               (None, 128)               1152      \n",
            "                                                                 \n",
            " dense_1 (Dense)             (None, 1)                 129       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 1281 (5.00 KB)\n",
            "Trainable params: 1281 (5.00 KB)\n",
            "Non-trainable params: 0 (0.00 Byte)\n",
            "_________________________________________________________________\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Make predictions on multivariate data\n",
        "model_6_preds = tf.squeeze(model_6.predict(X_test))\n",
        "model_6_preds[:10]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "b8g8ASraRuqo",
        "outputId": "9a0a987d-49c6-4aea-aec6-7ecb6dfa3134"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "14/14 [==============================] - 0s 2ms/step\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<tf.Tensor: shape=(10,), dtype=float32, numpy=\n",
              "array([1334.7512, 1322.1365, 1297.8569, 1331.9567, 1365.9224, 1363.9014,\n",
              "       1358.8566, 1343.0483, 1329.7842, 1327.1846], dtype=float32)>"
            ]
          },
          "metadata": {},
          "execution_count": 90
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_test[:10]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vfcqMAggSCsq",
        "outputId": "9ab46c69-f323-4bbe-d507-51442917ce58"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Date\n",
              "2022-10-01    1311.644409\n",
              "2022-10-02    1276.093506\n",
              "2022-10-03    1323.439209\n",
              "2022-10-04    1362.126587\n",
              "2022-10-05    1352.837158\n",
              "2022-10-06    1351.709473\n",
              "2022-10-07    1332.516968\n",
              "2022-10-08    1315.500488\n",
              "2022-10-09    1322.604248\n",
              "2022-10-10    1291.337646\n",
              "Name: Close_eth, dtype: float32"
            ]
          },
          "metadata": {},
          "execution_count": 91
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X_test"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "id": "SYgMHLqn5YMR",
        "outputId": "208b7b7c-6b15-48dd-ab58-8a500bc83d98"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "               Close_btc      Price-1      Price-2      Price-3      Price-4  \\\n",
              "Date                                                                           \n",
              "2022-10-01  19312.095703  1327.978638  1335.652344  1337.410889  1330.127686   \n",
              "2022-10-02  19044.107422  1311.644409  1327.978638  1335.652344  1337.410889   \n",
              "2022-10-03  19623.580078  1276.093506  1311.644409  1327.978638  1335.652344   \n",
              "2022-10-04  20336.843750  1323.439209  1276.093506  1311.644409  1327.978638   \n",
              "2022-10-05  20160.716797  1362.126587  1323.439209  1276.093506  1311.644409   \n",
              "...                  ...          ...          ...          ...          ...   \n",
              "2023-12-15  41929.757812  2316.579102  2260.648682  2202.038086  2224.578857   \n",
              "2023-12-16  42240.117188  2219.337402  2316.579102  2260.648682  2202.038086   \n",
              "2023-12-17  41364.664062  2226.926514  2219.337402  2316.579102  2260.648682   \n",
              "2023-12-18  42623.539062  2196.481201  2226.926514  2219.337402  2316.579102   \n",
              "2023-12-19  42270.527344  2217.273438  2196.481201  2226.926514  2219.337402   \n",
              "\n",
              "                Price-5      Price-6      Price-7  \n",
              "Date                                               \n",
              "2022-10-01  1335.320190  1294.216797  1317.993286  \n",
              "2022-10-02  1330.127686  1335.320190  1294.216797  \n",
              "2022-10-03  1337.410889  1330.127686  1335.320190  \n",
              "2022-10-04  1335.652344  1337.410889  1330.127686  \n",
              "2022-10-05  1327.978638  1335.652344  1337.410889  \n",
              "...                 ...          ...          ...  \n",
              "2023-12-15  2352.462646  2341.175293  2358.731934  \n",
              "2023-12-16  2224.578857  2352.462646  2341.175293  \n",
              "2023-12-17  2202.038086  2224.578857  2352.462646  \n",
              "2023-12-18  2260.648682  2202.038086  2224.578857  \n",
              "2023-12-19  2316.579102  2260.648682  2202.038086  \n",
              "\n",
              "[445 rows x 8 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-89eb4a51-84c4-485d-b672-c4868026036d\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Close_btc</th>\n",
              "      <th>Price-1</th>\n",
              "      <th>Price-2</th>\n",
              "      <th>Price-3</th>\n",
              "      <th>Price-4</th>\n",
              "      <th>Price-5</th>\n",
              "      <th>Price-6</th>\n",
              "      <th>Price-7</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2022-10-01</th>\n",
              "      <td>19312.095703</td>\n",
              "      <td>1327.978638</td>\n",
              "      <td>1335.652344</td>\n",
              "      <td>1337.410889</td>\n",
              "      <td>1330.127686</td>\n",
              "      <td>1335.320190</td>\n",
              "      <td>1294.216797</td>\n",
              "      <td>1317.993286</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-10-02</th>\n",
              "      <td>19044.107422</td>\n",
              "      <td>1311.644409</td>\n",
              "      <td>1327.978638</td>\n",
              "      <td>1335.652344</td>\n",
              "      <td>1337.410889</td>\n",
              "      <td>1330.127686</td>\n",
              "      <td>1335.320190</td>\n",
              "      <td>1294.216797</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-10-03</th>\n",
              "      <td>19623.580078</td>\n",
              "      <td>1276.093506</td>\n",
              "      <td>1311.644409</td>\n",
              "      <td>1327.978638</td>\n",
              "      <td>1335.652344</td>\n",
              "      <td>1337.410889</td>\n",
              "      <td>1330.127686</td>\n",
              "      <td>1335.320190</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-10-04</th>\n",
              "      <td>20336.843750</td>\n",
              "      <td>1323.439209</td>\n",
              "      <td>1276.093506</td>\n",
              "      <td>1311.644409</td>\n",
              "      <td>1327.978638</td>\n",
              "      <td>1335.652344</td>\n",
              "      <td>1337.410889</td>\n",
              "      <td>1330.127686</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-10-05</th>\n",
              "      <td>20160.716797</td>\n",
              "      <td>1362.126587</td>\n",
              "      <td>1323.439209</td>\n",
              "      <td>1276.093506</td>\n",
              "      <td>1311.644409</td>\n",
              "      <td>1327.978638</td>\n",
              "      <td>1335.652344</td>\n",
              "      <td>1337.410889</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",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2023-12-15</th>\n",
              "      <td>41929.757812</td>\n",
              "      <td>2316.579102</td>\n",
              "      <td>2260.648682</td>\n",
              "      <td>2202.038086</td>\n",
              "      <td>2224.578857</td>\n",
              "      <td>2352.462646</td>\n",
              "      <td>2341.175293</td>\n",
              "      <td>2358.731934</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2023-12-16</th>\n",
              "      <td>42240.117188</td>\n",
              "      <td>2219.337402</td>\n",
              "      <td>2316.579102</td>\n",
              "      <td>2260.648682</td>\n",
              "      <td>2202.038086</td>\n",
              "      <td>2224.578857</td>\n",
              "      <td>2352.462646</td>\n",
              "      <td>2341.175293</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2023-12-17</th>\n",
              "      <td>41364.664062</td>\n",
              "      <td>2226.926514</td>\n",
              "      <td>2219.337402</td>\n",
              "      <td>2316.579102</td>\n",
              "      <td>2260.648682</td>\n",
              "      <td>2202.038086</td>\n",
              "      <td>2224.578857</td>\n",
              "      <td>2352.462646</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2023-12-18</th>\n",
              "      <td>42623.539062</td>\n",
              "      <td>2196.481201</td>\n",
              "      <td>2226.926514</td>\n",
              "      <td>2219.337402</td>\n",
              "      <td>2316.579102</td>\n",
              "      <td>2260.648682</td>\n",
              "      <td>2202.038086</td>\n",
              "      <td>2224.578857</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2023-12-19</th>\n",
              "      <td>42270.527344</td>\n",
              "      <td>2217.273438</td>\n",
              "      <td>2196.481201</td>\n",
              "      <td>2226.926514</td>\n",
              "      <td>2219.337402</td>\n",
              "      <td>2316.579102</td>\n",
              "      <td>2260.648682</td>\n",
              "      <td>2202.038086</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>445 rows × 8 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-89eb4a51-84c4-485d-b672-c4868026036d')\"\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-89eb4a51-84c4-485d-b672-c4868026036d 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-89eb4a51-84c4-485d-b672-c4868026036d');\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-deb9c795-8373-4e2c-96b9-ffdb255ea6ac\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-deb9c795-8373-4e2c-96b9-ffdb255ea6ac')\"\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-deb9c795-8373-4e2c-96b9-ffdb255ea6ac button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_f26e3a23-8ef8-4309-b2f8-3a22394dc987\">\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('X_test')\"\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_f26e3a23-8ef8-4309-b2f8-3a22394dc987 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('X_test');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 105
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# plot the model_6_preds compared to y_test\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "plt.figure(figsize=(10, 7))\n",
        "plt.plot(y_test, label=\"y_test\")\n",
        "plt.plot(model_6_preds, label=\"model_6_preds\")\n",
        "# remove x axis\n",
        "plt.xticks([])\n",
        "# set x axis to the dates in X_test\n",
        "# plt.xticks(np.arange(0, len(X_test), 100), X_test[::100].index.Date, rotation=45)\n",
        "\n",
        "plt.legend()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 593
        },
        "id": "sm8-EtBW2gCR",
        "outputId": "8e2c86c7-006e-4e79-98da-087840dc5627"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x78ea70dc91b0>"
            ]
          },
          "metadata": {},
          "execution_count": 111
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x700 with 1 Axes>"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAA0cAAAIvCAYAAAC/aqAAAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzdd3hc1bXw4d+ZqjLq3b13Y2yaDcSYEgMxJJRAAgECgXBJDLnADSHtEkIKaYTcJEDyhWIIEFqA0MEUm+ICNrgX3CVbVi+j6e18f+xzpqjLlixLWu/z+JmZ02aPJEuzZq29tqbruo4QQgghhBBCDHGW/h6AEEIIIYQQQhwNJDgSQgghhBBCCCQ4EkIIIYQQQghAgiMhhBBCCCGEACQ4EkIIIYQQQghAgiMhhBBCCCGEACQ4EkIIIYQQQghAgiMhhBBCCCGEAMDW3wPoK7FYjMrKSrKystA0rb+HI4QQQgghhOgnuq7T0tLCsGHDsFg6zg8N2uCosrKSkSNH9vcwhBBCCCGEEEeJiooKRowY0eH+QRscZWVlAeoLkJ2d3c+jEUIIIYQQQvQXt9vNyJEj4zFCRwZtcGSW0mVnZ0twJIQQQgghhOhyuo00ZBBCCCGEEEIIJDgSQgghhBBCCECCIyGEEEIIIYQABvGco+6KRqOEw+H+HoYYhOx2O1artb+HIYQQQgghumnIBke6rlNVVUVTU1N/D0UMYrm5uZSWlspaW0IIIYQQA8CQDY7MwKi4uJiMjAx58yp6la7r+Hw+ampqACgrK+vnEQkhhBBCiK4MyeAoGo3GA6OCgoL+Ho4YpNLT0wGoqamhuLhYSuyEEEIIIY5yQ7IhgznHKCMjo59HIgY782dM5rUJIYQQQhz9hmRwZJJSOtHX5GdMCCGEEGLgGNLBkRBCCCGEEEKYJDgSQgghhBBCCCQ4GjLuvPNOjj322F695pIlS8jNze3VawohhBBCCNFfJDgSQgghhBBCCCQ4GlAee+wxCgoKCAaDKdsvuOACrrzyyg7PW7JkCT//+c9Zv349mqahaRpLliwBoKmpieuuu46ioiKys7M544wzWL9+ffzc9evXc/rpp5OVlUV2djbHHXcca9asYdmyZVxzzTU0NzfHr3nnnXf2xcsWQgghhBDiiBiS6xy1pus6/nC0X5473W7tdkezSy65hO9973u89NJLXHLJJYBaQ+fVV1/lrbfe6vC8r33ta2zatIk33niDt99+G4CcnJz4NdPT03n99dfJycnh73//O2eeeSaff/45+fn5fOMb32D27Nk88MADWK1W1q1bh91u5+STT+ZPf/oTd9xxB9u3bwfA5XIdzpdCCCGEEEKIfiXBEeAPR5l2x5v98txb7jqbDEf3vg3p6elcfvnlPPLII/Hg6PHHH2fUqFEsWLCg0/NcLhc2m43S0tL49g8//JCPP/6YmpoanE4nAH/4wx948cUXee6557j++uspLy/ntttuY8qUKQBMnDgxfn5OTg6apqVcUwghhBBCiIFKyuoGmG9/+9u89dZbHDhwAFAlc1dfffUhraezfv16PB4PBQUFuFyu+L89e/awa9cuAG699Vauu+46zjrrLH7zm9/EtwshhBBCCDHYSOYIVdq25a6z++25e2L27NnMmjWLxx57jIULF7J582ZeffXVQ3puj8dDWVkZy5Yta7PP7EJ35513cvnll/Pqq6/y+uuv87Of/YynnnqKCy+88JCeUwghhBBCiKOVBEeApmndLm07Glx33XX86U9/4sCBA5x11lmMHDmyy3McDgfRaOq8qjlz5lBVVYXNZmPMmDEdnjtp0iQmTZrELbfcwmWXXcYjjzzChRde2O41hRBCCCGEGKikrG4Auvzyy9m/fz//+Mc/+Na3vtWtc8aMGcOePXtYt24ddXV1BINBzjrrLObNm8cFF1zAW2+9xd69e1mxYgU/+clPWLNmDX6/nxtvvJFly5axb98+PvroIz755BOmTp0av6bH4+Gdd96hrq4On8/Xly9bCCGEEEKIPiXB0QCUk5PDxRdfjMvl4oILLujWORdffDHnnHMOp59+OkVFRfzrX/9C0zRee+015s+fzzXXXMOkSZP4+te/zr59+ygpKcFqtVJfX89VV13FpEmTuPTSSzn33HP5+c9/DsDJJ5/MDTfcwNe+9jWKior43e9+14evWgghhBBC9Jvdy2H7G/09ij6n6bqu9/cg+oLb7SYnJ4fm5mays7NT9gUCAfbs2cPYsWNJS0vrpxEenjPPPJPp06fz5z//ub+HIjoxGH7WhBBCCDHEeevh9+PU/dv3Qnpevw7nUHQWGyQbOBNtBACNjY0sW7aMZcuWcf/99/f3cIQQQgghxGCk67DsbsgbA+GkqRO+hgEZHHVXj8rq7r77bk444QSysrIoLi7mggsuiC8A2pqu65x77rlomsaLL76Ysq+8vJxFixaRkZFBcXExt912G5FIJOWYZcuWMWfOHJxOJxMmTGDJkiU9emGD1ezZs7n66qv57W9/y+TJk+Pbp0+fntKOO/nfE0880Y8jFkIIIYQQA07VRlj+W3jxO/BRUqVSsKX/xnQE9ChztHz5chYvXswJJ5xAJBLhxz/+MQsXLmTLli1kZmamHPunP/2p3bV3otEoixYtorS0lBUrVnDw4EGuuuoq7HY7v/71rwHYs2cPixYt4oYbbuCJJ57gnXfe4brrrqOsrIyzz+6flttHi71797a7/bXXXiMcDre7r6SkpA9HJIQQQgghBp2G3Yn7TfsS90OeIz+WI6hHwdEbb6ROwlqyZAnFxcWsXbuW+fPnx7evW7eOe+65hzVr1lBWVpZyzltvvcWWLVt4++23KSkp4dhjj+UXv/gFt99+O3feeScOh4O//e1vjB07lnvuuQeAqVOn8uGHH3LvvfcO+eCoI6NHj+7vIQghhBBCiMGicW/72wd55uiwutU1NzcDkJ+fH9/m8/m4/PLLue+++ygtLW1zzsqVK5k5c2ZKNuPss8/G7XazefPm+DFnnXVWynlnn302K1euPJzhCiGEEEIIIbrDDI6yh4MzqYFBcHBnjg45OIrFYtx8882ccsopzJgxI779lltu4eSTT+YrX/lKu+dVVVW1KfMyH1dVVXV6jNvtxu/3t3vdYDCI2+1O+SeEEEIIIYQ4BGZwdPpP4EcVMOU89Tg0uDNHh9ytbvHixWzatIkPP/wwvu2ll17i3Xff5bPPPuuVwfXE3XffHV9/RwghhBBCCHEYzOAob4y6dbjUrWSO2rrxxht55ZVXeO+99xgxYkR8+7vvvsuuXbvIzc3FZrNhs6nY6+KLL2bBggUAlJaWUl1dnXI987FZhtfRMdnZ2aSnp7c7ph/96Ec0NzfH/1VUVBzKSxNCCCGEEGJoi0Wh2XgvnWfMa3eawZFkjuJ0Xeemm27ihRdeYNmyZYwdOzZl/w9/+EOuu+66lG0zZ87k3nvv5fzzzwdg3rx5/OpXv6Kmpobi4mIAli5dSnZ2NtOmTYsf89prr6VcZ+nSpcybN6/DsTmdTpxOZ09ejhBCCCGEEKI19wGIRcDqgCyjuZqZORrk3ep6lDlavHgxjz/+OE8++SRZWVlUVVVRVVUVnwdUWlrKjBkzUv4BjBo1Kh5ILVy4kGnTpnHllVeyfv163nzzTX7605+yePHieHBzww03sHv3bn7wgx+wbds27r//fp555hluueWW3nztohMLFizg5ptv7vbxS5YsITc3t8/G0596+rUQQgghhBjQzJK63FFgsar7zix1O8gzRz0Kjh544AGam5tZsGABZWVl8X9PP/10t69htVp55ZVXsFqtzJs3jyuuuIKrrrqKu+66K37M2LFjefXVV1m6dCmzZs3innvu4cEHH5Q23oNIMBjkJz/5CaNHj8bpdDJmzBgefvjh/h6WEEIIIYRoPd8IEsHRIM8c9bisrqfaO2f06NFtyuZaW7BgQb80dhBHxqWXXkp1dTUPPfQQEyZM4ODBg8RisT57vlAohMPh6LPrCyGEEEIMGu0FR46hMefosNY5EkfeggULuOmmm7j55pvJy8ujpKSEf/zjH3i9Xq655hqysrKYMGECr7/+evyc5cuXc+KJJ+J0OikrK+OHP/whkUgkvt/r9XLVVVfhcrkoKyuLL76bLBgM8v3vf5/hw4eTmZnJSSedxLJlyw7pNbzxxhssX76c1157jbPOOosxY8Ywb948TjnllG6df/XVV3PBBRfw85//nKKiIrKzs7nhhhsIhUIpX6cbb7yRm2++mcLCwnjWcdOmTZx77rm4XC5KSkq48sorqaur69HX4v7772fixImkpaVRUlLCV7/61UP6OgghhBBCHJXazRxJt7qhQ9ch5O2ff4eQjXv00UcpLCzk448/5qabbuI73/kOl1xyCSeffDKffvopCxcu5Morr8Tn83HgwAG+9KUvccIJJ7B+/XoeeOABHnroIX75y1/Gr3fbbbexfPly/vOf//DWW2+xbNkyPv3005TnvPHGG1m5ciVPPfUUGzZs4JJLLuGcc85hx44dPR7/Sy+9xPHHH8/vfvc7hg8fzqRJk/j+97/f4RpW7XnnnXfYunUry5Yt41//+hfPP/98m1bujz76KA6Hg48++oi//e1vNDU1ccYZZzB79mzWrFnDG2+8QXV1NZdeemm3vxZr1qzhe9/7HnfddRfbt2/njTfeYP78+T3+GgghhBBCHLXcleo2J9GVWsrqhpKwD349rH+e+8eV4Mjs0SmzZs3ipz/9KaBamP/mN7+hsLCQb3/72wDccccdPPDAA2zYsIGXX36ZkSNH8te//hVN05gyZQqVlZXcfvvt3HHHHfh8Ph566CEef/xxzjzzTEAFFckt2svLy3nkkUcoLy9n2DD1dfr+97/PG2+8wSOPPMKvf/3rHo1/9+7dfPjhh6SlpfHCCy9QV1fHd7/7Xerr63nkkUe6dQ2Hw8HDDz9MRkYG06dP56677uK2227jF7/4BRaLivknTpzI7373u/g5v/zlL5k9e3bKeB9++GFGjhzJ559/zrBhw7r1tcjMzOS8884jKyuL0aNHM3v27B69fiGEEEKIo1rArW7TchPbHEOjIYMERwPQMcccE79vtVopKChg5syZ8W0lJSUA1NTUsHXrVubNm4emafH9p5xyCh6Ph/3799PY2EgoFOKkk06K78/Pz2fy5Mnxxxs3biQajTJp0qSUcQSDQQoKCno8/lgshqZpPPHEE+Tk5ADwxz/+ka9+9avcf//9Ha5llWzWrFlkZGTEH8+bNw+Px0NFRQWjR6t+/Mcdd1zKOevXr+e9997D5XK1ud6uXbvw+/1dfi2++MUvMnr0aMaNG8c555zDOeecw4UXXpgyFiGEEEKIAS1oBEfO7MQ2WedoCLFnqAxOfz13T0+x21Mea5qWss0MhHqrwYHH48FqtbJ27VqsVmvKvvYCja6UlZUxfPjweGAEMHXqVHRdZ//+/UycOPGwxwyQmZmakfN4PJx//vn89re/bXdMO3fu7PKaWVlZfPrppyxbtoy33nqLO+64gzvvvJNPPvlk0LYyF0IIIcQQYwZHaUnB0RBZ50iCIwBN63Fp20AxdepU/v3vf6Prejxo+uijj8jKymLEiBHk5+djt9tZvXo1o0aNAqCxsZHPP/+c0047DYDZs2cTjUapqanhC1/4wmGP6ZRTTuHZZ5/F4/HEg6vPP/8ci8WSUsLWmfXr1+P3++NZplWrVuFyuRg5cmSH58yZM4d///vfjBkzBput7Y/++PHju/xaANhsNs466yzOOussfvazn5Gbm8u7777LRRdd1O2vgRBCCCHEUUnXE9khc55R8v1oCCIhsA3OLsDSkGGQ++53v0tFRQU33XQT27Zt4z//+Q8/+9nPuPXWW7FYLLhcLq699lpuu+023n33XTZt2sTVV18dn7cDMGnSJL7xjW9w1VVX8fzzz7Nnzx4+/vhj7r77bl599dUej+nyyy+noKCAa665hi1btvD+++9z22238a1vfatbJXWgWnNfe+21bNmyhddee42f/exn3HjjjSnjbm3x4sU0NDRw2WWX8cknn7Br1y7efPNNrrnmGqLRaLe+Fq+88gp//vOfWbduHfv27eOxxx4jFoullN4JIYQQQgxYIS/oRvWRs53MEQzq7JFkjga54cOH89prr3Hbbbcxa9Ys8vPzufbaa+MNHQB+//vfx0vOsrKy+J//+R+am5tTrvPII4/wy1/+kv/5n//hwIEDFBYWMnfuXM4777wej8nlcrF06VJuuukmjj/+eAoKCrj00ktTOuh15cwzz2TixInMnz+fYDDIZZddxp133tnpOcOGDeOjjz7i9ttvZ+HChQSDQUaPHs0555wTD4C6+lrk5uby/PPPc+eddxIIBJg4cSL/+te/mD59eo+/DkIIIYQQRx2jpE632NDsSR9aW21gS4eIXx2Tka+2uyvh8zfgmK+DY+DPwdb0Q1nZdQBwu93k5OTQ3NxMdnZ2yr5AIMCePXsYO3YsaWlp/TRCcaiuvvpqmpqaePHFF/t7KF2SnzUhhBBCDBTuQJi/PvUKP957NY26i+rvbGVKadL76N9PAG8t3PARlM5Q2/5zI3z2TzjvXjj+W/0z8G7oLDZIJmV1QgghhBBCCD7cUccn2/cB0KKn89rGqtQD2mvK0LBH3TZVHIER9j0JjkSvmz59Oi6Xq91/TzzxRJfnd3Suy+Xigw8+OAKvQAghhBBi6PEEI2RpPnWfDD7eU8+mA81c/9ga9tZ5E00ZgknBUctBdeutPcKj7Rsy50j0utdee41wONzuPnMNps6sW7euw33Dhw/vlY55QgghhBAiVTAcxYUfgBbS+ay8ifP+8iEADpuFv8aDI6PVt64ngiNf/ZEebp+Q4Ej0OnMR1kM1YcKEXhqJEEIIIYTormAkRpamgqOgJZNgqNWama3L6oJuCKtME966IzTKviVldUIIIYQQQggC4SguVLDjdOWl7MvPdIDTCI7MsrqWpDlJg6SsbkgHR7FYrOuDhDgM8jMmhBBCiIEiEI6RbWSOsnPzW+2LJuYcmZkjd2XiACmrG7gcDgcWi4XKykqKiopwOBxomtbfwxKDiK7rhEIhamtrsVgsOByDcxVpIYQQQgwewUiUPGPOUUlREexM3heDLDNzZMw5Ss4cBd0QCYLNeYRG2zeGZHBksVgYO3YsBw8epLKysusThDhEGRkZjBo1Kr7IrBBCCCHE0SoQjpFllNXl5xfy8NXHs3RLNf/6uCI1cxQvq2v1PtpbBznDj+CIe9+QDI5AZY9GjRpFJBIhGo3293DEIGS1WrHZbJKVFEIIIcSAEAhH4628cWZxxpQS6j0h/vVxhcoctW7I0NJqHSSfBEcDmqZp2O127HZ7fw9FCCGEEEKIfhWMxOKtvEnLUTd2K2DMOUo3mjSY84vMNt6mQdCUQWp9hBBCCCGEEG0yRwBOm8XYF4PsMrXPfTD11uQd+E0ZJDgSQgghhBBiqFu7hItq7ycbMzjKBhKZI9WQYZjaZ841Msvq8sao20GQORrSZXVCCCGEEEII4K07OCfYnEidtMocBcPRROYo0AzBFvAYwVHpTGjcq+YcDXCSORJCCCGEEGIoiwQh2Jy6La2dzJEzO9GUoWojxCKABsXT1TavBEdCCCGEEEKIgay9BVyNsjqn3ZxzFAVNgywje3RgLQDRjELIKlXbJDgSQgghhBBCDGjtBkeqrC7NlpQ5AshW8448294FYEeoEDILjetIcCSEEEIIIYQYyFplfHQ0sKqlblIyRxAPjtIPrABga2wEZBYZ1xn4DRkkOBJCCCGEEGIoa5U50tDj983MUSSmE4nG4sGRNRoAYGtsJGQYmSNp5S2EEEIIIYQY0HwNHe4yGzKA2c67LGX/pvBwcBmZo1AL+Bv7ZIhHigRHQgghhBBCDGWdzBUyW3mDERxlD0/Zvzk6kpAtC/LHqQ371/TJEI8UCY6EEEIIIYQYyoyyuq2xUQCEJ5wd32WxaDisSfOOshOZoyo9j2Zc+ENRGDVPbSxfeYQG3TckOBJCCCGEEGIoM4Kjp6ML+FLw18Qufihld3wh2EgMsobFt28zgilfOAKj5qqN5auOwID7jgRHQgghhBBCDGVGt7oGPYutjMGR5krZ7TTmHQXCUdWZzmIDYJs+Up0eTMocHVirFpUdoCQ4EkIIIYQQYohatbuenfvKAWggG6fNgqZpKceYmaNAOAoWS7wpw/aYCo78oSgUTICMAogE4OD6I/gKepcER0IIIYQQQgxRS7dUkx1rBqBRz0rpTmdKsyeV1QFMv5AqCvkwNhMAXygCmjYo5h1JcCSEEEIIIcQQVd8SII8WQJXVJXenMzltSWV1gP7Fu5gf/gu15ALgMxeINYOjPR/07aD7kARHQgghhBBCDFE+TxN2TQU3DXQvc+QLRQlFEwvF+oJGcDRugbrd99GAnXckwZEQQgghhBBDVLSlFgCv7iSIgzRb2+Codeao0RdK2e8LRdSdkumQWQxhH1SshoC7D0feNyQ4EkIIIYQQYqgy2ng36NkAOO1tw4PWmaMmXzhlv98sq9M0GH+Guv/ZE3D/XFj+O9B1BgoJjoQQQgghhBiCdF3H4m8AVEkd0GnmKNhh5iiaeGAGRxueAvcB2PgchLy9PfQ+I8GREEIIIYQQQ5DbHyGXRKc66F7mqLFV5ig1ODo9cT+zCL7xLDhT1006mklwJIQQQgghxBBU7w3GO9XVG5kjZzfmHDW1zhwFI4kHrmKY8EVw5sBlT0Pe6L4Yep+x9fcAhBBCCCGEEEdevTdEgaaaJphzjtK6kznytsochaOpJ1z+jFoM1pHR20Puc5I5EkIIIYQQYgiq9wQp1RoBqNbzANpt5e20t9+tzmGsieQPtQqOLJYBGRiBBEdCCCGEEEIMSXWeECWtgqP2FoFNM7YFwma3OhUcDc9NB5JaeQ8CEhwJIYQQQggxBNV7QhTT/cxRMGIsFms0ZBiWmwa0asgwwElwJIQQQgghxBDU4Akkyuowg6O24YGzg8zRsBwzcyTBkRBCCCGEEGIA87Q0kqEFgaTMUTvd6tJaZY7MOUfDciU4EkIIIYQQQgwCuvsgAG4yCeAE2l/nqE3myOhWNzxPBUd+mXMkhBBCCCGEGMhs3ioA3LbC+Lb25hwlZ47C0RgtxrpGwyVzJIQQQgghhBgMnP4aAILpxfFt7ZXVJWeOmoxmDJoGJdnSkEEIIYQQQggxwEVjOq5wnXqQVRbf3l5ZXSJzFIs3Y8hOs5OVZgNUK29d1/t4xEeGBEdCCCGEEEIMMY2+ECU0AGDPGxbf7uwkcxQMR2k0Mkd5GXbSHerYmK4Cp8FAgiMhhBBCCCGGmPqkBWDtOcPj29tr5Z2cOTI71eVmOMhImp/kHySldRIcCSGEEEIIMcTUe4Lx4MiRnwiO2s0c2c05R9F4WV1ehh2b1YLDyCr5whIcCSGEEEIIIQagOm8ic5SR30XmyAiYAilldQ51rlFa5wsOjnbeEhwJIYQQQggxxDS0+CmmCYC0/OHYLJq6304rbzNz1LqsDoiX1g2WjnUSHAkhhBBCCDHE+JpqsGtRYmhoWaVMKsnCYbNQlpPW5lgzcxSJ6dS1qOAoP9MOEG/K4B0kC8Ha+nsAQgghhBBCiCMr0lwJgN+eR6bVzr+un4snGIlnhJIlt/eudgeAROYo06nCicv/sZoTx+Tz1PVzsRhZqIFIMkdCCCGEEEIMMVrLQQACxgKwOel2huemt3tscpOGymY/kJhzlJ5Uhvfx3gZqWoJ9Mt4jRYIjIYQQQgghhhibtxqAaEZJl8daLRql2arcbk+dF1Dd6gDcgdRyur313t4c5hEnwZEQQgghhBBDTHqgRt3JHtb5gYZpw7IB0HX12Cyr080Nhn31XrZVuXlrc1XvDPQIk+BICCGEEEKIIcYVrgXAltO94Gi6ERyZ8oyGDD9ZNJVTJhQwb1wBAHvrfVz/2Fqu/+dadtZ4enHER4YER0IIIYQQQgwhwUiUvGgDoNp4d8e0slbBkZE5+sLEIp64bi5nTVPleZ/saaC8wQckSvAGEgmOhBBCCCGEGEIavCFKNTM4GtGtc6YlZY7S7JY26yGNKcgAYM2+xvi2KqN5w0DSo+Do7rvv5oQTTiArK4vi4mIuuOACtm/fHt/f0NDATTfdxOTJk0lPT2fUqFF873vfo7m5OeU65eXlLFq0iIyMDIqLi7ntttuIRFIncy1btow5c+bgdDqZMGECS5YsOfRXKYQQQgghhACg3hOiWFNBjCW7rFvnjMzLIMto253XTrvv0UZwlOxgc+AwRtk/ehQcLV++nMWLF7Nq1SqWLl1KOBxm4cKFeL0qZVZZWUllZSV/+MMf2LRpE0uWLOGNN97g2muvjV8jGo2yaNEiQqEQK1as4NFHH2XJkiXccccd8WP27NnDokWLOP3001m3bh0333wz1113HW+++WYvvWwhhBBCCCGGpoYWL0WaWz3I6l5wZLFoTDVK69pbC2lEXgZaq+WNqtwDLzjS9NYtJnqgtraW4uJili9fzvz589s95tlnn+WKK67A6/Vis9l4/fXXOe+886isrKSkRNUm/u1vf+P222+ntrYWh8PB7bffzquvvsqmTZvi1/n6179OU1MTb7zxRrfG5na7ycnJobm5mezs7K5PEEIIIYQQYgh4/cOPOfftLxLBhu2OWrB0L19y50ubWbJiLyePL+DJb89ts/+U37zLgaZEKV1Hx/WH7sYGhzXnyCyXy8/P7/SY7OxsbDaVhlu5ciUzZ86MB0YAZ599Nm63m82bN8ePOeuss1Kuc/bZZ7Ny5coOnycYDOJ2u1P+CSGEEEIIIVKFGisBcNsKuh0YAcw1OtJNKHa1u791aV3VYC+rSxaLxbj55ps55ZRTmDFjRrvH1NXV8Ytf/ILrr78+vq2qqiolMALij6uqqjo9xu124/e3P7Hr7rvvJicnJ/5v5MiRh/rShBBCCCGEGLQibhUc+ZxFPTrv7OklvHzjqfz4S1Pb3T+6IBOAnHTV5rvKHWizDtLR7pCDo8WLF7Np0yaeeuqpdve73W4WLVrEtGnTuPPOOw/1abrtRz/6Ec3NzfF/FRUVff6cQgghhBBCDDSWFpWQCKYX9+g8TdOYOSKnTac60+yRuQBcOFu1B/eForgDkXaPPVrZDuWkG2+8kVdeeYX333+fESPatv9raWnhnHPOISsrixdeeAG73R7fV1payscff5xyfHV1dXyfeWtuSz4mOzub9PT0dsfkdDpxOp2H8nKEEEIIIYQYMmxeFRzFXKW9et2vHjeCUQUZHDsylxfXHaDJF6aqORDPJA0EPcoc6brOjTfeyAsvvMC7777L2LFj2xzjdrtZuHAhDoeDl156ibS0tJT98+bNY+PGjdTU1MS3LV26lOzsbKZNmxY/5p133kk5b+nSpcybN68nwxVCCCGEEEK0YvOqJER31zjqLotFY+64AtLsVkqzVQww0DrW9Sg4Wrx4MY8//jhPPvkkWVlZVFVVUVVVFZ8HZAZGXq+Xhx56CLfbHT8mGo0CsHDhQqZNm8aVV17J+vXrefPNN/npT3/K4sWL45mfG264gd27d/ODH/yAbdu2cf/99/PMM89wyy239PLLF0IIIYQQYugIhKNkRNQCsHnFvRscJSvNMYKjAbYQbI/K6h544AEAFixYkLL9kUce4eqrr+bTTz9l9erVAEyYMCHlmD179jBmzBisViuvvPIK3/nOd5g3bx6ZmZl885vf5K677oofO3bsWF599VVuueUW/u///o8RI0bw4IMPcvbZZx/KaxRCCCGEEEIAe+q85OIBIDO3Zw0ZesLMHA20hWB7FBx11W1iwYIF3epIMXr0aF577bUur/XZZ5/1ZHhCCCGEEEKITuyu9TKTFgC0jII+e55E5mhgBUeHtc6REEIIIYQQYuDYXeshV/OqB+l5ffY8ZTlDYM6REEIIIYQQYuDaW9tMtuZTDzLy++x5SrIHZubokFp5CyGEEEIIIQaempqk5XLScvvseWYOz+GBb8xhRF5Gnz1HX5DgSAghhBBCiCFA13Wa66tBg6gjG6u170KBApeTc2eW9dn1+4qU1QkhhBBCCDEE1HqC2ENNAFj6sKRuIJPgSAghhBBCiCFgb52PXE218dYkOGqXBEdCCCGEEEIMAY2+EHlGcNSXneoGMgmOhBBCCCGEGAI8gUh8Adi+7FQ3kElwJIQQQgghxBDgCUbiZXWkS3DUHgmOhBBCCCGEGAI8wQh5SFldZyQ4EkIIIYQQYghoCUTI1VrUAymra5cER0IIIYQQQgwBnmCYXLzqgZTVtUuCIyGEEEIIIYYATyCS6FaXIWV17ZHgSAghhBBCiCFANWQwyupkzlG7JDgSQgghhBBiCPAEI1JW1wUJjoQQQgghhBjoKj+DlfdDLNbhIcGAjwwtqB5IQ4Z22fp7AEIIIYQQQojDoOvwzDehaR9kFsExl7R7mNXfqA7XrGjO7CM5wgFDMkdCCCGEEEIMZBWrVWAEsOXFDg+zhpoAiDpzQdP6fFgDkQRHQgghhBBCDGQbnknc3/kOhLztHuYwgiNd5ht1SIIjIYQQQgghBqpoGDa/oO5bnRDxw46lbQ4LRWKUxarUg5zhR3CAA4sER0IIIYQQQgxUu94DfwNkFsOJ31bbtr7U5jBvMMJE7QAA1uIpR3KEA4oER0IIIQ5LRYMPfyja38MQQoijzv5GH69sqETXdaj4GB79MtTt6N0n2faKup32ZZj2FXV/5zuqSUMST1JwZJHgqEMSHAkhhDhke+u8nPb793jw7/fAkvOgfld/D0kIIY4aZ9/7Pjc++RnPrt0Pqx6APcth1f299wSxGHz+pro/+VwYNhtsaRBoavP7uCUQYYJFBUcUTe69MQwyEhwJIYQ4ZJ+WN3Ka9hnfqb8b9n4Aq//W30MSQoijhtfIqr++8SDU71Qb963svSc4+Bl4qsDhgjFfAKsdymapffs/STnU52lmhFanHhRJ5qgjEhwJIYQ4ZDX7d3Kf/c/YMBYd3PpKpwsQCiHEUNTgDSUyObVbwVuv7ldtgs+eaFMC123b31C3488Am1PdH3GCuj2wJuVQ3Sjna9JyZQHYTkhwJIQQ4pCV7n2ZDC3Iutg4YvZMaKlUq7QLIYSI0zxVEE5qr12+EnwN8LdT4D/fhQNrD+3Cn7+ubiefm9g2/Dh12ypzZK3fDkClfdShPdcQIcGREEKIQza96V0AnoqeQfOIM9TGdrokCSHEUJbj25e6oXwlvPvLxONDadIQ8qnME8D4MxPbzcxR9WZ1jJHNdzaq56hJG9Pz5xpCJDgSQghxSKJ1u5kY201Et/Bm9HgqSlRw5N/w4qGXiAghxCA0LGo0QrDY1e3GZ2HtI4kDvDU9v2j9TkCH9HzIKklszxkBrhKIReD34+GBeRD2k+lWZX0NGWMO6TUMFRIcCSGE6JFoTOfdbdXUffw0ACtj02gkmw+Zg1d3kt6yl+i21/p5lEIIcfQYqxmLr5rlb55q0JPmZ7ZU9fyidZ+r28JJqds1LZE9Cvugdht8/A+KmjcA4HaN7/lzDSG2/h6AEEKIgeXNzVV894lPec7xPCUWeD12EgDv7vFB9Gy+a3sJ7b1fqzcBFvkMTggxdFktGtGYzljtoNow7jTIH6cClmkXgK8O3vopuCtVxt1bB66i7l3cLMUrnNh23+k/UU0XYlFY9wQsvYNMdMpjRdTnz+mV1zZYyV8tIYQQPbJqt+qyVEIjAFtiowHYsL+Zv0fOw62nY6nZBNte7rcxCiHE0SArTeUhxpnBUcEE+OLP4fKn4djLIGek2t5SpeYg/WGCWsC1O+pUg4V21ywqmQZf/gt86feq7A5V6vzLyBWkZ2Qcxisa/CQ4EkII0SO56apm3qX5AbBl5AAQisZoxsVTUaMxw863+2V8QghxtIjGdKxEGaUZc4oKJqQekFWmblsq1QKxAJWfdu/i8czRpI6PcWTCSTcAsDX9ON6KHU+WUwrHOiNfHSGEED2iFjXUcaGCo8mjylizNRLfX6Ub62eE/f0wOiGEOHpEojrDtTrsWpSoxYk1a1jqAdlmcFQF/mZ131Pb9YVj0cSisu2V1SX7wv9A4UTuXZkLjX5cafL2vzOSORJCCNEjvlCENELYNbXy+xnHpn4SGsCh7khwJIQY4qIxnVw8AAQceW3nYbpKjQNDEDSCo+50rmuugEgArA7IHd35sVYbzLiImpBaJNbltPfkJQw5EhwJIYToEW8wSpaRNdLRmDa6LGV/QDf+8EpwJIQY4sKxGA7CAIRoJyixOSCjMHWbt67rC9caneoKJoDF2q2xeIMqw++SsrpOSXAkhBCiR3yhSHy+kebMpjArDU1L7PejPp0kEuiH0QkhxNEhGtPRdXBoKigJ6h0EJVmpHzDh6UbmKKmN9zOfVHDir97m4Q/3dHpKrScIQH6mo+vrD2ESHAkhhOgRbzAan2+EMwu71UJ+RuKPbaKsztcPoxNCiKNDJKbWMTIzR/4Og6PS1Mfebsw5aioHYEVjNj/49wZqWoI8s6aiw8M9wQhNPjWO4XnpXV9/CJPgSAghRI/4QhGyNCPwScsGoCjLGd+fCI4kcySEGLoiUdU+24nKHPmiHQRH2a0yR/4GiIY7v3hAzU9aVpFohrOjxkMgHG338AON6gOt3Ay7lNV1QYIjIYQQPeINJeYc4cwCoDg7Lb4/aM45isicIyHE0JUIjlSg44lY0HW97YGty+qg63lHRnDUrGcyKj+DQpeDaExny0F3u4fvb1QfaI2QrFGXJDgSQgjRI75gJKWsDmDuuHwsxryj+JwjyRwJIYawsFlWpxlldTEbVe52fi8ml9XZjQVa2yutW/cvePAsaD4QD45a9HSOG53HzOFqvblNB5rbHct+I3M0PFeCo65IcCSEEKJHvKFovCGDGRx9d8EENt55NsePzpNW3kIIgWrIAJBmNGQIYWNHtaftgebaR5lFkD9O3W+vnffK+2D/J7DrXQiqDJGbTOaMyo0HRxv2tx8cHWhSv49H5GUc6ssZMiQ4EkII0SO+UHLmKDu+PdNpw261ENCN4EjK6oQQQ1g4qjJHZnAUxM7n1S1tDxw1F0pmwvHXQqbR1rv1QrCRINRuVff9DeiBJgDcegZzRucxc0QuABs7CI7MsjrJHHVNZmQJIYTotlAkRjiqk2UzGjIYmSOTw2YhYK7lEQ2pVdy7uQaHEEIMJuaco3SLapIQwt5+5ig9F77zobr/72+r29ZldTVbIKaCrK279zHO04gTCNuzmFySRaFLlTPvqGnBH4qS7kj9vWs2ZJA5R12TzJEQQohu84XUH+esdjJHAHarJTHnCGStIyHEkBUxy+osas5RULexo6adzBEQM47FVaxuW5fVHdwQv7th+y6cUS8Ao4aVYbNaKMlOoyjLSUyHLQfbZo/ic44kOOqSBEdCCCG6zRtSn4BmW1LnHJkcNo1g8irwMu9ICDFEmescpWHOOVKZo9Yd6+o8QU789dv874ubEmV1rbvVHVwfvztSSwROJ0wZE78/qcQFwL761DXm/KEo9d4QIHOOukOCIyGEEN3mC6o/8jkWIyOUlpo5clgt6FiIWKQpgxBiaIu38jbmHEU0Oy3BSLxjnd/4sGlzpZs6T4gPdtRCppE58rTKHFUlMkejLGpf1JbONfMnx7eb84nMEjrTgSYVLGU5beSk2xGdk+BICCFEt5mZoxyt/cyR3ar+rEQsRmmdlNUJIYYosyGDGRylpauszY5qD+9tr2HmnW/yt+W78ASMRWJD0fbL6mJRqNoUfziMegCs6blYzTUUgGFGcFTZnBocSUldz0hwJIQQotvMzFHrVt4mh80MjoxFYSVzJIQYolq38s52qbK3z8qbuOaRT4jEdH7z+ja8xu9Vfyjaflld3Y6U7p8WzSjLazXn0wyO9je2HxxJM4bukeBICCFEt5mZo/ZaeUMicxTWzIVgJTgSQgxN4XhZnZrvM6YkD4C/Ld8VP2ZcUSYtRnDkC0fRM4vUDm+tyhgBVBtZo6yy1CdIy0l5OMLMHDX5eWdrNWff+z7bqtzx9uFjCzN754UNchIcCSGE6DazW10G7bfydhqZo7BF1joSQgxtZkMGh9GQYcaoIqaVZeMPR+PHpNms8cxRNKYTSi8GW5pq2924Vx1Us0Xdjjk19QlaBUfxsrqmAEtW7GV7dQtPfVzBlkq1YOz0YanHi/ZJcCSEEKLbvMEooJMRU21kO8ocheKZI5lzJIQYmsxW3k4jOLLY0/jpeVNTjvEEI3iM4AjAHwGKjCYLZlBUYyz+OuIEYlrSEqWtgqOyXFXO7A9HWbO3EYA1+xrYetAMjlJ/X4v2SXAkhBCi27zBCGmEsKI+Ee1ozlE8OJLMkRBiiDK71Tk0tc4RVicnjy/kZ+dP46LZw4G2wZEvFIXi6epBtRkcGbfFUwnakwKiVsGR02alKEv97jWzU5sOuPGGojhtFimr6yYJjoQQQnSbNxRJLACLBo7UP7Zm5iiIzDkSQgxtkahZVmcERzb1e/GaU8by/bNVdsgTiMS71YEZHBnZpZotEPImyuuKpxHoJDiCRDvv1qaUZmGzytv+7pCvkhBCiG7zhaJJneqyQdNS9icyR7LOkRBiaAsbZXUO3cwcOeL7XGmqPC4UjdHoC8W3+0NRKJmmHtRsgdrt6n5mEWQW4rMeWnA0TUrquk2CIyGEEN3mDUbIMpsxpLX9Y+uwqmApiNmQQeYcCSGGpqjRkMHeKnME4HIk5g4dbE78nvSFIlBsBEf1u6DyM3XfyCb5bEm/d9sJjoYZ844AhuUk7k+TZgzdJsGREEKIbkvNHGW12W9mjgJI5kgIMbSZrbxbl9UBWCwaLqcKkKqSg6NwVLXsTssFPQpb/qN2GAGT15L0e7edD6iSM0eXnzQqfn9amWSOukuCIyGEEN2mMkcdB0fmnCMJjoQQQ53ZkCGeObI6U/abwVFKt7pQVJUrm9mjPcvVrZE58li6yhwlgqNLTxhJboad7DQbU8va/r4W7bN1fYgQQgih+EJRSjoJjszMkV+XsjohxNBmltXZzDlHNkfK/qw0G1Xu1HN8xkLblEyD8hWJHUaw5NaSM0e5bZ5zalk2Fk2taVSclcbz3zkZHchwyFv+7pKvlBBCiG7zhiJkae0vAAuJzJFft6sNkjkSQgxRZlmdXe8gc5TW9m2431hom5mXwLZXIS0X34hT+O93dM479gC+lOCobeZoZH4Gr//3fApdKhAbV+TqhVcytEhwJIQQott8wWhSQ4a2f5jjmSMpqxNCDHERsyGD3nbOESTK6pLFM0ej5sL/bAPgsvs+Yn1FHUu31fHD0UnBTju/gwEml0oJ3eGQOUdCCCG6zRuKkB3PHLXXrU79WfHFzLI6CY6EEEOTmTmy6Uar7lbBUXaavc058eDIUO8Jsr6iKf64kaTgqJ3fweLwSXAkhBCi23yhaOetvI3MkS9eVidzjoQQQ1M0pgM61o7K6trJHPnDqcHRkhV74/fLctKoj6ngKGpxgD0N0fukrE4IIUS3eYNJc47amQxsj2eOjOBIMkdCiCEqEo1hI4oFlUFq3ZChvTlHvlAk5fHznx6I3/cEI+xhOO9FZzF20nGM6fURC+hh5ujuu+/mhBNOICsri+LiYi644AK2b9+eckwgEGDx4sUUFBTgcrm4+OKLqa6uTjmmvLycRYsWkZGRQXFxMbfddhuRSOoPw7Jly5gzZw5Op5MJEyawZMmSQ3uFQgghekUkGiMYiZFN12V1npjMORKdePvn8PoPQdf7eyRC9JlwTMdptvGGNpmjrHaDo0TmKBbTqXInsu/eYARfROOa8O2UH//j3h+wAHoYHC1fvpzFixezatUqli5dSjgcZuHChXi93vgxt9xyCy+//DLPPvssy5cvp7Kykosuuii+PxqNsmjRIkKhECtWrODRRx9lyZIl3HHHHfFj9uzZw6JFizj99NNZt24dN998M9dddx1vvvlmL7xkIYQQh8JnlHskMkftldVpAHiixh99CY5Ektc3HmT+r16HD/8Iqx+A+l39PSQh+kw0picWgIVuNWTwJwVHzf6wUZqnxHRw+9X10uzWXh6tMPWorO6NN95IebxkyRKKi4tZu3Yt8+fPp7m5mYceeognn3ySM844A4BHHnmEqVOnsmrVKubOnctbb73Fli1bePvttykpKeHYY4/lF7/4Bbfffjt33nknDoeDv/3tb4wdO5Z77rkHgKlTp/Lhhx9y7733cvbZZ/fSSxdCCNETvqD6o52tGQFPe93qrOoPtjdmVx+/yTpHIsm722rwtjSCOVWi8lMonNCvYxKir4SjMRwYlVEWG1hSA5quMkf13qA6zmmjxVgots6jtjlt0jagrxzWV7a5uRmA/Px8ANauXUs4HOass86KHzNlyhRGjRrFypUrAVi5ciUzZ86kpKQkfszZZ5+N2+1m8+bN8WOSr2EeY16jPcFgELfbnfJPCCFE7/EatfCddauzt8kcSXAkEgKRGJla0s/EgU/7bzBC9LFIVMehtd+MASCrnW51yZmjOo/qcleU5STDoQKrYES1B5fMUd855OAoFotx8803c8oppzBjxgwAqqqqcDgc5ObmphxbUlJCVVVV/JjkwMjcb+7r7Bi3243f336Jxt13301OTk7838iRIw/1pQkhhGiHmTnqtFtdmzlHviMyNjEwBMNRskj6O35gbf8NRog+FoklZY5aNWOA1LK6LOO+L5yYg9/gVcFRgctBZqsSvDS7ZI76yiF/ZRcvXsymTZt46qmnenM8h+xHP/oRzc3N8X8VFRX9PSQhhBhUvKEIDsKJCcbtZo7Un5WAuQhsH5bV3bv0cx75aE+fXV/0vmAkhis5OKraANFwxycIMYBFojppdJw5Su5WV5Sl9qeU1RkldAWZzjbzk5w2yRz1lUMKjm688UZeeeUV3nvvPUaMGBHfXlpaSigUoqmpKeX46upqSktL48e07l5nPu7qmOzsbNLT09sdk9PpJDs7O+WfEEKI3uMLRRJZI7ROu9UF9L7tVlfnCfJ/7+zgV69uJRaTjmcDRTASJVNL+pmIBKBmS/8NSIg+FEluyGBrGxxltxMctVdWl+9yxMvqTJI56js9+srqus6NN97ICy+8wLvvvsvYsWNT9h933HHY7Xbeeeed+Lbt27dTXl7OvHnzAJg3bx4bN26kpqYmfszSpUvJzs5m2rRp8WOSr2EeY15DCCHEkecNRpPmG2WBpe2fkHhwhFFLr0f7JDPgNSYnR2J6m0UTxRGw4i/w72/3OPhtkzkCmXckBq2UhgztBEcuZ2LOUbuZI6MhQ2Fm27I6yRz1nR4FR4sXL+bxxx/nySefJCsri6qqKqqqquLzgHJycrj22mu59dZbee+991i7di3XXHMN8+bNY+7cuQAsXLiQadOmceWVV7J+/XrefPNNfvrTn7J48WKcTvWDccMNN7B7925+8IMfsG3bNu6//36eeeYZbrnlll5++UIIIborJXPUTtYIwGLRsFk0AiS9EeiDeUfJAZEvKGVZR1Ttdnjrf2HjM7Dp+R6dGgzHcGmtSi1l3pEYpKKxzhsyJJfVFWepFo7+lLI6c85Re2V1kjnqKz36yj7wwAM0NzezYMECysrK4v+efvrp+DH33nsv5513HhdffDHz58+ntLSU559P/PK0Wq288sorWK1W5s2bxxVXXMFVV13FXXfdFT9m7NixvPrqqyxdupRZs2Zxzz338OCDD0obbyGE6EeeYDRpjaO2bbxNdquFEDZ0VOe6vuhYFwirjk1fsGyg4K8TYdO/e/05RAeW/xYwShnXPdGjU4ORKC5a/QxVftZ7YxPiKBKOJpfVtW3IkOmwohm/Js3MUSgaIxJVv98SwVFq5shhtWCxaH048qGtR+sc6d1YyTotLY377ruP++67r8NjRo8ezWuvvdbpdRYsWMBnn8kvTCGEOFr4gpFEp7F2OtWZHDYL/rCGbktDi/gh0vvzjgJG5ugUy2YsoRbYsRRmXNzrzyNaqdmalC3SYN9H0LAb8sd16/RgJIbLmHMUG/0FLNtfUXOOQl5wZPbRoIXoH5FYjIxOGjJomobLaaMlEIkHR6AW3M62WqjzJjdkSJTROWW+UZ+Sr64QQohu8YaiZGte9aCDsjpQmSOAmNVY6bNPMkfGgrQY4/HUdHK06DXrnwJ0mHIejD9dbVv3ZLdPV3OO1M9DIHc8ZJWBHoODG/pgsEL0r0hU73TOESRaeBdkOjCTQWZpndnKu9DlIMORyGfIfKO+JcGREEKIbkmZc9RJ5sishY86XGpDoLnXxxIPjswyPwmOjoyK1ep28rkw63J1f/sb3T49EI7GGzIEtHQYfpzaIfOOxCAUicUSc446CI7GFqmM6aiCjHgA5AtFCUdjNPnUuQUuZ0pZnXSq61s9KqsTQggxdHmDUUaZbZg7nXOkPv4MpxXibKkAb+8HLuaco0TmqLqTo0WviAQTneVGJXWPrfscYlGwdP1pdnJZnU/LIH/YbNj2ClRKxzox+KRkjqxt5xwB3Hf5HCqbAowvcpHusOIJRvCFIjQaWSOLBrnp9pSyujS7ZI76kgRHQgghusUXiiSCkU7K6hxG5ijoLMAFfZLVMTNHWWaw5qvr9ht0cYgq10E0CBmFao6RHlPzKKJBaNrX5bwjXdcJRWK47Op75iEdhh+jdkrmSAxC4ZieWDS7g8xRboaD3AwVOJlrGflD0cQaR5lOLBYtJXMkner6lnx1hRBCdIs3FE0EI52U1ZlzjgJphcaJtb0+Fn/rOUd6DHz1vf48IknFKnU7ai5omgpECyeqbbWfd3l6MKKyfWbmqEVPg2Gz1c7GveCV758YXKKxWJfBUbJ0IyPkC0UTaxy5VODkSimrkw+B+pIER0IIIbpFdavrupW3mTkKOArUhj4oeYuX1WlJayjJvKO+VW7MNxo1N7GtcJK6rdve5enx4MiYc9QcS4P0XCiaqg549RaV/RNikIhEO1/nqDUzc+QLReNtvPMzzaySZI6OFPnqCiGE6BZvKEp2F4vAQiJz5LPnqw19WFYXHw/IvKO+FA4kMkcjk4KjosnqtluZI/U9yzQWgW2KpKsd5/4WLHbY8h94566OThdiwAlHY112q0tmBkD76r0s3ap+nxW41HmZMufoiJHgSAghRLf4QpFuLQLrMIMjM3PUB2V1gUgUJyGc5qeyIJmjvhKNwHPXqLLFjAIom5XYFw+OtnV5maCR7TPXymqMGhPUx50GX/6Luv/pY9CNNRWFGAgisaRFYDtoyJAs3cgc3f36Nl7dcBCA6cPUB1EumXN0xMhXVwghRLd4g9FEWV03GjJ4bGbmqA/K6kLRxIK08QFKcNQnVvwfbH8NbGlw6WNgS3qTV2gER3WfdxnUqLI6nUzj+1YXTrrOjItV2ZG/QS0qK8Qg0J11jpKdPL4ATQObRWP2qFwe+MYcrv+CanSSKXOOjhjpVieEEKJbups5Mlt5t8SDoz7IHIVjiQVpTZI56htm++4FP2KTfSbf+8MyfnjuFBZOL4WC8aBZIOiGlirILuvwMoFwlHSCWDUVRNWGkoIjmwPKjoH9n8D+Neq6QgxwkR42ZLjmlLF8/YRROG0WLOaKsAaXrHN0xMhXVwghRJdiMR1/KJyY49NJtzqHsXp7s9UIjsJeCHp6dTyBSDR1vhFIcNRXzEV8c0fyxOp97K7z8ujKvWqbzZlo4d1FU4ZgJBZvxhDVNeqCrT6fHXGCut3/SS8NXIj+1dOGDKBK61oHRpBo1gDgtEnmqC9JcCSEEKJL/nCUcdpBbFoM3Z4BmcUdHmtmjvxaGtgz1MZeLnnzh6KJLJZJGjL0DX+Tuk3L4ZO9jQCsK28iElVziCiYoG4b9nR6mWAkistoxuAlHXcgknrAiOPV7YE1vTFqIfpdypyjbmSOOpOZ3K1OMkd9Sr66QgghuuQNRZipGW9+S48Ba8dV2eZk4VAkBplFamMvl9YFIrF45ihq/imTzFHfMDJHzbjYWaMygN5QlO3VLWq/ywiUvXWdXiY5c9RCOm5/OPUAM3NUtRHCreaTCTEARZK71XWjIUNnLBYtnj2SzFHfkuBICCFEl3zBKMdY1ER5zVy4swNmK+999T488Y51vRu4BMLR+JyjGov55lyCoz5hBEcb6lIbLqzdp7JI8SxiF1//YDgWXwDWq6fhDrQKjnJGgqsEYhE4uP7wxy1Ef9n+Oqz+O5FYtEdzjrpiNmWQOUd9S766QgghOuc+iN/TEA+O6CI4Mlt5//vT/Xx00Mzq9G7JWzCcmHO0TxumNvrqIRru5CzRY7EoBFVwtKZKrVNkM+ZDJIIjMzvYRXAUicYzRx7Scfsj6Mkd7jQNRp6k7r/+A/A19NKLEOIICvng2Wvg9R/wHf5NvmZkWHshODKbMkjmqG9JcCSEEKJjnlr4yxzGPXcO07W9altXmaOkNTjq9JzEdXqRP5yYc7RPLwHNeLPQB2sqDXp7P4JHvgRVm9ruC7rjdz/cr8qDLpg9HEgKjlxGcNTF1z65rM6jpxOKxvCGoqkHnfG/kFGoMkdPXS5rHomBp3wFRNTP+c22fzPDsldtL5x02Jc2y+okc9S35KsrhBCiY7VbIezD6dlPuhbCR3piAn4HmpPmktRiBke9mzkKhBNzjhqiGd3OXohWomH4z2LY9xGs/lvb/UZJnW7PYH2l+np/+wvjsGiwv9FPtTuQVFbXjeDIKKuL2l0APLFqX+pBRZPgmy+DxQblK6G54jBenBD9YOe7AOiOLAA8ehq+8x6AkumHfelMyRwdERIcCSGE6FhLalCz2zERLJ3/6Zg/sSh+P545OpSMTtWmDueeJM85qo+moZtNASQ46plPH4NGo9HGvo9SdsViOo++uw6AgNVFJKYzviiTyaVZjC9Swc2Wg+7ul9WFo7hQ3erGDC8B4L73dtLkC6UeWDINSmao+/ulc50YYHap4Ch07j18J/TfnBP6LRxzaa9c+ivHDmNCsYuTxub3yvVE+yQ4EkII0TFPVcrD8rQpXZ5yzoxSPvnJWcyfVERtvKyum0HL3o9US+i6nfC3U+Dhc9tdI8mfNOeoWc8k1s2mAMKw/im47yR48yeJbQ27wX0w/nBteSNvrP0cgNpIOgCLZqpFXieVqE/Fd1Z7Et3qAk0QaRXoJFGZI/U9G11WwpTSLNyBCPcv29X2YLOttwRHYiBpPqCy7ZqF4JjTeT12Evv1ImxdfKDUXd84aTRv33oaI/MzeuV6on0SHAkhhOhYiwqOKopOY0lkIR8Udu8T0KIsJxl2K/W6sVisr/M2zwDU74IlX4I/HwvPX6e2hb1Qv6PNocFwLD7nqEXPIJxWqHbIWkfd896voXabmhtRMBGKjZKfpOxRSyBMNio7Vx1Sk8nPNYKjCcUqc7SjpgXSclUZHHSaIUxuomFJy+b2c1SgvWTFXg40tWrdPVzWPBID0O731O2wOUQcufHNtnYWdRVHLwmOhBBCdMwINsqzjuXOyNVEMzpe/LW1DKeVBozgyFvf9QnVmxP3Kz9L3K9PzSxEYzqhaGLOkZsMQvHgSDJHXWrcC037VEBz9avw7Xdg3Glq374V8cM8wSg5RumiW89kXGEmU0pVxmhiiRkceVSZZWbXTRlC4RBnWI3va8FEFkwuYu64fEKRGPe8tT31YHPNo8p16tP4zS/Clpekg504uh1Yq27HnBpfJNmiqTWKxMAhwZEQQoiOGZmjRotaryjD0fHir61lOmyJzFGwudOSKwCaytvfXr8z5WEgrDqcZRuZI7eegd8pwVG37V6ubocfD2NOhbQcGH2y2rb3g/j3yROIJEoXyeRLM8vQNPUmb2KxUVZX41HtuDONr397wVEsBpEQ4+qWMVyrx2fLg2lfQdM0fnTuVABe+OxAfIFZAArGq4xUNAh/ng3PfhOeuRKev753vxZC9Cbzd1XRFCIx1WnRZpW32gONfMeEEGKo2/qKmuvTHiM4qtPyAMh0dr9LUobTipsMYhjndFVa12R0Lpt3I1y/DM66Uz1uFRyFGir4uvVdyjSVRWghA5/DmKAswVHX9hjBkZktAhhlBEd1n8Pvx8PG5/AGI/GmF2OHl3HDgvHxw8cUZmC1aLQEItS0BBMd69r7+r9+G/yqhEXlvwdgU9nFYE8DYNbIXM6cUoyuwwuf7U+co2mJeUfRIOSMUvd3vwcBN0IcleqNteAKJhCJquDILlmjAUeCIyGEGMo8NeoT+ScvbT+zY5TV7Q2qTEFBZvcXMsyw29Cx4LWZHeu6Co6MzFHBeLWWUsFE9bgudc6R8907+I39wfhjt56Bx1aQMl7RAV2HPe+r+2OTgqPMAjj9J2qNoaAb1i6hJZjIHM2eNCa+ACWoVsKjC9Sk8B3JTRlaZ46iEVj/NOgxMqPNhHQr20ddknLIhXPUukn/WVeZuijs6FPUbfF0uOF9yB8PsUgiuBPiaBLygdsI8AvGE46psjqrBEcDjgRHQggxlDXsAT0GIQ/UbE7dF/LFFwFd36Q+6R9XlNntS5tZpharERx1lTlqNDJHuUaWwFxPqX5XymKgzv2pWa4WMmixqcyWdKvrQs0WFcDYMxLzekyn/QC+/qS637AbbzASn3NEWm6bS00oSmrK0FFZ3cH1EGoBZw4fZi/iJ5FriWWWphxy5pQSMh1W9jf6EwvLApx0A1z0IFzzKqTnwcQvqu07lh7KKxeibzUYWaP0PMjIT2SOpKxuwJHvmBBCDGXupFKmA5+m7NpXrv7Y6/YMNjeoP/TjCl3dvrQ5P8mtmZmjTpoy6Hoic5Q7Rt3mjwXNot5cm+VaIR8Wvyqn26qN5+2MLxHBRpPFCI4CzRAOdHuMvckTjPDW5iqCkWi/PH+3mIHF6JPB5mi7v8AonXMfIOjzxDNHpOW0OTSlKUNHZXV7P1C3Y05hScEtPBtdgNOW+tYj3WHl7BkqYPrPusrEDkcGHHOJerMJMCEpOFr998TcKSGOBmb5r/GhTsTIHNmskjkaaCQ4EkKIIWr17npefv+TxIZWwdFjb60CwG0rIBTRsVs1hueld/v6GQ6VOWrSum7nvWXnHtW2G6iI5fPr17bSHLIkskjmG4+67Wjo1OnZ/Ff6PTxVciug1jrCarzZP5QFZ3vBr17dwvX/XMvm+6+Ae2fCYxfAir+2WUi3X33+hrqddE77+zMKwKkCoTRvRXzOUbvBUVJThkRZXUfB0RcIRtSbRae97VuPC45VpXWvbzpILKa32a+ucQrY0qClEl7/ATx9JcQ6CUQ3PgdLzoPa7R0fI0RvaR0cGZmj3lrjSBw58h0TQogh6v5lu6ir3J3YYLahNcSaVTOG8pB6Ezy6ILNH9fNmcBTvWNfJnKMlr6ksgD+tmF+9uYf/9/5u/rlqb1JpnZp3FK3aAsCO2AjS7dZ4dsobinbeFOAI+NfHFaQTYE7Da9BcrpoHvPUTtW5T416e/qSc43+5lN2r/tM/WQ9vHVSsVvc7Co40DQrGAZDt3UeOsc4R6bltDi3JVqWW9Z5goqxu9zL4f6fD/fPgX5dDuQqwGXNqvMtgmq1tU4+54wrIctqo84RYt7+p/bHZ02HKeYnHwWbVQKI9H/0Z/n2tCs7e/0P7xwjRm8wlB4zsq2SOBi4JjoQQYog60OSPd3wD1KKgwZb4w7SgysDsM4KjcYXdn28EkGlM4O/OQrBWtyqpq7KUsHK3Kr/bXedNCo52UtUc4LGXVOZjuz6CNLslHoD5Q9FE9qKfmjIMz00nH/X1060OOPd3kD0Cwj7Y+Q6vbawi7Glg3BtXwWNfVvNxjqQdb6n5ZaUzIXdkx8flqzd3eYGKeLv09jJHuRl2AJr94URgClD5qZrbtP1VNZctLRdKZnSaOXLYLJw2Wa2V9M7WTr5/5/8f/Nf7MGqe8VyftT1m/1pY+r+Jx1tfUuWWQvSlDjNHEhwNNBIcCSHEEKTrOgeb/JRpyfOA9Pgb9nA0RnZE7avR1ZyPsT1oxgCJzFFtzJin1EHmKBKNkRtUc002eHLUm22gosEXf6NOwx4+2dvAmKhq2vC5PhJn68yRq8R4nv7JHA3LTSNPU8FR0JHHjw7Mo2r8xWpnxcfUtgQZpx1MnPDyzZ2XhfW27a+r20nnxjf9Z90B1uxttbCq8cl3YWh/p3OOctITwZGeP1Yd48yGhb+EK55PZKcmnwsWC8GwERy1kzkC+OI09f17e0sn3z+nC8pmwbA56rEZHIW88PbP4eAGWG80lZh+ERRNgUgANj3f8TWF6A1GcLQzVko0psfXOZKGDANP91fzE0IIMWi0BCN4Q1GGOY3gKHe0WmfowFoYcyqNvhDFmuocVqPnAj3PHJmBS3XUCI587TdkqPeGGI6RpYoVxreXN/gSc46aytnf6OfLFtVAYntsBC67Nd4Rzx0Ig0tlHvqrrM4XilJgBEd7fWn86+MKikaXcitAxWpqPZdwipaUFan8FD57HI775pEZ4L4V6nbiQkDNFfrvp9ZRmp3Gqh+fmTjOCEhHRPaRoQXVtna61ZmZo3BUx0c6md9bp+Z9OY3v9/gz1HyfvDEA8UYVrRsymBZMKsZq0dhe3UJ5vY9RRqvwdg2brW4r16nbVffDh3+Ejc+qQAlgzpVQvRne+il88hAMn6PK7Zr2qeAtLbvj6wvRE74GMBrFnP9EJYsX7mTGcPWBgrTyHngknBVCiCHoYFMAB2GKNKPcaKax9szWVwBo8IYooVVwVNT9TnWQyBxVhY2gqoPMUbU7wEhNBUcVenHS9iBBl5qoT1M5tXW1DDcyXTuMsrqReeoNdHm9L5E56qfgyBOMkGeU1dUZ2bK33SMBDRr3oHlqGGOpSj1py4tHZnC6DoEmdT9HfU03HVDf+yp3ID4fCIhnjqbE1CfhOprKCLWSbrdiN+ZTNPvDkJGfCIxAzV8qnhJf8DVeVtdB5ignw84JY1SW8vnkBWHbM+xYdVu1AaJh2PCMetxcod6kukrUOk7HfE01cajeCH+fD5ueg/2fwK53O7++ED1Ruw2A/XohftQHI6GIOedI3moPNPIdE0KIIaiy2U+JMd8ooNsJH3ctaFbY/zHU7aDB7WemZQ8Au/RhAIw9xDlHByNqzlJHc47q6hs43qI6in0eG5Gyb79uZJICTaRXq4YRB/V83GSSZrcyvliNaVdtcjvp/plz5A1GyDcyR42o17y1yUKsaAoAx2qfM0pTgdty5wJ1Uvlq9ea+r0UCagFV4J7llazd18j26sT8stqWYOLYfNWQwY4KmHRnFrTTcUvTNHLSVYfAJl/Xr6GzOUemy05UmcJHPtpLSyBMIBxlxa461lU0pR6YPx4cWep1bXhaNWbQkq478xKwWNU8tCuehxEnqu02FahR8XGX4xWiu4IHNgKwPabm8h1o8rNil/ogxy6ZowFHgiMhhBiCqpoDDEMFRwf1fKr1XJhwltq5/l+ED24kR/Ph0dPZpI8lN8NOQWY76+J0wswcNehGcORvhGikzXHOna+SqQWpoJT1+niKs5xMKVXn7PNY4uvcjG9Si7+aAVS63cp4I5t1sDmAP90Ijhr39micvaUlEInPOXJrOaTbreg6NBeq+TFzLDsYa1GB2zMtx9CMS7UvP7ihT8e1Ylcd5/7u1fjjv350kJ++uIntVYngqModYNXuetUMISMf3VxbCNotqTOZpXVN/lCX4wiGOy+rAzjvmGGML8qk2R/migdXc+xdb3H5P1Zz8QMrqGjw4QlG2LC/CV3TEtmjd+5St9O+AtMvVAvczkkqVRxzClz7FtyyRTV0gETXvq5sfRn+NBMeWggVn3R9vBiSPOXq//A+2xguOU79fnr+U5X9lLK6gUeCIyGEGIKSmzEc1AuobArAsZerneufIvOACkT2ZB7DjxbN4J5LZqFpPfsj77RZsGgqi6JjnOtvaHPcyPIXAdheeh5/vmwO/7jqeMYUqIxQeX1i3tEJIfXmdLuuPp1Ns1vJzXBQ6FJB216nytBQvRmCnh6N9XCFozGCkVi8W92iudOZWqYCvL3pMwA4wbKdcUZw1JQxio+jk9XJ+z7s07H9/KUt+DyqhC5gyUDHwtaDbj4rb4wfU9nk59oln3D9P9fS7AsTGnkqAI26C+Z+p8Nrm00Z3P7uZ47S7O2X1YF6I3nTGRMBWL+/mYDRxCEa09lc2cyPn9/Il//6ESt31cOoueokM1N4zNfh4ofh9n1QNCn1wpqmygnNcw6uh7C/8wG//wd4+gq1OHHFanjoLHjlliP+syWOfpZatcRAo2siXzWCI3dAfRDk7OTnXRydJDgSQoghqLI5wDAjOKqkkANNPtVVLD0P3AeYsftBAPbnHsd1XxjHmVNLevwcmqaR6bARw0LMzD60nnfUVMGIZlUuVzHyy3x51jBmjcyNT8Yvb/BDjgqGRholaTt0NWfGLM8y50Jt92WpY/UoHFjT4/EeDm9QvREyM0e5BWXxrNanFhUczdZ2kqO7AfjS/JNZHVPBXGzvRzz4wW62VLr7ZGyZTisuVCDg0dPi2xuTSuHW7mvEG4oSjenUegJUnfUXTg3+iVP1f2CZ990Or51rBEddldVForF4967OMkcA588axteOH8mXZpby9PVzuXC2+n7vqvXyidFZb2tVC3zh+/ClP8DY+TDtAphwpir/s3WS4cwdreYjxcKJZg4dWbtE3Z74X3DsFer+mofhL3Ng6R1H1+K+4siKxRLlsLpOZrNab8ufN4UTxuQzfZiaozelNItvf2Fsf41SHCLpVieEEENQVXOAWWZwpOdjbQqAzQmn3Axv/4y0iHqj3lB40mE9T4bTSkswQjitAGugse28o51vY0FndWwKGcWJNxEj883gyAclo1NOMev6NSMbNb7Ixcd7GthZ44GRJ6lJ+eWrYNyCwxp7T7QYnxIXWoxStYx8JhSr4Ogzt4sa1xSKPWrSNplFpGXm8HE8OFrBrzdu5sRxhTx1/bxeH9uYgkwq96vgqCma1u4xH+9JZPSafGHSHVb268UUOzsvpTQzR01dZI7MrBF03JDBZLVo/Parx8Qfr9mnMlyf7mvkYHMAgKpmv2r0cOK31b9W9tZ5yc2wk5vRavyaBiNPVOVyFathdAdf75Zq9XOEBmf8VHW2O+ZS+M+NaoHfj/4PNv4brnoRCid2+nrEIPTsVar743dXQ8SPI+IhpFuxFE7EYtH493dOxh+KktfDUmRxdJDMkRBCDEGVzX5KjYYMVXoBB5qMEqOTbohnatx6OtHiGYf1PGY775DDmMPS+tP2uh0AbIyNpTgr8cZ9lBEcVTT42ixYamaOqprVmMcXJTVlMMumylcd1rh7ymNkjgo1o+QqoyCeOdpV62VT1hcSB+eNxZVmY7M+Br+Wji3cwnitMv7Gv7cFozEyzcwR6e0esy1p/lGzP4zHCPZczs4/Q81JXgi2la0H3Uz93zc4/y8f8nbSwq6OLjJHrZlfxw92JALrzr5WH+2s48w/LudbSzqYIzTSCPg7m3d0QGUzKZqcaPk97jS4aQ187XG10Kd7Pzx8Nmz5T7dfixgEwn7Y9ppammDPcqhWJXW79GGU5qtS2jS7VQKjAUyCIyGEGGJ0XaeqOUCJsY5RlZ5HpRkc2dPgiz8H4J3YHPKyOllrphvMpgzuXGM+0M63Uw+oV8HRbn0YxdnO+OZRSZkjPScRHNXZh+FHBVHmG3IzQ5MSHO3/pN3mD32ldVkdGQXxce2u9fChbW7i4PxxZDltRLFSqZUCMFyrpcHTdVODQ+ELRlLK6uaOy4/vG5bTNpPU5AvjDRnBUVrnwVFuJ93qXlpfiT8cZeOBZv77qXUA2K1ajyeoTzA6EoaiiexTVQfBUUsgzA+e20A0pvNpeRPN7ZX7jTEC1Z3vqPVp2mOWZQ4/PnW7zQlTz4dvvanWWvLVwzNXqTI7MTTUbFGluwAHPoWazYCaCzkst/0PH8TAIsGREEIMMW5/BF8oGg+OavTcRHAEMONirs38Kz8OX9vjDnWtZRqZozd0Vb6kb3tFlaM8+TWo2oReZwZHZZRkJ96oDzfeZPjDUZqdZfHtza7x/HTRVLKcNm75opp0b2YW9tb5iBRMUWvyhDzxNy1HQkswAujxOUVkFDAyPwOH1UIwEuON6lx2x1QgRP7YeNBxkAIAyrQGWoKR+EKpvckXiuLSVDDhIYPTJxcztUxlQ06bXNzm+CZ/OF4maH7/OpKTrvY3t9OtzizVm1ySFd8Wjuo9Hv+o/Mw2AVVHmaPfv7k9kQUF1u1vantQ2SwonQnRIKz/V/tPut8IjkYc1/7+zEK45g049Vb1ePX/g3DfZP7EUebg+sT9yk+hahMA22Oj4r+3xMAmwZEQQgwxlc1+LMQo1NQb+Wo9j/IGH+5A4lP2dYFS/KSR7zq84CjdyBz9amM2B/V8tJAHHrsAPn8DPrgHmvYBsI9h5CfND3HYLOQbgVmNNfEGPlQwmeu+MI71P1vIMSNyARVIpdkthKIxKppDak4JwO7lhzX2nvAEImTjw4qR3cjIx2rR4tmjSneQv0YuIOAaAdMuiJerHYipckOzxLHR2/trHvnD0UTmiHSOHZnLry+cweLTx3PtqW0nizf7w3iDKkjrMnNkfM+a/WE27G9S2TvAH4qywQhMHrhiTo9L6ZI5bBZG56dmMKvdAWJGg4ebn/qMy/7fKjzBCC98egBIrMllduSraPBx9SMfq4BN0+D4b6kLrXlELZCbLBaDys/U/daZo2T2NDjzDnCVQsTf/fbgYmBLbr1/cD26kQ1fE5vEsNz25/SJgUWCIyGEGGKq3QEKaMZKDF2zkFtYRiAc489vqyxOLKbT6FOZgPzDzRw5VXCkY+HVqDHXI2osOLrtVTQ9hltPR3OVYGmVHShyqTK76lAaHtSbXWvpdICUYy1JQcj2qpbEek07lx7W2HvCG0yscYQ9E+zqE+RzZpTGj3k+Np8D31wNxVPiwVFFRAVHw6hHI0ZDc3Ovj01ljlRwNKy4kONG5zF7VB63nT2FEXltP+lu9oXwBFWQ1uWcI6Mhw84aD199YCXn/flDNh1o5rPyRsJRnbKcNMYWZvLKTaeSl2HnrKltM1XdMd74/poiMZ16b4jdtR5eXFfJyt313P3aVlqCEQpdDq4+eQwAn5U3AfDQh3tYtr2Whz7crS4w8xJwuFRZ5653Up+seiME3WBLh+JpnQ9M0xKNP3a/d0ivTQwwyZmjsA8t6KZKz2Ojdcph/74URwcJjoQQYohp8oUp1poA0DKL+d8vq85gS1bsZWdNC03+MMaH8uS17vbVQxlJZVkvR43SOs0CmiUeJO3WyyjOafsmvShLBUc17iCr9Kn4dQcZE05t93mmlKoysW1Vbpi4UG3ctwICfdMeuzVPMBJf44iMgvj2C44dnnJcsfGazIxMZUzN/ynVGrjd9jRTlkxPZC16iT+UyBydPG0sNmviT3+a3RoPcExN/jAeM3PUzYYM1e4goWgMfzjKtY9+wovrVAbnxLH5aJrGpJIsVvzwTP5xVSeZmE6YpZM2ixZ/A1rVHODdbTXxY55YXQ7AgsnFHDdaBZ3rKpqIxXTe31ELQEWDUXLnzILZV6r7r/4PbH4R/nmhymo+fK7aPvIEsHajqe/409XtLgmOBr1oWK2jBvHGNQCvRU9iWG5mj9eCE0cnCY6EEGKIafKF4vONyCph/qQizppaQiSm8/BHe2nwqqAlJ92O3Xp4fyYyHYm2zev1CfwwfB3Pjf810dJj49t368M4dmRum3PN4GhHjYfrgzdzYvB+CoePb/d5ppSqeS3bq1qgYDzkj4dYBHYvO6zxd1dLIClzlJFoeDCqIINCV6LRhBlspNutWLTUOUcLLZ9giYVh43O9OjZfKNGQAWdWm/2l2amlQMnd6jK7CI5yWwVWoAKlZ9bsB1RwZEp3WA/5zaPZkXBcUSYjjWzXwWZ/SnBkOnNKMZNLs0izW2j2h/loVx27a72AKq/TzTK603+s3uA27oVnvwm73lXZn7BXldMt+mP3Bmdmjg6u77jBgxgc6j5XH+o4smD6BfHNL0fnSTOGQUSCIyGEGGKa/InMEVmq2cFlJ6pPQT/aWUe90TXtcJsxAKQnZY4KXQ6eip7BHysmUZufmOg+f9487jivbfmSmWXZeKCJGBbsmbmkdbDafCJzZAQoZvZox1uH/Rq6wxuMkK+1zRwBfHnWsPh9MzjQNA2X08ZBXQUPI7RaxmhGu+s97/fq2JLL6nC42uwvMTrW2a1qbE2+cLz7XlYXc45aZ52unz+OeePU69c04vcP18JppZwxpZjFp0+g1BjvjhpPvOlDWdJrOHViIXarhWOG5wLwhze3x6/TEowk2o6nZcOX/5J4khO+DRc8AN/4N1z3dvfXL8oqNcrvdNXaWQxeZla3dCaMUHMb3c4yPtMnyHyjQUQWgRVCiCGmyRemBCNz5CoB4KRxBVgtGvvqfXyyV73h7I36+eTM0TdOGs197+3kYHOADyOT+aqxvXD0dGinvbOZOdqwX83DaZ3hSDbZyBztrffiD0VJn7QQVj8AG56B/LFqcVtL54uPHg5PMEJeO2V1AP+zcBJ1niCnTixM2Z6VZqcqoIKjNC2pEUPVRpWBSMpAHapoTCcYiZFpNzqpObPbHFNifJ2nlGaz8UCzyhwFzW51nX/NWgdHX5xWwo/OncKy7bXo6IwrahuMHYqcDDsPX30CkJhH9OyaCiIxnXFFmVxx0mjuemUL88YXkpWmxrRwegkf721g/f7UeVwVDf7E4rDjT4dvvqJadJuNPA7FiONVi+fazw/9GuLoFovBqgfU/TGnwJRFcMb/8sS+4dCsUdZOabAYmCRzJIQQQ0xzO5kjl9PGbKO07S/v7gTguDF5h/1cGUllWceOzGXaMPXm/L6dRcR0IyAqaP8TejM4MttKl7WzJk/ysQWZDnQdPq9ugTHzYfKXVAnMO3fBuicO+7WEIjFW7Kprt912SyeZo0ynjT9fNptLj09dzNbltBHASYPeOoDQYe+Hhz1eUJ3qALK0jsvqLj1hJCeMyeNbp44BVNmlGRy50tqWzSWzWS3xUkFNg6ll2WiaxulTijljSkmvvIbWzMzR3nofoMrorpo3mt9cNJO7L5oZP+6aU8byhaSA1Az0Khp9qRcc+4WUwKjeE+Rrf1/J4ic/5d1t1YkyvM5kGdnBlspDeUliINj4LFRvAmcOzP2u+rBl/vf5KDgOgOHtNDcRA5MER0IIMdjVfg7GekKg3vwWJ805Mp08Qb2RDEZiWDS4cu7ow35qs1QLVHZnzigVcO3x2vlt5OvsGncFlExv91wzODKVdhIcAUwpS5p3ZLXB15+E465RO3uhycFjK/dy+T9W89CHe9rs8wYjjNDUpH9c3evIZnbyq9LbKT3rpdI6n7mYa3zOUdtMzglj8nn2hpM5Zbz6/jf7w7QEzG51XWfbzOzR2MLMLhs49IbkINlhs/DNk8dgs1r4+omp68xYLRp//vpsJpW4mFqWzelT1PelvMHX5prJXt9Uxeo9Dby64SDfWrKGHzy3gVAk1uk5ZBtrcbkPHtqLEke3aATe+6W6f+p/p2R1P69WH4pMLO6dLKnofxIcCSHEYBbywUNnwd++oCae0/6cI4BTJyQ+ZV84rZQRealryxyK5MU6y3LSmD0qN/7479HzCX3xbpVyaEdxq+Cos8wRwOQSlZV6f0etWghU06B0htrpaTtxv6e2HFSd72av/zk8+mWIJBY+9fjDHG8xSqpGdK8jm5mVMecdAax1GhmMXe9A7PAXhPWHjK5zmllW1zZzZMo2gpyYDhWNKpjK6iJzBJBrdKybPizncIbabcmLBV9z8phOf07zMh28/t/zee17p8bXPqroIjjaU6eaN4wvysSiwbNr93PFQ6tp9IbYU+dt/3zJHA1ue9+HpnJIz4OTvhPf3OQLUdOiGthMLOn4/5YYWCQ4EkKIwax2GwSa1SKVb98JQLMvnOhW50pkjo4dmUuW8cn/NaeM6ZWnP3m8yooUupxomhbPHIFqyzy+kzkpRa7UYKi0i5r+qUbm6JUNBzntd+/xxqYqtUAnQEvVoQw/RWWTn3zczGt8SU28r0osBpkROEiZ1kBMs8Hw4zq5SoL5tU4Ojp62LCJqd0HDbvjkocMesy/Uuqyu7ZwjU5rdSppdvS2oNd7wjTO6xHXGDI5mDOv42r1pfJELh9FF8bunT+jyeKtFQ9M0RhpBlBn4dcQMjr516lgeuvoEXE4bH+9pYP7v3+P0PyzjnD+9T1VS0A9I5miw2/hvAAKTzufut/fFFzv+vFrdDs9NPyJZU3FkSHAkhBCDWc2WxP3NL0D5Kty+AIUYk9STMkcOm4UHv3k8//f1Yzmpl7qMnTqhkKeun8sbN38BgBF56fHW1uOLXDhsHf8Zyk63pewf1kXm6JwZpVxw7DDGFWUSien86PkNNFhy1c5eyBwdbA5wgiXR+Sy5VHG8fxMA/oLp4Og6oIBEW++DRlldTNd4uXEkvwhcqh6/fSfU7TysMavgSCeDjrvVJctNTzThyE6zddoEw/T1E0YxZ1Qu5yV15etLRVlOXlx8Ch/efnqbhhCdGZlvBEddZI72GsHR2MJMTp9czPPfPZkReenxuW/eUJTHVu7ls/JGHl2xV81JMjNHvjqIBA/hVYmjViQIW18G4HVO5e/v7+bvy3cBsN0oqTMbwojBQYIjIYQYzGq2qluLehOpr/gLFn89Ni2GjgaZRSmHnzSugK+0Wrj0cGiaxtxxBfGASNO0eGldV28oNE2jKGmNoK7mHGWl2fnT12fzxn/PZ1pZNo2+MH9caQSBnirozsT6DsRiOgebApxg2ZbYWJ8IjqaG1cKQoWHd73hmLgRrZo7K9WL8pPFo+AzWxiZiCXvRH5inGkoc4tj9oSgZBLFgnN9JWR0kskCgutd1Z12i82cN4/nvnpIy36evTRuW3eOyz5H5anwHGv3EYu1/PcPRWHxOklmGN6kki5dvPJU/XDKLX3xFzY/758p9XPaPVfzspc0s+7xWzUGxGoFlL2QpRT8JNKtFgfevSWzbsRSCzZA1jA9DqnmMWS78ubF0wCQpqRtUJDgSQojBzFzNfc6V6nbXewzHaByQWawaFxxhlx4/kgyHla8c23WmIbkpQ1fBkclhs/Bro2vZf3aqT/uJhiDQ1P4Jug5L71BvijpYxLPOGyQUjbWbOdJ1nWNiRhA6am63xgiJzNGK2HQOaKU8HT1dXQ8LN4Vu4qPodLRoCD64B9wHun3dZCkLwGpWsHcewGQnZWIG26fhZTnp2CwaoWiMg+5Au8fsb/QTiemk262UZCV+3vIyHXz1uBFcftJoRuVn0BKMEAirJg0rd9Wr+W1ZvVfCKfrJp4/BJw/C01dA0Og+uf5f6nbGRexrUD83dcZacInMkTRjGEwkOBJCiMHMzBzNugxcpWhhLzfYVImIltN7GaKe+OK0ErbcdQ5nTu261bMZHOWk28lwdD+Qm2x8ktsSsaGn5aqNLdXtH7znffjo/9SbogdOSQSUSQ42BcggwHRtb2JjvSqtCXoamaTtB8A+dl63x2gusFpFATcWPczfYl+O75s2dRrfCP+YFptR3thB0NYVfzhKlmaUkTldHTa/MOUO4uDIatGYYHQU+96/PqPZpzryBcLReDe6PXVqDsmYwkws7ay9ZbVofHu+at1stgZfvbte7ZSmDAPf/k/UbctBWP5baNgD215V22ZfGW8fX9sSRNf1eKc6yRwNLhIcCSHEYOVrUOVkAMVTYdJCAM62GiUjs77eTwPrPrNjXVed6lpLd1jjmZlwulE66OkgOFr9d3Vrsak3tu/8InV/NEJlk585lh3YtBg+3chmNeyCWIzgnlVYNJ09sRIy8ro/7yYzaQJ3Vpo9pXLu2JG5gIbPanwiHUhdyLS7fKEomXS8AGxryWV1ZoOLweTXF80kO83G2n2N/Nfja6htCXLa79/j/L98SCAcZXetmm80rrDjeWNXnDSKx751Ii8uPgWATZVu1fpcmjIMfPvXJu6vegBeugnQYfyZeHImUOdR88kavEGq3AGafGEsGp02lhEDjwRHQggxWJnNGHJHq7kmk86N72rScmD2lf00sO4zM0fdLalr71y/s5PgqGEPbH9N3b/oH+p2z3IIB9S/566Fu4cT2beaUy2q6cLS2HHELA6IBKC5gsAutWDrOm1Ku9mGjrhSgqPE/eNG58WzZF7t8IMjl9a9ZgxASoODwfhp+JxReTz9X/NIs1tYtbuBbzy4imp3kO3VLTzy0V721ieaMXRE0zTmTypiYkkWI/PTicZ01uxrlMzRQNdSBe79gKZ+V8YisPcDtW/udyivTzTyiOnw8R6VzR1TkEmavev1wMTAIcGREEIMVmZJXfE0dTvuNKIWNWn8ddeF4Dj8dYz62txxBThsFk6bVNT1wa2YzRw8dqNVdnvB0ZqHMT8ZZvqF6g1u2Ac73oR/XgCbnoNIgGmf38fF1uUAvBY9kUCWWiD3kzWrKV/3LgA702b2aHyupIAoO83GHy+dxexRufz5stnxwMmjGW/SO5ov1QV/KEJWfAHYroOd3Az18zE8N71baxwNRFPLsrnhtPFAohUzwH3v7WTNXtXifkwnwVGyuWNV2ePq3Q2SORrozCYMxVPha4/DvBvV49JjYPyZ7DMCZ5P5s9JZIC0GJgmOhBBisDLr54unqltHJusm3sib0eNZVXhR/42rB+aOK2Dzz8/mmlPG9vjcwiz1Rr9RM9ZWaj1RPhaDTc+r+8d/S83HmfhF9fjFxVC+0ihF0xjv/pgizU2VnsfbseNwZ44B4NM1K5iJard98YVf7dH4slqV1V00ZwQvGF3fMpzqk2i3bgSwh1VW1/3gyCxjnH6E1izqL/81f3y8NfyFs4dzzIgcPMEI24zuY919w2u2vF+9pz7RFr9FgqMB6YARHA0/TjWqOftXcNOn8M2XwWKJzzcyrd2ngiOzRbwYPCQ4EkKIwaipAt14469POie+eWXJ5fxX+FbSMvM6OvOoY7ce2p8qM3NUp+WqDa3XOjqwFtz7adHT+f5nhWr9m0lnq30ho1PVJUtgcqIc8ZnYGUSxUuccCcDJ/mWkaWFi6QWMm3xsj8aXnDnKarWApDkfqbkXgqN4WZ2z67K6RceUcfs5U/jhuVMO6fkGinSHlfuvOI6rTx7Dz86fxr1fO5b5k4ooy0njxDH5zBjeveDw+NHq/9HmSjcRc8Fht5TVDUhm5mjE8YltBeMhPReA8obUzNG2KjcAoyQ4GnRkOV8hhBhIqjbC52/CKf8N1k7Knj68Fy0W5sPodLaXF3PtKLW5yejQlTzxfrAy5xxVRXPUBk9q5qhm9VMUA+/EZvPchnpWlq/ive99AYfVAdEQa/MX0RSewZlzvwPbXyOiW1hbcD5UQaV9NDOAmZY9AGijTuqyE1xrHc05Asg05hw1xQ4vOPKHohT0IHOU4bDxnQXjD+m5BppjR+YajS9UOeFj3+r+GlWm0QUZZKXZaAlE2B3MZhKozJGu9/jnQfSjaAQqP1P3hx/f7iF761TmyGG1EIrGMJfKkuBo8JHMkRBCHO2CLeCppdodQH/1+/DuL2Djsx0f31INn/0TgL9ELuLP7+zAHVBBUZNf3eYMoeCoImxkATw14KkFXScciaJv/g8A5aVfJCvNxoEmP9saYrDgR+zIPYVrKr/C/764ieCIk7kj/E1uDi+mbKQKHD7JnE9N/nHx59JGdb+FtynLmfgetJ7fk2G0ia6PGusSHWrmKBwlRzM+8TZbmoteo2kaM4ap4Htjo7EIbCSg5q2JgePAGgh51P8Rswy5FXPO0cwROSnbRxVIcDTYSHAkhBBHo+rN8XV0ePyrRP88hwt//TTh/canmwc+7fjcXe9CNMRWxrFan0qzP8yDH6gMRzxzlO7oy9EfFQqNsrq9AaOcrHYb/GECPHw2Vc/+DyV6LV7S+Mbl32LOKFUetb6iicqZ32FR3U24cVHZHOCNzdU8Fj2b92ynMq5IzUWp9Ws8MOL3PB89VTV8mHp+j8eX6Ux0uGqdOTKzSocbHPlDEQo141xX8SFdQ3TuGOPN8rqqYGJjSIKjAWXnO+p2/Olgadt57kCTP75wsFlKaRqZJ8HRYCPBkRBCHG02PgcPnAwPLVRZo4pVWENuvml7E4duvAE7uL7j8/eq1tLvRWbENz30wW4C4SjNfrWy+1Aqq9vhazW5vmI1I7c/AsA7JddRkJfLLKO8al1FM396+/P4oqAAv35Ndf1bMLmY/Ex1zQZfmA3VQW4Nf5d3vvQB5Pe8YYTNaiHNrv4MZ6e3yhwZgVNdxGhhfhhzjoowg6OuF90VPTdjuAqONhxoAbvxRjns7eQMcdTZZQZHZ7bZpes6P/z3BnQdThiTl7I4cqHLSbpD2ngPNj0Ojt5//33OP/98hg0bhqZpvPjiiyn7PR4PN954IyNGjCA9PZ1p06bxt7/9LeWYQCDA4sWLKSgowOVycfHFF1Ndndpitby8nEWLFpGRkUFxcTG33XYbkUik569QCCEGku1vwL+vU/d9dSoLZLjM+l7iuKqNqk6+PcbaHKtiU8nLsFOU5cQbirJhf3NS5mjoBEd7fHb0jEK18dRboGQGYWzcFr6e8InfAWC2ERyt2FXHC58dAOCsqSrTUu1WAek5M0rJz1Rft7qWIFsPqgnZ04alltn0hJndMm9NrnhDBrOV92EER1qTcVHJHPWFmUZwtLWqBd1hfL9CEhwNGL6GRCZ+/Bltdj+3dj8f7KjDabPw24uPif9eARiVn36kRimOoB4HR16vl1mzZnHfffe1u//WW2/ljTfe4PHHH2fr1q3cfPPN3Hjjjbz00kvxY2655RZefvllnn32WZYvX05lZSUXXZRoKxuNRlm0aBGhUIgVK1bw6KOPsmTJEu64445DeIlCCDFAhLzwys2AHt+0+d0n4/eztaRSnYgf6ne0vUZTOTTtI6ZZWRObzNjCTE4Yo8pA3ttew5469aZtxBAoBSkwsjzhKHxL/xnfTfsN3i/8FM8173F86O88G13ASePUGkhmadTB5gDhqM7M4TncdMbE+LWcNgunTykmz1gHaMtBN75QFKfNcljrnPzuq8fwiwtmMKE4tZNcms2Kph1+K29/KEqRJpmjvmQ2ZQhFYoQtxptlCY4Gjt3vAToUTYWc4W12P/lxOQDfO3Mi44pcrYKjwf97dCjqcXB07rnn8stf/pILL7yw3f0rVqzgm9/8JgsWLGDMmDFcf/31zJo1i48//hiA5uZmHnroIf74xz9yxhlncNxxx/HII4+wYsUKVq1aBcBbb73Fli1bePzxxzn22GM599xz+cUvfsF9991HKBQ6jJcrhBBHsZX3q05XOaNg2lcAGFH7fpvDdIwuWO2V1u39CIAa1zR8pDG20MXxo1UA8NiKvURiOmMLM4fEJGKHzRIvH3yvsYDXmkbx1pYq1uxrojmWzsj89HiQWOByMjLpU+CvnziSGcNzyDEybKdNKsLltMUDLtOU0ixsh9hqHODk8YVcOXd0m+0Wi0aG3YqbwwuOgqEA+RhtySU46hOapsWzRz6Mnw8JjgaOcvXeszz3JF40ssamek+QdRVNAFw0RwVOyVleCY4Gp16fc3TyySfz0ksvceDAAXRd57333uPzzz9n4cKFAKxdu5ZwOMxZZ50VP2fKlCmMGjWKlStXArBy5UpmzpxJSUniF/nZZ5+N2+1m8+bNvT1kIYTof74G+OhP6v6Zd0DZLABytLYTuyNjF6g7levaXseYb7TZcQwAYwszOGGMCo68oSgAp08eOuVVRa3K1V74rJJVuxsAmDu2IGXfrBG5AKTbrXx51jCsFo1zpqu1a7563AgA8jJTyxG/fuKovhg2oNY6cptldUE3xKI9vkZaqBGLpqNrVkjP7+URClOpsaBsQJPM0YDTrAKih7ZZuPnpdRxo8sd3Lf+8Fl2HqWXZlOWo721ehgOrRX1AJQvADk69Hhz95S9/Ydq0aYwYMQKHw8E555zDfffdx/z58wGoqqrC4XCQm5ubcl5JSQlVVVXxY5IDI3O/ua89wWAQt9ud8k8IIQaMyk9VK9m8MTDjYiicnLK70VYEQIueTvP4L6uNZuZo9zLY/IKxbR0AqyITABhTmMnUsiwykyYNnzFl6ARHGa0WV/1wRy0vfLYfgLnjUoOj+ZPU1/ji44bHW2vf+eXpvHnzfBYaQVLy2kTHj87j6yeM7LOxZzpttJD05ivY879rmeF6AKIZRWCRHkx9Jc2u/n8Fpaxu4Gk5CMCBqCo/3lqZ+H/27ja1cPQZU4ri26wWjUKXKq+VzNHg1CfB0apVq3jppZdYu3Yt99xzD4sXL+btt9/u7adKcffdd5OTkxP/N3Jk3/3BEkKIXhc0Sp+yytSb2KIpKbvfyb4AgE9ik6nPnq42Vm2AcAD+dTk8e42xjo9qbrOhRXVUGluYic1qYY7RfjbTYeXEsUMng2A2TQCYNTKXmK4aLIwuyGDh9NQP4b46ZwTP/Nc87jhvenxbusOa0p1K0zS+OW80J47N58FvHo/Whwt9ZjqthLERtRpvuP1NPTo/FtPJjqosmZ45dALi/pBmM4IjzeguKN3qBg4jOKrW1e/IbVXqd0YkGuP9z2uBth8ofX/hZC47cRTHtWrrLQYHW9eHdJ/f7+fHP/4xL7zwAosWLQLgmGOOYd26dfzhD3/grLPOorS0lFAoRFNTU0r2qLq6mtJS9clcaWlpfI5S8n5zX3t+9KMfceutt8Yfu91uCZCEEANCsy+Mr7aOMgCn8UY8bwxh7NhR3eVecp7Pi6FCtsdG8kfnKCbb0lWmadsriTdiTeXovno0YLdPfaI5pkCVZZ00Np8PdtQxf1IRDtvQySD84OzJ/PLVrdx81kQKXE7WVzQxPDedJ789t83CqxaL1q3A8edfmdHlMb0hw6H+RIfs2aRH/T2edxSIRCk02nhrWTLfqC+ZLdn9ZnAkmaOBIRqJf6BUFQ+O1AdV6/c34Q5EyM2wc+zI1CDokuNHcsnx8h5zsOrV4CgcDhMOh7G0St1brVZiMbVmxHHHHYfdbuedd97h4osvBmD79u2Ul5czb55aYXzevHn86le/oqamhuJiFa0vXbqU7Oxspk2b1u5zO51OnE5nu/uEEOJo9uX7PuSMpvX8zA44jK5lVhv7rcMZG93LQQppDFnZGJsJQHNQh9IZsP8T+PTRxIVqtqDpMWK6RgNZlGankWmUgV176jgsFo0LZ7ftxjSYffPkMZw6sZDJJVnEdNXCfO64gpSOU0crsxQyZMsineoeB0dqjaMmAKwSHPUps6zOjwRHA4q3BvQYEd1CPaqphhkcrdnbCMCJY/Ljc4zE0NDj4Mjj8bBz58744z179rBu3Try8/MZNWoUp512Grfddhvp6emMHj2a5cuX89hjj/HHP/4RgJycHK699lpuvfVW8vPzyc7O5qabbmLevHnMnTsXgIULFzJt2jSuvPJKfve731FVVcVPf/pTFi9eLAGQEGLQ2VfvI9OqVl/HmWjpvJsRjGUvu/UyPMHEmkbN/rBq2LD/E9iT6GYXPrAeO9CIi4UzhvOVYxOBULrDyncXTOjz13K0sVstTCnNBsCqwfmzhvXziLrPDGwDNpd629bD4MjtD8fbeEvmqG/FM0cSHA0sRkldDbnkZaZR7w2xp85LIBzl03IVHEnp3NDT49qKNWvWMHv2bGbPng2odY1mz54dX4Poqaee4oQTTuAb3/gG06ZN4ze/+Q2/+tWvuOGGG+LXuPfeeznvvPO4+OKLmT9/PqWlpTz//PPx/VarlVdeeQWr1cq8efO44ooruOqqq7jrrrsO9/UKIcRRyaWp4KgqYOfWp9dR2xJkXWwcABuiY6j3BOPHxoOjVvz7NwDQZMnlgSuO45wZ7Zchi4Eh0yir81uMgLmHwVGjL5S0AKwER33JzBx5dWnlPZBs2b4dgBo9j0XHlJGTbica09lZ42HtviZAgqOhqMeZowULFqDreof7S0tLeeSRRzq9RlpaGvfdd1+HC8kCjB49mtdee62nwxNCiAEpE9U+duX+IM/XHOCYETk8GDyTbRSyIjYdb6RV5mjysW2u4azfAkA4rfCIjFn0LTNz5D3E4KjBG05aAFYaMvQlsyGDBEcDx8FmP8++9zE/s0KLo4j/Om0826taWL2ngaVbqqnzBLFbNWYYa1iJoWPozMoVQoijkPlhU6aROSr3qF/L5Q1+/DE7S2PH4yU95Ry3P6y62VkdKdudEQ8A1ix5IzwYZDrVG27PIS4E2+gNxeccSeaobzmNsjqPGRxJt7qj3qrd9RTqqtX9vFkzGZ6bzhSjM+XTn1QAMH1YTjwrKIYOCY6EEKIfhaMqOMoyMkfVQdVBbW99x2+umv1hsDmg2GxQkzpZODO/rPcHKo44M3PkxlgItqeZI18oKXMkwVFfMt9At8QkczRQfLqviVJNzSuy5aq5iOaSB1Vu9WGVlNQNTRIcCSFEP/KHo0CirM6jqwnde+u6CI6AvelTAWgqnJOyP79kRK+PUxx5Zrc6t35omSOPu5ksTf1cSVld35LgaOD5tLyRYlRwRJb6QOm8Y4bxjZNGxY+R4Gho6tVW3kIIIXomaAZHRlmd1+h2Vd7g6/AcMzh60HIJhZEgGUVf5vq6q+P703KkEcNgYK5zVB8z5hzVbAFdh+4uPNu0D4CQNROHw9XFweJwpBlrh7VEjVLXUMf/f0X/8wYjbKtqodRmBEfZKjiyWjR+deFMThiTz7qKJs6aKhnXoUgyR0II0Y/MzJErnjlSWYJIrOPGN2ZwtNmdxp8iX2WX3qo9tWQJBgWzrG61dQ7YM6BqA2x9qdvnZ7l3AODOmtD9gEocEjNz1BQPjjz9OBrRlfX7m4jGdMosZuYo9XfoBbOHc+eXpw+pBbNFgnzXhRCiHwXCaoFsM3PkMddJaYe5lkqzTwVHFUZ2qS5gIWBNygxkSre6wcBsyHAgkg3zblQb3/45RMPdOr/Aq9Yk9OdP6ZPxiQQzOGqOB0dSVnc0+6y8iQwCuDAyfNkyT1MkSHAkhBD9KBCfc5RaVtee4bmqa11LMEJLIEydJwRAkz9Miy0/cWCmZI4Gg3gr71AETvkeZBRCwy7Y+nK3zi8L7gYgVjS1z8YoFPODi6aIaqhCWMrqjmaflTdRbDRjwJ4Jzqz+HZA4qkhwJIQQ/UiV1enx4Chiy8Rmab8EapgRHOk6bKl0x7c3+UI0WpKDo6I+G684csxFYL3BqHrzNudKtWPTv7t1/uiomnNkK53eJ+MTCWbmqDGclDnqZE1I0b/qvUGyzaxRRn7nB4shR4IjIYToR4FwlAyCWDT1RmrK6GHkZybWL0qeKlKQ6Yh/Qr3xQKJzWbM/TL2WC0DIlgX2jrNPYuDIMLrVeYPGAsAzvqpudyztsnNd2NfMCGrUdUYe02djFIq5CGx8nSN0CPv7b0CiU/5QFJfZyVGyRqIVCY6EEKIfBcLReBtvXbPw5ytPpsDljO8vzkrcd6XZyElXZTubkoKjJl+Y6phaxT2SXnAkhi2OAJdRVheMxIhEY1AyHQonQzQI217t9FzP/s0AVOu5ZOdLx62+Zi4C6ydpYWaZd9RWLAYPnwP/vKhfM2u+UDS+tpwER6I1CY6EEKIfBcIxXEYzBs3hIsNpp9CVeINlzjMCcDnt8eBoQ1JwFInp7A2qP/CxDCmpGywyjIYMAN94cDXLd9TBTCN7tPG5Ts8NHtgIwG5tFNYOyjRF73HaLGga6FiI2Y11qaRjXVvuA1C+Ena9A776fhuGLxSNdwiV4Ei0JsGREEL0I3846Y+0sRZNQVJZ3fC8jPh9l9NKbrrat7s29VPpT4IjAYiWzOzL4YojyGmzkm7MZVm9p4E7/rOJ2LSL1M7dy8Bb1+G5evUWAPbbx/b1MAWgaRpOo+2zbjP+z0pThra8NYn7xjpc/SEQTiqrkzXARCsSHAkhRD9K+SPtVH+k8zMTpXQj8pIzRzZOntB+2dxHsZnMD96LvvBXfTdYccTd9ZXpXHLcCFxOG/vqfaxqzoWyY0GPwpYX2z/JU0PBrhcAOJAhbbyPFLMpQ9SeqTb0Rlmdtx6evx4OfHr41zoaeJKDo/J+GYKu6/hCEckciQ5JcCSEEP3IH47GO9WZf6QLOiqrS7NzzSljyTLmokBiXgrAfkrIzkgcLwa+S44fye8vmcVXjlWLVD71SQXMuFjt3PR8+ye9dhuOcDObYmPYln/mERqpMLN8UVsvltWtewI2PA1v/fTwr3U08FQn7vdTcBSMxIjpkBX/UCq7X8Yhjl4SHAkhRD8KhGPxhgxmeUfKnKNWmaOcdDuXnTQqvm1yaeJTz5x0OxaZXzIoff0E9T1/Y1MV1aPOVRv3rYDmA6kHlq+GLS8Sw8rt4evJdUmwfKTEM0dW42se6oWyupaD6rZiNQTcnR87EBwFmSNzbbn4ArCSORKtSHAkhBD9SJXVtcocJZfVJWWOstJUlui/z5zI/ElFXD9/XMr8pLyMpE5ZYlCZMTybY0bkEIrG+Mo/y/GWnADosP211AM3Pqtu8heyWR9DXqb8TBwp5pyjcDw46oWyOjPTEovA3g8O/3r97SgIjnwhFRxlWVJ/7wphkuBICCH6UXIrbzNzlJ+UOcrNcMTXuzFL6DKdNh771on8+EtTyc2wJx2buC8GF03T+Mtls5lQ7KLKHeDtZlVmhzspcxSLwpb/ALAqcwEA+RIwHzFm5igRHPVCWV1yMLHz7cO/Xn9LLqtr7J+GDGZwlCPBkeiABEdCCNGPAuEomfHMkVFWl5Q5ykqzccyIHLKcNsYUZLY5PzlbJJmjwW10QSZ/uWw2AAeCxkK/vobEAftWqG5gabm87p0EQFmuLAh8pJgLNActRnDUG93qWqoS93e+3a9rAx2u2pYg9dX7Exuayvvl9ZhlddmaBEeifbauDxFCCNFX/OEYLrMhg5E5GpabxuSSLHIy7KTZrfzz2pPwh6Nkp7XNDOWkZI4kOBrsso11rqojmWAlda2YzapDXWjiItavUdnIE8fmH+khDllm5igeHPVKWV2rMrSG3VAw/vCv2w/+uHQ719cdoMD8WD7iV+3oXUd2bTYzc+TS/KAjDRlEGxIcCSFEP0opqzMyRzarhdf/+wtoRm8Fu9WC3dp+ot9c9wggT8rqBr1Mo8SyNuoygqOkzNHu9wDYnDMfXYdxRZkUZ0nm6EhJsxnBkWZ8zQ+zrO6Wx1dyb9BY7DlvDDTuhfpdAzY42t/op0gzXo9mAT2mAr4jHhxFAKSVt+iQlNUJIUQ/SmnI4Ej8kbZYNDSt685zyfOMZPL94JfhUJ9pNmL8rCRljkJNlQC8UKFaSc8d1/6aWKJvmGV1AQ4/c+QNRvhk8zYAYtY0yDcCIm/tYY2xPwV9LYnfdcXT1W0/LARrltVl6tKtTrRPgiMhhOhHgXA06RPMnq/UnpsuDRmGEofNgsNqoUFPDY4qDtbiiKk3ns9tDwMSHB1pZlmdx2J8b7x1h3wtTzBCMU0ABNIKwVVsXLOm45OOchafCuxCmhOKp6qN/dCxziyrS5fgSHRAgiMhhOhH/nCUTO3QyzuS5xxJQ4ahIcNpTQRH/gaIxXh11ToAvLoTH6qsa67MNzqizOCoyWYEpcnNFHqoJRChSGtS17PkQ6ZRenYYAVd/cwbU2N3WfMgbrTbW7Tji4/CFojgI4yBsDKznH0qJwU2CIyGE6EeBdhoy9ERyEwbJHA0NmQ4bTWZZnR4j5G3k442qBMtjUwHRxGIXxdky3+hIchpldfWWQrXBXMD1EHiCkfj8nJpYTiI48gzMzFEsppMeUsFRoyUPRs1VO3a+DbHYER1LyjxPSClnFgIkOBJCiH7lD0XjnxCT0fMyqDzJHA05mU4rYWxE7CqYXrlxOw7jU/mi0hH88oIZ3Pu1Y/txhEOT2ZChTjMydi0HD/mNvycQoVhrBGBfyJVUVjcw5xy1BCMUooK9enJgzBfUh0GeKji47oiOxReKqk51APYMsEpvMpFKgiMhxNCx6z347In+HkWK9HADhZobHQ0KJ/X8fLuVvAw7NotGqWQKhgSzKUPIkQdAVdUBCo0sgyWrhCvmjmbG8Jx+G99QZZbV1ZIHaBCLgO/QyuBaAmGKjGBit99FyGkEXAO0rK7ZF07NhNmcMP4MtXP760d0LL5QlCzpVCc6IcGREGJoCLbAvy6D/3xXtcPtb7oOsSjDw2pCciR7JDgyenwZTdN49FsnsuSaE6Vb3RCR6VRvwgP2XAAinrpE9tHMMIgjzuxW54tqiTI4d+UhXaslmJhzVKXnUhEyFoAeoA0Zmv1hiowGE1VRIyCZfK66/fzIBkeqrE4WgBUdk1yiEGJw8zWAxaY+nYwYnxY27u3ftUJiMXjwDAj7mRA7ASwQK+h51sh0zIjc3hubOOplGpkjvxEc6Z76eJYBV0k/jUrEF4ENRyG7TAUyh9iUwROIMMUIjmr1HD73pDMeVOYoFgPLwPps2+3xcIb1MwC2RkrVxokL1XpHVRtV17rcUUdkLL5QJFFWJ8GRaMfA+t8lhBA94T4If54N98+DNQ8nbT+0T3N7g67rNNRUQOVnULuNSy1q4U6KpvTbmMTAkulUwZHXapTOBRriZXXxjIU44uLrHIVjkDVMbWw5tN81KQ0Z9Fw2NBpzC/Uo+BsPe6xHWs7WJynVGjmgF/BK+AS11lBmIYw+RR2w6d9HbCxSVie6IsGREGLwev93EGgC936oWJXY3o/B0f97fzfX/99z8ceTLfsBsJRIcCS6J8OhMhQtlmwA7IHG+BtpyRz1H7MhQ8DMHIH6gOYQeAPBeAODWj2XvY0hSM8zdg6wpgyRIOO2/T8AHoh8mTA2WgIRtW/mV9Xtxuc6OLn3qYW3zeAo+4g9rxg4JDgSQgxODbvh08cAiGitKojdB/phQMqy7bWM1Nq+ubGVTO2H0YiByGVkjtya+tTbGW6Kv5GWOUf9xyyrC0SikGUER2bmqHw1vP5DVebbnWs178KuRfGTRi25NPnCSWsdDbDgaO8HZARrqNZzeSa6AAB3wFhjaNpXwGKH6k1QveWIDMcXiuJCFoAVHZPgSAgxOH30Z9UtasJZ/DnjJny6ky1ps9W+fsoc6brO1io3o7S2k6q1osn9MCIxEJnd6po09am3K9KUaMggZXX9xplSVpeUOYqE4N/XwuoH4OX/Vs1YAD74I7z4XQh521yryL0ZgL3OScSw0OQPQ6bZznuANWWo2gjAx7EphFDlgfHMUXqemnsEsPGZIzKclFbeEhyJdkhwJIQYVBq9IRb9+QMqNq8EIHzslTzQdCLTgg/ztONCdVA/BUdV7gBNvjAjLamf/B6kUP5Ii24zu9U16OpnZoRWS5pmfBIvmaN+E88cJZfVtVTB+iehuUI93vqSml8TCcE7P4d1T8ATl0I0nHKtYR4VHNXlzACg2RdSc3Rg4LXzrtoEwNbY6Pgmtz/p9c64SN3ufPuIDCcQljlHonMSHAkhBpWP9zawubKZHL9qkb2iMY9wVAc0dviN+vJ+KqvbetANwEgjcxTKUF2b9llG9st4xMBkNmSoM1oiT7EYb7wdLnBk9tewhrzEnKOkhgxN5fDBPep+8XR1++ZPoHFP4sR9H8Lbd6Zca0xgGwD+omMBaEwuq/MMsMxRtQqOtuiJbnTxsjqA4XPUbd0OiEWNZQ4ObfHc7lBldUZw5HD12fOIgUuCIyHEoNLoDZGLh2xN1ZTf/q47vm+L1/iUMNDUbilLX9t6sAVIBEf7jvsxH0Wn87zzK0d8LGLgMhsy1MVaBUKSNepXZre6YDgKWUa76lCLCpAyi+GaV0GzgqcK9ryfevInDyXmI4UDjIqo4Mk28jgA/OEo4XQzczSA5hyFAyroITVzFC+rA8gdDbY0iASgZgv8ZQ4sWQSRYJ8MScrqRFckOBJCDCoNvhBjtGoAKvV8qvyJX3NNsTR0u/GG8hC7SB2OLQfdOAhTimrFW114It8I/4TN6ccf8bGIgctc56g60io4ypTgqD+lNGQwO8sZQl/6k9pWMEFt2PIfdTvjq1A6U63B9umjalvVRmxEqdWzySkdh0VTm/2OfHXnSJfVeevg76fBM1f1/NzaraBHadayqSaPQpdaqDqlrM5ihcKJ6v7aJaqZTvkKeOeuwx97O/yhCFnSkEF0QoIjIcSg0uQLM1pTCy/W2Ia32qsRyjQnSh/50rqtB90M1+qwaDpe3UlFIANIvKkSojvMsrqqcAbetNLEDpc0Y+hP6cb/43BUJxTVYdwCYtY0vh2+je9vMMrsSozSun0fqdvCiTD3u+r+x/9Qc48OrAVgfWw8ORl2cjNUQNFiM1t5H8GyulhUNZM4uE4FdC3VPTvfmG+0QxsNaIzIU7/zUjJHkFjnbcOziW0r/6o6jpoNLHqBruv4w9FEx9DsYb12bTF4SHAkhBhUGryJzFF66YT49px01SXJl2asA3OEmzL4QhH21Hnjneoq9GIqGlVph1mOI0R3mA0ZPCGdx2c9xh/Cl7A/fTLMvrKfRza05aTbyTRKHvfVe+Ebz/GnY19maXQ2b22pIhSJQck0dbBuzKkpmAAzLlbzidwH4LlvoRtzlD6NTcTltJNr/O5qsBkf7NR+3qdzclJ8+Ef4/+3dd3hc5Zn+8e8509R7tyQ3XMHYBkwJzZRQAyGQXxqQbEKSTd/UTbLpm91lQ7KkkpBOsiFkU0kghNBrqAYDNi4Y9yLJ6n3q+f3xnjNFlmTJHhVb9+e6uCydOZo5Ywtp7nme93m3PpT63A1uY+auN1ofN+uNGspMOMpYcwTgTesMuyPpi+rNn3/5sKlYZSkghWMJgk44FY4qtYWCHEi/kUXkqNLRF2G2bcJR4zHLqC/NZXl9MctmFQPQFXDfXZ/kytG21j4cBxaF2gDY5VSy2w1HuaocyTh4o7x7wzH2RPL5XvwN/N/K/4WFF07xlc1stm2xsMa0aW1o6gFfgHu3mnUzg9EE6/Z2pYYyeMqPAX8ILvmGWY+04S9YfS28nJjNr+KvpSDHT3GeCUf7QnMgkGcCRNsr2X8CAx1w/1ehxQyDIDoIT3zffOyFlXGHIzN178WoGTrTUJoLjFI58rzlVjjvS2D7zYS/1s3je9wRDETizLf2YlsOTl65qq0yLIUjETkqRGLmnVSz5si01eVWH8MDn1jNnz5wOlWFIQDabHdR8yRXjnrdFwPz/Wa9wC6nim2tZiiE2upkPLzKUX8kTltvBICy/OBUXpK4FteYiZibmrpp6RlMTqgEeHpbe6py5PHWIB17hQkEgXyilUu5JvJZeqx88gI+St22us5BB+rcvdp2P3vwi9n1NLRuGfvFP/F9ePQb8POLzN5EG+6AgXYomgVnfNScs2cMj5uu7VUAtjimfW2WG44y1hxBZjgKFpp1WGd+HCoWmmPeKPTDNBCNs8Ayb4xZQwOZiEvhSESmnUc272f93q4xn/+PV1s57kt/5+ePbzOVI7etjrJ5BP02tm1RWWTCUZPj9u1PcuWoPxIHoMI2E+uanVLzTjIwv1LjZGXsvDVHsYTDvi5TfVQ4mh4Wu5Wjjft6eHRz5uCEp7e1Q3Ejg5YJCM2U4aSPXl90MXxyM7veeDftFFEQ9GPbVrKtrqM/ArPM9Dp2PzP6hex6Gn56AfxoNbRsGNvFb33Q/DnQAb+4DB663nx+wjug4RTz8Z7nxt7SF4+ZyXzAXqeCwpA/GfQOqByVzgXbPE/qTzRDGsAEM4Cu7Py87o/EWWDvNp9o420ZgcKRiEwrzd2DvOPnT/OOnz2DM8Y+8y/+eT2ReIKv3PEy0b4Oyi0TQCidmzynssCEo1fddzDZ92JWF/oeTF/EvBjwNh/sIyf58MfXF0/adciRLy+t0riz3Xw/Vbjf3zK1kuGoqYdHXjHrWs5aaFq3ntneThyL7T4z0vrVeA3b2/oz7yBUQG/U/GAozDEh2Gur6xyIQr072XK0Co7jwD2fBxwzSvy2t6TGhI9ksMsEH4CqpSYgtb9qWv1OuNYc8+dCuBvaxliN6tkHToK45aeVIopyA8nndMCaI58/NbGu/uTU8WK3nS9Lb2YNROIsdCtHWm8kI1E4EpEpE40n+O0zu/jxI1uTQWhP5wCOA629YXYMfeEwgiL3Fy5AWdj84kvkV0EoVZGpKsoBYE10rulj79mbtVaNsegLm3CUZ5k1CH1OTvI2bz2UyFj4fTYhv/n13dprvp9UOZoevLa6PZ0D3L/BDF9539nzKAj56RmMsbGpm40Js/5mq1PL8zs7DrgPrwW3wP25lmyr649C/SpzUvN6s1dbpA+2P26m3Hk2/AV2PWXWJxU3Qsd2+OXl0Nc28oVvfxycOJTNh/c+BOd90YweX/VuM9HN54e6FebcsbbWdZkKze54GQ42ly2voyjHBL0DKkdgBlOEiuG4K1PHir3K0e6xPeZBDETjHGOpciSjUzgSkSmxt3OAC7/1COE/f5TT77uCVze9CJiBCp6X9oyttS79XfPTbTMdyao+LuMcr3K0q8+CmuPNwZ1PHfS+d7X30xse5hf5OPWFTVtdHoPmc0w4qi4KJYObyFgVhPwZn5crHE0LxXkBaovN/8+94RgLqgo4dW45KxtLAHhhVxc/CZ/HPfET+VX8tTy/s/OA++j2wpH7b1ziVY76IyaoFNaZaXe3vQX+Zwnccgnc/VnzxbEI3Pdl8/FpH4Krf2cm4TW9BP/7+swQlc6bSDfvbDMg4sxPwKe3w8VfS51Td4L5c98LY/q7iHSYN5/2Uc5nL17Mpy9alKocDV1zBHDWJ+GzO6EqraJTbIJktsLRYH9vcmLoAUMgRFwKRyIyJX722Db27m/nrb4HWGrvYNaf3wTtW+noT/3SXDfGcJT+rvklPhN4rKWXZ5xT5a452t8ThsbTzMGdT4x6vzvb+jnzhge54qbHx3Qdo+l32+rynFRbHcCyWSWHfd8y8+SFUq11hTl+ytVWN214rXUA/3L+AmzbYk65WVv00p4u1sUbeW/0E2x0GnluuMpR2KscmVDkbUPQ6f1snHOG+XPbI6nR12tugc5dsObnZhPV/Eo4/SNQtRj+6S4z5KDpJdi7dviL3vaw+XPe6szjlpX62Gt7a9960L8DgD3bzUS9dl8l7z1rHpZlJZ9LTzjG3s6Bg99JUXYrR1b7q/gshx6rEAq0abIMT+FIREb1lxf2csVNj7NnLL/IxuGlPV0stXbgt8zi3tyBJrjrXzMqRy/uHls4iiVMS16j1czx9jbi2LDksoxzKt1pdT2DMSKz3NaUXaNXjp7ebvr0t7T00ua2Lx2qPncgQ8gLR45ZlK31RnIo8oOpytGZCyrw2dYoZ8tkWlxrWusWVBVwyXFmb6KGMvP/u9dGF/CZf6+NTT10pVVRHMehx12PUxga0lbnnXfR9XDZt83477f/GeacCYko3PUpeNit9JzzbxByQ1rlQpj9GvPx7qcPvODufbB/I2CZ+xpJmbuGs33bmP4eWveaEBUqn43lhqzyghAnzykD4N/vePngd5K+5igLa0QTzeYxm0NzMoOfSBqFIxEZ1Udue561uzr5tz++lLX7TCQc1u/t5njb/PLc7bjjtXc/TUefCSE+4sT3Pk8iHj/o/Q1GzTmX2ibsrAsuh/yKjHMKQ/7kZqv7Cpebg83rzULkEaT/6vzHq6P0649Bv/tucE7CrKNKVo4UjuQQ5Ke11a1eqHfAp5NrT53N646v5X/etBzbDa0NpWbz003NZljM3Ip8FlQVEE84fPNes4dPa2+Y065/gK+4oWHYtjowP9tO/Cc4+T2m0rP6M+b45r9BfxtULIKVb8+8qAZ3yMGuYcKRVzWqXQ55ZSM/MW/ATcd2SBz853K0fScAlfXzMo7/+xXH4rMt7l7fxAMbm0e/kyJ3gE5s0Dy3w2S3mb/rnsL5h31fcvRSOBKRMdnS0pu1+9re1kdvOMZKnwlHt8dPJ44PBrtIuO0T/+S7m9/yGToe+t5B728waqpPF/jMQuEXilYfcI5lWRxbZ4LI481+9xe9A1vuG/F+O9wXI9W0k3jqxxA79OqRVzkKxE3lKOrLw2dbHK9hDHIIwrHUi1NvGppMD3UluXzvbSdwfH1J8li9G4684kdlYYgvX242hP3FE9t5YVcnv3t2N03dg8mv8QJwSW7aQIbhzDkDVlxjfqad8j649k9mgEI6LxwNNwJ86wgtdUMV15tx24noQafH7ekcoChi1vbMn585+GBxTRHXnWGC1tf/vnn0qaT+EBRUm4+z0FpX0G0m7UXLFx72fcnRS+FIRMZkf8/htZWl8wYtnBjYDsCziYXs9JmFt4WdZnf2k+1N5uSX/3zQ+/MqR3WW2Veko3jpsOeds8i8iHxwUwv7Gi8FwLn/P0YMPd6LkU/6f8vr994Ij33zoNcykv5IDD8x/I4JXF990yncfM2JWisih2TdntTmojXFGugx3XltdZ7KghCnH1PBlStn4Tjw2T++xO/WZE7P9FrvSvJN5WggGk/+rDvAFTfBv6w1AxS8CW/p6k4AyzahJn3PIMdJG8awevQnYfug1IwhP1hr3T+2tFJrmUpPfuXsA27/wOr55Ad9bNjXzQMbW0Z/XG/dURbGeVcMbAcgUKMx3jIyhSMRGZNIfIwb/43Buj1dFNJPfdy8E/hiYj4b3PG25b2m7eEYn9k8sKR9LYR7Rr0/7wVDHibkhAqGr8asXmTajx7f0sr5T62kxSnB6tgKT9087Ple5cjbNDD23K/GvgHiEH3heHJSHcCZS+fw2qXVh3RfIssbSgBYNad0ai9ExqQ4N5BcQwSpNZCfu3QJJXkBXt7Xzdb9feQGfPzHFcextLaIy1eYlrLCkD+5pqxruClvQ3T2R1izY8i+RqECqDaVqox1R62vmG0NfCFoPPXgTyTZWjd6ONrf3pnab85bN5SmJC/INaea0PS9B7eMXj3yvv5wK0exMLWJvQAUNS47vPuSo5rCkRyyLS29PLJ5/1RfhkyisW7KCmYE9rU/fYpHXznwe2Tdnm6Os80v10RRA+0UsTZifgHWhl/FJkEjJhz5nDjs+MeojzUYiwMO+W74yMsvGfa8pbVFVBaG6I/E6SOXG2JvNjc88f1hz/cqR97oV3/3Ltg5+rWMpD8So8ALR74g+DV6WQ7djW9aznvOnMvN15w41ZciY2BZFrNKU9UjLxyVF4T4t4tTVYyLl9Vwzamzuetfzky2AadPeRuxtS7Nv/7+Ra76wRPcva4p84aGU8yfu9Ja67z1Ro2nQCCzujWsMQ5lSLjVqbCdBznDv1l13ZlzCfptnt/ZySstvazZ0c6X/7I+OZAiKUvhqHfvRvwk6HbyqKmbc1j3JUc3hSM5ZBd96xHe/rOneWb7QXbeliNa+n4q7WmT5A7mnpebefSVVm57emfyWDzhcN/Lzby0p4sLbLM+yK4/gcKQnw2OeRdxTnQbdVYrAdL2FvJ64kcwEImTSxjbMuEtv6hk2PNs22J12vqMu+Pu1LrepmEHM3T0RyignzIrbb3V2ttGvZaR9Ibj5FluOArmH9J9iHjmVxbwuUuXqi3zCNJQlpf82AtHAP/vpPrkxMG3nzZn2K+tKDBvpuzuGH1j7IFInIfcNy1/nfazF4DaFebPlrQpcdsfAyA2+8xhW/b+vHYPb/7hE+zrcqeVlrnDFQ5SObJ7TDjqz6kecSpcVWEOi6rNRL2dbf184++bueUf2/nZY9szT8xSOOrcYYYKbbUayHfHpIsMR+FIDpk3PvmPz2Vn/wGZnmJpbWQ720f/xZzOa/9I3wn963/fxLt/+SzHRl7iHf57zMEV11BXksuGhAlHDc4+jrW2Z96Z1xM/gsFoIlmVSTgWxYUjDzm4ZFlt8uNe8ujxuW1J7dv4n3s28a+/f4Go20LY0R+lwdqfvF/ArIEaw6SmofojsWRli2Dh6CeLyFHHm1gHmRtXW5bFT9+xin985lxWuO2SQ3nHn942+puRT25rIxIzP78ee2U/TV2pVt7k5LfetAlxe58H4JNPhnjtNx/OeANsc3MPn/r9izy1rZ0/Pe+u9/Ha6g6y11Fuzw4Awvm1o55XV2LWy+3tGkj+fvn9c7tIJNK6FEq8dU5j219pJJF9aWO8RUahcCSHbe2use1FI0eeRMJJToIro5t9LWNvo/RaI9LD0cv7urFJ8L38n2DjwMprYeEFzCrNpZVi+oPl2JbDRT7T9vFUwt3BvGU99I/8oiAcS1Vl+sihtnTk9pBzFlfxu/edxlevOA6Avbb55R3Zv4XvPrCF3z67Ozlat7M/kmypW+9Wtoj0wEDnmP8ePH3hOPmqHInMWPXDtNV5gn6b6qKRB2ucOq8cgCe3tdPWG+aPz+3mhV2dyTdyPOmt7gmHVKgBKHSDSo/bbtffDp0mxDzQWcuu9gG+csd6AKLxBB//7dpk0HrR+z2fbKvbPvK+Q47D2d1/AaCvatWIzwnMZD8wlSNvUt+u9oHkHnMAVLrT7lpfOeQ1nwB2qxny01M47yBnykyncCSHJP1dnQ37uoknxr4WRY4cYfcXYx6DPBT6GK+96yxY84sxbcbX64Yib7d3gI6+CHVWK5WxfWbdzUXXAzDL/QW5LXAMABfbZsHwc4kF9FpulaWvdcTHGojEk5Ujf04BS91NGEeyak4Z8ytNQNnm1Jj7aHolefvDjz5E613/xdsGfs0cq8k9r5YBu8CccAj7bWRUjkIF4/56ETmyZbTVjbMd8hQ3HK3b08V7/3cNH//tC7z+pse54qbH6Y/EGIzG6eiLJMPR2W778Dfv28xbf/Qkr+7vhULzs46BdjOh060atYXq6cb8PPzz2r3c+3Iz977czLo93clBEC/u7jRfWzIbsMybRHd/xlTS92/OvNhNf2NefBu9Tg49y9856vPyfvav2dmR8Trix49sZVtrn/mkdA7Yfoj2meERhyg/OcZ78SHfh8wMCkdySLwXzZ4N+7pHOFOOZANuD3qt1UaRNUAgMQB3fARuewv0jR4QvIpRb1rlqL0vQhWd5pPCmuQO7t5C5dtjZhf3HMtUnbY6tQxY7rupo0ysG4wlyMf0xOcWFCd3Yx+N9y7tK1HzIiLW+ioAZ9kv8NfAp6l4+mt82P497/L/DYCdThU9thu6Bsa3zi6RcOiPxNPa6lQ5EplpvHHeftuiNG98A1lmleTSUJZLPOGwZkcHftsiP+hj/d5u/u2PL3HRtx5h5Vfv5dX9ffhsi+uvXMa8ynwisQRPbG3jZ49tg9xSM5UOTGudG45eiJtq0LF15ufbjx/Zyv0bTMX8TSc1YFmwt2vQbOcQyIG5Z5n7eOpm+O3b4aZVsO0RcywRh4e/BsAv4xdQVDr6Hlxe5eil3aYyFfSZl6X3b2zhnG88xJ+e3w2+AJS5m7bu3zSuv7ek6CBlg2YNlsZ4y8EoHMkhGRiycPPJrYe/c7VMP96/c6EbPAASvhBsvpvED06Dl34/YhWpJ2wCTnrlqLM/QpXVaT4pTPWie+0mv+xaTpeTend1W6KGXtzPI8OHo2g8QTzhpA07GFtVpspta9nshiPbXWB8ir0BgDgmYFW717vTqaLbq2KNs3Lk/T3mj/MaReTosbCqkCtXzuJD5x6DbR/8DZyhTp1bnvz4TasauOnqEwC4fe1etrel1oOePKeMupJc7vvY2XztKjOyes2ODjMYodDdPqCnKRmO/jHQiN+2+NabV2BZ8PT2du5Zbyrmly2v5ZhK8/MqWT265o/wtt/C8rdCuan28+iN5s8nboJ9a+l1cvhp7GLK8kcPgV448tYwr5pbyucvXcK8CvMG0nM73MesdDdtbd089C4OtOU+6BwyjKJ1Ez4SdDgFlNUcuO+SSDqFIzkkQ8PRUwdZJCpHpoGICTaFlvnF+3JiNq/r/xKvJmqxe5vhD9fB/V8Z9mu9ylFpZC+JTfcwGI3TF4lTbXWYEwpSe/ysbDRDEcIE+VP8jOTxbU4tvbh9+iNUjrzvxeSY7DEGj4KQn7ygj+1uW13IXUB8fI55x/Sv8cw9P3Y5VXTghaPxfb/3uX+PBdbAuK5RRI4etm1x45tX8NHzFx7S13vrjgI+iw+sns/qRVX8vxPNJLdF1YXc+eEz+M5bV3Ljm5cnH+/cxebn7KbmHjMkp8Btretpgr1rAXgpMY+T5pSyoLqQVXPKzM3hGIUhP6vmlHF8fQkAL7jVHXx+WHghvOFmE5QsH2x9EJ75KTzwVQC+GruWDquYooNMhfMGMngaSvN495nzuPY0E2CSAyIqxhiOdj8Lv7oKbntrxmGnaR0AGxON1Jepci+jUziSQzJ05OeucUwxkyPHQMQdxuAzm6v2kMuu0DFcGr2eW2IXmJPcUbBDee103w18B/u2/0fvtjUAVNud5gSv/x3TMuKtAfpN/FwS2ETza2mjiB5n9HA0OLQqM8b1PJZlUVUYYodjNobNC+8nj0EW+vYB8If4Wex3UlPvdjlVtDvufY+zra4/bK6xxOfu36G2OhEZp4uOq+G1S6v5wuuWUu9OvvuvK5fx839axR8+8BqOm1XM5cvrqC3OHPwwpzwPx4Hndnakfu42vQjdu0lgsd6ZzdkLzc/By5bXJb/2rIWVBHw2yxvMz8Fk5Shd6Ww49grz8V8/DvEIPbPP5//iqynJCx60QlaRH0q20kGqi8CrOKXCkTuUYej6pqH2rTV/Nq+Dlo3Jw327XgBgE43MKdfPXxmdwpEckoFIZjgaz/43cuTwqjKz8k3QWTy7jrVfvICashL+EjfrgzLGwqbpHoxhkWCJtQuA8J4XAaj3u+vT0ipHYH4RA2x0GrllwXfZd9mtgEW3M/qao7A7Ta/EDXDjCR5VRTl0U0AkWALAfGsvFREz3emVxCzujZu2Fcf2s88poy3u3vc42+q8ylGxTwMZROTQ5If8/PjtJ2XshRTw2ZyzuCpjP7qhTnKrQc9ub0+Fo013A7CDOnrJ4+S55pxLjqtJDmE4d7EJTMtmmXDkrQs6wGs+YqpHWLD8rWw45euARWnewfcSsm2L2rTq0awh4aij3wtHC8yfrQdZc9T2aurjDX9JfhjZY/Y4ass/hqBfL31ldPoOkQNsbOrmjK89wG+f2TXiOeGYedHsvePT2R/FGcMEMzmyeOGoxDYv6ouLy/DZFkW5AVooMSf1tgy77qhnMEoVnYTc4QoJ95dWra/TnJC25ghS4Qigq+pkArVLAehOeOFo+KEf3jUWJ8PR2IOHt+6oM6cBgDPtl/A5McJWDvso4++JkwGIlcwjjo/mmDetbpxtdW7lqMiOjPsaRUQOx0mzTdvys9vTKkfNJiw8H59L0Gdz3CwzjKG8IMQHVs/nNfPLufA4c+4Cd6PWtr5IxhrSpLoV8N4H4UPPwhtupjWeGXAOpi6t0uVVxLyBFW1D2+r69o/+87dtS+rjl/+c/DCn3VSR4lXHjumaZGZTOJIDPPZKK7s7Bvjj8yNv7uq1W3nv+ETiCfqGVJPkyOdVCIu9tTLudLnCHD/7nRJzLDYIg5nvKEZiCcKxBLOtVFXJ7jQDDyqT0+oyK0fpi407+yPkBnxAejjqHfYavba6QjuccY1j4U2sawmYVpIL3f2VOnIbcbB5OHE8/1f3GcKXfg+A1oRXOTrENUf2+AOciMjh8CpHa3d1EsvL/Ln7UmIux80qIuT3JY994oJF/Po9pyarUQUhP4U55uOmrgGGVbscKsxwBq+TpGSME/m8oQyQaqsrL3ArR30R88ZrqACKzPoqfvAaeOybw99ZeuWoeZ35vLeFvGg7CceisH7ZmK5JZjaFIzlA14B5p39768jriJIVhbwgIbdE3aHWuqNOMnh44SjHvLtYGAoQJkjE7waR3paMr/M2gJ1tp8JRTrcZeFCecINFQU3G1+QGfcwuN+8anr2oktyg+WV9sIEM3ia1RdYhtNW5laOX/ebdxOW22YE9XOyOjcXi1foryJljNjJsd9zne4hrjgq1CayITLL5lfnkBGzCsQTtdlnGbS8m5nGCOxBnNLXF5o2kfV2DBz3Xey1QNsZwNMt9kzXgs6gqNB97laNYwqHHq1Ytvdz82bMPHv66GRueLh6Fju3mY69C9PDXTEjC7Gk3b9boo8VFQOFIhuGFo6buQfqGK6GTetGcG7Dd0rlDd/vwa0/kyNXvVo4KhqkcAfQFzC/aj/7076kN+0iN7260UqGpoG8nAWIUJtwqU2FmOAL48wdP59fvPoVzFlUR9NnYFgcdyJAck22Pf0y2Vzn6u3U6g06qP95XtSj5cUleAL/PJjfgo5ND2wTWqxzlaRNYEZlklmVRnGt+vnX5K5LH49i87MzmxNkHD0c1buvbmMJRv3kNUTrWtjq3clRbnJtc75QT8JHnvkHW3uu+8XrR9fCJzRDINxvCtr6SeUcdO8CJQyAPLvs2WDa8+H8493wBgI1OA4trxt5ZIDPXuMPRI488wmWXXUZdXR2WZXH77bcfcM6GDRu4/PLLKS4uJj8/n1WrVrFzZ2rm/ODgIB/84AcpLy+noKCAq666iubmzBfWO3fu5NJLLyUvL4+qqio+9alPEYsN/0JdsssLRwDb2/qGPWcgGY58lOb6+UHgWxz7qxWwe81kXKJMktSYbC8cuZUjdzxrt9+0wgV7dtB702r43slw17/S32l2aU9vqwvFe1lgua2ath9yM9/BBFOJfM0xFViWhWVZ5AX9qX2ODjKtruAQNlitKjKVo/XtFnclTkkeL2pI9aV772AW5PhTlaNxttX1h71wpFHeIjL5vHDUbqeC0JbELAbI4YQxhKNa942kpjGFI7dylH/wgQwAJ8wuxWdbyaEQnuTEuv60rpTCaqg93nzsTabzeOuNyudDwyo47YMAWM3riDk2t3MODaV5iBzMuMNRX18fy5cv56abbhr29ldffZUzzjiDxYsX89BDD/Hiiy/yhS98gZyc1DSSj33sY9xxxx387ne/4+GHH2bv3r1ceeWVydvj8TiXXnopkUiEf/zjH/ziF7/glltu4Ytf/OIhPEUZr/RwlF4NSBd2X5DmBHxc7dzBxe5aDXYMP9ZZjkzJMdmO+33gVo6Kck3lqNNnfqlebD/NMmezmST09A+puf8jgEOjlfmmxyrbnTRUUAP2wX/85AR89B1kWl0yHA2pbo2F94uyqXuQ38XPTh4vrF9Kodtv701cKgz56Uhvq0skxvw43nq8XEebwIrI5EuGo3g++EzoeDExl1kluckK+mi89cX7RlpzlGa8a44WVhfy7OfO54arjs84npxYN7Rlv3aF+dPdxDb1wO56ozK3Lfqcz8GiS2ipPYeLI/9Nc/VZh7T5rsw8I89+HMHFF1/MxRdfPOLtn/vc57jkkku44YYbksfmz5+f/Lirq4uf/vSn/PrXv+bcc88F4Oc//zlLlizhySef5NRTT+Wee+7h5Zdf5r777qO6upoVK1bw1a9+lU9/+tN8+ctfJhgc2/9wcmgyKkcjhCOvotDg7OMtXT9L3TDOdiOZ3ryBDHmOu/5sSOWo3TLh6GTbTALaFZxPfXw3pXsf5ip7CbPdtroBfzG5sS5OtjeY+xkyjGEkuUGb3n63rS4yejg6lODRUJbHMVUFbGnp5cnEEp7yreSUuhBW5SJOmtPPg5v2Jyc1FeT42e211TkJCHdB7sHfcQXod9vqcry/R605EpFJ5G3G2jUYM29Ode3kJWcuZxxTcZCvNMaz5qizf3xrjmD4FrwDJtZ56laaP4eGo2TlyAyGIJALb72N39z/Cq9s28wbq9VSJ2OT1TVHiUSCv/71ryxcuJALL7yQqqoqTjnllIzWuzVr1hCNRjn//POTxxYvXkxjYyNPPPEEAE888QTLli2jujr1AurCCy+ku7ub9evXD/vY4XCY7u7ujP/k0KSHo60jhCNvEfzs6Kv4SFsU2aN1R0cTLwTnJLxwlLnmaE/M7H+R7w5D+FP/Mp6Z/V4AvhT4BaWWmTC3regkAFbZ7gZ+BQeuNxpOXsA/hk1gzfdibrJlbXzB48Jjzc8ZB5uvV/wXXPd38AX4/tUn8ui/nsP8ShOICkJ+IgSI+d22jHG01nmjvEOJ8Ve3REQOV3LN0UAU5pxOhACPJI7nzIVjC0femqOxtNV5bXBjXXM0kvKRKkd1K8yfTS9B3F1u0b6V9o2mcyVSMi/j9N0d5vdXY5la6mRsshqOWlpa6O3t5b//+7+56KKLuOeee3jDG97AlVdeycMPPwxAU1MTwWCQkpKSjK+trq6mqakpeU56MPJu924bzvXXX09xcXHyv4aGhmw+tRmlewxtdQNDp5h5evZN2HXJ5PMGMuQkhrTVueFoS3/mL5stiXretuFktocWUeR+b+x3itgZNO/kVVmd5sQxVo5ygr4xTKtzr9E5tGEHFx6bCmoVBaHkx7lBHw1pv0y9sbaDgRJzYBzhyFSOHALxQwtwIiKHoygtHDWfeyMrB29mB7WcPn9s4ahujJWjRMJJDlAYyyawoykdbs0RmMpQsACi/XD7++Dby+E7KynrNW++vRSdlXG6d83pI8NFRpP1yhHA61//ej72sY+xYsUKPvOZz/C6172Om2++OZsPdYDPfvazdHV1Jf/btWvkDUxlZI7jJCtH+QwQ3r912PO8ditvof5+x7Rb0avK0dHECx6hmBeOzL+z16Lx6kDmi/y6BSuIOT7+ueddRBwzaWinU81eO3PD16EbwI4kL+Cj7yDh6IDq1jjX8yybVZz8xV9ZGBrxvAI3EA74i90HHl/lKIcINu46JYUjEZlE6ZWjR7e000cux88qHnN1p8b9Gdk1EKWrP8pLu7u47+XmZAsdQCye4JO/f4G+SJycgD2mtUyjSQ5k6B0Sjmwf1Ljrk176HXRsx7F8PJI4ng9EPsJma27G6Xs7zesU7+e8yMFkNRxVVFTg9/tZunRpxvElS5Ykp9XV1NQQiUTo7OzMOKe5uZmamprkOUOn13mfe+cMFQqFKCoqyvhPxm8gGicadwD4VuAm7nI+RM+GBw84LxzzFuqbF6RbHbOJpipHR5eBSByLBIF4ZuXIW3PU4m0EC2DZHLPU9IJvSjTwrdgbAVibOIanE4tpTj931oljevzcoC/VVhcbNPtYDOG11SVb1sYZjizL4oqV5p3GpXUj/9zwBjT0+dxzxrG+ri8SI5+0d1wDCkciMnm8ylH3YIxHXzHTRM9cMPY9fwpzAsnq+anX389l33uMd//yWT75uxcA88bq5/60jj8+twefbXHDG5eTHxr3svYMyYEMQytHAMe5Q7zmng1vuY22D27m7ZHPcFfiVPZ0pn7WOo6TrBzVqnIkY3R437lDBINBVq1axaZNmzKOb968mdmzZwNw4oknEggEuP/++7nqqqsA2LRpEzt37uS0004D4LTTTuM///M/aWlpoaqqCoB7772XoqKiA4KXZJdXNfLbFq/1PQdA6M4PwJINGed5lSNvncfWRC2n2BthsAuiA2YhpBzxBqJx8ghjYQJzchNYt4qyPz3wlM5lfm158tPvxy9nZ+mp3NdaQmV3iNPC36PO7uTRT52JVTpnTI+fG/TRR9q7feEeyMsc9zoYjRMkis9xe88PYQ+hj792IectqWJ5fcmI53iVo27LrRyNp60uHCff2wA2kD+mSX0iItmSXjny1uAMHZ19MDXFOWxp6WUgGifot4nEEjy4aT8dfRF+v2Y3//fsLmwLbnrbCVx03NjWlY7GG8jQPtwG86veDSe8Hfym2t+0pyt5057OVLt/10A02R5eq8qRjNG4w1Fvby9btmxJfr5t2zbWrl1LWVkZjY2NfOpTn+LNb34zZ511Fueccw533303d9xxBw899BAAxcXFXHfddXz84x+nrKyMoqIiPvzhD3Paaadx6qmnAnDBBRewdOlSrr32Wm644Qaampr4/Oc/zwc/+EFCoZHbXuTweeGoJMdHsgOob6/ZbK1iQfK85CJ4t5Vpr1POIEFyiJjWujG++JXpbSAaT+1xZPvBb365eOGogwKijo+AFYfKxcnJboZFX/lxDLbuZ1f7AGATzq8dczACs49WDD9RO4dAYnDEcJRP2tq3Q6jK+H02J84e/YVCQch9cWF5ex2NvXLUH02rHKmlTkQmWXo4auk2A3RmlY7vTcxaNxwBvP/s+dzzcjMb9nVz472b+dVTOwD4/KVLsxKMIK2tbrhwZFnJYATQ0pOqFu3pSP0+2OtWkcrzg+QEfFm5Ljn6jfvty2effZaVK1eycqVpn/n4xz/OypUrk3sQveENb+Dmm2/mhhtuYNmyZfzkJz/hD3/4A2eccUbyPr75zW/yute9jquuuoqzzjqLmpoa/vjHPyZv9/l83Hnnnfh8Pk477TSuueYa3v72t/Pv//7vh/t85SC63J2tG3KHLLp8InNfq6HrPHrIS1UReoYfmiFHnsFonEIrbVKdZfaI8NrqHGxacSsplYsoCPkz+rqHtjGUj3N6kbdDesQ38kawg9F4cloe/lzwZbUgnuRVjpJ7HY1jfd1AJE4u7jUqHInIJPOG6OztHKDX3ZS6Zpxrgvb3hJMf/9Nr5nCJG4L+98kdOA5ctryOd54+JzsXTGoT2WHD0RBe4IPMypG3L5O3T5PIWIz7VcTq1atxHGfUc971rnfxrne9a8Tbc3JyuOmmm0bcSBZg9uzZ3HXXXeO9PDlMXuWoMdgDaYPqnA1/IXHJjfh8Jk974SjkrkXpJZdmp4QGq0Xh6CjSH4lTyIHjp4N+m5yAzWA0QbNTQq3VDpWLATimupC93nSgIW0My2YVj+vxc913+sJ2Hvm0jxCOEqnK0QQGj4KQuZYttrvYd+cTY/7awWiCGi/ABTROVkQmV7E7Oc4LOIUh/7jXBF172mw+96d1/NNr5lCaH+TiZbX8z71mQlxuwMe/XbIYy8reJqtl+aYy1D0YIxpPEPCN/H5+c1o42tc1kDzfG8ZQW6xWfxk7Nb5LBi8c1QXc/WmcGsJOAKu/jYu/dAtrdnQAEHbDUdANR4NWXmrBvSbWHTUGInEKvHHtocxg41WPvhd7A6/WXAKLLwVgYVVqzU/NkF9IJ8we26apnly3cjRgj1w5GojGUy1rh7DeaKy8trpnWAqWD9q3QufYpmJ6a7cArccTkUnntdV5qorGv0ThLasauesjZ/Kly8za72OqCljktlK/7+z5WQ8gxbkBr1mBtqET64ZoTmurSzip/Zi8N+pmaRiDjIPCkWTwwlGNbRY39oRqeMkx75Qfl9jE3evMNDqvchRwRzxbOYW0OO4LX02sO+LEEw5v+/GTvPVHTxKNJ5LHB6NxCsncANbjrTu6L3Ei6079RjKYLKhOBZShC2BXNpaM67q8ytGA5YajyEhtdd56nonbXNWb1NQSCcKsE8zBbQ+P6WtNW537yz2oypGITC5v+wVPzSEMJ/DZFkvrijKqQ9988wo+f+kS3r96/mFf43CP54Wvhza1jHpuelsdpFrr9iUrR2qrk7FTOJIM3gawVW448hdV81zCDGI4wX4l+UPRG8jgj5kKk51TlBaOVDk60mxr7eMfr7bxxNY27nhhb/L4QDS9cpQZPNJ/2XpThYCMoQxDfwEvqBpfePEqR33WKGuOYolJGXbghcHecAzmrTYHtz500K9LJBwGonFy1FYnIlMkL+jDb6dCzeHuQeRZWlfEu8+cR9A/MS8nL1tutgn589q9o57nDWTwnqI3lMEbyKAx3jIeCkeSwasclTudABRWzGJNMhxtSW745lWOfFETjoL5xck9bxLdqhwdaTY1mdCRxyCtf/86ic49OI55UT/cmiNIhQVITRUC02rhvbFYlhaaGspy8dnj60f3KkejbQQ7GJmstjo3HA3GzN4aANsegYOswQzHzBsJaqsTkaliWVZGa914hzFMlcvdcPTktrZkq9xwmrvNbQvdN+e8ytHeLm0AK+OncCR09keSm7p64ag0YdYW1dfP4cxzLgFgkbWTgV5TURqMxAEnGY4uPWkhrZapHDXt2T6JVy/ZsKmpG4DrfHfx3vAt9PziTYQjURyH1Cjv0SpHaeGoKCfAF1+3lE9duCjj+MJxVo0gVTnqdUYJR7E4+dYkDGRww2BfJM4Ptpbj+HOht5mn/vgdtjR1wmD3sF/nvZGQbKvTBrAiMgXSw1G2KkcTraEsj5Nml+I4cNODW+gYZnJdPOHQ6q5J8ta17ukYIJFwkqGpTpUjGQeFoxmusz/C6f/9ANf+5GkgFY4K4yYcWQVVXPPaU+jPq8NnOVR2rwPMC9IQUayEGQm6etk83n2x2cQ3L7x/sp+GHKZNzSZ0nBNYD0Bxxzriz/4CIDXK290A1pNeOSrNy+xnf+fpc/ngOcdkHDt/afW4r8sb5d3tuL/IRxjlnapuFR1we7aU5wc5dZ7ZC+lr927jF4550+CkF79E+c3LcG6YC9sfO+DrvHCU7/PCkX5Ji8jkKzwCwxHAlSfUA2Zk+Olfe4Ct+3szbm/rCxNPONgWrHA38n5+Vwef/sOLROMOOQGbqkLtkSljp3A0w+1s76cvEueF3Z04jpMMR/lRd4PLgioAeqtWAXBC78PE4gmicSdVUQAIFrDgGLMgs8TqhXh08p6EHLZNTT3kEOZ4Xkkey33kPyikn2Lba1kbUjlyf9GG/Hay/W04t73nVD514SLefFLDuK/L27SvOzFyOBqIxCmz3ON55eN+jLGyLItfv/tUvvnm5cwqyeXLfVfym9hqfJZDKd1YiRiJh28Y9voAimyFIxGZOhltdUdQm9lbT27gi69bSlVhiP5InKe2tWfc7g1jqCgIsbTOvEG2ubmX363ZjW3Bly87Fv8oY8BFhtJ3ywznvXALxxL0R+LJcBQKDwlHx10NwPmRBxjsNlNjkgv1g4Vg2/jyyok55lvK6R19soxMH/2RGDva+znBfgU/MfY5Zey3K7HDnRxnb6PIHr4qU+iuwSnLD466t8Vp88v54DnHYI9zvRFAXtA8Rmd8tLa6BKWTEI4AbNviDSvruf8TZ/P5S5fy6in/wc7V3+Ff+Shxx8Le9jA0r8+8PrdyVGC7bxhoE1gRmQJH4pojMG9MveuMubzueLP+aEtLZuXIa52rLsrhuFnF/Prdp3DRsTU0luXxw2tP4i0nN076NcuRbWK2kpcjRr/7wg3MLtRdAzF8xAkMuu/MFJhWqOC8M3ghMY/l9lZ6n/4JsJLC5BQzswg+4PfRRhHVdBLvacFfPGsyn4ocoleae3EcODdnEzjwj8RSGn3dVLKfWtoos/rAAXKG7nNkfnykT6rLNq8i1e6Fo/62jNsTCYdILEFZYHLCkScn4OPdZ85zP1tGsPMl7l7zDy71PQ1Pfh9en9rgOtlWZ0cggSpHIjIlityf2bYFFQUT93N7ohzj7qGXHo5i8QT3bzRvxnqtc685poLXHFMx+RcoRw1Vjma4wUgqHLX1RegeiFJGDxYOWHbyxWZJfogfx8wmnzlrf45FgjJvDYXbbuWzLVod8wI6oXHeRwxvUt2ZgQ0APJlYyq6YWdRaa7VTh7uGrDizLa7C/UVUfQibCY6Vt+Zop3s9dGeOc/XCfckkVY5GMq+igJ/HLjKfrL89Y4KdV53N1yhvEZlCXuWooiB0RLaZDQ1HO9r6eNMPn+DXT+0E4JzFVVN2bXJ0UeVohhtIqxztaOsjEk9QaXWaA3kVYJsXp/lBH/dxMnHHwj/QSgXdlPoHTUXBDUcBn50KR70KR0eCNTs6uO2ZneQQ5pjIJgCeSCylwWoBG2ZZrVQ5rebkksxwdP6Saj52/kJeewiDFsbKW3O0I1YMPswGw46DNyu83Z1QVG657yTmlU3YtYxmXmU+LzruJoiRXuhvh3wT1PrdcJRneWuOFI5EZPJ54ehIWm+UzgtHezoHeGBjMx/+9fP0ReIUhvx89YrjeP2Kuim+QjlaKBzNcP1plaOX95pRxI0h94VmQepdGMuyKMjLY3+0hBo6qLHaKfUNQoxkOPLbFq2YcOT0aM3RdLettY833vwPHAdOsHbgI45TUENztJp9jnlhf7y9lQAxsHxQmPmLJyfg41/OXzCh1+hVjpocN/RE+2GwE3JNJam1z1RjJmMgw2jmVxYQIcB+p5hKqwu6dyfD0WBylLf2ORKRqTOr1PzsmVtxZK57LMsPUpYfpL0vwqd+9yJ9kTgnzynjxjcvp75UbzpJ9hx5dVXJqsG0ytHL+0w4mp/bZw4UZJaoS/ICyRfNdVYbJT73xV7QvJvjsy32u5Uj+jTOe7rb0zGA45g+7e+fYyoxVt0KyvKDyX/nJdYOc3LRLPBN/nspXuUoTJBErhuQ0lrr2nojBIiR701OnKLKUV1JLiG/zR73742u3cnbvOpsDqocicjUufDYGr79lhV87pIlU30ph+yYSvN6o60vgmXBd966UsFIsk7haIZLrxxtcMPRwoBb9RmyxqQkN8Be9x38GqudouSIZzPFzLIsOtzKEZpWN+31R8weVbUludT0bTQH61ZSlh9ir/si32e5a2dKpmbaj8+2ktWjaH6NOZgWjtr7wpTgVo0sH4SKh97FpPDZFnMr8tnruIuA08NRxAtH3psJ+kUuIpMv4LN5/YpZVB1Bk+qGmu+21gGsml12xLYIyvSmcDTDpa858naYnu+YxY1UH5txbklegCb3RXOt1ZYWjlL737TbJQBYqhxNe96/fV7AB3ufNwfrVlKeH0y1sXlKxr9HUbbUu60gvUGztqllz9bkba29kVRLXW4p2FP3I21eZX6y4jZc5SjkuP+/qHIkInJI5lemWgIvW147hVciRzOFoxnOe1f7Qvtpngm9n9fY66iPuC8+q5ZmnFucG0xWjuqstrRR3qlw1GmZtSB2v8LRdOdVDUv9EdhvhjFQa9rqusmj10l7R26KKkcAjWXml2GbbYLHbfc9ybo9XeZYejiaovVGnnkVBcmKW3o4GjwgHGnNkYjIofCGMtgWXHScwpFMDIWjGc4LR18P/JBKq4tfB/+LkvA+c+OQylFpWuWoxmqngMx9jgA63MqRT+Fo2vPC0UJnG+CYgQuF1ZTlBwErVQWBA1osJ1Njmam07E2YYF5NO89uN/twtfWFKWWahKPK/FQ46t6TPO79PxZIaJS3iMjhOGVuOacfU877zp5PZeHEbSMhM5vC0Qzntfz0MeTd7MLaAxa3m4EMqcpRchF8WuWoyza324MdEI9N0FVLNgy4a47mR18xB+pWAlCebzYH3JfeWjeFlaPZ5SZMvNBt/qy12tnUbCYqtvVGKJ3iMd6e+ZXDV47MXkwOgYTa6kREDkdu0Met7z6Vf71o8VRfihzFFI5mOK968EpiVuYNQ1rqAIrzUlPMqukg33Gn2rkDGQD67ELijmU2ke1vnZiLlqzw/u3rI6+aA7XLAShNhqO0SswUrjnyKkfPtJsAv8Lewr+uuwx++3Zae6dP5ai6KCc5kMHp2Zd8c2AwEidE1Pw/AWqrExERmcYUjmY4bz1EgHjmDdUHhqOS3AAtlBB3LAJWnNqYOzUsrXJk+/2044YlTayb1rxwVOi44aLQDDxIVo7wKjEWFNVP9uUlNbqVI6+SVWz1U5rogJf/TGHv1rQ1R1NbOcoL+WiliIjjw3ISZsNaTHU2uccRqHIkIiIyjSkczXDJiWXWYOYNVccecG5JXoA4PlowQxcKwk3mhmBqzVHAZ9Oa3OtI4Wg689bC5CYyK4BlbjhKtogV1oI/OOnX56kvzcWyOHCCHnBh+B5Kp8lAhryADwf7gIl1A9E4eV448gWnZL8oERERGRuFoxnOqx7kMyQcDVs5GmYtCmS8Y5+xEawqR9Nav7c5aTwzHJUXmH/nlxOzzXG33W6qhPw+aotyDlwXB1xhP0oVneaTKQ5Hfp9N0G+n9jpyhzIMROLkWt4wBrXUiYiITGcKRzPc4JDKUbdVCPWrhl1zVJIXAIaEo/qToTK127bftmjVRrBHBG8gQ9CrHOV4lSMzAWidM4/fnPAreMPNU3J96bzWOs9f4qfR7S+jwurmdN96c3CKwxFAXtDHXq8dsWsXYP4fy8HsIUYgf4SvFBERkelA4WiG63dfIBe472zfMOu78O77wBc44NzKwhAFIT9xfKmDl30rY+PNgM+m3XHXIPW3Tdh1y+HzqobBmDvtza0cleQGsC1zKFi/EnJLpuDqMnlDGT4W+wgbKy7g89F38XvOzzwpd2rXHIFprWtxTNspPc3AkLY6VY5ERESmNYWjGS657sR98VZUVDLiuTkBH3/7lzN5zRXvNwfO+dwBeyH5bIsIbrCKR7N+vZI9Jhw5BKJeODKh1rYtSvNMa11t8fR4MT+73FRcNlS8lu2rv0M3+Xyj96LkpsTAlA9kAMgL+ely3OpQuBtwBzJY2uNIRETkSKCVwTPcYDRBgBgBTAVpdm3lqOc3lOVB2evhuD0Zm796Aj6LqPdtlVA4ms4G3BHTtuPuR5WTGsl+zamzeWpbGysbS6bm4oY4dV4ZtgWrF1VxQmMpAZ9FfzyH/4pezfeC3zUn5VdM7UVi2uq6ccPRYBfgrjny2uqCCkciIiLTmcLRDBaLJ4jEExSnDWO46tSFY/viYYIRgN+2iTpu250qR9NafzRGEf3uZ1bGepiPvXaM3weT5MTZZbzwpQsoCPmxLItrTp3Nzx/fzp2JU7msepALj2+AnOKpvkwTjhw3AGWEI7XViYiIHAnUVjeDeWO8k5PqfCH8gcMb2ez3WcRQODoSDETiFFpuOAoVZawdm44KcwJYllkM9eFzF7hHLe6vvBZO/5epu7A0eUE/3XjhqBPHcdRWJyIicgSZ3q+GZEJ5643ybTccBQ9/kpbfVlvdkaI/EqeAAfNJWkvdkaAsP8gNVx1PZWGIt57cONWXk2QqR6m2ukg8QcIh1VancCQiIjKtqa1uBvMqR+V+N8QEh2+VGw+/zyaqytG051U0UpWjwqm9oEPwplUNvGlVw1RfRoa8oI8ebz+mwW4GIwkAtdWJiIgcIVQ5msG8cFTi9xaLZ6dyFPMyt8LRtDUYTeA4pCpHoSOrcjRd5QX9qcpRuJuBiPl/IN9W5UhERORIoHA0g3n73BRnMxylV47UVjdteftbFR3BlaPpyEyrcwOQk2Cw34zzLvRpWp2IiMiRQOFoBhv0wpEve+EoYFtEHVWOpjsvGJd6682OsDVH01Ve0EeYIFHLDDaJ9LYDUGCpciQiInIkUDiawbwXyEVZDEc+O21aXSJ22PcnE8NrqSz1u+FIbXVZkRc0bwwM2Ob/pVhfBwD5tvtGgdYciYiITGsKRzOY9wK5yHYXi2e7rS4eOez7k4nhBeMSr3KktrqsyAua7/1+ywtHZq8jrTkSERE5MigczWBeOCqwshiO0kd5q61u2vLWHBXbR+Yo7+kq1w1HvW44Sgx0ApCH9jkSERE5EigczWDePkcFycpRNkZ5p7fVKRxNV96/fZGlaXXZlO+21fXghqNBUzlKbQKrtjoREZHpTOFoBvMqR/lkbxPYgM9W5egI4LXVFeJNq1M4ygavra7LMRWieH8nAIVOnzlBFToREZFpTeFoBvNeIOdlMRz5bIuoo01gpzuvcpSP2uqyKS9k3hjoHBKOipxu94SKqbgsERERGSOFoxls0K0c5XrhKAvrIQLpm8CqrW7a8tYc5aN9jrLJqxx1xE37nDPQiUWC/JhpryNf4UhERGQ6UziawbzqQY7jVY6yseYofVqdRnlPV/1uMM5LuO1eaqvLilQ4ygHACndTRD82cfeE8qm6NBERERkDhaMZzGurCyWy3FaXXHOkUd7TVTIYJ8ORKkfZ4O1z1J4wVVhfpJtyy22pCxaCPzRVlyYiIiJjoHA0g3ltdSHHXXeSlYEMmlZ3JOiPxLFJEEp4a46Kp/aCjhJe5ajbXXMUiPVQhhuO8lU1EhERme4UjmYwb1pdIO6uO8lGW52ttrojQX8kToG33ghUOcqSkN/GtqAbE45yYr2UWT3mRg1jEBERmfYUjmYwb1F+IJ69ypHfZxFz1FY33Q1EYhR6k+p8IbV7ZYllWeQF/XQ75v+l3ERaONIwBhERkWlP4WgGG4gmAPAnK0dZCEd22j5HiSg4zmHfp2RffyROoaUx3hMhL+hLVo4K6Uu11alyJCIiMu0pHM1g4WgciwT+WBbDkc9KtdUBJOKHfZ+SfQPROMVoUt1EyAv66HHXHBXRT6XttdWVTeFViYiIyFgoHM1gg9E4OaS1vmWlcpQ2kAHUWjdN9UfiVFvt5pPC2qm9mKNMbtCfrBz5rQRz/W3mBrXViYiITHsKRzPYQDROPmH3Mwv8uYd9n2afI3/qgCbWTUt94RjVVof5pEjhKJvygz4GCBF33ySYazWZG9RWJyIiMu0pHM1gg9EEeVbaHkf24X87BOwhbXWaWDct7e0coMYLR6ocZVVu0AdYtPhrAGhI7DI3qHIkIiIy7SkczWCD0TgF3sSyQF5W7tNnWzjYxL1vLVWOpp2ugSjdg7FUW11R3dRe0FEm390Idj3zAbBxh5KociQiIjLtKRzNUImEQziWIA+3chQ6/D2OAAI+8y0VT+51pDVH083uDjOAo97XaQ4U1kzdxRyFvI1gnwrPybxBm8CKiIhMewpHM1Q4ZsZ4FyTb6rITjvw+CyC17iiuytF0s7vDVAtr7U5zoFCVo2zKC5lw9Fxs7pAbFI5ERESmO4WjGWogakZs5ycrR4VZuV+fbcJR3PL2OtKao+nGhCOHMsdrq9Oao2wqzg0AsN6ZQ8xxf8T6Qll7A0JEREQmjsLRDDXohqMiO7uVI6+tLqa2umlrV3s/ZfQQcNyqXoHa6rLp0mWmEjdIiM1OgzmYXwGWNYVXJSIiImOhcDRDeeGoxO+O8s7SmiO/rba66W53xwA13jCG/ErwB6f2go4yS+uKOP0Y00L3QmKeOaiWOhERkSOCwtEMNZCsHLmVnSxsAAvgd8eBRx23cqS2umlnd0d/ao8jDWOYEO8+04Si55wF5kDRrCm8GhERERkr/8FPkaPRYNQMZCiyByEBBLOz5sgbyJBqq1PlaDpxHIfdHQOsSIYjDWOYCKsXVnL2wko2dl1E7IRq/EsunepLEhERkTFQOJqhwkPXHGVtlLcJR5FkW53WHE0nXQNResMxavwaxjCRLMvilneuwrIs4LypvhwREREZI7XVzVBeW122R3n73La6mNrqpqVd7WaM95xAtzmgytGEsTSAQURE5IijcDRDeW11BVneBNYbyBBRW9205G0A2xDoNAdUORIRERFJUjiaobxpdXmYSkK2R3knBzKorW5a2dluwlFNcs2RwpGIiIiIR+FohhpIhqNst9W5lSNHm8BOR9vbTDgqjbeZAwpHIiIiIknjDkePPPIIl112GXV1dViWxe233z7iue973/uwLItvfetbGcfb29u5+uqrKSoqoqSkhOuuu47e3t6Mc1588UXOPPNMcnJyaGho4IYbbhjvpcoovMpRruNWjrI8kEHT6qan7a19BImSF+s0B4q05khERETEM+5w1NfXx/Lly7nppptGPe9Pf/oTTz75JHV1B774uvrqq1m/fj333nsvd955J4888gjvfe97k7d3d3dzwQUXMHv2bNasWcPXv/51vvzlL/OjH/1ovJcrIwjHzJqjnER22+r8Xlsdaqubjna09VHltdT5QpBbOrUXJCIiIjKNjHuU98UXX8zFF1886jl79uzhwx/+MH//+9+59NLM/T02bNjA3XffzTPPPMNJJ50EwHe/+10uueQSvvGNb1BXV8ett95KJBLhZz/7GcFgkGOPPZa1a9dy4403ZoQoOXQDEVM5CjmmzYpQlvY5ctvqot63VkKVo+liMBpnb9cgJ1lpY7w1UU1EREQkKetrjhKJBNdeey2f+tSnOPbYYw+4/YknnqCkpCQZjADOP/98bNvmqaeeSp5z1llnEQwGk+dceOGFbNq0iY6Ojmxf8oxk2uocQnE3HGWrcmQPbavTmqPpwhvGMCfkjfHWeiMRERGRdFnfBPZrX/safr+fj3zkI8Pe3tTURFVVVeZF+P2UlZXR1NSUPGfu3LkZ51RXVydvKy09sBUoHA4TDoeTn3d3dx/W8zjaDcbihIhiY9rrCOZn5X59qhxNW9tb+wBYnN8LfSgciYiIiAyR1crRmjVr+Pa3v80tt9wy6RsgXn/99RQXFyf/a2homNTHP9IMRBIUeGO8IWuVI8uy8NsWUW9andYcTRvb20w4mht03zjQMAYRERGRDFkNR48++igtLS00Njbi9/vx+/3s2LGDT3ziE8yZMweAmpoaWlpaMr4uFovR3t5OTU1N8pzm5uaMc7zPvXOG+uxnP0tXV1fyv127dmXzqR11BmNx8i13jHcgH+zsfSv4fZba6qYhb4z3LF+nOaDKkYiIiEiGrLbVXXvttZx//vkZxy688EKuvfZa3vnOdwJw2mmn0dnZyZo1azjxxBMBeOCBB0gkEpxyyinJcz73uc8RjUYJBAIA3HvvvSxatGjYljqAUChEKBTK5tM5qoWj8VTlKEtjvD1+2yYad8OR2uqmjR1u5ag84e5xVKRwJCIiIpJu3OGot7eXLVu2JD/ftm0ba9eupaysjMbGRsrLyzPODwQC1NTUsGjRIgCWLFnCRRddxHve8x5uvvlmotEoH/rQh3jLW96SHPv9tre9ja985Stcd911fPrTn2bdunV8+9vf5pvf/ObhPFdJMxCNk5/lDWA9fp9FLK5R3tPN9lZTOSqK7jcHVDkSERERyTDucPTss89yzjnnJD//+Mc/DsA73vEObrnlljHdx6233sqHPvQhzjvvPGzb5qqrruI73/lO8vbi4mLuuecePvjBD3LiiSdSUVHBF7/4RY3xzqLBaIJCy9vjKDvDGDx+204NZFBb3bQQiyfY2zUAOAQH3LZWhSMRERGRDOMOR6tXr8ZxnDGfv3379gOOlZWV8etf/3rUrzv++ON59NFHx3t5MkaD0Tg1uNP9srTHkcdvW6lNYNVWNy109EdxHCix+rBibsVQ4UhEREQkQ9b3OZIjw0A0Tn6ycjQBbXXJaXUKR9NBe59pb1yQ406qyy2DQM4UXpGIiIjI9KNwNEOFowkKvDVHWR7IEPClt9UpHE0HbX2mSjg/p8cc0BhvERERkQMoHM1Qg9E4+UxM5cintrppx6sczfb2OCocfiS+iIiIyEymcDRDmba6CZpWZ6fvc6RwNB209ZpwVOtzK0cF1VN4NSIiIiLTk8LRDOQ4jls5moy2Oo3yng7a3MpRhe2Go/yKKbwaERERkelJ4WgqDXbDMz+B/Zsn9WEj8QQJhwmrHGW21WmU93TQ7q45Kre6zIH8yim8GhEREZHpadyjvCV7Ek//BPuBr5hPlv0/uPy7EMid0Md89JX9bGoy1YMCb81R1itHFjFHbXXTibfmqDjRaQ7kqXIkIiIiMpTC0RSIxhNc/r3H+dTA45zrHXzpd5CIwxt/BpY1YY/90d+sTbVYeVWEYLb3ObKJed9aGsgwLbS6a47yY53mgCpHIiIiIgdQW90U2NXez4Z93eT17zEHVl4DdgDW/xEe/9aEPe5gNJ4MRlfaj3CCvQUsG2qPz+rj+H0WEY3ynla8ylFupN0c0JojERERkQMoHE2Bpi6z1qfe2g+As/JauPi/zY1P/wQcZ0Ie1wtGdbTy1cDPzcHVn4XKRVl9HE2rm35MOHIIhL1wpMqRiIiIyFAKR1NgX9cgPuLUYF6o3vKyw765bwBfELp3Q9uWCXnctl6zKP9s3wvkW2E2WvPgzE9k/XH8PjsVjtRWN+XiCYeO/ghF9GF5AzJUORIRERE5gMLRFNjXNUCt1Y7fShB2/Pz7Q62c8+2nidSdbE549cEJeVxvr5sGt2K1JrEAbF/WH8dvq61uOunoj+A4UGG5G8CGisAfmtqLEhEREZmGFI6mwL6uwWRL3UBeHeUFuQxGE2wpXGVO2Dox4ajVrRw1WC3mYWITUz3w+2xNq5tGvPVGs3P6zQFVjURERESGpXA0BZrSwlFJ7Xxed3wtAI8mlpkTtj06IaHCW3PkVY52O1VZfwyAQPqaI7XVTTmvYtgY8sKR1huJiIiIDEfhaAqkV44oaWRlYwkAf9tfCbllEOmB3c9m/XFbe7zKkXnsotr5WX8MMJvAqq1u+mhzN4CtD/aZAwpHIiIiIsNSOJoCTd2D1Fut5pOSRk5oLAVg3b5e4vPOMcc3/y3rj9vWFyGPQcrdtSf/dvXFWX8M8AYyKBxNF15bXbXPbP5LXvkUXo2IiIjI9KVwNFki5l37wWic9r5Ict0PJbOpL82lsjBELOGwrdLdFnbDHYc20juRgFh42Jtae8OpilVOCaVlE7P2JOCziKqtbtrw2uqqbHcggypHIiIiIsNSOJposTDc+ia4YR70tiT3OGpIqxxZlsUJbmvdw/Hl4M+B9q3QvH78j/e7d8D/LIauPQfc1NabFspKZx/KsxkTX8Y+R7EJexwZm13tZq1RmaVwJCIiIjIahaOJ5g9B336IDcKGv7CvaxA/MaotdzNON6R4rXVP7w3D/PPMbRvuGPPDtPaG+eRvniWx6W8w0A4v337AOW19YRrTKlYTJeCziTpeW11kwh5HDi6RcHjkFRPEk211mlYnIiIiMiyFo8lw3JXmz3V/oql7gBqrHR8J8IUg30yMO2mOCUfPbO/AWfI6c/5zv4QdT4zpIf73iR289MIz2F4b26bMNUuJhONWjty2utI5h/WURuO31VY3Xby8r5vW3jB5QR+F8U5zUOFIREREZFgKR5Nh6evNnzsep7N5VyqglDSAbf4Jls0qITfgo70vwpbSs6G4AXr2ws8vgk13H/QhNjf3sMTamTqw8wkY6Ex+2j0YJZZw0sLRxFWO/OltdU4CEvEJeywZ3cObzb/3a+aXY/e7rZxqqxMREREZlsLRZChphPpVgEPlrrszxnh7gn47WT36x54om6/4KwPzLjA3rv/TQR9ic3MPS+wdqQOJGGy5L/lpq7sof7bPe+w5h/x0Dsbvs4l60+pAE+um0MObzL/3+fPzoN9t5SyomcIrEhEREZm+FI4my7GmtW5B2wMZY7zTnTrPjFj++ePbuOCH6/jPvSeZG1pGH8wQjsXZ3tafrByFc9zNXTenKk5tvWECxGikyRwom3s4z2ZUfp+VGY6Osta6+15u5o4X9k71ZRxU92CUNTs7ADi3YBfgmLVm+RrlLSIiIjIchaPJMt+M6G4Mb04b4z00HJUBsL3NTBd7uMttf9q/adSpb9ta+4gnHJbYJhw9XfMWc8P2x5LntPVFWGFtIYeIaasqm3fYT2kkGW11cFRVjiKxBO/+5bN8+LbnWbena6ovZ1SvNPcSTzjUFudQ1fmCOdhw8tRelIiIiMg0pnA0Wcrngy9IrjPIKfYGc2zIxDhv3ZFnt1NJPJBvJr61bRnxrjc391JBF5VWFwnH4g+Js8DyQc8+6DYVjtbeMKf71pkvmHsWWFZ2n18av20TT//WShw947zb+lJ7SP3p+QPHpU8nuztMyG4oy4NdT5mDDadM4RWJiIiITG8KR5Ng3Z4u/vZyK/HyhQDMstrMDUMqR0G/zZkLUpPEHGy6C48xn4zSWvdK2nqjbU4NTzRZULXU3LhnDQBNXYO8xnbvY+5Zh/uURhXwWYBF1AqYA0fROO/9Palw9Oe1e4jGE1N4NaPb3TEAQENJCHY/aw6qciQiIiIyIoWjSfDeXz7L+299jrb8YzJvGBKOAL521fH85r2ncsWKOgD2huabG5pfHvH+zaQ6E442OQ00d4cZqFpubnTD0XNbdrPScqtPc88+jGdzcD53Al+co2+vo9becNrHER7c2DKFVzM6Lxwdn9MM4S4I5EPVsVN8VSIiIiLTl8LRJJhVmgvAFistDKXtcZSuND/IqfPKaSzPB+BV72uaR6sc9XK8vQ2AvXmLAdiRu8TcuGcN+3vChPY+TcCKEy9qmNBhDGAGMgDELC8cHT1rjrzKUSH9fMH/v7zw7GMH+Yqp47XVHRvbaA7MOgF8/lG+QkRERGRmUziaBHUlJhw92582Qjltj6PhzC7LA2BtZJY5MFxbneMQ7tjD9rY+lllbAeivOB6AdbgVpz3P89DGJs62zYJ83/yJrRqBGcgAEMVtq4uFRzn7yOKFo7cHH+I6/9/41LbrIDowxVc1vD1u5ah+cJM5UH/SFF6NiIiIyPSncDQJZrnh6N621Hqi4Vrq0s0uN+Hoid5qc6BzJwx0wKsPwD1fgMFuuPOjhL69lDfb9zPbNu1doYYTAHiqpwoCeRDpYcOLz3CJz12Qv/h1WXxmw/P7zLfV0bzmaHl+R+rgY9+amosZheM47Ok04ahk0B0cUX7MKF8hIiIiIgpHk8Brq3upJ58ux4Seg4WjRjccbery41QsMgc3/hX++M/wj+/AzafDmlsA+Kz/NnN72Txm15tK08aWAahdAcCZO79PjdVBPFiUHCk+kQJu5Sjmrjn6wf3reWpr24Q/7mTY7645qssZTB5zHvsmdO+bqksa1v7eMOFYAtuCUN9uc3DIdEQRERERyaRwNAm8tjqw2Oi4oeggL1QrC0LkBX0kHOiceykAzn1fhj53AEDnzuS5RVa/+0ArWVRTCJghDYmV1wBwjmWGMthLLgV/6PCf0EH43HAUcdvqHtu0jzf/6Ekcx5nwxx5qIBLnya1txBPZeezWHlMFqyEV9qx4GPY+n5X7zxZvGMOsoiBW5y5zsFThSERERGQ0CkeToD4ZjuC22Lm05c6BRReP+jWWZdHorjt6pfK15ljffgC2lJzBtkQ1f0mcwa7841JfVLeSxrI8Qn6bcCzBjvrXs7toZeo+j70yS89odAGvrc4NR0HMPkfr93ZPyuOn+8od63nLj57kBw9t4dX9vVz9kyf5x6uth3x/XuWoMGJCarNTYm7onl57Hnnh6LjiAUhEwfZD0awpvioRERGR6U3haBLUpYWj2xNn8Nez/gxVSw76dQ1uONoYr6MpN7Ve5BPtr+ecyI18JPIB/hh9TdoDrcRnWyyoLgBgU3MvNwbfz6AToC+nGuatzs4TOghvWl3EbasLYqbV3fHC3kl5/HS/ecZUTb5xz2ZufXInj29p4zdP7zrk+9vfE8YmQXDAhKPnEwvMDdMuHLmT6nLdtVHF9WD7RvkKEREREVE4mgT5IT8leYHk5xUFY2ttO6bKhJxntndwR/w0AF5MzOWFyCzABJBfdq9k0AkQ9+dBjZlUt7DatNa9uLuTO/cVcX7kG+x/y93gD2brKY0q1VZnwlHIrRz95YW9JLLU3nYontneDkBb36FNzxuIxOkNxyinCysRI4HNiwl3LHr35Ae/0XiVo2OC3obDaqkTERERORiFo0kyK616NNZwdNGxZvT33ev28T/d5/Ld+JV8xfch9z5M0GmjmDdGvkTLVX+EnCIAFrvrjn6/ZjeReIJoYT2zZ0/s3kbpvLY6b81RwA1H+7oGeX5X56RdB8C8ivzkx+v3dgHQ1nto0/O8DWBn+zsB6PaXsdupNDdOs3C0q91Ujhpw16hpvZGIiIjIQSkcTZLMcDS2Cs7x9cXMq8wnGncYJMQjs97DF9/1Rr502VI+ev7C5HkbrPlULDwl+fmKhlIAWtyx06fNK8eyrGw8jTHx9jkKO25bnZXaBHZzc8+kXQfgFdgA8IpWbX2HFo68v8+FeWbtVF+omianzNw4zdrqvL/nmkSzOaDKkYiIiMhBKRxNEm+cN0BF4dgqR5ZlceXK1CL6sxZUsryhhHeePpdls4pT912Sm6zWAJw8t4zPX7qEvKBZY3LekurDvfxx8dveQAZvzVEseZtX0ZgsvYOxA46V920ltuGv3PTgFp7f2XHA7V/+y3qu/elThGPxjOPeHkdzg6YCFcmrYR9eONoLUzCNbzhtvWGau8NYFpRE3BHjpXOm9JpEREREjgT+qb6AmcKrHAX9NoWhsf+1v37FLL5xz2YAzlpYmTy+qKYQn20RTzjJqXbp3n3mPC5bXseWll5eM7/8MK9+fLyBDMnKEanK0S53Lcxk6Q1nhqMSerg7+Cn4P/hz+GvcUb2Uuz96VvJ2x3H49VM7icQTPL2tnTMXpP7OvUl1DT4TqBKFdbQ4pkpHbNBs0ptXNsHP6OA27DNVo9llefi63JHvqhyJiIiIHJQqR5PEC0eVBaFxtbg1lOXxpcuW8pFzj+H4+lS1KCfgY36lWU/jbRg7VHVRDqcfUzGpLXUAATccDbrhKECM2e417pzEylE84dAfyaz+fNz/++THx1rb2dTckxGgugdjROIJAJ54NXPj2la3clRrmeP+0nrCBOmw3H+XadJat2GfaftbVpOTWgulNUciIiIiB6XK0SQ5aU4ZFQUhXrt0/C1u7zx9+GEKKxpK2Nzcy0J3qt104XPb6iKOHywIWTHmVeSzo62f3ZMYjvoiqdBz9sJKjo++wNX77k8em2M348Rg3Z4uinIC5AZ9JNJa457YmhmOXmkxFZmKhDmeU94AwL5EGaVWlwkiNcsm7PmMlReOTinuBhzw50J+5ehfJCIiIiIKR5OlsjDE0/92HradvSrOJy9YxPKGEt6wcnpt7ukNZBh0fGCZtrp5lQU8uGk/bX0R+sIx8sfRWniovPVGQZ/NL457Af72aSCRvH2uZdbj3PXSPn7zzC7K84N8680rkre/uLuL3nCMgpCf9r4I971sJr9VOmYT2cKq2UAXexKlLPVtm/LK0VNb29jVMZDcbPfk2BpzQ8PJMMnVQxEREZEjkcLRJMpmMAKoKsrh6lOmX7uUNxwi7JhR3kFilOUHKc4N0DUQZVdHP4triib8Orx2ufJgFO7+LDhxnsw/j9s6FvHt4PeZYzUBcOtTO4knHPZ1DbK1tS/59fGEw/89s4vKwhC72vuJxBOcVBci2GUmwOWVN5Af7KUpkTaUYYokEg7//Ks1dPan1nfN3v+A+WDJZVN0VSIiIiJHFoUjyTqffeCao7jPoqEsl649UXa1D0xKOOpxK0f1oX4YjIIvxO1zv8T69icBmGs1cay1jcvsJ/lx4hLaKGbdnq6M+/jqnS9nfP6Z6qehPWIGHBQ3UFW0jX0dUx+OXmnpzQhG83J6Ce571nyy6JIpuioRERGRI4sGMkjWeQMZImnT6gI+OzlVb7LGeXuVo+qAOyEvr4yyghA7nWoSjkWhNcBNge/wPv8d/Db479TSxjq3Ja26KIRFgg/4/8wvcr5BNe0UBx1O2PMrc19nfBRsm4KQn32OOw2wa/ekPK/hrNlhJuh5f/fXlr2MhQN1J0Dx9Gq7FBEREZmuVDmSrPO7bXURb58jK0bUZ9NQmsex1jY6m3KB4YdMZJO35qja74ax3DLK8oNECLDbqaDR2s8c27TIzbf3cVvwP7hy3/VADm89oYard36Ryr1mgMP/1ReRmHMW9rN7oKAalr/N3GXQRzPuOO+epgl/TiPxwtF7zpzHWaEtrFrzW3PDktdN2TWJiIiIHGkUjiTrvIEMEbw1R1GiPosloVY+Gfwi+zbPAZ6b8OvocytHFclwVEpFgdmAd7tTQyP7AdiYaKDUF2aO3cxXnB/xYT7MSX0PmmDkC4ETZ07rQ9D6kLmf0/8FAjkA5AV97HfMSHUGM1vyJsPX/76R3ICP59zNbM8t2sVJ974dnDiUzoWVb5/0axIRERE5UikcSdalwpHXVhcjbNssjm4gYMVpjLwK4V4ITewI8h43HJXZ7pCF3BLK8oMAbHVqOYuXAJj72vfy59Z6rlx7HZf5nuTe+Ek09JqJdJzyXrAD8NiN5vMT/wlOeX/yMfKCPnpw95kK90zo8xlqT+cANz34asax4/f8zgSj+efBm34BocJJvSYRERGRI5nWHEnWeQMZomnhyO+zqBnckjzHaX0FgBd3d7L66w/ylxeyP8zAa6srtXrNgdzSZDja5tQmzwsddzlWwypujpupblf4HqOia525cdZJcNan4IS3w7lfgEu/CXbqf5vcgJ8ex2zwS7QP4qm9lSZaU9dAxufLKm2Cm+8wn6z+rIKRiIiIyDgpHEnWWZaF37aIOKm2uqDPpqhrU/Kc3t0mfNx472a2t/Xz8hN3wWPfgrRNWA9Xb9hMbysmFY68trqXEu6ap/pVUDqH2uJc/ho/FYBT7Q3kdW40t886EYJ5cPl34axPZgQjgPyQj16vcgQQ7s7a9R9Mc3c44/N3FK+FaD+UL4D6kybtOkRERESOFgpHMiH8Potw2kAGv8/GbkmNxe7bs57trX08vNms+7m25Rtw35dg11NZuwZvWl2hkwpHpfkmsD3nLOTeVT+GN/0vADXFITY6DbQ6ReRZYaxEDPKroLh+1MfIDfqI4idqmYrU5IajQQBOnlvGR8+bz+Wxe8wNK96mTV9FREREDoHCkUyIgG0n2+oCxMiLtEFfS/J2p2Ujv3pyB44DISLUxt1Jb+1bs3YN3j5H+XF3LVBeGSG/j8KQuS573tlQZNrraopzcbB5PHFc6g5mnXjQkJEXMPc16HPXT03iuiOvcnRsXREfDd5BsOk58OfA8rdO2jWIiIiIHE0UjmRC+HxWxrS64p5XMm7P7dzC79aYfYFmW83YlttO17kza9fgTavLS7jVnFwzcntpXRF+22JpXWoj2oKQn8KQn8fSw1H9iQd9jLygD4AB25tYN3mVoxa3crQ8sQEe/E9z8NL/SQY+ERERERkfTauTCeG37bRNYGME3PVGe4qWM6v7BQoH9zA42EdhTh7HWfvBW2qUxXDktdXlRt0R2244uuWdJ9M5EKG2ODfj/JriHB5rWYab6Uzl6CBy3XDUb3kT6yYvHDW54WhZ5wOAA8deCSuvmbTHFxERETnaqHIkEyKQVjkKWVHyOzcA0FVzBp1OPj4SzLWaWNFQwvE5qXa7bIYjr60uOCQc5QZ9BwQjMOFoH+U8k3smVB8HDacc9DG8ylFyKMMkVo68NUdlg+7f2fxzJu2xRURERI5GCkcyIXy2lbHmKLd7GwDBumPZ4swCYIG1mxUNJSzwNae+MOuVIwd/JDMcjaSmyGzsetvc/4D3Pw7B/IM+xgHhaBIrRy3umqOCXvN3S/mCSXtsERERkaORwpFMiIDPTk2rI4YvYgYVlFXUsDlhwtESeycrG0todPakvrB7T9b2CuoNx8gjjJ0wI70PFo6OddcgLa4Z+/5AuUHzHLu9vY4mKRz1hWP0hGOEiODvcf/+KhSORERERA6H1hzJhPDbFuG0gQy+qBmnXVJSxgZrPvAgy6ytLK0vIT+yO/WFiRj07IOShsN6fMdx6B2MUeXtceQLQSBv1K+55tTZnDi7jCW1Yw9H+W7lqDthqk6H0la3vyfMf921gatOqOeMBRVj+pqWHlM1WhpswcKBnBLIKx/3Y4uIiIhIiipHMiF8tpUxkMGO9gFg5xTSUrgUgBW+bZRbveREOwFot8vMF3ftOuzHD8cSxBIOpVZqj6ODjeX2+2yW1Rfj9439fwtvIENHwqscjX+U9/V/28Cfnt/Df/z15YOf7PLWG63IazUHKhZobyMRERGRw6TKkUyIgC9tnyMrjhNxQ0qogGj5YsJ9AQqtPthyLwB7nHL2OXWU0W7WHc1+zWE9vjeprjg9HE2APLetriOeCxZjaqvb1d7PE6+2saO9jwVVhfzpedMWt7Gph90d/dSXjl7hglQ4WhxogkG03khEREQkCxSOZEL406bVAab1CyBYwKr5NWzY0cgK61VYeysA2xI17E2Uc5KP5FCG25/fQ3FugHMWV4378XvdSXU1gQFzYMLCkakctcdCZgT4kLa69r4I7X0RjqkqYOv+Xm64exN/f7mJQqeP8+013O3M52JrF9cF/kYOERK3zYN3/vyg1+sNY5hn7TMHKo7J+nMTERERmWkUjmRC+G2LyAHfXhYE83nPmXMZaD8LXnwVtj0CwPMsJpKwwA1Hv312F//6+xcB2Ppfl2Db42sZ8ypHVf5+iDNh4chrqxtpIMM7fvY0L+3p4v2r5/O7Z3fR2hthrrWPX+XfyKz4nqF3By074KkfwurPjPiYrb1hNjaZ9r3kfahyJCIiInLYtOZIJoTftg8MR6FCsCz8PpvCeSenHS/m74VvYI9jhhGEW7fzhdvXJW/uj8bH/fgd/REAqvxu5ShvgipHAROOepKjvFNrjhzH4aU9Zoz4Dx56ldbeCK+pjnFf8X+YUJNbimMHSfhzaD/pY9wQfRMAiad/AtHBYR/vleYeTrv+fv7w3G7AocLb40iT6kREREQOmypHMiH8PgsHm6jjI2C54SZYkDqh7oTUx6/5EEv3N/LKmloAontfJBKL4WX3nsEoBaHxfavud6e5VQf6IMyEVY78Ppugz6YnceAmsF71yjO3Ip+f1d+Gb30HVB0Lb78dK5iPZfko9Ye4++X7uKbvPur698O6P8DKqw94vD+v3Us07pAf9HF5yTaC3b1g+aBs3oQ8PxEREZGZZNyVo0ceeYTLLruMuro6LMvi9ttvT94WjUb59Kc/zbJly8jPz6euro63v/3t7N27N+M+2tvbufrqqykqKqKkpITrrruO3t7ejHNefPFFzjzzTHJycmhoaOCGG244tGcoU8LvtsFlVI9CaeGoYgFUHwdl8+HU93POoipecubSTw4F8S6WWN5msA6DLdvAccb1+K29JhxV+MyUPHJKDvGZHFxu0EcPXltdV/J4W6+pXuUGfPz1I2dw11V55Kz/jbnx8u9AQZXZaDaQg2VZLJ9dyS9jF5jbn/nxsI91z8tNAPz3Zcdwve+H5uDKa8Afyv4TExEREZlhxh2O+vr6WL58OTfddNMBt/X39/Pcc8/xhS98geeee44//vGPbNq0icsvvzzjvKuvvpr169dz7733cuedd/LII4/w3ve+N3l7d3c3F1xwAbNnz2bNmjV8/etf58tf/jI/+tGPDuEpylTwxmGnD2XIqBzZPvjnR+EDT0KokNMXVIAd4In4EgCuKH6FRaUOPw7cyNxbT4MnDvx+6+qPMhiNk0g4fOK3L/DuXzxLJJYAoNUNJpWJNnNyUd0EPEsjP+ijx0lrq3ODXFufuYbygiDHVgbJvftj5pzlb4X6kw64n6W1Rfw+frb5ZO9aGOjIuH17ax+bm3vx2Ravbf0FdGyDollwwVcn5HmJiIiIzDTjbqu7+OKLufjii4e9rbi4mHvvvTfj2Pe+9z1OPvlkdu7cSWNjIxs2bODuu+/mmWee4aSTzAvE7373u1xyySV84xvfoK6ujltvvZVIJMLPfvYzgsEgxx57LGvXruXGG2/MCFEyfXmVo+hIlSMA2wY7CEBRToATZ5fy+M7jOM/3PJcHn+PC3vuZ7XMrSHufy/jS9r4IZ9/wIGUFQd68qsFdgwP3b2jm4mW1tLptdeUxU2mhZHaWn2FKbtDHXq9y5CQg0gehAtrc6lV5QQj+9q/QvA7yK+H8rwx7P0vrimilmJ1WHY3OXrY9/wANp7whGTTvfbkZgHPmhMh5/ufmiy75OuQUT9hzExEREZlJJnwgQ1dXF5ZlUVJSAsATTzxBSUlJMhgBnH/++di2zVNPPZU856yzziIYDCbPufDCC9m0aRMdHZnvpnvC4TDd3d0Z/8nUSVWO0sJRsHDUrzlncRWPJY4DoKb7BWYndqZuHLK56jPb2+kJx9jR1s8Nd28CoNFqpuHOt8L629nfG8YmQeGgO+q6pPEwn9HI8oJ+BgiRsHzutZrvPa9ydLJvCzz3S8CCq34ChdXD3s+S2iIA/hFdCMDf7/oTF337UR7c2ELPYJTfrTGb476n8EmI9EDFIlh0yYQ9LxEREZGZZkLD0eDgIJ/+9Kd561vfSlGReeHX1NREVVXmvjV+v5+ysjKampqS51RXZ76A9D73zhnq+uuvp7i4OPlfQ0NDtp+OjEPArRyFnbS2uqGVoyEuW15HW+48evxlAMTwcVPMbcnsb8s496XdXRmfzy7N4euBH3Jc+HkSt3+QRNdequjAdmJg+6Gw9jCf0cjMOG+LmN99fu5QBq9ytMTabo4vuADmrR7xfsryg9QW5/BMYjEAq+yNbGnp5Z23PMNZNzzI5uZeSnNsTmr+rfmCU/4ZrPGNOBcRERGRkU1YOIpGo7zpTW/CcRx+8IMfTNTDJH32s5+lq6sr+d+uXbsm/DFlZL7h2uqCo4ejWSW5rPniBRSuvAqAOyvfy4PxFebG/vaMc1/Y3QnAR5d0c3fxf3Nn9Q85xd4IgB3t5V09N1Nv7TcnF80C38QNZvQ2go144citcnnrnupoMcfHMFFuaW0RzziLADje3sb/zf4Lvwz+N5+KfJ935DzKQ3Nuwde53QyYWP6WrD4PERERkZluQl4xesFox44dPPDAA8mqEUBNTQ0tLS0Z58diMdrb26mpqUme09zcnHGO97l3zlChUIhQSBO7poth2+oOUjlKuvA/4eT38uzjYTp2P2GODaTCUfr+Qe+w76Y0/CJsNxvG/ia2mv/nf4TznCfZ5XO/70onbr0RDBeOzLW1u211VXH3e3kMrX1L64q4f2MVzU4J1VYnpzT/xryFYQM8CNsBXxAu/R8z6U5EREREsibrlSMvGL3yyivcd999lJeXZ9x+2mmn0dnZyZo1a5LHHnjgARKJBKecckrynEceeYRoNJo8595772XRokWUlk7MfjWSXQGfN8o7fVrd6GuOkvwhqFxIYU6ATsdrVeuCuNk3aFf7AJ39UYI+m+KeV8ztDafQsfhtfC52HfckVgFwpe8xc9sErjcCyA2YANhvmYl1iQFvzZFpqyuNuKPsxxDSltYWARZPJczUPvIq4KKvwRkfh/pV0HAqvPNuWPbG7D4JERERERl/5ai3t5ctW7YkP9+2bRtr166lrKyM2tpa3vjGN/Lcc89x5513Eo/Hk2uEysrKCAaDLFmyhIsuuoj3vOc93HzzzUSjUT70oQ/xlre8hbo6M275bW97G1/5yle47rrr+PSnP826dev49re/zTe/+c0sPW2ZaF5bXcQ5hMqRqyDkp5O0rxnshPwKXtzTCcBxNbnYrZvNbVf+mLzCenjx7zwZX8zF9lMUWf3mtgmcVAepytHGDqj3wa0PvcAVCy5L7nOUP+CGozGEtFPmlVNREOTpuvdz+ezT4cR/ghKtnxMRERGZDOMOR88++yznnHNO8vOPf/zjALzjHe/gy1/+Mn/5y18AWLFiRcbXPfjgg6xevRqAW2+9lQ996EOcd9552LbNVVddxXe+853kucXFxdxzzz188IMf5MQTT6SiooIvfvGLGuN9BAm4bXXjWXM0VGGOnzg++u0C8hK9ZihDfgUvusMYVld0QVvUVKRKGglZFnPK83imdVHmHU1w5SgvZMLRK0495/M8J+//Pe/4ybm09kbIY5BguGPM11GWH+SZz51vtkqyXz+BVy0iIiIiQ407HK1evRrH3eRyOKPd5ikrK+PXv/71qOccf/zxPProo+O9PJkmvH2OMtrqQmNsq3MV5phvzx67yA1HZt3Ry3tN29qqXHdMd/XS5NS2hdWF/H1/I91OLkXWgLl9osOR21Z3c+wy3uR7iEX2bs5r+gm/iF1IvdVrTsopGfN+RJZlaQidiIiIyBSY8H2OZGbywlH4UAYyuApCJlh1ea117lCG5u5BAOqj283xqqXJr1lYXUgCm2cTadWjSWqr66KAH4X+CYAP+v/C0zkf5HP+W91rmNiAJiIiIiKHT+FIJoR/2La68VWOCkLmazsc9+vcypG3uWppj7veqPrY5NcsrDbnensFYQegcPgJh9mS64YjgKa5V/J0w3VsT5h9uc72mSl6Ez0xT0REREQOn8KRTAi/N61uHJvADuW11bU5qcpRLJ6go9+Eo9yOTeZ4WjhaVGPOfTRxnHvbUrBT4WUi5KWFoxWNpXDu57k4cj29Tk7qpAmuXomIiIjI4VM4kgmRWnN0eAMZAFrj7n4+/W2090VwHCi2+vH17DbHq5Ykv2Z2eT4Bn8U6Zx6PnPpTeOPPD/1JjFFGOGooYXlDMQl/HncnTk6dpHAkIiIiMu0pHMmE8NveJrCHM5DBfG1LzAtH7bS647GPz2s1xwqqITe191XAZ7Ok1mz+Glp4DpTPP5TLH5eO/tR+XEvrigj5fZzQWMof4memTtKaIxEREZFpb9zT6kTGwtsE9nBGeee7I7KTex0NdNDaazZWXRDqhn6guP6Ar/v6G5fzwq5OTp5bNv4LPwRnLazEb1usbCwh5Pclj92wdQltOY2UR5syWv9EREREZHpSOJIJ4XMrR8lpdb4g+IPjuo+Q30fQb9ORSA1k8MLR7GCnCUdFsw74ukU1hSyqGV+V6nDMKsnlqX87j6LcVJXsnafPYVZpLoG6u8Dp1UauIiIiIkcAhSOZEAcMZBhn1chTlOOnvd8NOgOpcFRvm8l1w1WOpkJ5QSjj85yAj8uX103R1YiIiIjIodCaI5kQqbY6d1jBOCfVeQpCfjq9aXX9bbS5a46qaTPHhqkciYiIiIgcCoUjmRC+oQMZxrnHkacgx0+Hk1pztL/HbABbHttvjhWpOiMiIiIi2aFwJBMikBzl7YajcU6q8xSGAnTgfm0iRl9PJwBF0WZzbJq01YmIiIjIkU/hSCaE32e+tbqdPHMgr/yQ7qcgx0+YIDHbbKga69mPTYLcQa9ypLY6EREREckOhSOZEN4msPclTuDxhn+Gcz93SPfjbQTbHzThytfXTAVd2E4MLB8U1mTngkVERERkxlM4kgnhTasbJMSaOe855H1+CkMmHHUGTQgqGNxHneUOYyisBdt3+BcrIiIiIoJGecsE8dup3O0FpUNR4FaO2vxVNAI1zn4GLPfbVsMYRERERCSLVDmSCZEeiIK+Q/82qy4ya432OBUA1FutzA12mBuLtd5IRERERLJHlSOZEN6ao6Efj1d9aS4AWyKlAMyyWvEHCiGKhjGIiIiISFYpHMmECKRViwL+Q68c1ZeaaXfr+0oAE46CvmITjjTGW0RERESySOFIJoQvrVoUsA89HM0qMZWjzeESCJlwVOCEzI0lsw/nEkVEREREMigcyYQIpK05CvgPva0uP+SnLD/Ivj4zyjvXipAb3mZurD/psK5RRERERCSdBjLIhMiYVncYlSMw644iBGh2SlIHy+ZDQdVh3a+IiIiISDqFI5kQGW11hzGtDlJDGbyJdQA0nnpY9ykiIiIiMpTCkUyIjIEMh7HPEaSGMmSEo4ZTDus+RURERESGUjiSCTExlaPK1EFVjkREREQkyxSOZEKkV4v8h1058sKRGcpAbimULzis+xQRERERGUrhSCaEP61aFDzsypFpq3sysZS45YPjroLDHPIgIiIiIjKURnnLhPDb6ZWjwwsy3l5Hrzj13Pu6p7hoxdzDuj8RERERkeHo7XeZEP6MNUeH11aXH/JTW5wDwMLGWvAp04uIiIhI9ulVpkyIbA5kALj5mhPZ0znAvMqCw74vEREREZHhKBzJhLAsC79tEUs4WQlHyxtKWN5QcvgXJiIiIiIyArXVyYQpzg1gWVCYowwuIiIiItOfXrXKhPnuW1eyvzdMRUFoqi9FREREROSgFI5kwrzmmIqpvgQRERERkTFTW52IiIiIiAgKRyIiIiIiIoDCkYiIiIiICKBwJCIiIiIiAigciYiIiIiIAApHIiIiIiIigMKRiIiIiIgIoHAkIiIiIiICKByJiIiIiIgACkciIiIiIiKAwpGIiIiIiAigcCQiIiIiIgIoHImIiIiIiAAKRyIiIiIiIoDCkYiIiIiICKBwJCIiIiIiAigciYiIiIiIAApHIiIiIiIigMKRiIiIiIgIoHAkIiIiIiICKByJiIiIiIgA4J/qC5gojuMA0N3dPcVXr+HQ7QAAAKRJREFUIiIiIiIiU8nLBF5GGMlRG456enoAaGhomOIrERERERGR6aCnp4fi4uIRb7ecg8WnI1QikWDv3r0UFhZiWdZUX46IiIiIiEwRx3Ho6emhrq4O2x55ZdFRG45ERERERETGQwMZREREREREUDgSEREREREBFI5EREREREQAhSMRERERERFA4UhERERERARQOBIREREREQEUjkRERERERAD4/1wB6RrJhAoBAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# set the x axis"
      ],
      "metadata": {
        "id": "0y7ogINg3-2j"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Train a model on the full historical data to mkae predictions into the future"
      ],
      "metadata": {
        "id": "jsNNZ0nk7w-p"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "eth_prices_windowed"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "id": "ijWvvrr72HOf",
        "outputId": "f72d827f-9c6f-45f5-d84f-44e3ddfaa633"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              Close_eth     Close_btc      Price-1      Price-2      Price-3  \\\n",
              "Date                                                                           \n",
              "2017-11-09   320.884003   7143.580078          NaN          NaN          NaN   \n",
              "2017-11-10   299.252991   6618.140137   320.884003          NaN          NaN   \n",
              "2017-11-11   314.681000   6357.600098   299.252991   320.884003          NaN   \n",
              "2017-11-12   307.907990   5950.069824   314.681000   299.252991   320.884003   \n",
              "2017-11-13   316.716003   6559.490234   307.907990   314.681000   299.252991   \n",
              "...                 ...           ...          ...          ...          ...   \n",
              "2023-12-17  2196.481201  41364.664063  2226.926514  2219.337402  2316.579102   \n",
              "2023-12-18  2217.273438  42623.539063  2196.481201  2226.926514  2219.337402   \n",
              "2023-12-19  2177.872559  42270.527344  2217.273438  2196.481201  2226.926514   \n",
              "2023-12-20          NaN           NaN  2177.872559  2217.273438  2196.481201   \n",
              "2023-12-21  2192.711426  43504.792969          NaN  2177.872559  2217.273438   \n",
              "\n",
              "                Price-4      Price-5      Price-6      Price-7  \n",
              "Date                                                            \n",
              "2017-11-09          NaN          NaN          NaN          NaN  \n",
              "2017-11-10          NaN          NaN          NaN          NaN  \n",
              "2017-11-11          NaN          NaN          NaN          NaN  \n",
              "2017-11-12          NaN          NaN          NaN          NaN  \n",
              "2017-11-13   320.884003          NaN          NaN          NaN  \n",
              "...                 ...          ...          ...          ...  \n",
              "2023-12-17  2260.648682  2202.038086  2224.578857  2352.462646  \n",
              "2023-12-18  2316.579102  2260.648682  2202.038086  2224.578857  \n",
              "2023-12-19  2219.337402  2316.579102  2260.648682  2202.038086  \n",
              "2023-12-20  2226.926514  2219.337402  2316.579102  2260.648682  \n",
              "2023-12-21  2196.481201  2226.926514  2219.337402  2316.579102  \n",
              "\n",
              "[2234 rows x 9 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-732704b0-5ea2-4a10-90df-a13c56c3d24e\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Close_eth</th>\n",
              "      <th>Close_btc</th>\n",
              "      <th>Price-1</th>\n",
              "      <th>Price-2</th>\n",
              "      <th>Price-3</th>\n",
              "      <th>Price-4</th>\n",
              "      <th>Price-5</th>\n",
              "      <th>Price-6</th>\n",
              "      <th>Price-7</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2017-11-09</th>\n",
              "      <td>320.884003</td>\n",
              "      <td>7143.580078</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-10</th>\n",
              "      <td>299.252991</td>\n",
              "      <td>6618.140137</td>\n",
              "      <td>320.884003</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-11</th>\n",
              "      <td>314.681000</td>\n",
              "      <td>6357.600098</td>\n",
              "      <td>299.252991</td>\n",
              "      <td>320.884003</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-12</th>\n",
              "      <td>307.907990</td>\n",
              "      <td>5950.069824</td>\n",
              "      <td>314.681000</td>\n",
              "      <td>299.252991</td>\n",
              "      <td>320.884003</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-13</th>\n",
              "      <td>316.716003</td>\n",
              "      <td>6559.490234</td>\n",
              "      <td>307.907990</td>\n",
              "      <td>314.681000</td>\n",
              "      <td>299.252991</td>\n",
              "      <td>320.884003</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</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",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2023-12-17</th>\n",
              "      <td>2196.481201</td>\n",
              "      <td>41364.664063</td>\n",
              "      <td>2226.926514</td>\n",
              "      <td>2219.337402</td>\n",
              "      <td>2316.579102</td>\n",
              "      <td>2260.648682</td>\n",
              "      <td>2202.038086</td>\n",
              "      <td>2224.578857</td>\n",
              "      <td>2352.462646</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2023-12-18</th>\n",
              "      <td>2217.273438</td>\n",
              "      <td>42623.539063</td>\n",
              "      <td>2196.481201</td>\n",
              "      <td>2226.926514</td>\n",
              "      <td>2219.337402</td>\n",
              "      <td>2316.579102</td>\n",
              "      <td>2260.648682</td>\n",
              "      <td>2202.038086</td>\n",
              "      <td>2224.578857</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2023-12-19</th>\n",
              "      <td>2177.872559</td>\n",
              "      <td>42270.527344</td>\n",
              "      <td>2217.273438</td>\n",
              "      <td>2196.481201</td>\n",
              "      <td>2226.926514</td>\n",
              "      <td>2219.337402</td>\n",
              "      <td>2316.579102</td>\n",
              "      <td>2260.648682</td>\n",
              "      <td>2202.038086</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2023-12-20</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2177.872559</td>\n",
              "      <td>2217.273438</td>\n",
              "      <td>2196.481201</td>\n",
              "      <td>2226.926514</td>\n",
              "      <td>2219.337402</td>\n",
              "      <td>2316.579102</td>\n",
              "      <td>2260.648682</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2023-12-21</th>\n",
              "      <td>2192.711426</td>\n",
              "      <td>43504.792969</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2177.872559</td>\n",
              "      <td>2217.273438</td>\n",
              "      <td>2196.481201</td>\n",
              "      <td>2226.926514</td>\n",
              "      <td>2219.337402</td>\n",
              "      <td>2316.579102</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2234 rows × 9 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-732704b0-5ea2-4a10-90df-a13c56c3d24e')\"\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-732704b0-5ea2-4a10-90df-a13c56c3d24e 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-732704b0-5ea2-4a10-90df-a13c56c3d24e');\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-edf24239-1026-4568-859c-302cdcfd887b\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-edf24239-1026-4568-859c-302cdcfd887b')\"\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-edf24239-1026-4568-859c-302cdcfd887b button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_b57d1d5f-51d4-4de6-a915-80c5cd69747c\">\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('eth_prices_windowed')\"\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_b57d1d5f-51d4-4de6-a915-80c5cd69747c button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('eth_prices_windowed');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 112
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Train model on entire data to make prediction for the next day\n",
        "X_all = eth_prices_windowed.drop([\"Close_eth\", \"Close_btc\"], axis=1).dropna().to_numpy() # only want prices, our future model can be a univariate model\n",
        "y_all = eth_prices_windowed.dropna()[\"Close_eth\"].to_numpy()"
      ],
      "metadata": {
        "id": "DFeO6UOx2XQS"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# turn into performance optimized tensorflow datasets\n",
        "\n",
        "# 1. Turn X and y into tensor Datasets\n",
        "features_dataset_all = tf.data.Dataset.from_tensor_slices(X_all)\n",
        "labels_dataset_all = tf.data.Dataset.from_tensor_slices(y_all)\n",
        "\n",
        "# 2. Combine features & labels\n",
        "dataset_all = tf.data.Dataset.zip((features_dataset_all, labels_dataset_all))\n",
        "\n",
        "# 3. Batch and prefetch for optimal performance\n",
        "BATCH_SIZE = 1024 # taken from Appendix D in N-BEATS paper\n",
        "dataset_all = dataset_all.batch(BATCH_SIZE).prefetch(tf.data.AUTOTUNE)\n",
        "\n",
        "dataset_all"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZG71Wuui8H5u",
        "outputId": "7e6b6fc6-2075-4b31-ec27-b064ac77c841"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<_PrefetchDataset element_spec=(TensorSpec(shape=(None, 7), dtype=tf.float64, name=None), TensorSpec(shape=(None,), dtype=tf.float64, name=None))>"
            ]
          },
          "metadata": {},
          "execution_count": 114
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "tf.random.set_seed(42)\n",
        "\n",
        "# Create model (nice and simple, just to test)\n",
        "model_9 = tf.keras.Sequential([\n",
        "  tf.keras.layers.Dense(128, activation=\"relu\"),\n",
        "  tf.keras.layers.Dense(128, activation=\"relu\"),\n",
        "  tf.keras.layers.Dense(HORIZON)\n",
        "])\n",
        "\n",
        "# Compile\n",
        "model_9.compile(loss=tf.keras.losses.mae,\n",
        "                optimizer=tf.keras.optimizers.Adam())\n",
        "\n",
        "# Fit model on all of the data to make future forecasts\n",
        "model_9.fit(dataset_all,\n",
        "            epochs=100) # don't print out anything, we've seen this all before"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hHethGnC2ERs",
        "outputId": "ea2b1d44-a0a9-4edd-bb8b-45b16cbcfb3f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/100\n",
            "3/3 [==============================] - 1s 14ms/step - loss: 1493.5579\n",
            "Epoch 2/100\n",
            "3/3 [==============================] - 0s 14ms/step - loss: 977.7289\n",
            "Epoch 3/100\n",
            "3/3 [==============================] - 0s 14ms/step - loss: 467.8264\n",
            "Epoch 4/100\n",
            "3/3 [==============================] - 0s 11ms/step - loss: 87.2321\n",
            "Epoch 5/100\n",
            "3/3 [==============================] - 0s 16ms/step - loss: 246.5744\n",
            "Epoch 6/100\n",
            "3/3 [==============================] - 0s 12ms/step - loss: 203.7254\n",
            "Epoch 7/100\n",
            "3/3 [==============================] - 0s 11ms/step - loss: 73.0699\n",
            "Epoch 8/100\n",
            "3/3 [==============================] - 0s 11ms/step - loss: 115.4075\n",
            "Epoch 9/100\n",
            "3/3 [==============================] - 0s 12ms/step - loss: 89.3012\n",
            "Epoch 10/100\n",
            "3/3 [==============================] - 0s 13ms/step - loss: 77.9560\n",
            "Epoch 11/100\n",
            "3/3 [==============================] - 0s 11ms/step - loss: 90.2601\n",
            "Epoch 12/100\n",
            "3/3 [==============================] - 0s 9ms/step - loss: 66.9725\n",
            "Epoch 13/100\n",
            "3/3 [==============================] - 0s 12ms/step - loss: 76.0583\n",
            "Epoch 14/100\n",
            "3/3 [==============================] - 0s 14ms/step - loss: 65.8404\n",
            "Epoch 15/100\n",
            "3/3 [==============================] - 0s 11ms/step - loss: 69.3883\n",
            "Epoch 16/100\n",
            "3/3 [==============================] - 0s 14ms/step - loss: 65.4350\n",
            "Epoch 17/100\n",
            "3/3 [==============================] - 0s 11ms/step - loss: 66.6796\n",
            "Epoch 18/100\n",
            "3/3 [==============================] - 0s 12ms/step - loss: 65.0062\n",
            "Epoch 19/100\n",
            "3/3 [==============================] - 0s 10ms/step - loss: 63.5425\n",
            "Epoch 20/100\n",
            "3/3 [==============================] - 0s 13ms/step - loss: 64.9365\n",
            "Epoch 21/100\n",
            "3/3 [==============================] - 0s 9ms/step - loss: 61.6438\n",
            "Epoch 22/100\n",
            "3/3 [==============================] - 0s 13ms/step - loss: 60.7881\n",
            "Epoch 23/100\n",
            "3/3 [==============================] - 0s 10ms/step - loss: 61.4946\n",
            "Epoch 24/100\n",
            "3/3 [==============================] - 0s 11ms/step - loss: 59.2039\n",
            "Epoch 25/100\n",
            "3/3 [==============================] - 0s 10ms/step - loss: 58.2988\n",
            "Epoch 26/100\n",
            "3/3 [==============================] - 0s 9ms/step - loss: 59.5636\n",
            "Epoch 27/100\n",
            "3/3 [==============================] - 0s 9ms/step - loss: 57.7417\n",
            "Epoch 28/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 56.7711\n",
            "Epoch 29/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 56.1869\n",
            "Epoch 30/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 55.3561\n",
            "Epoch 31/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 55.4743\n",
            "Epoch 32/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 54.4239\n",
            "Epoch 33/100\n",
            "3/3 [==============================] - 0s 10ms/step - loss: 54.3375\n",
            "Epoch 34/100\n",
            "3/3 [==============================] - 0s 6ms/step - loss: 53.4562\n",
            "Epoch 35/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 53.3331\n",
            "Epoch 36/100\n",
            "3/3 [==============================] - 0s 8ms/step - loss: 52.3381\n",
            "Epoch 37/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 53.5218\n",
            "Epoch 38/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 53.3705\n",
            "Epoch 39/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 54.3470\n",
            "Epoch 40/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 53.9836\n",
            "Epoch 41/100\n",
            "3/3 [==============================] - 0s 8ms/step - loss: 52.3609\n",
            "Epoch 42/100\n",
            "3/3 [==============================] - 0s 9ms/step - loss: 51.4279\n",
            "Epoch 43/100\n",
            "3/3 [==============================] - 0s 9ms/step - loss: 51.1112\n",
            "Epoch 44/100\n",
            "3/3 [==============================] - 0s 8ms/step - loss: 50.7559\n",
            "Epoch 45/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 52.2663\n",
            "Epoch 46/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 53.4609\n",
            "Epoch 47/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 52.1956\n",
            "Epoch 48/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 51.3540\n",
            "Epoch 49/100\n",
            "3/3 [==============================] - 0s 10ms/step - loss: 50.4608\n",
            "Epoch 50/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 50.2221\n",
            "Epoch 51/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 49.9874\n",
            "Epoch 52/100\n",
            "3/3 [==============================] - 0s 8ms/step - loss: 50.2382\n",
            "Epoch 53/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 49.9022\n",
            "Epoch 54/100\n",
            "3/3 [==============================] - 0s 6ms/step - loss: 49.8555\n",
            "Epoch 55/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 49.1072\n",
            "Epoch 56/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 49.3738\n",
            "Epoch 57/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 49.0560\n",
            "Epoch 58/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 49.4180\n",
            "Epoch 59/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 48.8086\n",
            "Epoch 60/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 48.7732\n",
            "Epoch 61/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 48.3633\n",
            "Epoch 62/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 49.0820\n",
            "Epoch 63/100\n",
            "3/3 [==============================] - 0s 8ms/step - loss: 48.7791\n",
            "Epoch 64/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 48.6925\n",
            "Epoch 65/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 48.3658\n",
            "Epoch 66/100\n",
            "3/3 [==============================] - 0s 9ms/step - loss: 48.5771\n",
            "Epoch 67/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 48.4781\n",
            "Epoch 68/100\n",
            "3/3 [==============================] - 0s 9ms/step - loss: 48.4754\n",
            "Epoch 69/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 48.5373\n",
            "Epoch 70/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 48.3003\n",
            "Epoch 71/100\n",
            "3/3 [==============================] - 0s 8ms/step - loss: 47.8681\n",
            "Epoch 72/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 47.7792\n",
            "Epoch 73/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 47.8189\n",
            "Epoch 74/100\n",
            "3/3 [==============================] - 0s 8ms/step - loss: 48.1912\n",
            "Epoch 75/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 48.1201\n",
            "Epoch 76/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 47.3612\n",
            "Epoch 77/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 47.0489\n",
            "Epoch 78/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 47.2034\n",
            "Epoch 79/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 47.3428\n",
            "Epoch 80/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 48.1737\n",
            "Epoch 81/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 47.1634\n",
            "Epoch 82/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 47.0240\n",
            "Epoch 83/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 46.8209\n",
            "Epoch 84/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 47.0417\n",
            "Epoch 85/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 47.0141\n",
            "Epoch 86/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 47.4235\n",
            "Epoch 87/100\n",
            "3/3 [==============================] - 0s 8ms/step - loss: 46.7743\n",
            "Epoch 88/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 46.8959\n",
            "Epoch 89/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 46.7046\n",
            "Epoch 90/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 46.7398\n",
            "Epoch 91/100\n",
            "3/3 [==============================] - 0s 9ms/step - loss: 46.6651\n",
            "Epoch 92/100\n",
            "3/3 [==============================] - 0s 10ms/step - loss: 46.7939\n",
            "Epoch 93/100\n",
            "3/3 [==============================] - 0s 8ms/step - loss: 46.6413\n",
            "Epoch 94/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 46.8261\n",
            "Epoch 95/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 46.2786\n",
            "Epoch 96/100\n",
            "3/3 [==============================] - 0s 8ms/step - loss: 46.5273\n",
            "Epoch 97/100\n",
            "3/3 [==============================] - 0s 6ms/step - loss: 46.6488\n",
            "Epoch 98/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 46.7361\n",
            "Epoch 99/100\n",
            "3/3 [==============================] - 0s 9ms/step - loss: 46.2547\n",
            "Epoch 100/100\n",
            "3/3 [==============================] - 0s 7ms/step - loss: 46.1683\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<keras.src.callbacks.History at 0x78ea7a4ca050>"
            ]
          },
          "metadata": {},
          "execution_count": 116
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "INTO_FUTURE = 14"
      ],
      "metadata": {
        "id": "WuatCTcV8kp1"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# 1. Create function to make predictions into the future\n",
        "def make_future_forecast(values, model, into_future, window_size=WINDOW_SIZE) -> list:\n",
        "  \"\"\"\n",
        "  Makes future forecasts into_future steps after values ends.\n",
        "\n",
        "  Returns future forecasts as list of floats.\n",
        "  \"\"\"\n",
        "  # 2. Make an empty list for future forecasts/prepare data to forecast on\n",
        "  future_forecast = []\n",
        "  last_window = values[-WINDOW_SIZE:] # only want preds from the last window (this will get updated)\n",
        "\n",
        "  # 3. Make INTO_FUTURE number of predictions, altering the data which gets predicted on each time\n",
        "  for _ in range(into_future):\n",
        "\n",
        "    # Predict on last window then append it again, again, again (model starts to make forecasts on its own forecasts)\n",
        "    future_pred = model.predict(tf.expand_dims(last_window, axis=0))\n",
        "    print(f\"Predicting on: \\n {last_window} -> Prediction: {tf.squeeze(future_pred).numpy()}\\n\")\n",
        "\n",
        "    # Append predictions to future_forecast\n",
        "    future_forecast.append(tf.squeeze(future_pred).numpy())\n",
        "    # print(future_forecast)\n",
        "\n",
        "    # Update last window with new pred and get WINDOW_SIZE most recent preds (model was trained on WINDOW_SIZE windows)\n",
        "    last_window = np.append(last_window, future_pred)[-WINDOW_SIZE:]\n",
        "\n",
        "  return future_forecast\n"
      ],
      "metadata": {
        "id": "vUDBTFx48xRd"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "future_forecast = make_future_forecast(values=y_all,\n",
        "                                       model=model_9,\n",
        "                                       into_future=INTO_FUTURE,\n",
        "                                       window_size=WINDOW_SIZE)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2K2KQEKo80rp",
        "outputId": "ce5e6218-fcf4-4dd3-93a1-078f1cf080b3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1/1 [==============================] - 0s 61ms/step\n",
            "Predicting on: \n",
            " [2260.648682 2316.579102 2219.337402 2226.926514 2196.481201 2217.273438\n",
            " 2177.872559] -> Prediction: 2275.55078125\n",
            "\n",
            "1/1 [==============================] - 0s 21ms/step\n",
            "Predicting on: \n",
            " [2316.579102   2219.337402   2226.926514   2196.481201   2217.273438\n",
            " 2177.872559   2275.55078125] -> Prediction: 2281.18994140625\n",
            "\n",
            "1/1 [==============================] - 0s 23ms/step\n",
            "Predicting on: \n",
            " [2219.337402   2226.926514   2196.481201   2217.273438   2177.872559\n",
            " 2275.55078125 2281.18994141] -> Prediction: 2223.95458984375\n",
            "\n",
            "1/1 [==============================] - 0s 21ms/step\n",
            "Predicting on: \n",
            " [2226.926514   2196.481201   2217.273438   2177.872559   2275.55078125\n",
            " 2281.18994141 2223.95458984] -> Prediction: 2217.71826171875\n",
            "\n",
            "1/1 [==============================] - 0s 20ms/step\n",
            "Predicting on: \n",
            " [2196.481201   2217.273438   2177.872559   2275.55078125 2281.18994141\n",
            " 2223.95458984 2217.71826172] -> Prediction: 2198.05322265625\n",
            "\n",
            "1/1 [==============================] - 0s 20ms/step\n",
            "Predicting on: \n",
            " [2217.273438   2177.872559   2275.55078125 2281.18994141 2223.95458984\n",
            " 2217.71826172 2198.05322266] -> Prediction: 2225.58203125\n",
            "\n",
            "1/1 [==============================] - 0s 21ms/step\n",
            "Predicting on: \n",
            " [2177.872559   2275.55078125 2281.18994141 2223.95458984 2217.71826172\n",
            " 2198.05322266 2225.58203125] -> Prediction: 2228.75390625\n",
            "\n",
            "1/1 [==============================] - 0s 23ms/step\n",
            "Predicting on: \n",
            " [2275.55078125 2281.18994141 2223.95458984 2217.71826172 2198.05322266\n",
            " 2225.58203125 2228.75390625] -> Prediction: 2275.3193359375\n",
            "\n",
            "1/1 [==============================] - 0s 21ms/step\n",
            "Predicting on: \n",
            " [2281.18994141 2223.95458984 2217.71826172 2198.05322266 2225.58203125\n",
            " 2228.75390625 2275.31933594] -> Prediction: 2259.61767578125\n",
            "\n",
            "1/1 [==============================] - 0s 30ms/step\n",
            "Predicting on: \n",
            " [2223.95458984 2217.71826172 2198.05322266 2225.58203125 2228.75390625\n",
            " 2275.31933594 2259.61767578] -> Prediction: 2221.23046875\n",
            "\n",
            "1/1 [==============================] - 0s 33ms/step\n",
            "Predicting on: \n",
            " [2217.71826172 2198.05322266 2225.58203125 2228.75390625 2275.31933594\n",
            " 2259.61767578 2221.23046875] -> Prediction: 2215.5068359375\n",
            "\n",
            "1/1 [==============================] - 0s 30ms/step\n",
            "Predicting on: \n",
            " [2198.05322266 2225.58203125 2228.75390625 2275.31933594 2259.61767578\n",
            " 2221.23046875 2215.50683594] -> Prediction: 2213.885986328125\n",
            "\n",
            "1/1 [==============================] - 0s 30ms/step\n",
            "Predicting on: \n",
            " [2225.58203125 2228.75390625 2275.31933594 2259.61767578 2221.23046875\n",
            " 2215.50683594 2213.88598633] -> Prediction: 2243.296142578125\n",
            "\n",
            "1/1 [==============================] - 0s 34ms/step\n",
            "Predicting on: \n",
            " [2228.75390625 2275.31933594 2259.61767578 2221.23046875 2215.50683594\n",
            " 2213.88598633 2243.29614258] -> Prediction: 2253.328857421875\n",
            "\n"
          ]
        }
      ]
    }
  ]
}