LinkPrediction_EDA_02_06.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GsB7fKGij8HQ"
      },
      "source": [
        "#***EDA***"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 36,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "v1lf1LHWyEFL",
        "outputId": "7a3ffb55-a06c-4242-b9c0-91eb3051a722"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ]
        }
      ],
      "source": [
        "from google.colab import drive\n",
        "\n",
        "drive.mount('/content/drive')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 37,
      "metadata": {
        "id": "rerVssLiiuXe"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hkrpaob4kAHG"
      },
      "source": [
        "## **Microbiome**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 38,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 256
        },
        "id": "17ML3304j63C",
        "outputId": "7f6d87d3-7b00-4af6-b2ec-d09691a502b6"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   host_ID     ASV_1  ASV_10  ASV_100  ASV_1001  ASV_1002  ASV_1004  ASV_1005  \\\n",
              "0     2010  0.090395     0.0      0.0       0.0       0.0       0.0       0.0   \n",
              "1     2011  0.075280     0.0      0.0       0.0       0.0       0.0       0.0   \n",
              "2     2014  0.031537     0.0      0.0       0.0       0.0       0.0       0.0   \n",
              "3     2015  0.254525     0.0      0.0       0.0       0.0       0.0       0.0   \n",
              "4     2018  0.176341     0.0      0.0       0.0       0.0       0.0       0.0   \n",
              "\n",
              "   ASV_1007  ASV_1008  ...  ASV_982  ASV_983  ASV_985  ASV_986  ASV_987  \\\n",
              "0       0.0       0.0  ...      0.0      0.0      0.0      0.0      0.0   \n",
              "1       0.0       0.0  ...      0.0      0.0      0.0      0.0      0.0   \n",
              "2       0.0       0.0  ...      0.0      0.0      0.0      0.0      0.0   \n",
              "3       0.0       0.0  ...      0.0      0.0      0.0      0.0      0.0   \n",
              "4       0.0       0.0  ...      0.0      0.0      0.0      0.0      0.0   \n",
              "\n",
              "   ASV_988  ASV_990  ASV_992  ASV_994  ASV_997  \n",
              "0      0.0      0.0      0.0      0.0      0.0  \n",
              "1      0.0      0.0      0.0      0.0      0.0  \n",
              "2      0.0      0.0      0.0      0.0      0.0  \n",
              "3      0.0      0.0      0.0      0.0      0.0  \n",
              "4      0.0      0.0      0.0      0.0      0.0  \n",
              "\n",
              "[5 rows x 1805 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-0ad17a96-b201-45f2-8b30-ed0b25e729b7\" 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>host_ID</th>\n",
              "      <th>ASV_1</th>\n",
              "      <th>ASV_10</th>\n",
              "      <th>ASV_100</th>\n",
              "      <th>ASV_1001</th>\n",
              "      <th>ASV_1002</th>\n",
              "      <th>ASV_1004</th>\n",
              "      <th>ASV_1005</th>\n",
              "      <th>ASV_1007</th>\n",
              "      <th>ASV_1008</th>\n",
              "      <th>...</th>\n",
              "      <th>ASV_982</th>\n",
              "      <th>ASV_983</th>\n",
              "      <th>ASV_985</th>\n",
              "      <th>ASV_986</th>\n",
              "      <th>ASV_987</th>\n",
              "      <th>ASV_988</th>\n",
              "      <th>ASV_990</th>\n",
              "      <th>ASV_992</th>\n",
              "      <th>ASV_994</th>\n",
              "      <th>ASV_997</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2010</td>\n",
              "      <td>0.090395</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2011</td>\n",
              "      <td>0.075280</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2014</td>\n",
              "      <td>0.031537</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2015</td>\n",
              "      <td>0.254525</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2018</td>\n",
              "      <td>0.176341</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 1805 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-0ad17a96-b201-45f2-8b30-ed0b25e729b7')\"\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-0ad17a96-b201-45f2-8b30-ed0b25e729b7 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-0ad17a96-b201-45f2-8b30-ed0b25e729b7');\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-26138176-af27-4159-848d-f495b37c011c\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-26138176-af27-4159-848d-f495b37c011c')\"\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-26138176-af27-4159-848d-f495b37c011c button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df"
            }
          },
          "metadata": {},
          "execution_count": 38
        }
      ],
      "source": [
        "df = pd.read_csv('/content/drive/MyDrive/LinkPredictionProject/Data/microbiome.csv', encoding='latin1')\n",
        "df.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 39,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2B7qSpODkJTk",
        "outputId": "4b0fd317-63b7-4d5c-db99-4bd65c63ef7d"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Row sums: 0      1.0\n",
            "1      1.0\n",
            "2      1.0\n",
            "3      1.0\n",
            "4      1.0\n",
            "      ... \n",
            "864    1.0\n",
            "865    1.0\n",
            "866    1.0\n",
            "867    1.0\n",
            "868    1.0\n",
            "Length: 869, dtype: float64\n",
            "All rows sum to 1: True\n"
          ]
        }
      ],
      "source": [
        "#Check that each row sums to 1\n",
        "row_sums = df.iloc[:, 1:].sum(axis=1)\n",
        "print(f'Row sums: {row_sums}')\n",
        "print(f'All rows sum to 1: {row_sums.all()}')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sq2mgVZC315Q"
      },
      "source": [
        "This plot describes the mean percentage of the presence of each microbes in hosts  - the top 5"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 40,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 407
        },
        "id": "iw3kRYkBlfRU",
        "outputId": "97469586-2063-4533-e51f-f99624e85515"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 400x400 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# Get the top 5 microbes by mean percentage across hosts\n",
        "top_microbes = df.iloc[:, 1:].mean().sort_values(ascending=False).head(5)\n",
        "# Plot a bar plot for the top 5 microbes\n",
        "plt.figure(figsize=(4, 4))\n",
        "sns.barplot(x=top_microbes.index, y=top_microbes.values)\n",
        "plt.title('Top 5 microbes')\n",
        "plt.xlabel('Microbes')\n",
        "plt.ylabel('Mean Percentage')\n",
        "plt.xticks(rotation=45, ha='right')\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9X7C6UyAbriX"
      },
      "source": [
        "We can observe that the five microbes that make up a high percentage of all the microbes found in the host are:<br> AVS_1, AVS_2, AVS_3, AVS_5 and AVS_4"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 41,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 470
        },
        "id": "nrbIQenA-D5s",
        "outputId": "97641d66-8558-41c7-8767-69ad88257986"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x500 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "hosts_count = df.iloc[:, 1:].gt(0).sum()\n",
        "\n",
        "# Plotting\n",
        "plt.figure(figsize=(12, 5))\n",
        "\n",
        "#filter the microbes\n",
        "filter_hosts = hosts_count[hosts_count > 30]\n",
        "new_xtick_labels = [x.split('_')[-1] for x in filter_hosts.index]\n",
        "\n",
        "filter_hosts.plot(kind='bar', color='skyblue')\n",
        "\n",
        "plt.title('Count of hosts for each microbes (min 30)')\n",
        "plt.xlabel('Microbes')\n",
        "plt.ylabel('Hosts')\n",
        "plt.yticks(range(0, max(filter_hosts)+1, 50))\n",
        "plt.xticks(range(len(filter_hosts)), new_xtick_labels, fontsize=6, rotation=90, ha='right')\n",
        "plt.tight_layout()\n",
        "\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qC6ygaV3c33S"
      },
      "source": [
        "According to the graph we can observe that AVS_2 microbe is the most common among the hosts, followed by AVS_4 microbe and then AVS_1 and so on"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KUttnKjBnq_t"
      },
      "source": [
        "**histogram**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 42,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 484
        },
        "id": "D90oQ7Ee5vMk",
        "outputId": "9d5ebea9-aeb6-4405-ddf9-bad7230f82e5"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAkQAAAHTCAYAAADGawc8AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAACMbUlEQVR4nOzdeVxU1f8/8NcMyM6AoDCSgOQK7mEi7guJaKapmUuKhdqCmVIulPuSa2quZK6Ztn00SysUV0xxw3DfU9F0wEIYwQSE9+8Pf9yvIwyCgAzxej4e91H3nnPufZ/x3rlv7nJGJSICIiIionJMXdoBEBEREZU2JkRERERU7jEhIiIionKPCRERERGVe0yIiIiIqNxjQkRERETlHhMiIiIiKveYEBEREVG5x4SIiIiIyj0mRGXMnj17oFKp8L///a+0QykVKpUKw4YNK+0wCuTBgwcYPXo03N3doVar0b17d6N1q1WrhpdffvnZBVdCqlWrhkGDBpV2GAXeT9asWQOVSoWrV68Wav1t27ZFvXr1njI64yZNmgSVSoW///672NddnK5evQqVSoU1a9Y8823/V44VMj1MiEyASqUq0LRnz57SDpUKYdWqVZgzZw569eqFtWvXYuTIkaUdkoEDBw5g0qRJSE5OLu1Qyp1PP/0UmzdvLu0wiEqVqR0H5qUdAAHr1q0zmP/qq68QFRWVa7m3tzfOnj37LEOjIti1axeee+45zJ8/v7RDydOBAwcwefJkDBo0CI6OjsWyzvPnz0OtLjt/Zw0YMAB9+vSBpaXlM93up59+il69euV71dCUeXp64t9//0WFChVKOxQqw0ztOGBCZALeeOMNg/mDBw8iKioq13IATIiegfv378PCwqLIJ/bExMRiSzTKimedWBSVmZkZzMzMSjuMMkelUsHKyqpY1pWWlgZbW9tiWZepuHfvHmxsbEpt+8X1HVbe8NMqo7KzszF9+nRUrVoVVlZW6NChAy5dupSr3qFDh9CpUyc4ODjAxsYGbdq0wf79+5+4/pxnlb7//vsnbsfYcyNt27ZF27Zt81zn5MmT8dxzz8He3h69evVCSkoK0tPTMWLECLi4uMDOzg5vvvkm0tPT84xv/fr1qF27NqysrODr64vo6Ohcdf766y+89dZbcHV1haWlJerWrYtVq1bl2c9vv/0W48aNw3PPPQcbGxvo9Xqjn01aWho+/PBDuLu7w9LSErVr18bcuXMhIgD+7/mK3bt34/Tp04W65fn777+jadOmsLKywvPPP4+vvvoqV50///wTr732GpycnGBjY4NmzZrhl19+yVVv0aJFqFu3LmxsbFCxYkU0adIEGzZsAPDwWZVRo0YBALy8vJQYc56liYqKQsuWLeHo6Ag7OzvUrl0bH3/88RPjf3xfyHlGZ//+/QgLC0PlypVha2uLV199Fbdv3853XT///DNUKhVOnDihLNu4cSNUKhV69OhhUNfb2xuvv/56rnVs3rwZ9erVU/79IyMjDcqNPUP022+/oU2bNrC3t4dGo8GLL76ofHaPOnPmDNq1awcbGxs899xzmD17dr59Ah4mE2lpaVi7dq3yuT9+/CQnJytX7hwcHPDmm2/i3r17udb19ddfw9fXF9bW1nByckKfPn1w/fr1J8aQ86zShQsX8MYbb8DBwQGVK1fG+PHjISK4fv06unXrBo1GA61Wi88++8ygvbFniM6dO4fevXujcuXKsLa2Ru3atfHJJ5/k2u6ZM2fQr18/VKxYES1btgTw8Jm7qVOnonr16rC0tES1atXw8ccfG/0O2L59Oxo1agQrKyv4+Phg06ZNueokJydjxIgRyrFao0YNzJo1C9nZ2U/8jH766Sd06dIFbm5usLS0RPXq1TF16lRkZWUZ1Mt5niw2NhatW7eGjY2Ncqykp6dj4sSJqFGjBiwtLeHu7o7Ro0cb7ZOx9TZv3hzW1tbw8vJCRESEQb0nfYcV5Bxw9+5djBgxAtWqVYOlpSVcXFzw0ksv4dixYwb1CrKunH/jS5cu5bsPF+Q4eOaETE5oaKgY+6fZvXu3AJDGjRuLr6+vzJ8/XyZNmiQ2NjbStGlTg7o7d+4UCwsL8ff3l88++0zmz58vDRo0EAsLCzl06FC+MRRmO56enhIcHJxrHW3atJE2bdrkWmejRo3E399fFi5cKMOHDxeVSiV9+vSRfv36SVBQkCxZskQGDBggAGTy5MkG6wQg9erVk0qVKsmUKVNk1qxZ4unpKdbW1nLy5Emlnk6nk6pVq4q7u7tMmTJFli1bJq+88ooAkPnz5+eKycfHRxo1aiTz5s2TGTNmSFpaWp6fS3Z2trRv315UKpUMHjxYFi9eLF27dhUAMmLECBERSU1NlXXr1kmdOnWkatWqsm7dOlm3bp3odDqjn7enp6fUrl1bXF1d5eOPP5bFixfLCy+8ICqVSk6dOmXQL1dXV7G3t5dPPvlE5s2bJw0bNhS1Wi2bNm1S6i1fvlwASK9eveSLL76Qzz//XEJCQmT48OEiInL8+HHp27ev8nnkxJiamiqnTp0SCwsLadKkiXz++ecSEREhH330kbRu3dpo/I/249F9YfXq1cp+1L59e1m0aJF8+OGHYmZmJr179853Xf/884+oVCpZtGiRsuyDDz4QtVotlStXVpYlJiYKAFm8eLGyDIA0bNhQqlSpIlOnTpUFCxbI888/LzY2NvL333/niu/KlSsGy1QqldSrV0+mT58uS5YskcGDB8uAAQOUOm3atBE3Nzdxd3eXDz74QJYuXSrt27cXAPLrr7/m269169aJpaWltGrVSvncDxw4ICIiEydOVD6vHj16yNKlS2Xw4MECQEaPHm2wnmnTpolKpZLXX39dli5dKpMnT5ZKlSpJtWrV5M6dO/nGkLOdRo0aSd++fWXp0qXSpUsXASDz5s2T2rVry7vvvitLly6VFi1aCADZu3ev0v7KlSsCQFavXq0sO378uGg0GnF2dpbw8HD54osvZPTo0VK/fv1c2/Xx8ZFu3brJ0qVLZcmSJSIiEhwcrOyzS5YskYEDBwoA6d69u0Hsnp6eUqtWLXF0dJSxY8fKvHnzpH79+qJWq2X79u1KvbS0NGnQoIE4OzvLxx9/LBERETJw4EBRqVTywQcf5Pv5iIh0795devfuLXPmzJFly5bJa6+9JgDko48+MqjXpk0b0Wq1UrlyZXn//ffliy++kM2bN0tWVpZ07NhRbGxsZMSIEfLFF1/IsGHDxNzcXLp16/bE7efsYy4uLjJs2DBZuHChtGzZUgDIypUrlXr5fYcV9BzQr18/sbCwkLCwMFmxYoXMmjVLunbtKl9//bVSp6DrKug+nN9xUFqYEJmggiRE3t7ekp6eriz//PPPBYCSFGRnZ0vNmjUlMDBQsrOzlXr37t0TLy8veemll/KNoaDbESl8QlSvXj3JyMhQlvft21dUKpUEBQUZtPf39xdPT0+DZQAEgBw9elRZdu3aNbGyspJXX31VWRYSEiJVqlQxOPmJiPTp00ccHBzk3r17BjE9//zzyrL8bN68WQDItGnTDJb36tVLVCqVXLp0yaD/devWfeI6RR5+hgAkOjpaWZaYmCiWlpby4YcfKstGjBghAGTfvn3Ksrt374qXl5dUq1ZNsrKyRESkW7duT9z2nDlzciUDIiLz588XAHL79u0Cxf54P/JKiAICAgz2w5EjR4qZmZkkJyfnu766desaJE4vvPCCcmI6e/asiIhs2rRJAMjx48eVegDEwsLC4N/j+PHjAsAgwXo8IUpOThZ7e3vx8/OTf//91yCWR+Nv06aNAJCvvvpKWZaeni5arVZ69uyZb59ERGxtbfM8ZnJOJm+99ZbB8ldffVWcnZ2V+atXr4qZmZlMnz7doN7JkyfF3Nw813Jj2xk6dKiy7MGDB1K1alVRqVQyc+ZMZfmdO3fE2traIN68EqLWrVuLvb29XLt2zWBbj35uOdvt27evQZ24uDgBIIMHDzZY/tFHHwkA2bVrl7Is51jZuHGjsiwlJUWqVKkijRs3VpZNnTpVbG1t5cKFCwbrHDt2rJiZmUl8fHx+H1Ge3wdvv/222NjYyP3795VlOftCRESEQd1169aJWq02OFZFRCIiIgSA7N+/P9/t56z3s88+U5alp6dLo0aNxMXFRfkONfYdVphzgIODg4SGhhqNpTDrKug+LGL8OCgtvGVWRr355puwsLBQ5lu1agXg4e0UAIiLi8PFixfRr18//PPPP/j777/x999/Iy0tDR06dEB0dHSBLhs/aTtPY+DAgQYPY/r5+UFE8NZbbxnU8/Pzw/Xr1/HgwQOD5f7+/vD19VXmPTw80K1bN2zbtg1ZWVkQEWzcuBFdu3aFiCh9//vvvxEYGIiUlJRcl4KDg4NhbW39xNh//fVXmJmZYfjw4QbLP/zwQ4gIfvvttwJ/Do/z8fFRPl8AqFy5MmrXrm3wWf/6669o2rSpcpsBAOzs7DB06FBcvXoVZ86cAQA4Ojrixo0bOHLkSKHjyHnu6aeffirQPlIQQ4cOhUqlUuZbtWqFrKwsXLt2Ld92rVq1wr59+wA8vKx//PhxDB06FJUqVVKW79u3D46Ojrlegw8ICED16tWV+QYNGkCj0eS770ZFReHu3bsYO3ZsrmdkHo0fePi5P/qcn4WFBZo2bVqkYyPHO++8YzDfqlUr/PPPP8ptkE2bNiE7Oxu9e/c22L+1Wi1q1qyJ3bt3F2g7gwcPVv7fzMwMTZo0gYggJCREWe7o6JhrP3zc7du3ER0djbfeegseHh4GZY9/bnn179dffwUAhIWFGSz/8MMPASDXLWE3Nze8+uqryrxGo8HAgQPxxx9/QKfTAQB++OEHtGrVChUrVjT4jAICApCVlZXnbfZHPfp9cPfuXfz9999o1aoV7t27h3PnzhnUtbS0xJtvvmmw7IcffoC3tzfq1KljsP327dsDQIH+jczNzfH2228r8xYWFnj77beRmJiI2NhYg7qPf4cV5hzg6OiIQ4cO4ebNm3nG8TTnkyftw6aID1WXUY9/6VSsWBEAcOfOHQDAxYsXATw8SIxJSUlR2j3tdp7G4+t0cHAAALi7u+danp2djZSUFDg7OyvLa9asmWudtWrVwr1793D79m2o1WokJydj+fLlWL58eZ4xJCYmGsx7eXkVKPZr167Bzc0N9vb2Bsu9vb2V8qf1+OcCPPy8H/2sr127Bj8/v1z1Ht1+vXr1MGbMGOzYsQNNmzZFjRo10LFjR/Tr1w8tWrR4Yhyvv/46VqxYgcGDB2Ps2LHo0KEDevTogV69ej31Q5pPux+1atUKERERuHTpEi5fvgyVSgV/f38lURoyZAj27duHFi1a5IqtIJ/n4y5fvgwABRpjqGrVqrlO9hUrVjR45ulp5fd5aTQaXLx4ESKS57EAoMBvf+V1LFpZWaFSpUq5lv/zzz9G15OTLBV0bKbHj7dr165BrVajRo0aBsu1Wi0cHR1zHVc1atTI9dnXqlULwMPnm7RaLS5evIgTJ06gcuXKecbw+HfA406fPo1x48Zh165duU7iKSkpBvPPPfecwR+OwMPv4LNnzz719oGHid/jD5w/2s9mzZopyx//TAtzDpg9ezaCg4Ph7u4OX19fdO7cGQMHDsTzzz9f6HXleNI+bIqYEJVRxt6Mkf//YG9Otj5nzhw0atQoz7p2dnZF3g6Q91+AAJCVlZVne2PrLMi2CiKn72+88YbRA7hBgwYG8wW5OlTSiqv/wMME6fz589i6dSsiIyOxceNGLF26FBMmTMDkyZPzbWttbY3o6Gjs3r0bv/zyCyIjI/Hdd9+hffv22L59+1O9lfW0fcu5EhYdHY0///wTL7zwAmxtbdGqVSssXLgQqamp+OOPPzB9+vRi22ZBleT6C3J8q1Qq/Pbbb3nWLcixbWw7Jf25AcaPN2PfJU8jOzsbL730EkaPHp1neU5ikZfk5GS0adMGGo0GU6ZMQfXq1WFlZYVjx45hzJgxua6G5NWf7Oxs1K9fH/PmzctzG4//AVhUj8dQmHNA79690apVK/z444/Yvn075syZg1mzZmHTpk0ICgp6qvPJs9iPihsTov+onFsFGo0GAQEBJbqtihUr5jm437Vr15S/MIpTzl8rj7pw4QJsbGyUv8bs7e2RlZVV7H339PTEjh07cPfuXYOrRDmX0D09PYt1e3lt//z587mW57V9W1tbvP7663j99deRkZGBHj16YPr06QgPD4eVlVW+Jx+1Wo0OHTqgQ4cOmDdvHj799FN88skn2L17d4nvT4/y8PCAh4cH9u3bhz///FO5pdi6dWuEhYXhhx9+QFZWFlq3bl0s28s5bk6dOpXrakVxKuqJv3r16hAReHl55Xtif1ZyjvNTp049VXtPT09kZ2fj4sWLytVOAEhISEBycnKu4+rSpUsQEYPP8cKFCwAevukIPPyMUlNTn2p/3bNnD/755x9s2rTJYN+6cuVKgddRvXp1HD9+HB06dHjqf++bN2/mGpbg8X7mt32g4OeAKlWq4L333sN7772HxMREvPDCC5g+fTqCgoJK7HxSnAlwceAzRP9Rvr6+qF69OubOnYvU1NRc5U965bkwqlevjoMHDyIjI0NZtnXr1gK9/vs0YmJiDJ4Bun79On766Sd07NhRGVemZ8+e2LhxY55f0EXpe+fOnZGVlYXFixcbLJ8/fz5UKhWCgoKeet0F3f7hw4cRExOjLEtLS8Py5ctRrVo1+Pj4AECu2xsWFhbw8fGBiCAzMxMAlC/Zx5PZpKSkXNvN+auwIK8LF7dWrVph165dOHz4sJIQNWrUCPb29pg5cyasra0Nnikrio4dO8Le3h4zZszA/fv3DcqK8y9bW1vbIo0Q3qNHD5iZmWHy5Mm54hKRfG9vlYTKlSujdevWWLVqFeLj43PF8ySdO3cGACxYsMBgec7VlS5duhgsv3nzJn788UdlXq/X46uvvkKjRo2g1WoBPLzqERMTg23btuXaXnJycq5nEx+Vc3Xj0dgzMjKwdOnSJ/YlR+/evfHXX3/hyy+/zFX277//Ii0t7YnrePDgAb744guDGL744gtUrlz5ift8Qc8BWVlZuW4Buri4wM3NTTneS+p8UtTjoLjxCtF/lFqtxooVKxAUFIS6devizTffxHPPPYe//voLu3fvhkajwZYtW4plW4MHD8b//vc/dOrUCb1798bly5fx9ddfGzzQWpzq1auHwMBADB8+HJaWlsqX1KO3gmbOnIndu3fDz88PQ4YMgY+PD5KSknDs2DHs2LEjz5N+QXTt2hXt2rXDJ598gqtXr6Jhw4bYvn07fvrpJ4wYMaLE+pxj7Nix+OabbxAUFIThw4fDyckJa9euxZUrV7Bx40blOZqOHTtCq9WiRYsWcHV1xdmzZ7F48WJ06dJFubKV84X6ySefoE+fPqhQoQK6du2KKVOmIDo6Gl26dIGnpycSExOxdOlSVK1a1eBh7melVatWWL9+PVQqlbJ9MzMzNG/eHNu2bUPbtm1zPb/xtDQaDebPn4/BgwfjxRdfVMbKOX78OO7du4e1a9cWy3Z8fX2xY8cOzJs3D25ubvDy8srz2TBjqlevjmnTpiE8PBxXr15F9+7dYW9vjytXruDHH3/E0KFD8dFHHxVLrAW1cOFCtGzZEi+88AKGDh0KLy8vXL16Fb/88gvi4uLybduwYUMEBwdj+fLlyu2qw4cPY+3atejevTvatWtnUL9WrVoICQnBkSNH4OrqilWrViEhIQGrV69W6owaNQo///wzXn75ZQwaNAi+vr5IS0vDyZMn8b///Q9Xr17N9axUjubNm6NixYoIDg7G8OHDoVKpsG7dukIlxQMGDMD333+Pd955B7t370aLFi2QlZWFc+fO4fvvv8e2bdvQpEmTfNfh5uaGWbNm4erVq6hVqxa+++47xMXFYfny5U98Tqyg54C7d++iatWq6NWrFxo2bAg7Ozvs2LEDR44cUcafKqnzSVGPg2L3zN5nowIryGv3P/zwg8HyvF6DFRH5448/pEePHuLs7CyWlpbi6ekpvXv3lp07d+YbQ2G389lnn8lzzz0nlpaW0qJFCzl69KjR1+4fX2fOq89HjhwxWJ7z+uajr38DkNDQUPn666+lZs2aYmlpKY0bN5bdu3fn6kNCQoKEhoaKu7u7VKhQQbRarXTo0EGWL1/+xJjyc/fuXRk5cqS4ublJhQoVpGbNmjJnzhyD11FFCv/afZcuXXItf/wzFBG5fPmy9OrVSxwdHcXKykqaNm0qW7duNajzxRdfSOvWrZV/9+rVq8uoUaMkJSXFoN7UqVPlueeeE7Varbx+vnPnTunWrZu4ubmJhYWFuLm5Sd++fXO9vmysH3m9dv/4v23O557Xv9vjTp8+rQwB8ahp06YJABk/fnyuNjn7SUHje3zogZ9//lmaN28u1tbWotFopGnTpvLNN98o5cb+bYODg3MNFZGXc+fOSevWrcXa2loAKDHltc/nF+fGjRulZcuWYmtrK7a2tlKnTh0JDQ2V8+fP57t9Y9sJDg4WW1vbXPUf76+x74FTp07Jq6++quybtWvXNvj3MbZdEZHMzEyZPHmyeHl5SYUKFcTd3V3Cw8MNXnEX+b9jZdu2bdKgQQOxtLSUOnXq5HkM3717V8LDw6VGjRpiYWEhlSpVkubNm8vcuXMNhv7Iy/79+6VZs2ZibW0tbm5uMnr0aNm2bVuu/Ta/4zwjI0NmzZoldevWFUtLS6lYsaL4+vrK5MmTcx2Lj8tZ79GjR8Xf31+srKzE09PTYLwtkSd/hz3pHJCeni6jRo2Shg0bir29vdja2krDhg1l6dKlhV6XSOH2YWPHQWlRiZjwE05ERETlUNu2bfH3338/9XNZVHh8hoiIiIjKPSZEREREVO4xISIiIqJyj88QERERUbnHK0RERERU7nEcogLKzs7GzZs3YW9vb3KjaxIREVHeRAR3796Fm5tbvr/HyISogG7evFnsvz1DREREz8b169dRtWpVo+VMiAooZ3Tf69evm+wv9RIREZEhvV4Pd3d3g9+fzAsTogLKuU2m0WiYEBEREZUxT3rchQmRCbh9+zb0ev1Tt9doNMqvvBMREVHhMSEqZbdv38Ybbw5G0t17T70OJ3sbfL16BZMiIiKip8SEqJTp9Xok3b2Hyv49YevkWuj2aUkJuB2zEXq9ngkRERHRU2JCZCJsnVyhcTH+9Ht+bhdzLEREROUNB2YkIiKicq9UE6Lo6Gh07doVbm5uUKlU2Lx5c646Z8+exSuvvAIHBwfY2trixRdfRHx8vFJ+//59hIaGwtnZGXZ2dujZsycSEhIM1hEfH48uXbrAxsYGLi4uGDVqFB48eFDS3SMiIqIyolQTorS0NDRs2BBLlizJs/zy5cto2bIl6tSpgz179uDEiRMYP348rKyslDojR47Eli1b8MMPP2Dv3r24efMmevTooZRnZWWhS5cuyMjIwIEDB7B27VqsWbMGEyZMKPH+ERERUdlQqs8QBQUFISgoyGj5J598gs6dO2P27NnKsurVqyv/n5KSgpUrV2LDhg1o3749AGD16tXw9vbGwYMH0axZM2zfvh1nzpzBjh074OrqikaNGmHq1KkYM2YMJk2aBAsLi5LrIBEREZUJJvsMUXZ2Nn755RfUqlULgYGBcHFxgZ+fn8FttdjYWGRmZiIgIEBZVqdOHXh4eCAmJgYAEBMTg/r168PV9f/e4AoMDIRer8fp06eNbj89PR16vd5gIiIiov8mk02IEhMTkZqaipkzZ6JTp07Yvn07Xn31VfTo0QN79+4FAOh0OlhYWMDR0dGgraurK3Q6nVLn0WQopzynzJgZM2bAwcFBmfg7ZkRERP9dJpsQZWdnAwC6deuGkSNHolGjRhg7dixefvllRERElPj2w8PDkZKSokzXr18v8W0SERFR6TDZhKhSpUowNzeHj4+PwXJvb2/lLTOtVouMjAwkJycb1ElISIBWq1XqPP7WWc58Tp28WFpaKr9bxt8vIyIi+m8z2YTIwsICL774Is6fP2+w/MKFC/D09AQA+Pr6okKFCti5c6dSfv78ecTHx8Pf3x8A4O/vj5MnTyIxMVGpExUVBY1GkyvZIiIiovKpVN8yS01NxaVLl5T5K1euIC4uDk5OTvDw8MCoUaPw+uuvo3Xr1mjXrh0iIyOxZcsW7NmzBwDg4OCAkJAQhIWFwcnJCRqNBu+//z78/f3RrFkzAEDHjh3h4+ODAQMGYPbs2dDpdBg3bhxCQ0NhaWlZGt0mIiIiE1OqCdHRo0fRrl07ZT4sLAwAEBwcjDVr1uDVV19FREQEZsyYgeHDh6N27drYuHEjWrZsqbSZP38+1Go1evbsifT0dAQGBmLp0qVKuZmZGbZu3Yp3330X/v7+sLW1RXBwMKZMmfLsOkpEREQmTSUiUtpBlAV6vR4ODg5ISUkp1ueJLl++jD5vvYNqXd57qt8y0yfewNVfluLbVREGYzQRERFRwc/fJvsMEREREdGzwoSIiIiIyj0mRERERFTuMSEiIiKico8JEREREZV7TIiIiIio3GNCREREROUeEyIiIiIq95gQERERUbnHhIiIiIjKPSZEREREVO6VakIUHR2Nrl27ws3NDSqVCps3bzYoHzRoEFQqlcHUqVMngzpJSUno378/NBoNHB0dERISgtTUVIM6J06cQKtWrWBlZQV3d3fMnj27pLtGREREZUipJkRpaWlo2LAhlixZYrROp06dcOvWLWX65ptvDMr79++P06dPIyoqClu3bkV0dDSGDh2qlOv1enTs2BGenp6IjY3FnDlzMGnSJCxfvrzE+kVERERli3lpbjwoKAhBQUH51rG0tIRWq82z7OzZs4iMjMSRI0fQpEkTAMCiRYvQuXNnzJ07F25ubli/fj0yMjKwatUqWFhYoG7duoiLi8O8efMMEiciIiIqv0z+GaI9e/bAxcUFtWvXxrvvvot//vlHKYuJiYGjo6OSDAFAQEAA1Go1Dh06pNRp3bo1LCwslDqBgYE4f/487ty5Y3S76enp0Ov1BhMRERH9N5l0QtSpUyd89dVX2LlzJ2bNmoW9e/ciKCgIWVlZAACdTgcXFxeDNubm5nBycoJOp1PquLq6GtTJmc+pk5cZM2bAwcFBmdzd3Yuza0RERGRCSvWW2ZP06dNH+f/69eujQYMGqF69Ovbs2YMOHTqU6LbDw8MRFhamzOv1eiZFRERE/1EmfYXocc8//zwqVaqES5cuAQC0Wi0SExMN6jx48ABJSUnKc0darRYJCQkGdXLmjT2bBDx8dkmj0RhMRERE9N9UphKiGzdu4J9//kGVKlUAAP7+/khOTkZsbKxSZ9euXcjOzoafn59SJzo6GpmZmUqdqKgo1K5dGxUrVny2HSAiIiKTVKoJUWpqKuLi4hAXFwcAuHLlCuLi4hAfH4/U1FSMGjUKBw8exNWrV7Fz505069YNNWrUQGBgIADA29sbnTp1wpAhQ3D48GHs378fw4YNQ58+feDm5gYA6NevHywsLBASEoLTp0/ju+++w+eff25wO4yIiIjKt1JNiI4ePYrGjRujcePGAICwsDA0btwYEyZMgJmZGU6cOIFXXnkFtWrVQkhICHx9fbFv3z5YWloq61i/fj3q1KmDDh06oHPnzmjZsqXBGEMODg7Yvn07rly5Al9fX3z44YeYMGECX7knIiIiRak+VN22bVuIiNHybdu2PXEdTk5O2LBhQ751GjRogH379hU6PiIiIiofytQzREREREQlgQkRERERlXtMiIiIiKjcY0JERERE5R4TIiIiIir3mBARERFRuceEiIiIiMo9JkRERERU7jEhIiIionKPCRERERGVe0yIiIiIqNxjQkRERETlXqkmRNHR0ejatSvc3NygUqmwefNmo3XfeecdqFQqLFiwwGB5UlIS+vfvD41GA0dHR4SEhCA1NdWgzokTJ9CqVStYWVnB3d0ds2fPLoHeEBERUVlVqglRWloaGjZsiCVLluRb78cff8TBgwfh5uaWq6x///44ffo0oqKisHXrVkRHR2Po0KFKuV6vR8eOHeHp6YnY2FjMmTMHkyZNwvLly4u9P0RERFQ2mZfmxoOCghAUFJRvnb/++gvvv/8+tm3bhi5duhiUnT17FpGRkThy5AiaNGkCAFi0aBE6d+6MuXPnws3NDevXr0dGRgZWrVoFCwsL1K1bF3FxcZg3b55B4vS49PR0pKenK/N6vb4IPSUiIiJTZtLPEGVnZ2PAgAEYNWoU6tatm6s8JiYGjo6OSjIEAAEBAVCr1Th06JBSp3Xr1rCwsFDqBAYG4vz587hz547Rbc+YMQMODg7K5O7uXow9IyIiIlNi0gnRrFmzYG5ujuHDh+dZrtPp4OLiYrDM3NwcTk5O0Ol0Sh1XV1eDOjnzOXXyEh4ejpSUFGW6fv16UbpCREREJqxUb5nlJzY2Fp9//jmOHTsGlUr1zLdvaWkJS0vLZ75dIiIievZM9grRvn37kJiYCA8PD5ibm8Pc3BzXrl3Dhx9+iGrVqgEAtFotEhMTDdo9ePAASUlJ0Gq1Sp2EhASDOjnzOXWIiIiofDPZhGjAgAE4ceIE4uLilMnNzQ2jRo3Ctm3bAAD+/v5ITk5GbGys0m7Xrl3Izs6Gn5+fUic6OhqZmZlKnaioKNSuXRsVK1Z8tp0iIiIik1Sqt8xSU1Nx6dIlZf7KlSuIi4uDk5MTPDw84OzsbFC/QoUK0Gq1qF27NgDA29sbnTp1wpAhQxAREYHMzEwMGzYMffr0UV7R79evHyZPnoyQkBCMGTMGp06dwueff4758+c/u44SERGRSSvVhOjo0aNo166dMh8WFgYACA4Oxpo1awq0jvXr12PYsGHo0KED1Go1evbsiYULFyrlDg4O2L59O0JDQ+Hr64tKlSphwoQJ+b5yT0REROVLqSZEbdu2hYgUuP7Vq1dzLXNycsKGDRvybdegQQPs27evsOERERFROWGyzxARERERPStMiIiIiKjcY0JERERE5R4TIiIiIir3mBARERFRuceEiIiIiMo9JkRERERU7jEhIiIionKPCRERERGVe0yIiIiIqNxjQkRERETlXqkmRNHR0ejatSvc3NygUqmwefNmg/JJkyahTp06sLW1RcWKFREQEIBDhw4Z1ElKSkL//v2h0Wjg6OiIkJAQpKamGtQ5ceIEWrVqBSsrK7i7u2P27Nkl3TUiIiIqQ0o1IUpLS0PDhg2xZMmSPMtr1aqFxYsX4+TJk/j9999RrVo1dOzYEbdv31bq9O/fH6dPn0ZUVBS2bt2K6Ohog1+y1+v16NixIzw9PREbG4s5c+Zg0qRJWL58eYn3j4iIiMqGUv21+6CgIAQFBRkt79evn8H8vHnzsHLlSpw4cQIdOnTA2bNnERkZiSNHjqBJkyYAgEWLFqFz586YO3cu3NzcsH79emRkZGDVqlWwsLBA3bp1ERcXh3nz5hkkTkRERFR+lZlniDIyMrB8+XI4ODigYcOGAICYmBg4OjoqyRAABAQEQK1WK7fWYmJi0Lp1a1hYWCh1AgMDcf78edy5c8fo9tLT06HX6w0mIiIi+m8y+YRo69atsLOzg5WVFebPn4+oqChUqlQJAKDT6eDi4mJQ39zcHE5OTtDpdEodV1dXgzo58zl18jJjxgw4ODgok7u7e3F2i4iIiEyIySdE7dq1Q1xcHA4cOIBOnTqhd+/eSExMLPHthoeHIyUlRZmuX79e4tskIiKi0mHyCZGtrS1q1KiBZs2aYeXKlTA3N8fKlSsBAFqtNldy9ODBAyQlJUGr1Sp1EhISDOrkzOfUyYulpSU0Go3BRERERP9NJp8QPS47Oxvp6ekAAH9/fyQnJyM2NlYp37VrF7Kzs+Hn56fUiY6ORmZmplInKioKtWvXRsWKFZ9t8ERERGSSSjUhSk1NRVxcHOLi4gAAV65cQVxcHOLj45GWloaPP/4YBw8exLVr1xAbG4u33noLf/31F1577TUAgLe3Nzp16oQhQ4bg8OHD2L9/P4YNG4Y+ffrAzc0NwMM31SwsLBASEoLTp0/ju+++w+eff46wsLDS6jYRERGZmFJ97f7o0aNo166dMp+TpAQHByMiIgLnzp3D2rVr8ffff8PZ2Rkvvvgi9u3bh7p16ypt1q9fj2HDhqFDhw5Qq9Xo2bMnFi5cqJQ7ODhg+/btCA0Nha+vLypVqoQJEybwlXsiIiJSlGpC1LZtW4iI0fJNmzY9cR1OTk7YsGFDvnUaNGiAffv2FTo+IiIiKh/K3DNERERERMWNCRERERGVe0yIiIiIqNxjQkRERETlHhMiIiIiKveYEBEREVG5x4SIiIiIyj0mRERERFTuMSEiIiKico8JEREREZV7TIiIiIio3GNCREREROVeqSZE0dHR6Nq1K9zc3KBSqbB582alLDMzE2PGjEH9+vVha2sLNzc3DBw4EDdv3jRYR1JSEvr37w+NRgNHR0eEhIQgNTXVoM6JEyfQqlUrWFlZwd3dHbNnz34W3SMiIqIyolQTorS0NDRs2BBLlizJVXbv3j0cO3YM48ePx7Fjx7Bp0yacP38er7zyikG9/v374/Tp04iKisLWrVsRHR2NoUOHKuV6vR4dO3aEp6cnYmNjMWfOHEyaNAnLly8v8f4RERFR2WBemhsPCgpCUFBQnmUODg6IiooyWLZ48WI0bdoU8fHx8PDwwNmzZxEZGYkjR46gSZMmAIBFixahc+fOmDt3Ltzc3LB+/XpkZGRg1apVsLCwQN26dREXF4d58+YZJE6PS09PR3p6ujKv1+uLocdERERkisrUM0QpKSlQqVRwdHQEAMTExMDR0VFJhgAgICAAarUahw4dUuq0bt0aFhYWSp3AwECcP38ed+7cMbqtGTNmwMHBQZnc3d1LplNERERU6spMQnT//n2MGTMGffv2hUajAQDodDq4uLgY1DM3N4eTkxN0Op1Sx9XV1aBOznxOnbyEh4cjJSVFma5fv16c3SEiIiITUqq3zAoqMzMTvXv3hohg2bJlz2SblpaWsLS0fCbbIiIiotJl8glRTjJ07do17Nq1S7k6BABarRaJiYkG9R88eICkpCRotVqlTkJCgkGdnPmcOkRERFS+mfQts5xk6OLFi9ixYwecnZ0Nyv39/ZGcnIzY2Fhl2a5du5CdnQ0/Pz+lTnR0NDIzM5U6UVFRqF27NipWrPhsOkJEREQmrVQTotTUVMTFxSEuLg4AcOXKFcTFxSE+Ph6ZmZno1asXjh49ivXr1yMrKws6nQ46nQ4ZGRkAAG9vb3Tq1AlDhgzB4cOHsX//fgwbNgx9+vSBm5sbAKBfv36wsLBASEgITp8+je+++w6ff/45wsLCSqvbREREZGJK9ZbZ0aNH0a5dO2U+J0kJDg7GpEmT8PPPPwMAGjVqZNBu9+7daNu2LQBg/fr1GDZsGDp06AC1Wo2ePXti4cKFSl0HBwds374doaGh8PX1RaVKlTBhwoR8X7knIiKi8qVUE6K2bdtCRIyW51eWw8nJCRs2bMi3ToMGDbBv375Cx0dERETlg0k/Q0RERET0LDAhIiIionKPCRERERGVe0yIiIiIqNxjQkRERETlHhMiIiIiKveYEBEREVG5x4SIiIiIyj0mRERERFTuMSEiIiKico8JEREREZV7T5UQXb58GePGjUPfvn2RmJgIAPjtt99w+vTpQq0nOjoaXbt2hZubG1QqFTZv3mxQvmnTJnTs2BHOzs5QqVSIi4vLtY779+8jNDQUzs7OsLOzQ8+ePZGQkGBQJz4+Hl26dIGNjQ1cXFwwatQoPHjwoFCxEhER0X9XoROivXv3on79+jh06BA2bdqE1NRUAMDx48cxceLEQq0rLS0NDRs2xJIlS4yWt2zZErNmzTK6jpEjR2LLli344YcfsHfvXty8eRM9evRQyrOystClSxdkZGTgwIEDWLt2LdasWYMJEyYUKlYiIiL67yr0r92PHTsW06ZNQ1hYGOzt7ZXl7du3x+LFiwu1rqCgIAQFBRktHzBgAADg6tWreZanpKRg5cqV2LBhA9q3bw8AWL16Nby9vXHw4EE0a9YM27dvx5kzZ7Bjxw64urqiUaNGmDp1KsaMGYNJkybBwsKiUDETERHRf0+hrxCdPHkSr776aq7lLi4u+Pvvv4slqIKKjY1FZmYmAgIClGV16tSBh4cHYmJiAAAxMTGoX78+XF1dlTqBgYHQ6/X53uJLT0+HXq83mIiIiOi/qdAJkaOjI27dupVr+R9//IHnnnuuWIIqKJ1OBwsLCzg6Ohosd3V1hU6nU+o8mgzllOeUGTNjxgw4ODgok7u7e/EGT0RERCaj0AlRnz59MGbMGOh0OqhUKmRnZ2P//v346KOPMHDgwJKIsVSEh4cjJSVFma5fv17aIREREVEJKXRC9Omnn6JOnTpwd3dHamoqfHx80Lp1azRv3hzjxo0riRiN0mq1yMjIQHJyssHyhIQEaLVapc7jb53lzOfUyYulpSU0Go3BRERERP9NhU6ILCws8OWXX+Ly5cvYunUrvv76a5w7dw7r1q2DmZlZScRolK+vLypUqICdO3cqy86fP4/4+Hj4+/sDAPz9/XHy5ElleAAAiIqKgkajgY+PzzONl4iIiExTod8yy+Hh4aE8V6NSqZ5qHampqbh06ZIyf+XKFcTFxcHJyQkeHh5ISkpCfHw8bt68CeBhsgM8vLKj1Wrh4OCAkJAQhIWFwcnJCRqNBu+//z78/f3RrFkzAEDHjh3h4+ODAQMGYPbs2dDpdBg3bhxCQ0NhaWn5tN0nIiKi/5CnGphx5cqVqFevHqysrGBlZYV69ephxYoVhV7P0aNH0bhxYzRu3BgAEBYWhsaNGytjBP38889o3LgxunTpAuDh80uNGzdGRESEso758+fj5ZdfRs+ePdG6dWtotVps2rRJKTczM8PWrVthZmYGf39/vPHGGxg4cCCmTJnyNF0nIiKi/6BCXyGaMGEC5s2bp1yJAR6+2j5y5EjEx8cXKtFo27YtRMRo+aBBgzBo0KB812FlZYUlS5YYHdwRADw9PfHrr78WOC4iIiIqXwqdEC1btgxffvkl+vbtqyx75ZVX0KBBA7z//vu88kJERERlTqFvmWVmZqJJkya5lvv6+vL3wYiIiKhMKnRCNGDAACxbtizX8uXLl6N///7FEhQRERHRs1SgW2ZhYWHK/6tUKqxYsQLbt29X3uQ6dOgQ4uPj/1MDMxIREVH5UaCE6I8//jCY9/X1BQBcvnwZAFCpUiVUqlQp398GIyIiIjJVBUqIdu/eXdJxEBEREZWapxqHKMeNGzdw48aN4oqFiIiIqFQUOiHKzs7GlClT4ODgAE9PT3h6esLR0RFTp05FdnZ2ScRIREREVKIKPQ7RJ598gpUrV2LmzJlo0aIFAOD333/HpEmTcP/+fUyfPr3YgyQiIiIqSYVOiNauXYsVK1bglVdeUZY1aNAAzz33HN577z0mRERERFTmFPqWWVJSEurUqZNreZ06dZCUlFQsQRERERE9S4VOiBo2bIjFixfnWr548WI0bNiwUOuKjo5G165d4ebmBpVKhc2bNxuUiwgmTJiAKlWqwNraGgEBAbh48aJBnaSkJPTv3x8ajQaOjo4ICQlBamqqQZ0TJ06gVatWsLKygru7O2bPnl2oOImIiOi/rdAJ0ezZs7Fq1Sr4+PggJCQEISEh8PHxwZo1azBnzpxCrSstLQ0NGzY0+sOss2fPxsKFCxEREYFDhw7B1tYWgYGBuH//vlKnf//+OH36NKKiorB161ZER0dj6NChSrler0fHjh3h6emJ2NhYzJkzB5MmTcLy5csL23UiIiL6jyr0M0Rt2rTBhQsXsGTJEpw7dw4A0KNHD7z33ntwc3Mr1LqCgoIQFBSUZ5mIYMGCBRg3bhy6desGAPjqq6/g6uqKzZs3o0+fPjh79iwiIyNx5MgR5ffVFi1ahM6dO2Pu3Llwc3PD+vXrkZGRgVWrVsHCwgJ169ZFXFwc5s2bZ5A4ERERUflVqCtEmZmZ6NChA9LS0jB9+nRs3LgRGzduxLRp0wqdDD3JlStXoNPpEBAQoCxzcHCAn58fYmJiAAAxMTFwdHQ0+LHZgIAAqNVqHDp0SKnTunVrWFhYKHUCAwNx/vx53Llzx+j209PTodfrDSYiIiL6bypUQlShQgWcOHGipGIxoNPpAACurq4Gy11dXZUynU4HFxcXg3Jzc3M4OTkZ1MlrHY9uIy8zZsyAg4ODMrm7uxetQ0RERGSyCv0M0RtvvIGVK1eWRCwmJTw8HCkpKcp0/fr10g6JiIiISkihnyF68OABVq1ahR07dsDX1xe2trYG5fPmzSuWwLRaLQAgISEBVapUUZYnJCSgUaNGSp3ExMRc8SUlJSnttVotEhISDOrkzOfUyYulpSUsLS2L3A8iIiIyfYW+QnTq1Cm88MILsLe3x4ULF/DHH38oU1xcXLEF5uXlBa1Wi507dyrL9Ho9Dh06BH9/fwCAv78/kpOTERsbq9TZtWsXsrOz4efnp9SJjo5GZmamUicqKgq1a9dGxYoViy1eIiIiKrsKfYWoOH/5PjU1FZcuXVLmr1y5gri4ODg5OcHDwwMjRozAtGnTULNmTXh5eWH8+PFwc3ND9+7dAQDe3t7o1KkThgwZgoiICGRmZmLYsGHo06eP8pB3v379MHnyZISEhGDMmDE4deoUPv/8c8yfP7/Y+kFERERlW6ETopSUFGRlZcHJyclgeVJSEszNzaHRaAq8rqNHj6Jdu3bKfFhYGAAgODgYa9aswejRo5GWloahQ4ciOTkZLVu2RGRkJKysrJQ269evx7Bhw9ChQweo1Wr07NkTCxcuVModHBywfft2hIaGwtfXF5UqVcKECRP4yj0REREpCp0Q9enTB127dsV7771nsPz777/Hzz//jF9//bXA62rbti1ExGi5SqXClClTMGXKFKN1nJycsGHDhny306BBA+zbt6/AcREREVH5UuhniA4dOmRwVSdH27ZtlbF/iIiIiMqSQidE6enpePDgQa7lmZmZ+Pfff4slKCIiIqJnqdAJUdOmTfP8HbCIiAj4+voWS1BEREREz1KhnyGaNm0aAgICcPz4cXTo0AEAsHPnThw5cgTbt28v9gCJiIiISlqhrxC1aNECMTExcHd3x/fff48tW7agRo0aOHHiBFq1alUSMRIRERGVqEJfIQKARo0aYf369cUdCxEREVGpKFBCpNfrlfGFnvSr74UZh4iIiIjIFBQoIapYsSJu3boFFxcXODo6QqVS5aojIlCpVMjKyir2IImIiIhKUoESol27dikjUxfnT3cQERERmYICJURt2rTJ8/+JiIiI/gue6qHq+/fv48SJE0hMTER2drZB2SuvvFIsgRERERE9K4VOiCIjIzFw4ED8/fffucr4DBERERGVRYUeh+j999/Ha6+9hlu3biE7O9tgKolk6O7duxgxYgQ8PT1hbW2N5s2b48iRI0q5iGDChAmoUqUKrK2tERAQgIsXLxqsIykpCf3794dGo4GjoyNCQkKQmppa7LESERFR2VTohCghIQFhYWFwdXUtiXhyGTx4MKKiorBu3TqcPHkSHTt2REBAAP766y8AwOzZs7Fw4UJERETg0KFDsLW1RWBgIO7fv6+so3///jh9+jSioqKwdetWREdHY+jQoc8kfiIiIjJ9hU6IevXqhT179pRAKLn9+++/2LhxI2bPno3WrVujRo0amDRpEmrUqIFly5ZBRLBgwQKMGzcO3bp1Q4MGDfDVV1/h5s2b2Lx5MwDg7NmziIyMxIoVK+Dn54eWLVti0aJF+Pbbb3Hz5k2j205PT4derzeYiIiI6L+p0M8QLV68GK+99hr27duH+vXro0KFCgblw4cPL7bgHjx4gKysLFhZWRkst7a2xu+//44rV65Ap9MhICBAKXNwcICfnx9iYmLQp08fxMTEwNHREU2aNFHqBAQEQK1W49ChQ3j11Vfz3PaMGTMwefLkYusLERERma5CJ0TffPMNtm/fDisrK+zZs8dgkEaVSlWsCZG9vT38/f0xdepUeHt7w9XVFd988w1iYmJQo0YN6HQ6AMh1+87V1VUp0+l0cHFxMSg3NzeHk5OTUicv4eHhCAsLU+b1ej3c3d2Lq2tERERkQgqdEH3yySeYPHkyxo4dC7W60HfcCm3dunV466238Nxzz8HMzAwvvPAC+vbti9jY2BLdrqWlJSwtLUt0G0RERGQaCp3RZGRk4PXXX38myRAAVK9eHXv37kVqaiquX7+Ow4cPIzMzE88//zy0Wi2Ahw96PyohIUEp02q1SExMNCh/8OABkpKSlDpERERUvhU6qwkODsZ3331XErHky9bWFlWqVMGdO3ewbds2dOvWDV5eXtBqtdi5c6dST6/X49ChQ/D39wcA+Pv7Izk52eCK0q5du5CdnQ0/P79n3g8iIiIyPYW+ZZaVlYXZs2dj27ZtaNCgQa6HqufNm1dswQHAtm3bICKoXbs2Ll26hFGjRqFOnTp48803oVKpMGLECEybNg01a9aEl5cXxo8fDzc3N3Tv3h0A4O3tjU6dOmHIkCGIiIhAZmYmhg0bhj59+sDNza1YYyUiIqKyqdAJ0cmTJ9G4cWMAwKlTpwzKHn3AurikpKQgPDwcN27cgJOTE3r27Inp06cridjo0aORlpaGoUOHIjk5GS1btkRkZKTBm2nr16/HsGHD0KFDB6jVavTs2RMLFy4s9liJiIiobFKJiJR2EGWBXq+Hg4MDUlJSoNFoim29ly9fRp+33kG1Lu9B41K18HEl3sDVX5bi21URqF69erHFRURE9F9Q0PP3s3kymoiIiMiEMSEiIiKico8JEREREZV7TIiIiIio3CtQQvTCCy/gzp07AIApU6bg3r17JRoUERER0bNUoITo7NmzSEtLAwBMnjwZqampJRoUERER0bNUoHGIGjVqhDfffBMtW7aEiGDu3Lmws7PLs+6ECROKNUAiIiKiklaghGjNmjWYOHEitm7dCpVKhd9++w3m5rmbqlQqJkRERERU5hQoIapduza+/fZbAIBarcbOnTvh4uJSooERERERPSuF/umO7OzskoiDiIiIqNQUOiECHv7cxIIFC3D27FkAgI+PDz744AP+dAQRERGVSYUeh2jbtm3w8fHB4cOH0aBBAzRo0ACHDh1C3bp1ERUVVazBZWVlYfz48fDy8oK1tTWqV6+OqVOn4tGfXxMRTJgwAVWqVIG1tTUCAgJw8eJFg/UkJSWhf//+0Gg0cHR0REhICN+UIyIiIkWhrxCNHTsWI0eOxMyZM3MtHzNmDF566aViC27WrFlYtmwZ1q5di7p16+Lo0aN488034eDggOHDhwMAZs+ejYULF2Lt2rXw8vLC+PHjERgYiDNnzii/eN+/f3/cunULUVFRyMzMxJtvvomhQ4diw4YNxRYrERERlV2FvkJ09uxZhISE5Fr+1ltv4cyZM8USVI4DBw6gW7du6NKlC6pVq4ZevXqhY8eOOHz4MICHV4cWLFiAcePGoVu3bmjQoAG++uor3Lx5E5s3b1bijYyMxIoVK+Dn54eWLVti0aJF+Pbbb3Hz5s1ijZeIiIjKpkInRJUrV0ZcXFyu5XFxccX+5lnz5s2xc+dOXLhwAQBw/Phx/P777wgKCgIAXLlyBTqdDgEBAUobBwcH+Pn5ISYmBgAQExMDR0dHNGnSRKkTEBAAtVqNQ4cOGd12eno69Hq9wURERET/TYW+ZTZkyBAMHToUf/75J5o3bw4A2L9/P2bNmoWwsLBiDW7s2LHQ6/WoU6cOzMzMkJWVhenTp6N///4AAJ1OBwBwdXU1aOfq6qqU6XS6XImaubk5nJyclDp5mTFjBiZPnlyc3SEiIiITVeiEaPz48bC3t8dnn32G8PBwAICbmxsmTZqkPNdTXL7//nusX78eGzZsQN26dREXF4cRI0bAzc0NwcHBxbqtx4WHhxskeHq9Hu7u7iW6TSIiIiodhU6IVCoVRo4ciZEjR+Lu3bsAAHt7+2IPDABGjRqFsWPHok+fPgCA+vXr49q1a5gxYwaCg4Oh1WoBAAkJCahSpYrSLiEhAY0aNQIAaLVaJCYmGqz3wYMHSEpKUtrnxdLSEpaWlsXcIyIiIjJFhX6G6FH29vYllgwBwL1796BWG4ZoZmamDA7p5eUFrVaLnTt3KuV6vR6HDh2Cv78/AMDf3x/JycmIjY1V6uzatQvZ2dnw8/MrsdiJiIio7HiqgRmfla5du2L69Onw8PBA3bp18ccff2DevHl46623ADy8WjVixAhMmzYNNWvWVF67d3NzQ/fu3QEA3t7e6NSpE4YMGYKIiAhkZmZi2LBh6NOnD9zc3Eqxd0RERGQqTDohWrRoEcaPH4/33nsPiYmJcHNzw9tvv23wA7KjR49GWloahg4diuTkZLRs2RKRkZHKGEQAsH79egwbNgwdOnSAWq1Gz549sXDhwtLoEhEREZkglTw67DMZpdfr4eDggJSUFGg0mmJb7+XLl9HnrXdQrct70LhULXxciTdw9Zel+HZVBH86hYiI6DEFPX8X6hmizMxMdOjQIddPYxARERGVZYVKiCpUqIATJ06UVCxEREREpaLQb5m98cYbWLlyZUnEQkRERFQqCv1Q9YMHD7Bq1Srs2LEDvr6+sLW1NSifN29esQVHRERE9CwUOiE6deoUXnjhBQBQfmMsh0qlKp6oiIiIiJ6hQidEu3fvLok4iIiIiErNU49UfenSJWzbtg3//vsvAIBv7xMREVFZVeiE6J9//kGHDh1Qq1YtdO7cGbdu3QIAhISE4MMPPyz2AImIiIhKWqETopEjR6JChQqIj4+HjY2Nsvz1119HZGRksQZHRERE9CwU+hmi7du3Y9u2baha1XBU5Zo1a+LatWvFFhgRERHRs1LoK0RpaWkGV4ZyJCUlwdLSsliCIiIiInqWCp0QtWrVCl999ZUyr1KpkJ2djdmzZ6Ndu3bFGhwRERHRs1DohGj27NlYvnw5goKCkJGRgdGjR6NevXqIjo7GrFmzij3AatWqQaVS5ZpCQ0MBAPfv30doaCicnZ1hZ2eHnj17IiEhwWAd8fHx6NKlC2xsbODi4oJRo0bhwYMHxR4rERERlU2FTojq1auHCxcuoGXLlujWrRvS0tLQo0cP/PHHHyXya+tHjhzBrVu3lCkqKgoA8NprrwF4+JD3li1b8MMPP2Dv3r24efMmevToobTPyspCly5dkJGRgQMHDmDt2rVYs2YNJkyYUOyxEhERUdlU6IeqAcDBwQGffPJJcceSp8qVKxvMz5w5E9WrV0ebNm2QkpKClStXYsOGDWjfvj0AYPXq1fD29sbBgwfRrFkzbN++HWfOnMGOHTvg6uqKRo0aYerUqRgzZgwmTZoECwuLPLebnp6O9PR0ZV6v15dcJ4mIiKhUPdXAjHfu3MHcuXMREhKCkJAQfPbZZ0hKSiru2HLJyMjA119/jbfeegsqlQqxsbHIzMxEQECAUqdOnTrw8PBATEwMACAmJgb169eHq6urUicwMBB6vR6nT582uq0ZM2bAwcFBmdzd3UuuY0RERFSqCp0QRUdHo1q1ali4cCHu3LmDO3fuYOHChfDy8kJ0dHRJxKjYvHkzkpOTMWjQIACATqeDhYUFHB0dDeq5urpCp9MpdR5NhnLKc8qMCQ8PR0pKijJdv369+DpCREREJqXQt8xCQ0Px+uuvY9myZTAzMwPw8Dmd9957D6GhoTh58mSxB5lj5cqVCAoKgpubW4ltI4elpSWHESAiIionCn2F6NKlS/jwww+VZAgAzMzMEBYWhkuXLhVrcI+6du0aduzYgcGDByvLtFotMjIykJycbFA3ISEBWq1WqfP4W2c58zl1iIiIqHwrdEL0wgsv4OzZs7mWnz17Fg0bNiyWoPKyevVquLi4oEuXLsoyX19fVKhQATt37lSWnT9/HvHx8fD39wcA+Pv74+TJk0hMTFTqREVFQaPRwMfHp8TiJSIiorKjQLfMTpw4ofz/8OHD8cEHH+DSpUto1qwZAODgwYNYsmQJZs6cWSJBZmdnY/Xq1QgODoa5+f+F7ODggJCQEISFhcHJyQkajQbvv/8+/P39ldg6duwIHx8fDBgwALNnz4ZOp8O4ceMQGhrKW2JEREQEoIAJUaNGjaBSqSAiyrLRo0fnqtevXz+8/vrrxRfd/7djxw7Ex8fjrbfeylU2f/58qNVq9OzZE+np6QgMDMTSpUuVcjMzM2zduhXvvvsu/P39YWtri+DgYEyZMqXY4yQiIqKyqUAJ0ZUrV0o6jnx17NjRIBl7lJWVFZYsWYIlS5YYbe/p6Ylff/21pMIjIiKiMq5ACZGnp2dJx0FERERUap5qpOqbN2/i999/R2JiIrKzsw3Khg8fXiyBERERET0rhU6I1qxZg7fffhsWFhZwdnaGSqVSylQqFRMiIiIiKnMKnRCNHz8eEyZMQHh4ONTqp/rlDyIiIiKTUuiM5t69e+jTpw+TISIiIvrPKHRWExISgh9++KEkYiEiIiIqFYW+ZTZjxgy8/PLLiIyMRP369VGhQgWD8nnz5hVbcERERETPwlMlRNu2bUPt2rUBINdD1URERERlTaETos8++wyrVq3CoEGDSiAcIiIiomev0M8QWVpaokWLFiURCxEREVGpKHRC9MEHH2DRokUlEQsRERFRqSh0QnT48GGsXbsWzz//PLp27YoePXoYTMXtr7/+whtvvAFnZ2dYW1ujfv36OHr0qFIuIpgwYQKqVKkCa2trBAQE4OLFiwbrSEpKQv/+/aHRaODo6IiQkBCkpqYWe6xERERUNhX6GSJHR8cSSXzycufOHbRo0QLt2rXDb7/9hsqVK+PixYuoWLGiUmf27NlYuHAh1q5dCy8vL4wfPx6BgYE4c+YMrKysAAD9+/fHrVu3EBUVhczMTLz55psYOnQoNmzY8Ez6QURERKat0AnR6tWrSyKOPM2aNQvu7u4G2/Ty8lL+X0SwYMECjBs3Dt26dQMAfPXVV3B1dcXmzZvRp08fnD17FpGRkThy5AiaNGkCAFi0aBE6d+6MuXPnws3N7Zn1h4iIiEyTSQ83/fPPP6NJkyZ47bXX4OLigsaNG+PLL79Uyq9cuQKdToeAgABlmYODA/z8/BATEwMAiImJgaOjo5IMAUBAQADUajUOHTpkdNvp6enQ6/UGExEREf03FfoKkZeXV77jDf35559FCujxdS1btgxhYWH4+OOPceTIEQwfPhwWFhYIDg6GTqcDALi6uhq0c3V1Vcp0Oh1cXFwMys3NzeHk5KTUycuMGTMwefLkYusLERERma5CJ0QjRowwmM/MzMQff/yByMhIjBo1qrjiAgBkZ2ejSZMm+PTTTwEAjRs3xqlTpxAREYHg4OBi3dbjwsPDERYWpszr9Xq4u7uX6DaJiIiodBQ6Ifrggw/yXL5kyRKDt7+KQ5UqVeDj42OwzNvbGxs3bgQAaLVaAEBCQgKqVKmi1ElISECjRo2UOomJiQbrePDgAZKSkpT2ebG0tISlpWVxdIOIiIhMXLE9QxQUFKQkKsWlRYsWOH/+vMGyCxcuwNPTE8DD23darRY7d+5UyvV6PQ4dOgR/f38AgL+/P5KTkxEbG6vU2bVrF7Kzs+Hn51es8RIREVHZVOgrRMb873//g5OTU3GtDgAwcuRING/eHJ9++il69+6Nw4cPY/ny5Vi+fDmAh7+dNmLECEybNg01a9ZUXrt3c3ND9+7dATy8otSpUycMGTIEERERyMzMxLBhw9CnTx++YUZEREQAniIhaty4scFD1SICnU6H27dvY+nSpcUa3Isvvogff/wR4eHhmDJlCry8vLBgwQL0799fqTN69GikpaVh6NChSE5ORsuWLREZGamMQQQA69evx7Bhw9ChQweo1Wr07NkTCxcuLNZYiYiIqOwqdEKUc+Ulh1qtRuXKldG2bVvUqVOnuOJSvPzyy3j55ZeNlqtUKkyZMgVTpkwxWsfJyYmDMBIREZFRhU6IJk6cWBJxEBEREZUakx6YkYiIiOhZKPAVIrVane+AjMDD21cPHjwoclBEREREz1KBE6Iff/zRaFlMTAwWLlyI7OzsYgmKiIiI6FkqcEKU8+Opjzp//jzGjh2LLVu2oH///vk+2ExERERkqp7qGaKbN29iyJAhqF+/Ph48eIC4uDisXbtWGTCRiIiIqCwpVEKUkpKCMWPGoEaNGjh9+jR27tyJLVu2oF69eiUVHxEREVGJK/Ats9mzZ2PWrFnQarX45ptv8ryFRkRERFQWFTghGjt2LKytrVGjRg2sXbsWa9euzbPepk2bii04IiIiomehwAnRwIEDn/jaPREREVFZVOCEaM2aNSUYBhEREVHpMfmRqidNmgSVSmUwPfqbaffv30doaCicnZ1hZ2eHnj17IiEhwWAd8fHx6NKlC2xsbODi4oJRo0ZxAEkiIiJSFPq3zEpD3bp1sWPHDmXe3Pz/wh45ciR++eUX/PDDD3BwcMCwYcPQo0cP7N+/HwCQlZWFLl26QKvV4sCBA7h16xYGDhyIChUq4NNPP33mfSEiIiLTUyYSInNzc2i12lzLU1JSsHLlSmzYsAHt27cHAKxevRre3t44ePAgmjVrhu3bt+PMmTPYsWMHXF1d0ahRI0ydOhVjxozBpEmTYGFh8ay7Q0RERCbG5G+ZAcDFixfh5uaG559/Hv3790d8fDwAIDY2FpmZmQgICFDq1qlTBx4eHoiJiQHw8GdF6tevD1dXV6VOYGAg9Ho9Tp8+bXSb6enp0Ov1BhMRERH9N5l8QuTn54c1a9YgMjISy5Ytw5UrV9CqVSvcvXsXOp0OFhYWcHR0NGjj6uoKnU4HANDpdAbJUE55TpkxM2bMgIODgzK5u7sXb8eIiIjIZJj8LbOgoCDl/xs0aAA/Pz94enri+++/h7W1dYltNzw8HGFhYcq8Xq9nUkRERPQfZfJXiB7n6OiIWrVq4dKlS9BqtcjIyEBycrJBnYSEBOWZI61Wm+uts5z5vJ5LymFpaQmNRmMwERER0X9TmUuIUlNTcfnyZVSpUgW+vr6oUKECdu7cqZSfP38e8fHx8Pf3BwD4+/vj5MmTSExMVOpERUVBo9HAx8fnmcdPREREpsfkb5l99NFH6Nq1Kzw9PXHz5k1MnDgRZmZm6Nu3LxwcHBASEoKwsDA4OTlBo9Hg/fffh7+/P5o1awYA6NixI3x8fDBgwADMnj0bOp0O48aNQ2hoKCwtLUu5d0RERGQKTD4hunHjBvr27Yt//vkHlStXRsuWLXHw4EFUrlwZADB//nyo1Wr07NkT6enpCAwMxNKlS5X2ZmZm2Lp1K9599134+/vD1tYWwcHBmDJlSml1iYiIiEyMySdE3377bb7lVlZWWLJkCZYsWWK0jqenJ3799dfiDo2IiIj+I8rcM0RERERExY0JEREREZV7TIiIiIio3GNCREREROUeEyIiIiIq95gQERERUbnHhIiIiIjKPSZEREREVO4xISIiIqJyjwkRERERlXtMiIiIiKjcY0JERERE5V6ZSohmzpwJlUqFESNGKMvu37+P0NBQODs7w87ODj179kRCQoJBu/j4eHTp0gU2NjZwcXHBqFGj8ODBg2ccPREREZmqMpMQHTlyBF988QUaNGhgsHzkyJHYsmULfvjhB+zduxc3b95Ejx49lPKsrCx06dIFGRkZOHDgANauXYs1a9ZgwoQJz7oLREREZKLKREKUmpqK/v3748svv0TFihWV5SkpKVi5ciXmzZuH9u3bw9fXF6tXr8aBAwdw8OBBAMD27dtx5swZfP3112jUqBGCgoIwdepULFmyBBkZGUa3mZ6eDr1ebzARERHRf1OZSIhCQ0PRpUsXBAQEGCyPjY1FZmamwfI6derAw8MDMTExAICYmBjUr18frq6uSp3AwEDo9XqcPn3a6DZnzJgBBwcHZXJ3dy/mXhEREZGpMPmE6Ntvv8WxY8cwY8aMXGU6nQ4WFhZwdHQ0WO7q6gqdTqfUeTQZyinPKTMmPDwcKSkpynT9+vUi9oSIiIhMlXlpB5Cf69ev44MPPkBUVBSsrKye6bYtLS1haWn5TLdJREREpcOkrxDFxsYiMTERL7zwAszNzWFubo69e/di4cKFMDc3h6urKzIyMpCcnGzQLiEhAVqtFgCg1WpzvXWWM59Th4iIiMo3k06IOnTogJMnTyIuLk6ZmjRpgv79+yv/X6FCBezcuVNpc/78ecTHx8Pf3x8A4O/vj5MnTyIxMVGpExUVBY1GAx8fn2feJyIiIjI9Jn3LzN7eHvXq1TNYZmtrC2dnZ2V5SEgIwsLC4OTkBI1Gg/fffx/+/v5o1qwZAKBjx47w8fHBgAEDMHv2bOh0OowbNw6hoaG8JUZEREQATDwhKoj58+dDrVajZ8+eSE9PR2BgIJYuXaqUm5mZYevWrXj33Xfh7+8PW1tbBAcHY8qUKaUYNREREZmSMpcQ7dmzx2DeysoKS5YswZIlS4y28fT0xK+//lrCkREREVFZZdLPEBERERE9C0yIiIiIqNxjQkRERETlHhMiIiIiKveYEBEREVG5x4SIiIiIyj0mRERERFTuMSEiIiKico8JEREREZV7TIiIiIio3GNCREREROWeySdEy5YtQ4MGDaDRaKDRaODv74/ffvtNKb9//z5CQ0Ph7OwMOzs79OzZEwkJCQbriI+PR5cuXWBjYwMXFxeMGjUKDx48eNZdISIiIhNl8glR1apVMXPmTMTGxuLo0aNo3749unXrhtOnTwMARo4ciS1btuCHH37A3r17cfPmTfTo0UNpn5WVhS5duiAjIwMHDhzA2rVrsWbNGkyYMKG0ukREREQmxuR/7b5r164G89OnT8eyZctw8OBBVK1aFStXrsSGDRvQvn17AMDq1avh7e2NgwcPolmzZti+fTvOnDmDHTt2wNXVFY0aNcLUqVMxZswYTJo0CRYWFqXRLSIiIjIhJn+F6FFZWVn49ttvkZaWBn9/f8TGxiIzMxMBAQFKnTp16sDDwwMxMTEAgJiYGNSvXx+urq5KncDAQOj1euUqU17S09Oh1+sNJiIiIvpvKhMJ0cmTJ2FnZwdLS0u88847+PHHH+Hj4wOdTgcLCws4Ojoa1Hd1dYVOpwMA6HQ6g2QopzynzJgZM2bAwcFBmdzd3Yu3U0RERGQyykRCVLt2bcTFxeHQoUN49913ERwcjDNnzpToNsPDw5GSkqJM169fL9HtERERUekx+WeIAMDCwgI1atQAAPj6+uLIkSP4/PPP8frrryMjIwPJyckGV4kSEhKg1WoBAFqtFocPHzZYX85baDl18mJpaQlLS8ti7gkRERGZojJxhehx2dnZSE9Ph6+vLypUqICdO3cqZefPn0d8fDz8/f0BAP7+/jh58iQSExOVOlFRUdBoNPDx8XnmsRMREZHpMfkrROHh4QgKCoKHhwfu3r2LDRs2YM+ePdi2bRscHBwQEhKCsLAwODk5QaPR4P3334e/vz+aNWsGAOjYsSN8fHwwYMAAzJ49GzqdDuPGjUNoaCivABERERGAMpAQJSYmYuDAgbh16xYcHBzQoEEDbNu2DS+99BIAYP78+VCr1ejZsyfS09MRGBiIpUuXKu3NzMywdetWvPvuu/D394etrS2Cg4MxZcqU0uoSERERmRiTT4hWrlyZb7mVlRWWLFmCJUuWGK3j6emJX3/9tbhDIyIiov+IMvkMEREREVFxYkJERERE5R4TIiIiIir3mBARERFRuceEiIiIiMo9JkRERERU7jEhIiIionKPCRERERGVe0yIiIiIqNxjQkRERETlHhMiIiIiKveYEBEREVG5Z/IJ0YwZM/Diiy/C3t4eLi4u6N69O86fP29Q5/79+wgNDYWzszPs7OzQs2dPJCQkGNSJj49Hly5dYGNjAxcXF4waNQoPHjx4ll0hIiIiE2XyCdHevXsRGhqKgwcPIioqCpmZmejYsSPS0tKUOiNHjsSWLVvwww8/YO/evbh58yZ69OihlGdlZaFLly7IyMjAgQMHsHbtWqxZswYTJkwojS4RERGRiTEv7QCeJDIy0mB+zZo1cHFxQWxsLFq3bo2UlBSsXLkSGzZsQPv27QEAq1evhre3Nw4ePIhmzZph+/btOHPmDHbs2AFXV1c0atQIU6dOxZgxYzBp0iRYWFjk2m56ejrS09OVeb1eX7IdJSIiolJj8leIHpeSkgIAcHJyAgDExsYiMzMTAQEBSp06derAw8MDMTExAICYmBjUr18frq6uSp3AwEDo9XqcPn06z+3MmDEDDg4OyuTu7l5SXSIiIqJSVqYSouzsbIwYMQItWrRAvXr1AAA6nQ4WFhZwdHQ0qOvq6gqdTqfUeTQZyinPKctLeHg4UlJSlOn69evF3BsiIiIyFSZ/y+xRoaGhOHXqFH7//fcS35alpSUsLS1LfDtERERU+srMFaJhw4Zh69at2L17N6pWraos12q1yMjIQHJyskH9hIQEaLVapc7jb53lzOfUISIiovLL5BMiEcGwYcPw448/YteuXfDy8jIo9/X1RYUKFbBz505l2fnz5xEfHw9/f38AgL+/P06ePInExESlTlRUFDQaDXx8fJ5NR4iIiMhkmfwts9DQUGzYsAE//fQT7O3tlWd+HBwcYG1tDQcHB4SEhCAsLAxOTk7QaDR4//334e/vj2bNmgEAOnbsCB8fHwwYMACzZ8+GTqfDuHHjEBoayttiREREZPoJ0bJlywAAbdu2NVi+evVqDBo0CAAwf/58qNVq9OzZE+np6QgMDMTSpUuVumZmZti6dSveffdd+Pv7w9bWFsHBwZgyZcqz6gYRERGZMJNPiETkiXWsrKywZMkSLFmyxGgdT09P/Prrr8UZGhEREf1HmPwzREREREQljQkRERERlXtMiIiIiKjcY0JERERE5R4TIiIiIir3mBARERFRuceEiIiIiMo9JkRERERU7jEhIiIionKPCRERERGVe0yIiIiIqNwz+YQoOjoaXbt2hZubG1QqFTZv3mxQLiKYMGECqlSpAmtrawQEBODixYsGdZKSktC/f39oNBo4OjoiJCQEqampz7AXREREZMpMPiFKS0tDw4YNjf5w6+zZs7Fw4UJERETg0KFDsLW1RWBgIO7fv6/U6d+/P06fPo2oqChs3boV0dHRGDp06LPqAhEREZk4k/+1+6CgIAQFBeVZJiJYsGABxo0bh27dugEAvvrqK7i6umLz5s3o06cPzp49i8jISBw5cgRNmjQBACxatAidO3fG3Llz4ebm9sz6QkRERKbJ5BOi/Fy5cgU6nQ4BAQHKMgcHB/j5+SEmJgZ9+vRBTEwMHB0dlWQIAAICAqBWq3Ho0CG8+uqrea47PT0d6enpyrxery+5jhRRZkYGrl279tTtNRoNKleuXIwRERERlS1lOiHS6XQAAFdXV4Plrq6uSplOp4OLi4tBubm5OZycnJQ6eZkxYwYmT55czBEXv/TUFFy98idGfDwJlpaWT7UOJ3sbfL16BZMiIiIqt8p0QlSSwsPDERYWpszr9Xq4u7uXYkR5y0z/F9kqc1Rq1gPObp6Fbp+WlIDbMRuh1+uZEBERUblVphMirVYLAEhISECVKlWU5QkJCWjUqJFSJzEx0aDdgwcPkJSUpLTPi6Wl5VNfcSkNNhUrQ+NS9ana3i7mWIiIiMoak3/LLD9eXl7QarXYuXOnskyv1+PQoUPw9/cHAPj7+yM5ORmxsbFKnV27diE7Oxt+fn7PPGYiIiIyPSZ/hSg1NRWXLl1S5q9cuYK4uDg4OTnBw8MDI0aMwLRp01CzZk14eXlh/PjxcHNzQ/fu3QEA3t7e6NSpE4YMGYKIiAhkZmZi2LBh6NOnD98wIyIiIgBlICE6evQo2rVrp8znPNcTHByMNWvWYPTo0UhLS8PQoUORnJyMli1bIjIyElZWVkqb9evXY9iwYejQoQPUajV69uyJhQsXPvO+EBERkWky+YSobdu2EBGj5SqVClOmTMGUKVOM1nFycsKGDRtKIjwiIiL6DyjTzxARERERFQcmRERERFTuMSEiIiKico8JEREREZV7TIiIiIio3GNCREREROUeEyIiIiIq90x+HCIqeZkZGbh27dpTt9doNPxhWCIiKtOYEJVz6akpuHrlT4z4eNJT/5itk70Nvl69gkkRERGVWUyIyrnM9H+RrTJHpWY94OzmWej2aUkJuB2zEXq9ngkRERGVWUyICABgU7EyNC5Vn6rt7WKOhYiI6FkrVwnRkiVLMGfOHOh0OjRs2BCLFi1C06ZNSzusMo/PIBERUVlXbhKi7777DmFhYYiIiICfnx8WLFiAwMBAnD9/Hi4uLqUdXplVHM8g2VmYYdb0KXB2dn7qOJhUERFRUZSbhGjevHkYMmQI3nzzTQBAREQEfvnlF6xatQpjx44t5ejKrqI+g5R04xJiv1+IwcM/euqECih6UlXUhOr27dvQ6/VP3Z4JHRFR6SoXCVFGRgZiY2MRHh6uLFOr1QgICEBMTEyebdLT05Genq7Mp6SkAECRTnp5uXv3LrIePEDyravIvH+v0O31iTcg2dnQ667DXFX47RdX+wfp958q/vt3k5Elalg83xQOzk93pS4l8SaO7f4Bb7434umvUlmaY9K4cDg5ORW6bVJSEiZNn4HU+w+eattF3T4R0X+Bo6NjiXwH5py3RST/ilIO/PXXXwJADhw4YLB81KhR0rRp0zzbTJw4UQBw4sSJEydOnP4D0/Xr1/PNFcrFFaKnER4ejrCwMGU+OzsbSUlJcHZ2hkr1FJdSjNDr9XB3d8f169eh0WjY/imUdgxsX7bbm0IMbF++25tCDGW9fX5EBHfv3oWbm1u+9cpFQlSpUiWYmZkhISHBYHlCQgK0Wm2ebSwtLXPdfnF0dCypEKHRaIq0E5T39qYQA9uX7famEAPbl+/2phBDWW9vjIODwxPrlIvfMrOwsICvry927typLMvOzsbOnTvh7+9fipERERGRKSgXV4gAICwsDMHBwWjSpAmaNm2KBQsWIC0tTXnrjIiIiMqvcpMQvf7667h9+zYmTJgAnU6HRo0aITIyEq6urqUal6WlJSZOnPjUb0eV9/amEAPbl+32phAD25fv9qYQQ1lvXxxUIk96D42IiIjov61cPENERERElB8mRERERFTuMSEiIiKico8JEREREZV7TIiIiIio3Cs3r92bir///hurVq1CTEwMdDodAECr1aJ58+YYNGgQf/GciIioFPC1+2foyJEjCAwMhI2NDQICApQxkBISErBz507cu3cP27ZtQ5MmTUo50pKzdetWHD58GIGBgWjRogV27dqFuXPnIjs7Gz169MDQoUMLtT4RwZ49e3Dp0iVUqVIFgYGBqFChQglFTyVl8uTJCA0NRaVKlYq0ngcPHuDmzZvw8PDIt15WVhauXbuGatWqQa1WIz09HT/99BOys7PRrl27pxqfLDMz85nue3/++Sd+//133Lp1C2q1Gs8//zxeeumlEvnZAype/4X9DwDS0tIQGxtrsA++8MILhf69zwcPHmD37t2Ij4+Hp6cn2rVrBzMzsxKKOh/F8GPyVEB+fn4ydOhQyc7OzlWWnZ0tQ4cOlWbNmuW7jrlz58rVq1eLNa527doVyzqTkpJk7dq1RssjIiLE3NxcfH19RaPRyLp168Te3l4GDx4sb7/9tlhbW8uCBQvy3UZQUJAkJyeLiMg///wjfn5+olKppHLlyqJWq6VOnTqSmJhY5L48yc6dO2Xy5MnyzjvvyHvvvSdz586VCxcuFHo9d+7ckeXLl8u4cePkyy+/VPpWEA8ePDCYP3jwoOzdu1cyMjIK1P7WrVuyefNmiYiIkIiICNm8ebPcunXrie3+97//SVpaWoHjfFRKSkquKTk5WSpUqCCHDh1Slj2tuLg4UavV+dY5fvy4VKlSRdRqtdSrV0/i4+OlXr16YmtrK3Z2dlKxYkU5fPiw0fbfffedpKenK/OLFi0SDw8PUavV4uzsLJMnT35inEuWLJEOHTrIa6+9Jjt27DAou337tnh5eRltm5qaKr169RKVSiUqlUrUarVotVoxMzMTOzs7Wbx48RO3/6jMzEzZvn27rFixQqKionLtVwWl0+nk2rVrhdpuXFycREZGSmRkpMTFxRVo3719+/ZTxfckkyZNKrZ1p6amyt69e/MsK+v7n4hIVlaWjBo1SmxsbEStVotarVb2R09PT/n555/zbT9s2DDZsmWLiIhcv35d6tSpI2ZmZuLq6ipmZmZSv359uXHjxhP7UdyYED1DVlZWcvbsWaPlZ8+eFSsrq3zXoVKpxMzMTAICAuTbb781ODCe5KeffspzMjMzk8WLFyvzT+tJJyMfHx9Zvny5iIjs2rVLrKysZMmSJUr56tWrxdvbO99tqFQqSUhIEBGRd999V3x8fOTPP/8UkYcHlq+vr7zzzjtG22dkZMioUaOkevXq8uKLL8rKlSsNynU6Xb59SEhIkKZNm4parRZzc3NRq9Xi6+urnJBGjRqVb/yvvvqq/PDDDyIicurUKalUqZJUrlxZ/Pz8xNXVVbRarZw5cybfddy8eVNatGghZmZm0rp1a0lKSpIuXbooX0i1atWSmzdvGm2fmpoq/fv3FzMzMzE3NxcXFxdxcXERc3NzMTMzkzfeeCPfhEelUolGo5EhQ4bIwYMH8431cTlfno9POSf2nP8+rYIkRIGBgdKrVy85efKkfPDBB+Lt7S2vvfaaZGRkSGZmprzxxhsSEBCQbx9y9sFVq1aJlZWVTJgwQX755ReZNm2a2Nraypdffmm0/eeffy42NjYSGhoqb7zxhlhYWMinn36qlD9pHxw6dKi0aNFCTp48KRcvXpRevXrJ6NGjJS0tTVauXCk2Njayfv16o+2LejLS6/XSv39/8fDwkIEDB0p6erq89957yr9d69at801qs7Ky5JNPPhFHR0dln82ZHB0dZdy4cZKVlWW0vVqtlvbt28v69evl/v37RusZU9JJuUj++2FZ3/9ERMaMGSPe3t6yZcsWiYqKktatW8usWbPk7NmzMn78eLG0tJRt27YZbe/q6ionT54UEZHevXtLQECAkoz+888/8vLLL0uvXr3yjaEkMCF6hqpVq5bvFZS1a9eKp6dnvutQqVSyevVq6datm1SoUEGcnZ3lgw8+UHauJ7V9NJPPa8rvQMjri+TRad++ffm2t7a2NvgLskKFCgZxX7lyRWxsbJ7Yh5wvg9q1a+dK4Hbs2JHvXzcTJ04UV1dXmTNnjnzyySfi4OAgQ4cOVcp1Op2oVCqj7V9//XXp3r27pKSkyP3792XYsGEycOBAEXl41cjZ2Tnfq1wVK1ZUkuKgoCDp16+fktRmZGRISEiIdOzYMd/PYMCAAdK8eXP5+eef5fXXX5fmzZtLq1at5MaNG3Lt2jVp0aKFhIaGGm0fEhIiNWvWlMjISIOrAQ8ePJBt27ZJrVq1ZPDgwUbbq1QqmTJlijRu3FhUKpXUrVtX5s+fL3///Xe+cYuIPPfcc9KlSxfZtWuX7NmzR/bs2SO7d+8WMzMzWb16tbLMmMaNG+c71alT54lf5hUrVlSSznv37omZmZkcOnRIKT916pQ4Ozvn2/+cfbBp06Yye/Zsg/KlS5dK48aNjbb38fExSFj2798vlStXlvHjx4vIk09IlSpVkqNHjyrzSUlJYmVlpSSxixcvlkaNGhltX9ST0bBhw6ROnTqycOFCadu2rXTr1k3q1asnv//+u+zdu1d8fHzk448/Ntp+1KhRUrlyZYmIiJArV67IvXv35N69e3LlyhX54osvxMXFRUaPHm20vUqlkk6dOomFhYVUrFhRhg0bJn/88YfR+o8r6aRcJP+EqKzvfyIiVapUkejoaGX+xo0bYmdnpySoU6ZMEX9/f6PtrayslD9kq1atatB/EZGTJ09KpUqV8o2hJDAheoYWL14slpaWMnz4cPnpp5/k4MGDcvDgQfnpp59k+PDhYm1tbXDFJC+PHgwJCQkya9Ys5STw4osvyvLly0Wv1+fZtlOnTtKlSxelfQ5zc3M5ffr0E+PP+aJ40heKMVWrVlUOor/++ktUKpX88ssvSvmePXukatWqT4wh55aYi4uLnDp1yqD86tWrYmlpabR9jRo1lL+ORUQuXrwoNWrUkEGDBkl2dvYTvww0Go3BNlNTU6VChQrKX5Tr1q2T2rVrG21vbW0tly5dEpGHXyrHjh0zKD9//rw4ODgYbZ/TLiYmRkQensBUKpXBZe+dO3fK888/b7S9o6Oj7N+/32j577//Lo6OjkbLH90Hjx49Ku+++644OjqKpaWlvPbaa7J9+3ajbf/55x/p3r27tGvXzuAqREH3QUtLSwkODpZJkyblOb399ttP/DJ3dHRUbm9mZGSImZmZxMbGKuVnz56VihUr5tv/nH2wUqVKEhcXZ1B+6dIlsbe3N9re2tparly5YrDs5MmT4urqKmPHjn3iPvho/Dl9MDc3V2K6cOFCvleai3oycnd3l127donI/x3Hjx5TW7duzfcYcHV1lcjISKPlkZGR4uLiYrQ8Z/+7ffu2zJ07V3x8fEStVssLL7wgS5cufeLVnaIm5SIPk5r8Jo1GY/TfsKzvfyIi9vb2cvnyZWU+KytLzM3NlVvup0+fzveP2wYNGsi3334rIiLe3t4SFRVlUH7gwAFxcnLKN4aSwIToGfv222/Fz89PzM3Nlasy5ubm4ufnJ999990T2z96MnpUdHS0BAcHi62trdja2hptP2/ePHF3dzf4AivoyUij0cisWbOUL4zHpy+//DLfAyk0NFRq1qwp06ZNk6ZNm0pwcLDUqVNHfvvtN4mMjJT69evLW2+99cT+d+7cWV599VWpWLGiQT9EHj5H4+rqarR9Xl8GN27ckFq1akn//v3lr7/+yrcPlStXNvis7t27J2q1Wv755x8REbl8+XK+CZmfn59y27Bx48by448/GpRv375dtFqt0fYiD09o8fHxyrytra1cvHhRmb927ZpYW1sbba/RaOTIkSNGyw8fPiwajcZoeV774L///itfffWVtG3bVtRqtVSrVi3fPixdulTc3Nxkw4YNIlLwfdDX11eWLl1qtPyPP/544pd5hw4dJCQkRG7cuCGTJ0+WGjVqyJtvvqmUv/fee9KqVSuj7VUqlXz11Vfy008/SdWqVeXAgQMG5adOncr383N3dzf46zrH6dOnxdXVVQYOHJhvH1566SWDK4Bz5syRKlWqKPPHjh3LN6Ep6snI0tLSYP+zsbGR8+fPK/NXr17N92RoY2MjJ06cMFp+/PjxfL/D8tr/Dhw4IG+99ZbY29uLjY2NDBgwwGj7oiblOX348MMPZc2aNXlOkydPNvpvWNb3PxGR5s2by7Rp05T5b775xuCPqJMnT+ab1K1evVqqVq0qu3fvlq+++kq8vb1lx44d8tdff8muXbukfv36+V6lLilMiEpJRkaG3Lx5U27evFngh2BFDO8f5yUlJUU54Rrzxx9/iI+PjwwdOlTS0tIK/EXQtm1bmTVrltHyuLi4fG83paamypAhQ6RevXoydOhQSU9Plzlz5oiFhYWoVCpp27Ztvn0TERk0aJDB9HgSOWrUKAkMDDTa3svLK9dDhCIP/9KtVauWvPTSS/l+Gbz66qvSs2dPSU1NlYyMDBkxYoTUqFFDKT948GC+Cc3WrVvFyclJVq9eLatXr5Zq1arJihUrZP/+/bJq1Spxd3d/4nNIHh4eBn/VjxkzRknIRB7+O+R3QuzXr580btw419UpkYcnU19fX+nfv7/R9k/aBy9evJjvLZMcp0+floYNG0rfvn0LvA8OHz5cPvjgA6Plly5dkrZt2+a7jsOHD4uzs7Oo1WqpXLmynDp1Svz8/ESr1Yqbm5tYW1vnuY/kePw286MnBhGRFStW5HvLom/fvjJixIg8y06dOqW8IGBMbGysODk5iVarFQ8PD7GwsJBvvvlGKV+8eLFyGzcvRT0Zubm5GVzR6Nu3r8H+cOrUqXxPhp07d5aOHTvm+QDz7du3lSvZxuS3/6WmpsqKFSukefPmRtvneNqkXORhQpDfrfH8bpmV9f1P5OGjCZaWltK0aVNp3bq1mJuby/z585XyOXPmSPv27fNdx2effSY2NjZibW0tFhYWBncbunfvLnfv3s23fUlgQlTGGLtCVFj37t2Tt99+W2rWrClmZmYF+iJYvny5fP7550bLdTqdTJo0qdCx/Pvvv0Zv8xVWamqq/Pvvv0bLQ0JCjF6FunHjhtSoUSPfL4PLly9L9erVxdzcXCpUqCCOjo4Gf2GvXr1axo4dm2+M//vf/6Rq1aq5nueysrKSESNGPPEtn1deeSXfL+PFixfn+2WUlJQknTp1EpVKJU5OTlKnTh2pU6eOODk5iVqtlqCgILlz547R9sW1D4qIpKeny8iRI6VRo0bKbZxnITU1VY4ePap86f7777+yYsUKWbRokZw7d65I696yZUu+t4SOHz8uq1atMlp+8uTJJx5HN2/elOXLl8uiRYsKfBJ/VFFORp06dZKIiAij5atXr843Icl5q8rc3FwaN24snTp1kk6dOknjxo3F3NxcGjRoYHAF6nHFuf89TVIuIjJ9+vR8/43i4+Nl0KBBRsvL+v4n8jDp+/jjj+XDDz/M9zZ5fu7cuSPff/+9zJw5Uz799FNZvXr1U72tW1w4DlE59/PPP2P37t0IDw+Hi4tLaYdT4q5du4Zz584hMDAwz/KbN28iKioKwcHBRtdx79497N+/H+np6WjWrNlTjZ2TlZWFY8eO4c8//0R2djaqVKkCX19f2NvbF3pdjzt8+DBsbGxQr169fOudO3cu1wCh/v7+qFOnTr7trl27Bnd3d6jVHOi+LEtOTsb27dtx5coVZR9s0aIFatasmW+7pKQkqNVqODo65ln+22+/wdraGm3btjW6juzsbGzbtg0HDx7Mtf917Ngx331r7dq16NOnDywtLZ/Yx4LIyMjA2LFjsXv3bmzatAleXl7Fsl4qe5gQ/cdcv34dEydOxKpVq/IsP3v2LA4ePKic+M6dO4cFCxYgIyMDb7zxBtq3b1/gbaWlpeH7779XBkXs27cvnJ2djdY/duwYKlasqHzhrFu3DhEREcpgXMOGDUOfPn2euN3Fixfj8OHD6Ny5M/r06YN169ZhxowZyuCOU6ZMgbk5B2E3ZYcPH85ztPYXX3yxQO2zs7PzPGlmZ2fjxo0bTxyYUURw9epVuLu7w9zcHBkZGfjxxx+Rnp6Ozp07FzrJvXLlinIcPCkR3bhxI4KCgmBjY1OobTzq+PHjiI2NRbt27eDl5YXTp09jyZIlyM7Oxquvvmo04SfTUVLHgIjg+vXrTzwGHte+fXusXr0anp6ehWqX41kfAyWi1K5NUYnI7971b7/9JhYWFuLk5CRWVlby22+/SeXKlSUgIEDat28vZmZmsnPnTqPr9vb2Vp5ViY+Pl2rVqomDg4O8+OKL4uTkJC4uLvne9mjQoIFye+nLL78Ua2trGT58uCxbtkxGjBghdnZ2ucYFetzUqVPF3t5eevbsKVqtVmbOnCnOzs4ybdo0+fTTT6Vy5coyYcKEfNeRnp4u3333nYwYMUL69Okjffr0kREjRsj3339fqHGd8qLT6Z44MNrff/8tu3btUj7L27dvy8yZM2Xy5MlPHIMoL9nZ2bJr1y5Zvny5bNmy5YnPpBXH4J5btmyR8ePHy++//y4iD99sCwoKksDAQPniiy+MtktISJCWLVsqA7g1bdpUmjZtKp6enqJSqaRly5ZPfEbutddeEysrK3FxcZHx48cb3GIsyBsy586dE09PT1Gr1VKjRg35888/xdfXV2xtbcXGxkYqVaqU72X7d999V7nVce/ePenZs6fBW5bt2rXL95ZTUcZxEhHZuHGjmJmZibOzs9jZ2UlUVJQ4OjpKQECABAYGipmZWb7jEOU4dOiQLFiwQMaOHStjx46VBQsW5HrjLD/GxgrKzs4u1ACNOYoyQOyff/4p27dvL9DwI0UZWPRxTzNAa2kfA8UxHl1pHwMlhQlRGWNsZ86Z5s+fb/Rg8Pf3l08++UREHr4VULFiRYOHX8eOHSsvvfSS0W0/eu++f//+0rx5c2Vk5bt370pAQID07dvXaHtra2vlC69x48a5Hv5ev369+Pj45Nv/6tWry8aNG0XkYfJnZmYmX3/9tVK+adMmg4ecH3fx4kV5/vnnxcrKStq0aSO9e/eW3r17S5s2bcTKykpq1Khh8MZWYT1pYMBDhw6Jg4ODqFQqqVixohw9elS8vLykZs2aUr16dbG2tjZ4YDUvRR2tuyiDe4oUbcTxnj17ir+/f57PSZw7d06aN2+e7xg4w4cPl1q1askPP/wgX375pXh6ekqXLl2UPjxpHCkRkW7duskrr7wiJ06ckBEjRoi3t7d069ZNMjIy5P79+9K1a1d54403jLZ/9KHe8PBwqVq1quzatUvS0tLk999/l+rVq+f7HFlRxnESEXnhhReUB2lz3u6ZMmWKUj537tx8xyEq6ydkUzgZF2WA1tI+Boo6Hp1I6R8DJYUJURlTlJ1Zo9EoJ/uccSMefdMoZyyK/LadcxA8//zzuR6k279/v7i7uxtt7+zsrAwo5+Likuf4Gfm9Li6S9+COj44L9KRXfgMCAqRbt255jlWSkpIi3bp1y3dgxOPHj+c7fffdd/l+mQQEBMjgwYNFr9fLnDlzpGrVqgZv9Lz55pvSvXt3o+1Fij5ad1EG9xQp2ojjdnZ2eb7dluPo0aNiZ2dntNzDw0N2796tzN++fVuaNm0qHTt2lPv37xfoClHlypWVgfxSU1NFpVLJvn37lPL9+/eLh4eH0faPfv716tVT3lLK8dNPP0mtWrUK1L6w4ziJPBxmIWfoiOzsbKlQoYLBa+yXL1/O9zMs6ydkUzgZF2WA1tI+Boo6Hp1I6R8DJYUJURnj5uYmmzdvNlqe3zgsGo1GGRRQ5OGB+ejgWlevXs13QLdHBwRzc3PLdQJ9Uvs33nhDQkJCRETktddek3HjxhmUf/rpp1K/fn2j7UUevjb/22+/icjDAejUarV8//33Svkvv/yS7xg41tbW+Z74T5w4kW9Slt+XeUEGp3x0lNqMjAxRq9UGtyliY2PlueeeM9o+J4aijNZdlME9RYo24rizs3O+g97t3r0731F6ra2tc92W1ev14u/vL+3bt5c///zziQnR4/Hb2dkZHBfx8fH5jiX1+MB4eQ0O+qR9qCjjOGm1WuUPi6SkJFGpVAYnyMOHD+c79ENZPyGbwsm4KAO0msIxUJTx6ERK/xgoKUyIypiuXbsqQ6znJb+xgBo0aKAkEyIPrwhlZmYq89HR0U88kdavX18aN24sdnZ28r///c+gfO/evfmezP/66y+pVq2atG7dWsLCwsTa2lpatmwpQ4YMkdatW4uFhYXByNV5GTdunFSuXFkGDx4sXl5eMnbsWPHw8JBly5ZJRESEuLu7y8iRI422r1KlSq7BHB/1888/Gwxy9zhnZ2dZuXKlXL16Nc/pl19+yffL6NG/7kVyJ6XXrl0r0O/ZFWW07qIO7lmUEcffe+898fT0lE2bNhlcpUtJSZFNmzZJtWrVZNiwYUa3Xbt27Tz3kbt374q/v780bNjwiSeD6tWrG1wRWrp0qUECGBsbm29CoVKp5O2335aRI0eKi4tLrhNobGxsvuNAFXUcpzfeeEP8/Pzk66+/lq5du0pgYKA0a9ZMzp49K+fOnZM2bdrke4WnrJ+QTeFkXJQBWk3hGBB5+vHoREr/GCgpTIjKmOjoaIOk5nGpqalGv+yWLVsmW7duNdo2PDxcuYKTl8d/JuHxsS4++ugj6dOnT77x37lzR8aMGSM+Pj5iZWUlFhYW4unpKf369ct39OQcWVlZMn36dHn55Zfl008/lezsbPnmm2/E3d1dnJ2dZdCgQZKammq0/fjx46VixYoyb948OX78uOh0OtHpdHL8+HGZN2+eODk5ycSJE42279ixo0ydOtVo+ZMGp6xTp47Bg+tbt26Ve/fuKfMHDx4s0M+XFGW07qIO7lmUEcfv378v77zzjjL2jZWVlVhZWYlarRYLCwt599138/3Bzvfff9/oyV6v14ufn98TTwZvv/12vj9+OWPGDOncubPR8jZt2kjbtm2V6fF1TZ06Vdq0aWO0fVHH0dHpdPLSSy+JnZ2dBAYGSnJysgwbNky5OlmzZk2DK16PK+snZFM4GRdlgFZjx4BKpXpmx0COpxmPTqT0j4GSwoSIyp2ZM2dKlSpVDH6bTaVSSZUqVfIdiVvk4UPb69atM1qelJQka9asMVo+adIkg1GFH/fxxx9Ljx498o2hqKN1F/XLqDhGHE9JSZFdu3bJhg0bZMOGDbJr164C/cJ4UlJSrisCj9Lr9U/8Haon+fPPP+XmzZtP3f7y5cty/fp1o+VXr16V7Ozsp15/ftt9/KpvXkwhKc3xNCdkUzgZF8cArSkpKbJz507lGNi5c2eRjoGcfeppjoGc39Ms6ueSE0NBjoG83lIsieOiMDgOEZVbV65cMRgDxBQGZLt37x7MzMyKNOhcWloazMzMYGVlVYyRPdn9+/eRmZlZLINLUsnT6/WIjY01OAZ8fX2h0WjybXfnzh3cvHkTdevWzbP87t27OHbsGNq0aVPgWIpzgNg///wTFhYWqFq1ap7l165dg4eHB1QqVZG2UxwDtD7KwsICx48fh7e3d5lsbyoxFAVHr6Nyy8vLK1cS9KSBLZ+kqO3/+eefIrUHHo4kXBp9sLKygpWV1RPb//vvv4iNjYWTkxN8fHwMyu7fv4/vv/8eAwcONLqdorY3hRhKu/2jA7S2a9cO586dw+eff45169Y9cYDWihUrQqfTYfXq1QYDvH7++edIT08v0ACvjw8QW6tWLfz6668YO3Zsodo3b94ctWvXLtT2PT098xygtjDxAw8Tqxs3bsDf3x+VKlUq8DrCwsLyXJ6VlYWZM2cqg9vOmzfPJNubSgwlolSvTxGZmCeNI2Tq7U0hhvzanz9/XhnvRq1WS+vWreWvv/5Syp/0hlJe7R+9vVWQ1+6Luo6y3r6oA7SW9/ZFXYdKpZJGjRoZ3PZr27atqFQqefHFF6Vt27bSrl07o9su7famEkNJ4C0zKld+/vnnfMv//PNPfPjhh8jKyjLJ9qYQQ1Hav/rqq8jMzMSaNWuQnJyMESNG4MyZM9izZw88PDyQkJAANzc3o9suantTiKG02zdv3hzt27fHtGnT8O233+K9997Du+++i+nTpwMAwsPDERsbi+3bt7O9EUVZx8yZM7F8+XKsWLHC4CpShQoVcPz48VxX/EytvanEUCKeeQpGVIqKOihcabc3hRiK0t7FxcVgEMHs7Gx55513xMPDQy5fvvzEqxtFbW8KMZR2+6IO0Fre2xfHOg4fPiy1atWSDz/8UPmpncK89l7a7U0lhuLGn6umcqVKlSrYtGkTsrOz85yOHTtm0u1NIYaitP/3338NfnhXpVJh2bJl6Nq1K9q0aYMLFy7ku+2itjeFGEq7fU4bAFCr1bCysoKDg4NSZm9vj5SUFLZ/gqKs48UXX0RsbCxu376NJk2a4NSpU4V6yLu025tKDMWNCRGVK76+voiNjTVarlKpIPncRS7t9qYQQ1Ha16lTB0ePHs21fPHixejWrRteeeUVo+stjvamEENpt69WrRouXryozMfExBj8Mnp8fDyqVKnC9vkojnXY2dlh7dq1CA8PR0BAQL63eU2xvanEUKxK7doUUSkoysCWptDeFGIoSvtPP/1UgoKCjLZ999138x3YsqjtTSGG0m5f1AFay3v74lrHo65fvy6bN2/Od1BZU25vKjEUFR+qJiIionKPt8yIiIio3GNCREREROUeEyIiIiIq95gQERERUbnHhIioHLl69SpUKhXi4uJKOxTFuXPn0KxZM1hZWaFRo0Z51mnbti1GjBjxTOMqCffu3UPPnj2h0WigUqmQnJxcqvGoVCps3ry5RLcxadIko/+uRKaECRHRMzRo0CCoVCrMnDnTYPnmzZtLfVCy0jJx4kTY2tri/Pnz2LlzZ6nEsGbNGjg6Opb4dtauXYt9+/bhwIEDuHXrlsFgfqXh1q1bCAoKKtUYiEwFEyKiZ8zKygqzZs3CnTt3SjuUYpORkfHUbS9fvoyWLVvC09NT+ZXr/6rLly/D29sb9erVg1arLfUkWKvVwtLS8qnaFuXfnMgUMSEiesYCAgKg1WoxY8YMo3Xyus2wYMECVKtWTZkfNGgQunfvjk8//RSurq5wdHTElClT8ODBA4waNQpOTk6oWrUqVq9enWv9586dQ/PmzWFlZYV69eph7969BuWnTp1CUFAQ7Ozs4OrqigEDBuDvv/9Wytu2bYthw4ZhxIgRqFSpEgIDA/PsR3Z2NqZMmYKqVavC0tISjRo1QmRkpFKuUqkQGxuLKVOmQKVSYdKkSUY/k+zsbIwePRpOTk7QarW56sbHx6Nbt26ws7ODRqNB7969kZCQoJQfP34c7dq1g729PTQaDXx9fXH06FHs2bMHb775JlJSUqBSqQziWLp0KWrWrAkrKyu4urqiV69eRuMDgI0bN6Ju3bqwtLREtWrV8Nlnnxl8Zp999hmio6OhUqnQtm3bPNdx+fJldOvWDa6urrCzs8OLL76IHTt25LvdnP1l1apV8PDwgJ2dHd577z1kZWVh9uzZ0Gq1cHFxUX58NMfjt8xu3LiBvn37wsnJCba2tmjSpAkOHTpksI0VK1bAy8sLVlZWBfrcc3zxxRdwd3eHjY0NevfuneunLVasWAFvb29YWVmhTp06WLp0ab59Jip2pTYkJFE5FBwcLN26dZNNmzaJlZWVXL9+XUREfvzxR3n0cJw4caI0bNjQoO38+fPF09PTYF329vYSGhoq586dk5UrVwoACQwMlOnTp8uFCxdk6tSpUqFCBWU7V65cEQBStWpV+d///idnzpyRwYMHi729vfz9998iInLnzh2pXLmyhIeHy9mzZ+XYsWPy0ksvSbt27ZRtt2nTRuzs7GTUqFFy7tw5OXfuXJ79nTdvnmg0Gvnmm2/k3LlzMnr0aKlQoYJcuHBBRERu3boldevWlQ8//FBu3bold+/ezXM9bdq0EY1GI5MmTZILFy7I2rVrRaVSyfbt20Xk4Q9sNmrUSFq2bClHjx6VgwcPiq+vr7Rp00ZZR926deWNN96Qs2fPyoULF+T777+XuLg4SU9PlwULFohGo5Fbt24pcRw5ckTMzMxkw4YNcvXqVTl27Jh8/vnnRv9tjx49Kmq1WqZMmSLnz5+X1atXi7W1taxevVpERP755x8ZMmSI+Pv7y61bt+Sff/7Jcz1xcXESEREhJ0+elAsXLsi4cePEyspKrl27ZnTbEydOFDs7O+nVq5ecPn1afv75Z7GwsJDAwEB5//335dy5c7Jq1SoBIAcPHlTaAZAff/xRRETu3r0rzz//vLRq1Ur27dsnFy9elO+++04OHDigbMPW1lY6deokx44dk+PHjxfoc89p1759e/njjz9k7969UqNGDenXr59S5+uvv5YqVarIxo0b5c8//5SNGzeKk5OTrFmzxmifiYobEyKiZygnIRIRadasmbz11lsi8vQJkaenp2RlZSnLateuLa1atVLmHzx4ILa2tvLNN9+IyP8lRDNnzlTqZGZmStWqVWXWrFkiIjJ16lTp2LGjwbavX78uAOT8+fMi8jBBady48RP76+bmJtOnTzdY9uKLL8p7772nzDds2FAmTpyY73ratGkjLVu2zLWeMWPGiIjI9u3bxczMTOLj45Xy06dPCwA5fPiwiIjY29sbPcGuXr1aHBwcDJZt3LhRNBqN6PX6fGPL0a9fP3nppZcMlo0aNUp8fHyU+Q8++MAgWSiounXryqJFi4yWT5w4UWxsbAxiDQwMlGrVquXaP2bMmKHMP5oQffHFF2Jvb280UZs4caJUqFBBEhMTlWUF+dwnTpwoZmZmcuPGDaXOb7/9Jmq1Wm7duiUiItWrV5cNGzYYbG/q1Kni7+9vtM9ExY23zIhKyaxZs7B27VqcPXv2qddRt25dqNX/dxi7urqifv36yryZmRmcnZ2RmJho0M7f31/5f3NzczRp0kSJ4/jx49i9ezfs7OyUqU6dOgAe3s7J4evrm29ser0eN2/eRIsWLQyWt2jR4qn63KBBA4P5KlWqKP06e/Ys3N3d4e7urpT7+PjA0dFR2VZYWBgGDx6MgIAAzJw506AveXnppZfg6emJ559/HgMGDMD69etx7949o/XPnj2bZ18vXrxYqB+tTE1NxUcffQRvb284OjrCzs4OZ8+eRXx8fL7tqlWrBnt7e2Xe1dUVPj4+ufaPx/eFHP+vvfsLaaqP4zj+1kqKKDRaLYOy0Mms42h0kxczQpQMobwwLDD7cxEY9keDupG0qLULL0aLoMDqxgxyZEElKIGNREmOlZHGRBMiqKyLVRfVnueiR2mPlvNpPV7s84JdnN/Odn7f3w6cD7/9zmaaJuvWrWPRokU/PcbKlSuxWCzj29GMO8CKFStYvnz5+PaGDRsIh8P09/fz8eNHgsEge/fujTjnTp06NeVnJBJLCkQiM8TlclFQUMDx48cnPJeYmDjhH+O/fPkyYb85c+ZEbCckJEzaFg6Ho+5XKBSiqKgI0zQjHi9evMDlco3vN3/+/KjfMxZ+t64TJ07Q19fHli1baG9vJysrC7/f/9P9FyxYQE9PD42NjSxbtoyamhocDscfv1W+uroav9/P6dOn6ejowDRNDMOYchHz754L8+bNm7Jvf+IzD4VCAFy8eDHifHv69CmdnZ0xP57IzygQicwgt9vNrVu3ePjwYUS7xWLh9evXEaEolr8d9OOF5uvXrzx69Ai73Q6A0+mkr6+PtLQ00tPTIx7TuSAuXLiQ1NRUAoFARHsgECArKys2hfzDbrczMjLCyMjIeNuzZ8/48OFDxLFsNhuHDx+mtbWV4uLi8QXnSUlJk87izJ49m7y8PDweD48fP2ZoaIj29vaf9mGyWm02G7NmzYq6lkAgQHl5Odu2bcMwDKxWK0NDQ1G//r/Kzs7GNE1GR0ejfk204/7y5UtevXo1vt3Z2UliYiKZmZksXbqU1NRUBgcHJ5xvq1atik1xIlFQIBKZQYZhsHPnTrxeb0T7xo0befPmDR6Ph2AwiM/n486dOzE7rs/nw+/38/z5cyoqKnj//j179uwBoKKigtHRUUpLS+nu7iYYDHLv3j127949ra9+AI4ePcrZs2dpamqiv7+fY8eOYZomBw8ejFkt8P3OvbGx7Onpoauri7KyMnJzc1m/fj2fP3/mwIED3L9/n+HhYQKBAN3d3eMhMC0tjVAoRFtbG2/fvuXTp0/cvn0br9eLaZoMDw9z9epVwuEwmZmZk/ahqqqKtrY2Tp48ycDAAFeuXOHcuXNUV1dPq5aMjAyam5sxTZPe3l527NgxrZmw/6q0tBSr1crWrVsJBAIMDg5y48aNCWH9R1ON+5i5c+eya9cuent76ejooLKykpKSEqxWKwC1tbWcOXMGr9fLwMAAT548oaGhgfr6+j9et8gYBSKRGVZXVzfhgme32zl//jw+nw+Hw0FXV9e0L6y/4na7cbvdOBwOHjx4QEtLC4sXLwYYn9X59u0b+fn5GIbBoUOHSE5OjliPEo3KykqOHDlCVVUVhmFw9+5dWlpayMjIiFkt8P2roJs3b5KSkoLL5SIvL4/Vq1fT1NQEfF9L9e7dO8rKyrDZbJSUlLB582Zqa2sByMnJYf/+/Wzfvh2LxYLH4yE5OZnm5mY2bdqE3W7nwoULNDY2smbNmkn74HQ6uX79OteuXWPt2rXU1NRQV1dHeXn5tGqpr68nJSWFnJwcioqKKCgowOl0/tb4RCMpKYnW1laWLFlCYWEhhmHgdrt/Obs11biPSU9Pp7i4mMLCQvLz88nOzo64rX7fvn1cunSJhoYGDMMgNzeXy5cva4ZI/lcJf/17oYKIiIhInNEMkYiIiMQ9BSIRERGJewpEIiIiEvcUiERERCTuKRCJiIhI3FMgEhERkbinQCQiIiJxT4FIRERE4p4CkYiIiMQ9BSIRERGJewpEIiIiEvf+BqfrXXkxCfseAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "data = pd.read_csv('/content/drive/MyDrive/LinkPredictionProject/Data/microbiome.csv', encoding='latin1')\n",
        "\n",
        "cells_condition = (data > 0) & (data <= 1)\n",
        "cells_count = cells_condition.sum()\n",
        "\n",
        "columns_count = cells_count.value_counts().sort_index()\n",
        "\n",
        "total_host_ids = len(data.index)\n",
        "\n",
        "bin_size = int(total_host_ids * 0.02)\n",
        "\n",
        "bins = range(0, cells_count.max() + bin_size - 1, bin_size)\n",
        "\n",
        "plt.hist(cells_count, bins=bins, edgecolor='black', alpha=0.7)\n",
        "\n",
        "plt.xticks(bins, rotation='vertical', ha='center')  # Adjust rotation and alignment\n",
        "\n",
        "plt.yticks(range(0, 1700, 100))  # Adjust the range up to 1650\n",
        "\n",
        "plt.ylim(0, 1650)\n",
        "\n",
        "plt.xlabel('Number of hosts of a microbe')\n",
        "plt.ylabel('Number of microbe')\n",
        "plt.title('The number of hosts in which the microbe are present')\n",
        "\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PGbdHPOzH1kW"
      },
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": 43,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "5SU6Gt9bPNzw",
        "outputId": "08468d40-ab55-4371-8ac0-5d4f534207e3"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjsAAAHHCAYAAABZbpmkAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAABJ1UlEQVR4nO3de3zP9f//8ft7Y5udjR2sMSJsjkWxCDmNfJTok44kdJqEkkMKUw0VUg6fTuig+lQkKsccPtUcS87HhGI2YbOpse35+6Ov96+3DXvPe95vr27Xy+V9uXg9X6fH87nX2r3X6W0zxhgBAABYlJe7CwAAAChNhB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB1c0VasWCGbzaZPP/3U3aW4hc1mU79+/dxdRrHk5eXp6aefVuXKleXl5aUuXbqU2r5GjRolm81Wats/H086HmfOnCmbzaZffvml1Pf1wAMPKDAw0DL7gfUQduBxbDZbsT4rVqxwd6lwwjvvvKOXXnpJd9xxh2bNmqWBAwe6uyQ44dSpUxo1atQ/7vfu0KFDGjVqlDZu3OjuUnAJyri7AOBc7733nsP0u+++qyVLlhRqj4uL0/bt2y9nabgE33zzja666ipNnDix1Pc1YsQIDR06tNT348nuv/9+3XXXXfL19XXJ9k6dOqXRo0dLklq1auWSbV4JDh06pNGjR6tq1apq2LChu8tBCRF24HHuu+8+h+nVq1dryZIlhdolEXYugz///FM+Pj7y8rq0E8Hp6ekKDQ11TVEXUaZMGZUpc+n/eTPG6M8//1S5cuVcUNXl5e3tLW9vb3eXAXgELmPBEgoKCvTCCy8oJiZGfn5+atOmjfbs2VNouTVr1qhDhw4KCQmRv7+/WrZsqe++++6i2z97L8Z///vfi+6natWqeuCBBwpto1WrVg7/R/z3bY4ePVpXXXWVgoKCdMcddygzM1O5ubkaMGCAIiIiFBgYqF69eik3N7fI+j744APVqlVLfn5+atSokVatWlVomd9++00PPvigIiMj5evrqzp16uidd94psp8fffSRRowYoauuukr+/v7Kyso679jk5OToySefVOXKleXr66tatWrp5ZdfljFGkvTLL7/IZrNp+fLl2rp1a7EuQ1atWlX/+te/tGLFCjVu3FjlypVTvXr17OvMmTNH9erVs/f3xx9/dFj/fPfsvP/++7rhhhvk7++v8uXLq0WLFlq8eHGh/S5atMi+3//85z+SpJ9//ln//ve/FRYWJn9/fzVt2lRffvllkfXn5+dr+PDhioqKUkBAgG699VYdPHiw0HLFOR5PnjypAQMGqGrVqvL19VVERITatWunH3744bzjJxV9z87Z/n377be64YYb5Ofnp6uvvlrvvvvuBbf1yy+/KDw8XJI0evRo+89w1KhRDsv99ttv6tKliwIDAxUeHq6nnnpK+fn5DssUFBRo0qRJqlOnjvz8/BQZGamHH35Yx48fv2ANzu7nYsflWUuWLFHz5s0VGhqqwMBA1apVS8OHD5f01+/D9ddfL0nq1auXvd8zZ84sdq3wEAbwcElJSeZ8h+ry5cuNJHPttdeaRo0amYkTJ5pRo0YZf39/c8MNNzgsu2zZMuPj42MSEhLMK6+8YiZOnGjq169vfHx8zJo1ay5YgzP7iY2NNT179iy0jZYtW5qWLVsW2mbDhg1NQkKCmTx5sunfv7+x2WzmrrvuMvfcc4/p2LGjmTJlirn//vuNJDN69GiHbUoydevWNRUrVjTJyclm3LhxJjY21pQrV85s3rzZvlxaWpqJiYkxlStXNsnJyWbatGnm1ltvNZLMxIkTC9UUHx9vGjZsaCZMmGBSUlJMTk5OkeNSUFBgWrdubWw2m+nTp495/fXXTefOnY0kM2DAAGOMMdnZ2ea9994ztWvXNjExMea9994z7733nklLSzvveMfGxppatWqZSpUqmVGjRpmJEyeaq666ygQGBpr333/fVKlSxYwdO9aMHTvWhISEmBo1apj8/Hz7+iNHjix0zIwaNcpIMjfeeKN56aWXzKuvvmruueceM2TIEIf91qhRw5QvX94MHTrUTJ8+3SxfvtykpaWZyMhIExQUZJ555hkzYcIE06BBA+Pl5WXmzJlTaPzq1atn6tevbyZMmGCGDh1q/Pz8TM2aNc2pU6fsyxb3eLznnnuMj4+PGTRokHnrrbfMuHHjTOfOnc37779/3vEzxpgZM2YYSWbfvn2FxjUyMtIMHz7cvP766+a6664zNpvNbNmy5bzbys7ONtOmTTOSzO23327/Gf7000/GGGN69uxp/Pz8TJ06dcyDDz5opk2bZrp162YkmalTpzpsq0+fPqZMmTKmb9++Zvr06WbIkCEmICDAXH/99eb06dMX7FNx91Oc49IYY7Zs2WJ8fHxM48aNzauvvmqmT59unnrqKdOiRQtjzF+/N8nJyUaSeeihh+z93rt37wXrhOch7MDjFSfsxMXFmdzcXHv7q6++aiTZ/+AXFBSYa665xiQmJpqCggL7cqdOnTLVqlUz7dq1u2ANxd2PMc6Hnbp16zr8R/7uu+82NpvNdOzY0WH9hIQEExsb69AmyUgy69evt7ft37/f+Pn5mdtvv93e1rt3b1OpUiVz9OhRh/XvuusuExISYv8jfLamq6++2uEP8/l8/vnnRpJ5/vnnHdrvuOMOY7PZzJ49exz6X6dOnYtu05i/xlCS+f777+1tixYtMpJMuXLlzP79++3t//nPf4wks3z5cnvbuWFn9+7dxsvLy9x+++0OocgY43A8nN3vwoULHZYZMGCAkWT+97//2dtOnjxpqlWrZqpWrWrf5tnxu+qqq0xWVpZ92f/+979Gknn11Vft+yzu8RgSEmKSkpKKNW5/d76wI8msWrXK3paenm58fX3Nk08+ecHtZWRkGElm5MiRheb17NnTSDLJyckO7Wf/5+Cs//3vf0aS+eCDDxyWW7hwYZHtJd1PcY/LiRMnGkkmIyPjvPtct26dkWRmzJhxwdrg2biMBUvo1auXfHx87NM33XSTpL8uPUjSxo0btXv3bt1zzz36/fffdfToUR09elQ5OTlq06aNVq1apYKCgkveT0n06NFDZcuWtU83adJExhg9+OCDDss1adJEBw8eVF5enkN7QkKCGjVqZJ+uUqWKbrvtNi1atEj5+fkyxuizzz5T586dZYyx9/3o0aNKTExUZmZmoUsiPXv2LNZ9Kl999ZW8vb3Vv39/h/Ynn3xSxhh9/fXXxR6Hc8XHxyshIcE+3aRJE0lS69atVaVKlULtF/oZfP755yooKNBzzz1X6N6jcy93VatWTYmJiQ5tX331lW644QY1b97c3hYYGKiHHnpIv/zyi7Zt2+awfI8ePRQUFGSfvuOOO1SpUiV99dVXkpw7HkNDQ7VmzRodOnTovP1zRnx8vP24laTw8HDVqlXrko7hsx555BGH6Ztuuslhu5988olCQkLUrl07h+OwUaNGCgwM1PLly12yn+Iel2fvIZs3b16xfv9x5eIGZVjC3//4SVL58uUlyX4fwO7duyX99Uf8fDIzM+3rlXQ/JXHuNkNCQiRJlStXLtReUFCgzMxMVahQwd5+zTXXFNpmzZo1derUKWVkZMjLy0snTpzQG2+8oTfeeKPIGtLT0x2mq1WrVqza9+/fr+joaIc/7NJfT8qdnV9SzoyLdOGfwd69e+Xl5aX4+PiL7reovu/fv98eqv7u7/2sW7euvf3cn4nNZlONGjXs9884czyOHz9ePXv2VOXKldWoUSPdcsst6tGjh66++uqL9qUo546r9NdxfCnHsCT5+fnZ7+s533Z3796tzMxMRUREFLmNc4/Dku6nuMdl9+7d9dZbb6lPnz4aOnSo2rRpo65du+qOO+645Bvy4VkIO7CE8z11Yv7vZsSz/9f20ksvnffx0eK8rOxi+5EKnyk4Kz8/v8j1z7fN4uyrOM72/b777jvvH9f69es7THvC00elPS7nczn67szxeOedd+qmm27S3LlztXjxYr300ksaN26c5syZo44dOzq979Iav+I8+VVQUKCIiAh98MEHRc4/N8SUdD/FVa5cOa1atUrLly/Xl19+qYULF+rjjz9W69attXjxYp5msxDCDv4RqlevLkkKDg5W27ZtS3Vf5cuX14kTJwq179+/v8T/N34hZ88S/N2uXbvk7+9v/+MRFBSk/Px8l/c9NjZWS5cu1cmTJx3+L3rHjh32+Z6gevXqKigo0LZt20r0rpTY2Fjt3LmzUPv5+nnuz8QYoz179thDpbPHY6VKlfTYY4/pscceU3p6uq677jq98MILJQo7JeWKN1JXr15dS5cuVbNmzUo1VDpzXHp5ealNmzZq06aNJkyYoBdffFHPPPOMli9frrZt27rlTdxwPc7T4R+hUaNGql69ul5++WVlZ2cXmp+RkeGyfVWvXl2rV6/W6dOn7W0LFiwo8tFjV0hNTXW45+bgwYOaN2+e2rdvb3/XSrdu3fTZZ59py5Ythda/lL7fcsstys/P1+uvv+7QPnHiRNlstsv6x/hCunTpIi8vLyUnJxe6N6M4ZzRuueUWrV27Vqmpqfa2nJwcvfHGG6patWqhy2PvvvuuTp48aZ/+9NNPdfjwYft4FPd4zM/PV2ZmpsO8iIgIRUdHn/c1BKXF399fkooM8sV15513Kj8/X2PGjCk0Ly8v75K2/XfFPS6PHTtWaN2zYfjs+AYEBEi6tH7D/Tizg38ELy8vvfXWW+rYsaPq1KmjXr166aqrrtJvv/2m5cuXKzg4WPPnz3fJvvr06aNPP/1UHTp00J133qm9e/fq/ffft//fvKvVrVtXiYmJ6t+/v3x9fTV16lRJsr/tVpLGjh2r5cuXq0mTJurbt6/i4+N17Ngx/fDDD1q6dGmR/9Evjs6dO+vmm2/WM888o19++UUNGjTQ4sWLNW/ePA0YMKDU+uysGjVq6JlnntGYMWN00003qWvXrvL19dW6desUHR2tlJSUC64/dOhQffjhh+rYsaP69++vsLAwzZo1S/v27dNnn31W6P6OsLAwNW/eXL169dKRI0c0adIk1ahRQ3379pVU/OPx5MmTiomJ0R133KEGDRooMDBQS5cu1bp16/TKK6+U2ngVpVy5coqPj9fHH3+smjVrKiwsTHXr1nW4V+liWrZsqYcfflgpKSnauHGj2rdvr7Jly2r37t365JNP9Oqrr+qOO+645FqLe1wmJydr1apV6tSpk2JjY5Wenq6pU6cqJibGfjN69erVFRoaqunTpysoKEgBAQFq0qRJse9rg2cg7OAfo1WrVkpNTdWYMWP0+uuvKzs7W1FRUWrSpIkefvhhl+0nMTFRr7zyiiZMmKABAwaocePGWrBggZ588kmX7ePvWrZsqYSEBI0ePVoHDhxQfHy8Zs6c6XAfTmRkpNauXavk5GTNmTNHU6dOVYUKFVSnTh2NGzeuxPv28vLSF198oeeee04ff/yxZsyYoapVq+qll14qtf6WVHJysqpVq6bXXntNzzzzjPz9/VW/fn3df//9F103MjJS33//vYYMGaLXXntNf/75p+rXr6/58+erU6dOhZYfPny4Nm3apJSUFJ08eVJt2rTR1KlT7WdHpOIdj/7+/nrssce0ePFizZkzRwUFBapRo4amTp2qRx991HWDU0xvvfWWHn/8cQ0cOFCnT5/WyJEjnQo7kjR9+nQ1atRI//nPfzR8+HCVKVNGVatW1X333admzZq5pM7iHpe33nqrfvnlF73zzjs6evSoKlasqJYtW2r06NH2G9/Lli2rWbNmadiwYXrkkUeUl5enGTNmEHauMDbjqrv6AAAAPBD37AAAAEsj7AAAAEsj7AAAAEsj7AAAAEsj7AAAAEsj7AAAAEvjPTv66/taDh06pKCgIF4NDgDAFcIYo5MnTyo6OvqCX95K2JF06NChQt+kDAAArgwHDx5UTEzMeecTdiT7F8UdPHhQwcHBbq4GAAAUR1ZWlipXruzwha9FIezo/3+bb3BwMGEHAIArzMVuQeEGZQAAYGmEHQAAYGluDTvTpk1T/fr17ZePEhIS9PXXX9vn//nnn0pKSlKFChUUGBiobt266ciRIw7bOHDggDp16iR/f39FRERo8ODBysvLu9xdAQAAHsqtYScmJkZjx47Vhg0btH79erVu3Vq33Xabtm7dKkkaOHCg5s+fr08++UQrV67UoUOH1LVrV/v6+fn56tSpk06fPq3vv/9es2bN0syZM/Xcc8+5q0sAAMDD2Iwxxt1F/F1YWJheeukl3XHHHQoPD9fs2bN1xx13SJJ27NihuLg4paamqmnTpvr666/1r3/9S4cOHVJkZKQkafr06RoyZIgyMjLk4+NTrH1mZWUpJCREmZmZ3KAMAMAVorh/vz3mnp38/Hx99NFHysnJUUJCgjZs2KAzZ86obdu29mVq166tKlWqKDU1VZKUmpqqevXq2YOOJCUmJiorK8t+dqgoubm5ysrKcvgAAABrcnvY2bx5swIDA+Xr66tHHnlEc+fOVXx8vNLS0uTj46PQ0FCH5SMjI5WWliZJSktLcwg6Z+efnXc+KSkpCgkJsX94oSAAANbl9rBTq1Ytbdy4UWvWrNGjjz6qnj17atu2baW6z2HDhikzM9P+OXjwYKnuDwAAuI/bXyro4+OjGjVqSJIaNWqkdevW6dVXX1X37t11+vRpnThxwuHszpEjRxQVFSVJioqK0tq1ax22d/ZprbPLFMXX11e+vr4u7gkAAPBEbj+zc66CggLl5uaqUaNGKlu2rJYtW2aft3PnTh04cEAJCQmSpISEBG3evFnp6en2ZZYsWaLg4GDFx8df9toBAIDnceuZnWHDhqljx46qUqWKTp48qdmzZ2vFihVatGiRQkJC1Lt3bw0aNEhhYWEKDg7W448/roSEBDVt2lSS1L59e8XHx+v+++/X+PHjlZaWphEjRigpKYkzNwAAQJKbw056erp69Oihw4cPKyQkRPXr19eiRYvUrl07SdLEiRPl5eWlbt26KTc3V4mJiZo6dap9fW9vby1YsECPPvqoEhISFBAQoJ49eyo5OdldXQIAAB7G496z4w68ZwcAgCvPFfeeHQAAgNLg9qexAKC0ZWRk8PLQYgoODlZ4eLi7ywBcirADwNIyMjJ0X68+OnbylLtLuSKEBfnr/RlvEXhgKYQdAJaWlZWlYydPKTyhmwLCIi++wj9YzrEjykj9TFlZWYQdWAphB8A/QkBYpIIjYtxdhsfLcHcBQCngBmUAAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBphB0AAGBpbg07KSkpuv766xUUFKSIiAh16dJFO3fudFimVatWstlsDp9HHnnEYZkDBw6oU6dO8vf3V0REhAYPHqy8vLzL2RUAAOChyrhz5ytXrlRSUpKuv/565eXlafjw4Wrfvr22bdumgIAA+3J9+/ZVcnKyfdrf39/+7/z8fHXq1ElRUVH6/vvvdfjwYfXo0UNly5bViy++eFn7AwAAPI9bw87ChQsdpmfOnKmIiAht2LBBLVq0sLf7+/srKiqqyG0sXrxY27Zt09KlSxUZGamGDRtqzJgxGjJkiEaNGiUfH59S7QMAAPBsHnXPTmZmpiQpLCzMof2DDz5QxYoVVbduXQ0bNkynTp2yz0tNTVW9evUUGRlpb0tMTFRWVpa2bt1a5H5yc3OVlZXl8AEAANbk1jM7f1dQUKABAwaoWbNmqlu3rr39nnvuUWxsrKKjo7Vp0yYNGTJEO3fu1Jw5cyRJaWlpDkFHkn06LS2tyH2lpKRo9OjRpdQTAADgSTwm7CQlJWnLli369ttvHdofeugh+7/r1aunSpUqqU2bNtq7d6+qV69eon0NGzZMgwYNsk9nZWWpcuXKJSscAAB4NI8IO/369dOCBQu0atUqxcTEXHDZJk2aSJL27Nmj6tWrKyoqSmvXrnVY5siRI5J03vt8fH195evr64LKAffJyMjgEmwx7N+/X3lneDoT+Cdza9gxxujxxx/X3LlztWLFClWrVu2i62zcuFGSVKlSJUlSQkKCXnjhBaWnpysiIkKStGTJEgUHBys+Pr7UagfcKSMjQ/f16qNjJ09dfOF/uD//OKVffzusKmfOuLsUAG7i1rCTlJSk2bNna968eQoKCrLfYxMSEqJy5cpp7969mj17tm655RZVqFBBmzZt0sCBA9WiRQvVr19fktS+fXvFx8fr/vvv1/jx45WWlqYRI0YoKSmJszewrKysLB07eUrhCd0UEBZ58RX+wdL3btH+g+8oP4+wA/xTuTXsTJs2TdJfLw78uxkzZuiBBx6Qj4+Pli5dqkmTJiknJ0eVK1dWt27dNGLECPuy3t7eWrBggR599FElJCQoICBAPXv2dHgvD2BVAWGRCo648KXff7rs34t+UAHAP4fbL2NdSOXKlbVy5cqLbic2NlZfffWVq8oCAAAW4lHv2QEAAHA1wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0t4adlJQUXX/99QoKClJERIS6dOminTt3Oizz559/KikpSRUqVFBgYKC6deumI0eOOCxz4MABderUSf7+/oqIiNDgwYOVl5d3ObsCAAA8lFvDzsqVK5WUlKTVq1dryZIlOnPmjNq3b6+cnBz7MgMHDtT8+fP1ySefaOXKlTp06JC6du1qn5+fn69OnTrp9OnT+v777zVr1izNnDlTzz33nDu6BAAAPEwZd+584cKFDtMzZ85URESENmzYoBYtWigzM1Nvv/22Zs+erdatW0uSZsyYobi4OK1evVpNmzbV4sWLtW3bNi1dulSRkZFq2LChxowZoyFDhmjUqFHy8fFxR9cAAICH8Kh7djIzMyVJYWFhkqQNGzbozJkzatu2rX2Z2rVrq0qVKkpNTZUkpaamql69eoqMjLQvk5iYqKysLG3durXI/eTm5iorK8vhAwAArOmSw05WVpY+//xzbd++/ZK2U1BQoAEDBqhZs2aqW7euJCktLU0+Pj4KDQ11WDYyMlJpaWn2Zf4edM7OPzuvKCkpKQoJCbF/KleufEm1AwAAz+V02Lnzzjv1+uuvS5L++OMPNW7cWHfeeafq16+vzz77rMSFJCUlacuWLfroo49KvI3iGjZsmDIzM+2fgwcPlvo+AQCAezgddlatWqWbbrpJkjR37lwZY3TixAlNnjxZzz//fImK6NevnxYsWKDly5crJibG3h4VFaXTp0/rxIkTDssfOXJEUVFR9mXOfTrr7PTZZc7l6+ur4OBghw8AALAmp8NOZmam/Z6ahQsXqlu3bvL391enTp20e/dup7ZljFG/fv00d+5cffPNN6pWrZrD/EaNGqls2bJatmyZvW3nzp06cOCAEhISJEkJCQnavHmz0tPT7cssWbJEwcHBio+Pd7Z7AADAYpx+Gqty5cpKTU1VWFiYFi5caL/sdPz4cfn5+Tm1raSkJM2ePVvz5s1TUFCQ/R6bkJAQlStXTiEhIerdu7cGDRqksLAwBQcH6/HHH1dCQoKaNm0qSWrfvr3i4+N1//33a/z48UpLS9OIESOUlJQkX19fZ7sHAAAsxumwM2DAAN17770KDAxUbGysWrVqJemvy1v16tVzalvTpk2TJPs2zpoxY4YeeOABSdLEiRPl5eWlbt26KTc3V4mJiZo6dap9WW9vby1YsECPPvqoEhISFBAQoJ49eyo5OdnZrgEAAAtyOuw89thjatKkiQ4cOKB27drJy+uvK2FXX321XnjhBae2ZYy56DJ+fn6aMmWKpkyZct5lYmNj9dVXXzm1bwAA8M/g9D07ycnJiouL0+23367AwEB7e+vWrbV06VKXFgcAAHCpnA47o0ePVnZ2dqH2U6dOafTo0S4pCgAAwFWcDjvGGNlstkLtP/30k/0pLQAAAE9R7Ht2ypcvL5vNJpvNppo1azoEnvz8fGVnZ+uRRx4plSIBAABKqthhZ9KkSTLG6MEHH9To0aMVEhJin+fj46OqVava330DAADgKYoddnr27ClJqlatmpo1a6YyZdz6hekAAADF4vQ9O0FBQQ5f+jlv3jx16dJFw4cP1+nTp11aHAAAwKVyOuw8/PDD2rVrlyTp559/Vvfu3eXv769PPvlETz/9tMsLBAAAuBROh51du3apYcOGkqRPPvlELVu21OzZszVz5sxL+tZzAACA0lCiR88LCgokSUuXLtUtt9wi6a/vzDp69KhrqwMAALhEToedxo0b6/nnn9d7772nlStXqlOnTpKkffv2KTIy0uUFAgAAXAqnw86kSZP0ww8/qF+/fnrmmWdUo0YNSdKnn36qG2+80eUFAgAAXAqnnx+vX7++Nm/eXKj9pZdekre3t0uKAgAAcJUSvyxnw4YN9kfQ4+Pjdd1117msKAAAAFdxOuykp6ere/fuWrlypUJDQyVJJ06c0M0336yPPvpI4eHhrq4RAACgxJy+Z+fxxx9Xdna2tm7dqmPHjunYsWPasmWLsrKy1L9//9KoEQAAoMScPrOzcOFCLV26VHFxcfa2+Ph4TZkyRe3bt3dpcQAAAJfK6TM7BQUFKlu2bKH2smXL2t+/AwAA4CmcDjutW7fWE088oUOHDtnbfvvtNw0cOFBt2rRxaXEAAACXyumw8/rrrysrK0tVq1ZV9erVVb16dVWrVk1ZWVl67bXXSqNGAACAEnP6np3KlSvrhx9+0NKlS7Vjxw5JUlxcnNq2bevy4gAAAC5Vid6zY7PZ1K5dO7Vr187V9QAAALhUicLOsmXLtGzZMqWnpxe6Kfmdd95xSWEAAACu4HTYGT16tJKTk9W4cWNVqlRJNputNOoCAABwCafDzvTp0zVz5kzdf//9pVEPAACASzn9NNbp06f5dnMAAHDFcDrs9OnTR7Nnzy6NWgAAAFyuWJexBg0aZP93QUGB3njjDS1dulT169cv9DblCRMmuLZCAACAS1CssPPjjz86TDds2FCStGXLFod2blYGAACeplhhZ/ny5aVdBwAAQKlw+p4dAACAKwlhBwAAWBphBwAAWBphBwAAWFqxws51112n48ePS5KSk5N16tSpUi0KAADAVYoVdrZv366cnBxJf303VnZ2dqkWBQAA4CrFevS8YcOG6tWrl5o3by5jjF5++WUFBgYWuexzzz3n0gIBAAAuRbHCzsyZMzVy5EgtWLBANptNX3/9tcqUKbyqzWYj7AAAAI9SrLBTq1YtffTRR5IkLy8vLVu2TBEREaVaGAAAgCsUK+z8XUFBQWnUAQAAUCqcDjuStHfvXk2aNEnbt2+XJMXHx+uJJ55Q9erVXVocAADApXL6PTuLFi1SfHy81q5dq/r166t+/fpas2aN6tSpoyVLlpRGjQAAACXm9JmdoUOHauDAgRo7dmyh9iFDhqhdu3YuKw4AAOBSOX1mZ/v27erdu3eh9gcffFDbtm1zSVEAAACu4nTYCQ8P18aNGwu1b9y4kSe0AACAx3H6Mlbfvn310EMP6eeff9aNN94oSfruu+80btw4DRo0yOUFAgAAXAqnw86zzz6roKAgvfLKKxo2bJgkKTo6WqNGjVL//v1dXiAAAMClcDrs2Gw2DRw4UAMHDtTJkyclSUFBQS4vDAAAwBVK9J6dswg5AADA0zl9g7IrrVq1Sp07d1Z0dLRsNps+//xzh/kPPPCAbDabw6dDhw4Oyxw7dkz33nuvgoODFRoaqt69e/Ot7AAAwM6tYScnJ0cNGjTQlClTzrtMhw4ddPjwYfvnww8/dJh/7733auvWrVqyZIkWLFigVatW6aGHHirt0gEAwBXiki5jXaqOHTuqY8eOF1zG19dXUVFRRc7bvn27Fi5cqHXr1qlx48aSpNdee0233HKLXn75ZUVHR7u8ZgAAcGVx6szOmTNn1KZNG+3evbu06ilkxYoVioiIUK1atfToo4/q999/t89LTU1VaGioPehIUtu2beXl5aU1a9ZcthoBAIDncurMTtmyZbVp06bSqqWQDh06qGvXrqpWrZr27t2r4cOHq2PHjkpNTZW3t7fS0tIKvciwTJkyCgsLU1pa2nm3m5ubq9zcXPt0VlZWqfUBAAC4l9P37Nx33316++23S6OWQu666y7deuutqlevnrp06aIFCxZo3bp1WrFixSVtNyUlRSEhIfZP5cqVXVMwAADwOE7fs5OXl6d33nlHS5cuVaNGjRQQEOAwf8KECS4r7lxXX321KlasqD179qhNmzaKiopSenp6ofqOHTt23vt8JGnYsGEOb3vOysoi8AAAYFFOh50tW7bouuuukyTt2rXLYZ7NZnNNVefx66+/6vfff1elSpUkSQkJCTpx4oQ2bNigRo0aSZK++eYbFRQUqEmTJufdjq+vr3x9fUu1VgAA4BmcDjvLly932c6zs7O1Z88e+/S+ffu0ceNGhYWFKSwsTKNHj1a3bt0UFRWlvXv36umnn1aNGjWUmJgoSYqLi1OHDh3Ut29fTZ8+XWfOnFG/fv1011138SQWAJTAmdOntX//fneXcUUIDg5WeHi4u8tAMZT40fM9e/Zo7969atGihcqVKydjjNNndtavX6+bb77ZPn320lLPnj01bdo0bdq0SbNmzdKJEycUHR2t9u3ba8yYMQ5nZT744AP169dPbdq0kZeXl7p166bJkyeXtFsA8I+Vm52pX/b9rAHDR3H2uxjCgvz1/oy3CDxXAKfDzu+//64777xTy5cvl81m0+7du3X11Verd+/eKl++vF555ZVib6tVq1Yyxpx3/qJFiy66jbCwMM2ePbvY+wQAFO1M7h8qsJVRxaZdVSE61t3leLScY0eUkfqZsrKyCDtXAKfDzsCBA1W2bFkdOHBAcXFx9vbu3btr0KBBToUdAIDn8S8fruCIGHeX4fEy3F0Ais3psLN48WItWrRIMTGOvwjXXHMN13kBAIDHcfo9Ozk5OfL39y/UfuzYMa7xAgAAj+N02Lnpppv07rvv2qdtNpsKCgo0fvx4h5uNAQAAPIHTl7HGjx+vNm3aaP369Tp9+rSefvppbd26VceOHdN3331XGjUCAACUmNNndurWratdu3apefPmuu2225STk6OuXbvqxx9/VPXq1UujRgAAgBIr0Xt2QkJC9Mwzz7i6FgAAAJcrUdg5fvy43n77bW3fvl2SFB8fr169eiksLMylxQEAAFwqpy9jrVq1SlWrVtXkyZN1/PhxHT9+XJMnT1a1atW0atWq0qgRAACgxJw+s5OUlKTu3btr2rRp8vb2liTl5+frscceU1JSkjZv3uzyIgEAAErK6TM7e/bs0ZNPPmkPOpLk7e2tQYMGOXypJwAAgCdwOuxcd9119nt1/m779u1q0KCBS4oCAABwlWJdxtq0aZP93/3799cTTzyhPXv2qGnTppKk1atXa8qUKRo7dmzpVAkAAFBCxQo7DRs2lM1mc/iG8qeffrrQcvfcc4+6d+/uuuoAAAAuUbHCzr59+0q7DgAAgFJRrLATGxtb2nUAAACUihK9VPDQoUP69ttvlZ6eroKCAod5/fv3d0lhAAAAruB02Jk5c6Yefvhh+fj4qEKFCrLZbPZ5NpuNsAMAADyK02Hn2Wef1XPPPadhw4bJy8vpJ9cBAAAuK6fTyqlTp3TXXXcRdAAAwBXB6cTSu3dvffLJJ6VRCwAAgMs5fRkrJSVF//rXv7Rw4ULVq1dPZcuWdZg/YcIElxUHAABwqUoUdhYtWqRatWpJUqEblAEAADyJ02HnlVde0TvvvKMHHnigFMoBAABwLafv2fH19VWzZs1KoxYAAACXczrsPPHEE3rttddKoxYAAACXc/oy1tq1a/XNN99owYIFqlOnTqEblOfMmeOy4gAAAC6V02EnNDRUXbt2LY1aAAAAXM7psDNjxozSqAMAAKBU8BpkAABgaU6f2alWrdoF36fz888/X1JBAAAAruR02BkwYIDD9JkzZ/Tjjz9q4cKFGjx4sKvqAgAAcAmnw84TTzxRZPuUKVO0fv36Sy4IAADAlVx2z07Hjh312WefuWpzAAAALuGysPPpp58qLCzMVZsDAABwCacvY1177bUONygbY5SWlqaMjAxNnTrVpcXhnyUjI0NZWVnuLuOKsH//fuWdyXN3GQBwRXA67HTp0sVh2svLS+Hh4WrVqpVq167tqrrwD5ORkaH7evXRsZOn3F3KFeHPP07p198Oq8qZM+4uBQA8ntNhZ+TIkaVRB/7hsrKydOzkKYUndFNAWKS7y/F46Xu3aP/Bd5SfR9gBgItxOuwApSkgLFLBETHuLsPjZf+e5u4SAOCKUeyw4+XldcGXCUqSzWZTXh73EQAAAM9R7LAzd+7c885LTU3V5MmTVVBQ4JKiAAAAXKXYYee2224r1LZz504NHTpU8+fP17333qvk5GSXFgcAAHCpSvSenUOHDqlv376qV6+e8vLytHHjRs2aNUuxsbGurg8AAOCSOBV2MjMzNWTIENWoUUNbt27VsmXLNH/+fNWtW7e06gMAALgkxb6MNX78eI0bN05RUVH68MMPi7ysBQAA4GmKHXaGDh2qcuXKqUaNGpo1a5ZmzZpV5HJz5sxxWXEAAACXqthhp0ePHhd99BwAAMDTFDvszJw5sxTLAAAAKB0u+9ZzAAAAT+TWsLNq1Sp17txZ0dHRstls+vzzzx3mG2P03HPPqVKlSipXrpzatm2r3bt3Oyxz7Ngx3XvvvQoODlZoaKh69+6t7Ozsy9gLAADgydwadnJyctSgQQNNmTKlyPnjx4/X5MmTNX36dK1Zs0YBAQFKTEzUn3/+aV/m3nvv1datW7VkyRItWLBAq1at0kMPPXS5ugAAADycW78ItGPHjurYsWOR84wxmjRpkkaMGGF/zP3dd99VZGSkPv/8c911113avn27Fi5cqHXr1qlx48aSpNdee0233HKLXn75ZUVHR1+2vgAAAM/ksffs7Nu3T2lpaWrbtq29LSQkRE2aNFFqaqqkv76TKzQ01B50JKlt27by8vLSmjVrLnvNAADA87j1zM6FpKWlSZIiIyMd2iMjI+3z0tLSFBER4TC/TJkyCgsLsy9TlNzcXOXm5tqns7KyXFU2AADwMB57Zqc0paSkKCQkxP6pXLmyu0sCAAClxGPDTlRUlCTpyJEjDu1Hjhyxz4uKilJ6errD/Ly8PB07dsy+TFGGDRumzMxM++fgwYMurh4AAHgKjw071apVU1RUlJYtW2Zvy8rK0po1a5SQkCBJSkhI0IkTJ7Rhwwb7Mt98840KCgrUpEmT827b19dXwcHBDh8AAGBNbr1nJzs7W3v27LFP79u3Txs3blRYWJiqVKmiAQMG6Pnnn9c111yjatWq6dlnn1V0dLS6dOkiSYqLi1OHDh3Ut29fTZ8+XWfOnFG/fv1011138SQWAACQ5Oaws379et1888326UGDBkmSevbsqZkzZ+rpp59WTk6OHnroIZ04cULNmzfXwoUL5efnZ1/ngw8+UL9+/dSmTRt5eXmpW7dumjx58mXvCwAA8ExuDTutWrWSMea88202m5KTk5WcnHzeZcLCwjR79uzSKA8AAFiAx96zAwAA4AqEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGmEHQAAYGkeHXZGjRolm83m8Kldu7Z9/p9//qmkpCRVqFBBgYGB6tatm44cOeLGigEAgKfx6LAjSXXq1NHhw4ftn2+//dY+b+DAgZo/f74++eQTrVy5UocOHVLXrl3dWC0AAPA0ZdxdwMWUKVNGUVFRhdozMzP19ttva/bs2WrdurUkacaMGYqLi9Pq1avVtGnTy10qAADwQB5/Zmf37t2Kjo7W1VdfrXvvvVcHDhyQJG3YsEFnzpxR27Zt7cvWrl1bVapUUWpqqrvKBQAAHsajz+w0adJEM2fOVK1atXT48GGNHj1aN910k7Zs2aK0tDT5+PgoNDTUYZ3IyEilpaVdcLu5ubnKzc21T2dlZZVG+QAAwAN4dNjp2LGj/d/169dXkyZNFBsbq//+978qV65cibebkpKi0aNHu6JEAADg4Tz+MtbfhYaGqmbNmtqzZ4+ioqJ0+vRpnThxwmGZI0eOFHmPz98NGzZMmZmZ9s/BgwdLsWoAAOBOV1TYyc7O1t69e1WpUiU1atRIZcuW1bJly+zzd+7cqQMHDighIeGC2/H19VVwcLDDBwAAWJNHX8Z66qmn1LlzZ8XGxurQoUMaOXKkvL29dffddyskJES9e/fWoEGDFBYWpuDgYD3++ONKSEjgSSwAAGDn0WHn119/1d13363ff/9d4eHhat68uVavXq3w8HBJ0sSJE+Xl5aVu3bopNzdXiYmJmjp1qpurBgAAnsSjw85HH310wfl+fn6aMmWKpkyZcpkqAgAAV5or6p4dAAAAZxF2AACApRF2AACApRF2AACApRF2AACApXn001hWkJGRwXdvFcP+/fuVdybP3WUAACyIsFOKMjIydF+vPjp28pS7S/F4f/5xSr/+dlhVzpxxdykAAIsh7JSirKwsHTt5SuEJ3RQQFunucjxa+t4t2n/wHeXnEXYAAK5F2LkMAsIiFRwR4+4yPFr272nuLgEAYFHcoAwAACyNsAMAACyNsAMAACyNsAMAACyNsAMAACyNsAMAACyNsAMAACyNsAMAACyNsAMAACyNsAMAACyNsAMAACyN78YCAKAEzpw+rf3797u7jCtCcHCwwsPD3bZ/wg4AAE7Kzc7UL/t+1oDho+Tr6+vucjxeWJC/3p/xltsCD2EHAAAnncn9QwW2MqrYtKsqRMe6uxyPlnPsiDJSP1NWVhZhBwCAK41/+XAFR8S4uwyPl+Hm/XODMgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTCDgAAsDTLhJ0pU6aoatWq8vPzU5MmTbR27Vp3lwQAADyAJcLOxx9/rEGDBmnkyJH64Ycf1KBBAyUmJio9Pd3dpQEAADezRNiZMGGC+vbtq169eik+Pl7Tp0+Xv7+/3nnnHXeXBgAA3OyKDzunT5/Whg0b1LZtW3ubl5eX2rZtq9TUVDdWBgAAPEEZdxdwqY4ePar8/HxFRkY6tEdGRmrHjh1FrpObm6vc3Fz7dGZmpiQpKyvLpbWdPHlS+Xl5OnH4F53585RLt201Wem/yhQUKCvtoMrY3F2N52O8io+xKj7GqvgYq+LLOZ6u/Lw8nTx50uV/Z89uzxhz4QXNFe63334zksz333/v0D548GBzww03FLnOyJEjjSQ+fPjw4cOHjwU+Bw8evGBWuOLP7FSsWFHe3t46cuSIQ/uRI0cUFRVV5DrDhg3ToEGD7NMFBQU6duyYKlSoIJvNdRE9KytLlStX1sGDBxUcHOyy7VoRY+Ucxqv4GKviY6yKj7EqvtIcK2OMTp48qejo6Asud8WHHR8fHzVq1EjLli1Tly5dJP0VXpYtW6Z+/foVuY6vr698fX0d2kJDQ0utxuDgYH4Ziomxcg7jVXyMVfExVsXHWBVfaY1VSEjIRZe54sOOJA0aNEg9e/ZU48aNdcMNN2jSpEnKyclRr1693F0aAABwM0uEne7duysjI0PPPfec0tLS1LBhQy1cuLDQTcsAAOCfxxJhR5L69et33stW7uLr66uRI0cWumSGwhgr5zBexcdYFR9jVXyMVfF5wljZjLnY81oAAABXriv+pYIAAAAXQtgBAACWRtgBAACWRtgBAACWRtgpBatWrVLnzp0VHR0tm82mzz//3N0lebTffvtN9913nypUqKBy5cqpXr16Wr9+vbvLcruLHUdz5sxR+/bt7W/+3rhxo1vq9ATF+Z3bvn27br31VoWEhCggIEDXX3+9Dhw4cPmLdbOUlBRdf/31CgoKUkREhLp06aKdO3c6LPPGG2+oVatWCg4Ols1m04kTJ9xTrJsVZ6wkKTU1Va1bt1ZAQICCg4PVokUL/fHHH26o2H2mTZum+vXr218cmJCQoK+//to+393HFGGnFOTk5KhBgwaaMmWKu0vxeMePH1ezZs1UtmxZff3119q2bZteeeUVlS9f3t2lud3FjqOcnBw1b95c48aNu8yVeZ6LjdXevXvVvHlz1a5dWytWrNCmTZv07LPPys/P7zJX6n4rV65UUlKSVq9erSVLlujMmTNq3769cnJy7MucOnVKHTp00PDhw91YqfsVZ6xSU1PVoUMHtW/fXmvXrtW6devUr18/eXn9s/68xsTEaOzYsdqwYYPWr1+v1q1b67bbbtPWrVslecAx5Zqv48T5SDJz5851dxkea8iQIaZ58+buLsPjXeg42rdvn5Fkfvzxx8tak6cqaqy6d+9u7rvvPvcU5OHS09ONJLNy5cpC85YvX24kmePHj1/+wjxQUWPVpEkTM2LECDdW5bnKly9v3nrrLYc2dx1T/6zoCY/zxRdfqHHjxvr3v/+tiIgIXXvttXrzzTfdXRYspKCgQF9++aVq1qypxMRERUREqEmTJlxe/j+ZmZmSpLCwMDdX4vnOHav09HStWbNGERERuvHGGxUZGamWLVvq22+/dWeZbpefn6+PPvpIOTk5SkhIcHc5kriMBTf7+eefNW3aNF1zzTVatGiRHn30UfXv31+zZs1yd2mwiPT0dGVnZ2vs2LHq0KGDFi9erNtvv11du3bVypUr3V2eWxUUFGjAgAFq1qyZ6tat6+5yPFpRY/Xzzz9LkkaNGqW+fftq4cKFuu6669SmTRvt3r3bneW6xebNmxUYGChfX1898sgjmjt3ruLj491dliQLfV0ErkwFBQVq3LixXnzxRUnStddeqy1btmj69Onq2bOnm6uDFRQUFEiSbrvtNg0cOFCS1LBhQ33//feaPn26WrZs6c7y3CopKUlbtmz5x5+JKI6ixurssfXwww/bv3j62muv1bJly/TOO+8oJSXFLbW6S61atbRx40ZlZmbq008/Vc+ePbVy5UqPCDyc2YFbVapUqdAvQlxc3D/yKRmUjooVK6pMmTIcZ+fo16+fFixYoOXLlysmJsbd5Xi0841VpUqVJIlj6//4+PioRo0aatSokVJSUtSgQQO9+uqr7i5LEmEHbtasWbNCj3Lu2rVLsbGxbqoIVuPj46Prr7+e4+z/GGPUr18/zZ07V998842qVavm7pI81sXGqmrVqoqOjubYOo+CggLl5ua6uwxJXMYqFdnZ2dqzZ499et++fdq4caPCwsJUpUoVN1bmeQYOHKgbb7xRL774ou68806tXbtWb7zxht544w13l+Z2FzuOjh07pgMHDujQoUOSZP8PblRUlKKiotxSs7tcbKwGDx6s7t27q0WLFrr55pu1cOFCzZ8/XytWrHBf0W6SlJSk2bNna968eQoKClJaWpokKSQkROXKlZMkpaWlKS0tzT6mmzdvVlBQkKpUqfKPupH5YmNls9k0ePBgjRw5Ug0aNFDDhg01a9Ys7dixQ59++qmbq7+8hg0bpo4dO6pKlSo6efKkZs+erRUrVmjRokWSPOCYuqzPfv1DnH207txPz5493V2aR5o/f76pW7eu8fX1NbVr1zZvvPGGu0vyCBc7jmbMmFHk/JEjR7q1bncozu/c22+/bWrUqGH8/PxMgwYNzOeff+6+gt2oqHGSZGbMmGFfZuTIkRdd5p+gOGNljDEpKSkmJibG+Pv7m4SEBPO///3PPQW70YMPPmhiY2ONj4+PCQ8PN23atDGLFy+2z3f3MWUzxpjSClIAAADuxj07AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7AADA0gg7wBXml19+kc1m08aNG91dit2OHTvUtGlT+fn5qWHDhi7b7ooVK2Sz2XTixAmXbbMorVq10oABA0p1H+eqWrWqJk2a5PLtzpw5U6GhoS7frjvGCHAVwg7gpAceeEA2m01jx451aP/8889ls9ncVJV7jRw5UgEBAdq5c6eWLVvmsu3eeOONOnz4sEJCQly2TU+xbt06PfTQQ5e0jdIKTO5QWiENkAg7QIn4+flp3LhxOn78uLtLcZnTp0+XeN29e/eqefPmio2NVYUKFVxWk4+Pj6KiokocIi+lT6UtPDxc/v7+7i4D+Ecg7AAl0LZtW0VFRSklJeW8y4waNarQJZ1JkyapatWq9ukHHnhAXbp00YsvvqjIyEiFhoYqOTlZeXl5Gjx4sMLCwhQTE6MZM2YU2v6OHTt04403ys/PT3Xr1tXKlSsd5m/ZskUdO3ZUYGCgIiMjdf/99+vo0aP2+a1atVK/fv00YMAAVaxYUYmJiUX2o6CgQMnJyYqJiZGvr68aNmyohQsX2ufbbDZt2LBBycnJstlsGjVqVJHbadWqlR5//HENGDBA5cuXV2RkpN58803l5OSoV69eCgoKUo0aNfT111/b1ynqMtZ3332nVq1ayd/fX+XLl1diYqI9dJ6vTytXrtQNN9wgX19fVapUSUOHDlVeXp5DfXl5eerXr59CQkJUsWJFPfvss/r7t+nk5ubqqaee0lVXXaWAgAA1adLE4YtE9+/fr86dO6t8+fIKCAhQnTp19NVXXxU5FlLhszI2m01vvfWWbr/9dvn7++uaa67RF198cd71W7Vqpf3792vgwIGy2WyFAuGiRYsUFxenwMBAdejQQYcPH3aY/9ZbbykuLk5+fn6qXbu2pk6det59nVVQUKCnn35aYWFhioqKKvSzPnDggG677TYFBgYqODhYd955p44cOWKf/9NPP+nmm29WUFCQgoOD1ahRI61fv14rVqxQr169lJmZae/L+Y4joEQuyzdwARbSs2dPc9ttt5k5c+YYPz8/c/DgQWOMMXPnzjV//5UaOXKkadCggcO6EydONLGxsQ7bCgoKMklJSWbHjh3m7bffNpJMYmKieeGFF8yuXbvMmDFjTNmyZe372bdvn5FkYmJizKeffmq2bdtm+vTpY4KCgszRo0eNMcYcP37chIeHm2HDhpnt27ebH374wbRr187cfPPN9n23bNnSBAYGmsGDB5sdO3aYHTt2FNnfCRMmmODgYPPhhx+aHTt2mKefftqULVvW7Nq1yxhjzOHDh02dOnXMk08+aQ4fPmxOnjxZ5HZatmxpgoKCzJgxY+z98vb2Nh07djRvvPGG2bVrl3n00UdNhQoVTE5OjjHm/3/B5/Hjx40xxvz444/G19fXPProo2bjxo1my5Yt5rXXXjMZGRnn7dOvv/5q/P39zWOPPWa2b99u5s6daypWrOjwhaln13viiSfMjh07zPvvv2/8/f0dvpS2T58+5sYbbzSrVq0ye/bsMS+99JLx9fW1j0OnTp1Mu3btzKZNm8zevXvN/PnzzcqVK4scC2OMiY2NNRMnTrRPn/2Zzp492+zevdv079/fBAYGmt9//73I9X///XcTExNjkpOTzeHDh83hw4eNMX99QWzZsmVN27Ztzbp168yGDRtMXFycueeee+zrvv/++6ZSpUrms88+Mz///LP57LPPTFhYmJk5c+Z5623ZsqUJDg42o0aNMrt27TKzZs0yNpvN/mWP+fn5pmHDhqZ58+Zm/fr1ZvXq1aZRo0amZcuW9m3UqVPH3HfffWb79u1m165d5r///a/ZuHGjyc3NNZMmTTLBwcH2vpzvOAJKgrADOOls2DHGmKZNm5oHH3zQGFPysBMbG2vy8/PtbbVq1TI33XSTfTovL88EBASYDz/80Bjz/8PO2LFj7cucOXPGxMTEmHHjxhljjBkzZoxp3769w74PHjxoJJmdO3caY/7643XttddetL/R0dHmhRdecGi7/vrrzWOPPWafbtCgwUW/bb1ly5amefPmhfp1//3329sOHz5sJJnU1FRjTOGwc/fdd5tmzZpdcB/n9mn48OGmVq1apqCgwN42ZcoUExgYaB/3li1bmri4OIdlhgwZYuLi4owxxuzfv994e3ub3377zWHbbdq0McOGDTPGGFOvXj0zatSoC47B3xUVdkaMGGGfzs7ONpLM119/XextGPNX2JFk9uzZ49DfyMhI+3T16tXN7NmzHdYbM2aMSUhIOO++zv35GfPXcTBkyBBjjDGLFy823t7e5sCBA/b5W7duNZLM2rVrjTHGBAUFnTdQzZgxw4SEhJx3/8Cl4DIWcAnGjRunWbNmafv27SXeRp06deTl9f9/FSMjI1WvXj37tLe3typUqKD09HSH9RISEuz/LlOmjBo3bmyv46efftLy5csVGBho/9SuXVvSX/fXnNWoUaML1paVlaVDhw6pWbNmDu3NmjUrUZ/r169fqF9/72tkZKQkFerrWRs3blSbNm0uuI9z+7R9+3YlJCQ4XOZp1qyZsrOz9euvv9rbmjZt6rBMQkKCdu/erfz8fG3evFn5+fmqWbOmw5iuXLnSPp79+/fX888/r2bNmmnkyJHatGnTxYajkL+PT0BAgIKDg887Fhfi7++v6tWr26crVapk305OTo727t2r3r17O/Tl+eefdzg2Llbfudvdvn27KleurMqVK9vnx8fHKzQ01H6sDBo0SH369FHbtm01duzYi+4PcJUy7i4AuJK1aNFCiYmJGjZsmB544AGHeV5eXg73fEjSmTNnCm2jbNmyDtM2m63ItoKCgmLXlZ2drc6dO2vcuHGF5lWqVMn+74CAgGJv0xUu1tezYeN8fS1XrtxF91EafcrOzpa3t7c2bNggb29vh3mBgYGSpD59+igxMVFffvmlFi9erJSUFL3yyit6/PHHi72fS/25X2g7Z4/F7OxsSdKbb76pJk2aOCx3bt9cXd+oUaN0zz336Msvv9TXX3+tkSNH6qOPPtLtt99e7G0AJcGZHeASjR07VvPnz1dqaqpDe3h4uNLS0hwCjyvfjbN69Wr7v/Py8rRhwwbFxcVJkq677jpt3bpVVatWVY0aNRw+zoSB4OBgRUdH67vvvnNo/+677xQfH++ajjihfv36Tj/aHhcXp9TUVIefw3fffaegoCDFxMTY29asWeOw3urVq3XNNdfI29tb1157rfLz85Wenl5oPKOiouzrVK5cWY888ojmzJmjJ598Um+++WYJe1o8Pj4+ys/Pd2qdyMhIRUdH6+effy7Ul2rVqpW4lri4OB08eFAHDx60t23btk0nTpxwOFZq1qypgQMHavHixeratav95vuS9AUoLsIOcInq1aune++9V5MnT3Zob9WqlTIyMjR+/Hjt3btXU6ZMcXjS6FJNmTJFc+fO1Y4dO5SUlKTjx4/rwQcflCQlJSXp2LFjuvvuu7Vu3Trt3btXixYtUq9evZz+gzJ48GCNGzdOH3/8sXbu3KmhQ4dq48aNeuKJJ1zWl+IaNmyY1q1bp8cee0ybNm3Sjh07NG3aNIenzM712GOP6eDBg3r88ce1Y8cOzZs3TyNHjtSgQYMcLh8eOHBAgwYN0s6dO/Xhhx/qtddes/exZs2auvfee9WjRw/NmTNH+/bt09q1a5WSkqIvv/xSkjRgwAAtWrRI+/bt0w8//KDly5fbw2dpqVq1qlatWqXffvvtgmNwrtGjRyslJUWTJ0/Wrl27tHnzZs2YMUMTJkwocS1t27a1/y788MMPWrt2rXr06KGWLVuqcePG+uOPP9SvXz+tWLFC+/fv13fffad169bZx6hq1arKzs7WsmXLdPToUZ06darEtQDnIuwALpCcnFzodH5cXJymTp2qKVOmqEGDBlq7dq2eeuopl+1z7NixGjt2rBo0aKBvv/1WX3zxhSpWrChJ9rMx+fn5at++verVq6cBAwYoNDTU4Q98cfTv31+DBg3Sk08+qXr16mnhwoX64osvdM0117isL8VVs2ZNLV68WD/99JNuuOEGJSQkaN68eSpT5vxX5K+66ip99dVXWrt2rRo0aKBHHnlEvXv31ogRIxyW69Gjh/744w/dcMMNSkpK0hNPPOHw0r8ZM2aoR48eevLJJ1WrVi116dJF69atU5UqVSRJ+fn5SkpKUlxcnDp06KCaNWsW63HuS5GcnKxffvlF1atXV3h4eLHX69Onj9566y3NmDFD9erVU8uWLTVz5sxLOrNjs9k0b948lS9fXi1atFDbtm119dVX6+OPP5b01yWy33//XT169FDNmjV15513qmPHjho9erSkv14g+cgjj6h79+4KDw/X+PHjS1wLcC6bOfemAgAAAAvhzA4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALA0wg4AALC0/wc0bFrLYw3Z7gAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "data = pd.read_csv('/content/drive/MyDrive/LinkPredictionProject/Data/microbiome.csv', encoding='latin1')\n",
        "\n",
        "cells_condition = (data > 0) & (data <= 1)\n",
        "cells_count = cells_condition.sum(axis=1)\n",
        "\n",
        "bin_width = 5\n",
        "bins = range(min(cells_count), max(cells_count) + bin_width, bin_width)\n",
        "\n",
        "plt.hist(cells_count, bins=bins, edgecolor='black', alpha=0.7)\n",
        "\n",
        "plt.xticks(bins)\n",
        "\n",
        "plt.xlabel('Number of microbes in the host')\n",
        "plt.ylabel('Number of hosts')\n",
        "plt.title('The number of microbes in the host')\n",
        "\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jLkgaIydszUr"
      },
      "source": [
        "# **host_metadata**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 44,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 660
        },
        "id": "DQrNGha6xzTo",
        "outputId": "262bad06-9a97-4ded-b9b5-54df585e7670"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   host_ID  day  month  year  season  preparation  \\\n",
              "0     2010    2     10  2019       1  skull, tail   \n",
              "1     2011    2     10  2019       1  skull, tail   \n",
              "2     2013    2     10  2019       1  skull, tail   \n",
              "3     2014    2     10  2019       1  skull, tail   \n",
              "4     2015    2     10  2019       1  skull, tail   \n",
              "\n",
              "                                            locality  village grid_name  \\\n",
              "0  Madagascar, Région SAVA, District Sambava, Com...  Mandena    Savoka   \n",
              "1  Madagascar, Région SAVA, District Sambava, Com...  Mandena    Savoka   \n",
              "2  Madagascar, Région SAVA, District Sambava, Com...  Mandena    Savoka   \n",
              "3  Madagascar, Région SAVA, District Sambava, Com...  Mandena    Savoka   \n",
              "4  Madagascar, Région SAVA, District Sambava, Com...  Mandena    Savoka   \n",
              "\n",
              "   grid_number     habitat_type trap_type trap_number   latitude  longitude  \\\n",
              "0            1  brushy_regrowth   Sherman           1 -14.466052  49.799352   \n",
              "1            1  brushy_regrowth   Sherman          15 -14.466166  49.798864   \n",
              "2            1  brushy_regrowth   Sherman          65 -14.465687  49.799079   \n",
              "3            1  brushy_regrowth   Sherman          90 -14.465359  49.799012   \n",
              "4            1  brushy_regrowth   Sherman         105 -14.465503  49.798734   \n",
              "\n",
              "   elevation.obs     sex  mass   hb  epididym  \n",
              "0     144.218796  female  80.0  153       NaN  \n",
              "1     145.284958    male  51.0  134  not con.  \n",
              "2     118.188316  female  88.0  157       NaN  \n",
              "3     133.551437    male  77.0  148  not con.  \n",
              "4     145.232788  female  65.0  134       NaN  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-67b01089-03a2-4847-86e9-380c6ccff6c6\" 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>host_ID</th>\n",
              "      <th>day</th>\n",
              "      <th>month</th>\n",
              "      <th>year</th>\n",
              "      <th>season</th>\n",
              "      <th>preparation</th>\n",
              "      <th>locality</th>\n",
              "      <th>village</th>\n",
              "      <th>grid_name</th>\n",
              "      <th>grid_number</th>\n",
              "      <th>habitat_type</th>\n",
              "      <th>trap_type</th>\n",
              "      <th>trap_number</th>\n",
              "      <th>latitude</th>\n",
              "      <th>longitude</th>\n",
              "      <th>elevation.obs</th>\n",
              "      <th>sex</th>\n",
              "      <th>mass</th>\n",
              "      <th>hb</th>\n",
              "      <th>epididym</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2010</td>\n",
              "      <td>2</td>\n",
              "      <td>10</td>\n",
              "      <td>2019</td>\n",
              "      <td>1</td>\n",
              "      <td>skull, tail</td>\n",
              "      <td>Madagascar, Région SAVA, District Sambava, Com...</td>\n",
              "      <td>Mandena</td>\n",
              "      <td>Savoka</td>\n",
              "      <td>1</td>\n",
              "      <td>brushy_regrowth</td>\n",
              "      <td>Sherman</td>\n",
              "      <td>1</td>\n",
              "      <td>-14.466052</td>\n",
              "      <td>49.799352</td>\n",
              "      <td>144.218796</td>\n",
              "      <td>female</td>\n",
              "      <td>80.0</td>\n",
              "      <td>153</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2011</td>\n",
              "      <td>2</td>\n",
              "      <td>10</td>\n",
              "      <td>2019</td>\n",
              "      <td>1</td>\n",
              "      <td>skull, tail</td>\n",
              "      <td>Madagascar, Région SAVA, District Sambava, Com...</td>\n",
              "      <td>Mandena</td>\n",
              "      <td>Savoka</td>\n",
              "      <td>1</td>\n",
              "      <td>brushy_regrowth</td>\n",
              "      <td>Sherman</td>\n",
              "      <td>15</td>\n",
              "      <td>-14.466166</td>\n",
              "      <td>49.798864</td>\n",
              "      <td>145.284958</td>\n",
              "      <td>male</td>\n",
              "      <td>51.0</td>\n",
              "      <td>134</td>\n",
              "      <td>not con.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2013</td>\n",
              "      <td>2</td>\n",
              "      <td>10</td>\n",
              "      <td>2019</td>\n",
              "      <td>1</td>\n",
              "      <td>skull, tail</td>\n",
              "      <td>Madagascar, Région SAVA, District Sambava, Com...</td>\n",
              "      <td>Mandena</td>\n",
              "      <td>Savoka</td>\n",
              "      <td>1</td>\n",
              "      <td>brushy_regrowth</td>\n",
              "      <td>Sherman</td>\n",
              "      <td>65</td>\n",
              "      <td>-14.465687</td>\n",
              "      <td>49.799079</td>\n",
              "      <td>118.188316</td>\n",
              "      <td>female</td>\n",
              "      <td>88.0</td>\n",
              "      <td>157</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2014</td>\n",
              "      <td>2</td>\n",
              "      <td>10</td>\n",
              "      <td>2019</td>\n",
              "      <td>1</td>\n",
              "      <td>skull, tail</td>\n",
              "      <td>Madagascar, Région SAVA, District Sambava, Com...</td>\n",
              "      <td>Mandena</td>\n",
              "      <td>Savoka</td>\n",
              "      <td>1</td>\n",
              "      <td>brushy_regrowth</td>\n",
              "      <td>Sherman</td>\n",
              "      <td>90</td>\n",
              "      <td>-14.465359</td>\n",
              "      <td>49.799012</td>\n",
              "      <td>133.551437</td>\n",
              "      <td>male</td>\n",
              "      <td>77.0</td>\n",
              "      <td>148</td>\n",
              "      <td>not con.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2015</td>\n",
              "      <td>2</td>\n",
              "      <td>10</td>\n",
              "      <td>2019</td>\n",
              "      <td>1</td>\n",
              "      <td>skull, tail</td>\n",
              "      <td>Madagascar, Région SAVA, District Sambava, Com...</td>\n",
              "      <td>Mandena</td>\n",
              "      <td>Savoka</td>\n",
              "      <td>1</td>\n",
              "      <td>brushy_regrowth</td>\n",
              "      <td>Sherman</td>\n",
              "      <td>105</td>\n",
              "      <td>-14.465503</td>\n",
              "      <td>49.798734</td>\n",
              "      <td>145.232788</td>\n",
              "      <td>female</td>\n",
              "      <td>65.0</td>\n",
              "      <td>134</td>\n",
              "      <td>NaN</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-67b01089-03a2-4847-86e9-380c6ccff6c6')\"\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-67b01089-03a2-4847-86e9-380c6ccff6c6 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-67b01089-03a2-4847-86e9-380c6ccff6c6');\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-c28e51f9-62e7-4ae0-a53d-d18eff3b89c5\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-c28e51f9-62e7-4ae0-a53d-d18eff3b89c5')\"\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-c28e51f9-62e7-4ae0-a53d-d18eff3b89c5 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 880,\n  \"fields\": [\n    {\n      \"column\": \"host_ID\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 585,\n        \"min\": 2010,\n        \"max\": 4037,\n        \"num_unique_values\": 880,\n        \"samples\": [\n          2749,\n          2607,\n          3885\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"day\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 8,\n        \"min\": 1,\n        \"max\": 31,\n        \"num_unique_values\": 31,\n        \"samples\": [\n          27,\n          23,\n          29\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"month\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2,\n        \"min\": 3,\n        \"max\": 12,\n        \"num_unique_values\": 10,\n        \"samples\": [\n          5,\n          11,\n          8\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"year\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 2019,\n        \"max\": 2022,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          2020,\n          2022,\n          2019\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"season\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 1,\n        \"max\": 3,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          1,\n          2,\n          3\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"preparation\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"pickle\",\n          \"skull\",\n          \"skull, tail\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"locality\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"Madagascar, R\\u00e9gion SAVA, District Sambava, Commune Rurale Maroambihy, Fokontany Mandena\",\n          \"Madagascar, R\\u00e9gion SAVA, Distict Andapa, Commune Rurale Marovato, Fokontany Sarahandrano\",\n          \"Madagascar, R\\u00e9gion SAVA, District Sambava, Commune Rurale Andratamarina, Fokontany Andatsakala\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"village\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"Mandena\",\n          \"Sarahandrano\",\n          \"Andatsakala\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"grid_name\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 10,\n        \"samples\": [\n          \"Vanilla, coffee, banana fields\",\n          \"Sugar cane\",\n          \"Rice field\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"grid_number\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2,\n        \"min\": 1,\n        \"max\": 7,\n        \"num_unique_values\": 7,\n        \"samples\": [\n          1,\n          2,\n          5\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"habitat_type\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 7,\n        \"samples\": [\n          \"brushy_regrowth\",\n          \"agriculture\",\n          \"flooded_rice\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"trap_type\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"Sherman\",\n          \"Tomahawk\",\n          \"Pitfall\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"trap_number\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 183,\n        \"samples\": [\n          \"80\",\n          \"67\",\n          \"house6, trap2\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"latitude\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.08157324706162576,\n        \"min\": -14.60889,\n        \"max\": -14.393162978813,\n        \"num_unique_values\": 567,\n        \"samples\": [\n          -14.3961200304329,\n          -14.3961870018392,\n          -14.47999\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"longitude\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.08819613746465284,\n        \"min\": 49.64405,\n        \"max\": 49.8865909595042,\n        \"num_unique_values\": 576,\n        \"samples\": [\n          49.8109700158238,\n          49.8106499947607,\n          49.65177\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"elevation.obs\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 252.20772479247614,\n        \"min\": 68.0,\n        \"max\": 800.5,\n        \"num_unique_values\": 608,\n        \"samples\": [\n          126.341843,\n          141.379288,\n          121.885634999999\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"sex\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"male\",\n          \"female\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"mass\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 37.50768768098439,\n        \"min\": 12.0,\n        \"max\": 203.0,\n        \"num_unique_values\": 189,\n        \"samples\": [\n          22.0,\n          184.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"hb\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 23,\n        \"min\": 75,\n        \"max\": 190,\n        \"num_unique_values\": 88,\n        \"samples\": [\n          116,\n          153\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"epididym\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"not con.\",\n          \"con. x not con.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 44
        }
      ],
      "source": [
        "df = pd.read_csv('/content/drive/MyDrive/LinkPredictionProject/Data/host_metadata.csv', encoding='latin1')\n",
        "df = df.drop(columns=['museum_number','animal_id','final_identification', 'field_identification',  'mammae_condition', 'mammae_number_ax', 'mammae_number_ab',\n",
        "       'mammae_number_ing', 'embryos_r', 'age_repro', 'age_dental', 'habitat_description', 'testicle_length', 'testicle_width', 'testicle_position','pitfall_position', 'tl', 'tv', 'hf', 'ear', 'notes', 'dist_village_center', 'vagina', 'embryos_l', 'embryos_l', 'embryos_cr', 'placental_scars_l', 'placental_scars_r'])\n",
        "df.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 45,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 388
        },
        "id": "qhKm-D_-ncds",
        "outputId": "e7fdcc65-05e8-4f5f-f2a6-00cc176f69aa"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 500x400 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# @title Hosts count for each habitat type\n",
        "plt.figure(figsize=(5, 4))\n",
        "df.groupby('habitat_type').size().plot(kind='barh', color=sns.palettes.mpl_palette('Dark2'))\n",
        "plt.xlabel('Number of hosts')\n",
        "plt.gca().spines[['top', 'right',]].set_visible(False)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eyArVg0g7b5K"
      },
      "source": [
        "In the exploratory data analysis, the distribution of hosts across various habitat types reveals notable differences in abundance.<br>\n",
        "Agriculture and agroforest habitats exhibit the highest counts with ~160 and ~170 hosts respectively, indicating their significance in hosting diverse populations.<br> Conversely, semi-intact forest stands out with the lowest count at ~20 hosts, suggesting its comparatively limited suitability for hosting microbes or its conservation status restricting host populations within this habitat.<br>\n",
        "These findings underscore the importance of habitat type in shaping host populations and potentially influencing microbe transmission dynamics within ecosystems."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 46,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 386
        },
        "id": "gEXsf2ZE8E2E",
        "outputId": "6f80e8dd-9518-48b2-fa57-d4a869997689"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 400x400 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# @title Village\n",
        "hosts_per_village = df['village'].value_counts()\n",
        "colors = plt.cm.tab20.colors[:len(hosts_per_village)]\n",
        "\n",
        "plt.figure(figsize=(4, 4))\n",
        "plt.pie(hosts_per_village, labels=hosts_per_village.index, autopct='%1.1f%%', startangle=90, colors=colors)\n",
        "plt.title('Distribution of Hosts Across Villages', pad=20)\n",
        "plt.axis('equal')\n",
        "\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 47,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sFIaFGN7680c",
        "outputId": "f8f34da4-3201-4a76-9f41-66025aced05a"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mandena: 345\n",
            "Sarahandrano: 301\n",
            "Andatsakala: 234\n"
          ]
        }
      ],
      "source": [
        "hosts_per_village = df['village'].value_counts()\n",
        "for village, count in hosts_per_village.items():\n",
        "    print(f\"{village}: {count}\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "F0TJlb6A9eSR"
      },
      "source": [
        "The differences in host distribution across Mandena, Sarahandrano, and Andatsakala appear relatively close, with Mandena having a slightly higher proportion of hosts compared to the other two villages.<br>While the differences may not be dramatic, they still indicate varying host populations across the villages,<br> which could be influenced by ecological, social, or geographic factors."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "42LpVb17-FJ6"
      },
      "source": [
        "###Temporal trends\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nWb1rljb-XB7"
      },
      "source": [
        "per year:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 48,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 407
        },
        "id": "-OfzHcAw9FYK",
        "outputId": "bac44b08-3814-4b5d-a7cf-fc4c4c904df3"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 500x400 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# Group the data by year and count the number of hosts examined each year\n",
        "hosts_per_year = df.groupby('year')['host_ID'].count()\n",
        "\n",
        "# Plot\n",
        "plt.figure(figsize=(5, 4))\n",
        "hosts_per_year.plot(kind='bar', color='skyblue')\n",
        "plt.title('Number of Hosts Examined per Year')\n",
        "plt.xlabel('Year')\n",
        "plt.ylabel('Number of Hosts')\n",
        "plt.xticks(rotation=45, ha='right')\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 49,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MrAgUFkq-Q1v",
        "outputId": "8d969dc5-ab15-40c4-ec7a-26fb236a79ac"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2020: 344\n",
            "2021: 275\n",
            "2022: 167\n",
            "2019: 94\n"
          ]
        }
      ],
      "source": [
        "hosts_per_year = df['year'].value_counts()\n",
        "for year, count in hosts_per_year.items():\n",
        "    print(f\"{year}: {count}\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Gpu8MUs_-wuz"
      },
      "source": [
        "The bar chart depicts the number of hosts examined each year, revealing a notable fluctuation in examination counts over time. <br>The year 2020 stands out with the highest examination count at 344 hosts, followed by 2021 with 275 hosts. <br>Conversely, the examination counts for 2019 and 2022 are notably lower, at 94 and 167 hosts respectively.<br> This variation suggests potential shifts in research focus, sampling efforts, or data collection methodologies across different years"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 50,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "k8O5JOfCHYfZ",
        "outputId": "537d3624-0b13-4c33-eafb-9c1e5a615c4a"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Season 1: [10, 11, 12]\n",
            "Season 2: [3, 4, 5]\n",
            "Season 3: [6, 7, 8, 9]\n"
          ]
        }
      ],
      "source": [
        "#check months for each season\n",
        "for season_value in sorted(df['season'].unique()):\n",
        "    season_df = df[df['season'] == season_value]\n",
        "    print(f\"Season {season_value}: {sorted(season_df['month'].unique())}\")\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "L-7aZpsE-ZTy"
      },
      "source": [
        "per season:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 51,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 507
        },
        "id": "0cOwWB67-a5m",
        "outputId": "38db4c28-8bf1-4799-f81b-ac64b1832317"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 400x500 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "season_labels = {\n",
        "    1: 'October - December',\n",
        "    2: 'March - May',\n",
        "    3: 'June - September'\n",
        "}\n",
        "df['season_label'] = df['season'].map(season_labels)\n",
        "hosts_per_season = df['season_label'].value_counts()\n",
        "ordered_months = ['October - December', 'March - May', 'June - September']\n",
        "\n",
        "# Plot\n",
        "plt.figure(figsize=(4, 5))\n",
        "hosts_per_season[ordered_months].plot(kind='bar', color='skyblue')\n",
        "plt.title('Number of Hosts Examined per season')\n",
        "plt.xlabel('Months')\n",
        "plt.ylabel('Number of Hosts')\n",
        "plt.xticks(rotation=45, ha='right')\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zJKlODUuAfjx"
      },
      "source": [
        "The bar chart illustrates the distribution of host examinations across different seasons.<br>June to September emerges as the period with the highest number of host examinations.<br>\n",
        "This distribution suggests seasonal variations in sampling efforts or ecological factors influencing host populations, highlighting the importance of considering seasonal dynamics in understanding disease ecology and transmission patterns."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PEq9OMCZzVz8"
      },
      "source": [
        "# **Pathogens**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 52,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 256
        },
        "id": "bRwW2z9Xxcyo",
        "outputId": "c4ab65c3-cce3-42cf-a852-9364fff5537d"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   host_ID  OTU_ID_1  OTU_ID_2  OTU_ID_3  OTU_ID_4  OTU_ID_5  OTU_ID_6  \\\n",
              "0     2010       0.0  0.907808       0.0       0.0       0.0       0.0   \n",
              "1     2011       0.0  0.000000       0.0       0.0       0.0       0.0   \n",
              "2     2013       0.0  1.000000       0.0       0.0       0.0       0.0   \n",
              "3     2014       0.0  1.000000       0.0       0.0       0.0       0.0   \n",
              "4     2015       0.0  0.000000       0.0       0.0       0.0       0.0   \n",
              "\n",
              "   OTU_ID_7  OTU_ID_8  OTU_ID_9  ...  OTU_ID_105  OTU_ID_106  OTU_ID_107  \\\n",
              "0       0.0       0.0       0.0  ...         0.0           0           0   \n",
              "1       0.0       0.0       0.0  ...         0.0           0           0   \n",
              "2       0.0       0.0       0.0  ...         0.0           0           0   \n",
              "3       0.0       0.0       0.0  ...         0.0           0           0   \n",
              "4       0.0       0.0       0.0  ...         0.0           0           0   \n",
              "\n",
              "   OTU_ID_108  OTU_ID_109  OTU_ID_110  OTU_ID_111  OTU_ID_112  OTU_ID_113  \\\n",
              "0         0.0         0.0           0         0.0         0.0         0.0   \n",
              "1         0.0         0.0           0         0.0         0.0         0.0   \n",
              "2         0.0         0.0           0         0.0         0.0         0.0   \n",
              "3         0.0         0.0           0         0.0         0.0         0.0   \n",
              "4         0.0         0.0           0         0.0         0.0         0.0   \n",
              "\n",
              "   OTU_ID_114  \n",
              "0         0.0  \n",
              "1         0.0  \n",
              "2         0.0  \n",
              "3         0.0  \n",
              "4         0.0  \n",
              "\n",
              "[5 rows x 115 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-ff1f8ceb-ffae-4733-ada6-8a1949551f39\" 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>host_ID</th>\n",
              "      <th>OTU_ID_1</th>\n",
              "      <th>OTU_ID_2</th>\n",
              "      <th>OTU_ID_3</th>\n",
              "      <th>OTU_ID_4</th>\n",
              "      <th>OTU_ID_5</th>\n",
              "      <th>OTU_ID_6</th>\n",
              "      <th>OTU_ID_7</th>\n",
              "      <th>OTU_ID_8</th>\n",
              "      <th>OTU_ID_9</th>\n",
              "      <th>...</th>\n",
              "      <th>OTU_ID_105</th>\n",
              "      <th>OTU_ID_106</th>\n",
              "      <th>OTU_ID_107</th>\n",
              "      <th>OTU_ID_108</th>\n",
              "      <th>OTU_ID_109</th>\n",
              "      <th>OTU_ID_110</th>\n",
              "      <th>OTU_ID_111</th>\n",
              "      <th>OTU_ID_112</th>\n",
              "      <th>OTU_ID_113</th>\n",
              "      <th>OTU_ID_114</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2010</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.907808</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2011</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2013</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2014</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2015</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 115 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-ff1f8ceb-ffae-4733-ada6-8a1949551f39')\"\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-ff1f8ceb-ffae-4733-ada6-8a1949551f39 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-ff1f8ceb-ffae-4733-ada6-8a1949551f39');\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-cd31c885-595c-422d-a24b-c6b83e36f558\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-cd31c885-595c-422d-a24b-c6b83e36f558')\"\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-cd31c885-595c-422d-a24b-c6b83e36f558 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df"
            }
          },
          "metadata": {},
          "execution_count": 52
        }
      ],
      "source": [
        "df = pd.read_csv('/content/drive/MyDrive/LinkPredictionProject/Data/pathogen.csv', encoding='latin1')\n",
        "df.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 53,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BGqy7DKvy3b0",
        "outputId": "61ebfb27-de42-4adb-8b17-12d42bec4df0"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Row sums: 0      2.0\n",
            "1      1.0\n",
            "2      1.0\n",
            "3      1.0\n",
            "4      1.0\n",
            "      ... \n",
            "749    1.0\n",
            "750    1.0\n",
            "751    1.0\n",
            "752    1.0\n",
            "753    1.0\n",
            "Length: 754, dtype: float64\n",
            "All rows sum to 1: True\n"
          ]
        }
      ],
      "source": [
        "#Check that each row sums to 1\n",
        "row_sums = df.iloc[:, 1:].sum(axis=1)\n",
        "print(f'Row sums: {row_sums}')\n",
        "print(f'All rows sum to 1: {row_sums.all()}')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-iL82f822Ci9"
      },
      "source": [
        "This plot describes the mean percentage of the presence of each pathogen in hosts  - the top 5"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 54,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 407
        },
        "id": "HzkAbrUey_HR",
        "outputId": "fe6c81fb-b032-4543-ab98-838599bbed60"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 400x400 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# Get the top 5 pathogens by mean percentage across hosts\n",
        "top_pathogens = df.iloc[:, 1:].mean().sort_values(ascending=False).head(5)\n",
        "# Plot a bar plot for the top 5 pathogens\n",
        "plt.figure(figsize=(4, 4))\n",
        "sns.barplot(x=top_pathogens.index, y=top_pathogens.values)\n",
        "plt.title('Top 5 pathogens')\n",
        "plt.xlabel('Pathogens')\n",
        "plt.ylabel('Mean Percentage')\n",
        "plt.xticks(rotation=45, ha='right')\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zhOOCD7CqYFI"
      },
      "source": [
        " We observed the top 5 pathogens by mean percentage across hosts.<br>OTU_ID_2 emerges as the most prevalent pathogen, constituting 75% on average."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 55,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 507
        },
        "id": "nWctb7rd6GE5",
        "outputId": "45542e4f-02dd-46a0-9e02-8896efd871c0"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1100x500 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "hosts_count = df.iloc[:, 1:].gt(0).sum()\n",
        "\n",
        "plt.figure(figsize=(11, 5))\n",
        "\n",
        "hosts_count.plot(kind='bar', color='skyblue')\n",
        "new_xtick_labels = [x.split('_')[-1] for x in hosts_count.index]\n",
        "\n",
        "plt.title('Counts of hosts for each pathogen')\n",
        "plt.xlabel('Pathogens')\n",
        "plt.ylabel('Hosts')\n",
        "plt.xticks(range(len(hosts_count)), new_xtick_labels, rotation=90, ha='right', fontsize=7)\n",
        "plt.tight_layout()\n",
        "\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fekoWpngqlnB"
      },
      "source": [
        "In order to minimize noise and enhance clarity, we selectively filtered pathogens on the graph,<br>retaining only those with a count of hosts exceeding 10.<br>\n",
        "This adjustment allows for a more focused analysis of notable changes between the different pathogens."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 56,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 507
        },
        "id": "D-SRpJWQ4xVF",
        "outputId": "6d9bcb42-b62c-4c10-ecda-0e679c606357"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "hosts_count = df.iloc[:, 1:].gt(0).sum()\n",
        "\n",
        "# Plotting\n",
        "plt.figure(figsize=(7, 5))\n",
        "\n",
        "filter_hosts = hosts_count[hosts_count > 10]\n",
        "filter_hosts.plot(kind='bar', color='skyblue')\n",
        "\n",
        "plt.title('Filter counts of hosts for each pathogen (min 10)')\n",
        "plt.xlabel('Pathogens')\n",
        "plt.ylabel('Hosts')\n",
        "plt.xticks(fontsize=8, rotation=45, ha='right')\n",
        "plt.tight_layout()\n",
        "\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GvIymdUfsOE7"
      },
      "source": [
        "\n",
        "In this plot, we can now observe the variations between the pathogens clearly.\n",
        "<br>The graph illustrates the 22 pathogens with the highest frequency among hosts.\n",
        "<br>Pathogen number 2 stands out with the highest examination count- exceeding 600 hosts."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "67dS_CgLquHY"
      },
      "source": [
        "**Histogram**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 57,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "M4wuqg5pzlNO",
        "outputId": "f3a4f46d-904a-4276-abbf-27db71b7ef1d"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "data = pd.read_csv('/content/drive/MyDrive/LinkPredictionProject/Data/pathogen.csv', encoding='latin1')\n",
        "\n",
        "cells_condition = (data > 0) & (data <= 1)\n",
        "cells_count = cells_condition.sum()\n",
        "\n",
        "columns_count = cells_count.value_counts().sort_index()\n",
        "\n",
        "total_host_ids = len(data.index)\n",
        "\n",
        "# Define the bins for the histogram (each bin representing 10% of the total host IDs)\n",
        "bin_size = int(total_host_ids * 0.1)\n",
        "\n",
        "bins = range(0, cells_count.max() + bin_size - 1, bin_size)\n",
        "\n",
        "plt.hist(cells_count, bins=bins, edgecolor='black', alpha=0.7)\n",
        "\n",
        "plt.xticks(bins)\n",
        "\n",
        "plt.xlabel('Number of hosts of a pathogen')\n",
        "plt.ylabel('Number of pathogens')\n",
        "plt.title('The number of hosts in which the pathogens are present')\n",
        "\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 58,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "NrGaq2J5H3H3",
        "outputId": "8eb74d67-a0fe-4670-c104-7a48dbdc4bc0"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "\n",
        "data = pd.read_csv('/content/drive/MyDrive/LinkPredictionProject/Data/pathogen.csv', encoding='latin1')\n",
        "\n",
        "cells_condition = (data > 0) & (data <= 1)\n",
        "cells_count = cells_condition.sum(axis=1)\n",
        "\n",
        "# Define the range of bins, each representing a range of 3 pathogens IDs\n",
        "bin_width = 3\n",
        "bins = range(min(cells_count), max(cells_count) + bin_width, bin_width)\n",
        "\n",
        "plt.hist(cells_count, bins=bins, edgecolor='black')\n",
        "plt.xticks(bins)\n",
        "\n",
        "\n",
        "plt.xlabel('Number of pathogens in the host')\n",
        "plt.ylabel('Number of hosts')\n",
        "plt.title('The number of pathogens in the host')\n",
        "\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TFKK5FIMzh_u"
      },
      "source": [
        "# **Pathogen_metadata**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 59,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "p1RXiH55zpWx",
        "outputId": "cf7f3c96-7c7e-47ee-e2ce-0a28c0d338aa"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   OTU_ID pathogen_type       otu_Order         otu_Family  \\\n",
              "0      89      Protozoa  Incertae_Sedis       Blastocystis   \n",
              "1      97      Protozoa     Apicomplexa        Eimeriorina   \n",
              "2      76      Protozoa     Parabasalia   Tritrichomonadea   \n",
              "3      79      Protozoa     Parabasalia   Tritrichomonadea   \n",
              "4      84      Protozoa     Parabasalia  Hypotrichomonadea   \n",
              "\n",
              "                    otu_Genus  \n",
              "0  Blastocystis_sp._subtype_3  \n",
              "1                     Eimeria  \n",
              "2              Tritrichomonas  \n",
              "3              Tritrichomonas  \n",
              "4             Hypotrichomonas  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-82b80588-dba5-4034-84c9-23e0fa9b0bac\" 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>OTU_ID</th>\n",
              "      <th>pathogen_type</th>\n",
              "      <th>otu_Order</th>\n",
              "      <th>otu_Family</th>\n",
              "      <th>otu_Genus</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>89</td>\n",
              "      <td>Protozoa</td>\n",
              "      <td>Incertae_Sedis</td>\n",
              "      <td>Blastocystis</td>\n",
              "      <td>Blastocystis_sp._subtype_3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>97</td>\n",
              "      <td>Protozoa</td>\n",
              "      <td>Apicomplexa</td>\n",
              "      <td>Eimeriorina</td>\n",
              "      <td>Eimeria</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>76</td>\n",
              "      <td>Protozoa</td>\n",
              "      <td>Parabasalia</td>\n",
              "      <td>Tritrichomonadea</td>\n",
              "      <td>Tritrichomonas</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>79</td>\n",
              "      <td>Protozoa</td>\n",
              "      <td>Parabasalia</td>\n",
              "      <td>Tritrichomonadea</td>\n",
              "      <td>Tritrichomonas</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>84</td>\n",
              "      <td>Protozoa</td>\n",
              "      <td>Parabasalia</td>\n",
              "      <td>Hypotrichomonadea</td>\n",
              "      <td>Hypotrichomonas</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-82b80588-dba5-4034-84c9-23e0fa9b0bac')\"\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-82b80588-dba5-4034-84c9-23e0fa9b0bac 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-82b80588-dba5-4034-84c9-23e0fa9b0bac');\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-fa480cb6-f1f4-4a12-b42c-87174c9c2b33\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-fa480cb6-f1f4-4a12-b42c-87174c9c2b33')\"\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-fa480cb6-f1f4-4a12-b42c-87174c9c2b33 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 114,\n  \"fields\": [\n    {\n      \"column\": \"OTU_ID\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 33,\n        \"min\": 1,\n        \"max\": 114,\n        \"num_unique_values\": 114,\n        \"samples\": [\n          72,\n          84,\n          5\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"pathogen_type\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Nematoda\",\n          \"Protozoa\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"otu_Order\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"Apicomplexa\",\n          \"Rhabditida\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"otu_Family\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 19,\n        \"samples\": [\n          \"Blastocystis\",\n          \"Cryptosporida\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"otu_Genus\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 19,\n        \"samples\": [\n          \"Blastocystis_sp._subtype_3\",\n          \"Tetratrichomonas\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 59
        }
      ],
      "source": [
        "df = pd.read_csv('/content/drive/MyDrive/LinkPredictionProject/Data/pathogen_metadata.csv', encoding='latin1')\n",
        "df.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 60,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 407
        },
        "id": "urjms2QgZCEu",
        "outputId": "b9fc0143-4b11-4979-80fd-ee59feab1524"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 400x400 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "pathogen_counts = df['pathogen_type'].value_counts()\n",
        "pathogen_counts = pathogen_counts.astype(int)\n",
        "\n",
        "plt.figure(figsize=(4, 4))\n",
        "plt.pie(pathogen_counts, labels=pathogen_counts.index, autopct='%1.1f%%', colors=plt.cm.tab20.colors)\n",
        "plt.title('Distribution of Pathogen Types')\n",
        "plt.axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
        "plt.tight_layout()\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "m0sZHSw2xn4P"
      },
      "source": [
        "The pie chart reveals a notable predominance of Nematoda, comprising 64.9% of the pathogen types,<br>while Protozoa accounts for 35.1%.<br>\n",
        "This distribution sheds light on the ecological dynamics within the studied ecosystem, indicating a higher prevalence of nematode-related infections compared to protozoan pathogens."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 61,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 506
        },
        "id": "QIwSpFYDbbze",
        "outputId": "006d0265-89b0-41ea-849e-5c6962088c3d"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x400 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "plt.figure(figsize=(10, 4))\n",
        "sns.countplot(x='otu_Family', data=df)\n",
        "plt.title('Count of OTU Families')\n",
        "plt.xlabel('OTU Family')\n",
        "plt.ylabel('Count')\n",
        "plt.xticks(rotation=45, ha='right')\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-xHLLAqM0uKW"
      },
      "source": [
        "Comparing with the next analysis of genera, families such as Hypotrichomonadea and Trichostrongylidae<br>exhibit substantial representation, indicating their significance across different taxonomic levels within the dataset<br>and potentially pointing towards their ecological importance or host associations."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 62,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 449
        },
        "id": "ZxSF2YD2WR0W",
        "outputId": "e1c78d30-582c-4c1c-d830-22ca4786958d"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "df.groupby('otu_Genus').size().plot(kind='barh')\n",
        "plt.xlabel('Number of pathogens')\n",
        "plt.gca().spines[['top', 'right',]].set_visible(False)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nPbqO8r-uxQ2"
      },
      "source": [
        "These findings suggest varying levels of prevalence and distribution among the identified genera.<br>\n",
        "Hypotrichomonas emerges as the most prevalent genus with a count of 8,<br>followed by Viannaia with 5 occurrences.<br>Tritrichomonas, Nippostrongylus, and Cryptosporidium share the next highest count at 4 each."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 63,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 814
        },
        "id": "jSJdSZ2Te0-A",
        "outputId": "f7824f2f-6a1e-4c74-f89e-d08a6b242963"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x800 with 2 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "ct = pd.crosstab(df['otu_Order'], df['otu_Family'])\n",
        "plt.figure(figsize=(10, 8))\n",
        "sns.heatmap(ct, cmap='YlGnBu', annot=True, fmt='d')\n",
        "plt.title('Heatmap of OTU Orders vs OTU Families')\n",
        "plt.xlabel('OTU Family')\n",
        "plt.ylabel('OTU Order')\n",
        "plt.xticks(rotation=45, ha='right')\n",
        "plt.yticks(rotation='horizontal')\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Lk3sIfBJ3S3l"
      },
      "source": [
        "The heatmap visualization of OTU Orders versus OTU Families illustrates several notable associations.<br>For instance, within the Parabasalia order, Hypotrichomonadea and Trichomonadea families each account for 8 and 5 occurrences respectively, indicating a significant presence of these families within this order.<br>Similarly, the Strongylida order exhibits a prominent relationship with Trichostrongylidae, with 7 instances recorded."
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}