Copy_of_Lab_FTX.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/jpwrk/DS1002/blob/main/Copy_of_Lab_FTX.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# DS1002 Lab 1:  FTX\n",
        "\n",
        "### Due Monday 1 April at noon\n",
        "\n",
        "In this lab you will work with a dataset, writing python to generate the deliverables specified in the cells below.\n",
        "\n",
        "> **FTX** was a cryptocurrency exchange founded by Sam Bankman-Fried that saw both a spectacular rise and collapse between 2021 and 2022. At one point it had a valuation of $32B. In November Bankman-Fried was found guilty on seven counts of fraud and conspiracy.  His sentencing hearing is today.\n",
        "\n",
        "The dataset for this assignment covers that rise and fall from the viewpoint of daily stock closing prices for FTX (ticker symbol `FTT`).\n",
        "\n",
        "Answer the questions below with the appropriate Python code.\n",
        "\n",
        "**Put code and outputs in this notebook.**\n"
      ],
      "metadata": {
        "id": "2yEePrJ-1G1Z"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Group Submissions\n",
        "\n",
        "As usual you may work in a group to complete this lab, with no more than 3 members in a group. Group members should be indicated in the cell below -- list both names and UVA computing IDs.\n",
        "\n",
        "Each student should then submit **the same URL** for the lab in Canvas. (If a group has Member1, Member2, and Member3, only one member needs to save the completed work back to GitHub and all members should submit that URL for grading.)"
      ],
      "metadata": {
        "id": "acXFkytd2PWS"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# List group members (if applicable). Identify names and computing IDs\n",
        "#\n",
        "# Name                    Computing ID"
      ],
      "metadata": {
        "id": "4N8_o3tG232h"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 1. Load Libraries & Data\n",
        "\n",
        "https://s3.amazonaws.com/ds1002-resources/data/ftx-2021-01-01--2023-12-31.csv\n",
        "\n",
        "Import any necessary libraries and load the remote CSV file below into a DataFrame. **Resolve any import issues you need to.**"
      ],
      "metadata": {
        "id": "w0VxTDNf1k2O"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 47,
      "metadata": {
        "id": "I0B9chFD1GR0"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "\n",
        "data = pd.read_excel('./ftx-final.xlsx')"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 2. Get Summary Data"
      ],
      "metadata": {
        "id": "H389W9dkobGI"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "In code, display how many rows and columns are in the raw dataset."
      ],
      "metadata": {
        "id": "KA0wbjmE-4Q9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "len(data.columns)"
      ],
      "metadata": {
        "id": "XhULtu7qox-p",
        "outputId": "e1b41a3e-5b76-4455-ac1b-c1768cfae1d4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "11"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(data.index)"
      ],
      "metadata": {
        "id": "JoF-yxWZ4hcX",
        "outputId": "ec471e5d-c746-4a19-acb0-40d058f8944d",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "741"
            ]
          },
          "metadata": {},
          "execution_count": 55
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 3. Clean and Organize the Data\n",
        "\n",
        "Check for data quality.\n",
        "\n",
        "- Resolve any empty values or duplicate rows.\n",
        "- Order the data properly if necessary.\n",
        "- Drop the following columns and save the dataframe: `timeOpen`, `timeClose`, `timeHigh`, `timeLow`, `marketCap`\n",
        "\n"
      ],
      "metadata": {
        "id": "abshX7QeooAs"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data_clean = data.drop_duplicates()"
      ],
      "metadata": {
        "id": "Aq3J7yD82uwW"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "final_data = data_clean.dropna()"
      ],
      "metadata": {
        "id": "L8pJWAderITG"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "columns_dropped = ['timeOpen', 'timeClose', 'timeHigh', 'timeLow', 'marketCap']"
      ],
      "metadata": {
        "id": "Dmco-yKZs1ch"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data_frame = final_data.drop(['timeOpen', 'timeClose', 'timeHigh', 'timeLow', 'marketCap'], axis=1)"
      ],
      "metadata": {
        "id": "uo2ATbqgr2Io"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Now display the first 10 rows of the cleaned dataset."
      ],
      "metadata": {
        "id": "Ccwu8bUx_Azj"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data_frame.head(11)"
      ],
      "metadata": {
        "id": "1iVIskCs_Ewe",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 394
        },
        "outputId": "304a27d9-c388-4564-cddb-0f063e4fc883"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        open      high       low     close       volume  \\\n",
              "0   0.838968  0.853502  0.835226  0.842688   3001502.06   \n",
              "1   0.860193  0.864752  0.826643  0.839048   3608615.07   \n",
              "2   0.885723  0.887118  0.843029  0.860231   3766979.57   \n",
              "3   0.921162  0.925702  0.869842  0.886091   4192949.85   \n",
              "4   0.931138  0.955402  0.916414  0.923668   4574953.05   \n",
              "5   0.894567  1.011183  0.893652  0.930696   7065306.21   \n",
              "6   0.924432  0.935517  0.894370  0.894657   2577834.83   \n",
              "7   0.957505  0.975671  0.921085  0.924433   5055004.16   \n",
              "8   1.027133  1.038282  0.948058  0.957006  17088962.94   \n",
              "9   0.873973  1.127198  0.835625  1.027162  22418556.51   \n",
              "10  0.938134  0.938586  0.860896  0.873704   4393351.59   \n",
              "\n",
              "                   timestamp  \n",
              "0   2022-12-31T23:59:59.999Z  \n",
              "1   2022-12-30T23:59:59.999Z  \n",
              "2   2022-12-29T23:59:59.999Z  \n",
              "3   2022-12-28T23:59:59.999Z  \n",
              "4   2022-12-27T23:59:59.999Z  \n",
              "5   2022-12-26T23:59:59.999Z  \n",
              "6   2022-12-25T23:59:59.999Z  \n",
              "7   2022-12-24T23:59:59.999Z  \n",
              "8   2022-12-23T23:59:59.999Z  \n",
              "9   2022-12-22T23:59:59.999Z  \n",
              "10  2022-12-21T23:59:59.999Z  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-8f2e3ae1-3d4e-4782-bb4a-21f33559cc2a\" 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>volume</th>\n",
              "      <th>timestamp</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.838968</td>\n",
              "      <td>0.853502</td>\n",
              "      <td>0.835226</td>\n",
              "      <td>0.842688</td>\n",
              "      <td>3001502.06</td>\n",
              "      <td>2022-12-31T23:59:59.999Z</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.860193</td>\n",
              "      <td>0.864752</td>\n",
              "      <td>0.826643</td>\n",
              "      <td>0.839048</td>\n",
              "      <td>3608615.07</td>\n",
              "      <td>2022-12-30T23:59:59.999Z</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.885723</td>\n",
              "      <td>0.887118</td>\n",
              "      <td>0.843029</td>\n",
              "      <td>0.860231</td>\n",
              "      <td>3766979.57</td>\n",
              "      <td>2022-12-29T23:59:59.999Z</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.921162</td>\n",
              "      <td>0.925702</td>\n",
              "      <td>0.869842</td>\n",
              "      <td>0.886091</td>\n",
              "      <td>4192949.85</td>\n",
              "      <td>2022-12-28T23:59:59.999Z</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.931138</td>\n",
              "      <td>0.955402</td>\n",
              "      <td>0.916414</td>\n",
              "      <td>0.923668</td>\n",
              "      <td>4574953.05</td>\n",
              "      <td>2022-12-27T23:59:59.999Z</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>0.894567</td>\n",
              "      <td>1.011183</td>\n",
              "      <td>0.893652</td>\n",
              "      <td>0.930696</td>\n",
              "      <td>7065306.21</td>\n",
              "      <td>2022-12-26T23:59:59.999Z</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>0.924432</td>\n",
              "      <td>0.935517</td>\n",
              "      <td>0.894370</td>\n",
              "      <td>0.894657</td>\n",
              "      <td>2577834.83</td>\n",
              "      <td>2022-12-25T23:59:59.999Z</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>0.957505</td>\n",
              "      <td>0.975671</td>\n",
              "      <td>0.921085</td>\n",
              "      <td>0.924433</td>\n",
              "      <td>5055004.16</td>\n",
              "      <td>2022-12-24T23:59:59.999Z</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>1.027133</td>\n",
              "      <td>1.038282</td>\n",
              "      <td>0.948058</td>\n",
              "      <td>0.957006</td>\n",
              "      <td>17088962.94</td>\n",
              "      <td>2022-12-23T23:59:59.999Z</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>0.873973</td>\n",
              "      <td>1.127198</td>\n",
              "      <td>0.835625</td>\n",
              "      <td>1.027162</td>\n",
              "      <td>22418556.51</td>\n",
              "      <td>2022-12-22T23:59:59.999Z</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>0.938134</td>\n",
              "      <td>0.938586</td>\n",
              "      <td>0.860896</td>\n",
              "      <td>0.873704</td>\n",
              "      <td>4393351.59</td>\n",
              "      <td>2022-12-21T23:59:59.999Z</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-8f2e3ae1-3d4e-4782-bb4a-21f33559cc2a')\"\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-8f2e3ae1-3d4e-4782-bb4a-21f33559cc2a 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-8f2e3ae1-3d4e-4782-bb4a-21f33559cc2a');\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-b240a79c-25d6-448f-8bea-dd058526a114\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-b240a79c-25d6-448f-8bea-dd058526a114')\"\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-b240a79c-25d6-448f-8bea-dd058526a114 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "data_frame",
              "summary": "{\n  \"name\": \"data_frame\",\n  \"rows\": 727,\n  \"fields\": [\n    {\n      \"column\": \"open\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 16.1035338133042,\n        \"min\": 0.8389684425,\n        \"max\": 79.52836962,\n        \"num_unique_values\": 727,\n        \"samples\": [\n          35.95654525,\n          13.24616686,\n          37.5674349164\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"high\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 16.787965749134525,\n        \"min\": 0.853501666,\n        \"max\": 85.0168524,\n        \"num_unique_values\": 727,\n        \"samples\": [\n          38.1509959,\n          14.84458089,\n          40.2846120528\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"low\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 15.450005209358025,\n        \"min\": 0.8266428992,\n        \"max\": 71.9259352,\n        \"num_unique_values\": 727,\n        \"samples\": [\n          34.44777827,\n          13.24616686,\n          37.3302258384\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"close\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 16.110665264905244,\n        \"min\": 0.8390481756,\n        \"max\": 79.87131341,\n        \"num_unique_values\": 727,\n        \"samples\": [\n          37.74977039,\n          14.84458089,\n          39.8977878501\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"volume\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 334134232.9378182,\n        \"min\": 2577834.83,\n        \"max\": 3919748072.71,\n        \"num_unique_values\": 727,\n        \"samples\": [\n          75863474.17,\n          43477028.95,\n          110481935.78\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"timestamp\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"num_unique_values\": 727,\n        \"samples\": [\n          \"2021-08-04T23:59:59.999Z\",\n          \"2021-02-05T23:59:59.999Z\",\n          \"2021-12-18T23:59:59.999Z\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 4. Calculate Daily Gains/Losses"
      ],
      "metadata": {
        "id": "3-4dd8nsr_zF"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Using Pandas, add a new column named `[\"close_change\"]` to the dataframe that calculates the difference between daily closing prices for FTX. This will result in positive (growth) and negative (loss) values.\n",
        "\n",
        "Note:\n",
        "- Be careful about how you calculate this. Each row should calculate that difference from the row above it, which must be the previous calendar day.\n",
        "- Hint: This is not complicated and does not require a for-loop.  See the Pandas review notebook for reference."
      ],
      "metadata": {
        "id": "HrGLlM83vH0c"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data_frame['close_change'] = data_frame['close'].diff()\n",
        "data_frame.close_change"
      ],
      "metadata": {
        "id": "7P8J0jEtvCiv",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b7160468-242c-4565-c3a0-d5d7578f3b82"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0           NaN\n",
              "1     -0.003640\n",
              "2      0.021183\n",
              "3      0.025860\n",
              "4      0.037577\n",
              "         ...   \n",
              "735    0.181143\n",
              "736   -0.171334\n",
              "737   -0.726110\n",
              "738   -1.150608\n",
              "739   -0.590111\n",
              "Name: close_change, Length: 727, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 5. Identify Growth Days"
      ],
      "metadata": {
        "id": "KKg8d9RDyeDa"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Based on the daily change in closing prices calculated above, identify the top 10 days of positive growth for FTX.\n",
        "\n",
        "Display your results in a table showing both the rate of change and their dates."
      ],
      "metadata": {
        "id": "5kKBo3_sykGD"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "growth_days = data_frame.sort_values(by='close_change', ascending=False)"
      ],
      "metadata": {
        "id": "xRlliRMY2_-c"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "top_10_growth_days = growth_days.head(10)\n",
        "top_10_growth_days"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "id": "NHJOjyVmWmgg",
        "outputId": "f850344f-1678-4cbd-9371-8b1a3c9d64c2"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          open       high        low      close        volume  \\\n",
              "56   22.263740  23.151038  21.923954  22.142196  7.211689e+08   \n",
              "468  71.161896  71.519686  66.035973  67.482300  4.886910e+08   \n",
              "598  50.424719  54.028511  50.015720  50.955200  1.552346e+08   \n",
              "478  67.676450  72.960747  66.715633  71.181617  5.739419e+08   \n",
              "473  63.646636  63.964677  59.981068  60.813879  4.261729e+08   \n",
              "484  77.694911  85.016852  71.891980  79.871313  3.338582e+09   \n",
              "350  46.731222  49.846724  45.218760  45.225963  2.595717e+08   \n",
              "594  36.064557  36.743029  32.408227  33.298743  1.336769e+08   \n",
              "481  72.638122  77.945811  70.939263  73.528094  9.845208e+08   \n",
              "605  59.203232  61.358692  57.460908  61.283271  1.261705e+08   \n",
              "\n",
              "                    timestamp  close_change  \n",
              "56   2022-11-07T23:59:59.999Z     16.623292  \n",
              "468  2021-09-16T23:59:59.999Z     14.497738  \n",
              "598  2021-05-18T23:59:59.999Z     14.017812  \n",
              "478  2021-09-15T23:59:59.999Z      9.506381  \n",
              "473  2021-09-19T23:59:59.999Z      8.315742  \n",
              "484  2021-09-09T23:59:59.999Z      6.929033  \n",
              "350  2022-01-20T23:59:59.999Z      6.770635  \n",
              "594  2021-05-22T23:59:59.999Z      6.228516  \n",
              "481  2021-09-12T23:59:59.999Z      5.201864  \n",
              "605  2021-05-11T23:59:59.999Z      5.154806  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-8b3ba469-9872-403f-838d-bb1020b2a882\" 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>volume</th>\n",
              "      <th>timestamp</th>\n",
              "      <th>close_change</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>56</th>\n",
              "      <td>22.263740</td>\n",
              "      <td>23.151038</td>\n",
              "      <td>21.923954</td>\n",
              "      <td>22.142196</td>\n",
              "      <td>7.211689e+08</td>\n",
              "      <td>2022-11-07T23:59:59.999Z</td>\n",
              "      <td>16.623292</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>468</th>\n",
              "      <td>71.161896</td>\n",
              "      <td>71.519686</td>\n",
              "      <td>66.035973</td>\n",
              "      <td>67.482300</td>\n",
              "      <td>4.886910e+08</td>\n",
              "      <td>2021-09-16T23:59:59.999Z</td>\n",
              "      <td>14.497738</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>598</th>\n",
              "      <td>50.424719</td>\n",
              "      <td>54.028511</td>\n",
              "      <td>50.015720</td>\n",
              "      <td>50.955200</td>\n",
              "      <td>1.552346e+08</td>\n",
              "      <td>2021-05-18T23:59:59.999Z</td>\n",
              "      <td>14.017812</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>478</th>\n",
              "      <td>67.676450</td>\n",
              "      <td>72.960747</td>\n",
              "      <td>66.715633</td>\n",
              "      <td>71.181617</td>\n",
              "      <td>5.739419e+08</td>\n",
              "      <td>2021-09-15T23:59:59.999Z</td>\n",
              "      <td>9.506381</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>473</th>\n",
              "      <td>63.646636</td>\n",
              "      <td>63.964677</td>\n",
              "      <td>59.981068</td>\n",
              "      <td>60.813879</td>\n",
              "      <td>4.261729e+08</td>\n",
              "      <td>2021-09-19T23:59:59.999Z</td>\n",
              "      <td>8.315742</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>484</th>\n",
              "      <td>77.694911</td>\n",
              "      <td>85.016852</td>\n",
              "      <td>71.891980</td>\n",
              "      <td>79.871313</td>\n",
              "      <td>3.338582e+09</td>\n",
              "      <td>2021-09-09T23:59:59.999Z</td>\n",
              "      <td>6.929033</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>350</th>\n",
              "      <td>46.731222</td>\n",
              "      <td>49.846724</td>\n",
              "      <td>45.218760</td>\n",
              "      <td>45.225963</td>\n",
              "      <td>2.595717e+08</td>\n",
              "      <td>2022-01-20T23:59:59.999Z</td>\n",
              "      <td>6.770635</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>594</th>\n",
              "      <td>36.064557</td>\n",
              "      <td>36.743029</td>\n",
              "      <td>32.408227</td>\n",
              "      <td>33.298743</td>\n",
              "      <td>1.336769e+08</td>\n",
              "      <td>2021-05-22T23:59:59.999Z</td>\n",
              "      <td>6.228516</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>481</th>\n",
              "      <td>72.638122</td>\n",
              "      <td>77.945811</td>\n",
              "      <td>70.939263</td>\n",
              "      <td>73.528094</td>\n",
              "      <td>9.845208e+08</td>\n",
              "      <td>2021-09-12T23:59:59.999Z</td>\n",
              "      <td>5.201864</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>605</th>\n",
              "      <td>59.203232</td>\n",
              "      <td>61.358692</td>\n",
              "      <td>57.460908</td>\n",
              "      <td>61.283271</td>\n",
              "      <td>1.261705e+08</td>\n",
              "      <td>2021-05-11T23:59:59.999Z</td>\n",
              "      <td>5.154806</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-8b3ba469-9872-403f-838d-bb1020b2a882')\"\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-8b3ba469-9872-403f-838d-bb1020b2a882 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-8b3ba469-9872-403f-838d-bb1020b2a882');\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-947e0ecb-8a19-4499-a73d-352d6b5f3814\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-947e0ecb-8a19-4499-a73d-352d6b5f3814')\"\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-947e0ecb-8a19-4499-a73d-352d6b5f3814 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_721ac688-de60-440d-8c36-c9458e0cf8e4\">\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('top_10_growth_days')\"\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_721ac688-de60-440d-8c36-c9458e0cf8e4 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('top_10_growth_days');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "top_10_growth_days",
              "repr_error": "0"
            }
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 6. Calculate the Percentage Rate of Change"
      ],
      "metadata": {
        "id": "Y3AmR3eDxgfb"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Next, create a new column named `[\"rate_of_change\"]` based on `[\"close_change\"]`.\n",
        "\n",
        "Use the Pandas Review notebook for reference. Again, this is an easy operation in Pandas and does not require a for-loop."
      ],
      "metadata": {
        "id": "XK3yweENxjdn"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data_frame['rate_of_change'] = (data_frame['close_change']/data_frame['close'])*10"
      ],
      "metadata": {
        "id": "FqL5yyvi6w7r"
      },
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data_frame"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "Ofbb8FJ4X7V3",
        "outputId": "9416ba06-dd4a-4270-c6be-0ccf2dc7b04f"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         open       high       low     close       volume  \\\n",
              "0    0.838968   0.853502  0.835226  0.842688   3001502.06   \n",
              "1    0.860193   0.864752  0.826643  0.839048   3608615.07   \n",
              "2    0.885723   0.887118  0.843029  0.860231   3766979.57   \n",
              "3    0.921162   0.925702  0.869842  0.886091   4192949.85   \n",
              "4    0.931138   0.955402  0.916414  0.923668   4574953.05   \n",
              "..        ...        ...       ...       ...          ...   \n",
              "735  9.386493  10.004872  9.215244  9.562131  46303336.73   \n",
              "736  8.671285   9.390797  8.425946  9.390797  31404627.93   \n",
              "737  7.528216   8.714947  7.081120  8.664688  49479278.39   \n",
              "738  6.948680   7.632146  6.358218  7.514079  40526109.15   \n",
              "739  6.201133   7.007523  6.171834  6.923968  31046652.87   \n",
              "\n",
              "                    timestamp  close_change  rate_of_change  \n",
              "0    2022-12-31T23:59:59.999Z           NaN             NaN  \n",
              "1    2022-12-30T23:59:59.999Z     -0.003640       -0.043385  \n",
              "2    2022-12-29T23:59:59.999Z      0.021183        0.246248  \n",
              "3    2022-12-28T23:59:59.999Z      0.025860        0.291840  \n",
              "4    2022-12-27T23:59:59.999Z      0.037577        0.406822  \n",
              "..                        ...           ...             ...  \n",
              "735  2021-01-07T23:59:59.999Z      0.181143        0.189437  \n",
              "736  2021-01-06T23:59:59.999Z     -0.171334       -0.182448  \n",
              "737  2021-01-05T23:59:59.999Z     -0.726110       -0.838010  \n",
              "738  2021-01-04T23:59:59.999Z     -1.150608       -1.531270  \n",
              "739  2021-01-03T23:59:59.999Z     -0.590111       -0.852273  \n",
              "\n",
              "[727 rows x 8 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-caa556bd-bacb-47cc-9537-b7f518eb69bd\" 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>volume</th>\n",
              "      <th>timestamp</th>\n",
              "      <th>close_change</th>\n",
              "      <th>rate_of_change</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.838968</td>\n",
              "      <td>0.853502</td>\n",
              "      <td>0.835226</td>\n",
              "      <td>0.842688</td>\n",
              "      <td>3001502.06</td>\n",
              "      <td>2022-12-31T23:59:59.999Z</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.860193</td>\n",
              "      <td>0.864752</td>\n",
              "      <td>0.826643</td>\n",
              "      <td>0.839048</td>\n",
              "      <td>3608615.07</td>\n",
              "      <td>2022-12-30T23:59:59.999Z</td>\n",
              "      <td>-0.003640</td>\n",
              "      <td>-0.043385</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.885723</td>\n",
              "      <td>0.887118</td>\n",
              "      <td>0.843029</td>\n",
              "      <td>0.860231</td>\n",
              "      <td>3766979.57</td>\n",
              "      <td>2022-12-29T23:59:59.999Z</td>\n",
              "      <td>0.021183</td>\n",
              "      <td>0.246248</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.921162</td>\n",
              "      <td>0.925702</td>\n",
              "      <td>0.869842</td>\n",
              "      <td>0.886091</td>\n",
              "      <td>4192949.85</td>\n",
              "      <td>2022-12-28T23:59:59.999Z</td>\n",
              "      <td>0.025860</td>\n",
              "      <td>0.291840</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.931138</td>\n",
              "      <td>0.955402</td>\n",
              "      <td>0.916414</td>\n",
              "      <td>0.923668</td>\n",
              "      <td>4574953.05</td>\n",
              "      <td>2022-12-27T23:59:59.999Z</td>\n",
              "      <td>0.037577</td>\n",
              "      <td>0.406822</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>735</th>\n",
              "      <td>9.386493</td>\n",
              "      <td>10.004872</td>\n",
              "      <td>9.215244</td>\n",
              "      <td>9.562131</td>\n",
              "      <td>46303336.73</td>\n",
              "      <td>2021-01-07T23:59:59.999Z</td>\n",
              "      <td>0.181143</td>\n",
              "      <td>0.189437</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>736</th>\n",
              "      <td>8.671285</td>\n",
              "      <td>9.390797</td>\n",
              "      <td>8.425946</td>\n",
              "      <td>9.390797</td>\n",
              "      <td>31404627.93</td>\n",
              "      <td>2021-01-06T23:59:59.999Z</td>\n",
              "      <td>-0.171334</td>\n",
              "      <td>-0.182448</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>737</th>\n",
              "      <td>7.528216</td>\n",
              "      <td>8.714947</td>\n",
              "      <td>7.081120</td>\n",
              "      <td>8.664688</td>\n",
              "      <td>49479278.39</td>\n",
              "      <td>2021-01-05T23:59:59.999Z</td>\n",
              "      <td>-0.726110</td>\n",
              "      <td>-0.838010</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>738</th>\n",
              "      <td>6.948680</td>\n",
              "      <td>7.632146</td>\n",
              "      <td>6.358218</td>\n",
              "      <td>7.514079</td>\n",
              "      <td>40526109.15</td>\n",
              "      <td>2021-01-04T23:59:59.999Z</td>\n",
              "      <td>-1.150608</td>\n",
              "      <td>-1.531270</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>739</th>\n",
              "      <td>6.201133</td>\n",
              "      <td>7.007523</td>\n",
              "      <td>6.171834</td>\n",
              "      <td>6.923968</td>\n",
              "      <td>31046652.87</td>\n",
              "      <td>2021-01-03T23:59:59.999Z</td>\n",
              "      <td>-0.590111</td>\n",
              "      <td>-0.852273</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>727 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-caa556bd-bacb-47cc-9537-b7f518eb69bd')\"\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-caa556bd-bacb-47cc-9537-b7f518eb69bd 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-caa556bd-bacb-47cc-9537-b7f518eb69bd');\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-2e7f6056-f4d8-48d5-a167-1dc9cb05b15a\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-2e7f6056-f4d8-48d5-a167-1dc9cb05b15a')\"\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-2e7f6056-f4d8-48d5-a167-1dc9cb05b15a button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_9020bc51-1a4f-41d1-b70e-827fe4d212f6\">\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('data_frame')\"\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_9020bc51-1a4f-41d1-b70e-827fe4d212f6 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('data_frame');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "data_frame",
              "summary": "{\n  \"name\": \"data_frame\",\n  \"rows\": 727,\n  \"fields\": [\n    {\n      \"column\": \"open\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 16.1035338133042,\n        \"min\": 0.8389684425,\n        \"max\": 79.52836962,\n        \"num_unique_values\": 727,\n        \"samples\": [\n          35.95654525,\n          13.24616686,\n          37.5674349164\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"high\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 16.787965749134525,\n        \"min\": 0.853501666,\n        \"max\": 85.0168524,\n        \"num_unique_values\": 727,\n        \"samples\": [\n          38.1509959,\n          14.84458089,\n          40.2846120528\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"low\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 15.450005209358025,\n        \"min\": 0.8266428992,\n        \"max\": 71.9259352,\n        \"num_unique_values\": 727,\n        \"samples\": [\n          34.44777827,\n          13.24616686,\n          37.3302258384\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"close\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 16.110665264905244,\n        \"min\": 0.8390481756,\n        \"max\": 79.87131341,\n        \"num_unique_values\": 727,\n        \"samples\": [\n          37.74977039,\n          14.84458089,\n          39.8977878501\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"volume\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 334134232.9378182,\n        \"min\": 2577834.83,\n        \"max\": 3919748072.71,\n        \"num_unique_values\": 727,\n        \"samples\": [\n          75863474.17,\n          43477028.95,\n          110481935.78\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"timestamp\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"num_unique_values\": 727,\n        \"samples\": [\n          \"2021-08-04T23:59:59.999Z\",\n          \"2021-02-05T23:59:59.999Z\",\n          \"2021-12-18T23:59:59.999Z\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"close_change\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2.1996795296587517,\n        \"min\": -16.67715586,\n        \"max\": 16.623292319,\n        \"num_unique_values\": 726,\n        \"samples\": [\n          0.7277392533999958,\n          -0.673613139999997,\n          1.9139805399999972\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"rate_of_change\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.7105708344483693,\n        \"min\": -5.2868637346376,\n        \"max\": 7.50751747373825,\n        \"num_unique_values\": 726,\n        \"samples\": [\n          0.1541679656669245,\n          -0.21099742191489093,\n          0.5934012720107229\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 7. Identify Days of Greatest Percentage Change"
      ],
      "metadata": {
        "id": "2ifRW8qU3OOB"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Based on the rate change column calculated above, identify the top 5 days of greatest positive rate change, and the top 5 days of greatest negative rate change.\n",
        "\n",
        "Display your results in a table showing both the rate of change and their dates."
      ],
      "metadata": {
        "id": "ISZf2C1j3bAA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sorted_pc = data_frame.sort_values(by='rate_of_change', ascending=False)"
      ],
      "metadata": {
        "id": "sGlUUWFxfS2w"
      },
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "top_5_pc = sorted_pc.head(5)\n",
        "bottom_5_pc = sorted_pc.tail(5)\n",
        "top_5_pc[['rate_of_change', 'timestamp']]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "9cT8COffaoev",
        "outputId": "76bd9221-3a97-438d-a648-1b69ea323838"
      },
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     rate_of_change                 timestamp\n",
              "56         7.507517  2022-11-07T23:59:59.999Z\n",
              "55         5.831368  2022-11-08T23:59:59.999Z\n",
              "51         2.870585  2022-11-12T23:59:59.999Z\n",
              "598        2.751007  2021-05-18T23:59:59.999Z\n",
              "53         2.634439  2022-11-10T23:59:59.999Z"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-71a399fb-376e-4a27-9261-b7dce23aaa11\" 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>rate_of_change</th>\n",
              "      <th>timestamp</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>56</th>\n",
              "      <td>7.507517</td>\n",
              "      <td>2022-11-07T23:59:59.999Z</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>55</th>\n",
              "      <td>5.831368</td>\n",
              "      <td>2022-11-08T23:59:59.999Z</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>51</th>\n",
              "      <td>2.870585</td>\n",
              "      <td>2022-11-12T23:59:59.999Z</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>598</th>\n",
              "      <td>2.751007</td>\n",
              "      <td>2021-05-18T23:59:59.999Z</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53</th>\n",
              "      <td>2.634439</td>\n",
              "      <td>2022-11-10T23:59:59.999Z</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-71a399fb-376e-4a27-9261-b7dce23aaa11')\"\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-71a399fb-376e-4a27-9261-b7dce23aaa11 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-71a399fb-376e-4a27-9261-b7dce23aaa11');\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-4fb36688-7612-4889-9888-e26cebcb7ce2\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-4fb36688-7612-4889-9888-e26cebcb7ce2')\"\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-4fb36688-7612-4889-9888-e26cebcb7ce2 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "repr_error": "0"
            }
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "bottom_5_pc[['rate_of_change', 'timestamp']]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "XhPozbVscdux",
        "outputId": "0d994e20-81fe-4316-b86b-d812c8e27fea"
      },
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     rate_of_change                 timestamp\n",
              "25        -2.468484  2022-12-08T23:59:59.999Z\n",
              "693       -3.176645  2021-02-18T23:59:59.999Z\n",
              "493       -3.438254  2021-08-31T23:59:59.999Z\n",
              "54        -5.286864  2022-11-09T23:59:59.999Z\n",
              "0               NaN  2022-12-31T23:59:59.999Z"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-674b50bb-954a-4803-b4ab-d473a957d0af\" 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>rate_of_change</th>\n",
              "      <th>timestamp</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>-2.468484</td>\n",
              "      <td>2022-12-08T23:59:59.999Z</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>693</th>\n",
              "      <td>-3.176645</td>\n",
              "      <td>2021-02-18T23:59:59.999Z</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>493</th>\n",
              "      <td>-3.438254</td>\n",
              "      <td>2021-08-31T23:59:59.999Z</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>54</th>\n",
              "      <td>-5.286864</td>\n",
              "      <td>2022-11-09T23:59:59.999Z</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>NaN</td>\n",
              "      <td>2022-12-31T23:59:59.999Z</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-674b50bb-954a-4803-b4ab-d473a957d0af')\"\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-674b50bb-954a-4803-b4ab-d473a957d0af 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-674b50bb-954a-4803-b4ab-d473a957d0af');\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-cabac52a-b96b-4f4f-82a4-b52d7c5db27f\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-cabac52a-b96b-4f4f-82a4-b52d7c5db27f')\"\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-cabac52a-b96b-4f4f-82a4-b52d7c5db27f button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"bottom_5_pc[['rate_of_change', 'timestamp']]\",\n  \"rows\": 5,\n  \"fields\": [\n    {\n      \"column\": \"rate_of_change\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.2015278895018258,\n        \"min\": -5.2868637346376,\n        \"max\": -2.468483834734651,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          -3.1766451740494728,\n          -5.2868637346376,\n          -2.468483834734651\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"timestamp\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"2021-02-18T23:59:59.999Z\",\n          \"2022-12-31T23:59:59.999Z\",\n          \"2021-08-31T23:59:59.999Z\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 8. Plot the Data"
      ],
      "metadata": {
        "id": "2B9dxJbno0s0"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Create two separate plots of the data -- one for the daily closing price and one for the daily gains/losses. These can be histograms or line plots."
      ],
      "metadata": {
        "id": "LwMrL6-AplCH"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data_frame['close'].hist()\n",
        "\n",
        "plt.xlabel('Daily Closing Price ($)')\n",
        "plt.ylabel('Frequency')\n",
        "plt.title('Histogram of Daily Closing Price')"
      ],
      "metadata": {
        "id": "R0vq1cLRB0Kl",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 489
        },
        "outputId": "cf74db30-40d7-4b98-d54a-8c00e2e51362"
      },
      "execution_count": 54,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Histogram of Daily Closing Price')"
            ]
          },
          "metadata": {},
          "execution_count": 54
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data_frame['close_change'].hist()\n",
        "\n",
        "plt.xlabel('Daily Gains/Losses')\n",
        "plt.ylabel('Frequency')\n",
        "plt.title('Histogram of Daily Gains/Losses')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 489
        },
        "id": "gNgGD4tdddCd",
        "outputId": "4e1da1a1-77d8-4a7c-fd62-3e56d6f33d37"
      },
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Histogram of Daily Gains/Losses')"
            ]
          },
          "metadata": {},
          "execution_count": 49
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Combine the two plots from above into a single plot, displaying both together. Your plot should have two Y-axis scales, should differentiate the two values by color, and should include a legend."
      ],
      "metadata": {
        "id": "xRT2iFAI5s4S"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plt.hist(data_frame['close'], bins=10, alpha=0.5, label='Daily Closing Price', color='blue')\n",
        "plt.hist(data_frame['close_change'], bins=10, alpha=0.5, label='Daily Gains/Losses', color='orange')\n",
        "\n",
        "plt.xlabel('Daily Closing Price and Daily Gains/Losses')\n",
        "plt.ylabel('Frequency')\n",
        "plt.title('Daily Closing Price and Daily Gains/Losses')\n",
        "\n",
        "plt.legend()\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "epypcCLc6QxL",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "outputId": "af8fbf44-c449-4601-b018-e2b680fa8c76"
      },
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjsAAAHHCAYAAABZbpmkAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAABqF0lEQVR4nO3deVxO6f8/8FelfVXaUIkKUZYMGlsUWbLPWIciDDL2dWYkywhjN5bBZypDmjF2JjQazFgTqaFp7DEqSyqFpK7fH36dr1uLSrlz5vV8PM5jnOtc5zrvc+5zz/3uOtc5R0UIIUBEREQkU6rKDoCIiIioIjHZISIiIlljskNERESyxmSHiIiIZI3JDhEREckakx0iIiKSNSY7REREJGtMdoiIiEjWmOwQERGRrDHZoUohODgYKioquHXrllTm5uYGNzc3pcQTEBAAFRWVCmtfRUUFAQEBFdZ+RSrss5ITHx8f1KpVS6kxvHnu37p1CyoqKggODlZaTCUl9/ODPkxMdqjE8v8nlj9paWmhevXq8PT0xOrVq/HkyRNlh/hWz58/x4oVK9CiRQsYGhpCS0sLDg4OGDduHP755x9lh1fh8n808yc1NTVYW1ujd+/eiImJUXZ4HxQ3NzfpOKqqqsLAwAB169bFkCFDEBERoezwSuTmzZsYN24cHBwcoKOjAx0dHTg6OsLPzw+xsbHKDq9Yjx8/RpUqVfDzzz8DAGrVqgUvLy8lR0WVVRVlB0Afnnnz5sHW1hY5OTlITk7GsWPHMHHiRCxfvhz79u2Ds7NzqdscMmQIBgwYAE1NzQqI+JWHDx+ic+fOiI6OhpeXFwYNGgQ9PT0kJCQgLCwMGzduxIsXLyps+6979uwZqlRR3tdv4MCB6Nq1K3JzcxEfH4/169cjPDwcZ86cQePGjYtd9318Vh+KmjVrIjAwEACQlZWFa9euYdeuXdi6dSv69euHrVu3Ql1dvdTtHjlypLxDLeDAgQPo378/qlSpgsGDB6NRo0ZQVVXF33//jV27dmH9+vW4efMmbGxsStXu+zo/Dh8+DBUVFXTq1KlCt0PywGSHSq1Lly5o1qyZND9r1ixERkbCy8sLPXr0QHx8PLS1tUvVppqaGtTU1Mo7VAU+Pj64ePEifvnlF/Tt21dh2fz58/HVV19V6PZfp6Wl9d62VZimTZvis88+k+ZbtWqFHj16YP369fj+++8LXScrKwu6urrv5bP6UBgaGiocRwBYtGgRxo8fj3Xr1qFWrVpYvHhxqdvV0NAorxALdf36dQwYMAA2NjY4evQoLC0tFZYvXrwY69atg6pq6Tv/39f58euvv6JVq1YwMjKq8G3Rh4+XsahcdOjQAbNnz8bt27exdetWqTw2NhY+Pj6oXbs2tLS0YGFhgeHDh+PRo0cK67/tOn9mZiZ0dXUxYcKEAsvu3r0LNTU16S/swpw9exYHDx6Er69vgUQHADQ1NbF06dJi9/Hly5eYP38+6tSpA01NTdSqVQtffvklsrOzFeqdP38enp6eqFatGrS1tWFra4vhw4cr1HlzzE7+GKFr167Bx8cHRkZGMDQ0xLBhw/D06VOFdZ89e4bx48ejWrVq0NfXR48ePfDvv/++0zigDh06AHh1WQP4v8/j+PHjGDt2LMzMzFCzZk2FZW9+VuHh4WjXrh309fVhYGCAjz76CKGhoQp1zp49i86dO8PQ0BA6Ojpo164dTp48+db4Xrx4AX9/f7i4uMDQ0BC6urpo06YNfv/9d4V6+Zfpli5dio0bN0qf1UcffYSoqKgC7e7ZswcNGzaElpYWGjZsiN27d5f4mBVFTU0Nq1evhqOjI7777jukp6dLy4KCgtChQweYmZlBU1MTjo6OWL9+fYE23jZeLSgoCCoqKrh48WKBZQsXLoSamhr+/fffItdfsmQJsrKyEBQUVCDRAYAqVapg/PjxsLKyksre5bucf4npzz//RPPmzaGlpYXatWtjy5YtCuvm5ORg7ty5sLe3h5aWFkxMTNC6desClwXz8vJw6NAhdOvWrch9LEx5fofDwsLg4uIine9OTk5YtWqVQp20tDRMnDgRVlZW0NTUhJ2dHRYvXoy8vLxSt0XvhskOlZshQ4YAUOyCj4iIwI0bNzBs2DCsWbMGAwYMQFhYGLp27QohRInb1tPTQ+/evfHTTz8hNzdXYdn27dshhMDgwYOLXH/fvn0KMZbFiBEj4O/vj6ZNm2LFihVo164dAgMDMWDAAKnO/fv30alTJ9y6dQszZ87EmjVrMHjwYJw5c6ZE2+jXrx+ePHmCwMBA9OvXD8HBwZg7d65CHR8fH6xZswZdu3bF4sWLoa2tXer/6b/p+vXrAAATExOF8rFjx+LKlSvw9/fHzJkzi1w/ODgY3bp1Q2pqKmbNmoVFixahcePGOHTokFQnMjISbdu2RUZGBubMmYOFCxciLS0NHTp0wLlz54qNLyMjA5s3b4abmxsWL16MgIAAPHjwAJ6enoWONQoNDcW3336Lzz//HAsWLMCtW7fQp08f5OTkSHWOHDmCvn37QkVFBYGBgejVqxeGDRuG8+fPl+SQFUtNTQ0DBw7E06dP8eeff0rl69evh42NDb788kssW7YMVlZWGDt2LNauXVuq9j/55BNoa2tj27ZtBZZt27YNbm5uqFGjRpHrHzhwAHZ2dmjRokWJt/mu3+Vr167hk08+QceOHbFs2TJUrVoVPj4+uHz5slQnICAAc+fORfv27fHdd9/hq6++grW1NS5cuKDQVlRUFB48eICuXbuWOH6g/L7DERERGDhwIKpWrYrFixdj0aJFcHNzU0jcnz59inbt2mHr1q0YOnQoVq9ejVatWmHWrFmYPHlyqdqiciCISigoKEgAEFFRUUXWMTQ0FE2aNJHmnz59WqDO9u3bBQBx4sSJAm3fvHlTKmvXrp1o166dNH/48GEBQISHhyu05+zsrFCvML179xYAxOPHj4utl2/OnDni9a9HTEyMACBGjBihUG/q1KkCgIiMjBRCCLF79+63HiMhhAAg5syZU2B7w4cPLxC3iYmJNB8dHS0AiIkTJyrU8/HxKdBmYW7evCkAiLlz54oHDx6I5ORkcezYMdGkSRMBQOzcuVMI8X+fR+vWrcXLly8V2njzs0pLSxP6+vqiRYsW4tmzZwp18/LypP/a29sLT09PqUyIV+eHra2t6NixY7Fxv3z5UmRnZyuUPX78WJibmyscs/z9MzExEampqVL53r17BQCxf/9+qaxx48bC0tJSpKWlSWVHjhwRAISNjU2x8Qjx6vxs0KBBkcvzz4VVq1Yp7O+bPD09Re3atQu0/fo5nb9fQUFBUtnAgQNF9erVRW5urlR24cKFAvXelJ6eLgCIXr16FVj2+PFj8eDBA2l6Pd53+S7b2NgUqHf//n2hqakppkyZIpU1atRIdOvWrcjY882ePbvAZ2RjY1PsuuX5HZ4wYYIwMDAo8N143fz584Wurq74559/FMpnzpwp1NTURGJiYonbonfHnh0qV3p6egp3Zb0+duf58+d4+PAhWrZsCQAF/lp7Gw8PD1SvXl3hr9m//voLsbGxBcZNvCkjIwMAoK+vX6pt5vv1118BQOEvMgCYMmUKAODgwYMAII0fOHDggEIvQkmNHj1aYb5NmzZ49OiRFH9+T8nYsWMV6n3xxRel2s6cOXNgamoKCwsLuLm54fr161i8eDH69OmjUG/kyJFvHX8RERGBJ0+eYObMmQXGIuXfvh8TE4OrV69i0KBBePToER4+fIiHDx8iKysL7u7uOHHiRIGu/depqalJ41jy8vKQmpqKly9folmzZoWeR/3790fVqlWl+TZt2gAAbty4AQBISkpCTEwMvL29YWhoKNXr2LEjHB0di93fktLT0wOAIr8P6enpePjwIdq1a4cbN24oXO4qiaFDh+LevXsKl/K2bdsGbW3tQi/V5ss/l/Lje52bmxtMTU2l6fUep3f9Ljs6OkqfAwCYmpqibt260mcCvPr+XL58GVevXi22rV9//bXUvZnl+R02MjJCVlZWsXfd7dixA23atEHVqlWl8/3hw4fw8PBAbm4uTpw4UeK26N0x2aFylZmZqZBQpKamYsKECTA3N4e2tjZMTU1ha2sLAKX+n7uqqioGDx6MPXv2SONYtm3bBi0tLXz66afFrmtgYAAAZb49/vbt21BVVYWdnZ1CuYWFBYyMjHD79m0AQLt27dC3b1/MnTsX1apVQ8+ePREUFFRgTEBRrK2tFebzf7AfP36sEEf+Mcz3ZlxvM2rUKERERODo0aOIjo7G/fv3MX369AL13txOYfIvgTVs2LDIOvk/Xt7e3go/pqampti8eTOys7Pfej6EhITA2dlZGsthamqKgwcPFrpeSY4jANjb2xdYt27dusXGUVKZmZkAFBPskydPwsPDA7q6ujAyMoKpqSm+/PJLAKX/PnTs2BGWlpZS8p+Xl4ft27ejZ8+exSb1+cvy43vd999/j4iICIVxd/ne9bv85mcCvPpc8j8T4NWdnmlpaXBwcICTkxOmTZtW4Bb45ORkXLhwodTJTnl+h8eOHQsHBwd06dIFNWvWxPDhwxUu2QKvzvlDhw4VON89PDwAvLpcVtK26N3xbiwqN3fv3kV6errC/0z69euHU6dOYdq0aWjcuDH09PSQl5eHzp07F/uXfFGGDh2Kb7/9Fnv27MHAgQMRGhoKLy8vhb/OC1OvXj0AQFxcnMJfl6X1tgcNqqio4JdffsGZM2ewf/9+HD58GMOHD8eyZctw5syZQv+afl1RvSiiFOObSsLe3l76n25xSntXXVHyP+tvv/22yFvbizs2W7duhY+PD3r16oVp06bBzMxMGpSen2y97n0dx+L89ddfAP4vEb1+/Trc3d1Rr149LF++HFZWVtDQ0MCvv/6KFStWlPr7oKamhkGDBmHTpk1Yt24dTp48iXv37r21l9PQ0BCWlpZSfK/LH8NT2I0C7/pdLsln0rZtW1y/fh179+7FkSNHsHnzZqxYsQIbNmzAiBEjALwaCK+lpYX27du/dZuFKY/vsJmZGWJiYnD48GGEh4cjPDwcQUFBGDp0KEJCQgC8Ouc7duxY6B8RAODg4AAAJWqL3h2THSo3P/74IwDA09MTwKu/oo8ePYq5c+fC399fqve2LuriNGzYEE2aNMG2bdtQs2ZNJCYmYs2aNW9dr3v37ggMDMTWrVvLlOzY2NggLy8PV69eRf369aXylJQUpKWlFXgWScuWLdGyZUt88803CA0NxeDBgxEWFib9D7us8uO4efOmQq/EtWvX3qndd1GnTh0Ar37ci+phyq9jYGBQoiTrTb/88gtq166NXbt2KfxYzZkzpwwRQ/q8CjsXExISytTm63JzcxEaGgodHR20bt0aALB//35kZ2dj3759Cr0cb95RVhpDhw7FsmXLsH//foSHh8PU1FT6/hWnW7du2Lx5M86dO4fmzZu/tX5FfJeLYmxsjGHDhmHYsGHIzMxE27ZtERAQIH13Dh48iPbt25c6ES/v77CGhga6d++O7t27Iy8vD2PHjsX333+P2bNnw87ODnXq1EFmZmaJzve3tUXvjpexqFxERkZi/vz5sLW1le6Kyv9L7s2/pleuXPlO2xoyZAiOHDmClStXwsTEBF26dHnrOq6urujcuTM2b96MPXv2FFj+4sULTJ06tcj18+/6eDP25cuXA4DUpf748eMC+5vfk1HSS1nFyf8hW7dunUJ5SRK+itKpUyfo6+sjMDAQz58/V1iWfyxcXFxQp04dLF26tNDLJw8ePCh2G4WdS2fPnsXp06fLFLOlpSUaN26MkJAQhUswERERuHLlSpnazJebm4vx48cjPj4e48ePly6hFrYP6enpCAoKKvO2nJ2d4ezsjM2bN2Pnzp0YMGBAiR5WOX36dOjo6GD48OFISUkpsPzNc7iivstvevM2dj09PdjZ2UnfnZycHERERJTp7sPy/A6/Gaeqqqr0MNX8Ov369cPp06dx+PDhArGkpaXh5cuXJW6L3h17dqjUwsPD8ffff+Ply5dISUlBZGQkIiIiYGNjg3379kmDVA0MDNC2bVssWbIEOTk5qFGjBo4cOSI9y6WsBg0ahOnTp2P37t0YM2ZMiZ9Qu2XLFnTq1Al9+vRB9+7d4e7uDl1dXVy9ehVhYWFISkoq8lk7jRo1gre3NzZu3Ii0tDS0a9cO586dQ0hICHr16iV1qYeEhGDdunXo3bs36tSpgydPnmDTpk0wMDAo9W2yhXFxcUHfvn2xcuVKPHr0CC1btsTx48elV11U5Pu8imJgYIAVK1ZgxIgR+OijjzBo0CBUrVoVly5dwtOnTxESEgJVVVVs3rwZXbp0QYMGDTBs2DDUqFED//77L37//XcYGBhg//79RW7Dy8sLu3btQu/evdGtWzfcvHkTGzZsgKOjY6HJU0kEBgaiW7duaN26NYYPH47U1FSsWbMGDRo0KHGb6enp0viWp0+fSk9Qzn9o3/z586W6nTp1kv6C//zzz5GZmYlNmzbBzMwMSUlJZdoH4FXvTn6i/rZLWPns7e0RGhqKgQMHom7dutITlIUQuHnzJkJDQ6Gqqio9W6mivstvcnR0hJubG1xcXGBsbIzz58/jl19+wbhx4wAAf/75JzIyMopMdq5du4YFCxYUKG/SpAm6detWbt/hESNGIDU1FR06dEDNmjVx+/ZtrFmzBo0bN5Z6jaZNm4Z9+/bBy8sLPj4+cHFxQVZWFuLi4vDLL7/g1q1bqFatWonaonKgnJvA6EOUf0tp/qShoSEsLCxEx44dxapVq0RGRkaBde7evSt69+4tjIyMhKGhofj000/FvXv3CtwmXZJbz1/XtWtXAUCcOnWqVPvw9OlTsXTpUvHRRx8JPT09oaGhIezt7cUXX3whrl27JtV789ZzIYTIyckRc+fOFba2tkJdXV1YWVmJWbNmiefPn0t1Lly4IAYOHCisra2FpqamMDMzE15eXuL8+fMKbb25//nbe/DggUK9wo5LVlaW8PPzE8bGxkJPT0/06tVLJCQkCABi0aJFxe5//i3M3377bbH1invMQGExCSHEvn37xMcffyy0tbWFgYGBaN68udi+fbtCnYsXL4o+ffoIExMToampKWxsbES/fv3E0aNHi40nLy9PLFy4UNjY2AhNTU3RpEkTceDAAeHt7a1wC3Jx+/fmMRdCiJ07d4r69esLTU1N4ejoKHbt2lWgzaK0a9dO4fugp6cn7O3txWeffSaOHDlS6Dr79u0Tzs7OQktLS9SqVUssXrxY/PDDD2899wu79TxfUlKSUFNTEw4ODm+N+U3Xrl0TY8aMEXZ2dkJLS0toa2uLevXqidGjR4uYmBiFuu/yXS7qtvA393PBggWiefPmwsjISIrlm2++ES9evBBCvLpN3NHRsdB9yb+9vbDJ19dXCFF+3+FffvlFdOrUSZiZmQkNDQ1hbW0tPv/8c5GUlKQQ05MnT8SsWbOEnZ2d0NDQENWqVRMff/yxWLp0qbRPJW2L3o2KEO9xxB5ROenduzfi4uKUOlalMomJiUGTJk2wdevWYh+uSPLz8OFDWFpawt/fH7Nnz1Z2OBXK0dERXl5eWLJkibJDoQ8Mx+zQBycpKQkHDx58p6chf8iePXtWoGzlypVQVVVF27ZtlRARKVNwcDByc3Nl/3148eIF+vfvj2HDhik7FPoAsWeHPhg3b97EyZMnsXnzZkRFReH69euwsLBQdljv3dy5cxEdHY327dujSpUq0u2qo0aNKvIlniQ/kZGRuHLlCmbPno327dtj165dyg6JqNLiAGX6YBw/fhzDhg2DtbU1QkJC/pOJDgB8/PHHiIiIwPz585GZmQlra2sEBAS817e2k/LNmzcPp06dQqtWrZR6Nx7Rh4A9O0RERCRrHLNDREREsqbUZGf9+vVwdnaGgYEBDAwM4OrqivDwcGm5m5sbVFRUFKY3X5SYmJiIbt26QUdHB2ZmZpg2bZr0sCYiIiIipY7ZqVmzJhYtWgR7e3sIIRASEoKePXvi4sWLaNCgAYBXb12eN2+etI6Ojo7079zcXHTr1g0WFhY4deoUkpKSMHToUKirq2PhwoUljiMvLw/37t2Dvr6+Uh7KRkRERKUnhMCTJ09QvXp1qKoW03+jvEf8FK5q1api8+bNQohXD5yaMGFCkXV//fVXoaqqKpKTk6Wy9evXCwMDA5GdnV3ibd65c6fIh1Fx4sSJEydOnCr3dOfOnWJ/5yvN3Vi5ubnYsWMHsrKy4OrqKpVv27YNW7duhYWFBbp3747Zs2dLvTunT5+Gk5MTzM3Npfqenp4YM2YMLl++jCZNmhS6rezsbIV3joj/P0b7zp070ntsiIiIqHLLyMiAlZUV9PX1i62n9GQnLi4Orq6ueP78OfT09LB79244OjoCePUOJBsbG1SvXh2xsbGYMWMGEhISpOdJJCcnKyQ6AKT55OTkIrcZGBiIuXPnFijPHztEREREH463DUFRerJTt25dxMTEID09Hb/88gu8vb1x/PhxODo6YtSoUVI9JycnWFpawt3dHdevX0edOnXKvM1Zs2Zh8uTJ0nx+ZkhERETyo/RbzzU0NGBnZwcXFxcEBgaiUaNGWLVqVaF1W7RoAQDS+5AsLCyQkpKiUCd/vrgHzmlqakq9OOzNISIikjelJztvysvLUxhP87qYmBgAgKWlJQDA1dUVcXFxuH//vlQnIiICBgYG0qUwIiIi+m9T6mWsWbNmoUuXLrC2tsaTJ08QGhqKY8eO4fDhw7h+/TpCQ0PRtWtXmJiYIDY2FpMmTULbtm3h7OwMAOjUqRMcHR0xZMgQLFmyBMnJyfj666/h5+cHTU1NZe4aEVGlkJubi5ycHGWHQVQm6urqUFNTe+d2lJrs3L9/H0OHDkVSUhIMDQ3h7OyMw4cPo2PHjrhz5w5+++03rFy5EllZWbCyskLfvn3x9ddfS+urqanhwIEDGDNmDFxdXaGrqwtvb2+F5/IQEf0XCSGQnJyMtLQ0ZYdC9E6MjIxgYWHxTs/B47ux8GqAsqGhIdLT0zl+h4hkISkpCWlpaTAzM4OOjg4fmEofHCEEnj59ivv378PIyEgawvK6kv5+K/1uLCIiKl+5ublSomNiYqLscIjKTFtbG8CrK0FmZmZlvqRV6QYoExHRu8kfo/P663WIPlT55/G7jD1jskNEJFO8dEVyUB7nMZMdIiIikjUmO0REJEvBwcEwMjKS5gMCAtC4ceMK3+6xY8egoqJSbnfCubm5YeLEieXSVkVQUVHBnj17lB1GsThAmYjoPyQgoHJvz8fHByEhIQCAKlWqwNjYGM7Ozhg4cCB8fHygqlryv9H79++Prl27li6AErh48SIWLlyIEydOID09HVZWVnBzc8O0adPg4OBQ7tvbtWsX1NXVy73dN7m5ueH48eMAXr1poHbt2hg3bhzGjh1b7HpJSUmoWrVqhcf3LtizQ0RElUrnzp2RlJSEW7duITw8HO3bt8eECRPg5eWFly9flrgdbW1tmJmZlWtsBw4cQMuWLZGdnY1t27YhPj4eW7duhaGhIWbPnl2u28pnbGz81rd6l5eRI0ciKSkJV65cQb9+/eDn54ft27cXWvfFixcAXr2eqbI/yJfJDhERVSqampqwsLBAjRo10LRpU3z55ZfYu3cvwsPDERwcLNVbvnw5nJycoKurCysrK4wdOxaZmZnS8jcvY73uxIkTUFdXR3JyskL5xIkT0aZNm0LXefr0KYYNG4auXbti37598PDwgK2tLVq0aIGlS5fi+++/L3Kfdu7ciQYNGkBTUxO1atXCsmXLFJavW7cO9vb20NLSgrm5OT755BNp2ZuXsWrVqoWFCxdi+PDh0NfXh7W1NTZu3KjQ3qlTp9C4cWNoaWmhWbNm2LNnD1RUVKTXLhVFR0cHFhYWqF27NgICAmBvb499+/ZJcYwbNw4TJ05EtWrV4OnpCaDgZay7d+9i4MCBMDY2hq6uLpo1a4azZ89Ky/fu3YumTZtCS0sLtWvXxty5c0uVxJYFkx0iIqr0OnTogEaNGmHXrl1SmaqqKlavXo3Lly8jJCQEkZGRmD59eonaa9u2LWrXro0ff/xRKsvJycG2bdswfPjwQtc5fPgwHj58WOQ2ikqsoqOj0a9fPwwYMABxcXEICAjA7NmzpcTt/PnzGD9+PObNm4eEhAQcOnQIbdu2LTb+ZcuWoVmzZrh48SLGjh2LMWPGICEhAcCrB+11794dTk5OuHDhAubPn48ZM2a85YgUTltbW+rBAYCQkBBoaGjg5MmT2LBhQ4H6mZmZaNeuHf7991/s27cPly5dwvTp05GXlwcA+OOPPzB06FBMmDABV65cwffff4/g4GB88803ZYqvpDhmhyqn2IB3W9/5HdcnokqnXr16iI2Nlebf7O1YsGABRo8ejXXr1pWoPV9fXwQFBWHatGkAgP379+P58+fo169fofWvXr0qxVEay5cvh7u7u3SZy8HBAVeuXMG3334LHx8fJCYmQldXF15eXtDX14eNjQ2aNGlSbJtdu3aVxtLMmDEDK1aswO+//466desiNDQUKioq2LRpE7S0tODo6Ih///0XI0eOLHHMubm52L59O2JjYzFq1Cip3N7eHkuWLClyvdDQUDx48ABRUVEwNjYGANjZ2UnL586di5kzZ8Lb2xsAULt2bcyfPx/Tp0/HnDlzShxfabFnh4iIPghCCIVnrvz2229wd3dHjRo1oK+vjyFDhuDRo0d4+vRpidrz8fHBtWvXcObMGQCvLnv169cPurq6RW6/LOLj49GqVSuFslatWuHq1avIzc1Fx44dYWNjg9q1a2PIkCHYtm3bW/ch/4XYwKvLSBYWFrh//z4AICEhAc7OztDS0pLqNG/evESxrlu3Dnp6etDW1sbIkSMxadIkjBkzRlru4uJS7PoxMTFo0qSJlOi86dKlS5g3bx709PSkKX+cUEk/t7JgskNERB+E+Ph42NraAgBu3boFLy8vODs7Y+fOnYiOjsbatWsBQOGyS3HMzMzQvXt3BAUFISUlBeHh4UVewgIg3Wn1999/v+OeKNLX18eFCxewfft2WFpawt/fH40aNSr21vU3785SUVGRLhW9i8GDByMmJgY3b95EVlYWli9frnAHXFGJYL781zsUJTMzE3PnzkVMTIw0xcXF4erVqwrJWXljskNERJVeZGQk4uLi0LdvXwCvxsHk5eVh2bJlaNmyJRwcHHDv3r1StztixAj89NNP2LhxI+rUqVOgB+Z1nTp1QrVq1Yq8jFNUclK/fn2cPHlSoezkyZNwcHCQ3vVUpUoVeHh4YMmSJYiNjcWtW7cQGRlZ6v0BgLp16yIuLg7Z2dlSWVRUVInWNTQ0hJ2dHWrUqFGq2/zzOTs7IyYmBqmpqYUub9q0KRISEmBnZ1dgKsv2SorJDhERVSrZ2dlITk7Gv//+iwsXLmDhwoXo2bMnvLy8MHToUACvxoHk5ORgzZo1uHHjBn788cdCB8y+jaenJwwMDLBgwQIMGzas2Lq6urrYvHkzDh48iB49euC3337DrVu3cP78eUyfPh2jR48udL0pU6bg6NGjmD9/Pv755x+EhITgu+++w9SpUwG8up199erViImJwe3bt7Flyxbk5eWhbt26pd4fABg0aBDy8vIwatQoxMfH4/Dhw1i6dCmAin+FyMCBA2FhYYFevXrh5MmTuHHjBnbu3InTp08DAPz9/bFlyxbMnTsXly9fRnx8PMLCwvD1119XaFxMdoiIqFI5dOgQLC0tUatWLXTu3Bm///47Vq9ejb1790o9IY0aNcLy5cuxePFiNGzYENu2bUNgYGCpt6WqqgofHx/k5uZKiVRxevbsiVOnTkFdXR2DBg1CvXr1MHDgQKSnp2PBggWFrtO0aVP8/PPPCAsLQ8OGDeHv74958+bBx8cHwKu7uHbt2oUOHTqgfv362LBhA7Zv344GDRqUen8AwMDAAPv370dMTAwaN26Mr776Cv7+/gBQoZeKAEBDQwNHjhyBmZkZunbtCicnJyxatEj63Dw9PXHgwAEcOXIEH330EVq2bIkVK1bAxsamQuNSEWUdcSUjGRkZMDQ0RHp6OgwMDJQdDgG8G4voHTx//hw3b96Era1thf+4yYGvry8ePHggPU9GjrZt24Zhw4YhPT39reNqKpvizueS/n7z1nMiIvpPSk9PR1xcHEJDQ2WX6GzZsgW1a9dGjRo1cOnSJcyYMQP9+vX74BKd8sJkh4iI/pN69uyJc+fOYfTo0ejYsaOywylXycnJ8Pf3R3JyMiwtLfHpp59W+IP7KjMmO1QxYgOUHQERUbGOHTum7BAqzPTp00v8NOn/Ag5QJiIiIlljskNERESyxmSHiIiIZI3JDhEREckakx0iIiKSNSY7REREJGtMdoiISJaCg4NhZGQkzQcEBKBx48ZKi+dNPj4+6NWrl7LD+E/gc3aIiP5LYgPe7/ZK+eoWHx8fhISEAHj1JnBjY2M4Oztj4MCB8PHxKdWbsfv374+uXbuWavslcfHiRSxatAgnTpxAamoqLCws4OTkhM8//xxeXl4lftnmqlWrUBFvbGrfvj0GDx4MDw8P2Nra4uLFi5UqyVMG9uwQEVGl0rlzZyQlJeHWrVsIDw9H+/btMWHCBHh5eeHly5clbkdbWxtmZmblGtvevXvRsmVLZGZmIiQkBPHx8Th06BB69+6Nr7/+Gunp6SVuy9DQUKHnqTykpqbi5MmT6N69e7m2+6FjskNERJWKpqYmLCwsUKNGDTRt2hRffvkl9u7di/DwcAQHB0v1li9fDicnJ+jq6sLKygpjx45FZmamtPzNy1ivO3HiBNTV1ZGcnKxQPnHiRLRp06bQdbKysuDr64tu3brh4MGD6NSpE2rXro369evD19cXly5dgqGhIQAgNzcXvr6+sLW1hba2NurWrYtVq1YptPfmZSw3NzeMHz8e06dPh7GxMSwsLBAQECAtF0IgICAA1tbW0NTURPXq1TF+/HiFNg8ePIimTZvC3Ny8qMMryc7Oxvjx42FmZgYtLS20bt0aUVFR0vLHjx9j8ODBMDU1hba2Nuzt7REUFAQAePHiBcaNGwdLS0toaWnBxsZG4a3zaWlpGDFiBExNTWFgYIAOHTrg0qVL0vJLly6hffv20NfXh4GBAVxcXHD+/Pm3xlxWTHaIiKjS69ChAxo1aoRdu3ZJZaqqqli9ejUuX76MkJAQREZGlvgVCW3btkXt2rXx448/SmU5OTnYtm0bhg8fXug6R44cwaNHj4rdRv4lrLy8PNSsWRM7duzAlStX4O/vjy+//BI///xzsXGFhIRAV1cXZ8+exZIlSzBv3jxEREQAAHbu3IkVK1bg+++/x9WrV7Fnzx44OTkprL9v3z707NmzRMdg+vTp2LlzJ0JCQnDhwgXY2dnB09MTqampAIDZs2fjypUrCA8PR3x8PNavX49q1aoBAFavXo19+/bh559/RkJCArZt24ZatWpJbX/66ae4f/8+wsPDER0djaZNm8Ld3V1qe/DgwahZsyaioqIQHR2NmTNnQl1dvURxlwXH7BAR0QehXr16iI2NleYnTpwo/btWrVpYsGABRo8ejXXr1pWoPV9fXwQFBWHatGkAgP379+P58+fo169fofX/+ecfAEDdunWlsqioKLRv316aDwsLg5eXF9TV1TF37lyp3NbWFqdPn8bPP/9cZPsA4OzsjDlz5gAA7O3t8d133+Ho0aPo2LEjEhMTYWFhAQ8PD6irq8Pa2hrNmzeX1s3OzsahQ4cUeoOKkpWVhfXr1yM4OBhdunQBAGzatAkRERH43//+h2nTpiExMRFNmjRBs2bNAEAhmUlMTIS9vT1at24NFRUV2NjYSMv+/PNPnDt3Dvfv34empiYAYOnSpdizZw9++eUXjBo1ComJiZg2bRrq1asn7WtFYs8OERF9EIQQCoN/f/vtN7i7u6NGjRrQ19fHkCFD8OjRIzx9+rRE7fn4+ODatWs4c+YMgFeXvfr16wddXd0Sx+Ts7IyYmBjExMQgKytLYUzR2rVr4eLiAlNTU+jp6WHjxo1ITEx8a3uvs7S0xP379wG86i159uwZateujZEjR2L37t0K24uMjISZmRkaNGjw1rivX7+OnJwctGrVSipTV1dH8+bNER8fDwAYM2YMwsLC0LhxY0yfPh2nTp2S6vr4+CAmJgZ169bF+PHjceTIEWnZpUuXkJmZCRMTE+jp6UnTzZs3cf36dQDA5MmTMWLECHh4eGDRokVSeUVhskNERB+E+Ph42NraAgBu3boFLy8vODs7Y+fOnYiOjsbatWsBvBpPUhJmZmbo3r07goKCkJKSgvDw8CIvYQH/1/uQkJAglWlqasLOzg52dnYKdcPCwjB16lT4+vriyJEjiImJwbBhw94a25uXclRUVJCXlwcAsLKyQkJCAtatWwdtbW2MHTsWbdu2RU5ODoBXl7B69OhRon0viS5duuD27duYNGkS7t27B3d3d0ydOhUA0LRpU9y8eRPz58/Hs2fP0K9fP3zyyScAgMzMTFhaWkpJYP6UkJAg9aIFBATg8uXL6NatGyIjI+Ho6Ijdu3eXW+xvYrJDRESVXmRkJOLi4tC3b18AQHR0NPLy8rBs2TK0bNkSDg4OuHfvXqnbHTFiBH766Sds3LgRderUUejpeFOnTp1gbGyMxYsXv7XdkydP4uOPP8bYsWPRpEkT2NnZlUvvhba2Nrp3747Vq1fj2LFjOH36NOLi4iCEwP79+0s8XqdOnTrQ0NDAyZMnpbKcnBxERUXB0dFRKjM1NYW3tze2bt2KlStXYuPGjdIyAwMD9O/fH5s2bcJPP/2EnTt3IjU1FU2bNkVycjKqVKkiJYL5U/6YHwBwcHDApEmTcOTIEfTp00ca/FwROGaHiIgqlezsbCQnJyM3NxcpKSk4dOgQAgMD4eXlhaFDhwIA7OzskJOTgzVr1qB79+44efIkNmzYUOpteXp6wsDAAAsWLMC8efOKraunp4fNmzejf//+6NatG8aPHw97e3tkZmbi0KFDAAA1NTUAr3qBtmzZgsOHD8PW1hY//vgjoqKipJ6psggODkZubi5atGgBHR0dbN26Fdra2rCxsUF0dDSePn2K1q1bF1jv9Z6ofA0aNMCYMWMwbdo0GBsbw9raGkuWLMHTp0/h6+sLAPD394eLiwsaNGiA7OxsHDhwAPXr1wfw6k44S0tLNGnSBKqqqtixYwcsLCxgZGQEDw8PuLq6olevXliyZImUiB48eBC9e/dGgwYNMG3aNHzyySewtbXF3bt3ERUVJSWyFYHJDhERVSqHDh2CpaUlqlSpgqpVq6JRo0ZYvXo1vL29pYcKNmrUCMuXL8fixYsxa9YstG3bFoGBgVIyVFKqqqrw8fHBwoULS7Ru7969cerUKSxevBhDhw5FamoqDA0N0axZM2lwMgB8/vnnuHjxIvr37w8VFRUMHDgQY8eORXh4eOkPyP9nZGSERYsWYfLkycjNzYWTkxP2798PExMTrFy5El27dkWVKgV/1gcMGFCg7M6dO1i0aBHy8vIwZMgQPHnyBM2aNcPhw4dRtWpVAICGhgZmzZqFW7duQVtbG23atEFYWBgAQF9fH0uWLMHVq1ehpqaGjz76CL/++qv0+fz666/46quvMGzYMDx48AAWFhZo27YtzM3NoaamhkePHmHo0KFISUlBtWrV0KdPH4UB3eVNRVTE4xs/MBkZGTA0NER6ejoMDAyUHY48xAYod/ulfGorkZw8f/4cN2/ehK2tLbS0tJQdTqXn6+uLBw8eYN++fcoOpcycnZ3x9ddfF3un14equPO5pL/f7NkhIqL/pPT0dMTFxSE0NPSDTnRevHiBvn37SreQU0FMdoiI6D+pZ8+eOHfuHEaPHo2OHTsqO5wy09DQkJ7NQ4VjskNERP9Jx44dU3YI9J7w1nMiIiKSNaUmO+vXr4ezszMMDAxgYGAAV1dXhZHqz58/h5+fn/QUxr59+yIlJUWhjcTERHTr1g06OjowMzPDtGnTSvVWXCIiueL9JyQH5XEeKzXZqVmzJhYtWoTo6GicP38eHTp0QM+ePXH58mUAwKRJk7B//37s2LEDx48fx71799CnTx9p/dzcXHTr1g0vXrzAqVOnEBISguDgYPj7+ytrl4iIlC7/KbwlfW0CUWWWfx6/y4tCK92t58bGxvj222/xySefwNTUFKGhodIjqP/++2/Ur18fp0+fRsuWLREeHg4vLy/cu3dPep39hg0bMGPGDDx48AAaGhol2iZvPa8AsQHK3T5vPaf/uKSkJKSlpcHMzAw6OjoK75Qi+hAIIfD06VPcv38fRkZGsLS0LFDng7v1PDc3Fzt27EBWVhZcXV0RHR2NnJwceHh4SHXq1asHa2trKdk5ffo0nJycpEQHePU0zDFjxuDy5cto0qRJodvKzs5Gdna2NJ+RkVFxO0ZEpAQWFhYAIL1EkuhDZWRkJJ3PZaX0ZCcuLg6urq54/vw59PT0sHv3bjg6OiImJgYaGhowMjJSqG9ubo7k5GQAQHJyskKik788f1lRAgMDK/RJjUREyqaiogJLS0uYmZlJL4ok+tCoq6tLr+B4F0pPdurWrYuYmBikp6fjl19+gbe3N44fP16h25w1axYmT54szWdkZMDKyqpCt0lEpAxqamrl8mNB9CFTerKjoaEBOzs7AICLiwuioqKwatUq9O/fHy9evEBaWppC705KSorUnWVhYYFz584ptJd/t1ZxXV6amprQ1NQs5z0hIiKiyqjSPWcnLy8P2dnZcHFxgbq6Oo4ePSotS0hIQGJiIlxdXQEArq6uiIuLU7gmHRERAQMDA4VX1BMREdF/l1J7dmbNmoUuXbrA2toaT548QWhoKI4dO4bDhw/D0NAQvr6+mDx5MoyNjWFgYIAvvvgCrq6uaNmyJQCgU6dOcHR0xJAhQ7BkyRIkJyfj66+/hp+fH3tuiIiICICSk5379+9j6NChSEpKgqGhIZydnXH48GHpHSUrVqyAqqoq+vbti+zsbHh6emLdunXS+mpqajhw4ADGjBkDV1dX6OrqwtvbG/PmzVPWLhEREVElU+mes6MMfM5OBYgNUO72+ZwdIiLZK+nvd6Ubs0NERERUnpjsEBERkawx2SEiIiJZY7JDREREssZkh4iIiGSNyQ4RERHJGpMdIiIikjUmO0RERCRrTHaIiIhI1pjsEBERkawx2SEiIiJZY7JDREREssZkh4iIiGSNyQ4RERHJGpMdIiIikjUmO0RERCRrTHaIiIhI1pjsEBERkawx2SEiIiJZY7JDREREssZkh4iIiGSNyQ4RERHJGpMdIiIikjUmO0RERCRrTHaIiIhI1pjsEBERkawx2SEiIiJZY7JDREREssZkh4iIiGSNyQ4RERHJGpMdIiIikjUmO0RERCRrTHaIiIhI1pjsEBERkawx2SEiIiJZY7JDREREssZkh4iIiGSNyQ4RERHJGpMdIiIikjUmO0RERCRrTHaIiIhI1pjsEBERkawpNdkJDAzERx99BH19fZiZmaFXr15ISEhQqOPm5gYVFRWFafTo0Qp1EhMT0a1bN+jo6MDMzAzTpk3Dy5cv3+euEBERUSVVRZkbP378OPz8/PDRRx/h5cuX+PLLL9GpUydcuXIFurq6Ur2RI0di3rx50ryOjo7079zcXHTr1g0WFhY4deoUkpKSMHToUKirq2PhwoXvdX+IiIio8lFqsnPo0CGF+eDgYJiZmSE6Ohpt27aVynV0dGBhYVFoG0eOHMGVK1fw22+/wdzcHI0bN8b8+fMxY8YMBAQEQENDo0L3gYiIiCq3SjVmJz09HQBgbGysUL5t2zZUq1YNDRs2xKxZs/D06VNp2enTp+Hk5ARzc3OpzNPTExkZGbh8+XKh28nOzkZGRobCRERERPKk1J6d1+Xl5WHixIlo1aoVGjZsKJUPGjQINjY2qF69OmJjYzFjxgwkJCRg165dAIDk5GSFRAeANJ+cnFzotgIDAzF37twK2hMiIiKqTCpNsuPn54e//voLf/75p0L5qFGjpH87OTnB0tIS7u7uuH79OurUqVOmbc2aNQuTJ0+W5jMyMmBlZVW2wImIiKhSqxSXscaNG4cDBw7g999/R82aNYut26JFCwDAtWvXAAAWFhZISUlRqJM/X9Q4H01NTRgYGChMREREJE9KTXaEEBg3bhx2796NyMhI2NravnWdmJgYAIClpSUAwNXVFXFxcbh//75UJyIiAgYGBnB0dKyQuImIiOjDodTLWH5+fggNDcXevXuhr68vjbExNDSEtrY2rl+/jtDQUHTt2hUmJiaIjY3FpEmT0LZtWzg7OwMAOnXqBEdHRwwZMgRLlixBcnIyvv76a/j5+UFTU1OZu0dERESVgFJ7dtavX4/09HS4ubnB0tJSmn766ScAgIaGBn777Td06tQJ9erVw5QpU9C3b1/s379fakNNTQ0HDhyAmpoaXF1d8dlnn2Ho0KEKz+UhIiKi/y6l9uwIIYpdbmVlhePHj7+1HRsbG/z666/lFRYRERHJSKUYoExERERUUZjsEBERkawx2SEiIiJZY7JDREREssZkh4iIiGSNyQ4RERHJGpMdIiIikjUmO0RERCRrTHaIiIhI1pjsEBERkawx2SEiIiJZY7JDREREssZkh4iIiGSNyQ4RERHJGpMdIiIikjUmO0RERCRrTHaIiIhI1pjsEBERkawx2SEiIiJZY7JDREREssZkh4iIiGSNyQ4RERHJGpMdIiIikjUmO0RERCRrTHaIiIhI1pjsEBERkawx2SEiIiJZY7JDREREssZkh4iIiGSNyQ4RERHJGpMdIiIikjUmO0RERCRrTHaIiIhI1pjsEBERkawx2SEiIiJZY7JDREREssZkh4iIiGSNyQ4RERHJWpmSnRs3bpR3HEREREQVokzJjp2dHdq3b4+tW7fi+fPn5R0TERERUbkpU7Jz4cIFODs7Y/LkybCwsMDnn3+Oc+fOlXdsRERERO+sTMlO48aNsWrVKty7dw8//PADkpKS0Lp1azRs2BDLly/HgwcPStROYGAgPvroI+jr68PMzAy9evVCQkKCQp3nz5/Dz88PJiYm0NPTQ9++fZGSkqJQJzExEd26dYOOjg7MzMwwbdo0vHz5siy7RkRERDLzTgOUq1Spgj59+mDHjh1YvHgxrl27hqlTp8LKygpDhw5FUlJSsesfP34cfn5+OHPmDCIiIpCTk4NOnTohKytLqjNp0iTs378fO3bswPHjx3Hv3j306dNHWp6bm4tu3brhxYsXOHXqFEJCQhAcHAx/f/932TUiIiKSCRUhhCjryufPn8cPP/yAsLAw6OrqwtvbG76+vrh79y7mzp2LjIyMUl3eevDgAczMzHD8+HG0bdsW6enpMDU1RWhoKD755BMAwN9//4369evj9OnTaNmyJcLDw+Hl5YV79+7B3NwcALBhwwbMmDEDDx48gIaGxlu3m5GRAUNDQ6Snp8PAwKBsB4MUxQYod/vOSt4+ERFVuJL+fpepZ2f58uVwcnLCxx9/jHv37mHLli24ffs2FixYAFtbW7Rp0wbBwcG4cOFCqdpNT08HABgbGwMAoqOjkZOTAw8PD6lOvXr1YG1tjdOnTwMATp8+DScnJynRAQBPT09kZGTg8uXLZdk9IiIikpEqZVlp/fr1GD58OHx8fGBpaVloHTMzM/zvf/8rcZt5eXmYOHEiWrVqhYYNGwIAkpOToaGhASMjI4W65ubmSE5Oluq8nujkL89fVpjs7GxkZ2dL8xkZGSWOk4iIiD4sZUp2rl69+tY6Ghoa8Pb2LnGbfn5++Ouvv/Dnn3+WJaRSCQwMxNy5cyt8O0RERKR8ZbqMFRQUhB07dhQo37FjB0JCQkrd3rhx43DgwAH8/vvvqFmzplRuYWGBFy9eIC0tTaF+SkoKLCwspDpv3p2VP59f502zZs1Cenq6NN25c6fUMRMREdGHoUzJTmBgIKpVq1ag3MzMDAsXLixxO0IIjBs3Drt370ZkZCRsbW0Vlru4uEBdXR1Hjx6VyhISEpCYmAhXV1cAgKurK+Li4nD//n2pTkREBAwMDODo6FjodjU1NWFgYKAwERERkTyV6TJWYmJigcQEAGxsbJCYmFjidvz8/BAaGoq9e/dCX19fGmNjaGgIbW1tGBoawtfXF5MnT4axsTEMDAzwxRdfwNXVFS1btgQAdOrUCY6OjhgyZAiWLFmC5ORkfP311/Dz84OmpmZZdo+IiIhkpEw9O2ZmZoiNjS1QfunSJZiYmJS4nfXr1yM9PR1ubm6wtLSUpp9++kmqs2LFCnh5eaFv375o27YtLCwssGvXLmm5mpoaDhw4ADU1Nbi6uuKzzz7D0KFDMW/evLLsGhEREclMmXp2Bg4ciPHjx0NfXx9t27YF8OoBgRMmTMCAAQNK3E5JHvGjpaWFtWvXYu3atUXWsbGxwa+//lri7RLR+xMQoOwICqqMMRFRxSlTsjN//nzcunUL7u7uqFLlVRN5eXkYOnRoqcbsEBEREVW0MiU7Ghoa+OmnnzB//nxcunQJ2tracHJygo2NTXnHR0RERPROypTs5HNwcICDg0N5xUJERERU7sqU7OTm5iI4OBhHjx7F/fv3kZeXp7A8MjKyXIIjIiIieldlSnYmTJiA4OBgdOvWDQ0bNoSKikp5x0VERERULsqU7ISFheHnn39G165dyzseIiIionJVpufsaGhowM7OrrxjISIiIip3ZUp2pkyZglWrVpXoOTlEREREylSmy1h//vknfv/9d4SHh6NBgwZQV1dXWP76E46JiIiIlKlMyY6RkRF69+5d3rEQERERlbsyJTtBQUHlHQcRERFRhSjTmB0AePnyJX777Td8//33ePLkCQDg3r17yMzMLLfgiIiIiN5VmXp2bt++jc6dOyMxMRHZ2dno2LEj9PX1sXjxYmRnZ2PDhg3lHScRERFRmZSpZ2fChAlo1qwZHj9+DG1tbam8d+/eOHr0aLkFR0RERPSuytSz88cff+DUqVPQ0NBQKK9Vqxb+/fffcgmMiIiIqDyUqWcnLy8Pubm5Bcrv3r0LfX39dw6KiIiIqLyUKdnp1KkTVq5cKc2rqKggMzMTc+bM4SskiIiIqFIp02WsZcuWwdPTE46Ojnj+/DkGDRqEq1evolq1ati+fXt5x0hERERUZmVKdmrWrIlLly4hLCwMsbGxyMzMhK+vLwYPHqwwYJmIiIhI2cqU7ABAlSpV8Nlnn5VnLERERETlrkzJzpYtW4pdPnTo0DIFQ0RERFTeypTsTJgwQWE+JycHT58+hYaGBnR0dJjsEBERUaVRpruxHj9+rDBlZmYiISEBrVu35gBlIiIiqlTK/G6sN9nb22PRokUFen2IiIiIlKnckh3g1aDle/fulWeTRERERO+kTGN29u3bpzAvhEBSUhK+++47tGrVqlwCIyIiIioPZUp2evXqpTCvoqICU1NTdOjQAcuWLSuPuIiIiIjKRZmSnby8vPKOg4iIiKhClOuYHSIiIqLKpkw9O5MnTy5x3eXLl5dlE0RERETlokzJzsWLF3Hx4kXk5OSgbt26AIB//vkHampqaNq0qVRPRUWlfKIkIiIiKqMyJTvdu3eHvr4+QkJCULVqVQCvHjQ4bNgwtGnTBlOmTCnXIImIiIjKqkxjdpYtW4bAwEAp0QGAqlWrYsGCBbwbi4iIiCqVMiU7GRkZePDgQYHyBw8e4MmTJ+8cFBEREVF5KVOy07t3bwwbNgy7du3C3bt3cffuXezcuRO+vr7o06dPecdIREREVGZlGrOzYcMGTJ06FYMGDUJOTs6rhqpUga+vL7799ttyDZCIiIjoXZQp2dHR0cG6devw7bff4vr16wCAOnXqQFdXt1yDIyIiInpX7/RQwaSkJCQlJcHe3h66uroQQpRXXERERETlokzJzqNHj+Du7g4HBwd07doVSUlJAABfX1/edk5ERESVSpmSnUmTJkFdXR2JiYnQ0dGRyvv3749Dhw6VW3BERERE76pMY3aOHDmCw4cPo2bNmgrl9vb2uH37drkERkRERFQeytSzk5WVpdCjky81NRWamprvHBQRERFReSlTstOmTRts2bJFmldRUUFeXh6WLFmC9u3bl7idEydOoHv37qhevTpUVFSwZ88eheU+Pj5QUVFRmDp37qxQJzU1FYMHD4aBgQGMjIzg6+uLzMzMsuwWERERyVCZLmMtWbIE7u7uOH/+PF68eIHp06fj8uXLSE1NxcmTJ0vcTlZWFho1aoThw4cX+TDCzp07IygoSJp/s+do8ODBSEpKQkREBHJycjBs2DCMGjUKoaGhZdk1IiIikpkyJTsNGzbEP//8g++++w76+vrIzMxEnz594OfnB0tLyxK306VLF3Tp0qXYOpqamrCwsCh0WXx8PA4dOoSoqCg0a9YMALBmzRp07doVS5cuRfXq1Uu+U0RERCRLpU52cnJy0LlzZ2zYsAFfffVVRcSk4NixYzAzM0PVqlXRoUMHLFiwACYmJgCA06dPw8jISEp0AMDDwwOqqqo4e/YsevfuXWib2dnZyM7OluYzMjIqdieIiIhIaUo9ZkddXR2xsbEVEUsBnTt3xpYtW3D06FEsXrwYx48fR5cuXZCbmwsASE5OhpmZmcI6VapUgbGxMZKTk4tsNzAwEIaGhtJkZWVVoftBREREylOmAcqfffYZ/ve//5V3LAUMGDAAPXr0gJOTE3r16oUDBw4gKioKx44de6d2Z82ahfT0dGm6c+dO+QRMRERElU6Zxuy8fPkSP/zwA3777Te4uLgUeCfW8uXLyyW4N9WuXRvVqlXDtWvX4O7uDgsLC9y/f79AbKmpqUWO8wFejQPiLfJERET/DaVKdm7cuIFatWrhr7/+QtOmTQEA//zzj0IdFRWV8ovuDXfv3sWjR4+kQdCurq5IS0tDdHQ0XFxcAACRkZHIy8tDixYtKiwOIiIi+nCUKtmxt7dHUlISfv/9dwCvXg+xevVqmJubl2njmZmZuHbtmjR/8+ZNxMTEwNjYGMbGxpg7dy769u0LCwsLXL9+HdOnT4ednR08PT0BAPXr10fnzp0xcuRIbNiwATk5ORg3bhwGDBjAO7GIiIgIQCnH7Lz5VvPw8HBkZWWVeePnz59HkyZN0KRJEwDA5MmT0aRJE/j7+0NNTQ2xsbHo0aMHHBwc4OvrCxcXF/zxxx8Kl6C2bduGevXqwd3dHV27dkXr1q2xcePGMsdERERE8lKmMTv53kx+SsvNza3YNg4fPvzWNoyNjfkAQSIiIipSqXp28l/Z8GYZERERUWVVqp4dIQR8fHyky0jPnz/H6NGjC9yNtWvXrvKLkIiIiOgdlCrZ8fb2Vpj/7LPPyjUYIiIiovJWqmTn9RdyEhEREX0IyvQEZSIiIqIPBZMdIiIikjUmO0RERCRrTHaIiIhI1pjsEBERkawx2SEiIiJZY7JDREREssZkh4iIiGSNyQ4RERHJGpMdIiIikjUmO0RERCRrTHaIiIhI1pjsEBERkawx2SEiIiJZY7JDREREssZkh4iIiGStirIDICIiICBA2REoqmzxEL0L9uwQERGRrDHZISIiIlljskNERESyxmSHiIiIZI3JDhEREckakx0iIiKSNSY7REREJGtMdoiIiEjWmOwQERGRrDHZISIiIlljskNERESyxmSHiIiIZI3JDhEREckakx0iIiKSNSY7REREJGtMdoiIiEjWmOwQERGRrDHZISIiIlljskNERESyxmSHiIiIZE2pyc6JEyfQvXt3VK9eHSoqKtizZ4/CciEE/P39YWlpCW1tbXh4eODq1asKdVJTUzF48GAYGBjAyMgIvr6+yMzMfI97QURERJWZUpOdrKwsNGrUCGvXri10+ZIlS7B69Wps2LABZ8+eha6uLjw9PfH8+XOpzuDBg3H58mVERETgwIEDOHHiBEaNGvW+doGIiIgquSrK3HiXLl3QpUuXQpcJIbBy5Up8/fXX6NmzJwBgy5YtMDc3x549ezBgwADEx8fj0KFDiIqKQrNmzQAAa9asQdeuXbF06VJUr179ve0LERERVU6VdszOzZs3kZycDA8PD6nM0NAQLVq0wOnTpwEAp0+fhpGRkZToAICHhwdUVVVx9uzZ9x4zERERVT5K7dkpTnJyMgDA3Nxcodzc3FxalpycDDMzM4XlVapUgbGxsVSnMNnZ2cjOzpbmMzIyyitsIiIiqmQqbc9ORQoMDIShoaE0WVlZKTskIiIiqiCVNtmxsLAAAKSkpCiUp6SkSMssLCxw//59heUvX75EamqqVKcws2bNQnp6ujTduXOnnKMnIiKiyqLSXsaytbWFhYUFjh49isaNGwN4dbnp7NmzGDNmDADA1dUVaWlpiI6OhouLCwAgMjISeXl5aNGiRZFta2pqQlNTs8L3gYgqp4AAZUdARO+TUpOdzMxMXLt2TZq/efMmYmJiYGxsDGtra0ycOBELFiyAvb09bG1tMXv2bFSvXh29evUCANSvXx+dO3fGyJEjsWHDBuTk5GDcuHEYMGAA78QiIiIiAEpOds6fP4/27dtL85MnTwYAeHt7Izg4GNOnT0dWVhZGjRqFtLQ0tG7dGocOHYKWlpa0zrZt2zBu3Di4u7tDVVUVffv2xerVq9/7vhAREVHlpCKEEMoOQtkyMjJgaGiI9PR0GBgYKDsceYgNUO72nZW8fZLwkhGVF55L9KaS/n5X2gHKREREROWByQ4RERHJGpMdIiIikjUmO0RERCRrTHaIiIhI1pjsEBERkawx2SEiIiJZY7JDREREssZkh4iIiGSNyQ4RERHJGpMdIiIikjUmO0RERCRrTHaIiIhI1pjsEBERkawx2SEiIiJZY7JDREREssZkh4iIiGSNyQ4RERHJGpMdIiIikjUmO0RERCRrTHaIiIhI1pjsEBERkawx2SEiIiJZY7JDREREssZkh4iIiGSNyQ4RERHJGpMdIiIikjUmO0RERCRrTHaIiIhI1pjsEBERkawx2SEiIiJZY7JDREREssZkh4iIiGStirIDIKLyExCg7AiIiCof9uwQERGRrDHZISIiIlljskNERESyxjE79EE4dryU9XdVTByv4/gYIqIPA3t2iIiISNaY7BAREZGsMdkhIiIiWWOyQ0RERLJWqZOdgIAAqKioKEz16tWTlj9//hx+fn4wMTGBnp4e+vbti5SUFCVGTERERJVNpU52AKBBgwZISkqSpj///FNaNmnSJOzfvx87duzA8ePHce/ePfTp00eJ0RIREVFlU+lvPa9SpQosLCwKlKenp+N///sfQkND0aFDBwBAUFAQ6tevjzNnzqBly5bvO1QiIiKqhCp9z87Vq1dRvXp11K5dG4MHD0ZiYiIAIDo6Gjk5OfDw8JDq1qtXD9bW1jh9+nSxbWZnZyMjI0NhIiIiInmq1MlOixYtEBwcjEOHDmH9+vW4efMm2rRpgydPniA5ORkaGhowMjJSWMfc3BzJycnFthsYGAhDQ0NpsrKyqsC9ICIiImWq1JexunTpIv3b2dkZLVq0gI2NDX7++Wdoa2uXud1Zs2Zh8uTJ0nxGRgYTHiIiIpmq1MnOm4yMjODg4IBr166hY8eOePHiBdLS0hR6d1JSUgod4/M6TU1NaGpqVnC0RERUnirjK1oqY0xUUKW+jPWmzMxMXL9+HZaWlnBxcYG6ujqOHj0qLU9ISEBiYiJcXV2VGCURERFVJpW6Z2fq1Kno3r07bGxscO/ePcyZMwdqamoYOHAgDA0N4evri8mTJ8PY2BgGBgb44osv4OrqyjuxiIiISFKpk527d+9i4MCBePToEUxNTdG6dWucOXMGpqamAIAVK1ZAVVUVffv2RXZ2Njw9PbFu3TolR01ERESVSaVOdsLCwopdrqWlhbVr12Lt2rXvKSIiIiL60HxQY3aIiIiISovJDhEREckakx0iIiKSNSY7REREJGtMdoiIiEjWmOwQERGRrDHZISIiIlljskNERESyxmSHiIiIZI3JDhEREckakx0iIiKSNSY7REREJGtMdoiIiEjWKvVbz4kqs4AAZUdAREQlwWSHZMnNJKDM6x57VPZ1iYio8uFlLCIiIpI1JjtEREQka0x2iIiISNaY7BAREZGsMdkhIiIiWWOyQ0RERLLGW8+paLEByo6AiIjonbFnh4iIiGSNyQ4RERHJGpMdIiIikjUmO0RERCRrTHaIiIhI1pjsEBERkawx2SEiIiJZY7JDREREssZkh4iIiGSNyQ4RERHJGpMdIiIikjUmO0RERCRrTHaIiIhI1pjsEBERkawx2SEiIiJZq6LsAIiIiD5UAQHKjqCgyhiTsrFnh4iIiGSNPTtEREQyUhl7dpQdE3t2iIiISNZkk+ysXbsWtWrVgpaWFlq0aIFz584pOyQiIiKqBGRxGeunn37C5MmTsWHDBrRo0QIrV66Ep6cnEhISYGZmpuzw6APjZhLwTusfe/Ru6xMRUfmSRbKzfPlyjBw5EsOGDQMAbNiwAQcPHsQPP/yAmTNnKjk6JYoNUHYEVEpMtIiIyt8HfxnrxYsXiI6OhoeHh1SmqqoKDw8PnD59WomRERERUWXwwffsPHz4ELm5uTA3N1coNzc3x99//13oOtnZ2cjOzpbm09PTAQAZGRnlH+Bfge+2fsNZZV83M/vtdT4QWc+UHUHJZWeX/TzKevZun9m7bJuIqKJUxM/rq3ZfNSyEKLbeB5/slEVgYCDmzp1boNzKykoJ0bzNImUHQKWmzM+M5wsRVT6LKvh/TU+ePIGhoWGRyz/4ZKdatWpQU1NDSkqKQnlKSgosLCwKXWfWrFmYPHmyNJ+Xl4fU1FSYmJhARUVFoW5GRgasrKxw584dGBgYlP8OUAE85u8fj7ly8Li/fzzmylFRx10IgSdPnqB69erF1vvgkx0NDQ24uLjg6NGj6NWrF4BXycvRo0cxbty4QtfR1NSEpqamQpmRkVGx2zEwMOAX4z3jMX//eMyVg8f9/eMxV46KOO7F9ejk++CTHQCYPHkyvL290axZMzRv3hwrV65EVlaWdHcWERER/XfJItnp378/Hjx4AH9/fyQnJ6Nx48Y4dOhQgUHLRERE9N8ji2QHAMaNG1fkZat3oampiTlz5hS47EUVh8f8/eMxVw4e9/ePx1w5lH3cVcTb7tciIiIi+oB98A8VJCIiIioOkx0iIiKSNSY7REREJGtMdoiIiEjWmOwU4datW/D19YWtrS20tbVRp04dzJkzBy9evFCoFxsbizZt2kBLSwtWVlZYsmSJkiKWj7Vr16JWrVrQ0tJCixYtcO7cOWWHJBuBgYH46KOPoK+vDzMzM/Tq1QsJCQkKdZ4/fw4/Pz+YmJhAT08Pffv2LfCEciq7RYsWQUVFBRMnTpTKeMzL37///ovPPvsMJiYm0NbWhpOTE86fPy8tF0LA398flpaW0NbWhoeHB65evarEiD98ubm5mD17tsLv5vz58xXeW6W04y6oUOHh4cLHx0ccPnxYXL9+Xezdu1eYmZmJKVOmSHXS09OFubm5GDx4sPjrr7/E9u3bhba2tvj++++VGPmHLSwsTGhoaIgffvhBXL58WYwcOVIYGRmJlJQUZYcmC56eniIoKEj89ddfIiYmRnTt2lVYW1uLzMxMqc7o0aOFlZWVOHr0qDh//rxo2bKl+Pjjj5UYtXycO3dO1KpVSzg7O4sJEyZI5Tzm5Ss1NVXY2NgIHx8fcfbsWXHjxg1x+PBhce3aNanOokWLhKGhodizZ4+4dOmS6NGjh7C1tRXPnj1TYuQftm+++UaYmJiIAwcOiJs3b4odO3YIPT09sWrVKqmOso47k51SWLJkibC1tZXm161bJ6pWrSqys7OlshkzZoi6desqIzxZaN68ufDz85Pmc3NzRfXq1UVgYKASo5Kv+/fvCwDi+PHjQggh0tLShLq6utixY4dUJz4+XgAQp0+fVlaYsvDkyRNhb28vIiIiRLt27aRkh8e8/M2YMUO0bt26yOV5eXnCwsJCfPvtt1JZWlqa0NTUFNu3b38fIcpSt27dxPDhwxXK+vTpIwYPHiyEUO5x52WsUkhPT4exsbE0f/r0abRt2xYaGhpSmaenJxISEvD48WNlhPhBe/HiBaKjo+Hh4SGVqaqqwsPDA6dPn1ZiZPKVnp4OANJ5HR0djZycHIXPoF69erC2tuZn8I78/PzQrVs3hWML8JhXhH379qFZs2b49NNPYWZmhiZNmmDTpk3S8ps3byI5OVnhmBsaGqJFixY85u/g448/xtGjR/HPP/8AAC5duoQ///wTXbp0AaDc4y6bJyhXtGvXrmHNmjVYunSpVJacnAxbW1uFevmvqEhOTkbVqlXfa4wfuocPHyI3N7fAaz7Mzc3x999/Kykq+crLy8PEiRPRqlUrNGzYEMCr81ZDQ6PAi3HNzc2RnJyshCjlISwsDBcuXEBUVFSBZTzm5e/GjRtYv349Jk+ejC+//BJRUVEYP348NDQ04O3tLR3Xwv5fw2NedjNnzkRGRgbq1asHNTU15Obm4ptvvsHgwYMBQKnH/T/XszNz5kyoqKgUO735w/rvv/+ic+fO+PTTTzFy5EglRU5Uvvz8/PDXX38hLCxM2aHI2p07dzBhwgRs27YNWlpayg7nPyEvLw9NmzbFwoUL0aRJE4waNQojR47Ehg0blB2arP3888/Ytm0bQkNDceHCBYSEhGDp0qUICQlRdmj/vZ6dKVOmwMfHp9g6tWvXlv597949tG/fHh9//DE2btyoUM/CwqLAHRP58xYWFuUT8H9ItWrVoKamVugx5fEsX+PGjcOBAwdw4sQJ1KxZUyq3sLDAixcvkJaWptDTwM+g7KKjo3H//n00bdpUKsvNzcWJEyfw3Xff4fDhwzzm5czS0hKOjo4KZfXr18fOnTsB/N//n1NSUmBpaSnVSUlJQePGjd9bnHIzbdo0zJw5EwMGDAAAODk54fbt2wgMDIS3t7dSj/t/rmfH1NQU9erVK3bKH4Pz77//ws3NDS4uLggKCoKqquLhcnV1xYkTJ5CTkyOVRUREoG7duryEVQYaGhpwcXHB0aNHpbK8vDwcPXoUrq6uSoxMPoQQGDduHHbv3o3IyMgCl2FdXFygrq6u8BkkJCQgMTGRn0EZubu7Iy4uDjExMdLUrFkzDB48WPo3j3n5atWqVYFHKvzzzz+wsbEBANja2sLCwkLhmGdkZODs2bM85u/g6dOnBX4n1dTUkJeXB0DJx71Chz9/wO7evSvs7OyEu7u7uHv3rkhKSpKmfGlpacLc3FwMGTJE/PXXXyIsLEzo6Ojw1vN3EBYWJjQ1NUVwcLC4cuWKGDVqlDAyMhLJycnKDk0WxowZIwwNDcWxY8cUzumnT59KdUaPHi2sra1FZGSkOH/+vHB1dRWurq5KjFp+Xr8bSwge8/J27tw5UaVKFfHNN9+Iq1evim3btgkdHR2xdetWqc6iRYuEkZGR2Lt3r4iNjRU9e/bkrefvyNvbW9SoUUO69XzXrl2iWrVqYvr06VIdZR13JjtFCAoKEgAKnV536dIl0bp1a6GpqSlq1KghFi1apKSI5WPNmjXC2tpaaGhoiObNm4szZ84oOyTZKOqcDgoKkuo8e/ZMjB07VlStWlXo6OiI3r17KyT59O7eTHZ4zMvf/v37RcOGDYWmpqaoV6+e2Lhxo8LyvLw8MXv2bGFubi40NTWFu7u7SEhIUFK08pCRkSEmTJggrK2thZaWlqhdu7b46quvFB7PoqzjriLEa482JCIiIpKZ/9yYHSIiIvpvYbJDREREssZkh4iIiGSNyQ4RERHJGpMdIiIikjUmO0RERCRrTHaIiIhI1pjs0H9GcHCwwruHAgIC3st7cI4dOwYVFRWkpaWVS3tubm6YOHFiubRVEVRUVLBnzx5lh1Fq5f05vY2Pjw969eolzVe2z7VWrVpYuXKlssMgKhdMdqhS8/Hxkd5Gr66uDnNzc3Ts2BE//PCD9L6Vkurfvz/++eefco/x4sWL+PTTT2Fubg4tLS3Y29tj5MiRFbItANi1axfmz59fIW2/zs3NTTr2WlpacHR0xLp16966XlJSErp06VLh8SlDrVq1pGOira2NWrVqoV+/foiMjCx1W6tWrUJwcHC5x7hz50506NABVatWhba2NurWrYvhw4fj4sWLpWonKioKo0aNKtfYnj17Bl1dXVy7dq3AHx9EFYnJDlV6nTt3RlJSEm7duoXw8HC0b98eEyZMgJeXF16+fFnidrS1tWFmZlausR04cAAtW7ZEdnY2tm3bhvj4eGzduhWGhoaYPXt2uW4rn7GxMfT19Suk7TeNHDkSSUlJuHLlCvr16wc/Pz9s37690LovXrwA8OqN0pqamu8lPmWYN28ekpKSkJCQgC1btsDIyAgeHh745ptvStWOoaFhuf/Yz5gxA/3790fjxo2xb98+JCQkIDQ0FLVr18asWbNK1ZapqSl0dHTKNb6IiAjY2NjAzs6uXNsleqsKfyEF0Tvw9vYWPXv2LFB+9OhRAUBs2rRJKlu2bJlo2LCh0NHRETVr1hRjxowRT548kZYHBQUJQ0NDaX7OnDmiUaNGQgghjh8/LqpUqVLgfUQTJkwQrVu3LjS2rKwsUa1aNdGrV69Clz9+/FgIIcTvv/8uAEjzQgjxyy+/CEdHR6GhoSFsbGzE0qVLFdZdu3atsLOzE5qamsLMzEz07dtXWvbme5VsbGzEN998I4YNGyb09PSElZVVgZfRnjx5UjRq1EhoamoKFxcXsXv3bgFAXLx4sdDYC9uOEELY29uLAQMGSMv9/PzEhAkThImJiXBzcxNCvHr/1u7du6V17ty5IwYMGCC998nFxUXhfWd79uwRTZo0EZqamsLW1lYEBASInJycIuM6d+6c8PDwECYmJsLAwEC0bdtWREdHK9TJPzd69eoltLW1hZ2dndi7d69CnYMHDwp7e3uhpaUl3NzcpPfhvf45vcnGxkasWLGiQLm/v79QVVUVf//9txBCiJcvX4rhw4eLWrVqCS0tLeHg4CBWrlypsM6b5/brx3vu3LmiQYMGBbbTqFEj8fXXXxca2+nTpwUAsWrVqkKX5+XlSf++du2a6NGjhzAzMxO6urqiWbNmIiIioth9fdsxTU1NFYMGDRLVqlUTWlpaws7OTvzwww8KbQ4fPlzMmDFDCFHw+/im27dvix49eghdXV2hr68vPv30U4UXAsfExAg3Nzehp6cn9PX1RdOmTUVUVJQQQohbt24JLy8vYWRkJHR0dISjo6M4ePCgtG5cXJzo3Lmz0NXVFWZmZuKzzz4TDx48kJbv2LFDNGzYUGhpaQljY2Ph7u4uMjMzi4yVKj/27NAHqUOHDmjUqBF27dollamqqmL16tW4fPkyQkJCEBkZienTp5eovbZt26J27dr48ccfpbKcnBxs27YNw4cPL3Sdw4cP4+HDh0Vuo6i/2qOjo9GvXz8MGDAAcXFxCAgIwOzZs6VLGufPn8f48eMxb948JCQk4NChQ2jbtm2x8S9btgzNmjXDxYsXMXbsWIwZMwYJCQkAgIyMDHTv3h1OTk64cOEC5s+fjxkzZrzliBROW1tb6sEBgJCQEGhoaODkyZPYsGFDgfqZmZlo164d/v33X+zbtw+XLl3C9OnTpUuQf/zxB4YOHYoJEybgypUr+P777xEcHFxsL8mTJ0/g7e2NP//8E2fOnIG9vT26du2KJ0+eKNSbO3cu+vXrh9jYWHTt2hWDBw9GamoqAODOnTvo06cPunfvjpiYGIwYMQIzZ84s0zEBgAkTJkAIgb179wIA8vLyULNmTezYsQNXrlyBv78/vvzyS/z8888lam/48OGIj49HVFSUVHbx4kXExsZi2LBhha6zfft26OnpYezYsYUuV1FRkf6dmZmJrl274ujRo7h48SI6d+6M7t27IzExsdi4ijums2fPxpUrVxAeHo74+HisX78e1apVk9bNy8vDgQMH0LNnz7fuf15eHnr27InU1FQcP34cERERuHHjBvr37y/VGTx4MGrWrImoqChER0dj5syZUFdXBwD4+fkhOzsbJ06cQFxcHBYvXgw9PT0AQFpaGjp06IAmTZrg/PnzOHToEFJSUtCvXz8Ary7DDhw4UPoMjh07hj59+kDwNZIfNmVnW0TFKapnRwgh+vfvL+rXr1/kujt27BAmJibSfHE9O0IIsXjxYoX2du7cKfT09Ir8i27x4sUCgEhNTS12H97s2Rk0aJDo2LGjQp1p06YJR0dHabsGBgYiIyOj0PYK69n57LPPpPm8vDxhZmYm1q9fL4QQYv369cLExEQ8e/ZMqrNp06ZS9ey8fPlS/PjjjwKA+O6776TlTZo0KbAeXuvZ+f7774W+vr549OhRodtwd3cXCxcuVCj78ccfhaWlZZFxvSk3N1fo6+uL/fv3K8Tweg9IZmamACDCw8OFEELMmjVLOt75ZsyYUeaeHSGEMDc3F2PGjClyXT8/P4UeuuJ6doQQokuXLgrtffHFF1LvWWE6d+4snJ2dFcqWLVsmdHV1pSktLa3I9Rs0aCDWrFkjzRfWs1PcMe3evbsYNmxYke2fPHlSmJmZidzcXCFE8T07R44cEWpqaiIxMVEqu3z5sgAgzp07J4QQQl9fXwQHBxe6vpOTkwgICCh02fz580WnTp0Uyu7cuSMAiISEBBEdHS0AiFu3bhW5L/ThYc8OfbCEEAp/rf72229wd3dHjRo1oK+vjyFDhuDRo0d4+vRpidrz8fHBtWvXcObMGQCv7t7q168fdHV1i9x+WcTHx6NVq1YKZa1atcLVq1eRm5uLjh07wsbGBrVr18aQIUOwbdu2t+6Ds7Oz9G8VFRVYWFjg/v37AICEhAQ4OztDS0tLqtO8efMSxbpu3Tro6elBW1sbI0eOxKRJkzBmzBhpuYuLS7Hrx8TEoEmTJjA2Ni50+aVLlzBv3jzo6elJU/44oaL2OSUlBSNHjoS9vT0MDQ1hYGCAzMzMAr0Srx8TXV1dGBgYSMckPj4eLVq0UKjv6upa7L68zZvn49q1a+Hi4gJTU1Po6elh48aNb+05ed3IkSOxfft2PH/+HC9evEBoaGiRvYxFGT58OGJiYvD9998jKytLOmczMzMxdepU1K9fH0ZGRtDT00N8fPxb4yvumI4ZMwZhYWFo3Lgxpk+fjlOnTimsu3fvXnh5eUFV9e0/O/Hx8bCysoKVlZVU5ujoCCMjI8THxwMAJk+ejBEjRsDDwwOLFi3C9evXpbrjx4/HggUL0KpVK8yZMwexsbHSskuXLuH3339XOOfq1asHALh+/ToaNWoEd3d3ODk54dNPP8WmTZvw+PHjt8ZMlRuTHfpgxcfHw9bWFgBw69YteHl5wdnZGTt37kR0dDTWrl0LAAqXXYpjZmaG7t27IygoCCkpKQgPDy/2x8XBwQEA8Pfff7/jnijS19fHhQsXsH37dlhaWsLf3x+NGjUq9pbo/O77fCoqKqW+W60wgwcPRkxMDG7evImsrCwsX75c4ceqqEQwn7a2drHLMzMzMXfuXMTExEhTXFwcrl69qpCcvc7b2xsxMTFYtWoVTp06hZiYGJiYmBT4nCvqmBTm0aNHePDggXQ+hoWFYerUqfD19cWRI0cQExODYcOGlfhcBIDu3btDU1MTu3fvxv79+5GTk4NPPvmkyPr29va4ceMGcnJypDIjIyPY2dmhRo0aCnWnTp2K3bt3Y+HChfjjjz8QExMDJyent8ZX3DHt0qULbt++jUmTJuHevXtwd3fH1KlTpbr79u1Djx49Srz/bxMQEIDLly+jW7duiIyMhKOjI3bv3g0AGDFiBG7cuIEhQ4YgLi4OzZo1w5o1awC8OufyL1++Pl29ehVt27aFmpoaIiIiEB4eDkdHR6xZswZ169bFzZs3yy12ev+Y7NAHKTIyEnFxcejbty+AV+Ng8vLysGzZMrRs2RIODg64d+9eqdsdMWIEfvrpJ2zcuBF16tQp0APzuk6dOqFatWpYsmRJocuLSk7q16+PkydPKpSdPHkSDg4OUFNTAwBUqVIFHh4eWLJkCWJjY3Hr1q0y3d4MAHXr1kVcXByys7OlstfHghTH0NBQ+rEsyV/kb3J2dkZMTIw0ruNNTZs2RUJCAuzs7ApMRW3v5MmTGD9+PLp27YoGDRpAU1MTDx8+LFVc9evXx7lz5xTK8nv0ymLVqlVQVVWVnptz8uRJfPzxxxg7diyaNGkCOzs7hZ6HkqhSpQq8vb0RFBSEoKAgDBgwoNjkceDAgcjMzCzR4wFOnjwJHx8f9O7dG05OTrCwsMCtW7dKFV9hTE1N4e3tja1bt2LlypXYuHEjAODq1au4ffs2OnbsWKJ26tevjzt37uDOnTtS2ZUrV5CWlgZHR0epzMHBAZMmTcKRI0fQp08fBAUFScusrKwwevRo7Nq1C1OmTMGmTZsAvDrnLl++jFq1ahU45/KTdxUVFbRq1Qpz587FxYsXoaGhISVS9GGqouwAiN4mOzsbycnJyM3NRUpKCg4dOoTAwEB4eXlh6NChAAA7Ozvk5ORgzZo16N69e5EDZt/G09MTBgYGWLBgAebNm1dsXV1dXWzevBmffvopevTogfHjx8POzg4PHz7Ezz//jMTERISFhRVYb8qUKfjoo48wf/589O/fH6dPn8Z3330n/UgdOHAAN27cQNu2bVG1alX8+uuvyMvLQ926dUu9PwAwaNAgfPXVVxg1ahRmzpyJxMRELF26FIDioNWKMHDgQCxcuBC9evVCYGAgLC0tcfHiRVSvXh2urq7w9/eHl5cXrK2t8cknn0BVVRWXLl3CX3/9hQULFhTapr29PX788Uc0a9YMGRkZmDZt2lt7kN40evRoLFu2DNOmTcOIESMQHR1d4mfePHnyBMnJycjJycHNmzexdetWbN68GYGBgdIt1fb29tiyZQsOHz4MW1tb/Pjjj4iKipJ6fkpqxIgRqF+/PgAUSJDf5OrqiilTpmDKlCm4ffs2+vTpAysrKyQlJeF///sfVFRUpATS3t4eu3btQvfu3aGiooLZs2e/c6+Xv78/XFxc0KBBA2RnZ+PAgQNS7Hv37oWHh0eBW9lzc3MRExOjUKapqQkPDw84OTlh8ODBWLlyJV6+fImxY8eiXbt2aNasGZ49e4Zp06bhk08+ga2tLe7evYuoqCjpj5+JEyeiS5cucHBwwOPHj/H7779Lsfj5+WHTpk0YOHAgpk+fDmNjY1y7dg1hYWHYvHkzzp8/j6NHj6JTp04wMzPD2bNn8eDBA2l9+kApd8gQUfG8vb0FAAFAVKlSRZiamgoPDw/xww8/SAMd8y1fvlxYWloKbW1t4enpKbZs2aIw4PRtA5TzzZ49W6ipqYl79+6VKMaoqCjRp08fYWpqKjQ1NYWdnZ0YNWqUuHr1qhCi+FvP1dXVhbW1tfj222+lZX/88Ydo166dqFq1qtDW1hbOzs7ip59+kpYXNkD5zUGzjRo1EnPmzJHmT548KZydnYWGhoZwcXERoaGhAoB0q3RhCrv1vCTL8cat57du3RJ9+/YVBgYGQkdHRzRr1kycPXtWWn7o0CHx8ccfC21tbWFgYCCaN28uNm7cWOR2L1y4IJo1aya0tLSEvb292LFjR6GDaV+PQQghDA0NRVBQkDS/f/9+6fb+Nm3aiB9++KFEA5Tzz0cNDQ1hbW0t+vXrJyIjIxXqPX/+XPj4+AhDQ0NhZGQkxowZI2bOnKlwvr1tgHK+Nm3aFHobelF++ukn4ebmJgwNDYW6urqoWbOmGDRokMLt/jdv3hTt27cX2trawsrKSnz33XdvPa/edkznz58v6tevL7S1tYWxsbHo2bOnuHHjhhBCiNatWys8JkIIId3q/+ZUp04dIUTxt55nZ2eLAQMGCCsrK6GhoSGqV68uxo0bJw3CHzdunKhTp47Q1NQUpqamYsiQIeLhw4fStv/55x/Ru3dvYWRkJLS1tUW9evXExIkTRV5enrhy5Yrw9PSUvs8ODg4KA7fpw6QiBO+nI3qdr68vHjx4gH379ik7lAqzbds2DBs2DOnp6aXuFaH3RwgBe3t7jB07FpMnT1Z2OGXy8OFDWFpa4u7duzA3N1d2OPQfxctYRP9feno64uLiEBoaKrtEZ8uWLahduzZq1KiBS5cuYcaMGejXrx8TnUrswYMHCAsLQ3JycpHP1vkQpKamYvny5Ux0SKmY7BD9fz179sS5c+cwevToEg+k/FAkJyfD398fycnJsLS0xKefflrq1xvQ+2VmZoZq1aph48aNqFq1qrLDKTMHBwfpzkUiZeFlLCIiIpI13npOREREssZkh4iIiGSNyQ4RERHJGpMdIiIikjUmO0RERCRrTHaIiIhI1pjsEBERkawx2SEiIiJZY7JDREREsvb/AMsuq2olKoQ7AAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}