livro_ESCD_analise_exploratoria.ipynb

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      "cell_type": "markdown",
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      "source": [
        "# Livro Engenharia de Software para Ciência de Dados (Ed. Casa do Código)\n",
        "Marcos Kalinowski, Tatiana Escovedo, Hugo Villamizar e Hélio Lopes\n",
        "\n",
        "### Exemplo Prático de Análise Exploratória de Dados em Python\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "M4VxLCqsiC9K"
      },
      "source": [
        "## Trabalhando com Pandas"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "O_sPsKXZRM15"
      },
      "source": [
        "Para exemplificar como funciona a etapa de Análise Exploratória de Dados em um dataset, iremos utilizar o pacote Pandas, focando em algumas possibilidades interessantes de análises, mas sem nenhuma pretensão de ser um tutorial exaustivo deste pacote, que é muito amplo e rico. Para conhecer mais sobre o Pandas, você pode explorar um dos diversos tutoriais oficiais, como o disponível em https://pandas.pydata.org/pandas-docs/stable/user_guide/10min.html.\n",
        "\n",
        "Iniciaremos esta prática importando o Pandas:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "g04kBFFcMnDH"
      },
      "source": [
        "# importação do Pandas\n",
        "import pandas as pd"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Agora iremos importar o dataset com que iremos utilizar a partir de um link, e armazenaremos os dados em um dataframe. Nesta prática, trabalharemos com o dataset Iris, um dos datasets mais conhecidos e utilizados em Machine Learning, criado em 1936. Este é um dataset pequeno e simples, ideal para uma primeira prática, e contém 150 instâncias (linhas), 4 variáveis numéricas (largura e comprimento da sépala e da pétala em centímetros) e 1 variável categórica (espécie da flor, podendo ser setosa, versicolor ou virginica)."
      ],
      "metadata": {
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    {
      "cell_type": "code",
      "metadata": {
        "id": "aGjVCGsWMsMR"
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      "source": [
        "# importando dados uma url para um dataframe\n",
        "\n",
        "# url a importar\n",
        "url_dados = 'https://raw.githubusercontent.com/profkalinowski/livroescd/main/iris.data'\n",
        "\n",
        "# labels dos atributos do dataset\n",
        "atributos = ['comprimento_sepala', 'largura_sepala', 'comprimento_petala', 'largura_petala', 'especie']\n",
        "\n",
        "# carga do dataset através da url - há diversos parâmetros no read_csv que podem ser interessantes, como sep, usecols e header\n",
        "iris = pd.read_csv(url_dados, names=atributos)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Inicialmente, iremos utilizar alguns comandos da biblioteca Pandas para exibir algumas estatísticas descritivas e fazer uma rápida análise exploratória do dataset. Os comentários nos blocos de código auxiliam no seu entendimento."
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        "outputId": "e84ca12f-f8fb-4b3d-87f7-521b2c362130"
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      "source": [
        "# verificando que iris é um dataframe\n",
        "type(iris)"
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      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "pandas.core.frame.DataFrame"
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      "source": [
        "# verificando os tipos de cada coluna do dataframe\n",
        "iris.dtypes"
      ],
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          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "comprimento_sepala    float64\n",
              "largura_sepala        float64\n",
              "comprimento_petala    float64\n",
              "largura_petala        float64\n",
              "especie                object\n",
              "dtype: object"
            ]
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          "execution_count": 4
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      "source": [
        "# exibindo as primeiras linhas\n",
        "iris.head()"
      ],
      "execution_count": null,
      "outputs": [
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            "text/plain": [
              "   comprimento_sepala  largura_sepala  comprimento_petala  largura_petala  \\\n",
              "0                 5.1             3.5                 1.4             0.2   \n",
              "1                 4.9             3.0                 1.4             0.2   \n",
              "2                 4.7             3.2                 1.3             0.2   \n",
              "3                 4.6             3.1                 1.5             0.2   \n",
              "4                 5.0             3.6                 1.4             0.2   \n",
              "\n",
              "       especie  \n",
              "0  Iris-setosa  \n",
              "1  Iris-setosa  \n",
              "2  Iris-setosa  \n",
              "3  Iris-setosa  \n",
              "4  Iris-setosa  "
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      "source": [
        "# exibindo as últimas linhas\n",
        "iris.tail()"
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      "execution_count": null,
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        {
          "output_type": "execute_result",
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              "     comprimento_sepala  largura_sepala  comprimento_petala  largura_petala  \\\n",
              "145                 6.7             3.0                 5.2             2.3   \n",
              "146                 6.3             2.5                 5.0             1.9   \n",
              "147                 6.5             3.0                 5.2             2.0   \n",
              "148                 6.2             3.4                 5.4             2.3   \n",
              "149                 5.9             3.0                 5.1             1.8   \n",
              "\n",
              "            especie  \n",
              "145  Iris-virginica  \n",
              "146  Iris-virginica  \n",
              "147  Iris-virginica  \n",
              "148  Iris-virginica  \n",
              "149  Iris-virginica  "
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              "                                                     [key], {});\n",
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        "id": "o1NLzANRPKjW",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "outputId": "4f35441e-b345-4ab2-d37f-fc985d944683"
      },
      "source": [
        "# exibindo as primeiras 10 linhas\n",
        "iris.head(10)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   comprimento_sepala  largura_sepala  comprimento_petala  largura_petala  \\\n",
              "0                 5.1             3.5                 1.4             0.2   \n",
              "1                 4.9             3.0                 1.4             0.2   \n",
              "2                 4.7             3.2                 1.3             0.2   \n",
              "3                 4.6             3.1                 1.5             0.2   \n",
              "4                 5.0             3.6                 1.4             0.2   \n",
              "5                 5.4             3.9                 1.7             0.4   \n",
              "6                 4.6             3.4                 1.4             0.3   \n",
              "7                 5.0             3.4                 1.5             0.2   \n",
              "8                 4.4             2.9                 1.4             0.2   \n",
              "9                 4.9             3.1                 1.5             0.1   \n",
              "\n",
              "       especie  \n",
              "0  Iris-setosa  \n",
              "1  Iris-setosa  \n",
              "2  Iris-setosa  \n",
              "3  Iris-setosa  \n",
              "4  Iris-setosa  \n",
              "5  Iris-setosa  \n",
              "6  Iris-setosa  \n",
              "7  Iris-setosa  \n",
              "8  Iris-setosa  \n",
              "9  Iris-setosa  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-5c5bc9d7-a931-4882-a6fb-fad167d30d41\">\n",
              "    <div class=\"colab-df-container\">\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>comprimento_sepala</th>\n",
              "      <th>largura_sepala</th>\n",
              "      <th>comprimento_petala</th>\n",
              "      <th>largura_petala</th>\n",
              "      <th>especie</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>5.1</td>\n",
              "      <td>3.5</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>4.9</td>\n",
              "      <td>3.0</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>4.7</td>\n",
              "      <td>3.2</td>\n",
              "      <td>1.3</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4.6</td>\n",
              "      <td>3.1</td>\n",
              "      <td>1.5</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5.0</td>\n",
              "      <td>3.6</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>5.4</td>\n",
              "      <td>3.9</td>\n",
              "      <td>1.7</td>\n",
              "      <td>0.4</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>4.6</td>\n",
              "      <td>3.4</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.3</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>5.0</td>\n",
              "      <td>3.4</td>\n",
              "      <td>1.5</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>4.4</td>\n",
              "      <td>2.9</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>4.9</td>\n",
              "      <td>3.1</td>\n",
              "      <td>1.5</td>\n",
              "      <td>0.1</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5c5bc9d7-a931-4882-a6fb-fad167d30d41')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "      </button>\n",
              "      \n",
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              "      display:flex;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-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-5c5bc9d7-a931-4882-a6fb-fad167d30d41 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-5c5bc9d7-a931-4882-a6fb-fad167d30d41');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QEj-Iz1MPR7l",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a7839f54-bc4e-452f-ceb7-dad9034ae86a"
      },
      "source": [
        "# exibindo os nomes das colunas\n",
        "iris.columns"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['comprimento_sepala', 'largura_sepala', 'comprimento_petala',\n",
              "       'largura_petala', 'especie'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "K6FWMzvCjrNT",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2f10f123-8a0f-46ed-fed1-273576f8c92e"
      },
      "source": [
        "# exibindo as dimensões do dataset\n",
        "iris.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(150, 5)"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LqrTYFAgaKHL",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6bdc99df-5e1e-452f-b0fc-16c9582b34b3"
      },
      "source": [
        "# exibindo a quantidade de linhas por coluna\n",
        "iris.count()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "comprimento_sepala    150\n",
              "largura_sepala        150\n",
              "comprimento_petala    150\n",
              "largura_petala        150\n",
              "especie               150\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yrFoAZskPfGH",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "outputId": "cdf8f0d0-6862-4cc3-e1bb-5f06f841d5c9"
      },
      "source": [
        "# exibindo um sumário estatístico\n",
        "iris.describe()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       comprimento_sepala  largura_sepala  comprimento_petala  largura_petala\n",
              "count          150.000000      150.000000          150.000000      150.000000\n",
              "mean             5.843333        3.054000            3.758667        1.198667\n",
              "std              0.828066        0.433594            1.764420        0.763161\n",
              "min              4.300000        2.000000            1.000000        0.100000\n",
              "25%              5.100000        2.800000            1.600000        0.300000\n",
              "50%              5.800000        3.000000            4.350000        1.300000\n",
              "75%              6.400000        3.300000            5.100000        1.800000\n",
              "max              7.900000        4.400000            6.900000        2.500000"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-8a8baf09-0439-4738-a7ba-f53b1eb32404\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>comprimento_sepala</th>\n",
              "      <th>largura_sepala</th>\n",
              "      <th>comprimento_petala</th>\n",
              "      <th>largura_petala</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>150.000000</td>\n",
              "      <td>150.000000</td>\n",
              "      <td>150.000000</td>\n",
              "      <td>150.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>5.843333</td>\n",
              "      <td>3.054000</td>\n",
              "      <td>3.758667</td>\n",
              "      <td>1.198667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>0.828066</td>\n",
              "      <td>0.433594</td>\n",
              "      <td>1.764420</td>\n",
              "      <td>0.763161</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>4.300000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.100000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>5.100000</td>\n",
              "      <td>2.800000</td>\n",
              "      <td>1.600000</td>\n",
              "      <td>0.300000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>5.800000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>4.350000</td>\n",
              "      <td>1.300000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>6.400000</td>\n",
              "      <td>3.300000</td>\n",
              "      <td>5.100000</td>\n",
              "      <td>1.800000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>7.900000</td>\n",
              "      <td>4.400000</td>\n",
              "      <td>6.900000</td>\n",
              "      <td>2.500000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8a8baf09-0439-4738-a7ba-f53b1eb32404')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
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              "    .colab-df-container {\n",
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              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "\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-8a8baf09-0439-4738-a7ba-f53b1eb32404 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-8a8baf09-0439-4738-a7ba-f53b1eb32404');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gd58Ne9manUL",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ff152fb8-0c24-4804-d313-671efdb969e6"
      },
      "source": [
        "# exibindo informações sobre colunas e uso de memória\n",
        "iris.info()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 150 entries, 0 to 149\n",
            "Data columns (total 5 columns):\n",
            " #   Column              Non-Null Count  Dtype  \n",
            "---  ------              --------------  -----  \n",
            " 0   comprimento_sepala  150 non-null    float64\n",
            " 1   largura_sepala      150 non-null    float64\n",
            " 2   comprimento_petala  150 non-null    float64\n",
            " 3   largura_petala      150 non-null    float64\n",
            " 4   especie             150 non-null    object \n",
            "dtypes: float64(4), object(1)\n",
            "memory usage: 6.0+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "A fim de analisarmos os nossos dados de diversos ângulos, o Pandas permite reorganizarmos um dataframe, por exemplo, ordenando-o por alguma coluna. Também podemos selecionar uma ou mais colunas e/ou linhas específicas, como mostram os exemplos a seguir. Os comentários nos blocos de código auxiliam no seu entendimento."
      ],
      "metadata": {
        "id": "k-_Xyw8yJL_j"
      }
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "t_CREFDWPt2G",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "outputId": "f40d5e3d-e084-4f25-e496-71834eae8f21"
      },
      "source": [
        "# ordenando o dataframe por uma coluna\n",
        "iris.sort_values(by='largura_sepala')\n",
        "\n",
        "# obs: este comando retorna apenas o resultado da query. Se quisermos alterar a ordenação do dataframe em si, \n",
        "# teríamos que fazer: iris = iris.sort_values(by='largura_sepala')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     comprimento_sepala  largura_sepala  comprimento_petala  largura_petala  \\\n",
              "60                  5.0             2.0                 3.5             1.0   \n",
              "62                  6.0             2.2                 4.0             1.0   \n",
              "119                 6.0             2.2                 5.0             1.5   \n",
              "68                  6.2             2.2                 4.5             1.5   \n",
              "41                  4.5             2.3                 1.3             0.3   \n",
              "..                  ...             ...                 ...             ...   \n",
              "16                  5.4             3.9                 1.3             0.4   \n",
              "14                  5.8             4.0                 1.2             0.2   \n",
              "32                  5.2             4.1                 1.5             0.1   \n",
              "33                  5.5             4.2                 1.4             0.2   \n",
              "15                  5.7             4.4                 1.5             0.4   \n",
              "\n",
              "             especie  \n",
              "60   Iris-versicolor  \n",
              "62   Iris-versicolor  \n",
              "119   Iris-virginica  \n",
              "68   Iris-versicolor  \n",
              "41       Iris-setosa  \n",
              "..               ...  \n",
              "16       Iris-setosa  \n",
              "14       Iris-setosa  \n",
              "32       Iris-setosa  \n",
              "33       Iris-setosa  \n",
              "15       Iris-setosa  \n",
              "\n",
              "[150 rows x 5 columns]"
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              "      <th>68</th>\n",
              "      <td>6.2</td>\n",
              "      <td>2.2</td>\n",
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              "      <td>1.5</td>\n",
              "      <td>Iris-versicolor</td>\n",
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              "    <tr>\n",
              "      <th>41</th>\n",
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              "      <td>Iris-setosa</td>\n",
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              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>5.4</td>\n",
              "      <td>3.9</td>\n",
              "      <td>1.3</td>\n",
              "      <td>0.4</td>\n",
              "      <td>Iris-setosa</td>\n",
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              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>5.8</td>\n",
              "      <td>4.0</td>\n",
              "      <td>1.2</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
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              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>5.2</td>\n",
              "      <td>4.1</td>\n",
              "      <td>1.5</td>\n",
              "      <td>0.1</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>5.5</td>\n",
              "      <td>4.2</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
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              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>5.7</td>\n",
              "      <td>4.4</td>\n",
              "      <td>1.5</td>\n",
              "      <td>0.4</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>150 rows × 5 columns</p>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ed4b7f05-c7bb-4e20-bf88-f58af286a3f9')\"\n",
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              "\n",
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              "          const element = document.querySelector('#df-ed4b7f05-c7bb-4e20-bf88-f58af286a3f9');\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",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VGddANmgQL8Z",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "outputId": "29ba7e45-e1cb-48fb-e5f9-52ad30ca020c"
      },
      "source": [
        "# ordenando por uma coluna de ordem descendente\n",
        "iris.sort_values(by='largura_sepala', ascending=False)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     comprimento_sepala  largura_sepala  comprimento_petala  largura_petala  \\\n",
              "15                  5.7             4.4                 1.5             0.4   \n",
              "33                  5.5             4.2                 1.4             0.2   \n",
              "32                  5.2             4.1                 1.5             0.1   \n",
              "14                  5.8             4.0                 1.2             0.2   \n",
              "16                  5.4             3.9                 1.3             0.4   \n",
              "..                  ...             ...                 ...             ...   \n",
              "87                  6.3             2.3                 4.4             1.3   \n",
              "62                  6.0             2.2                 4.0             1.0   \n",
              "68                  6.2             2.2                 4.5             1.5   \n",
              "119                 6.0             2.2                 5.0             1.5   \n",
              "60                  5.0             2.0                 3.5             1.0   \n",
              "\n",
              "             especie  \n",
              "15       Iris-setosa  \n",
              "33       Iris-setosa  \n",
              "32       Iris-setosa  \n",
              "14       Iris-setosa  \n",
              "16       Iris-setosa  \n",
              "..               ...  \n",
              "87   Iris-versicolor  \n",
              "62   Iris-versicolor  \n",
              "68   Iris-versicolor  \n",
              "119   Iris-virginica  \n",
              "60   Iris-versicolor  \n",
              "\n",
              "[150 rows x 5 columns]"
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              "    <tr>\n",
              "      <th>...</th>\n",
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              "      <td>Iris-versicolor</td>\n",
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              "    <tr>\n",
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              "      <td>6.0</td>\n",
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              "    <tr>\n",
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              "      <td>6.0</td>\n",
              "      <td>2.2</td>\n",
              "      <td>5.0</td>\n",
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              "      <td>Iris-virginica</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>60</th>\n",
              "      <td>5.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.5</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Iris-versicolor</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>150 rows × 5 columns</p>\n",
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              "\n",
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              "          const element = document.querySelector('#df-f000676e-d0db-4360-847b-177a0acd0ac0');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9-TmuHWqQXXZ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "fae26d7c-8721-4065-d958-49d310002aee"
      },
      "source": [
        "# selecionando uma coluna específica\n",
        "iris['largura_sepala']"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0      3.5\n",
              "1      3.0\n",
              "2      3.2\n",
              "3      3.1\n",
              "4      3.6\n",
              "      ... \n",
              "145    3.0\n",
              "146    2.5\n",
              "147    3.0\n",
              "148    3.4\n",
              "149    3.0\n",
              "Name: largura_sepala, Length: 150, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Jww5ZpjnQ0cG",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "outputId": "72f4b8a1-cf36-4cc8-8731-c30f7ff8c31b"
      },
      "source": [
        "# selecionando um subconjunto de linhas consecutivas\n",
        "iris[7:11]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    comprimento_sepala  largura_sepala  comprimento_petala  largura_petala  \\\n",
              "7                  5.0             3.4                 1.5             0.2   \n",
              "8                  4.4             2.9                 1.4             0.2   \n",
              "9                  4.9             3.1                 1.5             0.1   \n",
              "10                 5.4             3.7                 1.5             0.2   \n",
              "\n",
              "        especie  \n",
              "7   Iris-setosa  \n",
              "8   Iris-setosa  \n",
              "9   Iris-setosa  \n",
              "10  Iris-setosa  "
            ],
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              "\n",
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              "      <th></th>\n",
              "      <th>comprimento_sepala</th>\n",
              "      <th>largura_sepala</th>\n",
              "      <th>comprimento_petala</th>\n",
              "      <th>largura_petala</th>\n",
              "      <th>especie</th>\n",
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              "  <tbody>\n",
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              "      <th>7</th>\n",
              "      <td>5.0</td>\n",
              "      <td>3.4</td>\n",
              "      <td>1.5</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>4.4</td>\n",
              "      <td>2.9</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>4.9</td>\n",
              "      <td>3.1</td>\n",
              "      <td>1.5</td>\n",
              "      <td>0.1</td>\n",
              "      <td>Iris-setosa</td>\n",
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              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>5.4</td>\n",
              "      <td>3.7</td>\n",
              "      <td>1.5</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c86a5966-82a8-43b3-90ea-77d933eec69f')\"\n",
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              "    [theme=dark] .colab-df-convert {\n",
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              "      fill: #D2E3FC;\n",
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              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
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              "\n",
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              "          const element = document.querySelector('#df-c86a5966-82a8-43b3-90ea-77d933eec69f');\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",
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              "  </div>\n",
              "  "
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          "execution_count": 16
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    {
      "cell_type": "code",
      "metadata": {
        "id": "GaZYNKMURj9U",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "outputId": "6d60a15c-0c73-472a-bbd7-f28dae9df275"
      },
      "source": [
        "# selecionando um subconjunto de colunas para todas as linhas\n",
        "iris.loc[:, ['largura_sepala', 'largura_petala', 'especie']]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     largura_sepala  largura_petala         especie\n",
              "0               3.5             0.2     Iris-setosa\n",
              "1               3.0             0.2     Iris-setosa\n",
              "2               3.2             0.2     Iris-setosa\n",
              "3               3.1             0.2     Iris-setosa\n",
              "4               3.6             0.2     Iris-setosa\n",
              "..              ...             ...             ...\n",
              "145             3.0             2.3  Iris-virginica\n",
              "146             2.5             1.9  Iris-virginica\n",
              "147             3.0             2.0  Iris-virginica\n",
              "148             3.4             2.3  Iris-virginica\n",
              "149             3.0             1.8  Iris-virginica\n",
              "\n",
              "[150 rows x 3 columns]"
            ],
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              "\n",
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              "      <th></th>\n",
              "      <th>largura_sepala</th>\n",
              "      <th>largura_petala</th>\n",
              "      <th>especie</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>3.5</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3.0</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3.2</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3.1</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>3.6</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "      <th>145</th>\n",
              "      <td>3.0</td>\n",
              "      <td>2.3</td>\n",
              "      <td>Iris-virginica</td>\n",
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              "    <tr>\n",
              "      <th>146</th>\n",
              "      <td>2.5</td>\n",
              "      <td>1.9</td>\n",
              "      <td>Iris-virginica</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>147</th>\n",
              "      <td>3.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>Iris-virginica</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>148</th>\n",
              "      <td>3.4</td>\n",
              "      <td>2.3</td>\n",
              "      <td>Iris-virginica</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>149</th>\n",
              "      <td>3.0</td>\n",
              "      <td>1.8</td>\n",
              "      <td>Iris-virginica</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>150 rows × 3 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-96f111af-9c76-4ff2-a1a2-6f8c9b6b39a3')\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
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              "      fill: #174EA6;\n",
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              "\n",
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              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
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              "\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",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-96f111af-9c76-4ff2-a1a2-6f8c9b6b39a3 button.colab-df-convert');\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-96f111af-9c76-4ff2-a1a2-6f8c9b6b39a3');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fY5X-keFRzun",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "211bdb18-0c70-4c4a-883a-75ee0d25bcbc"
      },
      "source": [
        "# selecionando um subconjunto linhas e colunas\n",
        "iris.loc[7:11, ['largura_sepala', 'largura_petala', 'especie']]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    largura_sepala  largura_petala      especie\n",
              "7              3.4             0.2  Iris-setosa\n",
              "8              2.9             0.2  Iris-setosa\n",
              "9              3.1             0.1  Iris-setosa\n",
              "10             3.7             0.2  Iris-setosa\n",
              "11             3.4             0.2  Iris-setosa"
            ],
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              "  <thead>\n",
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              "      <th></th>\n",
              "      <th>largura_sepala</th>\n",
              "      <th>largura_petala</th>\n",
              "      <th>especie</th>\n",
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              "  <tbody>\n",
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              "      <th>7</th>\n",
              "      <td>3.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>2.9</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>3.1</td>\n",
              "      <td>0.1</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>3.7</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>3.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8228684d-9aa1-4cc3-8a04-f0c2c6be1d7b')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "        \n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
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              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      fill: #1967D2;\n",
              "      height: 32px;\n",
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              "      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",
              "    [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-8228684d-9aa1-4cc3-8a04-f0c2c6be1d7b 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-8228684d-9aa1-4cc3-8a04-f0c2c6be1d7b');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6dQixnWVS7mo",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 614
        },
        "outputId": "41fcbc35-ac46-4079-dccd-61c6da7c4923"
      },
      "source": [
        "# selecionando linhas segundo um critério\n",
        "iris[iris['largura_sepala'] > 3.5]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     comprimento_sepala  largura_sepala  comprimento_petala  largura_petala  \\\n",
              "4                   5.0             3.6                 1.4             0.2   \n",
              "5                   5.4             3.9                 1.7             0.4   \n",
              "10                  5.4             3.7                 1.5             0.2   \n",
              "14                  5.8             4.0                 1.2             0.2   \n",
              "15                  5.7             4.4                 1.5             0.4   \n",
              "16                  5.4             3.9                 1.3             0.4   \n",
              "18                  5.7             3.8                 1.7             0.3   \n",
              "19                  5.1             3.8                 1.5             0.3   \n",
              "21                  5.1             3.7                 1.5             0.4   \n",
              "22                  4.6             3.6                 1.0             0.2   \n",
              "32                  5.2             4.1                 1.5             0.1   \n",
              "33                  5.5             4.2                 1.4             0.2   \n",
              "44                  5.1             3.8                 1.9             0.4   \n",
              "46                  5.1             3.8                 1.6             0.2   \n",
              "48                  5.3             3.7                 1.5             0.2   \n",
              "109                 7.2             3.6                 6.1             2.5   \n",
              "117                 7.7             3.8                 6.7             2.2   \n",
              "131                 7.9             3.8                 6.4             2.0   \n",
              "\n",
              "            especie  \n",
              "4       Iris-setosa  \n",
              "5       Iris-setosa  \n",
              "10      Iris-setosa  \n",
              "14      Iris-setosa  \n",
              "15      Iris-setosa  \n",
              "16      Iris-setosa  \n",
              "18      Iris-setosa  \n",
              "19      Iris-setosa  \n",
              "21      Iris-setosa  \n",
              "22      Iris-setosa  \n",
              "32      Iris-setosa  \n",
              "33      Iris-setosa  \n",
              "44      Iris-setosa  \n",
              "46      Iris-setosa  \n",
              "48      Iris-setosa  \n",
              "109  Iris-virginica  \n",
              "117  Iris-virginica  \n",
              "131  Iris-virginica  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-f03c58ce-a378-4174-8ce7-2f47c5a71171\">\n",
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              "      <th>comprimento_sepala</th>\n",
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              "      <th>largura_petala</th>\n",
              "      <th>especie</th>\n",
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              "      <td>Iris-setosa</td>\n",
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              "      <th>5</th>\n",
              "      <td>5.4</td>\n",
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              "      <td>Iris-setosa</td>\n",
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              "      <th>18</th>\n",
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              "      <td>1.7</td>\n",
              "      <td>0.3</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>5.1</td>\n",
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              "      <td>1.5</td>\n",
              "      <td>0.3</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>5.1</td>\n",
              "      <td>3.7</td>\n",
              "      <td>1.5</td>\n",
              "      <td>0.4</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>4.6</td>\n",
              "      <td>3.6</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>5.2</td>\n",
              "      <td>4.1</td>\n",
              "      <td>1.5</td>\n",
              "      <td>0.1</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>5.5</td>\n",
              "      <td>4.2</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>5.1</td>\n",
              "      <td>3.8</td>\n",
              "      <td>1.9</td>\n",
              "      <td>0.4</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>5.1</td>\n",
              "      <td>3.8</td>\n",
              "      <td>1.6</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>5.3</td>\n",
              "      <td>3.7</td>\n",
              "      <td>1.5</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>109</th>\n",
              "      <td>7.2</td>\n",
              "      <td>3.6</td>\n",
              "      <td>6.1</td>\n",
              "      <td>2.5</td>\n",
              "      <td>Iris-virginica</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>117</th>\n",
              "      <td>7.7</td>\n",
              "      <td>3.8</td>\n",
              "      <td>6.7</td>\n",
              "      <td>2.2</td>\n",
              "      <td>Iris-virginica</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>131</th>\n",
              "      <td>7.9</td>\n",
              "      <td>3.8</td>\n",
              "      <td>6.4</td>\n",
              "      <td>2.0</td>\n",
              "      <td>Iris-virginica</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f03c58ce-a378-4174-8ce7-2f47c5a71171')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
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              "      flex-wrap:wrap;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      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",
              "    [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-f03c58ce-a378-4174-8ce7-2f47c5a71171 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-f03c58ce-a378-4174-8ce7-2f47c5a71171');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# exibindo a média de cada atributo, agrupado por espécie\n",
        "iris.groupby('especie').mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "iC_97MIDJVpL",
        "outputId": "0eaac66f-5e8c-4a40-b06a-0f330ce3cf9f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                 comprimento_sepala  largura_sepala  comprimento_petala  \\\n",
              "especie                                                                   \n",
              "Iris-setosa                   5.006           3.418               1.464   \n",
              "Iris-versicolor               5.936           2.770               4.260   \n",
              "Iris-virginica                6.588           2.974               5.552   \n",
              "\n",
              "                 largura_petala  \n",
              "especie                          \n",
              "Iris-setosa               0.244  \n",
              "Iris-versicolor           1.326  \n",
              "Iris-virginica            2.026  "
            ],
            "text/html": [
              "\n",
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              "      <th></th>\n",
              "      <th>comprimento_sepala</th>\n",
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              "      <th>largura_petala</th>\n",
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              "      <th>especie</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Iris-setosa</th>\n",
              "      <td>5.006</td>\n",
              "      <td>3.418</td>\n",
              "      <td>1.464</td>\n",
              "      <td>0.244</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Iris-versicolor</th>\n",
              "      <td>5.936</td>\n",
              "      <td>2.770</td>\n",
              "      <td>4.260</td>\n",
              "      <td>1.326</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Iris-virginica</th>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-85f2dedd-6ee9-49db-bad1-002313d825ef')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\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",
              "    [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-85f2dedd-6ee9-49db-bad1-002313d825ef 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-85f2dedd-6ee9-49db-bad1-002313d825ef');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Trabalhando com Matplotlib"
      ],
      "metadata": {
        "id": "VeNg9Gy6JfTq"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Agora que já exploramos um pouco os nossos dados com auxílio da Estatística Descritiva e da biblioteca Pandas, vamos examinar o dataset Iris graficamente com a biblioteca Matplotlib. O primeiro tipo de gráfico que criaremos será o gráfico conhecido como scatter plot, no qual são marcados os pontos de cruzamento entre duas variáveis. Para isso, será necessário importar o módulo pyplot do Matplotlib."
      ],
      "metadata": {
        "id": "xd6CCOBKJhbH"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# importação do pyplot\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# plotando o gráfico de comprimento x largura da sépala\n",
        "plt.scatter(iris['comprimento_sepala'], iris['largura_sepala'])\n",
        "\n",
        "# incluindo título do gráfico e rótulos dos eixos\n",
        "plt.title('Iris: comprimento x largura da sépala')\n",
        "plt.xlabel('comprimento_sepala')\n",
        "plt.ylabel('largura_sepala');"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        },
        "id": "UwAypnYmJkSa",
        "outputId": "246fc19f-b573-40e4-8541-d37209aa20db"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Se quisermos, também podemos plotar o mesmo gráfico, mas colori-lo de acordo com as espécies das flores (setosa, versicolor ou virginica). Para tal, faremos:"
      ],
      "metadata": {
        "id": "fCRtp0MuJmJM"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# criando o dicionário de cores\n",
        "cores = {'Iris-setosa':'r', 'Iris-versicolor':'g', 'Iris-virginica':'b'}\n",
        "\n",
        "# plotando cada um dos pontos de dados\n",
        "for i in range(len(iris['comprimento_sepala'])):\n",
        "    plt.scatter(iris['comprimento_sepala'][i], iris['largura_sepala'][i], color=cores[iris['especie'][i]])\n",
        "\n",
        "# incluindo título do gráfico e rótulos dos eixos\n",
        "plt.title('Iris: comprimento x largura da sépala separado por classe')\n",
        "plt.xlabel('comprimento_sepala')\n",
        "plt.ylabel('largura_sepala');"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        },
        "id": "pRc7cy9NJmRD",
        "outputId": "a0c96ee4-5f6a-4749-b6e9-d28bbfc49dde"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Também podemos separar as classes usando diferentes marcadores em vez de usar cores (o que é útil em relatórios impressos em preto e branco). Para tal, basta fazer:"
      ],
      "metadata": {
        "id": "kr8rMAtwJpcP"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# criando o dicionário de marcadores\n",
        "marcadores = {'Iris-setosa':'.', 'Iris-versicolor':'+', 'Iris-virginica':'x'}\n",
        "\n",
        "# plotando cada um dos pontos de dados\n",
        "for i in range(len(iris['comprimento_sepala'])):\n",
        "   plt.scatter(iris['comprimento_sepala'][i], iris['largura_sepala'][i], color='blue', marker=marcadores[iris['especie'][i]])\n",
        "\n",
        "# incluindo título do gráfico e rótulos dos eixos\n",
        "plt.title('Iris: comprimento x largura da sépala separado por classe')\n",
        "plt.xlabel('comprimento_sepala')\n",
        "plt.ylabel('largura_sepala');"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        },
        "id": "VRvdos2uJqyp",
        "outputId": "2dde928b-f4df-4302-bed3-32e9fd45cf0d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Vamos agora trabalhar com um tipo diferente de gráficos: o gráfico de linhas (line plot). Este tipo de gráfico é utilizado geralmente quando estamos interessados em expressar variáveis que representam passagem de tempo, ou seja, mostrar a evolução histórica, o que não é o caso deste dataset. Mas imagine que o dataset Iris esteja representado na ordem em que as amostras foram coletadas ao longo do tempo e queremos visualizar a variação dos atributos dos exemplos coletados ao longo do tempo. Neste caso, faríamos:"
      ],
      "metadata": {
        "id": "a5bpoJ1wJs6q"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Gráfico de Linhas\n",
        "\n",
        "# selecionando apenas os atributos para serem plotados em um novo dataframe, sem a classe\n",
        "atributos = iris.columns.drop(['especie'])\n",
        "\n",
        "# criando o eixo x - vai de 0 até a quantidade de linhas do dataset iris - de 0 a 149\n",
        "x_data = range(0, iris.shape[0])\n",
        "\n",
        "# plotando cada atributo\n",
        "for atributo in atributos: # esse for percorre a lista: ['comprimento_sepala', 'largura_sepala', 'comprimento_petala', 'largura_petala']\n",
        "    plt.plot(x_data, iris[atributo], label=atributo)\n",
        "    \n",
        "# incluindo título do gráfico e legenda\n",
        "plt.title('Variação dos atributos do dataset Iris')\n",
        "plt.legend();"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 281
        },
        "id": "lTZnnhgAJvmx",
        "outputId": "53c85a96-9b96-4d92-ce9c-d6f3bd256eb0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "O histograma exibe a distribuição de frequências de uma determinada variável. É possível informarmos como parâmetro (entre muitas outras possibilidades) o número de bins (colunas), que queremos exibir. O exemplo de código a seguir cria um histograma para o atributo comprimento da sépala, com 7 bins:"
      ],
      "metadata": {
        "id": "DZ3h16MlJxvl"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Histograma\n",
        "\n",
        "# plotando o histograma\n",
        "plt.hist(iris['comprimento_sepala'], bins=7, edgecolor='black', color='yellow')\n",
        "\n",
        "# incluindo título do gráfico e legenda\n",
        "plt.title('Distribuição de comprimento da sépala')\n",
        "plt.ylabel('Frequência')\n",
        "plt.xlabel('comprimento_sepala');"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        },
        "id": "zdFmjJq8JtB4",
        "outputId": "183cfd2d-9190-4ba4-a17d-489ca8d2b005"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Por sua vez, o gráfico de barras (bar plot) apresenta retângulos (barras), com uma das dimensões proporcional à quantidade a ser representada e a outra arbitrária, mas igual para todas as barras. Os exemplos a seguir ilustram gráficos de barras (o primeiro, com barras verticais, também chamado de gráfico de colunas; e o segundo, com barras horizontais) para um dataset simples, que representa a profissão dos respondentes de uma pesquisa fictícia."
      ],
      "metadata": {
        "id": "yphovObYJ08E"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Atribuindo os valores de x e y\n",
        "profissoes = ['Engenheiro', 'Médico', 'Professor', 'Vendedor', 'Administrador', 'Outros']\n",
        "quantidade = [15, 30, 25, 28, 33, 39]\n",
        "\n",
        "# Gráfico de Barras\n",
        "\n",
        "# criando o gráfico de colunas\n",
        "plt.bar(profissoes, quantidade) \n",
        "\n",
        "# incluindo título do gráfico e legenda\n",
        "plt.title(\"Profissão dos respondentes\")\n",
        "plt.xlabel(\"Profissão\")\n",
        "plt.ylabel(\"Número de respondentes\");"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "by7VZUo8J2eP",
        "outputId": "0152a6e6-306c-43ca-dc3a-9ab0c55f65fe"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        " # Gráfico de Barras Horizontal\n",
        "\n",
        "# criando o gráfico de barras\n",
        "plt.barh(profissoes, quantidade)  \n",
        "\n",
        "# incluindo título do gráfico e legenda\n",
        "plt.title(\"Profissão dos respondentes\")\n",
        "plt.xlabel(\"Número de respondentes\")\n",
        "plt.ylabel(\"Profissão\");"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        },
        "id": "jtNLXN-BJ4Rh",
        "outputId": "c52d689f-bcd2-4582-bd96-4f0d7043e5d3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Outra visualização interessante para quantidades de uma variável é o gráfico de pizza (pie plot). Vejamos este gráfico com os mesmos dados do exemplo anterior:"
      ],
      "metadata": {
        "id": "5OPfGTY7J5qE"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# criando o gráfico de pizza\n",
        "plt.pie(quantidade, labels = profissoes);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 248
        },
        "id": "LCfQ-RBjJ7XG",
        "outputId": "f2c2bb7e-12d5-44e9-8053-87efa8a52242"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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jpchn8GYkcKJvC8d9/0/BHIi+NRzu47qGVGjR0MbvNd+wcHzjfWe8r4eMcljKuNHTZp7U3QeLSExE3kj4mpbO4trs+1ER+WKSz5mXqv1bkH3cpa4LSByIftn84AxE3xUOBfoMrCqxV2JjZ5/U+ODAx2MXnOm6Hl8yh5cNqnpywtf0tFWVAqp6TtvbRKRHLV8LsgS1xSUFwMWu62gVUoZPeSk4A9EbRA52XUNP7dLCty5vumPllObbuzPAO5OuGj1tZq8+pyKyRkTuEJHXRWSpiBT7tw8Xkb+JyFsi8pCIrBWRYf59XxGRRX7L7gERCfu37xaRn4jImyKyQEQOSdjVBBGZJyKrEltnInKbiLwqIktE5I6E23f7/04Skbki8gzwtoj0E5FH/FoXi0iX68ZakB1oEjDIdRFtFe3lk3c9FBt5yxOx2ZEWbXRdT0diXcwQko1UqX+g5ZK5JzY+WLJYxxzvup52jMR7X3ZHYZtDyysS7tuiqqcA97P/0qIfArNUdSzwV+BIABEpAa4AxqvqyUAMmOI/pz+wQFVPAuYANybs4zDgXOASYLq/rYuAMcAZwMnAqSLS3pntU4BvqepxQBmgqhoFrgKqRDqffMHWuj+Q88PKjgj0PesdnXjqXbE1910a2ragJJSK4TCpJdJvZ0jqB8U1EAPIV8ZHzru66fYxmxh8nutauvBZundxdoMfPO15wv/3n0DrdEHnAp8HUNXnRKR13YULgFOBV0UEoBDY5N/XBNQkbOtTCft4Sr0heG8ntNQu8r8W+z8PwAu2OW3qW6T60VHHufiz5qrqchFZCxwHLOnohVuQHeizrgvoSkGc0bc8FR9dNzf+yo+uDh+XbQPRPwxHtg2KN2d1kDVpeO13msu2zIyf9bE+mix1Cb2/QLa1JR+j68+9AFWq+r127mvW/Reftt1W4tGCJPz7U1V9oIt99upiaju09NUWl5xECgaIZ8qorYx/4L5Ynyn/iM0hi65qXh+J7HRdQ0dUaXo2dsZL0caHD5kZP+tU1/Uk4djR02Yel4btvgJ8GT46BBzs3/4i8EURGeHfN0REevrZeB64XsQbiicih7dutxNz8Q9lReQ4vEPeTscnW4tsv6w9rOyIQNFlC3TChYtjy35yRbhg5eHivI9nXUFkL1m4WN5WHbj46qbbD35Hj5zkupYeughY0cVjCkXkjYSfn1PVzi7BuAN4XES+CswHPgB2qeoWEfk+8IKIhPBGGZQBa5MtWlVf8Pvc5vuHqbvxro/b1MnTfgPcLyJLgRbgWtXO+4ZtiJKvtrjkVeA013X0VOtA9Du/EDqtsY/0d1XH1fW7Zn9v2/asWUE7rrLlzpYvv3N/7LJ0j41Mt2fWTJ+c0ul9RKQvEFPVFhE5G7i/kz62rGZBBtQWl4wE6sjgsKR0iQkbHvqXUN2Lnwx1ttBF2kzcu3f2rz/c4jzIVNElevTLX2uaFq1nQGAvC0lQDwxeM31yyj6wIjIG+DNeF1MT8A1VfTVV288kO7T0TCQHQgwgrIy8+bn4yMvnxRfd4WAg+ofhSDiT+2tPg/Z596bmW/bNjZ+Y7Wcjk1EEHA8sT9UGVfVd2ixxGFTW2e/JuTm0hjsaiL4tHHK22EriAO+58RMzOcA7U5y0soPAgswz1nUB6eBiIPquUMhJ/1wWDPDOBAuyDuTqf3iycjLIWvkD0XXlYfG5P70iHN1dmL6hRI0ig7t+VOq0aGjjD1quff+PsQuzZWxkOlmQdSDvO/tri0sK8U4J50XrNC5sfnxiaMXTZ4fScxZPtWXJmnVhSXOfoyqxefGxL9/UfMupWTY2Mp2agIFrpk9ucl1ItsmLD28Xismj30PaB6KLRLaHQttSvt0EWTzAO9364L1fTRt58wHuRE4fVnakdSD6d56MvZTqgegbI5HtXT8qed4A78lzsniAdyYc67qAbGRBlqdBBt5A9LOX66Squ2IbU7ki+vpIeFeqttVqZXzkvLMaf93405YpPVnBO5dYkLXDOvvzOMhapXog+rqCggZSNE4pgAO80+0Y1wVko3z+y9Yq74OsVcJA9Lm9GYheFwk397YWVZqei50exAHe6WYtsnbkdYustrjkIOAo13VkE38g+nkXLo4t+/GV4T7vjZSkZ13YEOnd2yoHBninkwVZO/I6yIDR5MjQpFTr38i4/6qKtSwZLbN/keRA9E2Rnl2QGlfZ8ouWL7/zm+AP8E6nka4LyEadHlqKyD9E5F/a3PZtEbm/Nzv15xAflsTjrxWRX/dmnx3IhcHEaSMQOWmNTnz0l7H60je6vyL69nC4MJn9qKJL4kfNPaWxMmwh1qXI6Gkzs246dte66iN7HLiyzW1X+rdnrSRWYsnqmUyzRVgZOfX/4mfOmNGyaMQOXd/V43eLDOzuthu04N2vNU9bdmnTT87bwcCMjgoIsCGuC8g2XQXZX4HJItIHQERG4zVtC0Vkvr8qy18SZn/saLWWoSLyQutqLSQcznWyWst1IrJCRBYB4xMeP1pEZvkrsrwoIq0LJjwqIpUishD4eTdfvwVZEloHot/0f50PRG/qxjAlVfZWt0yaPa7xd7k6wDudLMja6DTIVHUbsAj4tH/TlcALwO3Ahf6qLK8BtyQ8raPVWl72V2t5ki5WaxGRw/BmrxyPtxDBCQnbvw9vPvETgT8A9ybcNwo4R1UT6+mMBVmSBPpf+MZHA9GXtfcYhSEt3sye7dqgQxZNbPrVtn9vuWliDg/wTicLsja6c/lF4uHllcA6vGB5xZ9W9xoOnOs+cbWW0f73E4D/BlDVmUB7q7W84f98NHAm8JKqblbVJqA6YftnA3/0v/89XtC1+ouqxrrxmlpZkPWQPxB97E+qWub0b9D6A+4UCW0Nh7e2fU6Lhjbe3nz9wnMaf+16Be+gs0PwNroTZE8DF4jIKcBBwOvA3xJWMz5BVW9IeHxPVmtp3dbxqlqR5GtIlOxKLEl1SpsDCciYDUx4+J5Y06ULDlwRfWMkvKP1+8QVvP+QH7NUpJuzqcyzVZdBpqq7gX8Av8NrnS0AxovIsQAi0t9f6aQzc4Cr/cd/mq5Xa1kITPT71gqALyVsax77W4hT8FZc6Sk7rEmBkDL8K/+Ij3/wnpbXWwei10UiuyCvB3ink/NZeLNNdz/Ij+P1bV2pqptF5Fq81Vf6+vd/n85XeGldreUtvCB6H0BV325vtRZVXSAiFXgru+wAEleG+SbwiIjcBmwGruvma2iPBVkKFe3llLseijUuKJaX1o3v2/LblvPn/LTlqnPzfGxkOliQtZHX85HVFpfcyf4TEiYF4hJpfPfYyxeuGbh9T0tslR1GpkGzFHz3e3968mHXdWSTfG+R2F+2FIlLqGX16Mnz1x75qWOQ8AQa5s2V2Co7u5YGfbTXQ1lzTr4HmeklReLvH3HB/FVHfXaUhiIfrVoUCo8YmMzpY5OUjC0mExT5HmQfu0TAdN+Gw85ZuOLYLw2Jh/t8bFiRhId1ewiaSZoFWRv5HmQfuC4giD4cfsrry4+/um8sUthhH5iEBh2G94HL9/dYOux0XUC2yfc3mQVZErYOLln6dsm1seY+A07p6rEioTCE3of4kZmoLc986LqAbGNBZrpUP+iod5adcMPOxn6DT0/qidJvC7rXgiz1LMjayPcgszdEJ3b3H7l66dgbP2goHH4WIknP2yahgXs0tjcdpeU7e9+2YUEGik2ueICGfsPqlo79+prdA0adjUiPZ9CV8NC4xuwzl2L15dU1+1wXkW3yOshKltc21xaXbAOGuq4lGzT2Kdq07ITra+uLjjkbkV4P6g6FhxfEU1GYSWR/GdqR10Hm+4A8D7LmSP/tb5d87c2tQ8aegcjEVG1XwiNsdpHUsyBrhwWZF2R5uZJSS7jvruXHXf36phGnnozIpFRvPxQeckiqt2ksyNpjQZaHZy5joci+d4/94sINh40fh4RS1gJrS0L9hwG7AZv1InXecV1ANrIggw2uC8iUuISaVx116fz3j7hgTDoD7ECRjdAyJjP7ygtvui4gG1mQHThFUE5SJL72yE/NXz168hEaikzI6M5DhduJ78roLnOcBVk7LMi8+dFyVt3I8xasPObyYe2Nh8yEUKhoX9yCLFX2AitdF5GN8j7ISpbXrqktLtkIHOa6llT6cMSpry0/7uqDYpF+Z7msQ8LDlJY6lyXkkmXl1TV2RUs78j7IfPOBy10XkQpbh5yw5K2Sa7WloP9prmsBkPAIWxchdeywsgMWZJ55BDzIdgw6unbZ2Bv2NPU9OCsCrFUoPNwmV0wdC7IOWJB55rsuoKd29T/8vWXjbtzc0G/YmT0ZD5luEh6cU4fsji12XUC2siDz/BNvGbu+XT0wW+wtHL5u6dgb1+7pP/IcRI5xXU9HRPr0x1skZrjrWgJuJ95i2aYdFmRAyfLaxtriktfxFv/Navv6HvzBshNuWLFz0FFnI3KE63q6p88maLIg651Z5dU1NjNsByzI9ptPFgdZU0H/bW+XXLt02+CSMxDJ7LVgvSSh/vUab3JdRtA977qAbGZBtt884BbXRbTVEu63s/b4Ka9vHv7JU1M5oDuTJDy4SePbXZcRdBZknbAg2+8VsmhusliooGHFmC8v2njo2dF0DOjOJAkPD9O8ynUZQfZueXXNatdFZDMLMl/J8toPaotL5gJOD9viEm567+jLFqwbdf7xmRsPmV6h8IgBtjRcr1hrrAsWZAf6PY6CTJHYmk9cPH/NJz49WkPhQPWBdcWWhus1C7IuWJAd6M/AfUC/TO1QQesOn7hg5TGfP0RDBedmar+ZJKGiw4AYtrJ7T+wEXnRdRLazIEtQsrx2Z21xydPAFZnY38ZDznj1neOuHBgP983as6WpIBKKQKgO4r2ePjsP/bm8uqbBdRHZzoLs4x4jzUG2eWj0jdrir4VaCg5Kbnm1IJO+m9EGC7LkPeK6gCCwIPu45/GmE075NM3bi459+62xN+xr6jOoywVuc42EBu7WmDUskrSivLomp6eZShULsjZKltfGaotLHge+napt7hpwxMqlY7++dV/hsDNTtc2gkfCQmMY2uS4jaB51XUBQWJC17zFSEGR7Cg9Zu2zcjev3HHToWYgcm4K6AisUHtEnznLXZQRJHO99aLrBgqwdJctrF9cWlywFoj15fkPfIRuXjb1h5a6BnzgbkU+kuLxAkvDwQa5rCJi/l1fXrHddRFBYkHXs98DPk3lCU8HALW+dcN1b2w8+7kxEzktTXYEUCg+1peGS81vXBQSJBVnHqoA7gC5nOG0OF9bXFn/1jS3DTgzseMh0k9CA4Xhzzh/kupYAWA486bqIIAm5LiBblSyv3UQXfxVjoT573y7+6uy5596pW4afNBERW7+xU+G8WXqvl35qc/Mnx1pknfsZcDNtrvSPS7hp5TGfX1B3+MSSXBkPmRFSuA3d7bqKbLcK+KPrIoLGWmSdKFleuxF4qPVnRWKrRk9+efZ5v9pcN+r8CUjIJgtMgoSL9rmuIQB+ZhMoJs9aZF2brvD1daNKF7939GWHaiiSk+MhMyEUHqaxFjsR14n12LVjPWJB1oWS5bXrH7z+qbub+gya5rqWoJPwiIwNxg+oO8ura2wq3R6wQ8tuaOoz6FeAde70Uig8bLDrGrLYeuySix6zIOuGssrSTcAvXdcRdBIeYkvDdazcZrnoOQuy7rsTqHNdRJCJ9B0IbHVdRxZ6sby6ptp1EUFmQdZNZZWlu4H/57qO4Cv40HUFWaYZ+KbrIoLOgiwJZZWlTwL/67qOIJNQ/3rXNWSZu8ura2pdFxF0FmTJ+zdgj+sigkrCgxtd15BF1gM/cl1ELrAgS1JZZen7wA9d1xFUEh5u8/bvV15eXWNnw1PAgqxn7gHecF1EEIXCw/u7riFLPG0d/KljQdYDZZWlLcBXATtdniQJDx/quoYsUAdc77qIXGJB1kNllaXLSOF02PlCQkUj8WY/zVdxYEp5dc0214XkEguyXiirLP0t3lqYpptEwgUgG13X4dCPy6tr5rguItdYkPXeTcBq10UEivTd4roER17GzlKmhQVZL5VVltYDV+Fd2Gi6QUIDd7muwYHteIeUMdeF5CILshQoqyxdCHzHdR1BIaEh+TbflhUQjaoAAAmuSURBVALXlVfXvO+6kFxlQZYiZZWlM4B7XdcRBKHI8D6ua8iw75VX1zztuohcZkGWWt8BnnFdRLaT8IiBrmvIoIfKq2t+5rqIXGdBlkJllaVx4Grgdde1ZLNQeOgI1zVkyN+Bb7guIh9YkKVYWWXpHuCz2JQ/HZMBI8j9i4n/CVxeXl1jJ4EywIIsDcoqSzcAFwObXdeSjUREcnxpuJXAZ8qra7o8Oysio0TkaRF5V0TeE5F7RKTTPkQR+Y+UVZojLMjSpKyy9C2gFAuz9klhrl7Z/j7wL+XVNZu6eqAX6DwBPKWqY4DjgAHAT7p4artBJp68/Ezn5YvOFH8Yk4VZOyQ0KBcPLd8FziuvrlnVzceXAvtU9REAVY3hnTC6XkS+ISK/bn2giNSIyCQRmQ4UisgbIvIHERktIu+IyGPAMuAIEblTRJaJyFIRucJ//mEiMsd/3jIROS+VL9w1C7I0szBrXyg8VF3XkGLLgAlJXis2Fq8v7SOquhOvVdfuCmeqOg1oUNWTVXWKf/MY4DeqOhY4DTgZOAm4ELhTRA7DOwn1vKq23pdTs7dYkGWAhdnHSWREX9c1pNCrwMTy6poPHO1/raou8L8/F3hcVWOq+iEwGzjdr/E6EakAoqqaU6MrLMgyxA+zs4EVrmvJBqHw8FxZGm4OcEEPZ7N4Gzg18QYRGQQcCezgwM9nZ2uCdjljsarOASbgLwIsIl9LutosZkGWQWWVpe/hhdls17W4JqGcWBruOeDi7pyd7MCLwEGtoSIiYeAuvNXGVwEni0hIRI4Azkh4XrOIFHSwzbnAFSISFpHheOG1SEQ+AXyoqg8CDwGn9LDmrGRBlmFllaXbgIuA37uuxSUJ9RuEN5A6qH4BXNKbtShVVYHPA18SkXfxWuv78M5KvoI3q8rbeEPfEi+y/i2wRET+0M5mnwSWAG8Cs4DvquoHwCTgTRFZDFyBN8txzhDvd2lcmDF11g+BCtd1uLJv+3210Fziuo4k7QFusGmqs4u1yBwqqyy9A/gikJdLpEnooB2ua0jSSuAsC7HsY0HmWFll6f/gnS5f0NVjc42EBje5riEJM4HTy6trlrkuxHycBVkWKKssXQOcB/wMb+6qvCDhYeK6hm6I4R3+f7a8uiZoLci8YX1kWWbG1FkXAY8Bh7iuJd1iTctfa97z7Gmu6+jEEuD68uqaf3b5SOOUtciyTFll6QtAFGjvjFROkfCwYa5r6EAT3iLMp1mIBYO1yLLYjKmzLgTuB451XUs6qMaaGnfcEyG7/qC+itcKs76wAMmmN5Bpo6yy9O94rbMf47UScopIuA/Ih67r8DUA3wXOthALHmuRBcSMqbOKgV8DF7iuJZX27fjNEnTfiQ5LiAFVQEV5dc06h3WYXrAgCxj/ZMB04JOua0mFxp2PvayxLec62v2TwO3l1TW1jvZvUsSCLIBmTJ0lwJfxOqSDdmX8AZp217wUb14xKcO7fQmYVl5dszDD+zVpYkEWYDOmzgrhjZu7HW9uq8BpaVj4csu+VzLVIpsH/Ki8uub5DO3PZIgFWY6YMXXWBcA38RY+CcxJnFjzqiXNu59KZx/ZPuBx4L7y6prFadyPcciCLMfMmDrrKLwlyG4Asn7OL43v3NhY/1A6pvRZg3fpysPl1TVb07B9k0Wy9i+3iHxORFREiju4/yUR6fZV4SJymoh0uRK4iMzr4v5er2Djz71e09vttKessnR1WWXpbcAo4DrgBaAlHftKCRl4KNCYoq01Ac8CnwOOKa+u+bmFWH7I2haZiFQDI4FZqvrDdu5/CbhVVV/LcF27VXVAO7cL3u8z3o1tTMKr/ZJu7jOiqj0OoxlTZw0DvoDXnzaRLPsDtm/7PashdlQPn74Hb4LDJ4Ca8uqanamrzARFVgaZiAwA3gHOB/5XVY8XkULgEbyFE5bjhVyZqr4mIrvxDiM+A2zEm5ju53hTBn9bVZ9JDA9/3vIjgaP9f+9W1Xv9fe9W1QH+gg3VwCC8hSD+FZgM3AYsBd7C62R/HliIN2XxZ4BpeHOkFwJ/bQ1hEbkYuBvYC7wMHO3XMgT4nV/LXuAmVV3i13iMf/v7qnpVKn63M6bOOhS4HG9yx4nAwanYbm/s2/HAa+ieZMZc7gBq8MLrud5MbmhyQ7srtWSBy4DnVHWFiGwVkVPxPnR7VbVERE7kwBkz++O13G4TkSfxroT/FHAC3sWOz7Szj2K8oBwIvCMi96tq4qrQravO/MSfgvggVZ0rIv/mr0SDiIzGW8HmmtbFH0TkdlXd5j/nRb/WFcCDeAuQrMQLyFZ3AItV9XMiUoo3YPxk/74TgHNVNWUf1LLK0g+A3wC/8c96nuL/HkrxZuDon6p9dZeEBu3VWKfTzq8F5uOddZwPvFFeXZO9h8sm47I1yK5i/1S8f/J/PhZvyl/8FsuShMc34R1egNdaalTVZhFZCozuYB8zVbURaBSRTXizTdQl3P8q8Dt/bvSnVLWj5bMSV7AB+LKI3IT3uz0ML4xCwGpVfRdARP4buMl//Ll4h32o6iwRGeovQAHwTCpDrK2yytI48Jr/deeMqbMK8C7jiAIn+v9G8Vq/aRMKD9VYbGPrj5vwWuOL8IOrvLpmY0fPNQayMMj8Q61SICoiCoTx5ujq7NR5s+4/Ro7jdx6ralxEOnqNiR3MMdr8LlR1johMwDucfFREfqmqj7WznY+aEiJyFHArcLqqbheRR+l89ZuudLk6TiqVVZY24613eEBoz5g6ayhewI3CC+eRCf+OxDs72ifhq20fXCOwC9iZ8O8OvPUb3w8VHLki1rTsVmCF9XGZnsi6IMOb+vn3qnpz6w0iMhtvIdOrgVkiMg6vxZA2/qozdar6oIj0xTsEewx/BZs2h6GtBuGFT72IHAJ8Gu8q8uXAaBE5RlXfw2thtpoLTAH+0+/H26KqO71zB9mhrLJ0K96yZ90yY+qsMF6gFQANfkB2ohTvihFjeiYbg+wqvJlSE/0P3tjCQhGpBWpps0JzGkwCbhORZmA30LoOYOsKNq/jdfZ/RFVbV6lZDqzDWwkHVd3nH27OFJG9eOE10H9aBd4h7BK8zv5r0vmiMqGssjSGN5uEdcKbjMjKs5bGGJOMrLqeyBhjesKCzBgTeBZkxpjAsyAzxgSeBZkxJvAsyIwxgWdBZowJPAsyY0zgWZAZYwLPgswYE3gWZMaYwLMgM8YEngWZMSbwLMiMMYFnQWaMCTwLMmNM4FmQGWMCz4LMGBN4FmTGmMCzIDPGBJ4FmTEm8CzIjDGBZ0FmjAk8CzJjTOBZkBljAs+CzBgTeP8fdrUu3ntffB4AAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Para finalizar os exemplos da biblioteca Matplotlib, vamos plotar, em uma única figura, quatro histogramas do dataset Iris, um para cada atributo:"
      ],
      "metadata": {
        "id": "P6ZIwsR6J82L"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# configurando um grupo de subplots em um grid de 1 linha e 2 colunas\n",
        "# e também o tamanho da figura\n",
        "fig, ax = plt.subplots(2,2, figsize = (8, 8))\n",
        "\n",
        "# subplot1: histograma do comprimento_sepala\n",
        "ax[0,0].hist(iris['comprimento_sepala'], bins=7, edgecolor='black')\n",
        "ax[0,0].set_title(\"comprimento_sepala\")\n",
        "\n",
        "# subplot2: histograma da largura_sepala\n",
        "ax[0,1].hist(iris['largura_sepala'], bins=7, edgecolor='black')\n",
        "ax[0,1].set_title(\"largura_sepala\")\n",
        "\n",
        "# subplot3: histograma do comprimento_petala\n",
        "ax[1,0].hist(iris['comprimento_petala'], bins=7, edgecolor='black')\n",
        "ax[1,0].set_title(\"comprimento_petala\")\n",
        "\n",
        "# subplot4: histograma da largura_petala\n",
        "ax[1,1].hist(iris['largura_petala'], bins=7, edgecolor='black');\n",
        "ax[1,1].set_title(\"largura_petala\");"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 499
        },
        "id": "glpfc3TiJ-O8",
        "outputId": "45b74b01-a98d-4230-fdfc-9354dbd55bf9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 576x576 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Poderíamos fazer o mesmo do exemplo anterior, substituindo os histogramas por boxplots:"
      ],
      "metadata": {
        "id": "_0FF0alyKAzl"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# configurando um grupo de subplots em um grid de 1 linha e 2 colunas\n",
        "# e também o tamanho da figura\n",
        "fig, ax = plt.subplots(2,2, figsize = (8, 8))\n",
        "\n",
        "# subplot1: boxplot do comprimento_sepala\n",
        "ax[0,0].boxplot(iris['comprimento_sepala'])\n",
        "ax[0,0].set_title(\"comprimento_sepala\")\n",
        "\n",
        "# subplot2: boxplot da largura_sepala\n",
        "ax[0,1].boxplot(iris['largura_sepala'])\n",
        "ax[0,1].set_title(\"largura_sepala\")\n",
        "\n",
        "# subplot3: boxplot do comprimento_petala\n",
        "ax[1,0].boxplot(iris['comprimento_petala'])\n",
        "ax[1,0].set_title(\"comprimento_petala\")\n",
        "\n",
        "# subplot4: boxplot da largura_petala\n",
        "ax[1,1].boxplot(iris['largura_petala']);\n",
        "ax[1,1].set_title(\"largura_petala\");"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 499
        },
        "id": "cnbHSQfvKClK",
        "outputId": "f7459ba0-4165-4241-f5ed-985ee8a20ad6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 576x576 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "É importante ressaltar que a biblioteca Matplotlib é muito extensa e seus gráficos são altamente configuráveis. Aqui procuramos trazer apenas exemplos simples para facilitar o entendimento dos códigos. Entretanto, praticamente tudo pode ser customizado, desde configurações mais simples como cores, tamanhos ou exibição de labels, e até outras personalizações mais avançadas. Recomendamos que você procure estas opções na documentação oficial de acordo com a sua necessidade de uso."
      ],
      "metadata": {
        "id": "AcGsgUPRKGiF"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Trabalhando com Seaborn"
      ],
      "metadata": {
        "id": "dSWUcwoqKIHp"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Vamos agora explorar outra biblioteca para gráficos em Python: o pacote Seaborn. Todos os exemplos a seguir também utilizarão o dataset Iris, que já carregamos previamente. Você notará que os três primeiros exemplos de gráficos com Seaborn produzem o mesmo resultado de alguns gráficos que criamos com Matplotlib. Vamos começar importando a biblioteca:"
      ],
      "metadata": {
        "id": "SBhHN2wXKK_B"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# importação do seaborn\n",
        "import seaborn as sns"
      ],
      "metadata": {
        "id": "BJqJFmO6KUXm"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Agora vamos plotar um scatter plot simples, em seguida o mesmo colorido por espécies e um gráfico de linhas com os atributos do dataset Iris. Repare que são necessárias bem menos linhas de código em comparação com o Matplotlib:"
      ],
      "metadata": {
        "id": "dhwlj5SfKXqb"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# scatter plot com Seaborn\n",
        "sns.scatterplot(x='comprimento_sepala', y='largura_sepala', data=iris);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 283
        },
        "id": "nVO3svEpKZol",
        "outputId": "834aaf74-bb19-490e-ebf8-115eb50fe165"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# scatter plot com Seaborn colorido por classes\n",
        "sns.scatterplot(x='comprimento_sepala', y='largura_sepala', hue='especie', data=iris);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 283
        },
        "id": "CFZfAi5CKqSz",
        "outputId": "de9c40c9-56cc-4104-94fe-fd3e19e86061"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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6G7yPYgCn080r6+u59T9bsbvc6KMEty2fy3mLJhITrZmMNtd1c+PLm6hq6Qdg4aQUfv/dIubmJQNarqNVZXXc/sY2XG6JUa/jrz9YyEmzw7s/W1HfzSVPldHWr6XJ/uERk/jlKTNIjzcM01OhUIwEwxqVpZQfH+hvmL5SStk/cKgf+Bt/yZPGEVsae7jtdU0ZADhckjve2MbWxh7PNW9sbvQoA4D1td18UtXmOd7Z2s+tr2/F5dY+KqvDzQ3/2kR9lzlscppsTu56a7tHGQA891UtFfU9B+ilUChGkhEPTBNCRAkhNgKtwHtSyq8CXHauEGLzwPgB/caEEFcIIcqEEGVtbW2BLlEArX02bE63T5vN6aal16q9drgo39vl129Dbbd3jF6rXyxDt9lBp8keNjl7LA7W1/rL0dRtDdt7KBSK0BjxwDQppUtKWQJMAJYIIYqGXPIGUCClLAbeA57ezziPSSlLpZSlmZmZIYh9eJGbbCQuJsqnLVYf5TF0G/RRHDU1w6/fEYPKZ+alxBI1pIpOZoKBzMTwbeWkxsVwdAA5JqaNvkFeoThciVhgmpSyG1gDnDakvUNKuW/f4HFgUQgyKYYwNy+Ju8+ZR+KAcTbBEM1d5xRRlJfkuea0omyWFKR6jr81O4tjpnuV7NSsBO75XjFGvfb1SInTc/8FJWGNZYiNieLGU2dSmKEZs3UCfnHiNOblq+RkCsVoEYpLh09gGppX0AED04QQmYBDStkthIgFTgb+OOSaXCll08DhcrRYB8VBotPpWF6Sz9TMBJp7reQkGz3G4n0U5afwwIUL2NnaT5ROMDMrkfRBT//6KB1nlWgFbzpNdnKSjSNS6Wx2bhIvXXkUtZ1m4mKimJIRj0EfNXxHhUIxIoxoYJoQohhtCygKbTXykpTyDiHEHUCZlPJ1IcRdaIrACXQCP5NSbj+QLGM5ME2hUCjGKmGvmCaESEJzIOr7psIdLGNZIZjsTlp7bcTHRB102uu2XivNvVZS42KYkHZwT+ZN3Wba++2kJ8SQl+I/hsstaegyo9MJ8lNiA8YYdPTb6LU4yEgwkBirPyg5atr76bO6yE81kjae3UmlhJ46kG5Ingi60FcyLreLJlMTQgjy4vMCznmXtYteey9pxjQSYyKb9kRx6BO2SGUhRCmaYTlx4LgHuERKWf6NpTxE2Nnax8rVlXxc1UZOkpGV3y1i2czMkGoVf13TyZ2rt7GxvodJaXH87szZnDgrC50u+DE+39XO7W9spaqln+lZCdz6nTk+NoKWXitPfbGHJz6tIUonuObEaVywZKLPDfvL3e3c8loFNe1mFk1K5Y7vzvXbejoQNruTdytb+cOblTT1WDmyMI2bT5tFyaTU4TuPNcydsP4Z+PiP4HbCkT+DI34GSblBD9FqbuWFyhd4ZtszROuiuaL4Cs6dfi6pRu98rGtax+1f3k5tXy3zM+ez4ogVzE6fPRL/kUIRkFCMyv8Afi6lLJBSFgD/g6YgFGh+9b9/YxsfD/jzN/daufK5cnY0B7+Qqu8ycfMrFWwc8MWv7TRz9Ysb2NwQvG9+VXMf1/5zgyfOYGdrP9f+c6OPHB9ub+Hhj6qxu9xYHC7+750drK3u9JyvbuvnkqfKqGnX4g7Ka7v4xYsb6BwUMzAcm+p7uG7VRpp6NDfStdWd3PVWJR19wY8xZqj5DN6/FRxmcNnh8/uh6q2Qhvik/hOe2PIEDrcDi9PC/evv5+vmrz3na3pquPrDq6ntqwVgU9smfv3Jr+m0dO5vSIUi7ISiEFxSyk/3HUgpP0Pb91egPXV/srPdp83lllS3B5+ffW+Hhd1t/T5tVoebPSEUt9nbaaK93zdeoMNkZ2+HNobT5ebl8ga/fm9vafK83tthxuJw+Zzf3WaiodsStBy72/s9gW37+GpPF3VhDG6LGDv+69+24TlNOQSB0+3kP7v+49f+wd4PPK/r+uqwOH3nd0/vHppMTUO7KRQjRigK4WMhxKNCiGVCiOOFEH8DPhJCLBRCLBwpAccL8YbogH76qSHUMk4y6okN4GWTGh/8GClxMQwJIUAnNNdRgOgoHXMHuaDuY2aOt23ftYMx6nUh5RkKVMM5IyGGROM4zFWUGWDbJnc+6IKzq0Tropmd5j/G9NTpntdJBv/PxBhlJEGvMswrIkcoCmE+MAO4FbgNmA0sAP7MN8t3dEiQnWRk5VlFDLYTnlaUzazc4A2Dc/MSufHUGT5t5y7MZ04IY8zOTuRnx0/1abviuEJmD7rhn794os9NPyfZwClzvHmKpmclcPFRBT5j/PbMOUxOjw9ajrl5SZw4y2u3EAJu+fYspmaNQ0PpzG9DUr73ODYVFl0MIST7O2fGOSQbvDaY7LhsTph0gud4avJUfjDrBz59blp8ExOTVMEXReQI2ctoLDBWvYwcLjfbm3rZ024iNS6G2XlJZCSE5lnTbbGxua6H2k4LGQkGivOTyAsxBqCtz0ZFfTeNPVZyk40U5yeTOcTjqbqtnx3N3mynQ2/23WY7lU29tPbZmJQWx6ycRGJDTKe9t8PEloYeuswOpmTEUzIxhfjxms20qwaat4B0QdYcyJg+bJeh1PTUsLNrJzqdjhmpM/yqe/XYetjRuYM2SxsTEiYwM22mKhivCCthczsVQmQDfwDypJTfFkLMAZZKKZ8Ij6jBM1YVgkKhUIxlhlMIoWwZPQW8A+QNHFcB1x28aIqRxjrEMDwUu8uFY0giPMXoIt1urLZRC/Hx4HA6MNlVwfrDjVDW7xlSypeEELcASCmdQogD33EUo0J1Wz+vbWjgw+2tnDAzi3MW5lOY6TVOmmxOvqzu4IlPq4mJ1nHZsYUsKUhTaSNGmV3NG3lt938o69zGyblLOW3yKUzInBNxOdY2ruWlqpdoMjVxesHpHDfxOCYnTY64HIrIE4pCMAkh0hmoZyCEOBJQyevHGJ0mO9e/tImNdVo6662NvXxS1caTP11M+oA946vqDi572rvl9nFVOy9efiRLp6aPiswKaO7cxTWf/Zp6UyMA2zq3sbmzkruOuYv4uLRheoeP9S3r+cWaX3hcYLe0b6HH3sPVC1T9qsOBULaMrgdeB6YKIT5HS399zYhIpTho9rT3e5TBPjY39LBnIB7C5ZY8/cVev36vb/KPTVBEjuqunR5lsI81TV9Q370ronJUdVX5xUO8uP1FqruHLX2iOAQIeoUgpVwvhDgemAkIYIeU0jFikikOiuj9pLiIHghOEEBsjP81geIfFJEjWuf/UxQIdCKyn0sgOfQ6PVEHkbtJMf4IpWLaeWg1EbYC3wVWqYC0sceUjHifmALQ6h3ssyHodIKfHFXgE7ymjxKcWZyHYvSYmjaD4tRZPm3nTTmDSWkz9tNjZJiVOos0o+8W1aXzLlU2hMOEUNxON0spi4UQx6Clv74H+J2U8oiRFDAQyu30wDR2W/hsVzvr9nSyZEoaR0/NID/VW9zG4XKzsbabt7c2ExOl45S52cyfkIJuaIizIqLUtW3li6Yv2dK5nSOzS1mcvZistKnDdwwzG1o38Gn9pzT2N3L8hONZnLOYjDj/6naK8Uc44xA2SCkXDNQvqJBSvrCvLVzCBotSCAqFQhE64YxDaBBCPAqcD7wphDCE2F+hUCgUY5hQ3E6/j1YP+Z6Bkpi5wE37TgohUqWUXeEWMFLYHC421/ewqb6btPgYFk5KpSAj+Nw9oPn3b6rrZktjD7nJRhZMTPUrcLOhtouNtd30252UTExhyeRUDCGmhBiO9j4bG+u72dXSz7SsBEomppARIPGeYgBzFzSUQ+tWSC2A/MWQPPZsKk6HjW0tZVS0VxAXHcf8zGIKs0t8rmnsa2Rz+2aaTc3MSpvFvMx5xOtD+x4Ph9lhpqK9gsqOSrLjsynOLCY/Id/nmuruaja1bcLkMFGcWcyc9Dm+BuswzHmHpYOK9gqqe6opTC6kKKOIjFi1tfVNCMXLyAy8Oui4CRicm/cDYNwamT/a0caVz3lr/RSkx/H0JUtCSuj2+sZGbnmtwnNcPCGZx35USk6ylo9mQ20XVzxTTttAXQGdgId/uIhT5+aE6b8As83JfR/s5Lm1XtfSHyyZyIoz5xAfZsVzSOBywtePw5qV3rbpp8HZf4O4sRWXUd74GVd+fAMuqcWDphvTeWLZfUwdUAqt5lZu+vQmNrdt9vT57ZG/5fszvx9WOd7c8ya3f3m757govYj7T7ifrPgsQFMGl7xzCR3WDgB0Qsej33qUI/OO1DqEYc7NDjMPb3qYVTtWedq+N/173LT4JuL04a//fbgQzi2fcWuR7DTZ+MNblT5tNR1mtoRQmKahy8JdQ8bYXN9DZVOv5/jrmk6PMgBwS3jko910mcNXNKa63eSjDABeWFdHdatKQxCQzmr45I++bTvfhtYDlvWOOFZrNw9vedKjDAA6rB0+RXaqOqt8lAHAX8r/QmO/b3zDN6Gpv4l7y+71advSsYUdXTs8x+Ut5R5lAOCWbv626W+YHQO1MMIw53t79/ooA4CXd77Mnt49QY+h8CecCmH8pU0dwOZ009nvX+zEZAs+M4fd5abf5l8vyGz3jtFt9g/b6DDZsdjDlwFkaGEbb7uqZRQQpxVcAcJpHGOrkI/daaPd3u3X3mXzPrRYXP4FjEwOE/YgC/kEJYfbjsnp/3AxOJit2+YvZ5ulDce+eQ7DnA8NntuH1WkNegyFP8ooDGQnGvnRUl8/6yidYGZO8Ln781KMnFXiuwdq1OuYnu3NIVRa4F9P+LxFE8hLCd8StyA9jikZvuNNSoulIIStr8OKlMkw+RjfttjUg0pvPZIkJWRzUeFyv/YlOV6HkcLkQmKjY33On1ZwGrnxwdd+Ho6cuBxOn3K6T5sxykhhSqHneGG2/87xRbMuItk4UA8iDHM+KWmSX2zEhIQJTEqcFPQYCn/CVg8hki6oI+F22tht4V9ldTz/VS15KUZuPHUWSwvTiQrBN7+2w8Sza/fy7w2NTM2M58ZTZ1Ja4A3y6bc4+LCqjb9+uIteq4PzF09keUkehRnhrYq1vbmXv67ZxRe7OjhqWjr/s2was3L9K3IpBmirgrV/he2rIW8RnHAL5EXcm3pYOrpr+O+eN3lm16sk6xO5Zt5lLM0/FoPR+9lubN3IgxseZHf3bk6fcjoXzrow7EV26vrqWLV9FaurV1OYXMg1C65hQbZ3vuwuO182fskDGx6gx9bDj+b8iDMKz/A1+IZhzqs6q3h8y+N81fQVS3KWcHnx5cxIjWwg33gjbHEIgwbMAjxVO6SUtQPtaVLKiFQEH8k4hPY+m1Yu0hhcecShuN2SDpONeEM0cfsx4rb0WrA73UxMG7mndpvTRY/FQXKsHkO0SjswLC4HmDvBkAQxscNfP4p09taj18WQmJAV8LzZYcbsMJMWm4ZOjMwmgFu66bR0EqeP268Rt8/Wh8PtIC12P8n5wjDndpedXlsvSYYkYqKCLzV7uBLOwLTlaOUy84BWYDJQKaWcGw5BQ0EFpikUCkXoDKcQQvFD/D1wJPD+QMTyCcAPv6mAhxJSSqrbTOztNJMap2d6VkLIKw2XW7KrtZ+GLjOZiQamZSX4la6sau6lqrUft1syPSuB2XnJ+xlNcajR0NdATW8NhigDU1Omkmr0t0t9U3q69rK7Zycmex+TkwqYlBP69llD9x6qundhdVmZmlTIjMyIPzcqDoJQFIJDStkhhNAJIXRSyjVCiPtGTLJxyBe7O7j06a+xOrQqZD89uoDrTppBclzwSuH9bc1c/eIGHC5t5XbTqTO55OgCj1JYv7eTFa9tobJZq6o1ITWWe79fwpIpkcuZrxgdtnds56r3r/K4dC7NXcptR91GXkL4gug62qu4Z9NfWV3/IQAJ+gQePvb/KJl4bNBj7Gzbyh/K/0RZixbXk25M58/H/R+LcpeETU7FyBDKBmO3ECIB+AR4XghxP6Cc2wdo77Nx86ubPcoA4MnPa6hs7j1AL1/qOs3c9MpmjzIA+NM7O9jZ2u85/nx3h0cZANR3WfjPRlXL4FDH4XLw5NYnffz7v2z6kg2tG8L6Ptu6tnuUAUC/o58/bXyIvt7gv2MbOyo8ygC0eImntj2LyRb8b0ExOoSiEM4CzMAvgfm0HmYAACAASURBVLeB3cB3RkKo8UiPxUFdp79vdGtv8H7RXWY7vRb/eIG2Pm/g2tYG/x9VRUMPfZbw+Zorxh4mh4lNbZv82nd37w7r+7RZ/f1CKrt30m/1jy3YHzW9tX5t27u202XpCHC1YiwRlEIQQkQBq6WUbimlU0r5tJTyASml+oQHyEg0MH+i/17+pLTgYwxykozkJRt92qJ1wid19ZGF/ltDx03PJDFWeVgcyiQZkvjWpG/5tc/LmBfW95kYIGbh2JwlpCYEn15ldtosv7ajcpeSFRe+eAjFyBCUQpBSugC3EEJZL/dDcqyeO787j6mZmitpXEwUfzxnXkj+/1lJRh78wUKPUkgyRvPAhQuYlumNU1g8JY1zFuZ7CtycOCvLryCO4tBDJ3ScN/M8luYuBSBaRHNp0aWUZJYM0zM0ZmcUceO8K4nRaQ8Yc1JmcE3RZRhDyOu0IL2IH866iGih2b0WZS3kvGnnEBNjHKanYrQJxe30P8AC4D0G2Q6klL8YGdH2z1h2O+3st9HQbSHRqGdyehxChJ7iqbXXSnOvldS4GCYGWGF0m21sb+rDLWFqVjzZSWPbb14RPvrt/dT316PX6ZmUOAl91MHFyxwIl91KXcdWzA4z+UmTSE4JvVqaxdpPVfd2bC47hUlTyEhUq4OxQDjjEH4SqF1K+fRBynbQjGWFoFAoFGOVsMUhHMyNXwhhRPNKMgy818tSyluHXGMAngEWAR3A+VLKmlDfKxgaus30W13kJBtIDrDnbrI6aeixEKuPCvhkHinqu8w09VhIi49haqZ/PiWny01dlwW3WzIhLTZgJHJbn40Ok430+BgyE0dxqd5dB7Y+SMqD2JSDG6N5C9hNkDYFAkXnWnqgrwFiEiHl4NI0dPc20GpqItmYRnZqod95p9tJQ18DbtzkJ+QHjIrt6N5Lh6WNtNhMMg7iqTpcVHZU0mfvIy8hjwmJE/wvsPVBTz3o4yA1sJwN7duxOM3kJk4mPt5/u6jX1kuLuYUEfQK5CSPz9B/UnFs66LB2kGZIG9Uyn039TfQ7+smOyybJ4L9NbHKYaDI1YYwyBv5MxghBKwQhxB4CZDSVUvr/erzYgBOllP1CCD3wmRDiLSnl2kHXXAp0SSmnCSEuAP6IVpUtbNidbt7b1syKf2+h2+xg/oRk/nhusc/+/u62fm77z1Y+3dVOfEwUvzljNt8tySfeENkaAmt3t7Pi31vZ3dZPZqKBW8+cw2lzc4iO1sw97X02nvh8D49/Wo3LLfl+6UR+cdJ08lK820br9nRw/UubqO+yMCE1lnvOm8+RhRHO7e+0w47/wupfgqUL8hbCWQ9CdlHwY5g6YdML8PHd2k1s0lFw6p2QPyh5WstWeP0X0FCmJUg7/c8w+zsQHbyRfWvjV/zvV3eyq3cPGbEZ3F76K46ZfDK6KO2zb7e089y253h629O4pZuzp53NlcVX+twIy+s+YcVXd9JgaiQ/Po+VS26hdNKy4P/XMNBv7eed2nf4y/q/0GPrYVbaLG5ecjOLshd5L2qvgjd/DdUfQkwCnLIS5n0fDJrty2Lp5L+7X+eezY9gcpg4ImshKxbdwJSsYs8QVV1V3PbFbVS0V5BsSGbFESs4adJJYU0dEdSct5Sz4tMVNJgayI/PZ+UxKynN2e/D74jgcDn4sO5Dfr/29/TYepibPpc7jrqDGWnenEp7evZw97q7+aLxC+Ki47ih9AbOLDxzTNZtCMXttBRYPPB3LPAA8NyBOkiNfU70+oG/oUrlLGDf6uNl4CRxMBvvB2BHSx9Xv7jBk356U30P//vvLfRZtGOb08VDH+zk013tAJjsLla8tiWkegjhYG+HiV+9UsHuNm3K2vpsXP/SJioavXJ8Wd3Bwx/txuGSuCX88+s63tna7Dlf12nmimfLqe/SXGDruyxc8WwZdZ0RTufcug1e/qmmDAAa18PqG8Aagi96/dfw7gpNGQDUfgGf/tl7bOuDN2/SlAFo7/XqpVoVriDp6NnLTV/exq6BPPrtlnau+3wFe9q3eK4pay7jiS1P4HQ7cUs3r+x8hQ/rvL76De3bufbz39Bg0uoONJgaufbzFdS3+9bHGGkqOiu4/cvb6RlIib29czt/Lvuztx6C0wYf36MpAwB7P6y+Dpo2esaobNvE7eV/xuTQzIRfta7nkYrHsdm072S/vZ8/fPUHKtq1QlA9th5+/cmv2dm1M6z/y7Bz3tfAtWuupcGkxUc0mLTj+r76sMoxHDu7d3LTxzd55nxrx1ZWrl1Jn137jtpddh7b/BhfNH4BgNlp5vdrf8+2jm0RlTNYglYIUsqOQX8NUsr7gDOG6yeEiBJCbETLf/SelPKrIZfkA3UD7+EEeoCwPs7WtJsYaiop29tFy4B/f2e/nbcG3VT3Ud0e2bi7+k4ztUNu3HaXmz2D5PigssWv3783NGB3anUQGrotfnUXei1O6rsirBA6q/Gb9Lq10NcU+Pr9jTGUXe9B98CPvq8Z9n7ue15K6AjeN7+lr4G6ft+biMPtoK7HW2Too7qP/Pqtrl7tqTPQ1F/vuSHso9feS2OEb061vbXIIc9bFe0VNPcPfLdNbbD9df+OHbs8L2t66/xOv9/4OZ0DSqXd0k75oKAzAIlkb99ev37fhGHn3NQUeM7DWAwoGALN+Ya2DbSZ2wDotHby/t73/frV9NZEQryQCVohCCEWDvorFUJcRRBbTlJKl5SyBJgALBFChLBn4PP+VwghyoQQZW1tbSH1zUjwX8pmJxlIMmriJxiimZntv1efmRDZOsQp8TEkBNiiGixHUb6/5+/Cyanoo7SPMjVOT/SQlN1ROkFqfITjFOIz/dsSc8EYgudygL1r0qd7xzAkQVK+/zX7yQIaiERDSsCaw+mDUjXPSZ/jd35+xnz0Os3DJ9mQ5nGx3EeUiCLVGNl0IoGyimbFZZEYM/DdNiRB5mz/joPmK93gnxtpWlIB8THa9mp8TDzZcf5uzunG8G5JDj/nyfuZ8/DndjoQaQE+48FzHq+PZ2rKVL9rxmrt51C2jP486O8uNCNw0MVapZTdwBrgtCGnGoCJAEKIaCAZzbg8tP9jUspSKWVpZmaAm80BmJ2bxPdLvYacaJ3gD2fPIytJM7Ymxur53zNmY9R7p+OEmZnMmxDZGgJz85K55fRZDN4w+8nSycweZOs4cVYWUzO8N7DMBAPfL53ocW+dkpHA/57h+6P/zemzmBrmmgvDkj0XFvzIe6yLhu/cD4kh1I/OWwCFy7zH0UY46VZvMfbEbPjOfdrY+yi5KCQ7xcTMOfx24S8RgyrAXjrjfArTZ3qOj5twHFOSpniO043pnDP9HM+cF6TP4sb5P/MZ94Z5V1IQ4KY2kkxPmc5pBd6fV7SI5oZFNzA9baDwjDFJs8HoB7kpTzsFcr2xDHMy5nJ8zhGeY0OUgZsW/IKkgc8tMzaTW5fe6nMzPmvqWcxM9c5XOBh2zpMKuHHxjT59blh0AwVJBWGVYzhmpM3gnGnneI6jRTS/O/J3ZMZp96jEmER+tfhXGKO8jh3H5h8bUOGNBcJWICfg4EJkoiXF6xZCxALvAn+UUq4edM3/APOklFcNGJXPkVIeUNEcjNtpt9nO9uY+usx2CtLjmZGd6Ff8ZmdLH9Xt/SQY9MzKSSQ9wisEAJPNweb6Hmo7zWQlGinKSyIzyddLqLHbQlVLHy63ZHp2ol80tMXupKqln8ZuC7nJsczM8c+YGhHMXZotwdwBaYWQNRt0IdZm6NwDzRVg64WMGTBxSII0twtaK6FrD8SmQdYciAvtKdFuN7G7fQv1vXVkxGUyPW0OCQm+Dx3NpmZ2du3ELd1MTZnq5ylitXSzq2MrTf1N5MTnMj1jLsaD9ar6BtT21FLVXUW3tZuJSROZnz4f49CAsLYdmnHZkKTN15D/tbO7lp1d2+m391OQPIWpQ7KdutwudnXvoq6vjhRDCtNTp5NsCH/M6rBz7rSyq3sXTaYmcuJymJ46HWN05D3qemw97OzaSbetm0mJk5iaMpWoId/z6u5q9vTsIV4fz4y0GQFXFpEgnHEI1wdo7gHKpZQbA5xDCFGMZjCOQluNvCSlvEMIcQdQJqV8fcA19Vm0oLdO4AIpZYDNYy8qDkGhUChCJ5z1EEoH/t4YOD4T2AxcJYT4l5Ty/4Z2kFJuRrvRD23/3aDXVuC8EOQYUXotDgzROgx6VWVszOCwgst2YPuDpVvbCokewVWd3QTSDYb91Np2uzQvKmPS/ldCtn4QAmICV8tzuB1YHBYSYhL2X+3M2qdtk32Tym7WHogygP7QTydhcpgQiDHp5jnWCEUhTAAW7nMjFULcCvwXOA4oB/wUwniipdfKmxVNPLd2LxNS47j6hGmUFqQeVOoJRZiQEmrXaq6m3TWw6Kcw9xxIGhQI1V0Lm1/S4hWy5sIx10H+ov0OeVA4LFD9MXzyJ81185jrtL332EE2prYdsO7vsPsDmHoiLL4csgYlebP2ah5Sn90HOj0cfyNMWQYx3pvUjs4dPLvtWTa0buCkSSdx7vRzmZw8KHDM1AE73tRqEcemw3E3QsExEEr6it5m2PYalD2hFbs/9gaYtBQOwe95v72fTxs+5R8V/0AfpefyeZezNG/pqGwrjRdC2TLajrbX7xg4NgCbpJSzhBAbpJQRq0oe7i0jKSUPfriTe9/z+lLHROl49edHBfTqUUSIps3w+EngGpTae9ktcPyvtRuY067FIax/ynvekAiXfQCZYTRyVn8Mzyz3bTvvGZh7lva6vw2eOcs3/iFjFlz8hteDp/INWDWkwOCP/g1TTwC0SNeL3ryINovXg25p7lLuXXYvCTEDDgHlz8Ab13j7Cx389G2YdARBIaWm1Nbc6W2LioFL34O88CbJGwt8UPsB1625zqftsZMfY2ne0lGSaPQZbssoFC+j54GvhBC3DqwOPgdeEELEA2MzyiJIWnptPP7ZHp82u8tNZZMq6DGqtGz1VQYAXz4EvQO+5j11sPFZ3/O2Ps3IHE62vOrftu5RrUg8QOdu/2C49u3eeAiXU1s9DKXiZc/L6p5qH2UAWgGcur6BuABrL3z5gG9/6YY9nwT/f/Q1wZd/9W1z2bV5PsRwup28WPmiX/ub1W+OgjTjh6C2jAYih58C3gKOHmi+Skq57zH9ovCLFjn0UYKEmGi/4jTKjjDKBLIHGBK9WyRReoiO1SJuffqFeUsgLoBHSFyG9oS+PznBmz5D6CBQ+uhB4xqi/MeIElHebKa6KDAG8Franz0jEDo9GBJgaLGbQ3ALRSd0AWMSUgLNocJDsPUQJPCmlLJMSnn/wN8h4+aTnmDg5tN9i3pkJxmYlxfZOATFEHJL/APPvnW7dxsmeSKc+L++5zNnQ85BxT7un9nLfX33dVFwxJVew3H6NCgekn5r3nmQPpDPRqeDI67wjZfQx8Lcsz2HhSmFLMnxdan94ewfMjlxwIYQEw/H3+y7129MgSnB1zomIVObv8Ek5kLe/ODHGCfohI4LZ13oEy9hjDJyasGpoyjV2CcUG8LTwENSyq9HVqThGQm3U7Pdycbabr7Y3UF2koGlU9OZlhXC05diZGivgj2fQm8DTDke8ks9idgAzVumbp2WwiK1UDOyph8o3+JB0rRRsyU47VqwXP5CX0+i3iYtNUfjBk2RTVrqa/x2u7V8TtUfaSubKcf77ds39TdR3lJOVVcV87PmU5JZQnrsoJWF0w4N5doYsSkw5TgtADAU7CaoL9O2mhJzNYUSTnvLGMIt3Wxp38LaprXodXqOyD1izAaERYpwxiFsB6YBe9EK5Ai0xUPxATuOACoOQaFQKEInnHEIaq2lUCgUhzChFMjZCyCEyAIOPSuUYkyyp2cP65rW0WJuYXHOYuZnzvcNMOptgr1faNs1qQUw+Wi/rZiqriq+bvqabns3R+YeybyMeWHN3Q9AW5WWnrtpM+QWa7UbMr058V1uF1s7trK2aS3RumiOzD3Sb/ti35bRzu6dFGcW+20ZmR1mylrKWNe0jsSYRBbnLGZh9kKfMeishprPNA+nyUfBxCMOvjDR/rD2QN1X2ryP5DZdBBhuzsOBxWlhU9sm1jWtIysuiyU5SyhMGZvzFcqW0XK0xHZ5aKmsJwOVUsoQNzG/OWrL6PCgtreWS9+5lGazNzX53cfezRmFg7Kuf3IPfPh773H6NDj/OS1vErCzaycXv30xvXbNhVgg+OtJf+XYCSEYY4ejvxX+eyNU/sfbNusMOOM+SNQM4Otb1nPpO5filJonmzHKyJOnPUlRhmYA77J2cdPHN/FVszc7/MVzL+YXC37h8TR6r+Y9bvj4Bk+65aSYJB466SEWZA2EAPU0wPPf0/JH7eOUO2Hp/4Q38GztI/D2r73HmbPhhy9D8titBBaIYOY8HLy15y1+9cmvPMfZcdk8ccoTvkGHESKccQi/B44EqqSUU4CTgLUH7qJQHDyVHZU+ygDgL+V/ocMykAy3ZSt89hffTh27tGR4A5S3lHuUAWi5+x/e+LCnAExYaK30VQYA2//riU2QUvLi9hc9ygDA6rLybs27nuPd3bt9bkwAz257ltq+WgC6rd08ufVJn9z7vfZeypoHPRi1bPFVBgAf/UGL5g4X3bW+ChigrVIrczrOGG7Ow0GntZO/lPt+R1vMLWzrHJuhW6EoBIeUsgPQCSF0Uso1aLmNFIoRwea2+bWZHCYc7oGAMJcDnBb/jk6r56XZ4V8YqNfRi9Pt9Gs/aBzWwO1OTX6XdNFl7fI73W3zxgPYXP7/q0u6cAwEvzncDvqHxlsA/Y5BbU6733kcFi0wLlwEMefjheHmPBw4XI6ADx+B3nssEIpC6BZCJACfAM8LIe5H8zZSKEaEGakziNH57vX/eM6PvQVa0qdD0fd8OxkStZxGAyzMXuiXJO7Hc34c3nTNmTP9XTczpnvaonXRXDj7Qr9u357ybc/rwuRCsmJ9C/sszV3qSfmcGZfJ92b4/q86oWNx9mJvQ9YsLaX1YEougpQwbuUkT4SSH/m2GRK1NNrjjOHmPBxkxWXx4zk/9mnT6/TMSJ2xnx6jSyg2hHjAiuZuehFaIZvnB1YNEUXZEA4PpJRsaN3A3yv+Tn1fPefNOI/TppxGVtygH3HLVqj4F1S+DmlTYenVUHi857TD7aC8uZxHNz9Kl62LH83+ESdOPJHU2DBX1qovg7InNcPyxCOh9BKY6L1Z70u09kTFE8RExQRMtLYvud361vV8a9K3OHfGuUxO8u4z1/fVs6ZuDa/sfIVEfSIXz72Yo/KPIjZ6UNBcw3otgV5LBRRfAPMvhNRJ4f1fu2th0yrY/OLIJRSMEMPNeThoNbfybs27vLTjJfIT87l83uUsyFowKokzwxaHMJZQCuHwwuayYXPZSIo5QOR4b6P2dGwIXBnO6rTicDu85SRHAqdDMzAnZEF0YKPkcKmYHW4HZoeZxJjE/aa/7rB0EKOLIXF/aSucdnCYw+9dNJRIpByPAMHMeTjotfdiiDIETFMSKb5xHIIQog8IpDX2Baap/A6KESWoH1FS3gFPG6ONGEfaWzpaDykBajwPIlD95sHodfpht7OGdYuMjvHmURpJRqEi3EgQzJyHgwM+0IwRhlUIUkqVv+FwxNYHLdugv0XLm581OzI3maGY2rVtIVvvwL78rOH7DKGmYzs7undjdVmZllzI3OyDyNTe06B58Lhd2lykht9lsN/ez67uXbRZ2shPyGdayjS/eIm9PXup7qnGEGVgeup0T+1ehSIcjEKhXcWYx9YPn9+v5c4HzYf9u49C8fcjW0ilrxlWXwc73tKO9bFw0atQcFTQQ+xo2cjv1t3lcfNL1Cdy3/H3sCQ/+DFo3wn//IGWVwkgIQd+9GroeYQOgNlh5smtT/LY5scALV7izmPu5MzCMz17zVvbt3LFe1d43GjnZczjT8f9ifzEA69KFIpgGbkNM8X4pW2HVxmAVljlv9drhewjSeMGrzIAzYXynZu1vesg2dC5zcfnu8/Rx5PbnqXf3Bm8HDvf8SoDgP5mWP+MNi9hYnfPbo8yAC1eYuXalZ56CHaXnccrHveJqahor6C8tTxsMigUaoWg8Mfc7t9m7w/pRhwWTAHkaNuubWcFuX9d39fg17a7Zze91i4SAtU5CETjpgADr9N88sO0jRYoTsHsNHsUgNlhprLTv/DP3t69YXn/g8XhcFBfX4/VOv7iEA5ljEYjEyZMQK8PLeJaKQSFPymTNc8Rp823LSnCqQnSp/q3zfqOtx5CEMxNn+3XdvyE48gJxbVwxmlQ8ZJv27zzw2pTyU/IJ0YXg93tDS7Lj88nJy4HgGRDMt+e8m0er3jcp9/8jNGtZVBfX09iYiIFBQWq/vgYQUpJR0cH9fX1TJkyJaS+astI4U/GDDj/eUjMGTieCd970pOXJ2Lkzofv3O+tCjZlmVZPOQQ3xwWps7hq3pUYozQPo2UTjuecKWeiiw7hWWjKsXDML7U6BkIHC38Cs88M4R8J4i2Sp3D/ifeTGasZiQuTC/nT8X8iIy4DACEE504/l1MLTkUgMEQZuG7hdczPGl2FYLVaSU9PV8pgDCGEID09/aBWbSoOQbF/epvA0qkZUePDmwEyJLpqNPtB0gQwhu705nTY2Nm5DbvbwZTEApJCWGF4cDk1OXB7V1AjQIu5hR5bD5mxmQFLQFqdVhr6G4jRxZCfmD+ifvPBUFlZyezZ/qswxegT6LMJZz0ExeFGUq5v1a/RIrXgG3WP1huYfTCupoOJioaMad9sjCDIjsv2puYIgDHayNSUAFtpiohy2WWXcf311zNnzvhL2XEglEJQjC7mLi0VQkwcpBX6lqUMFlM79NRrkcppU/xdY50O6KrWbCKpBWAcmQChZlMzHZYO0mLTyI0fA4pUMWI8/vjjw180CKfbicPtQIeOmKiYMbvFpmwIitGjdTs8dw48dhw8fBR8+Vew9g7fbzBNm+Afp8Fjx8MjR8OG57TtpX2YOuDju7XxHz0W/nkRtO8K7/8BfNn4JResvoAL/nsBF6y+gC8avgj7eyj2z3PPPceSJUsoKSnhyiuvxOVycfHFF1NUVMS8efP4y1+0FNTLli3j2muvpaSkhKKiItatWweAyWTikksuYcmSJSxYsID//EdLZ+5yubjxxhspKiqiuLiYBx980DPOvm3rd999l6VLl7Jw4ULOO+88+vt9s9JanVb29u6lurua3T276bB24HK7IjU1IaEUgmJ0cFi1XP2N67Vjlx3e+y00bgx+DEsPrL4eOnYOjGmG16/WIqz3Ub8OPr0H9qW7rvkEyp7QIo7DRF1fHdd/dD0dVi3PY6e1k+s/vp7a3jDWIVDsl8rKSlatWsXnn3/Oxo0biYqKYuXKlTQ0NLBlyxYqKir46U9/6rnebDazceNG/va3v3HJJZcAcOedd3LiiSeybt061qxZw0033YTJZOKxxx6jpqaGjRs3snnzZi666CKf925vb2flypW8//77rF+/ntLSUu69917Pebd002ZpwzqQHlxKSYupBUugFOJjAKUQFKODuR12vuvf3lkd/BimVmgI4FzQNWiMQAqm8nWw+Pv9HywtphbfugRoSeyaTc376aEIJx988AHl5eUsXryYkpISPvjgAzo7O6muruaaa67h7bffJinJu0144YVaKvLjjjuO3t5euru7effdd7n77rspKSlh2bJlWK1Wamtref/997nyyiuJHvBKS0vzjV1Zu3Yt27Zt4+ijj6akpISnn36avXu9sSEut4s+e5+fzIPdi8cSyoagGB2MyZAzX6uFPJhQjNjGZEgpgO4a3/bEQWNkBMg7P2GJ15U1DKQaU9Hr9N7CPWg1EMJdm1cRGCklP/nJT7jrrrt82u+8807eeecdHnnkEV566SX+8Y9/APjt3wshkFLyyiuvMHPmkLoWQbz3ySefzIsvvhjwvE7oiI2O9SvUpNeFr0RnOFErBMXoYEiEU+/Ubur7KDoX8kqCHyMhC5Y/oOU42scRP4PsIu/xpCOg8ETvcXymFlMQRrfRyUmTWXHECo8LqE7oWHHEirDn1VcE5qSTTuLll1+mtbUVgM7OTvbu3Yvb7ebcc89l5cqVrF+/3nP9qlWrAPjss89ITk4mOTmZU089lQcffJB9bvgbNmwA4OSTT+bRRx/F6XR6xh7MkUceyeeff86uXZpdymQyUVXlTXMSpYsiOy7bxz042ZBMbFQsYxG1QlCMHhNK4YqPNCOvMREyZkNciCmVpxwHV3yi5VmKTdWyoQ72IkqeAOc+rqW8cFq0KmthzlQarYtm+dTlzM2YS4uphey4bApTConWqZ9XJJgzZw4rV67klFNOwe12o9fruffeezn77LNxu90APqsHo9HIggULcDgcnlXDb3/7W6677jqKi4txu91MmTKF1atXc9lll1FVVUVxcTF6vZ7LL7+cq6++2jNWZmYmTz31FBdeeCE2mxbZv3LlSmbM8K5M4/RxFKYUYnfZ0QkdxigjUQfjTRcBVGCaQqE4aMZbYNqyZcu45557KC099MvBH0xg2ohuGQkhJgoh1gghtgkhtgohrg1wzTIhRI8QYuPA3+9GUqZDhR5bD93Wb5hsztShxQGMNv2tWsK6/WHr067Zz8OLW7ppN7f77dOOR6y2Xtq7a3A4RtcLxeQw0WHpYDw+MCoOnpFe0zqBG6SU64UQiUC5EOI9KeW2Idd9KqUMb3KYQxSzw8yn9Z/y0MaHcLgdXDbvMk6efHJoFZ/MXbD9Dfj0z1og2AkrYPopYTW0BkVPPWx4Hsr/oaWlOOl3UHCMNzjN7YK9n8P7d0BvHSy8GBb8EFImeoao66tj1fZVrK5ezdSUqVxdcjULvmlU8iixrelrHq74OxVdVRyfs4SLZ/+QKVnFEZXB5XZR1lLGA+sfoMnUxPdmfI+zp51NbsKhEWj30UcfjbYIY5oRVQhSpiEYTAAAHZ1JREFUyiagaeB1nxCiEsgHhioERZCsb13PjZ/c6Dm+/cvbiYuO4/TC04MfpHoNvH6N9/jlS+Cif2lKIVK43fD1E/DZgM92XzM8dzZc+j7kL9TamjfDs2d7Ywg+vluzA5x0G+h02Jw2/rbxb6yuXg1AR3MHV7x3BS+e+SLTUkY+zUQ4qW+v5KqPb6DLpq3YXq15i929tfxt2X0k7UsyGAG2d27nqveuwim1OX9408PYXDauXXjtqOdNUow8EfuEhRAFwALgqwCnlwohNgkh3hJChK8M1SHIezXv+bWt2rEKp8sZ3AAul3YjHsqWV76hZCHS1wRfDwn/d7u0cpn7aK30KoN9fP049DUC0Gxu5s09b/qctrqsVHeHEMswRqjpqfYog31s6txKfW9NROXY1b3Lowz28eL2F2k1t0ZUDsXoEBGFIIRIAF4BrpNSDs1NsB6YLKWcDzwI/Hs/Y1whhCgTQpS1tbWNrMBjmKw4/0ydOfE56HRBfpQ6HSQHKLmYFOEyjNFGCFSgJibB+1of538+Lh2iNJfRGF0M8dH+Retjo8emS9+BCOSGGC2iMUYbIytHgLlLNaQSoxuFetqKiDPiCkEIoUdTBs9LKV8del5K2Sul7B94/SagF0JkBLjuMSllqZSyNDPz8C0sfuKkE0nQe2+aep2eC2ddGPxyXghYfLmvH74hEWafFWZJhyE+HU5Z6duWOsU3DiGvBNKGZPY85U5I0D7/3IRcri+93ud0UXoRM1NDCy4aC0xNn8mynCN92i6f9QMmpkX2f5mTPofJib5uuTcuvpG02CCryynGNSPqdiq0kMCngU4p5XX7uSYHaJFSSiHEEuBltBXDfgU73N1Oq7qq2Ny2GafbSXFmMbPTZoeWPVFKLSlcQxmIaJi4OKwF44PGYdXqJjes1xTEhCWQXuh7TWc11H0NpjbNtpC3EPTep2azw8yW9i1UdlaSHZfNvMx55CeMz6LzLZ27qGivoK6vnukp05iXWUxypFduQG1vLZvbN9Nh6aAoo4ii9CIM+wnkGwtupwkJCX4J5fZx1FFH8cUXI5No8A9/+AO/+c1vRmTscHAwbqcjrRCOAT4FKgD3QPNvgEkAUspHhBBXAz9D80iyANdLKQ/4CR7uCkGhGCuMVYXgdDo9+Yci+b5jiTEXhyCl/ExKKaSUxVLKkoG/N6WUj0gpHxm45iEp5Vwp5Xwp5ZHDKQOFQjF++feGBo6++0Om3Pxfjr77Q/69oSFsY3/00Ucce+yxLF++3FO4JiFB215tamriuOOO86S9/vTTT/36b9261ZNCu7i4mJ07tSy6gVJr33zzzVgsFkpKSjwZUO+9916KioooKirivvvuA7RUFmeccQbz58+nqKjIkzbjjjvuYPHixRQVFXHFFVeMmXgPFVs/3nC7tZTR21drBV9mfUdLARHGgu8Ro68Zaj6Dqne02ILpp2q5hxSHJP/e0MAtr1ZgcWipxxu6LdzyagUA310Qnq2x9evXs2XLFr/i8i+88AKnnnoqK1aswOVyYTb7BzE+8sgjXHvttVx00UXY7XZcLpdPam29Xs/Pf/5znn/+ee6++24eeughNm7UsumWl5fz5JNP8tVXXyH/v717D4+qvBY//l1AaiARIgGJEK41YklCAjRBuQjoUVQgoEDxhsRKwKMUCopY9aGU6u/Y0h4Vj9BaPSgIgnIKUqDQgxAux6Ji5H4rhrQFIiIImFtJwvr9sXfCJJlcSTIzYX2eZ57MvPPuvde8ybNX9t6z16tK7969GTBgAOnp6bRt25Y1a9YAcO7cOQAmTZrEzJnOPbhjx45l9erVDBs2rFbG4HJYQgg0J9JgwV3O/AEAn8yHh1c5NX0Czf4P4c9PX3r9+dvwwPtOgjMNzpz1h4qTQZHc/ELmrD9UawkhMTGxTDIASEhI4Mc//jH5+fmMGDGC+PiyRRRvvvlmXnzxRY4dO8a9995LVFRUidLaALm5uVx7bdlv+m3bto177rmHkBDnW2/33nsvW7du5c477+TJJ59kxowZDB06lP79+wOwadMmfv3rX5OTk8OZM2eIjo72i4Rgd5oEmv0fXkoG4Fwg3j6/Vid8qRdnjsK2l0u25Zx2bkYzDdKJs97LcZTXXhNFO+TSbrnlFrZs2UK7du1ITk5m4cKFrFixgvj4eOLj49mxYwcPPPAAq1atomnTptx9991s3LixuLT2zp072blzJ4cOHWLWrFlVjueGG24gLS2N2NhYnn/+eWbPnk1eXh6PP/44y5cvZ8+ePaSkpJCXl1dLI3B5LCEEmgte6vVcyCm3zo/fulgIhf8q217VG+xMwGkb5v3+kPLaa9Pf//532rRpQ0pKCuPHjyctLY177rmneEf/wx/+kPT0dLp06cLkyZMZPnw4u3fvLre0NkBQUBD5+c4cGP3792flypXk5OSQnZ3NihUr6N+/PydOnKBZs2Y89NBDTJ8+nbS0tOKdf6tWrcjKymL58uV1/vmryk4ZBZqYe+Dzt0omgJseg8YB9qtsdT0kTHDKURQJagoRMeUvYwLa9MFdS1xDAGga1Jjpg+v+XovU1FTmzJlDUFAQoaGhLFy4sEyf999/n0WLFhEUFERERATPPvssLVu2LFNa+/XXX6djx45MmDCB7t2707NnTxYvXkxycjKJiYkAjB8/nh49erB+/XqmT59Oo0aNCAoKYv78+YSFhZGSkkJMTAwRERHFp6P8gZW/DjQFF5yCb3993anrc9MTzvWDq0IrX9bfnE53ptHcs8wpbpfwKHQZ6OuoTDVU92unK784zpz1hzhxNpe2YU2ZPrhrrV0/MCXV5GunAfZvpaHJ9+D7g6BjPxCFxgH47aIi4V0g/DGIf9ApZdHEP6cVNLVnRI92lgD8mCWEQNWQdp7B9Vx22xjjlSWEajh5Po8Dmec5n5fP9a1DuTGiOY0aVaNkRH3513fw1V5nvoEW7Zw5hj2nlfQXFy/C1/vh1CEnKbSJheYNo+5+jeR8Cyf3OvdnXNPJuZ4SFHiF+kzgsoRQRZnncpm6bCfb051JtoMaCwuSE+kXVaYOn2/l/ws+eQM2zr7UNug56DO5RA0gv5CxDRbfC4XONzXocDOMfMt7NdaGLu+8c4H9k99dahv6CvQc51SoNaYe2F9aFe09fr44GQDkFyq/XLOfczkXKljKB04fgU2lqoim/ofT7k9yz8L6n11KBgD/+KtT7O5KdOpgyWQAzvh8G3hzO5jAZQmhir7NLrvjz/gmm6wLfnZDWN5Z0Isl2/SiswP2JxeynEqmpeWcrv9Y/IG3309+LuRVMNe0MbXMEkIVff/asndAJsW15dpQ72WBfSasA4SUmi8ipBVc09F7f18JbQOxo8u2tw68uQxqRcvOZScECo8qMX+08a6ogJ03ffr0qcdIyjpx4gSjRo2q0bIDBw6kvr9ebwmhimLatmDu/fGEh3wPERgSG8Hjg75PUBM/G8Kw9nD/UoiIdV5fGwP3LfW/HUvjIOg7BWJGOpP2hLSCe9+E6+J8HZlvtIpy6jiFu3NBR/aGUf/tjIuptoIC5473upoLobztlda2bdt6uxO5sLAWzlaoasA9evXqpb6SeTZHj57K0rwLBT6LoUqyz6ieOuL89GcXclW/+VL13HFfR+Ifsk45v7fcc76OpEr2799fvQV2LVP9z2jVn7dwfu5adtkxhISEqKrqpk2btF+/fjps2DCNiooq8d6JEye0f//+GhcXp9HR0bply5YS6zh79qx26NBBCwsLVVU1KytLIyMj9cKFC3rkyBEdPHiw9uzZU/v166cHDhxQVdVx48bpxIkTNTExUadOnaqpqakaFxencXFxGh8fr+fPn9ejR49qdHS0qqoWFBTok08+qdHR0RobG6tz585VVdUNGzZofHy8xsTE6COPPKJ5eXmqqjpgwAD97LPPVFV1yZIlGhMTo9HR0fr000+X+OzTpk3T7t2769atW0t8Jm+/G2CHVrBv9fnOvSYPXyYEY8wl1UoIu5apvtBG9efNLz1eaHPZScEzITRr1kzT09PLvPeb3/xGX3jhBVV1dsznz58vs56kpCTduHGjqqouXbpUH330UVVVvfXWW/Xw4cOqqrp9+3YdNGiQqjoJYciQIVpQ4PxzOHToUN22bZuqqn733Xean59fIiHMmzdPR44cqfn5+aqqevr0ac3NzdXIyEg9dOiQqqqOHTtWX375ZVW9lBCOHz+u7du316+//lrz8/N10KBBumLFClVVBXTZMu/jV5OE4GfnO4zxT9k5pzlwfDt7j/0f57NO1mwlueec6UJP7HTuFbnSfDTbuVDuKT/Xaa8lFZW/XrBgAbNmzWLPnj1cfXXZmyHHjBlTPIHN0qVLGTNmDFlZWXz88ceMHj26eIKczMzM4mVGjx5N48aNAejbty/Tpk1j7ty5nD17tsyMbRs2bGDixInF7S1btuTQoUN07tyZG264AYBx48axZcuWEst99tlnDBw4kNatW9OkSRMefPDB4j6NGzdm5MiRNR2uMuw+BGMq8dXpw/z2i9dYdzwVgN6te/DzhGdo37pb1Vdy5ij86adw1FkH3UbA4BehRWStx+u3zh2rXnsNVFb+es2aNSQnJzNt2jSuvvpqfvGLXwDw5ptvkpSUxLPPPsuZM2f4/PPPufXWW8nOziYsLKx4IpyKtvfMM88wZMgQ1q5dS9++fVm/fj3BwXV7709wcHBxQqoNdoRgTCW2Z35SnAwAPjn1BX/OWFe9lexbeSkZAOxfCUc21kp8AaO85FcPSbEq5a9DQ0NJSEhgypQpDB06lMaNG9O8eXM6d+7MBx98ADin2Hft2uV1G19++SWxsbHMmDGDhIQEDh48WOL922+/nd///vfFF6DPnDlD165dycjI4MgR5z6hRYsWMWDAgBLLJSYmsnnzZr755hsKCwt57733yvSpLZYQjKnE9q/TyrRtPPkpF7zNTeFNYQEcWlO2PX3TZUYWYG6bWbYUR1BTp72OpaamEhcXR48ePVi2bBlTpkzx2m/MmDG8++67jBkzprht8eLFvPXWW8TFxREdHc2HH37oddlXXnmFmJgYunfvTlBQEHfddVeJ98ePH0+HDh3o3r07cXFxLFmyhODgYBYsWMDo0aOJjY2lUaNGPPbYYyWWu+6663jppZcYNGgQcXFx9OrVi+HDh1/miHhn5a+NqcT7u9/il1+8UqJtQtcH+MlNP6v6Sjb9R8m5HwDu/i0kjq+FCH2nuuWv2f2+c83g3DHnyOC2mdD9R3UX4BXMyl8bUwf6tu1D4j838ek3zqmCG5p3YWjnIdVbSexoOLgGTjqTytOxL1z/b7UcaQDo/iNLAH7MEoIxlWjX6gf8tv+vOPrt3yjUQjqHXU94WDXv/G51PYz9I3zzN6dYXasboFl43QRsTA1ZQjCmCsKat6NH88uswhp6rfMwxk/ZRWVjjDGAJQRjjDEuSwjGGGMASwjGmABX1+WvZ86cyYYNG6q1zKpVq3jppZcq7HM5pbHrit2HYIypsWrfh1AHQkNDycrKKtFWUFBQppZQbSssLKzVshG1rSb3IdgRgjGm3qxJX8Mdy++g+zvduWP5HaxJ93IHdw2lpqbSv39/kpKS6NbNqTNVdPSQmZnJLbfcQnx8PDExMWzdurXEsufOnaNjx45cvOjMNpidnU379u3Jz88nOTm5eE6DTp06MWPGDHr27MkHH3zA2rVrufHGG+nVqxeTJ09m6NChALz99ttMmjQJgOTkZCZPnkyfPn3o0qVL8boyMjKIiYkBnOTy1FNPFd/p/NprrwEwe/ZsEhISiImJYcKECdT1P/D2tVNjTL1Yk76GWR/PIq8wD4DM7ExmfTwLgCFdqnmjXznS0tLYu3dvmYqnS5YsYfDgwTz33HMUFhaSk1Oy7EiLFi2Ij49n8+bNDBo0iNWrVzN48GCCgoLKbCM8PJy0tDTy8vKIiopiy5YtdO7cmfvvv7/cuDIzM9m2bRsHDx4kKSmpzKmiN954g4yMDHbu3EmTJk04c8aZv33SpEnMnOmU9hg7diyrV69m2LBhNRqbqrAjBGNMvXg17dXiZFAkrzCPV9NerbVt1Hb5a2+K2g8ePEiXLl2Kt1dRQhgxYgSNGjWiW7dunDxZtny6t9LYAJs2baJ3797ExsayceNG9u3bV9HHv2x1mhBEpL2IbBKR/SKyT0TKVJQSx1wROSIiu0WkZ13GZIzxja+yv6pWe01UVv66Xbt2JCcns3DhQlasWEF8fDzx8fHs2LGDpKQk1q1bV6L8dXW2UZGrrro093pVT/vk5eXx+OOPs3z5cvbs2UNKSgp5eXmVL3gZ6voIoQB4UlW7ATcBT4hI6SLydwFR7mMCML+OY2r4vs2A7fPh3ZHw13lwJsPXERlDREhEtdprU03LX1eka9eupKenk5GRAVB8dFET3kpjF+38W7VqRVZWVr3MzVyn1xBUNRPIdJ9/JyIHgHbAfo9uw4GF7vRu20UkTESuc5c11ZV71pmIpai08pENcGgd/OgdaHaNb2MzV7QpPaeUuIYAENw4mCk9vZeirk2pqanMmTOHoKAgQkNDWbhwodd+Y8aMYfTo0aSmpla6zqZNmzJv3jzuvPNOQkJCSEhIqHF848eP5/Dhw8Wls1NSUpg0aRIpKSnExMQQERFxWeuvqnr72qmIdAK2ADGqet6jfTXwkqpuc19/BMxQ1XK/V2pfO63AsR3w5m1l2x/dAO3r/g/KXFmq+7XTNelreDXtVb7K/oqIkAim9JxSaxeUfSErK4vQ0FBUlSeeeIKoqCimTp3q67AAPy5/LSKhwP8AP/VMBtVcxwScU0p06NChFqNrYMpN8IF3v4lpeIZ0GRLQCaC0P/zhD7zzzjtcuHCBHj16MHHiRF+HdFnqPCGISBBOMlisqn/00uU40N7jdaTbVoKqvgG8Ac4RQh2E2jCEXw+dboEMj4m6O/Rx2o0xtWrq1Kl+c0RQG+o0IYiIAG8BB1T1P8vptgqYJCJLgd7AObt+cBmaXQNJc53JWA6vg6g74AdDoVlLX0dmjPFzdX2E0BcYC+wRkZ1u27NABwBV/R2wFrgbOALkAI/UcUwNX8vO0GeS8zCmjqkqzv9+xl/U9NpwXX/LaBtQ4V+K++2iJ+oyDmNM3QgODub06dOEh4dbUvATqsrp06cJDg6u9rJWusIYU2ORkZEcO3aMU6dO+ToU4yE4OJjIyMhqL2cJwRhTY0FBQV5LRZjAZLWMjDHGAJYQjDHGuCwhGGOMAQJ0xjQROQX83YchtAK+8eH2qyNQYrU4a1egxAmBE2tDiLOjqrYub8GATAi+JiI7KqoH4k8CJVaLs3YFSpwQOLFeCXHaKSNjjDGAJQRjjDEuSwg184avA6iGQInV4qxdgRInBE6sDT5Ou4ZgjDEGsCMEY4wxLksIlRCRxiLyhTuzW+n3kkXklIjsdB/jfRRjhojscWMoM5WcOOaKyBER2S0iPX0RpxtLZbEOFJFzHmM600dxhonIchE5KCIHROTmUu/7xZhWIU6fj6eIdPXY/k4ROS8iPy3Vx1/Gsyqx+nxM3Timisg+EdkrIu+JSHCp968SkWXumH7izlpZIatlVLkpwAGgeTnvL1NVf6gzPUhVy/vu8V1AlPvoDcx3f/pKRbECbFXVofUWjXevAutUdZSIfA9oVup9fxnTyuIEH4+nqh4C4sH5BwtnAqwVpbr5xXhWMVbw8ZiKSDtgMtBNVXNF5H3gPuBtj26PAt+q6vUich/wK2BMReu1I4QKiEgkMAR409exXKbhwEJ1bAfCROQ6Xwflr0SkBXALzuROqOoFVT1bqpvPx7SKcfqb24AvVbX0jaU+H08vyovVXzQBmopIE5x/BE6Uen848I77fDlwm1RSo9wSQsVeAZ4GLlbQZ6R7iLtcRNpX0K8uKfAXEfncnXu6tHbAPz1eH3PbfKGyWAFuFpFdIvJnEYmuz+BcnYFTwAL3dOGbIhJSqo8/jGlV4gTfj6en+4D3vLT7w3iWVl6s4OMxVdXjwG+AfwCZODNN/qVUt+IxVdUC4BwQXtF6LSGUQ0SGAl+r6ucVdPsT0ElVuwP/y6VsXN/6qWpPnMPuJ0TkFh/FURWVxZqGc3t9HPAasLK+A8T5z6snMF9VewDZwDM+iKMyVYnTH8YTAPeUVhLwga9iqKpKYvX5mIrINThHAJ2BtkCIiDx0ueu1hFC+vkCSiGQAS4FbReRdzw6qelpV/+W+fBPoVb8hFsdx3P35Nc75zsRSXY4DnkcvkW5bvassVlU9r6pZ7vO1QJCItKrnMI8Bx1T1E/f1cpwdryd/GNNK4/ST8SxyF5Cmqie9vOcP4+mp3Fj9ZEz/DTiqqqdUNR/4I9CnVJ/iMXVPK7UATle0UksI5VDVn6lqpKp2wjl03KiqJTJwqXOcSTgXn+uViISIyNVFz4E7gL2luq0CHna/yXETzuFlZj2HWqVYRSSi6DyniCTi/I1W+Edc21T1K+CfItLVbboN2F+qm8/HtCpx+sN4erif8k/B+Hw8Syk3Vj8Z038AN4lIMzeW2yi7/1kFjHOfj8LZh1V445l9y6iaRGQ2sENVVwGTRSQJKADOAMk+CKkNsML9+2wCLFHVdSLyGICq/g5YC9wNHAFygEd8EGdVYx0F/LuIFAC5wH2V/RHXkZ8Ai91TB+nAI346ppXF6Rfj6f4DcDsw0aPNH8ezKrH6fExV9RMRWY5z+qoA+AJ4o9T+6S1gkYgcwdk/3VfZeu1OZWOMMYCdMjLGGOOyhGCMMQawhGCMMcZlCcEYYwxgCcEYY4zLEoIxxhjAEoK5wonIYyLycB1vY4SIdKvLbdSUOOXIfXXnsvEzdmOauWKJSBP3RqO6NgJYTdm7nY3xK3aEYPyCiDzsVo3dJSKLRKSTiGx02z4SkQ5uv7dFZL6IbBeRdHEmK/lvcSaHedtjfVki8rI4E4h8JCKt3fZUEXlFnMl5pojILBF5yuO9l0Vkh7u+BBH5o4j8TURe8Fj3QyLyqTiTo/xenLr5Rdt80f0M20WkjYj0wSlrMsft/30RiXff3y0iK9xCZeWNy2QR2e/2Xeq2hbif+VNxqpwOd9uTReRD93P8TUR+7rGeleJUmN0n5VSZrUof08Cpqj3s4dMHEA0cBlq5r1viVJId577+MbDSff42TrFBwan2eB6Ixfnn5nMg3u2nwIPu85nAf7nPU4F5HtueBTzl8d6v3OdTcOrLXwdchVNILhz4gRtbkNtvHvCwxzaHuc9/DTzvEfMoj23uBga4z2cDr1QwNieAq9znYe7P/wc8VNTmjl0ITumUTDfOpjh1on5YNKbuz6L2cPd1hue4e+tjjyvnYUcIxh/cCnyg7ixqqnoGuBlY4r6/COjn0f9P6uy59gAnVXWPql4E9gGd3D4XgWXu83dLLb+M8q1yf+4B9qlqpjoVbdNxKkfehlPV9jMR2em+7uIucwHn1BA4yakolmLiTGoTpqqb3aZ3cCa5Kc9unFpFD+HUrAGnKOAz7vZTgWCgg/ve/6pThTcXpwJm0eeeLCK7gO3u54jysq2q9DENmF1DMIGoqOT4RY/nRa/L+5v2LNqVfRnrFuAdVf2Zl2Xz3UQFUFhBLNUxBCdhDAOeE5FYN4aR6kz3WExEelPycwKoiAzEKZd8s6rmiEgqThLxXLbSPqbhsyME4w82AqNFJBxARFoCH3OpOuODwNZqrrMRTlVKgAeAbbUQJ8BHwCgRuRacWEWkYyXLfAdcDaCq54BvRaS/+95YYLO3hUSkEdBeVTcBM3Dq2YcC64GfuGWPEZEeHovd7sbUFOdi9v+5y33r7uhvBG7ysrmq9DENnB0hGJ9T1X0i8iKwWUQKcUr5/gRnasjpONNEVrcccjaQKCLPA19TyeTi1Yh1v7vOv7g77HzgCaCieXeXAn8Qkck4SWoc8DsRaYZbsrqc5RoD77qnmQSYq6pnReSXONO77nZjOAoUTfj+KfA/OBPMvKuqO0RkD/CYiBwADuGcEiptXRX6mAbOyl+bBklEslQ11Ndx1CcRSca5iDzJ17GYwGSnjIwxxgB2hGCMXxCR13Hm8fb0qqou8EU85spkCcEYYwxgp4yMMca4LCEYY4wBLCEYY4xxWUIwxhgDWEIwxhjj+v+hM7lBLSyxvgAAAABJRU5ErkJggg==\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# gráfico de linhas com Seaborn\n",
        "sns.lineplot(data=iris.drop(['especie'], axis=1));"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "qbMsdb2fKr3s",
        "outputId": "f8a49c2c-f28e-43e9-a674-a28a96914822"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Vejamos um exemplo do gráfico boxplot com a biblioteca Seaborn, exbindo os boxplots de todos os atributos em um mesmo gráfico:"
      ],
      "metadata": {
        "id": "9VCBplHUKtJ7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# boxplot com Seaborn\n",
        "sns.boxplot(data = iris);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 266
        },
        "id": "MeQUwbVTKulj",
        "outputId": "5187db13-90bd-4409-a1c3-c7841f9bc5ca"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Agora vamos plotar um histograma do comprimento da sépala:"
      ],
      "metadata": {
        "id": "wr9mwRYjKwE6"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# histograma com seaborn\n",
        "sns.histplot(iris['comprimento_sepala'], bins=7);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 280
        },
        "id": "HUSg5r5IKwLB",
        "outputId": "cd7a98b2-cadf-475a-e88d-7d4868aebe7d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Podemos também plotar boxplots simples facilmente:"
      ],
      "metadata": {
        "id": "hsIy8psiK8VW"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# boxplot com seaborn\n",
        "sns.boxplot(x=iris['comprimento_sepala']);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 280
        },
        "id": "MgXpbnL5KwPy",
        "outputId": "61b6ab52-0c34-459c-a55a-0707d978f576"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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AAElFTkSuQmCC\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Um gráfico muito útil para a análise de dados é o gráfico de correlação, que exibe graficamente as correlações entre os atributos numéricos de um dataset. Com Seaborn, basta uma linha de código para plotá-la. Para fazer algo similar com Matplotlib são necessárias diversas linhas de código."
      ],
      "metadata": {
        "id": "BmHVUupzK-z_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# gráfico de correlação com Seaborn\n",
        "sns.heatmap(iris.corr(), annot=True, cmap='RdBu', vmin=-1, vmax=1);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "id": "19EDbVUCLAU_",
        "outputId": "6a7ba16a-d22f-4d09-dab9-254d182f2019"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Para finalizar, vamos plotar um gráfico composto muito interessante que apresenta, em uma só figura, scatter plots de cada par de atributos numéricos do dataset e o histograma do atributo na diagonal principal. Se configurarmos o parâmetro hue, em vez do histograma, o gráfico exibirá na diagonal principal a distribuição de cada uma das espécies pelo atributo, usando density plots. Os dois exemplos são exibidos a seguir. Repare que basta uma única linha de código para que este gráfico tão interessante seja exibido."
      ],
      "metadata": {
        "id": "YLZn2yiALBwB"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# pair plot 1 com Seaborn\n",
        "sns.pairplot(iris);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 726
        },
        "id": "93PKUIwyLDdq",
        "outputId": "c474f8c9-ce93-4dfa-a0cb-b162d194c4c9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x720 with 20 Axes>"
            ],
            "image/png": 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t0pT2T4hTUeX60IXR4AAllneryyVwbngU6185HLWP7gFfUEcKANuPnGS/yjHi1VK7+AL3DPhwrG8Ij7wansfJ3lN0o3VQLIS4EcC3ARQCuEwIMQfAWinlcp3HIYTER4c3pVn9VyzfYZVPsWr/6fSmJCQV4vU1lZZYpf0FjD2LQ/uL1+PGTfPqkOcCytz52Hv8FDr7fagqnYAJ+S5b6UiJ9ej0KVa113VPMTOPJFZ7K+LUrSn+GoAFAH4DAFLK3UKIBs3HIITEwawWWIXK+1KlR6vzFBnqv2pKCw19ipc3ew33X+cpSqs3JSHJEq+vxdIS/9OyK6O0v7E8iwP98ZsvH8TK+fVYv/UQKooLUVSQh++9cijY/ms3NuGrn5qJdf910BY6UmI9Kq1unadIy7yQ62ZW45cHe1K+p9RXFJuaR6Jqr/peqcapW1P8ppRyoRBil5Ry7vi2vVLKFm0HATVIJGM4Rh+nU4dl5H2pKi4qT8lNdy3A5w38iJ9cdRXm1VdE7X9fx2mrvCmzFWqKM0S8vhZLS1w6oSBK+xvPszigLQ70j7uvmY6Nr0e3/7db5uBg9wDmTrkEUytLMqUjdUzNdDoqre76W+ca1lKz80I2r15oaj+x4tQxT0UVj4k40+JTfEAI8VkAeUKIRiHEQwDe0HwMQkgcdHpTGnlfqlB5SvYo/Ih7BnyG+0+3NyUhyRKvr8XSEr9/Jvq9eJ7FAW1xoI0Qxu0HfBew/pXDKCrMi9tvifMJ1eo+vPUwHnn1MI71DSlrqepeoMpXs/uJFaeV8aQap275xL0A/ieA8wB+AuAXAL6h+RiEkDikw5vS0I/YU2R43OryCYrtam9KQ+9Vi7wpCUkWleaxqnRMK+wSImZfjHwvnmdx4JihbQw9jAvzqSPOUlR+xEZ5qKqlsTS8Ru3N7kdFMvNUjOOxJk6tT4qllOeklP9TSvkRAFcB+KaUko92CEkzAe2hu2Csi+vWFAZ0Zzes34bP/GAHbli/DS8f6MaMqlKsXdEcdtwxP+Iyw+0ttR7D/Td5y7GuNbz9utZmNHmN2xOSKQKax42vt+PhrYfx6LZ23LukESdOjy2ve9/m3ViztNGwLxr104Bncay+G/q5/3zrRNT+H1zWhE1vtFNHnIWoam+dp8gwD2dWl5m6F6juHU3eci33FLP3JnU8xv0k1Th1a4p/DOBLAEYB/DeAcgDfk1L+q7aDgBokkjEcpY8zowU2Syyd1zdePIDPf6wBQ8MjKCrMx6Y32vGtm+cY+hQXFuYpjxFwn+ju96HG40aT18NJdmqoKc4Qqr6w+uqGoH2a1+PGp+fXGep7jfopENuzOPJz1WVunPFdQGe/DxNLJyDfBZQXFdphFTtH1UwnkIzm16xPsereoeueYnY/ZuNJcP/W+xQDuFJKOSCE+ByAnwP4ewBvAdA6KCaExCeg1bXCyzGWzmvnsX7sPLYr7D2VT3Es8vNdmD2lArOnaAmZEEtQ9QV/yPOmrn4f1r9yGE+tviqqP6r6aby+a/S5FvaVrCcZza9Zn2JVTuq6p5jdj9l4UolT96C4QAhRAKAVwMNSygtCCH2PogkhaUelX1Ppua67ciI+t/AynDp7AZeWFODJN/8UU8+lw/uSkEyh6guRKRxP1xjaD7weN0b9Y/8zGdknYvUX9qXsJxnNr668MLsfs17zdshf3YPi7wM4CmAPgNeEEFMBDGg+BiEkTcTyrDTyF758YgmunVmLLz7x1kU/4uXNqFUMBnT5KROSKYy8vL/z6TnwS39wkBLPizW0H1QUF+LzH50a5jsc6BMAlP0l1nvsS9mDyjs+oKWN3F5fUawlL8zW6pERvymvebvcC7RqiqN2LoQAkCelHBn/+wtSysdT3W82a5AmT6lH54njSX8+r2ACRi+cT/rztXVT0HH8vaQ/n+XknD4ulqekkU7t7fdO4baNOwz9iI2kExaua59rUFOcQSI1jC4BfOGxaM/Yx+5YENeLVeU7/FLbYgBQ9pdY72WwL+VczUwHZrS0R/vOaskLs7Va5Vmv8prPwL0gLZriMOTYiHskZNMaACkPirOZzhPHsfL7yVs7b/7ix1L+PCEB4q07H6nb6la07xkw50Fp1br2hFhBpIZx+5GTQc/YUFR5HdoPVL7D75/xQcbwMI71HvtSdmFGS6urxprdTyyveaN5Ina5F1g6KDaAv+EQYlNU2uH5Uz1jbhLnR1A8IR+Pv9Gu1Kl5FXq36nLj9rHWtSfE7hjlNAAUj3sEJ+vFavTZfJcLFUUFwf5SNiEfM2vLcPrcMApcLkwsK7Tcm5zYAzPaW12e9bFqtRnP+hqP+XtBOrXG6R4Uc9IdITZEpeda0liFWz4yFV95ds9FjfCKMY2wqv3aFc144Ln9Ye2ba8qV7e++pjGqfZ2nKNOnhJCYqPpMYb7AN158B21LGrF+a7guOJ4X6/1P7w76DodqituWNOJvn9mNf7xhJu65phH/FNJf2pY04ru/+iPuXdKI798+D1984u2EjkmciVntbX1FMda1Nkdpe1X6dhUBP+7I/dR5igzjuXbGJMPjzqw2vhdcO2OSqf1bpTW2VFMcdTAhdkkp56a6n2zWIAkhMi6fSGdOOIys1cep9FxPrrpKqRE22v5S22JDP+IT/UOm9q/SnREl1BSnmXj+xF6PGzfNq0OeC1h6xSTMmnxJwl6sNeVunBwcxmuHejHqB3769gl09fvQtnQ6NrwWrTdetagBG19vx+a/XoiyogJLvMmTJGtrZqYwq71t7x3EnT9KXN9u9rix/JHrK4qjvObfO3XO1H5i7T9FWUX6NcUG/C7NxyOEJIBKz6XSCKu2q/yITe9foTsjxC7E8yfu6vcFNcUf+1Bl3MFppB70D91dwcU/AvgVuuGADrl7wIfZ9RXUEGcxZrW3PQM+U/p2s8eN548c6TVvdj/x9q8brYNiIYQHwNcALB7f9FsAa6WU/QAgpbxH5/EIySWs9IhU6bm8iu01JrXAKl1bjWq7x62M3w5eloSE5nToU+HLq8vg9bjR1T82uTSQ5+29g8GcrfMU4WDPALr6fairKII7Pw+9g+dRXJiP4dFRVJZMGNse0TfyhLHeeEZ1GaZWFqHGE93/2F+yC7PzMMzOCzGrTfZ69NwLVBpkr0etiVbFn0rO635S/EMA+wHcMv737QAeA3CT5uMQklNY7RGp0otdWV1mqPltqi4zbK/Sqam8NVtqPYa6sxlVZYbxL59Vi1+/+37GvSwJCeT0N18+iJXz68P0w2uWNmLT9mM4dW4YD392Lt7pOhPM2flTPbjlI1PxwHP7DT2J25Y0YvPO9/CVP5+Jf725BV9+dm/wvemTSvGdT8/B3z6zO6z9t3/5B9z9Z42YUVUWFqNdvF+JPlS1WlV76zxFpuaFqHKjzlNkOF/k8omlWu4FKp/lJq/HlP/ydTOr8cuDPUnnvFZNsRBit5RyTrxtqZLNGiRqim1NxvRxmfKI1KnzUnlrBp4Ih+rODnT1G+4/lpY5x38ypqY4A/j9Evs6Thvm6uN3LkBV2QRICXzqoYt9a/1n5gYHKCpP4oBG+MV7FuHs8EhY33C5BN5+71SU3tiof9vAB5yaYs3ouheYraV7jp9C21O7orTJ3/n0HNM12YzPsln/ZRP3prRoioeEEIuklK8DgBDi4wCGNB+DkJwjUx6ROnVeKm/N/HxXlO5MGb9NvCwJAcZy+tzwqGFOSkg0VJVi+5GTYe8PnR8J/q3yJA5sP3n2PBY2TIzqsycHz0fpjY36t128X4k+tN0LktiPkTY5mZpsxmdZtT1ZjXM8dA+KvwRg07i2GABOAfiC5mMQktWoPBzNeE3G8og0QqfOSwfK49LXmNgIv1+iuDAPbUunwy+B/3zr4lNbAYH23sGwvuL1uFFziTvYvqjAZZjnUkb3p9C6UFU6AVMri3Csbyjsc5H9W5dHLbEPZjXFyntBEvcU1bwTq3PMzD0x1XuT8ayb5BmQUs4G0AKgZdx+7YzmYxCStQQ0gDes34bP/GAHbli/DS8f6EZ9RTG+e8scuAvGumw8D9ImbznWtTaHtV/X2owmr8ewfUDnFbn/mdVlhvuZUWW83az3pQpl/DXluHdJIza+3o6Htx7Go9vace+SRm3HJSRRAn115YY3sf6VsVy8feFUTK0swpqljbhv827csH4b3uk6g4c/OxdTK4tw+8Kp+OITbwXblxbm4/5PXB6W521LGvHi3o6w/h1ZFz63cQfuvqYRUyuLgp8z6t+qfk3vYucS0BQnWgNnVpdh7YrwWhrwjjeTGzPH55eEHvfuaxrRZHI/ZjF7TwxokJONR7em+G0p5byIbW9JKT+s7SDIbg0SNcW2xnJ9XCy9WEBHlagHqZFWV+U+ARjrvI72nTX0uFx/61xDfZlZ78tYGMWv8rikppia4nSj6qvfvnk2/vmlg2HuE/9172IMnr9gqHV86q8XonRC/rj7RB4ujPpxacmEsP4dy0e8b/B8zP6t0mmmCWqKNZOMT/FXnt095j4xPIKiwnxseqMd37p5jql7is57k67vqzpugjlvnaZYCHEFgCYAHiFEqNNEOQD+TkNIgsTTixnprVQYaXVjodJtGenIVPoynVpFo/ipkSR2QZWLf+g5ExwQB7b1DvogFR7DvpFRzKmvwPTqcOeIRI414vfjz5u9MeNU6TSJM0nGp3jnsX7sPLYrbLvZe4rOe5MZkjluKjmvS1M8A8AyAJcAuDFk+xkAf63pGIRkPenQAOryplTFacYf2SzUSJJ0EquvqHIx0JVCvYuLC/Ix4veHaYsD7xUV5MPvlzGfrKmOVVSQh+1HTtJ/OEsxO79keHgUezv70T3gg7fcjVm1Hm0106yWWRfprvla7lRSyueklHcCWCalvDPk1SalTP63fEJyDKs1gCp9lt9vLJkJeFNG6tEun1hqqPmtLXNjy54OrNzwJr705NtYuWE7tuzpwMiI33D/ZqFGkqSLeH1FlYstdZ6gfnjj6+1Y/8ph3LJhO/Z39ONvrr086r2VG7bH7IOqY61rbUbbU7sS6sfEeajyr85TZFh7vaUTsGVvJ27buAP3/HgXPrdxB7bs7URtmVtLzTSrZdZFumu+bk1xFcaeDE9DyFNoKeVd2g6C7NYgUVNsa9Kij7NSA5iMx6XKm/Jvn9mdsGelyh85GTKskbQr1BRrJpG+YpSLAJTexWuWNmJyRXHQp1i1XyNCj1VUkIe2p3ZFuU/YUFtPTXGSxPKON6rJ3755Nm7/4e8Ndefz6itSrpmZ9Ly2qOanxaf4OQDbAPwawKjmfaeFyVPq0XnieNKfr62bgo7j72mMiOQaVmoAk/G4VHlTmvGsVPkjJwM1kiQdJNJXVLmo8i4+OzyKP/acSUoXH3qs7UdOhg2IE90HcQ6xfHiNa+95w/Y9Az4tNTOT8znSWfN1D4qLpZR/Z/ZDQohLADwKoBmABHCXlHK75tgSovPE8ZSftBKSCpnS5Brp12J5XKo8K422q/yRkyGVde0JSZRktYwjI34U5hn7D5cU5qGuoljpa7zn+GkMj46iMsJ9QldsJLNYOZ+jpnyC4fbqcvU8DzP3mkxpitON7kHxi0KIG6SUL5n83PcAvCylvFkIUQiApqMkJxkZ8WPLno6odeRbZ0/WMjBWrTuvWkf+2hmTsK61OSqe5nG/4MjtV457WT7w3MXta1c0Y2Z1uYazc1Fnl+y69oQkSn1FsWHux9JQBvrvQ1sPoW1JI9ZvPRT87D9+8goMXfDjy+PSiYAn8ead7+HWj9Tjvs27cerccHDb310/U5nXqn5Mbb19MVu7VNc44MMbuX2W14O1K5qjam9TdZnhPWVZkxcvHuhK+F4T0BSb6Q9ORLem+AyAEgDD4y8BQEoplXfE8dXvdgNokAkGY6UGSYemN5VzSk2xrbFcH6dap95qTa5qHfmX2hajvqI4Yb9gE+vOJ0UmdW02h5pizbT3Dhp6dMfy4g7tv6EOE1c3VkEI4HOPRuvtjXyNVy1qwMbX22PmtUO09dQUj5NM7VJdY9X2gPtE4El0S60HB3sGDGvyE3ctMNQgq+41WVh7rdcUSynVRotqLgPQC+AxIcRsAG8BWCOlPBvaSAixGsBqAKivr081VEK0oTM3lQP2lTIAACAASURBVOvUW6zJjacXS9QvONV15+NBn+LEYc1MDZVHd6xcC83/rn5f8LNN3nKUFxUk7GssRPy8drK2PhdzM5napbrGqu2FhXmYP+3SsG3Ke4pCg6y61+RK7dU6KBZCCACfA3CZlPIbQogpALxSyt/HiWEegHullDuEEN8D8PcA/im0kZRyA4ANwNj/WeqMm5BU0JmbSg2vRk2uEWY1imq9W5Fp3ZkOnV226dp0wJqZGqpcqyp1o7130DBfY/XfMndBwr7GjZPKMLWyKGvzOhdzM1O1Sz0vxFiDrLrX5IqmWM/snYv8bwAfBfDZ8b8HATwS5zMnAJyQUu4Y//tZjA2SCck5mrzlhh6UTV6Ppcc16wWpaj+jqhR3XxPuZXn3NY2o8xQZ7sesbzJ9ikm6UOXan/oGlfkaq/8GNMqR7xn5Gn/52T1p8YAl6SNTtWtmdZmh13xzjbl7TZ2nyFRtdyq6J9pdJaWcJ4TYBQBSylPjE+eUSCm7hRDHhRAzpJTvAlgK4B3NcRHiCPLzXWidPRmNk0rDNLy63CdUuFwC1zfV4Iq2xQlpFFXt93WcDk70AMZ+Xnvguf2YUV1qqFM72nc2OGEk0P7+p3fjCoVOzWychCSLUa65BHD997Yp8zVW/23vHcRDWw9h1aKGoEb5oa2H8PidC7D+1rlhuk/fBT++umU/5tVXZNVP07lMpmrXif4hPP3fx/Ctm2djaHgERYX52PRGO+ZPrTB1rznYM2CqtjsV3YPiC0KIPIzZqgUW80hkKat7Afyf8QF0O4A7NcdFiGPIz3dFaXjTgVmNolF7s5ponTo7QnQTmWvbj5yMm6+q/qvSKHcP+CAlckKvmetkonb1DPiw81g/dh7bFbZdNV9ERTrmu9gB3YPi9QB+BmCSEOKfAdwM4KvxPiSl3A1gvuZYCCEGqDS8Pt8I9nX1o3vgPGrKJ2CW1wO3O9+U5tesJtrpGuFs80zOtu+TLIHz0Hf2PArzXDg3PIpJZW6UufMNPYYTydd4ue7kfpAunJ6fZuPX4Vmvq8bGqu1WeuvHwop80O0+8X+EEG9hTAIhALRKKQ/qPIbtceVDCOd0UpJbqLwyr5k+ES/s78YDz4d4XC5vxo3NNXj18MmEvTUDmspIL0uVTs3JfqvZ5pmcbd8nWQLn4ZsvH8TK+fVhXsNrljbimZ0novyEE8nXWLk+PDyKtcubo/pfLQfFQZyen2bj1+VZr6vGqmr7jCpjH2Rd3voqrMoHrT7FACCEqAAwBSEDbinl2zqPYXefYqd/nj7FShzvuanymtx01wJ83sCzUrU9ljdl4KlBoppoh/itRmEz386UfYpt9n0yRuA8BLyCI8/HqkUNeOTVw0FP11mTL0k4X1W5vvPoB/jbZ3ZHeSJ/59Nzoiy2HIa2mun0/DQbv07Pel011qi2H+jqt9xb3wgN+WC9T7EQ4hsA7gBwBOO64vH/LtF5HEJIcqg0vD0Kz0rV9lhaR7OaaKdqhLPNtzPbvk+yBM5DwCs4lMD2wL+HLoyaGlyocr1boTfuGfCBjOH0/DQbv04Nr64aa1TbM6U1tiofdGuKbwHwISnlsOb9EkJMYqS3UunLqhWelartk8rcSj1Xruj+0qGHTue5TOT7GMUDwDHXO5HzGTgPQLjO1+tx49Pz6zCtsgSP3/URnD43jAKXCyMj/rBfQsxeM79forpM1f8onwgQKz+dUIvM+vyqPN9rPO7gynXdAz54y92YVetBYWFemr5JdJwqrbGV59+q+qt7ULwfwCUA3te8X0KICVR6q2tnTDLUhTXXlBlqGptqSrF2RXPQiifgcVlb5jbc/3Uzq/HLgz05ofuzWg+dbg1lvO9jFM/Dn52L4RHpiOud6PkMnIdvvnwQbUsasX7rIVQUF+LzH52K771yUV/ctqQR3/3VH3HvksagftLsNQu0/+HrR/DgsiZ8/cUDYf2spdZaf3InocrP+opiR9Si+opi3LukMar2qryoZ1aX4e5rGqNqb+PEEmzZ2xm1vbWlNiMDY5XWeGZ1uaX1y6r6q1VTLISYD+A5jA2Ozwe2SymXazsIqCm2+vPUFCtxjKZYpbfavHoh2p7aFaVdfOyOBagtc2NfVz96Bs6jetx94t3eM4btv/PpObht4w7D/Rvpy7JV92elHtpkLClrioHY38conral07HhtWjdrR2vt5nzGTgPH5w9j4K8sadRX3gsWlsf0B0H9JNm8ye0fcvkcvzV1R+Cb3gEl00swezJl2Ts6Z9GtNZMo/w82ndWWevsVItSyY3Q9k/ctQC3G8zzeHLVVRnTnxtpjd87dc5yDXiK9dd6TTGAxwF8E8A+JOZPTAixAJXeqqvfWLsY0GF95LLKsO2q9t0x9p9Luj8r9dCZ0FDG+j5G8fgd5K9r5nwm6k8c0B0H9JNmr1lo+70dA2j7yZiX7FOrr8qGAbF2jPIzVq2zU26mkhuh7buV8z8ypz830hqno35ZUX91D4rPSSnXa94nIcQkKr2V12NOl6fUtSWxfydgJ99kO8WiiidPOMdfV3U+BQTaewfDnjJF9oVJZcaflTLchztR3Whg/0MXRrFm6XQ8vXPM8ziwXzueP7uSTK3LBGY10ar2Ncr5H+rvlQlttVkNtV3QbSK3TQjxL0KIjwoh5gVemo9BCIlDfUWx4br2M6vL8d1b5oRtD9Xl3bB+Gz7zgx24Yf02vHygGzOqSg3Xu2+qLjPc/+UTxzTIodvXrmhGnacoMyfCJAGdWuT5yYRvsp1iUcUzq85jqxhjYRT/mqWNuG/z7mC++/0yqPMN7QsnTp+Nyve2JY14cW8H1q4Y61fARd1oaH+5d0ljmG40dP93/Wgnvv9aOz7/0anBQZxdz59dUfWTJq+9clMVp6r21lcUG7a/sqYUa5dH1Njlzbiy2vhpqVE+B3LdShLpC3ZEt6b4VYPNUkqp1ZKNmmJrP09NsRJHaYrv/NHvDbXDAR1eKro8lTb5O5+eY+i3uv7WuZZ6VurETr7JJmLRoilOJh4Atjlf8QjEf6zvLHYdP41nIp7QvtS2GAAMtdPP7e7A3153Bbr7hzCjpgynzw1DCBc2vdGOb908Bw1VpQnpRlVtHr9zAarKJtj6/CVBWmqmqp/YqS+r4lTV3pfaFhvW6rffO4X/9fN38PmPNWBoeARFhfnY9EY7/v6TVxpqijPl7+wAX2nrNcVSymt07o84j8lT6tF54njSn6+tm4KO4+9pjCg36VH4ngb0XKnq8mJpjQ23W+xZqRM7+SbbKRZAHY+dYoxFIP6eAR/WvxKeowG9ozTQSfslcKxvCH/sOYOHt4Z/DrjYrxLRUaraSEhHnEM7ospLJ/SfeDkT2b57wIedx/qx89iusM+oNMWZ8nd2qq+0lkGxEOI2KeWTQoj7jd6XUn5Xx3GI/ek8cTzlJ9XEGJUuzGjd+Vh6LjP6NZUHpUqv51Xp4DzW68js5EmqwgkxBgiNtbgwH8Ojo6gsyY4nmaH57vW4cdO8OuS5gOLCfLjE2JNhvwRee/d9LL58EuorirBm6XQU5rsM87uq1I323sGENMJ204o7CaNaZ+VSwrpR1V4ztVpVY1Wa4kzlm1PzXNeT4oBIp0zT/gghIcTyHX5+X2eUR+SyJq+hJ2adp0jp6Wnk+djkLVds9xhun1XrMfSsbPJa67eabk/fZHBCjAGMYm1b0ojNO9/D310/05YxmyHUi3jl/Hqs3zrmP7zhtXasWdqIZ3aeQGG+wJeunh7mHfyPn7wCf3Pt5fi3X/8x7Br+qW8Q9/x4V3DbmqWN2LT9GE6dG47SsVrtb52tjIz4sWVPR1RtCXhE251YNdxMrf6z6ZXGnvLVxsOvTOWbU/Ncm6ZYCJEHoE1K+W9adhgDaoqt/XwqOaHj/NlY05wxTbFKn/XkqqsM/YJV22N5dxrp12Lp8lTbjTwrrb5pOUC/ZnWMWjXFqlgDvrx2Oq/J4vdL7Os4bdgfVi1qAABsfD3ag/nxuz4Cd34ezg2PorrcDZcArv+eOY2w3bSuFqKtZu45fko5v8EJ8xViecervpfR9idXXWV63kam8s3meW6tplhKOSqE+AwAywfFhOQaas9Kc9vjeXea0eXF2l7mLsC54VGUuQu0F0Gjn1CT0a+ZkTLo+NnWSRo7VawBX953ugZwxjeCJu+Y64ITf9J2uQTODY8qv2fg35HvnT57AX/ePDG4TeVhfOrcMKrKJiiPbSetqxNQ1a5Y8xXstBxyMvM2VLU92Xkb6X7e5MQ81+1T/DshxMMANgM4G9gopXxb83EIySmUml+z2xUaYV06L6slAqqfUOfWXWLqe5mJU9fPtk7S2MXz5T3YdQb/45k9WNfajAn5Lnz52b2O/ElbdU2kBITCgzlSH6/ax76OAdy3ebdtJTJOQ1W7VFra4eFRWy2HbNZPWfV9VR7xqnkbTpJt2QHdVWsOgCYAawF8Z/z1bc3HICTnUHlcBjS8odvXtTZjVq2xR2dAI2yVd+fRvrPB4guMPdm4/+ndONp3Ns4nE+NAV39wcBrY/1e37MfQyKip72UmTtUxD3T1m4rdbr7DschzAWuWNhr68rYtacRP3z4RPA+H3h9M+dxkCpV38U/fPoEX9nREeW4b6eON9hF6jnTmfy5TmA88eGNT2Hl+8MYmTCgwHtjt7ewPDoiBsdx84Ln92NuZmdw066esqtUtipqvmrdhdU3ONmjJRogDcLkErm+qwRVti6P0Wa2zJ6NxUmmUhlfVXrVdB1ZLBFQ/KXacGjL1vczEmczPtkZYfe510tXvw6btx7BqUQMm5LswbWIJpPRjWctkPPHmsaCzgu+CH5FrACRzbjJF5DWpKnUjzwXMrb8Ek8rcqPMUYUZ1dN9S7eOPPWewr2Mg6hzZUSLjNI71DeEnO47hWzfPDvrzPvraEVxaPB0zvZdEtVdJyDK1HHKs/m92u6rmG+Ek2ZYd0DooFkJUAngQwCIAEsDrANZKKft0HoeQXESlzzJadz5Weyt1XlZLBJQ/KXrcpr6XmSVIYx3TLE7R2FWXu3Hq3HCYbnHN0ul4cW8HbppXF3bOIsf06bLg04XRNZk28eK/jfqWah8AcN/m3Zblfy7j9RSh33cB73afCeZfv++CMtfMWpelg2TmZ5ip+UY4SbZlB3TLJ54C0AvgLwHcPP7vzZqPQQixKVZLBJq85aZ+OlRhZglSXcd0EkbXcd7US4yX/K4tz6lzEwsnSWScxszqMsP8CyyxHcmsWo/hkvMttbmVm8xJc+ieaOeVUn4j5O91QoiVmo9BCLEpVksE8vNdpn46VPHeqXOGOuF59RWGT2V0HNNJGF1HKYEvPvF2lEbzxXsWYfPqhTlzbmLhJImM0zjRP2SoEZ4/NbrPAkBhYR5aW2rRMLEk6DDTkkH3iUzBnDSH7kHxL4UQtwJ4evzvmwH8QvMxiJW48iEEOwtJHqslAmZ+OlRhVmen45hOI/I6qqzHTp49j4UNE3Pq3MTCKRIZp5GMNrawMA/zp12ajvBsDXMycXQPiv8awH0Anhz/2wXgrBDiiwCklNL4dw5iH/wjXKY5R3HKEsSqOM3Eb7XOzinnMhEC38UlRM5oE7Pp+jkRM0vRZ2P+JQvzNnV0u09wmWdCHIhTvCxVcV43sxq/PNiTcPxWLkHqlHOZCKHf5fJJpXjwxiZ8/YWLyx6vXTG2HG02kU3Xz4mozv+SxiqsXdEc5TucbfmXLMxbPWgXfgkhWoQQy4UQNwVeuo9BCNGLU7wsVXEe6Oo3FX9AZ/dS22I8tfoqvNS2WNvNwynnMhFCv8viyyfhP357GKsWNeCeJdOxalEDHnn1EA72DGQ6TK1k0/VzIqrzv797AI+8eijr8y9ZmLd60G3J9kMALQAOAAj8xiEB/FTncQghenGKl6XZpVJjxW+Vzs4p5zIRQr+LEEh6eVknkU3Xz4nEWtI+F/IvWZi3etCtKV4opbxS8z4JIUlgJ41tMqh0hUb+wqqlUmPFrzo/w8Oj2NvZj+4BH7zlbswyOWPdjucyWSK/S+Dcl7nzMPmSYhzrO4uJpRNw9OQguvrHzmN9RTHeO3UuLbpGKzSU2XT9nIjq/NeUuzF/qgef/1gDhs6PoHhCPh5/ox01HjdGRvw40NWPrn4fvJ4iNHnLkZ/vUm63m/ZWRzzMWz3oHhRvF0JcKaV8R/N+CSEmMKsvs1Jjmwyq+K+dMQn3LmkM2qkFfHEvn1hqSm8YS7f4/P6uqP20ttQmPDC227lMhTpPUfC8vvbu+/jS/zMd//Hbw1g5vx5ffnZP8PutWdqITduPoTBfRF0fq3SNVmkos+n6ORHV+b+yuhS3zJ+Kr4Tk3drlzZg+sRhb9nRE1YRlTV68eKAravvyWbX49bvv20Z7qyuPmbd60D0o3oSxgXE3gPMABMZcJ1o0H4cQEgOVvuyKtsWGP6XZzctSFf/m1QsN/YWnVZYE9YZCAFICj7x6CDOqSzF7SkXC+3/irgWGXqgNE0sStnay27lMhYM9F3WcCy6rwBefeAurFjVg/dZDYefoe6+MtQEQdX1i5V0qmM3xRMmm6+dEVOf/7fdO4YHnI/rm8/sxbeICw5ow9dJiZa2wIm+SRVceM2/1oHtQvBHA7QD24aKmmBCSZpLRl9nJy9Ksdtis3lCtWzxvuL1nwGcqfjudy1To6r94XhsnzYHvgh9CwPAcBeQs6dI1WqmhzJbr51SMzn+34nr3KPqsqi+r9pMp7a3OPGbepo7uQXGvlPL5ZD4ohDgK4AyAUQAjUsr5OgMjJFPo0q85RSNs9vua0w4XmdYbmvE8rSmfYLi9ujw3dHmh58rrcaOqbAL+8ZMz4L2kGAV5AmuWTkdRYZ7hOZJybDJeuvIuXo4bXXcAttKSksTxKmpCdfkEw+2qvlwTI2+s1hobaZypBbYXugfFu4QQPwbwAsbkEwAAKWWi7hPXSClPao6JkIyhSy/mFI2w2TjNa4dLDLXDM6tLDPWGl08sVfoaG52fWV6P4f5baj2Wnjc7EHotKooL8fmPTsVT//1elH74y38+A//yF7PwDz/bF3Kum/DmkZN46/hprGttjtIUW5F3sXJclVeF+QL3/HiXLbSkxBwzqotx9581BiUUgT4+o6YEd1/TGNVnm2rKDPtyc025Yd7UVxRb6vM7MuI31D4vn1VLLbCN0D0oLsLYYPi6kG20ZCM5iy69mFM0wmbj1KUdvqyy2FBv2FBlrB8M+BIbnZ/Wllo0TCwJPi1qMek+4VRCr8VN8+qCOuFI/fC//uJdrFnaGH4NfnMY//qXs3HP0stRX1GMefUVluddrBxv7x00vO6rr26wjZaUmOOd7rNKTbHRPIAZ1aWGtWL+1ArDvLFKox7gQFe/YU1rnFRKLbCN0L2i3Z2pfBzAL4UQEsD3pZQbQt8UQqwGsBoA6uvrUzgMIXqJlZu69GJO0QibjVObdjhJ/aDR+SkszEt4Up2dMVszIz2JY+mHzw6PRl2D3sHzWNBQCQBpyztVjqvyyi8RtY0+ruknmfu5Sjus2h6qhw9F1fet9vlV1rR+H2ZPoRbYLmhd0U4IUSeE+JkQ4v3x138KIeoS/PgiKeU8AJ8EcLcQ4urQN6WUG6SU86WU86uqqnSGTUhKxMrNgF4slGT0YrH24/dLtPcOYvuRk2jvHYR//M6v2m4lseIcHh7FzqMf4MW9nXjr6AcYHh5Vtg9ohyO31yjaB/SDibbPBb2e2ZoZeS0C/zY6f5EPseymu1bllVHcunMhE/3OacTLTeNaYdzHVdsD3uWR21XXW1etVqGsaR779JsAuZzDupd5fgzA8wBqx18vjG+Li5SyY/y/7wP4GYAFmmMjJO0EdI+hA4xk9GKq/QR0cDes34bP/GAHbli/DS8f6MbIiN9wu9XFrb6iGOtam8PiXNfaDG/pBGzZ24nbNu7APT/ehc9t3IEteztRW+Y2/F5N3nLD7S21HsP9z/Iab2+p9Wg5/7lAaI7951snsGZpI17Y04G2JY1h5+/+T1yOyuLCsG12012r8rClzmNpLgS0zOnud9nE8PCoYa2YWVOCtcvDr+na5c1oqilV1BBzfV9XrVYxs3pM4xzZb2ZWl2vZvy5yPYd1a4qrpJShg+AfCSHui/chIUQJAJeU8sz4v68DsFZzbISkHV3aXtV+YmlyM+HF+d6pc3hoa7iO76GthzD10mKl/6/q/Cg1v7Mno3FSKbr7fajxuNHk9SA/36XcTr1eYkSe85pyNz7+oUq8dewUvn/7h3H+gh/7O/vx2O+OAgBWLWpAngtYNH0i5ky+xFa6a1UePn7nArxkYS5YrUvNBfZ29hvWissqF+CP3afwozsXoPeMD1Vlbvz6QAfmTzPWCJutvVbPwzjRP4Sn//sYvnXzbAwNj6CoMB+b3mjH/KkVtsqNXM9h3YPiPiHEbQB+Mv73ZwD0JfC5agA/E2N+KvkAfiylfFlzbIRkBF3aXqP9mNXkWq2f7DGp+e0Z8CnPj2p7fr4Ls6dURPkPq7bTuzNxIs/V9iMn8fUXDwIA/n3lHKx/5eJ1DVzjGdVlthoQA7Hy0IeFDRMtywWrdam5gGoeQPfAeTz6u+N49HfHw967tqlWOT/AbN+3slb0DPiw81g/dh7bFbbdbrmR6zmse1B8F4CHAPwbxibOvQHgjngfklK2A5itI4DJU+rReeJ4/IaEZAEqj0uVn6/VWtpqlV+wRv9fI6/P/HzdSjAChF/PwnGf4qd3nkBX/9hiJu4CF6rKJmBkxB+8BlZ7vSYad6byn56zqeGN4SF+3ZUT8bmFl+HU2Qu4tKQAT775p7T4C+vAKbnhlDitQvegeC2AL0gpTwGAEOJSAN/G2GA5LXSeOI6V338j6c9v/uLHNEZDiLWovFoDmtx0e1/WeYpwy0ci/IJXNOPKmlKsXd4c5THaXGNOT6fy+mydPZkDYwswup5rljZi0/ZjOHVuGA8ua8K3Xj6IWxdMRevsyXC5hKVer4mSKZ/uTB03m2iqKTesFTNrSnDtzFp88Ym3wrZ7SyfYIufi4ZTccEqcVqF7UNwSGBADgJTyAyHEXM3HIISME0sHlwkt7cGeAYV2+Co8vdNATzetAg3uxH+Si+X1OXtKhSXfKZcxup7fe+UQ/vdn52FweBSPvnYEezsGsL9z7BqUuQtsoUfMVP5n6rjZROcZn2GtuGyisRf5ZROLbZFz8XBKbjglTqvQPSh2CSEqIp4U6z4GISQEs5pcK4nlL6xDTxfb6zP5uIkxqvP99vHTeHjr4bBt3f0+nBsetY0eMVNacmrYU0OlvVV7kRtvt6MG1im54ZQ4rUD3gPU7ALYLIZ4Z//vTAP5Z8zEIITZFpWWuiaFTM6MRVu7fhl6fTsfvl6gqNdaCG/n91njcKHMX5LQekaSOStOqmpeg2s6cI8mgVYQnpdwE4CYAPeOvm6SUT+g8BiHEvjR5y035Bdd5irBlTwdWbngTX3rybazcsB1b9nRgZMRvav9NXvt45GYDAa/Sf/n5O3hwWVPY+f7nv5iF6ZNKDf1WrfZ6JdmPKoeaasoUPsVlzDmiDe3SBinlOwDe0b1fQoj9MesXvK/jtCmNcKz9E32EepUOj4zpO33DI2ioKkVlSSHu+NHvwzyAH3n1UNBvNZf1iCR1VJrWfR2n8chvwr2nH/nNIcyoYc4RfVDvSwjRihm/4GQ0wqr9E32EepXu7RhA20/G9J1Prb4K3QoP4ICGM5f1iEQPqlph6D3d78PsKcw5ogcOigkhacHIS9TrKcLUyiIsa5kMMf5g54U9HTE1wmY9SZ3gYZopVOcmVNfZMrkcf3X1hzA0PIKCPBfcBS5qOEnaiVUr2MeJLjgoJoRYTkCjGul9uaSxCndf0xi0/QrVp5rZj8qT1Gz7XCLWuQnoOn/4+hH85bz6MJ/iry9vwv+8YSb++aWDOeljSjLD5RNLcPefNUb5FzdOLGEfJ9qgEI9kFZOn1EMIkfRr8pT6TH+FrCRUowpc9BJ9t/eMoa/xif4hU/s52ndWS/tcIta5Ceg6//6TV+LrLx4Ia/Pg8wcwsXQCVi1qQNvS6di8eiEHIMRyDvScMfQpPtB9hn2caINPiklWwRUN7UmoRjWA74JfqSlWeYyq9qOrfS4R79y4XAInB409YAd8F4Lazo99qJIDYmI53Yp8dZJPMbE/HBQT4hCcrJtTeY+qfIdV+lTVfnS1zyXinZtYPsVFhflR7QmxEm8M/2IjrTHzkiQD5RPEXrjyU5I/ZCsB/ecN67fhMz/YgRvWb8PLB7rh98tMh5YQSu9Rb7kpj1GzPrj0zVUT69wE9cbP7EbbksawNg/e2IRHXzvCc0nSyqxaD9auiPApXtGM5ppy3LukERtfb8fDWw/j0W3tuHdJI+orijMcMXEifFJM7IV/hPIHA1T6zyvaFjviJ0KV92is7Wb3o6N9LhHr3LT3Dgbz7Yk3j2HVogbkuYCrG6tQVVaIyyYW81yStFJYmIfWllo0TCwJ/lrWUuvBif4hQ6/zefUVjqiNxF5wUEyIA8gGbazKv9asr63V7XMJ1bkJzbeufl+YfnhqZSmmVvJckvRTWJiH+dMuDduWDbWR2AcOiglxAHbUxqo0zvQRdj7V5W5DnWZRQR78fsnrQzLC8PAo9nb2o3vAB2+5G7NqPbasjcS5cFBMiAMI6D8jvTgzpedUedxeN7MavzzYQx9hh1PnKYryj/768iY88uof0Tq3nteHpJ3h4VFs2dsZ5Wm+vNlrq9pInA0HxYQ4ALtpY1Ua582rF5rSPjtdK52tHOwZiPKPfvD5A/jWzbN5fUhG2NvZb+hp3jCxxFa1kTgbDooJcQh20sZmyneYpAfVdRwaHuH1IRlB5VPcM+CzVW0kzoaDYkKIaTLlO0ysIVLXrbqORYX5vD7EcozmGah8iqvLmYtEH/QpJoSYRuVxO7O6DOtaw71E17U2Kz1D6SOceYw8sE8PnY+6jg8uY1yK1QAAIABJREFUa8KmN9p5fYilqDzZm2rKDX2KW2o9GY6YZBN8UkwIMY1K43y07ywe2noIqxY1QAhASuChrYeUnqF200rnIka67i8+8TZ+cd9ibF69EF39PkwsnYB8F/Ctm+fw+hBLUc0zeKltsaFPcWFhXoYjJtkEB8WEkKQw0vH1DPhwrG8o6GsbIJYGlXrAzBJLH76wYSJmT8lQYCQniTfPINKnmBCdUD5BCNFGQCMcCjWo9obXjNgJ5iPJJBwUE0K0QY2w8+A1I3aC+UgyCeUThBBtUCPsPHjNiJ1gPpJMwkExIUQr1Ag7D14zYieYjyRTUD5BCCGEEEJyHg6KCSGEEEJIziOklJmOwTRCiF4AxzIdxzgTAZzMdBAxYHypERrfSSnl9bEax8lNu39X3eTS9830d42ZmzaomZk+P6ni9PiBzHyHRGvmWTj//JohG/LJDHb8voa56chBsZ0QQuyUUs7PdBwqGF9q6IzP7t9VN7n0fXPpuyaD08+P0+MH7P0d7BybFfD72hfKJwghhBBCSM7DQTEhhBBCCMl5OChOnQ2ZDiAOjC81dMZn9++qm1z6vrn0XZPB6efH6fED9v4Odo7NCvh9bQo1xYQQQgghJOfhk2JCCCGEEJLzcFBMCCGEEEJyHg6KCSGEEEJIzsNBMSGEEEIIyXnSMigWQuQJIXYJIV40eO8OIUSvEGL3+Ouv0hETIYQQQgghAfLTdJw1AA4CKFe8v1lKeU+aYiGEEEIIISQMy58UCyHqAHwKwKO69nn99ddLAHzxle5XXJibfGXoFRPmJV8ZesWFuclXhl6GpONJ8b8D+AqAshht/lIIcTWAPwL4Gynl8cgGQojVAFYDQH19vRVxEpIUzE1iR5iXxK4wN4ldsfRJsRBiGYD3pZRvxWj2AoBpUsoWAL8C8LhRIynlBinlfCnl/KqqKguiJSQ5mJvEjjAviV1hbhK7YrV84uMAlgshjgJ4CsASIcSToQ2klH1SyvPjfz4K4MMWx0QIIYQQQkgYlg6KpZT/IKWsk1JOA3ArgK1SyttC2wghvCF/LsfYhDwSgd8v0d47iO1HTqK9dxB+v1ISQwghlsA6RJwE85WYJV3uE2EIIdYC2CmlfB5AmxBiOYARAB8AuCMTMdkZv1/i5QPduP/p3fBd8MNd4MJ3b5mD65tq4HKJTIdHCMkBWIeIk2C+kmRI2+IdUsrfSCmXjf/7gfEBceBpcpOUcraU8hop5R/SFZNTONp3NtixAcB3wY/7n96No31nMxwZISRXYB0iToL5SpKBK9o5gJ4BX7BjB/Bd8OP9M74MRUQIyTVYh4iTYL6SZOCg2AFUl7vhLgi/VO4CFyaVuTMUESEk12AdIk6C+UqSgYNiBzCtsgTfvWVOsIMHtFHTKksyHBkhJFdgHSJOgvlKkiEjE+2IOVwugeubanBF22K8f8aHSWVuTKss4WQBQkjaYB0iToL5SpKBg2KH4HIJNFSVoqGqNNOhEEJyFNYh4iSYr8QslE8QQgghhJCch4NiQgghhBCS83BQTAghhBBCch4OigkhhBBCSM7DiXY2we+XONp3Fj0DPlSXc5YsIcQesDYRu8BcJFbDQbEN4BrthBA7wtpE7AJzkaQDyidsANdoJ4TYEdYmYheYiyQdcFBsA7hGOyHEjrA2EbvAXCTpgINiG8A12gkhdoS1idgF5iJJBxwU2wCu0U4IsSOsTcQuMBdJOuBEO4swM0uWa7QTQuxIZG2qKnUjzwXs+FMfZ/8Ty1DdP3mfJFbDQbEFJDNLlmu0E0LsSKA2Tass4ex/Yjnx7p+8TxIroXzCAjhLlhCSbbCukXTAPCOZhINiC+AsWUJItsG6RtIB84xkEg6KLYCzZAkh2QbrGkkHzDOSSTgotgDOkiWEZBusayQdMM9IJknLRDshRB6AnQA6pJTLIt6bAGATgA8D6AOwUkp5NB1xWUU6ZslyDXhiJ+rqp6LzxPGE2tbWTcGJ945ZHBFJhlh1hbP/STqIlWe87xGrSZf7xBoABwGUG7y3CsApKeV0IcStAL4JYGWa4rIMK2fJcg14Yjc6TxzHLf/xu4TaPv2lj1scDUmGROoKZ/+TdGCUZ7zvkXRguXxCCFEH4FMAHlU0WQHg8fF/PwtgqRCCGR4Dzs4lhOiGdYXYGeYnSQfp0BT/O4CvAPAr3p8M4DgASClHAPQDqIxsJIRYLYTYKYTY2dvba1WsjoCzc+0Fc5PYEbN5ybpC0kUyNZP5SdKBpYNiIcQyAO9LKd9KdV9Syg1SyvlSyvlVVVUaonMunJ1rL5ibxI6YzUvWFZIukqmZzE+SDqx+UvxxAMuFEEcBPAVgiRDiyYg2HQCmAIAQIh+AB2MT7ogCzs4lhOiGdYXYGeYnSQeWTrSTUv4DgH8AACHEnwH4H1LK2yKaPQ/gCwC2A7gZwFYppbQyLjswMuLHga5+dPX74PUUoclbjvz8xP4fhbPACSG6iawrNeVujPqBHX/qiznTn44AJB0kc99L5T5LcpN0uU+EIYRYC2CnlPJ5ABsBPCGEOAzgAwC3ZiKmdDIy4seWPR346pb9wVm061qb0Tp7sqmBMWeBE0J0Eqgr0ypLEprpT0cAkk7M3Pd03GdJ7pG2zJBS/ibgUSylfGB8QAwppU9K+Wkp5XQp5QIpZXu6YsoUB7r6gx0VGJss8NUt+3Ggqz/DkRFCSOIz/ekIQOwK77MkGfi/Sxmgq994Fm13P2fREkIyT6Iz/ekIQOwK77MkGTgozgBeT5HhLNoaD2fREkIyT6Iz/ekIQOwK77MkGTgozgBN3nKsa20Om0W7rrUZTV5PhiMjhJDEZ/rTEYDYFd5nSTJkZKJdNjI8PIq9nf3oHvDBW+7GrFoPCgvzDNvm57vQOnsyGieVorvfhxqPG01eT0zxP2d4p0a888fzS8hFVDP9AaC9dxB9Z8+jMM+Fc8OjmDGpFM9+6aM4cWoIXk8RZlaXsS85kFg10C71URWHymVi+axaTKssCbsvc5Jd+jCbN3bIMw6KNTA8PIotezvxwHMXZ7muXdGM1pbamAPj2VMqMHtK/P1zhndqxDt/PL+ERBM50z/QT7758kGsnF+P9VsPBfvLmqWN2LT9GArzBe5d0hg24599yf7EqoEAbFEfVTFeO2MSnt/XGeUysXxWLX797vsZjztXMXtftct9mP/LpIG9nf3BATEwJuZ/4Ln92NupZ5YrZ3inRrzzx/NLSHwC/WRZy+TggBgY6y/fe+UQbppXh2Utk6Nm/LMv2Z9YNdAu9VEVx95OY5eJvZ39tog7VzGbN3bJMw6KNdCtmIHdM6BnlitneKdGvPPH80tIfAL9RAgY9hchoHyPfcnexKqBdqmPqjhU91/VduZiejCbN3bJMw6KNeBVzMCuLtczy5UzvFMj3vnj+SUkPqH9xKi/BNYhZV9yHrFqoF3qoyqOGsV21X2ZuZgezOaNXfIs4UGxEKJRCPGsEOIdIUR74GVlcE5hVq0Ha1eEz3Jdu6IZLbUXZ7n6/RLtvYPYfuQk2nsHMTLiD/vb71evbM0Z3qkR7/zx/BISn2mVJfj+7fPQ7C3Hv9w0C2uWTofX4w5qin/69gm8sKcjasY/+5L9iVUD7VIfp1WW4OHPzkXb0um4Z8l0rFk6HQ9/di5aaj2GLhOzaj22iDtXMZs3dskzMxPtHgPwIIB/A3ANgDvBJ80AxibNVZcX4ts3z8bZ4RGUFOajrCgvOMvVSEC+rrUZD209hGN9Q3EF5cms+U4uEu/88fwSEp+RET96BobDJhR/Y0Uz5tVfgjyXwNz6SzCpzI36imLMq69gX3IQ8WqgHeqj3y9x+twFbHitPew+6nIJQzcnl0ugMF9g9dUN8EvAJYDCfOZhujB7X7XLfVhIqX5CGdZQiLeklB8WQuyTUs4K3WZphAbMnz9f7ty5M92HVdLeO4gb1m8L08O4C1x4qW0xGqpKle+vWtSAR149HNWe2Ja4vdNuuZkuXC4XbvmP3yXU9ukvfRx+vz9+Q2KGmLmpIy93Hv0At23cEVXHnlx1FeZPuzSlfZOsRVvN3HP8FFZueDMq/zavXojZUyqi2se7L5OcxzA3zTzpPS+EcAE4JIS4RwjxFwCYWUh+IpcQxu0JIcRuWD2hmJBYmF222S4Tt4izMDMoXgOgGEAbgA8DuB3AF6wIymkkO5Er9CE9JwAQQuyM1ROKCYmF2WWb7TJxiziLhAfFUsr/llIOSilPSCnvlFLeJKV808rgnEIyE7nWtTbjxb0dhu0JIcRuJDKhmBCrMLtss10mbhFnEXeinRDiBQBK4bGUcrnWiNJEqssJRn7+upnVeMnERC5ORomNHZZ7JCTbSaSfhbZZ2FCBJ1ddFWzfEmM5e2I/nFxX8/NdWNbkxdRLi9E9cB415RMwy6tettkuE7dI+kklzxNxn/h2auHZj1SXE4z1eZWAP3LJVABRf5Mx7LLcIyHZTCL9TNXmk81e9kWH4fS6OjLix4sHuqKWc26dPTnmwJj32dwi1TyPK5+QUv421kvLt0gzqS4naJflCLMVnl9CrCeRfsa+mD04/Voe6DJezvlAV3+GIyN2ItU8z8nFO1KdlcpZrdbC80uI9STSz9gXswenX0uz7hMkN0k1z824TzwG4P8HMIKxxTs2AXjSxOdtQ6qzUjmr1Vp4fgmxnkT6Gfti9uD0a2nWfYLkJqnmuZlBcZGU8hWMLfhxTEr5NQCfMvF525DqrFTOarUWnl9CrCeRfsa+mD04/VqadZ8guUmqeW5mRbs3ACwC8CyArQA6APwvKeWMGJ9xA3gNwASMTep7Vkr5YESbOwD86/j+AOBhKeWjsWLRsTpTYHZisrNSh4dHsbezH90DPnjL3biyugx/PDmIrn4fvJ4izKwuw4n+oYRnPzp5VrAVpHp9LIIr2inginYZJ6kV7WL1s5ERPw509aPrtA+Xlhbi3PAIKooKUTwhH6eHhlGY58K54VHWKweRgbqqtWYODV3Avu4B9AycR3X5BMyqKUdRUcHFXB2//zZ5y5WT72LB+3B2kGCeG17YRNwnAoQu3vENAEsQf/GO8wCWSCkHhRAFAF4XQvzcwN94s5TyHhOxpEwqs1JHRvx4fl9n2CzYtcub8fTOY9h5rB9TK4tw9zWNeOC5i+/Hmv3o9FnBVsBZw4RYj6qfjYz4sWVPR1iNe/DGJrw/4MMjvzmClfPrsX7rIdYrh+Hkujo8PIoXDnSH3VfXrmjGjU01+K93uk25UhjB+3D2kEqem168A8AAgLZEFu+QYwyO/1kw/krs0bSNMZoF+8Dz+/H5jzUAAJa1TA523MD7sWY/On1WMCEkuzCqcV9/4QCKCwuwrGVycEAceI/1iljN3s7+qPvqA8/tx77uAS2uFLwPE8Cc+8R8IcQ+AHsB7BNC7BFCfDiBz+UJIXYDeB/Ar6SUOwya/aUQYu+4u8UUxX5WCyF2CiF29vb2Jhq2JahmwQ4NjwAAhICp2Y9OnxWc69gpNwkJkEpeqmrc2eER0/WNkEiSyc1uxX2yZ+C8FlcK3ocJYG6i3Q8B/L9SymlSymkA7saYI0VMpJSjUso5AOoALBBCNEc0eQHANCllC4BfAXhcsZ8NUsr5Usr5VVVVJsLWj2oWbFFhftjfke+rZj86fVZwrmOn3CQkQCp5qapxJeM1jvWKpEIyuelV3CeryydocaXgfZgA5gbFo1LKbYE/pJSvY8yeLSGklKcBvArg+ojtfVLK8+N/Pgog7tPnTGM0C3bt8mZsemPMtvmFPR1Yu6I54dmPTp8VTAjJLoxq3IM3NuHc8AW8sKcDbUsaWa9IWplV64m6r65d0YxZNXpcKXgfJoC5iXa/FUJ8H8BPMKYLXgngN0KIeQAgpXw78gNCiCoAF6SUp4UQRQA+AeCbEW28Usqu8T+XAzho/muYJ94s01izWY3WYL+yphQNVSVhbhQzqkvDPh9r/9fOmISXNK7RHu/7Rb5fX1GM906d46xbQgjy811onT0ZjZPGatilJYU4OzyCqpIJ+PbNs/HBuQvYdNcCnDo7jImlE1BZWogdf+pjLYF1Dga5XrMLC/PwyaYqTKtcEHSfmFlTgqKiAiyfVYtplWP335pyN1pqPcjPd5lypXC5BK5vqsEVGu/DdscpbhuqOK2I38ygePb4fx+M2D4XY4PkJQaf8QJ4XAiRh7Gn0k9LKV8UQqwFsFNK+TyANiHEcow9df4AwB0mYkqKeLNMjWZeh85mjVyD3chtYl1rMx7aegjH+oZM7V/HrOB438/o/VjxEkJyj/x8F5q8Hhx6fxD3bd6NyyeV4jNXTcXXXzhw0ZFiWRN+sO0Ils6swabtx1CYL3Dvksaw2pZLtcQqBwPWbODc0DB+vr8XDzwf7vr0qeZJ+O3hD6LO+bUzJkW5RMVzpXCyO4dZnOK2oYrzupnV+OXBHu3xJ+xTbCdS9YJt7x3EDeu3hYnq3QUuvNS2GA1Vpdhz/BRWbngz6v3Nqxdi9pSKqPfvvmY6Nr7eHtV+1aIGPPLqYdP7T5V430/1vipeEoQ+xQroU5xxkvIpjkdorVr/mbn4yrN7ourGt26eja88uwerFo257xjVwlypJfFqr+79OqBma6uZv/9THz7/w99HnYNNdy0w3P7kqqtw28Ydlt1nnY5VuaobVZybVy80HEeZiN8wN824T1QLITYKIX4+/veVQohViX7eTsSbZRpvjfXI91WzsYUI/zvR/adKvO+nel8VLyEkNwmtVUPnR5SuO4H6kevOFFY5GLBmQ+kyoXSfUJwzXfdZp+MUtw1VnKpxVKrxm5lo9yMAvwBQO/73HwHcl9LRM0S8Wabx1lhXvR/5d+hDeDP7T5V430/1vipeQkhuElqriifkK113QutHLs/gt8rBgDUbSpcJ1XaVW4Wu+6zTcYrbhipOr8ea+M0MiidKKZ8G4AcAKeUIgNGUjp4h4s0yjbfGeuT7Rm4T/5e99w9vqzjzvr8jy7L8U3Ecx3bsOCHEkGA7IanLr5Y+SwJs2oYkL+VHS7d0t3RTnrchKfTtw9sukCVkdy+2hS4hPEvp0j6lhZIW2ABpm6UksNBCaQMhTpwACYGEOHbimFj+KcuS5vlDPop0NCOdkc6RdKT7c12+EklzZubMGd0zmrnv72xc1YZtnd0p5W/1/Yk+T1RfgiAKk2hb9eNX3sf6q1pjFSmWt+Kx1w5j3dIWPPPWMTy/pzvOthWSLbFKwYBsNtBWX4kNK+JVn1rrK4Rt3j7DY+k4a3fsorYhq2drg8eS+hv2KWaMvQzgCwgfwLGYMXYRgHs55/8jrRqkgBl+m8nOxtaiVnu9PtR73Ght8MQ45/v9QXQe98aoTbx3angyytWN+XVVOOYdSzn/dEl2f/rPZ1S6sa93MCZ61+UqMlyeWWfP5zjkUyyBfIqzjiU+xUCsrWuc4gYDQ/fAGGorSzAeCMBT6oIDDMcGxtDgKcX8usqEti/fEdleAGlHyevz1dQnTg75UFfpxpBvAscF9jfLCgOm2syRsXF09Q5H1Cda6ytQXloiHe9k46xdVBesJnbcNn8eIkO1/WXPN9lzTzIfERaoMileDOBBAG0A9gGoBXAN57zTUAYmku2JR75FAidT27D6ehtBk2IJNCnOOpZMilNRsrGT7csEVrdRIvvrcLBsPx/TbKZZ7Uh9Nky22iGb3wfdfCS9QLtJHeL/AeASAN8A0JqNCXEuIDoj/Y6t+7B8QWPktZ3OTO/q8aZ1dny61xMEkZuIbF20bUv2OWF9GyWyv/n0fMy6l3xqk3TIVjtk8/tgBBX1iWsBlHLOuwCsArBFO7ij0Mi3SOB01TCsVtMgCCI7pKpkYxfblwmsbqNE9jefno9Z95JPbZIO2WqHbH4fjKCyt30n53yIMfZpAEsBPArg3xWuzxvyLRI4XTUMq9U0CILIDqkq2djF9mUCq9sokf3Np+dj1r3kU5ukQ7baIZvfByOoTIo1pYnPA/gx5/w3AFwK1+cN+RYJnK4ahtVqGgRBZIdUlGzsZPsygdVtlMj+5tPzMete8qlN0iFb7ZDN74MRVALttgHoBnAFgMUAxgD8mXO+MOGFFmDEMT9ZdKP+8yZPKQ6cGDSsnqCP2kymNmE16UbT6qN0z62txLt9Q5H20CLKZfnrr9faQ0uvRUrLXid7PjkSHVxQgXZNzbNw/NhHhtJyznH9j14zlJYC7SzBlEC76O9dfVVY0cDr88PtdKJ/xB+JUHc4WCTd9Eo3ihxA72Bhqk3oEdmuUIijq8eL/pFxVLld8AdCqPfEtpXoOsCYakW0QoimHuR0OvBh/wh6vT6UOB3w+vyoKXdnWhnIVJs5OubHvt6hiPpEW30lykrV1+aSqTPZFdm4mex9o+2gqjJlVrl6ta/2JOpYBtW9hAU6pbnGcx2AZQB+wDkfYIw1APhOJHfGqjnnpxXys4xUIqY3rGzDQy+dUY9IpJ4QCnHpmdvZOB7RjGhOp9OBhTOrsXCmOHpT3z76/KOvN6LOkUitg6KDc4Pjxz4yrCix5RuXWFwbwmqiv3fVZS7cePEsPPmXo7i+oxmbdh6M+S66nAxrnthN308dMtvlcjLcs22/sC2XtdYDQNx1m29YBH+AJ7WDoRDHi++eTHrt2iUt2LJrP25fNt+Wz2psbALb9p3AXc9FjUsr2nBVWz1KS4uV8nI4GObUVuTUccbpIut7V86vk85XVNpBVWUq2ThutFy/P4itncdx17Ox85FVC2ZIJ8bR8xFVVNQnRjnnz3DOD06+7uGcvxCVZId68daQSsT0Xc/GqkckilbMtehVs+sjit7Ut0+i/I2ocyRS68i19iWIQiD6e3f14iY8sOMgli9ojEzigDPfxc5jXvp+CpDZrs5jXmlbftg/Iryu85jXkB00eu2mneHnaddntbd3MDIhBibHpef2YW/vYJZrlhvI+l5Xj7F+lAxVVQezxvHO497IhFjL565n96HzuDXqVmbuoeTMz85UI6b16hGyaMVci141uz6y6E2j6hpG21eWX661L0EUAtHfO8bOfEdF38WQzuuOvp9hZLYrxCFty5NDYpWIEJenT1am7FqtDnZ8VicGx4X3dGJwPEs1yi1kfU82nqv2AVVVB7PG8V5JPicGrenDZk6KjTknZ4BUI6b16hGyaMVci141uz6y6E2j6hpG21eWX661L0EUAvrvXXSgSjTuYgf0O+/0/Qwjs11ae8nsmui6IiZPn6xM2bWc2/dZ1VWVCO+prqokSzXKLWR9Tzaeq/YBVVUHs8bxBkk+dVXW9OG8Om5MI5WI6Q0rY9UjEkUr5lr0qtn1EUVv6tsnUf5G1DkSqXXkWvsSRCEQ/b17+s1jWLe0Bc/v6cbaJS1x38UFTR76fgqQ2a4FTR5pW86uKRde197kMWQHjV67dkkLtnV22/ZZtddXYcMK3bi0og3t9VVZrlluIOt7rQ1VpoynqqoOZo3j7TM82LAyfj6yYIY16laG1SeSZsTYbs75IlMyS4KK+oQsulGvHqGpLcjUE2ZUurGvdzAS/dhaX4XjQ76ciV41O5pWH+2Z7H6TpW+oKJlsv3HUV5Wgrb4KPcPj0vxyNDq4oNQnVI5u3vKNS0h9IruYqj5xcsiHusqw+kT/yDgq3S5MBEOYVl6C4fEJdA/4ML2qBOOBAKrcJZlWNMg5oqPsRWocmvrEiUEfaspLEAKHq8gBfzCEmvKSmDTRkf2aysfJobCqRDAEnBzyoczlRIiH4GAMo/6gsEzgjHJFmasIE8EQpk6WlUFbmpLNlKkNjIyNo6t3OKI+0VpfgfJSWinWkKlDqKo3yFDNRzaOq6pL+XwB7O3xRuYP7Q0euN3OdFWq0lafCOfC2HQAkXVrzvnRyf8uVc3LShJFNyZSj1g4M179oGOWB9d1zIqNep2MfsyV6FUzo2lF0cyJ1DUSRYfOqa1I+rnV90MQhDESfe98vgCe29sTYwfXL2/F028dxNc+fbYtFQ3MwIjakX680avvJFKamFNbgdk15TFlzKopxc2fmYu7t3UlVKawow2VjRdXtdbjd/tPGlY/KDRk85rLz52O5/YeT7vdEs0LZN97kT1RVZcKhTh2HuxTVtVIFZVjnlcwxg4C+ADAfwP4EMDvtM855x+nXIsMo6pOceMlc+KjXi2Mfsw2qlGjyaJDMx09ShCE+ezt8cbZwbu3deHGS+bYVtHADFJRO9Kr7yRTmtDnsXxBY2RCLEpvZ2Tjxd7eQSX1g0JDqnxyXE01QjV/1T6nmo/Vqhp6VH5e3QPgIgDvcc7PQnhl+E9plZ4lVNUpxsYDGY1+zDaqUaPJokMzHT1KEIT59Eqi/8f8AdsqGpiBGWpHyZQm9HkkUrKwO/LxQtz/ZOoHhYasn8naU7XdzFKTUM3HalUNPSqT4gnOeT8AB2PMwTl/CUBHWqVnCVV1irISZ0ajH7ONatRosujQTEePEgRhPvWS6P9Sl9O2igZmYIbaUTKlCVkesvR2Rj5eiPufTP2g0JCqT0jeV203s9QkVPORq2pYo1KlMikeYIxVAHgFwOOMsQcA2HKvRlWd4mevHY6PerUw+jHbqEaNJosOzXT0KEEQ5tPe4Imzg+uXt+Kx1w7bVtHADFJRO9Kr7yRTmtDn8fyebqxf3pqXCiCy8aK9Xk39oNCQ9cP2GR5T2s0sNQnVfOSqGsbUWVQxrD7BGCsHMIbwRPrLADwAHp9cPZZd40Z4El2CcFDfU5zz9bo0JQAeA/AJAP0Aruecf5ioLqJoVX0UYnN1GY6eHpVGJSZTN9BHWc6rK8f+3uE49YQUox6TRk3qo0jn11XGqGGopm/ylOLAiUHlM8u19pGpb2j511e44s6k7x32x6l3aK8X6KJWVZ+favumm98kpD4hgdQnsk5a6hMiewSE/flODY+DAegbHscMjxucA91eH6ZXauoTLrQ2ePI+2Elro/6RcTAwfDwyjrqqsC0FELG/M6eWIhAT3h8uAAAgAElEQVTk6B8ZR5XbBX8ghLqqsDrEqeFxFBc5MOILoqTYAa/Pj2kVblSWODEw5kcwFE7TOKUUDMCxgbE4JYperw/FRQwj/gDKXU5MBDnqPbEqF5qdn1LmxPGB+Gdq1A6mGd0PpGgzx8YmsLd3MDKetNdXobS0WPq+CfXMSWT3JXtfpg6h2m6y92X5qNZfVU1Cdl9pqlSlrj7BGCsCsI1zfhmAEICfGSx0HMASzvkwY6wYwB8YY7/jnEf7It8E4DTnfC5j7IsA7gVwvcH8AcRHM86qKcUtS1pioi31UYmJoqwDgVBctOaGlW341V+OYNcRr6H8Veqrv15/xvismlJ887KWmGjcROm1+j700pnoZv3rZNGn0e0jjAZe0YYXDxzHC/tPhdU5PjkrLlo4urxk0aWqz8/s/kAQhYrIHmlqCPduP4DrO5ojxxO7ix24Z2UbppQV48af/Llgvk9aG4naY+OqcHuseWI3qstcuPHiWXjyL0fj0okUJtYuacGWXftx06fOwthECD988b3IZ+uWtuCx14/g9Kg/Yq+bq8vw1tHTcUoCF8yeilCIx40D669qxS/fOIL3Tg4nVLgwYpcz9ZwDgRB+s7837h4/f149nu/qjRtnVrQ1CNUJ7N4fZe0vU12QqUyotpss/8vmTsPz+3pjVbhWtGFFewPc7vippKz+S1pq8dy+HsP1SaaeYbbCiqGf9pzzIIAQY0xpvZ2HGZ58WTz5p1+aXokzk+ynACxljCn1ZFFkrj7aUiUqUXTG913P7sONl8wxJf9k0Zf68pcvaIyLxk2UXqtvdHSz/rVK9KkwGvi5ffjyRWcBmFTnEEQLR5enEl1qdvummx9B5DMie6SpISxf0BiZ2Gmf3fnsPuzt9hbU90lrI1F73LF1HzqPhdvj6sVNeGDHQWE6kcLEpp3htKdG/JEJsfbZAzsO4urFTTH2WmTrE3129/Nd+PpnzpaWn0rUv9XPWXaPe3sHxaoUFqkQZBtV1QWZyoRqu8ny39s7GK/C9Vw4H5X67+2RqIso3pdVqiMq+13DAPYyxh5ljG3S/pJdxBgrYoy9DeAkgN9zzt/QJWkE8BEAcM4DALwAagT5rGaM7WKM7err64v5zOzIXFlU45g/YEr+yaIv9eUnK09W3+ifFqLXRqNPZdGrA6MTAOTqHPryjEaXmt2+VkdqJ+qbBJEtjPZLkT3S1BBk352QbmnDzO9TLqK1UbL20D4XpZMpTDCW+DPt/71en9TWJ/pMG7eSKVzI7tloehUS9U3ZfUjVJyTv270/qqouKKt2SN5Xbf8Tg+NK9ZeVK3/fHPUMo6hMip8BcCfCPsJvRv0lhHMe5JyfD6AJwAWMsbZUKso5f4Rz3sE576itrY35zOzIXNkZ36UuZ8zrVPNPFn0pK181fbS7uOi10ehTWfTqlLKwL5FMnUNfnmp0qf51uu2ban7JSNQ3CSJbGO2Xou9LtBqC6Luj35XOF+UDGdFtlKw9ZOlkChOcJ/5M+3+9xy219Yk+08atZAoXie7ZSHoVEvVN2X1I1Sck79u9P6qqLiirdkjel+Uvy6euSnyioKz+snKl9TFJPcMohifFnPOfif4Urh8A8BKAZbqPugHMBADGmBPhAD5p8J4IUWSuPtpSJSpRdMb3hpVteOy1w6bknyz6Ul/+83u646JxE6XX6hsd3ax/rRJ9KowGXtGGx//0AYBJdQ5BtHB0eSrRpWa3b7r5EUQ+I7JHmhrC83u6sXZJS8xn96xsQ3ujp6C+T1obidpj46o2LGgKt8fTbx7DuqUtwnQihYm1S1qwrbMbNeUu3Hr5OTGfrVvagmfeOhZjr0W2PtFn669qxX+88r60/FSi/q1+zrJ7bK+vEqtSWKRCkG1UVRdkKhOq7SbNv74qXoVrRTgflfq3N0jURRTvyyrVERX1iQ8Q7w8MzvmcBNfUIqxvPMAYKwXwAoB7OefbotJ8E0A75/zmyUC7qznn1yWqSyL1CS0KMVZtwa0cHa2pOfR6faj3uDG/rgrHvGOR/DU1gxSjHpXUL+qr3Gitq8R7p4al6hH6+p5bW4l3+4Yi93/OtAp0nRiK5NemU4/QqzPoX+vVI2Lrc6Y8WXsZjXKWta+qekSy/Eh9IjmkPmErTFGfiP5+AGfUJwCgb2gc0yvDkeIuV1E6Ud85gapigZbeO+ZHIMhxcmgcTVNKwVjYxaymvAQhcNRWlKB/2I/+UT+mlBZjcGwC0ytLUOkuxqmRcbiKHBj1B1HmKsJEMITqspIYZYpRfxC1FSXwBYLoPj2Get34Fa00NK0ifK2n1BWjPtHrDdv5KeXF6PHGP1OjdjXN6H4gRZupH8+0+0+mWmDn/ihCdl+jY/44taeyUlfcvEFTeVJtN9VyVeuv1VOvRiVLL+sPaSLsICqT4mg/XzeAawFM5ZzfleCaBQgH0RUhvCr9K875BsbYBgC7OOfPTcq2/RzAIgAfA/gi5/xworoYMfDZiJo1i3TVE0T3v3FVGx7cGVaD0Ocnyj86vb68TLdvDj1PmhRLoElx1klrUiwjh757ppLqfUVfpylNPLBDrEShvXfr5eegtNiBf/7dO6a1oRnPJUPP1jSbma99UZWxsQmhCsTytjq8fKjfsJqEaruJVK6SqVjlOMKbV3Gf6I/66+ac/xuAzye5ppNzvohzvoBz3sY53zD5/l2c8+cm/+/jnF/LOZ/LOb8g2YTYCNmKmjWLdNUTRPd/x9YzahD6/ET5R6fXl5fp9rX78yQIu5Kv371U7yv6Ok1pQm83NSUK7b0fvvgeTo34TW1DM56L3Z6t3eprFTIViH29Q0pqEqrtlkj5JJ8wPClmjC2O+utgjN0MgzrHmcbKqNlMkK56guz+tUhmfX6y/GXqEZluX7s/TyJ1mppnweFwGPprap6V7ermHfn63Uv1vqKvU1HmMFutw4znYrdna7f6WkUiFQgVNQnVdkukfJJPqExq74v6fwDAhwAS+v5mCy3qMfoB2ikaVVZ/o/cju16vBpEsf5l6RKbb1+7Pk0id48c+MuzC8aubP2VxbQqPfP3upXpf+utEeYiUOcxW6zDjudjt2dqtvlahqUDo20H2vqbmkW67yfKxSgUiW6i4T1wW9XcF5/zvOefvWlm5VMlW1KxZpKueILr/javOqEHo8xPlH51eX16m29fuz5Mg7Eq+fvdSva/o6zSlCZkShfberZefg2nlLlPb0IznYrdna7f6WoVMBaKtvlKiJlFlSrslUj7JJ1QC7W4TvO0F8Cbn/G1Ta5UEI475do9GjY4wbvCU4pxp5RH1iIYqN1p16hHJooY19Qjt+vN0ahbn1lZEqVUkLy+ZmoPZZ9HL1CRUI8fTrA8F2kmwKtBOpQ4FHsBnSaAdYH9bKsPIfUXbjQaPG8EQcHLIhzKXExPBIGrKSzDkm0BPVFQ8EPa/PDE4juqyYoz4A6irKsH4BMfQuB9upxMfj/oxbVKtoqa8JEY5QqYwpCdaaaChyo32yQh+I/ds1I7LrlPoA6bazHztizJk7T485sP+3pGICsR59eWoKHXHzRu0PpRKXxEhy0dWT1l9ZOlTVYRJcVwXJlRxn+iY/Ht+8vVyAJ0AbmaM/Zpz/q8KeVmOw8FMPxM7U4RCPC5adMPKNjz00hn1iG9e1hJzdrg+mjT6/vVRo/rrReoT0eVpr3/1lyPYdcQbU56ofa2IEo6+H9X8KWqZIFLHzrY0EcnuK5nSxP3XnY/FzVPhcDAsmBl/jZbuu8vm4b0Tw3ihqwdfWNyMu7e9Ffls7ZIWbNl1FHcuPw8DoxOGI/sDgRCe23tcSQkgkR1M9GxzyX7ma18UIWv3JS21+G1XX8z4v2FlG1a0NWDnwb649JefO125r8jq8+K7Jw2rW8jKXdE+QymfTI/rKjoaTQAWc86/zTn/NoBPAJgO4DMA/jblGhBxiKJs73o2Vj1Cf3Z4omhSfdSo/nqR+kR0edrrGy+ZY6g8q6OEVfOnqGWCIFRJpjQhsiEiW9M/6sf9v38PN14yB3dv64r5bNPOg1i+oBGdx9Qi+1NRAjBDcUPlOiI9ZO2+t8cbN/7f9ew+7JWoTHQeN0c1QlYfmbqFrNzO4+L0qioZVvVLlUnxdADRh1xPAKjjnI/p3ifSRFU9QvtcFk2qjxpNVX1izB8wVJ7VUcKq+VPUMkEQqhhRmtDbEJGtCfFJ+zkekNpZLY3+M1lkfypKAGYobqhcR6SHrN17JSoT8vfNUY2Q1UfaF6X1V8sn0+O6yqT4cQBvMMbWM8bWA/gjgCcYY+UA9qdVCyIG2ZnhejUI/eeyaFLZWfLJXuvLK3U5Y14nU78wWj9VVPO3uj4EQeQferthxIaIbE0RC6ctK3FK7ayWRv+ZLLJfZtMTKQGkagfJfmYHWbvXT6pMGH2/QZaPomqErD7SvihLr5hPpsd1Q5NixhgD8H8ArAYwMPl3M+d8A+d8hHP+5bRqQcQgirLdsDJWPUJ/dniiaFJ91Kj+epH6RHR52uvHXjtsqDyro4RV86eoZYIgVEmmNCGyISJbM7XMhduuOAc/e+0w1i9vjfls7ZIWbOvsRnuTRymyPxUlADMUN1SuI9JD1u7tDZ648X/Dyja0N3jE6Weo9S3V+sjULRZIym2fIa6nqkqGVf1SRX1iL+e8Pa3STMIOEf7pqh3ERm26cW5tJd7tG4qc/T13Whm6eocj0aft9VUoLS2Wlt/kKcWBE4OR6+fXVeGYdywSxat9rpV3zrSKiPpEfZUbbZPqE0ajfq2OElbN36T6kPqEBFKfyDqWqU8UIpr9PTHoQ82kSsS0SaWJ3sFxTC13gUcpR8iUd8pcRZgIhjCtogTBEDDk8yMQAk6P+DGlrBhD4xOoKXejtaEKExNB7O0djLHpJSVO6Tii1bE3SvkiWeBUqnYwDftZUDYzGarzApl6g88XwN4eL3oHx1FfVYL2Bg/cbmfcvEHrE7K+kl59zuSTrD6ycvX9KcPjetrqE28xxj7JOf+LwjUFSbpRkSL1Ce36hTMZfL4AntvbE3f2+Yr2BrjdzoTlL5x5pvxEag4bV7XhwZ1n1CeMRClHY3WUsGr+hRS1TBBE6ujVejR76B2bwD3b9uP6jmZs2nlQatuNqlp85Sd/juTx4JcWYWB0AndGKQrcs7INU8qKccsvdwvLcjodWDizGgtnGr+3VO0g2c/0SUU1STQPuHJ+nVBlIpF6g6ivmFWfJS21eG5fT5waxqoFM+ByFQn7qKw/5cK4ruJTfCGA1xlj7zPGOhljexljnabVJI9INyoy2fV7e7zCs8/3TkaTmqHOcMfWWPUJijYmCKIQkCk7dB7zYvmCxsiEWPtM1TaK7O3ebm9kQqy9d+ez+7C320uqD3mCWapJMpUGq9UbVNUwOo+rqVvkCiqT4r8GcDaAJQCuQlin+CorKmV30o2KTHa9LMr0xOB4SuUnU7tQrT9BEIRdkUXBh7i68o+IRAoVojLTKYvIHcwal2X902r1BlU1jBOD9uynKsc8H+GcHwEwBoBH/RE60o2KTHa9LMq0rqokpfKNql1QtLH9aWqeBYfDYejPaLwBQeQTsih4bUc53Yj3RAoVsjJTLYvIHcwal2X9s8FjrSqTqhpGXZU9+6nhSTFjbAVj7CCADwD8N4APAfzOonrZmnSjIpNd397gEZ593j4ZTWqGOsPGVbHqExRtnB8cP/YRrnv4j4b+CKIQkSk7LGjy4Pk93Vi7JLkKRSJE9rat0YN7dIoC96xsQ3ujh1Qf8gSzVJNkKg2tEvUJs9QbVNUwFsxQU7fIFVTUJ/Yg7DrxIud8EWPsMgB/wzm/ycoKirBDtGqqUZSyM+m119rn9RUu7OsdSqo+IbteFjGtT58vZ8ynqwYyie0jqa1SlCD1iaxD6hMGMGoHtKj5j0fGUel2wR8Ioa7KjSIHcGp4HMVFDoz6g5E8ACjZF9H4EAiE0HncG8ljwYxwpL5sHDHJpqWMwfJtbzPNRKYmIcPvD6LzuBe9gz40VLnRPsMDl6tIOr9Qzd8stQetntF91+UqSqutROWa3NfTVp+Y4Jz3M8YcjDEH5/wlxti/pVurfEUlKjLZmfT6z2fVlOKWJS0x0dGJIqCNRJmK6psv0cZWnZFOEIR9ULEDTqcD7Y1TsL2rF//z8TcSpk/FvojsrctVhI7ZU+PSiuxwtm1atsu3I4lUpWQ/zJ7bezxOBWXVwkY4nY64fqGaP2Ce2oOs75pBpvuaSqDdAGOsAsArAB5njD0AgMJgTSBZFKj+8+ULGuOio7NxRrhdKPT7zzU4KyK/ZiLjmBVtr0+fDfuSbZuW7fLtiGqbyVRQunrEqg75+kwyfV8qK8UrAfgA3ArgywA8ADZYUalCI1EU6JzairjPE0VAi37xJcs/3yn0+885QgFcp+CWQRBmoGoHjKbPhn3Jtk3Ldvl2RLXNZGoSvV6fUJs6X59Jpu9LRX1ihHMe5JwHOOc/45xv4pz3m16jAiRZFKjsc1l61fzznUK/f4IgzIu216fPhn3Jtk3Ldvl2RLXNZCoT9Z7CGuczfV9JJ8WMsSHG2KDgb4gxNmhJrQqMZFGg+s+f39MdFx2djTPC7UKh3z9BEOZF2+vTZ8O+ZNumZbt8O6LaZjIVlNYGsapDvj6TTN9XUvcJznllqpkzxmYCeAxAHcKaxo9wzh/QpfkrAM8iLPUGAM9wznPOLSNZ9GM60ZEOB8OV8+uwZfVFkTPF59dVxeR3+bnToz4vxfy6SixurjYUNepwMCxrrce8tZdK06tGraq2TzYxcv8EQdgPFbujYge0fBs8JfjFTRfi1PA4GjxutDZ44tLr862vciMYAt74oF9ap+h6z5jixsDIBHoGjdte2b0AwOG+YcvtMNlUdRK1mWz8XbWwES3TK9Dr9aF+sv85nQ5pv5flrzo+y9Kb9b5Z7WYFKj7FqRAA8G3O+VuMsUoAbzLGfs85369L9yrnfLnFdUmZZNGP6UZHiqJGN65qw4M7D+JI/1hCtQkzzggPBELYuqdbGuWabvvkAlackU4QRPYwS/VBlu+92w/g+o7myLHOifLX8p1dU560TtH1Pmd6Bb504Szc/XyXsu3V30vGo/TJpiojarNk4+/CmdUxPsTJnrNIlUKlX8jSXzm/Tqhuofp+Kv0xk31NRX1CGc55D+f8rcn/DwE4AKDRyjKtQFUdQjU6UnT9HVv3YfmCcFOpqk2oohrlaqT++RD1ahfolDqiELHK7mj5Ll/QGJkQG83fSJ2i03z9M2dHJsRaehXbq1o2kXtYrTJhVvquHq8p7+d6f7R6pTgCY2w2gEUA3hB8fPHk4SDHAfx/nPMuwfWrAawGgObmZusqKkBVHUL/ear5s8kfU6pqE6qoRrnqydeoV6Nks28CZ06pMwKpORQO2e6XVmOV3dHyTcXuGqlTdJqx8UBatle17Fwh3/umClarTJiVXlZP1fdzsT9GY+lKscakvvHTAL7FOdcH570FYBbnfCGABwFsFeXBOX+Ec97BOe+ora21tsI6UlWHMBodKbs+elHPyuhL1ShXPfka9WqUbPZNgpCR7/3SKrsTna9q/kbqFJ2mrMSZlu1VLTtXyPe+qYLVKhNmpZfVU/6+ffpjNJZPihljxQhPiB/nnD+j/5xzPsg5H578/28BFDPGplldLxVU1SFUoyNF129c1YZtnd0A1NUmVFGNcjVS/3yIeiUIInexyu5o+T6/pxtrl7Qo5W+kTtFpfvzK+1h/VWvKtle1bCL3sFplwqz0rQ1Viu97bNkfmZU+howxBuBnAD7mnH9LkqYewAnOOWeMXQDgKYRXjqUVy8ZZ6bHRoWeiQDVUzxDXE33GeX2VG231VTg+5Ivk11xdhqOnRy2LvtTuTx/lapR0798mJL2hbPRNh8Oh5D5xvcLBGXZK+6ubP4VQKJQ8YX6SsG9mo19mgkR2x2jke3S66ZVuFDnCW9plLic4D4ExhlF/0HD0vBFbGJ2mwRNWn+gdTM32qpadYXLSZmYLmcqEfvxfMMMDl6tImo/qczYrvVnv5wjCiljtU/wpAF8BsJcx9vbke98D0AwAnPOHAVwD4H8yxgIAxgB8MdGEOBsYOVM8nejIRGecR+dnZfSlKMpVBYpEJggi08jsjtGIe1G6dUtb8NjrR3B61J9StLwRW6hPM6sGWKh476mWTWQHmcrEivYZePHdk6arqFiR3qz3cxmr1Sf+wDlnnPMFnPPzJ/9+yzl/eHJCDM75Zs55K+d8Ief8Is65sWWhDGJ1VG+66g8EQRDEGYzabFG6B3YcxNWLm2wTLU/YA9k433ncnioN+UpGAu3sTqLoTTNIFH1KEIQxOCsyLE3ndLkNp21qnpXtWyMUMWqzkyn/mGnnicJGOs5bPL8g1MiYJJud0aIxozuuFeoP+vxTiUAmiIIlFMB1FvkqE/bCqM2WpdMc+OwQLU/YA+k4b/H8glCDVooNYHVUb7rqDwRBEMQZjNpsUbp1S1vwzFvHbBMtT9gD2Ti/YIY9VRrylYJZKU7nDG7R2dvN1WVpn+mt4XQ6sKJ9BmbXlMdEn6YagZwKZpxRThBE/mBnm+BwMFw5vw5bVl8UE+kvOp452rbXVoTVJxY1T1Gy83Zuq3zADu2vH+cbqtxon1SZ0M8vktVfpmJBpE9BTIrNOBM+OorS7DPmQyGuHH1qJmbfD0EQ9sbuNsGIYpCGKEJ+9jTjdt7ubWV37NL+ycZ5oyoNMhWLVQsbaWJsAgXRgmarR+R6fnYrnyCI3MLuNsGM+qejYGGntrI7dml/s+pJalXWUhCTYrPVI3I9P7uVTxBEbmF3m2BG/dNVsLBLW9kdu7S/WfUktSprKYhJsdlnwud6fnYrn4inqXmWYcmwHDvrhsgD7G4TzKi/0Tzs3lZ2xy7tb1Y9NRULfT6kVmUOBTEpNls9Itfzs1v5RDzHj32E6x7+o6E/gjAbu9sEM+qfjoKFndrK7til/c2qJ6lVWUtBBNqJ1CPSiU7N9fyA5NGp+mjdK+fX4bcmlk8QhH2xwiZlEjPqn66CxRsf9BtSQrCDckIuY5e+Gt+f3Ght8CjX0+l0YNXCRrRMr0Cv14f6yXwSBdmRWoVxCmJSDJh/Bncu55csOjVRtK6dzignCMI6zLZxmSbd+qeiYDG7plxJCcEuygm5jh36qkp/SobT6cDCmdVYODN5WlKrUINaJA9JFp1ql2hdgiCIbJGKnVS9hmxx4ZCtZ01qFWrQpDgPSRadapdoXYIgiGyRip1UvYZsceGQrWdNahVq0KQ4D0kWnWqXaF2CIIhskYqdVL2GbHHhkK1nTWoVatCkOA9JFp1ql2hdgiCIbJGKnVS9hmxx4ZCtZ01qFWoUTKBdIZEsOtUu0boEQRDZIhU7qXoN2eLCIVvPOhW1ikKGJsV5SrLoVDtE6xIEQWSTVOyk6jVkiwuHbD1rFbWKQod+KhAEQRAEQRAFD02KCYIgCIIgiIKHJsUEQRAEQRBEwUOTYoIgCIIgCKLgsXRSzBibyRh7iTG2nzHWxRhbJ0jDGGObGGOHGGOdjLHFVtbJLEIhjsN9w3j9/VM43DeMUIhnu0oEQVgAZ0VwOByG/pqaZ2W7ukQCyG4T2YT6X+5jtfpEAMC3OedvMcYqAbzJGPs953x/VJrPAmiZ/LsQwL9P/puz0Hn1BFFAhAK47kevGUr6q5s/ZXFliFQhu01kE+p/9sDSlWLOeQ/n/K3J/w8BOACgUZdsJYDHeJg/AZjCGGuwsl7pQufVEwRB2Auy20Q2of5nDzLmU8wYmw1gEYA3dB81Avgo6vUxxE+cwRhbzRjbxRjb1dfXZ1U1DUHn1RPR5FLfJLJLLrlaUL+Mhex27lCIfZP6nz3IyOEdjLEKAE8D+BbnfDCVPDjnjwB4BAA6Ojqy6oijnWEe3cHpvPrCJZf6JpFlcsjVgvplLGS3c4dC7JvU/+yB5SvFjLFihCfEj3POnxEk6QYQfc5K0+R7OQudV08QBGEvyG4T2YT6nz2wdKWYMcYAPArgAOf8fkmy5wCsYYw9iXCAnZdz3mNlvdKFzqsnUqGpeRaOH/soeUIAnBfE4klBo7laGGFG00wcO3rE4hrlN2S3iWxC/c8eWO0+8SkAXwGwlzH29uR73wPQDACc84cB/BbA5wAcAjAK4O8srpMp0Hn1hCrHj32E6x7+o6G0W75xicW1IbJODrlaFApkt4lsQv0v97F0Usw5/wOAhD+DeHhJ7JtW1oMgCIIgCIIgEkEn2hEEQRAEQRAFD7Oj7yJjrA9ArjjYTQNwKtuVSADVLz2i63eKc74sUeIkfTPX79VsCul+s32vCftmDtjMbLdPuti9/kB27sGozRyB/dtXhXzoTyrk4v0K+6YtJ8W5BGNsF+e8I9v1kEH1Sw8z65fr92o2hXS/hXSvqWD39rF7/YHcvodcrpsV0P3mLuQ+QRAEQRAEQRQ8NCkmCIIgCIIgCh6aFKfPI9muQBKofulhZv1y/V7NppDut5DuNRXs3j52rz+Q2/eQy3WzArrfHIV8igmCIAiCIIiCh1aKCYIgCIIgiIKHJsUEQRAEQRBEwUOTYoIgCIIgCKLgoUkxQRAEQRAEUfDQpJggCIIgCIIoeGw5KV62bBkHQH/0l+m/pFDfpL8s/SWE+iX9ZekvKdQ36S9Lf0JsOSk+dSrXjtAmiDDUN4lchPolkatQ3yRyiZyYFDPGzmWMvR31N8gY+1a260UQBEEQBEEUBs5sVwAAOOfvAjgfABhjRQC6AfxnVitFEARBEARBFAw5MSnWsRTA+5zzI9muCJE/hEIcH/aP4MSgD3VVbsyuKYfDwbJdraxAbUEQBEHYhUyOWbk4Kf4igF/q32SMrQawGgCam5szXSfCxoRCHNu7enHbr96GbyIEd7ED9193Ppa11pvyxbJT37S6LYjcwU79kigsqG8SRsn0mJUTPsUajDEXgBUAfq3/jHP+COe8g3PeUVtbm/nKEbcK47YAACAASURBVLblw/6RyBcKAHwTIdz2q7fxYf+IKfnbqW9a3RZE7mCnfkkUFtQ3CaNkeszKqUkxgM8CeItzfiLbFSHyhxODvsgXSsM3EcLJIV+WapQ9qC0IgiAIu5DpMSvXJsVfgsB1giDSoa7KDXdxbFd3FzswvdKdpRplD2oLQkTjzGYwxlL6a5xJ298EQVhDpsesnPEpZoyVA7gCwDeyXRciv5hdU47NNyxC5zEvQhwoYkB7kweza8qzXbWMM7umHPdfd36cf1aitii0wLxCu18AOH7sI1z/o9dSunbLNy4xuTYEQeQDqrZUlD6VMSsdcmZSzDkfAVCT7XoQ+UcoxDEwOoFHXjkc+VJtXNWGUIjn/WRHj8PBsKy1HvPWXoqTQz5Mr0xsqAotMK/Q7pcgCMIKVG1povQqY1a65Jr7BEGYTlePF3ds3RfjqH/H1n3o6vFmuWbZweFgmFNbgYvmTMOc2oqExqXQAvMK7X4JgiCsQNWWJkqvMmalC02KibwkFOI43DeM198/he6BMaGjfq+XgsuSkUqQQ3TbH+4bRigkPWY+56BARIIgiPRJZEtFY0Su2N6ccZ8gCLPQb8NsvmER3MWOmC+cu9iBeg8FlyVDC3LQt50syMHu7geq90sQBEHEI7OltRVu4Rhxbl1lTtheWikm8g79Nswj//0+1l/VGolg1XyKWxs82aymLdCCHKLbLlGQg93dD1TvlyAIgohHZkuLHBCOEUUO5ITtpZViIu/Qb8N0dg8CbxzBY393AU6P+lHvcaO1wQOnk34TJkM1MC/RFtic2opMVDktVO+XIAiCiEdmS9/4oF/szjjoywnbS5NiIu8Qbdu8d3IY0ypLcMEcscBJIcpwGUULcjAyqc0n9wNuH1dogiCInCXaliYaI1TGGqugpTIi71DdAtf8YD+36VV86cdv4HObXsX2rl5bBYjlCnZ3P6C+QBAEkT4yW9pcXZbTYwStFBN5h+oWuMwPdt7aS22x5Z9L2N39gPoCQRBE+shs6W/XXprTYwRNiglboOreoLINY3c/2Gwheya5sAWWKtQXCIIgxKiMw8lsaa6OETQpJnIeq2W+8skPNlPYXXpNBvUFgiCIeFRtvl1tKfkUEzmP1TJfdveDzQZ2l16TQX2BIAgiHlWbb1dbSivFRM5j9Za23f1gs0G+uhlQXyAIgohH1ebb1ZbSpJjIeTKxDWNnP9hsYNetMSNQXyAIgoglFZtvR1tK7hNEThJ9NjrniBzVDIS/iJtvWATOEXN2utH8jKQnziBqu0RbY7nW1rlWH4IgCLuRTZuvmn869aGVYiLnkDn0b193KXoHfaivcmN/zxA+/+Crhhz+8zUoLBMkajvR1hiAnGprevYEQRDpI3OHAKy1+ao2PF2bnxMrxYyxKYyxpxhj7zDGDjDGLs52nQqNXFpN+7B/BPduP4CbPj0Ha5bMxdcvnYN7tx9AiAMXzZmGEBefnS5z+M/XoLBMkKjttK2xi+ZMw5zaCjgcLKW2lvU9M/okPXuCIAhziT6hzmobq5p/uvXJlZXiBwBs55xfwxhzASjLdoUKiVxbTesfGcf1Hc3YtPNgpD5rl7Tg45FxzKmtUHb4z9egsExgdVvL+t6V8+vwwoETafdJevYEQRDpI7PV1WXFltpYs8agE4PG6pP1lWLGmAfAZwA8CgCccz/nfCC7tSoscm01zVXkiEyItfps2nkQxUXh7qo5/EeTyOFfNT1xBqvbWtb3unq8pvRJevYEQRDpI7PVZS6npTZW1YbL6lPmKjJUXtYnxQDOAtAH4KeMsd2Msf9gjMUJ2THGVjPGdjHGdvX19WW+lnlMol9iqZKOY/zHI35hfUb9QQDq+odW6yXmc9+0uq1PDPpQXebCNy+bizVLwn/VZS70eM3pk3bVyjSDfO6XhL2hvmk/ZPOEiWBQ2caqzA9m15Rj8w2LsHZpeHxYt3QuNt+wSJq/PxjE2iUtMfVZu6QFE8GQML2eXHCfcAJYDOAWzvkbjLEHAPz/AO6MTsQ5fwTAIwDQ0dFB4eMmYra8VrqO8euWzhXWp64qXB9V/UOr9RLzuW+m0nYuJ8Pqz8xBiAMOFn4to8Hjxo0Xz8IDO864yqxb2oKm6lJT+qRdtTLNIJ/7JWFvqG/aD9k8YWp5CRY3TzVsY1Nx1/QHOB555XBMehk15SXYsusobvr0HDAW9n/esusolrXVG7pPUyfFjLEWAP8C4DwAkdGLcz4nwWXHABzjnL8x+fophCfFRIbQVtP0nTT6l1iyM8+jPy9zFQm3WeatvVTo06PflvnVrmP43mfn4dSIHyEOFDGgvckTUx9V/UM76iWmi8o59YlQabsP+0fw8MuHcOMlczA2HkBZiRMPv3wIc6aJrw+GEJkQA+G+8sCOg7hifl3SPmlF/QmCIAoFlTEi0TxBdYyQzQ9m15TH1SdRelF5s2vKcfuy+SmPHWavFP8UwHoAPwRwGYC/QxIXDc55L2PsI8bYuZzzdwEsBbDf5HoRCUi2mpbsl53+87VL56btGD82ETL8y5CIJ1vBk94xP76wuBn/66k9kXLXL2/F4JhfmP7kkHhL7tTIeMGu8BIEQVhNKmOEyi6gDJkbxscj43indyjtQL50dwfN9iku5ZzvAMA450c45/8I4PMGrrsFwOOMsU4A5wP4Z5PrRSRBJK+lkSwQ78P+EfzkD+/jX69ZiHuvbkfHrGrMqimNyd9d7EBpcZHQh0jvSH/14ib88MX3cibwz45kK3gyGALu3tYVU+7d27oQkLhzJQqiCIU4hnwTGBidwJAvQIduEARBmEQqUmdrntiNTTsOYfPOQ9i04xDWPLE7peDnWTWlMXEks2pKUVzkMD2Qj6cwZJi9UjzOGHMAOMgYWwOgG0DS9XTO+dsAOkyuC2ESySRRRKuDd69oxf9++RCO9I/BXezAxlVtWPvk7sjr6F+k+m2ZIgdIRitNsiVFdmp4XLzyOzwuTN9cXYaNq9pwx9Z9kb6zcVUbZlS6sXVPd9z7qxY2wunMhfhggiAI+5ItadPm6jLcsqQlzrb7gyFh/pyHhGNEc7VYuTfdXVKzJ8XrENYYXgvgHgBLAHzV5DKIDJMsEE+0Orj+uS78/GsXIMg5SouLIhNi7fNonyD9dkdpsTPiOiEqj0iO2cGTRmnwiAPkGjzico+eHsWDOw/GBEU8uPMgZteUR4wgEO4zd2zdh5bpFVg4s9rSeyAIgsh3VMcIs8aUo6dHhbZ9y+qLhPkzxoRjxOLmakMxSsl8kPWYOinmnP9l8r/DCPsTEzlCMof6QCCErh4verw+NHhKcW5tBd7tG4q8/tFXFuMbP39L6LguWx3sH/FjWVsDXn//VGRCHP159C/MaEf9UIibFmRVqCQKilANwNP3jdaGKjidDmE+rQ1Vwl/1rQ0eYfoTgz4c6R/DQy8diimzV7Iq0ev1ob3RnABCgiCIfMKswDkz0svQZDivXtwENlm1p988hlF/EJtvWITOY96YAPtRf1A4Rpwc8qG5uixubEp3RduUSTFj7HkAUu8NzvkKM8ohUiPZdkIgEIrbqt6wog0PvXwwxv3hv751KXq88Y7rM6aIVwdnTK4Oqv7CLGQZLbMw65x6Ud/YuKoNK9pn4MV3TwrzWbWwES3TK9Dr9aHe40ZrgwcOBxOWe15DpXhlWdJnGjzunDp9kSAIIhdQdRuwWm5ThkyGc8YUN7qOD8UF2M+tlY8ForFpUdOUtFa0zXLO+wGA+xL8EVkkmUN9V483bjvjoZcP4ttXzsOaJXPx9Uvn4MGdB9E35Bc6rleWOLFuaaxY9rqlLShyMLz+/ik4GJTFvRMF/hHGELWhanCFqG/csXUfOo8nP3Eu3FXCz01WbjAk7hvtMzzYuKot5v2Nq9pQ6S7OqdMXCYIgcoFUgqtVxllNbnPu9ErMnFKKlumVePjlQ8q2VybDOTAyoTRGDIxMCMemsYD6YSLRmLJSzDn/bzPyIawh2XaC/vSwBo8b13fEBs6tXdKC4wOjWPvknrhfoL2DPjz2+pEYn5/HXj+CsYkgNu04BHexA5tvWITf3HIp+oZp5TebqG4tyU6Wk7k3DI75sfXo6fjAuapSabmy1QrRivNfjnxMQZgEQRA6rA6uVpXblCGT4eyR1L9vWDxGvLC/V5i++/RY7kiyMcZaGGNPMcb2M8YOa39mlkGok+zscC04SuPqxU3YtDP2l9ymnQfhKXNFXkf/Aq2rcuP0qB8PvRSWannopUM4PeqHdqqibyKENU/sBmOgld8so3qOvL5vaOnrJfkEQhD+ei92Mul59LLVCqfTgYUzq/HXbQ1YOLMaTqdDuf4EQRCFgNW2UVVuU4ZMYq22okRaf9EYIR2bPOL0RjFb2+inAP4dQADhwzseA/ALk8sgFNEc5KO3EzbfsAicA6+/fwoVriJ8/5oFkc9lkmgHeoZiXp8c8knzX7ukBc+8dSySvrrMhb6hcUNnnRPWIXpWibaWtMA5vRvDghkeYT6yoMvTYxO49fJzYtLfevk5hs+jj67/5hsWYe3SsL7luqVzsfmGRRSESRBEQaNq21VRlduU4Q8G8d1l82Js+HeXzUORQ+5mGQpxHO4bjpk/yMam1gZPWvdptiRbKed8B2OMcc6PAPhHxtibAO4yuRxCAb1DfX2VG/t7hvD5B1+NbIPcd+35eOrmi9F9egzTKkqEkmhDvkDMa+0XaLykWliCrccbnjRrjvVf/emfKTgqy6gGVzidDqEbg9PpEOazt9srDHKoqyhB78BYTJBGabED0ypKlO/BH+B02iFBEEQUVgeoq8ptyqitKMF4MPbE2tuuOAdTylxY0FStFBwuG5vSweyV4pjDOxhj/w8MHN5BWE/0dkKII86h/du/Dp8c89dtDVjUXI37ro39xXbPyjZs6+yOvNb/Ao3Ov71xCm5fNj9y/bUdTXGO9RQclT1kW0uiX+OA2I1Blo/s13tZiRP//Lt3Yk5D+uffvYNgSF6uiGyd1EcQBJHrWBmgnmhlVsWGB0PA/b+PPbH2/t+/h2BIPThcNjalg9WHd1wG4EaTyyDSJJlDfijEEeKhmFW9qlInHr3xkzg1Mp70F6j+F+uoP0jBUTlOuqcAachWlhMFyL17Iv68e1m52TqpjyAIopCR2XaZ3KbMhssC7fqGfTh7uvGT9E4MWmPzzZ4Uz548wCNyeAdj7FoAb5hcDpEGyXSDu3q8+M5TnTGfz6opxX3Xni89S1wkGq4dxnG4bzgrp6sRxkn3FCAR0ZJssj5X5irC3/2fvxguN1sn9REEQRQ62srswpln3jvcNywdO2bXlMfNC1RtuBaYJxo7rMBs94nvGnyPyCLJHPJlEm1/8+gb+NKP38DnNr2K7V29kS0SbZXxc5teFX5udQAAkT6JVmBV0A77uP6RP+HmX7yF6x95HVv3dKPJUyrsA7Lz7mXlUl8iCILIHWRjx8cj48J5QXN1mZIND/EQ1i9vjUm/fnkruGyFLk3MOtHuswA+B6CRMbYp6qMqhJUoiBwimUO+3qFeJNEWvZqXbJWRTqjLfcxagZUd9tEyvULYBz7sH6HTDgmCIGyKbOwoLnII5wW/XXupkg13MIaHXzkUcw7Cw68cwqYvLrLkfsxynzgOYBeAFQDejHp/CMCtJpVBROH3B9F53IveQR8aqtxora/C8SFfZJuiuboMR0+PSs9A1xzatS1qzVH+xKAP0ytK8P1rFkRcKGQSbZofp4qfp0U/7og0mV1Tjge/tAh7u8+cO9/W6MHsmnIEAqG48+VlAQ09XvG59r1eH9obw6+j+4C28qv3RzNy2iH5EBMEQSRH5N7ocDDp+yr5aDKZncfOjB3tTZ6ksURGbfioP4gj/WN46KVDce+r1t8IZp1otwfAHsbYE5N5NnPO3zUjbyIevz+IrZ3Hcdez4RW5WTWl+OZfteCu52JPEXtw50Ec6R9L6vguCrIyItFWWxFezUu2ymhWEBdhHYFACAOjEzEyOfesbMP4eAC/2d8bd0LdqoWNwolxU3Wp8Fz7ximlwj5w5fw6uJwsJqjT5aQ+QRAEYQay8ffK+XV44cAJw+OyLJ/Lz50eN3ZsXNWGWVPLhfMCbd5glOmV4vlFbUWJJfMKs32KlwF4G8B2AGCMnc8Ye87IhYyxDxljexljbzPGdplcL9sTLXmyp3sgMiEGgOULGiMTYuDMlvW3r5yHNUvm4uuXzsG92w9IZas+7B/BvdsP4KZPz4mk/9f/OhCRaKupcGHd0pYYn551S1tQNNl7kvl5koyWGiryNokIBELY89FpbN/Xgz0fDSCQ4OihzuNe3PlsbB+689l92Ns7KHSH6OrxCvNxO4uE59qHwIV9oKvHizVP7I6RalvzxG7qGwRBECYgG3+7erzScVk0Bsny6TzuxYM7D8bMHx7ceRAj4wHcdkXsgU23XXFOZN5glCIHhPMPXyBoybzCbPWJfwRwAYCXAYBz/jZj7CyF6y/jnJ8yuU62R/8L7d4vtMf8amJM7N5w6OQQNu88FDlh7uORceF2Rf/IOK7vaI74DevT93h9eOz1IzE+PY+9fgSLmqdg9rRwfolW+0hGyzhmraprAW9GV3h7pbI34lOMer2+mAhkjT7JqUfHByTn3XupbxAEQViFXNJMbKtPDPrwTm+8TGZ1WbHUVovmD6dGxlFS5IiZF5QUOXBqeDwybzCCbP5x1rRyS8YOsyfFE5xzL2Mxgzd5kaaJ/heaTKJE/1o7Qdc3EcKmnQexZfVFwvxdRY64QLro9HVVbpwe9cf49ES7R3zYP4I1T+yOK/+3k4F2JKNlHLOk0RIFvC2cWR2XvkHyjOqqSoTv10tOMZL1zWkV4nwaPNQ3CHvTOLMZx499lPL1M5pmovujoybWiCDOILPJU8tdSjKZW1ZfLHVjuO1Xe+LmD4997QKs2R4/L5DNQ2TI5h9WjR1mu090McZuAFDEGGthjD0I4DWD13IALzDG3mSMrdZ/yBhbzRjbxRjb1dfXZ2adc5Lo7Yu+oXFUl7kin/34lfdjJEqe39ONDStiT5pZu6QFz7x1LHJNdZkLvomQcEte5hA/6g8CSO4ekUzOK99ltMzsm2ZJo8lWYHu94nzaZ3hwz8rYPnTPyja016udL+8PBnHr5bFbZrdefg6cknPtWxs8ed03skmh2cxscfzYR7j+R6+l/JfOhNquUN/MHP5gEGuXtMTNDzi4kkzmRDAYd9LtfdeeDw7xTvXA6ASqy1z45mVzsWZJ+K+6zBWZVxhFNn+wauwwe6X4FgD/AGAcwC8B/BfCJ9sZ4dOc827G2HQAv2eMvcM5f0X7kHP+CIBHAKCjoyOvV59FW+jrlrbgsdePoMfrQ2f3IFxvHcXPv3YBTg6No67Kjbb6KnTMrsbJIR9Ki4uw9snd6JmcADV43Ljx4ln46k//LNySny5ZxautKAGQXAbLyEpwPgdTmdk3zVpVl51TX18lzsfpdGBKWXHMM5pSVozi4iLh+zJXjtqKEpQWx26ZlRY74Cl14dSIP64PkMSadRSSzSTsBfXNzDG11IUtu47GuB9s2XUUV55Xh080TzUsk1lbWYIery/Ghod4CDVl4hXn+qoSYdB1g2SXUUaiMcKKscPUSTHnfBTAPzDG7g2/5EMK13ZP/nuSMfafCPsmv5L4qvxEtIX+wI6DWP2ZOdi0I+wj/LVPn41PzJoa6QDayi/ngKe0GHcuPy8ikTKvvhLf/6934rZDGldfhFF/EGXFRbjtinMi55FHO7JrJJLBkslqORjw+vunUOZy4p5t+3GkfyxyTbR7BXGGVCTKREwpc2L9Va24+/muSD7rr2rFlPJiYfoP+0dwyy/FW133bNuP5QsawRgQ4sA92/ZjzjRxXwiGgEf/+EFM+kf/+AHOnzlF6mKj3RvJ9REEQaSOSKJsLBDEFz/ZHDc59QWCwnFdNgYNjEzgBy+8G2Pbf/DCu3johsXC9JXuYmHQ9ZXn1Svfl2z+YYU8p6mTYsbYJwH8BEDl5GsvgK9xzt9Mcl05AAfnfGjy/1cC2GBm3eyEbAt90cwpeHL1hXG/iPQry7NqSnHLkpYYiZS1S1rw8z8diawe+yZC2PHOycgk+7vL5mHNZXPhC4QijuxzppWjrXFK0vrqf7HVVrjxQf8wlj3wasLyKZgqHrN+/R4f8OGXbxzBv16zEGP+AEpdTvzHK+/jrGllmFVj/Hx5WRBmvyRo8+NRcfpTI+Kgjo9HxoVBHSTXRxAEYRxZkLa7mAkD1WTju2wMeuXgCbFtHx4Xpn/jg36hze8b9uHs6bk77pvtU/wogP+Xcz6bcz4bwDcB/NTAdXUA/sAY2wPgzwB+wznfbnLdbIO2hR6Nu9iBWTXluGjOtMgpcRr6leXlCxrjgqw27TyIqxc3xeQXHYj3L9vfwdhECJt3HsJDLx3C6VG/NJhKhPaL7aI508AYYlYFZeVTMJWY6LbUP2uj1FW58d7JYaz95W7c/vRerP3lbrx3clja5rI+V1lSLAzCZBDXSRa0WeV2CfOXnXpEkmwEQRDGkQVpV7ldkUA1o+O7aAwqc4nHgjKXU5heNqbk+rhvtk9xkHP+qvaCc/4HxljSY54554cBLDS5LrZFdQtdv8onk2jT9AGjV25lnycKphIRvW3jYAzVZa7IqrAo/2j3CrNOoiHOoNqHpFtmoxOSFV6/cKtOFrQ5EQwpn3qk+beZeVoRQRCEXVA5sU222zcRDOH71yzAwZPDEds7d3oFWhs8SvmfkshtnhoeF6Y3yxUw05g9Kf5vxtiPEA6y4wCuB/AyY2wxAHDO3zK5vLxEdQtdFpylf33O9EqsWTIX8+oq8f0X3omZtLqLHeiYVY17v9COcpcTlaVFhicgyQIDtfyXzpuOS86uEbpX0Ja5uaj2IVn6vd1eSeCf+DShc+sqpYGC754YinHpuf+683H2NHHfnVZuzWlFBEEQdkBVs14WMF9XWYKPR2JPnLvv2vMBQCn/OsnJcrKVX7sGUZvtPrEQwDkA1iN8kMd8AIsA3AfgByaXldeobKHrJUue39MdJ6N12xXn4KPTowCAYwOj+PKFs2I+X7e0Bbc/vRe3P70Xa365G9/4+VsxW9j6E24CgVDk9d7uAWFg4LUdTZH877/ufLQ3TpG6V9CWufmoumGI0msBe9F9Zf1VrSgpZsKtuiKJ9FqRA8L0Q76JjJ5WRBAEYQcSnQQrOnFuLBDE9z47D2uXhuXP1i2di+99dh5Oj03g27+Ozefbv058op2I9hkebNDJdm5Y2YYFM+Q7yma4AmYas9UnLkv0OWPsq5zzn5lZJiH+RdZcXYbFzWGJtmCI49CJYfzL79+J/CL87rJ5ePSrHShyMDAwfGvL23HuDlognCyQT/NbXrt0rlJgIJ1wZx9kAXvVZeJn3jc8LpTfk550l+HTigiCIOyA/CQ68YlzZS6GsYlQzIrwrZefg49H/MJ8VE8TdbmKsGrBDMyZVh5xt1gwwwOXq8j8m88iZrtPJGMdAFtOilV8b8zIT/95c3UZjp4elabXS5MEAiEM+SYwMDqBqeUu/Mv2WEm2f9n+Dn7+tQsQCHGUuoridIPdxQ6UFhdNSqoVJQzkC3Gxu8asmnLhl4tOuEuMWX3NjHzKXM5IwJ6Gu9iBmnIXZtWURuR5gPAOBQMTSq9tWX2R8Jk3eNwxfY9NTqJlOsvTK92mfxcJgiByDdk4KTtx7udfuwA/fPG9mPd/+OJ7eOxrF4hd1CpKhDY8kY11uYrQMXtq5hohC2R6UmzLkUvVtyfd/ESfb1zVhgd3HsSR/rGk5QcCIWzd0510JfeNDz7GD154T5j/xlVtWPvkbhzpH4u7Xh/I9/Sbx7B2SUuMVEsqQV257oCfCczqa6blw0NYv7wVd2+L0jte3ooQgrj5M3Pj3h8YFa9KjIwHhc98fl1VzK6D1vfm11UK0zdXl5GvMUEQeY9snJSdOHdaYnuHfBPYsKIVdz13xlZvWNGKKWUOoe1t8pQWtI3N9KTYlvL8Mt+eeSkePpEsP9Hnd2zdh5s+PQcPvXQoafldPV5DK7ljuvy3rL4IYxPByIl42mEbsuu11z1eH7bsOhq5PtWgrkL4wiXDrL5mVj4OxvDwK4di3BsefuUQfnDNwsiEWMv/7m1d0lUJl9MhfOYf9o/EyQfesXUfFjdXS9Ob+V0kCILIRVSDn2vKxYF2le5ibNi2P8aGP/TyIXz/moVC29syvaKgbSytFBvAbB9YUX7VZS70DY0nlDRjUa2XqHy9r5BoJVcvyVZd5oJvInxwh28iBH+AS69/fk93nMTL4llTUFFSbPhccytOoskHEvU1FYkys/IZ9QdxpH8MD710KOZ92arEwNiEsK8N+fyRdNEn1yX7bun7CPmjEwRRaETbTH8wiO8um4f+UX9k/J1a5kKRA7jv2vMjQXWaysTp0QmhDT8xKI7zUPU1zjcyPSn+Y4bLMwWzfWD1+TV43Ljx4ln46k//HOnMIkmz6C9GovL1/pjaSu4vbroQgVAoshKs5Z2sfP1KcH2VG13HY+W1Nq5qw13Pdhly7yDkyPpafZVbTT5Hkk9thTn51FWJfX5rylz4p11HY1Yltuw6ik1fXCQs97wGuYSbSvuQPzpBEPmEzAWudUYldgdjA+puu+IcTK1w4aPTYzFBziEewtQymQ0XrywniucoBEyVZGOMeRhjP2SM7Zr8u48xFtHr4JyvMbO8TKGXPEvXB1af37UdTcIzwqMlzTauasO2zm5D5bc2VMVJst2ypAXnN4Ul0dobp+DO5edFpFv+4fPz8eRfjsaV/w+fmx+Rdrlz+XkRSbUQR5zEyx1b92H5gsbIa5LPSg1ZXwuGxJJmsjaW5SOTRlPNp7WhCptvWBQj/7P5hkWoqXDhi59sxqN/OIzNOw/h0T8cxhc/2QynQyzhFgyJJdyS+aOb9V0kCILIRWSuYgMjE3j8jbBiz5olc/H1S+fgzb316wAAIABJREFU8TeO4OSgH995qhObdoRPrtu04xC+81QnKt1F2LBCJ6W2og1t9ZVS217INtbsleKfANgH4LrJ119B+Jjnq00uJ6OY7QOrz092qle0pFm0xFqy8p1OB1YtbETL9Ar0en2o97jR2uCB03nmN5A/wGN+aWruFNrqsW8ihPdODmHzzkORL4WGbAvbqHsHIUfW12TnyMva2Op8QiGOgdGJuN2CvuFxJYm1vmGfKYeM0I4EQRD5hGyc7R8dx/UdzXEuajKXtiP9Y7iqrR6zp5XhxOA46qpK0F5fhdLSYqktLWQba/ak+GzO+ReiXt/NGHvb5DKygtk+sNH5He4bNiRpplK+0+nAwpnVWDgz/jPRL9BNOw9GAvm08oOT1dE72su2sI26dxCJEfW1VNwGrMxnb/eAMEjjFzddiNOj/hj/NU16TVau6neL/NEJgsh3ZLa6sqQ4MiEGzozfsiDneo8bpaXFuOCsmrgyZLa0kG2s2SfajTHGPq29YIx9CsCYyWXkHaIt4c03LALniJxY4/cHseej09i+rwd7PhpAIBD7i1B0wo0M2S/QosneoP3yfOatYzGfnxzySeur4t5BqGOW20CifFT6kCwY4+MRv9CtorXBU9BbcgRBECrMrikX2tKB0Qmh7fWOTsS5TW5c1YbWBo+SbS90zF4pvhnAY1F+xKcBfNXkMvIO/XZFfZUb+3uG8PkHX4VvIoSOWR5c98lZuOvZWD3BVQsb4XQ6lDVpZb9Al86bjkvOrokLxNM+11YTk52gV2jbLZnArC0tWT4AlPrQjCniYIz6qhK8d3I4zq0CQEFvyREEQaiid3O8/7rzMbNabHvrPCW47NzpcW6TDgcraN1hVcyeFA9yzhcyxqoAgHM+yBg7y+Qy8hK9O0W0e8ONl8zBfS+8E/HTBIAHdx7E7JpyTARDKHM5ce/2A4Z1BWWi4O2NUyKHh9y+bH7CwzVE2yuFut2SKcza0hLlo+9z0X1IJOFWWeLEuqUtkQBRTbGEc0i1LxfOrKY+QhBEwaJyGqcs0O7Jv78I3/vsPJwaOSPJVlPuggNM6DaZyLaTLY7H7Enx0wAWc84Ho957CsAnTC4nr9G7N/BQSOhYf3xgFGuf3CMNlFMNntK+nIXuaF+ISIM6RsbxTu9Q3A+k2kqXMKCueWqZMJ8Tg+OZvB2CIIicQnVHV6rJPjyOsYlYSbZbLz8HJ4d9cXkkzIcC4YWY4lPMGJvHGPsCAA9j7Oqov78FYCjaijFWxBjbzRjbZkad7EyZyxnxCwKAKeUuoWO9p8wV8/rqxU2Ra4wGT100Zxrm1FbEfSmTfU7kF/o+B4T7EINYSs1V5IgE1G3eeQgPvXQIp0f9mF5ZIsxnarkrY/dCEASRa8hWfmVymJqbYzTuYgemlBbjhy++F5PPD198D5UlxUr5UCC8GLMC7c4FsBzAFABXRf0tBvD3BvNYB+CASfWxHYFAKBJINx4M4NbLz4l05Hd7hsRBTcN+rFkSdsKvnjzRBhAH6gUCIXK0twmyoAjVYAmVfPzBINYuaYkJ0li7pAUfj4hPPRr1B4WBc84iJsyH2/OEd4IgCFNItGIrQhYU7R0TB9oNjE4o5UNBzmJMcZ/gnD8L4FnG2MWc89dVr2eMNQH4PIB/AnCbGXWyE4FACFv3dEd8Md3FDnzvs/Ow5rK58AVCaJAENX3QPxLREV63tAWXtkzDJWfXxAXqzaopxS1LWmLyJ0f73ES2xXbl/Dq8cOCE4a031XzOa6jEFsFJdA9+abFUSu3Cs2riXGw+7B8R5rOsrT6TzUgQBJFTTK+UnzIqw+VkMSfUuZwM0ytk8pYlwjzIHVINsyXZDjHGvscYe4Qx9hPtz8B1/wbgfwEIJUtoF1RW9bp6vHHBSf/8u3fgD4aweech/OCFd+KkVtYtbcGvdx2LpH9gx0GUFjsjJ85Fb9MsX9AYlz+dOJebyLbYunq8SltvqvkEQ8Cdy8+L7DY4HeHXWkCdvu8VOcQuNrNrynH7svkxJ9rdvmw+rUoQBFHQFDkgtaWi+cKH/SNY88TumBPq1jyxG8FQSJgPmHzeQe6QxjE70O5ZAK8CeBFA0MgFjLHlAE5yzt9kjP1VgnSrAawGgObm5vRraiGqDvUyzdemKaVYs2QuHAyorXThN7dcir5hHxgYvrXl7RjJNG0b5uzpFXHbNIyBHO0txMy+Kdtik/UR2TNMJR/RCXWnRsQn1C1qnoLZ09SDOInMYSebSRQWhdg3e7w+oS395Oxq7O+JD2aeUlostNXdknyap5ahe8BH0mtpYvakuIxzfrviNZ8CsIIx9jmEg/KqGGO/4Jz/TXQizvkjAB4BgI6Ojpx2UJSt0skkUBo8YveIIx+PxZww99u1l+KiOdOw56MBnB71x+ThLnagzFUEQK5DrHKKGWEcM/um7NklOhFOJPOjBc7Fb9WVCN8vLnIonVCnegIekXnsZDOJwqIQ+2ZdlVtoS4uLHLh3+4EYydV7tx/A/deeL3WTENvkEnzlJ38m6bU0Mdt9Ytvk5NYwnPPvcs6bOOezAXwRwE79hNhuqDrUz6+rxIaVse4R65e34tX3TgqvlwVFTUyey6x3rH9+T3ec+wU52ucmsqAI2YlwzdVl2N7Vi89tehVf+vEb+NymV7G9qxchHhL2kSIHhPkM+vzSE+ooSIMgCCI9ZLbdHwxLrmouZ//x6mFc39GMoXG/0IYXF7G4+cKGlW1wFjGleQchxuyV4nUAvscY8wPwA2AAOOe8yuRychrZap9sde2YdwwPvXQwZjvk4VcOYfmCRnR2D8ZdX1NekjCYiU6csy+J3A9E78t2JbasvkjaRxY0Vcfls7fbKz4lqaoE7Y1TyB2CIAgiDWQ2fG/3gFBy9fGbLpTa8FULPJgzrTyyO7hghgfHvGO0I2wCpk6KOeeVaV7/MoCXTalMFpGdGCdbXTsx6IM/cGYHibHw8Y7REmvR12vBTHTiXH4icz8QvX9i0IfqMheuXtwU2Xp7+s1jGPUHpX1ElE9rQxU2rmqLUSjZuKotckwo9R2CIAhz4FEOI6P+oHCFNwT5ybIOB0PH7Kkx16jOOwgxpk6KGWMMwJcBnMU5v4cxNhNAA+f8z2aWk+uoBhs1eNy48eJZcUfmahJrdOIcIUPWdxo8Ysk0WR9xOh1YtbARLdMr0Ov1od7jRmuDB06n2R5WBEEQhYcsAP+8hkrhCm9NeQk+0TzVsA2neYE5mD3i/W8AFwO4YfL1MICHTC7DFqhIoARDiExqgDMSa6EQj/lFmWr+RP4i6zvBkHofcTodWDizGn/d1oCFM6uTTohVDxMhCIIoVGSubsGQOM4jeldPb8NJes06zPYpvpBzvpgxthsAOOenGWN0vmsSTg6JA/NefOckNu04RNIqhBRZ3+kbDsvzWYWq7CBBEEQhIwvA7xv2Ka3wku21FrNXiicYY0VA+ExXxlgt8uhADquQnU0+KSZBh20QUrJ1rr1s1YP6KEEo4nCCMZbyX+PMwtD5tTuJbLXKCi/ZXmsxe6V4E4D/BDCdMfZPAK4BcIfJZeQEIm3YVH+liRzk1y5pwc//dCSSprrMhb6hcVPKIzKLmX1FTyrBFWbUJ5HsIAXkEYQCoQCu/9FrKV++5RuXmFgZwipm15TjvmvPx7d/fcZW33eteiAc2V5rMVt94nHG2JsAliIsx7aKc37AzDJyAbO3L/QO8qXFRVj75O7IiXVaMNVXf/pn2i6xGVZvdakGV5hVH1XZQYIgiEImFOII8RBWf2YOQhxwMCDEQwiFONneHMKK0PITCB/1/BqAUsbYYgvKyCpWbF9Eb5+0N07B7cvmR7Zaru1oigumou0Se5CJra5sbL3JhOhJ/ocgCCKerh4vvvNUJzbtOITNOw9h045D+M5Tnejq8SrlQ7bXWsyWZLsHwN8CeB+TfsWT/y4xs5xsY/X2hX71T6ZjSNsluU+ubXWZVR+S/yEIgjBOj1dse3u9PiycaTwfsr3WYrZP8XUAzuac+03ON6fIxPZF9IEJh/uGabvEpuTaVtf/Ze/do9uqzrz/75Zv8k2K49iWbMcJAQPBN8i43Fo6NLRMStMk03JpO1PeFjq084OGlr4zs2aGCYs0fTttB+YHhfW2TNsp6RVaOiFhKL0A/VEG2hIucWzSEggk+O4YItuJ5Zv27w9bsnS0t6QjHUlH0vezllZyztlnn+fs8zxb20f7+W4r7eGiHoQQkhhed7my7/W42ffaCasHxb0AVgAYtbjerBOenOR1O3HPx85DT78PAQkUCaCj2Z22ny+4Uk3uYuWz0yXImUmcoy8RQkjmafO68LUrO3F4dCo0bjijvgptXne2TSNhWD0o/jKAF4UQvQBmgjullFssvk5GMSYnraktx2c3tuK+p45EDCzSBX8uyV2sena6BLnL1zfgl4dGEk6coy8RkmcsSbolS2Pzagy8ecxCg4iO2QUZMW740l92ZNskYsDqQfH9AL4C4CDySJ/YmJy0ubMJt+7pjUpWOnv7JWn7OYM/l+QuVjw7XYLcAzdcqNwfyxfpS4TkEZR0ywn6hnz45/86GNFX//N/HcQZdZXoWl2TZetIEKsHxaeklHdbXGfWMSYnCQFbJU+R/EeXIKdL3qAvEkKIfbAq0Y6kF6sHxb8VQnwZwF5ETp94weLrZBRdcpJdkqdI/qPzQa/bXol8hBBCorEy0Y6kD6t1is8DcCGA/wPgjqXPv1l8jYxj1AXcd2AAu7a1UyeQZAydNmWb103NSkIIsTltXlfUuGHXtnYm2tkMq1e0e4+V9dkFVXJSS00FNrTUMFmJZIRYCXJMnCOEEHtTXOzAtq4mtNZXYdjnh8ftRJvXjeLidKyhRpLFkkGxEOKvpZTfF0LcojoupbwzzvlOAE8BKFuy6adSytussM0qVMlJ4duBgMSRsamEZLEISQZdgpxuvxmpNkIIIemluNiBrtU1UXOI2VfbB6veFAd/q61O8vwZABullFNCiBIATwshfi6l/J015qUXnVyWThaLkHRDnyQkMZpWt2Cw/81sm0EKFPbV9sKSQbGU8ptCiCIAE1LKf0/ifAlgammzZOkj9WfYC51cVjol2giJBX2SkMQY7H+TkmYka7CvtheWTWaRUi4A+Giy5wshioQQL2FxNbxfSSl/bzh+gxBivxBi/9jYWIrWWotOLmt00p8li0gmsaNv0ieJHf2SEIC+GQ77anth9Qzv/xFC3COEuEQIsSH4SeREKeWClPJcAM0AzhdCtBuO3yel7JZSdtfV1VlsdmoE5bLCoSxW4WBH36RPEjv6JSEAfTMc9tX2wupB8bkA2gDsRJKSbFLKEwCeBLDJYtvShk4ui7JYJFvQJwkhxP6wr7YXtpBkE0LUAZiTUp4QQpQDeB8Wl4vOCSiLRewGfZIQQuwP+2p7YemgWAhRC+A2AO/CYqLc0wB2SinH45zqBXD/UrKeA8CDUspHrLQt3ehksQjJFvRJQgixP+yr7YPVyzz/GIt6wx9e2v4rAA8AeG+sk6SUPVhcDY8QQgghhJCMY/Wg2Cul/GLY9i4hxDUWX4MQQgghhBBLsTrR7pdCiI8IIRxLn6sB/MLiaxBCCCGEEGIpVg+K/wbADwHMLn1+DODTQohJIcSExdcihBBCCCHEEqxWn0h2mWdCCCGEEEKyhtVziiGE6ASwNrxuKeXPrL4OIYQQQgghVmG1JNt3AHQC6AMQXLdQAuCgmBBCCCGE2Bar3xRfKKU8x+I6CSGEEEIISStWJ9o9K4TgoJgQQgghhOQUVr8p3o3FgfEwgBkAAoCUUnZafB1CCCGEEEIsw+pB8bcBfBzAQSzPKSaEEEIIIcTWWD0oHpNS7rW4TkIIIYQQQtKK1YPiF4UQPwSwD4vTJwBQko0QQgghhNgbqwfF5VgcDF8eto+SbIQQQgghxNZYvaLdJ62sjxBCCCGEkExgqSSbEKJZCPFfQojRpc9DQohmK69BCCGEEEKI1VitU/yfAPYCaFz67Fvap0UIsVoI8aQQ4mUhRJ8Q4maLbSKEEEIIISQmVg+K66SU/ymlnF/6fBdAXZxz5gF8YWklvAsB3MgFQAghhBBCSCaxOtFuXAjx1wB+tLT9UQDjsU6QUg4BGFr6/6QQ4hCAJgAvW2ybKQIBiTfGT2Jkwo8GlxNrayvhcAjLyhNCkiPdscZYJsSe8HuZpBurB8XXAfg6gH/HourEMwA+kejJQoi1AM4D8HvFsRsA3AAALS0tKRsai0BA4rG+Ydzy4EvwzwXgLHHgzqvPxaY2jzKgzJYn+UUmfbPQSXes5VMs0y+JXUnGN/m9TDKB1dMndgL4X1LKOillPRYHybcncqIQogrAQwA+J6WcMB6XUt4npeyWUnbX1cWbkZEab4yfDAUSAPjnArjlwZfwxvhJS8qT/CKTvlnopDvW8imW6ZfEriTjm/xeJpnA6kFxp5Ty7eCGlPItLL75jYkQogSLA+If2GGhj5EJfyiQgvjnAhid9FtSnhCSHOmONcYyIfaE38skE1g9KHYIIWqCG0KIlYgzRUMIIQB8G8AhKeWdFtuTFA0uJ5wlkU3jLHGgvtppSXlCSHKkO9YYy4TYE34vk0xg9aD4DgDPCiG+KIT4IhbnFH81zjnvBPBxABuFEC8tfa6w2C5TrK2txJ1XnxsKqOBcpLW1lZaUB4D5+QAOvPk2HusdwoE3T2B+PqAtCyzOjzoyNoVnXzuOI2NTCARkkndHSG6g8vlkYs0MuvpbaioYf4RkkVixb7av4Pcp0WH1ina7hRD7AWxc2vUhKWVMFQkp5dMAbDXr3eEQ2NTmwdnbL8HopB/11fGzVkuLBW549zoEJOAQi9s65ucD2HNgALfu6Q0lAOza1o5tXU0oLo7+O4UJA6TQ0Pn85esbTMVaMqjq/83hUdz0wxcZf4RkEVVsBgISvzw0knBfoSvPeCaA9eoTWBoEZ1VOzQocDoF1dVVYV1cVt+wb4ydDX5hBnCUOPLr9EuX5fUO+0IAYWJzndOueXrTWV6FrdU1UeV3CwNma+gnJdXQ+/8ANF5qKtWSuq6r/hnevY/wRkkV0sfnADRea6it05RnPBEjDoDhXMeoZNrvLcWhkAkM+P7zucrR5XRFvcWdnF9Az6MPwhB/11WW4oq0B3ppKiKU/NB96vh+jk35lkA351AkAwz4/ulZH2xYrYYBBTOyGThvUzH6dzw/5/KipKMWHNjRHxdra2sqUNUlHJtT1G39dZfwRkllGJvy4oq0BV76jBccnZ1BXXYafPHdM+32q6yt05a3qQ0huw0Exon+qXVNbjhvf04odD6unN8zOLmBPz2Do+Jractx46RnYsbcvVP7my1rhcakn9Hvd5XCWOKL+gvW4YycMGMszYYDYjVjTHnQ/car2n+OtVvp884pyXHvRGtz1+OGoWLNiipHX7VTWX2SogvFHSGZpqnHiwtNX4brvPheKzZ1b2nB6nfr7tLlG3Vc012i+fy3qQ0huU7CD4vC3UxWlRRE/p2zubAoNeIHFvyJ//IejaFlZgdHJGdRXl0Uc39zZFBoQB8vf9fhhvGPtSvxxeAhedznWN1Sj3zeNkQk/6qvKcNdHzkXf4AQCEigSwBn1VWjzupW2BhMGjMFqVXIRIVYRa9rDd55+DV+9sgvTM/OoKCvGd55+DU0rnMry//3ZS5Q+H4DE44eGI+q5/5kjOH/tStM/iYb/2uN1OdHR6MZCAKEv0WA9dz1+GN/6X92hL9JE4s+qlbS4IhcpRPz+eRwc8mF4YgYeVxk6vG4M+2Zw729exfXvWhd683vvb17F167swj0fOw89/b7Q92lHsxvO4iL8+LljEeV//NwxvG99g7JvWQiA0ypIYQ6KjW+ztl92RsRfjUIgYruzyYUPb2jBtd/5Q0LlgcXt3x0Zx7/98hXlm+edW9vx8EsDODo+HXoTHYt0JxcRYgW6aQ8T/ll8eEML/v6nB0IxcNvmNkz4Z5Xlx6b8ymTX/3ltVFnP2NSMsp6RCfUUB+OvPcGYXLuyQllPkRB4NMHEW6sSY5lgSwoRv38eew8OYcfesNjc0o5VrhJc092Cu59YfvO7fWMrfNNzmFuQuO+pIxFx8tbJWWX5t6dnlX3L718f5zRFYrkkW05gfJsVkFDqGQb51LtPx+2P9CVcPrjdsvQmSfXmecfDvdjc2RTavnVPL/qGfFp7b/rhi7j78VdxzxOv4u7HX8VNP3yRK/MQ26HTBi0rLo6IIf9cALc/0oey4mKtlmgw2fXCdauwrq4KDofQ1rOyslRZT0VpkdLOnkGfMiYh1LFcUVoUZYsOq1bSypkVuRzFEEIk/WlandoS1E2rW1K6fsGT5edn5OCQLzQgBpZic28vqkpLQgPc4P67nzgMd3mJMk4goCwPCWXfQl1jAuTxm+JYPzuOTPhxZn0VPvXu0zE9Mw93RQn++Yr1+NKjh+CfC2DfgQF89cpOvDo6hYAEqkqLUFNRiiHf4ko4Dz3fj3/cdDbGT82Gjn/5Lzvwj/91MOIv0sETpwDo3ySH98c1FaWY8M/j2deOK+3lX7DEbqhibG1tJb7+0fNwcGD5p8z2JjdGJ9RvckcnZ5Q/fQa1RI31j02q6zlxag7bN7ZGvRWaWwgo6xnWxNTY5Iy2nkSJFa9mEnlyJu4D87jmm88kffoDn744pcsP9r+Z1evnPFl+fkaGY/QVqsS541Pq/bq+YmxqRnldTlMkQJ4OiuP97Ni4womPXrAm4ifY27e04aHPXITJmXk0VDvxwpsnIn6OufmyVux+9mhoYDyzEIg4/nd/cRZuvqwVJ2cXICXwwP5joTfBAJQT++VSRnswuedvdu9X2stEO2I3dDG2sbUOJ07NRcTGF7e2o7W+UunDTW4nhiZmon761GmJNq9QJ8nUVJTggf3L8weDMfi+cxqUdnq1MVWGr/7ij1H1bGr3JNw2ung1m8jDuCeFiMddpkmyVSfBNrnVCXWNbnPxk8z6BCT/yMvpE2+Mnwwl9XzlQx342pVd2PPiMRwcOIFnXzuOsclZ3L4v8ifY25YS5aQExk/O4p+X3voGj9/1+GFc1d0MALiquxl3/uqViONf+8WfMD23gHueeBXffvoIPvPnZ+CRngEAwL4DA7jtg20RK+vs3NoeOn5Vd3MoIeCmjWfgU5esw1ceOxT6mTTdq3iR3MBOqzDpfto/OOTDvximJfzLw72QAHZuaY+MgS3tqCpT//TZN+RT7g9IGRVLi9tFuPHS07HeU43VK8qx3luNGy89HSdn5pX11LlKsXNre1RMdnjd+IdN6/Htp4+EYvkfNq03taKdLl51iTy66RCMe1KI1FeX4fYtkTF++5Y2zGuSYOcWAsr9QkAZ452N6oR2QD2tghQWefmm2DcdndRz+5Y2bP/xizg6Ph2VKAcsBtJrY1P4+4cO4isf7lAeP8frwl0fOTfqr0/j8RUVJbjjF3/C5s6m0NumH/3+KO7/5PmQkKircqL/xElsPbcJAQmcXlepTAh46+RMKDD5F2xhY7ekK/1P++qfLId8fmzp8OK0VRUYmZhBw1JG+Qv9J7TlVfsHfH786PdHF9UnZudRXlqMbz31Gj5/+ZlYkAL/OzwB74NtODGtTuQbPOHHts5GrFtVGZrK0NnoRmlpUVSstdRUmFoBSxevZhN5GPekEBk84cdjB4fwzY//GU6cmsOKihJ89+nX8eHu1cr40U23GJ6YQYOrFP92ZRdOzs6jsrQY1eVFylVjCQmSl4PihQCiknFu29uH69+1Dvc++WooUc74s4qzdLE5KkqLlcdnFyRu/vFL2H3dO2Iev2njGXhldAo9AxMRx+uqy7CurgpHxqbw6e+9EDr/6x89T5kQ8MANF4bON66wF3xrSKmmwsBuqxrqftqvq1b/9FlXVQansxjvOK02op6yYoeyfO1S4pxqCsIro1PY/qMXI/ZXlhbj9n0vRLTP7fv6sPu687U/oZaWFqF77cqoezPG2pGxKW3b6+YIq1bETGY6hJmVNQnJBxpcTjz7+lt48pXjoX3OEgf+9j1nqOPHpe5zVlaWhhSjwvdbtfolyU/y8k+m4xp5pvBJ+Ns3tkb+BLu5Dd966jUAwH889Rpu2xw93WH3M0cAAMfGT0Wdv31jK8YnF+cb7zswEPWzTfjPnsa3bK8fP6m099TsgvL+gm8Nr7j7t/jof/weV9z9WzzWN5zVn9NJeomVdJUNdD/tQ0IZG9D8vTY5M6ssP7uwoKy/s9GNXdsiY2vXtnaMT6nfCL91cjblKQi6th+Z8JuKQ06HICQ+ujg5NTsf9b182+Y2zC4sKPsQ3/ScrfpMkhvk5Zti3YpxwcS2IZ8fD+w/hu9ffwHGp2ZQW1WGf/35y6E3uz0DEyh9Yfm4x+3E+gYXutfUYHTSjxKHA7f85KWoZJx/u7IL3/zrDVHljT97Gt8YzS4ElPY2aFbEs9tbQ5J+7JZ0pftp/43xk8qEN12iWnVZqbL8+aedi01tdcqpA9u6mtBaX4Vhnx8etxNtXjf6hiaU7eN1O9HRtCKlKQi6tq8oLcInl1bXAuLHIadDEBIfXZzsP/oWHnrhcMTUqd3PHMHfb1qv7EPuuCp6qiMTVUk88mZQHC671LjCiV3b2nHrnkhh/nufPAxgMTD+YdN6bGipgcMhEAhIXPeu09E7uDxn8Lp3nR46HiT4M+Zzb4wr5wALAfxFuzeqvBGj9Mu+AwNR9sZ6g5QzUk3EMuwoF6T6aX9tbSX+YdP6hO0MQCpjSUJqpw4UFzvQtboGXauX97V5XVExtGtbO9q87pSnIOjafnYhYDoOOR2CkMSRYT+6BOQCruqOzhUqLZL47MbWqNjvbHTbrs8k9icvBsWqJKRvfnwDHvibCzE84Y/75tbsG5zayjJTb8OMqK7XUlOBDS1q+4zY7a0hST+59JbRzOqLqcZSkOJih/INshVJNbHeijMOCbEWXVJx04pyPH5nfMjqAAAgAElEQVTo9YgEvB/87nWc7TlTG/u50mcS+2CLQbEQ4jsANgMYlVLGXu9YgWo6wae/9wIe3X4JulpqQuXiJaol+gbH7NswFao3Rmauz7+AC49ceMsYXH0x0eQWK2IpiOoNMhB7IZ9E0b0VZxwSYi266YG/+NwluLytEZ/+3vNRvwbpYj8X+kxiL2wxKAbwXQD3ANidzMlmpxOkKm+V7bd22b4+ITrMxmK6fTmdUnaMQ0KsR9eHjE3OYEVFScSvUCsqShhvxFJsMSiWUj4lhFib7PlmpxNYkaiW7b9As319QlTYTXYs3UmpjENCrEXXh5QUOUz9CkVIMuSMJJsQ4gYhxH4hxP6xsbGIY2aljuwmb0Vym1i+WWjYTXaskGOdfknsSjLf56dmFwo2lknmsMWb4kSQUt4H4D4A6O7ujhACNfszJhPViJXE8s1Cw25TCgo51umXxK4k833OxFaSCXLmTXE8zKxZbre3WYTkE2ZiMd0w1gnJPVR9CGOZZIKceVNsJXZ7m0UISQ+MdULyA8YyyQS2GBQLIX4E4FIAq4QQ/QBuk1J+O53XZIIMIYUBY52Q/ICxTNKNLQbFUsqPZtsGQgghhBBSuOTNnGJCCCGEEEKSRUiZe0nJQogxAEezbccSqwAcz7YRMaB9qRFu33Ep5aZYheP4pt3v1WoK6X6zfa8xfdMGfWa22ydVct1+IDv3kGifeRK5375myAd/MoMd71fpmzk5KLYTQoj9UsrubNuhg/alhpX22f1eraaQ7reQ7jUZcr19ct1+wN73YGfb0gHv175w+gQhhBBCCCl4OCgmhBBCCCEFDwfFqXNftg2IA+1LDSvts/u9Wk0h3W8h3Wsy5Hr75Lr9gL3vwc62pQPer03hnGJCCCGEEFLw8E0xIYQQQggpeDgoJoQQQgghBQ8HxYQQQgghpODhoJgQQgghhBQ8HBQTQgghhJCCh4NiQgghhBBS8OTkoHjTpk0SAD/8ZPoTF/omP1n6xIR+yU+WPnGhb/KTpY+SnBwUHz9+PNsmEKKEvknsCP2S2BX6JrETOTkoJoQQQgghxEo4KCaEEEIIIQVPcTorF0KsBrAbQAMW53DcJ6W8y1DmUgAPA3h9adfPpJQ702kXiSYQkHhj/CRGJvxocDmxtrYSDofI2Pnpro/kHvPzAfQN+TDk88PrLkeb14XiYvN/x9OXSL4Ty8fDj3ndTiwEgNFJxgIhKtI6KAYwD+ALUsoXhBDVAJ4XQvxKSvmyodxvpZSb02wL0RAISDzWN4xbHnwJ/rkAnCUO3Hn1udjU5kmow0z1/HTXR3KP+fkA9hwYwK17ekM+sGtbO7Z1NZkaGNOXSL4Ty8cBhI7VVJTi2ovW4K7HDzMWCNGQ1ukTUsohKeULS/+fBHAIQFM6r0nM88b4yVCHCgD+uQBuefAlvDF+MiPnp7s+knv0DflCA2Jg0Qdu3dOLviGfqXroSyTfieXj4cc+tKE5NCA2liOELJKxOcVCiLUAzgPwe8Xhi4QQB4QQPxdCtGnOv0EIsV8IsX9sbCyNlhYeIxP+UEcZxD8XwOikPyPnp7u+dEPftJ4hn9oHhn3mfCDXfMlK6JeFQSwfDz8mBGwTC/RNYlcyMigWQlQBeAjA56SUE4bDLwBYI6XsAvB1AHtUdUgp75NSdkspu+vq6tJrcIHR4HLCWRLpCs4SB+qrnRk5P931pRv6pvV43eVKH/C4zflArvmSldAvC4NYPm48ZpdYoG8Su5L2QbEQogSLA+IfSCl/ZjwupZyQUk4t/f9RACVCiFXptosss7a2EndefW6owwzONVtbW5mR89NdH8k92rwu7NrWHuEDu7a1o83rNlUPfYnkO7F8PPzYQ8/34+bLWhkLhMRASKld2CP1yoUQAO4H8JaU8nOaMh4AI1JKKYQ4H8BPsfjmWGtYd3e33L9/f1pszhWszqhPNdM/8nwn2rzupJQCggTvb3TSj/pq22RJxzUgH33TKl8zW0/Qp4Z9fnjCfMpsPTb1JauJeUP56Jf5RrLxMeTzo7mmHM7iIhw/ORPl4+H+73Etqk+MTWUsFgqyzyQ5gdI3060+8U4AHwdwUAjx0tK+fwLQAgBSym8AuBLA3woh5gFMA/hIrAExSY/awy8PjaSkPpHK+SocDoF1dVVYV1eV1PnEGqzytWTqKS52oGt1DbpWp1YPfYnYHbN+bUadReX/p9czFghRkW71iaellEJK2SmlPHfp86iU8htLA2JIKe+RUrZJKbuklBdKKZ9Jp035gN3UHpjhn79Y9WztVg8hdsKsX1ulzkIIiYQr2uUgdlN7KOQM/3zHqmdrt3oIsRNm/doqdRZCSCQcFOcgdlN7KOQM/3zHqmdrt3oIsRNm/doqdRZCSCQcFOcgdlN7YIZ//mLVs7VbPYTYCbN+bZU6CyEkkrSqT6QLZqumnlFvzHRuqanAsbdPheoLbieTCe11l2N9QzX6fdOh85vd5Tg0MpG0ukWqpKqusUReZFKnW71B19a6/bOzC+gZ9GF4wg+vy4mORjdKS4tM11/gUH0ix1GpSYxNzaCitBizCwuoqyrDQgAYnYzsU4d9i6oSKypLMHhiOaYBRMW5al+yydAJ9iN50WeSvCQr6hMkTaSSUR8r03ldXZXpTGiV+sSube34+hOHcXR8Gs4SB3Zubce9Ty5v6zKl04GZTO18J93qDbq23tLRiF//aTTquhtb67C3dwg7Hl4uv3NrO7Z1NioHxulQOiEk24T7dU1FKa69aE1oSWZniQP/uOlszCwEcOevXony+44m4LG+YVzzH78LHbvnY+dhdl5GxUlpscBNP3wx5dixWgFJR9PqFgz2v5n0+Y3NqzHw5jHL7CH5D98UFyBHxqZwxd2/jUjUcJY48Oj2S7Curiru8UTru/5d63Dvk69qtx+44UJ0ra5J122GOPDm27jmvt9F2ZfE9XP+rYfZZ2sWXVt///oL8Nff/n3U/u9ddz4+/p0/KMt3r12ZcftzGL4pzmHC/frG95yBbz99JMLHt192Bu576ojS7wFExYSu/A3vXoe7H381qg6zsWMiDlPqM4UQuOabyQtSPfDpi5GLYxySEZS+WVivyQiA+JnOZjOhdeWFiL2dqUxpZmovk271Bm1ba647PDGj3D8yYc7XqD5BcplwvxYCUT4ekNH7gn6vigld+YBhfJhs7DAOSb7CQXEBEi/T2WwmtK58+B/oqu1MZUozU3uZdKs3aNtac12Pq0y5v8FlzteoPkFyGaNfG328SETvC/q9KiZ05Y0zG5KNHcYhyVc4KC5A4mU6m82EVpXfta0dj/QMhLZ3bo3czmSmNDO1l0m3eoOurTsb3crrdnjd2Lk1svzOrYvls2E/Idkg3K8fer4fN1/WGuHjKytKccv7zlT6vSomOprV8dbZ7LYkdhiHJF/hnOICJZ6iQDw1CWN5Y31GNYuITGm3E21ed0aT3MIVDjwuJzrjKBxoyPk5xYB5NQmzahW6ttZdN1g+WH+8Z5Oq8ko8zN6vTeCc4hwn3K89LmdIaaKitAhzCwGsWlKfGJuKVgiqr3aiyLE4famitAizC4GQWkWwfLj6hNnYUcVEgnVxTjGxK1SfIMvEUhRIRE3CmGmsqs+43bW6Bl2r039vRgIBqVQ+KFTFAjNqEskokcRqa9V1S0uLlEl1Vthvlkxl1RNiROXXp9dH+/jp9XqFoNJigU9+97mYvms2duKpFRV4givJMzh9gkTxxvjJUAcILCZQ3LqnF5s7m0Lbtzz4Et4YP5lNMxNGdT+5ZH82Mdt2ud7WuW4/KQx0ftrT77PcdxkTpJDgoJhEkaiaRK5kGjNTOnmsUiLJlbbOdftJYaDzU6vUJRK5FmOC5CMcFJMoElWTyJVMY2ZKJ49VSiS50ta5bj8pDHR+apW6RCLXYkyQfISDYhJFImoSuZRpzEzp5LFCiSSX2jrX7SeFgc5PrVKXSORajAmSj1B9giiJVJ9wYn2DC/2+aW2msTE7OTwzWrUd7/xUM/519qSoWJAX6hNmMfpCPOUQv38eB4d8GJ6YgcdVhg6vG05nselnnC0ViHSrW6QJqk/kOeHxUFFaDCEkZucljk/NwOtyYkVlCQZPLB6bW1hATUVZSJEi2fgJXnP85AxKixw4Nbtgti6qTxC7QvUJkhgq9YnwbGNVeWN2crhaxZracnx2Yytu3dOrzIq2OuM/XrY0SZxYvqB6NrOzC9jbO4QdDy8/651b27Gl3YsnDo+ZUrHIlgpEOtUtCEkGVTzctrkN33jq1ZAi0M2XtWL3s0fx9qlZ3Hn1uTgxPYebfvhi0vGji8ELTqvNhT8SCUkKTp8gUVihOBCuVrG5syk0IFbVZ3V2M7OlrcNsW/YM+kID4mD5HQ/34uCQr6BULAixElU83P5IX4Qi0F2PH8aHNjRbpkTBGCSFCAfFJAqrFAeCahVCIGZ9Vmc3M1vaOsy25bCm/PDETEGpWBBiJYkqAgW3rVCiYAySQoSDYhKFVYoDRrUKXX1WZzczW9o6zLalV1Pe4yorKBULQqwk0T42uG2FEgVjkBQiHBSTKKxQHAhXq9h3YAC7trVr67M6u5nZ0tZhti07Gt3YuTXyWe/c2o4Or7ugVCwIsRJVPNy2uS1CEejmy1rxsxf6LVOiYAySQiSt6hNCiNUAdgNoACAB3CelvMtQRgC4C8AVAE4B+ISU8oVY9RZCJnU8NYd0Z8QbM/Cb3eU4NDKxpEBQjjavK0KBwFjeqPYQT/3B6ox/nT0pql/klPqEVeoNs7ML6Bn0YXjCD4/Lic5GN0pLi7Tl46lPGJ+xzs5sqUBkS/UiRag+kUOE+1h9tTOkElFRWozZhQXUVZVhIQCMTi77IIAw9YkiSCkhhMCp2YVQHcMTy7ESLJ9o/Kj8PljHWydnUEL1CZJfZEV9Yh7AF6SULwghqgE8L4T4lZTy5bAy7wfQuvS5AMD/Xfq3YImn5pCJTPzwDPz5+QD2HBiIUI/Yta0d27qaQgNjVcZ+vG3d9ay2P56SQTaVDtKFVfc0Px/A3oODMZ+98bqxVCaMzzienZlWgchHXyD2QuVj4coR/7jpbMwsBHDnr15RqufEioe1qyKPJRo/sfx+bW0l/jg8yZggBUFap09IKYeCb32llJMADgFoMhTbCmC3XOR3AFYIIbzptMvuxFNzyHQWcN+QL0o94tY9vegb8mXk+qkSL4s6H7Osrbons8/eCuWSbLa93ewh+YfKx8KVI8ZPzYYGxMHj6fbBWH7PmCCFRMbmFAsh1gI4D8DvDYeaALwZtt2P6IEzhBA3CCH2CyH2j42NpctMW5BopnGmsoCHfBpFAV9uZCHHy6JONcvajr5pVea42WdvlXJJtjLc7WZPKtjRL0n8/j0gY6v1ZNKm0Ul/WmKCvknsSkYGxUKIKgAPAficlHIimTqklPdJKbullN11dXXWGmgzEs00zlQWsNddrlYUcOdGFnK8LOpUs6zt6JtWZY6bffZWKZdkK8Pdbvakgh39ksTv34tEbLWeTNpUX+1MS0zQN4ldSfugWAhRgsUB8Q+klD9TFBkAsDpsu3lpX8EST80h01nAbV5XlHrErm3taPO6M3L9VImXRZ2PWdZW3ZPZZ2+Fckk2295u9pD8Q+Vj4coRKytKccv7zsyoD8bye8YEKSTSrT4hANwP4C0p5ec0ZT4A4CYsqk9cAOBuKeX5seothEzqeGoO8dQgkr2eTu0ieL1hnx8etxNtXndK10sVswoB8ZQMElQ6yCn1ifn5APqGfAn7SLjKhNflRMeSyoRuvw6zqhHZUpnIFXsShOoTOUS4jzVUOzHpn8PwhB8rKkox4Z9DXWUZKsqKcXxqBhWlRZhdCKC2sswyVR5VvxnL71OICapPELuSFfWJdwL4OICDQoiXlvb9E4AWAJBSfgPAo1gcEL+KRUm2T6bZppwglppDImoQZjCjdtG1OvuDg2QUAuIpGWRD6SCdBAISvzw0knAbzc4uYE/PYGiJ5qC+8JZ2b0w1CRVm29JubW83e0j+EfSxtbWVUX3Z9o2t+OL+l/HZja1YUVGCT373OUtUH+L1m7H8njFBCoV0q088LaUUUspOKeW5S59HpZTfWBoQY0l14kYp5elSyg4pJV9nxMFqNQi7qV3Eg9nQ8THbRj2DvtCAOFh+x8O9ODjkY1sTkiZUcXr3E4exubMJt+7pRU+/z7LYY79JSHy4ol0OYrUahN3ULuKRTwoB6cJsGw1ryg9PzLCtCUkTsfpe/1wAAcMv/6nEHvtNQuLDQXEOYrUahN3ULuKRTwoB6cJsG3k15T2uMrY1IWkiVt/rLHHAOEsildhjv0lIfEwNioUQHxBC/L0QYkfwky7DiB6r1SDspnYRD2ZDx8dsG3U0urFza6RP7dzajg6vm21NSJpQxen2ja14pGcAu7a1o7PZbVnssd8kJD4Jq08IIb4BoALAewB8C8CVAP4gpbw+feapYSb1srJAUA3irLpq/GlsMqQ0sL6hGv2+aa2ahHG7sdqJ3uEJDE/44XE50dZQjVeOT2nr06k3JKoGEY94ahhGNY4MKQTksPpEfMUQv38eB4d8GJ6YgcdVhg6vG05nsbYenbqFrh6dj5hVySBKqD6RAwSVXEYn/VhVVYZTs3NYVeWEs7gIb0/PAhIYm5pBQ/WiyktxsSNK9SEQkKF4qasqg8MBuMtLQ4NbY4yF7/O6nVgIAGNTkapGVvXbCqg+QexKyuoTF0spO4UQPVLK24UQdwD4uTW2EbMUFzvQtboGXauhVKPYubUd9z65rB5hVJMwboeXX1Nbjhvf0xqhRKBTo3A4RFJqELEwo4bBbGg1ZtUnAgGpVJm4fH2Dsp73nlWPvQcHoxRQrjinAY/0jmDH3jBf3NKOD7Z78OSrxxOuJ1klFULsikrhZfvGVjyw/2X878vPgkM48IWfRMdruOqDqq+/bXMbHnrhGD5z6RmYnZcRMXbPx86L2hesF4Cl/TYh+YCZb53ppX9PCSEaAcwB8FpvEjGLSo1ix8OR6hFGNQnjdnj5zZ1NUUoEsdQorM5qzjU1DDti9pnoyvdp1Cd6BtUKKL3Dk6EBcXD/jr29ODg8YaqeZJVUCLErKoWXoNLE4dGp0IA4eEwVr6q+/vZH+nDtxevQ0x8dq6p9wXqpRkFINGYGxY8IIVYA+BqAFwC8AeBH6TCKmEOnRmFUj0h0O5j5HK++YNay1VnNuaaGYUfMPhNdea3Siab8iEatQrdfq3qRpJIKIXZF5+tCAAGp7nON8aqLx+nZeWUdseqlGgUh0SQ8KJZSflFKeUJK+RCANQDOllL+S/pMI4miU6MwqkeY3Y5XXzBr2eqs5lxTw7AjZp+JrrxW6URTvkGjVqHbr6snWSUVQuyKTuFFSqBIqPtcY7zq4rG8tFhZR6x6qUZBSDRxB8VCiA8ZPwA+AOCypf8XBIGAxJGxKTz72nEcGZtCwCggmUVUahQ7t0aqRxjVJIzb4eX3HRiIUiKIpUZhdVZzrqlh2BGzz0RXvs3rUu7vbHQrFVDaPdXYucXgi1va0eExV0+ySiqEZBvdd4VK4SWoNHF6fRW+/JcdceNV1dfftrkNu585go7maKUY1b5gvVSjICSauOoTQoj/jHFYSimvs9ak+GQ6k9rqRLJ0YFSjWN/gQr9vOpS1bFRrMG43u8txaGQi4fPDs5QDAYkn/jSCnn4fAhJwCKCz2Y2NZzUk3T5BpYJErp9BckZ9IplnYmzzYBvr9ht9rs3rhsMhsP/YcSwsCByfmsGqqjIUFUl0t6wCgITrYZKdaag+YQPifVdEq0/Mo6y4CHf88o8YODGDq7qbcWZDNdZ7XDhtlbqPC1drWVVVhmIH4DKoT4THmGpfeN+tO2YRVJ8gdkXpmwlLstmJTHfwR8amcMXdv42Yf+UsceDR7ZdQ/QAF1T45MyjO1jMpIF+wGxwU2wCz/l8A8cJBMbErSt/k4h0JwISE2LB97Ee2ngl9gRQyViW4Ml4IyQ4JD4qXFu+4BsBnsTjCvgqLCXd5DxMSYsP2sR/Zeib0BVLIWJXgynghJDuYeVN8sZTyWgBvSylvB3ARgDPTY5a9YEJCbNg+9iNbz4S+QAoZqxJcGS+EZAczK9oZF+8YR4Es3uFwCGxq8+Ds7ZdkO9ErYcwunZvKMs3paB+rl40uNJJ5Jla0ucMhcPn6Bjxww4URvpfsyoYqe+gbxK5E+78zpKRyZGwqymfD4/StkzMoKXLg1OwC3hg/mZRfMzYISQ0zg2Lj4h0SwLfSYpUNcThExHKbdka1FGispXOtUNewsn1yQe0jFzDzTKxqc7PLS5u1R7fsNH2D2AGd/5cWC9z0wxeVPutwCKytrcQfhydT8mv2m4SkjpnpE181Lt4BYFd6zCKpoFoKNNbSuXZb7tNu9hQCVrV5uuvRLTtN3yB2QOe3Pf2+mD5rRdyw3yQkdcwMip8N/kdKOSOl9IXvI/ZBuzSvZulcu2VA282eQsCqNk93PTrfpm8QO6DzW+NaT0aftSJu2G8Skjpxp08IITwAmgCUCyHOw7K2mwtARRptI0kSXArUqH2pWzo3mAFtLJ+tDGi72VMIWNXm6a5H59v0DWIHdH5rnL1g9Fkr4ob9JiGpk8ib4r8A8G8AmgHcCeCOpc/nAfxT+kwjyaJaCjTW0rl2y4C2mz2FgFVtnu56dMtO0zeIHdD5bWezO6bPWhE37DcJSZ2EV7QTQnx4aT5x4pUL8R0AmwGMSinbFccvBfAwgNeXdv1MSrkzXr35sDpTvCxhs1nExvLeqjL0Dk9geGIGHlcZOrxuOJ3F2vKN1c6l8n54XU60eVwYnPSHjgeXWU7W3mTvx2ZqHxlZ0c6scogOq9pcZ4+ufr9/HgeHfFG+Z7Yes8tOFzhc0S5DxIurU9Oz6B2exMjEDBpcZXCVF6G8pBgnTs5haGLR98+qq8KfxiYx5POjuaYczuIivD09CwGBt07OoMGVXNzbMDa4oh2xK0rfNKM+8T9CiG8DaJRSvl8IcQ6Ai6SU345xzncB3ANgd4wyv5VSbjZhR84TL0vYbBaxsXz3Gjeufsca7HhYrT6RSPmdW9vx4HNHsf+oD2tqy/HZja0RahZm7E0mKzqX1D6sxKxyiA6r2lxnz5aORvz6T6NR9W9srcPe3qEoX/pgmwf//fJwwvUE7VT5QKH6Bsk+8eJqenoOj/SOYMfeZT//6oc7cOLUHP7Pz/8YERP3PnkYs/MS1160Bj9+7hiu6W7B3U8cTkk5grFBSGqY+TP0PwH8AkDj0vYrAD4X6wQp5VMA3krOtPwlXpaw2SxiY/lrL14XGpQEzw9Xn0ik/I6He3HtxesAAJs7m6LULMzYy6zoxDGrHKLDqjbX2dMzqFaBODjkU/rSweEJU/XQN4gdiRdXB4cnQgPi4PFXx06GBsTBfTse7sXmziZ8aEMz7nr8MDZ3NoUGxKp6CSGZwcygeJWU8kEAAQCQUs4DWLDAhouEEAeEED8XQrTpCgkhbhBC7BdC7B8bG7PgstkjXpaw2SxiY/npmfmY6hOJlp+enQcACIGU7M33rGgrfdOscogOq9pca4+m/uGJGeX+Ec1+XT354hvZJJ/6TLsQv6+L9vOAVPefQiz3rfH62HyDvknsiplB8UkhRC0WF+2AEOJCAOZeX0XzAoA1UsouAF8HsEdXUEp5n5SyW0rZXVdXl+Jls0u89e7jHY9XX0VZsfL8oPpEouXLS4sjtpO11+z95BpW+mZQXSGcWMohOqxqc609mvo9rjLl/gbNfl09+eIb2SSf+ky7EL+vi/bzIqHuP4NTXcMT43T15hv0TWJXzAyKbwGwF8DpQoj/weI84c+mcnEp5YSUcmrp/48CKBFCrEqlzlwgXpaw2SxiY/n7nzmCnVv16hOJlN+5tR27nzkCANh3YCBKzcKMvcyKThyzyiE6rGpznT2djW5l/R1et9KXOjzm6qFvEDsSL646PC7s3BLp56fXVeKf3n92VEw80jOAh57vx82XtWLfgQFs39jKOCARNK1ugRAi6U/T6pZs30LOkbD6BAAIIYoBnIXFrL0/SSnnEjhnLYBHNOoTHgAjUkophDgfwE+x+OY4plG5kEmdqBqDLkvYbBaxsXyzuxyHRiYw7PPD43bizFVV6BuZjFKX0JVf3+BCv286dDyoPmHcDt5f8PxFZYHl843qFbrzbZAlnQgZVZ8IPos2rzsl9QmdeoNO7cG4f3Z2AT2DPgxP+OFxOdHZ6EZpaZFBTWLZzunpORwcnghl33d4XCgvLzFdDzEF1ScsJFb/rYqrQECGfHjtqnJMTi/grVNzqKkowcT0HOpdTsiAxIBvGnVVZQhIiWKHAxP+WdRVO+EsLsKJ6VmUFDlwanYhKcUhm/ahVJ9IgUK//zSTmvqEEMIJ4P8B8C4sTqH4rRDiG1JK7aQnIcSPAFwKYJUQoh/AbQBKAEBK+Q0AVwL4WyHEPIBpAB+JNyDOBRLJ/I+XJWw2i1hVvmt1DbpWA7OzC9jTMxilCLCts1FZPoixvuC26v52bWvH1584jKPj0zHVKnTnJ5Npna8UFzuinkUyqHxC1/aXr2/ALw+NKPer1CF05d97Vr0plQldPfQFki3i9U/GuFIptHztyk44hAPXfucPoX23vO9MlBU5cMuDByLqPcfrNu3r7EMJSQ9mXsfsBtCGxbm/9yz9/3uxTpBSflRK6ZVSlkgpm6WU35ZSfmNpQAwp5T1SyjYpZZeU8kIpZfJ/EtkIu6kt9AyqFQF6BpObEq66v1v3LGZTA6mrVZD0oWv7viG1CoTZ/T2D5tQqdPXQF0i2MNs/qRRaDo9O4Qs/iazjzl+9gvFTs5b4OvtQQtKDmUFxu5Tyeinlk0ufv8HiwJgYsJvagi7Df2QiOXt09yeWXlCkqlZB0oeu7XUqE2b361UpzNVDXyDZwmz/pPJhneJEwPA7aLK+zj6UkPRgZlD8wpLiBHH5ex8AACAASURBVABACHEBAE5SU2A3tQWvxp4GV3L26O4vfOJLIatR2Bld23vduv1q9Qltea0qhbnr0hdItjDbP6liRKc4YZzZkKyvsw8lJD2YGRT/GYBnhBBvCCHeAPAsgHcIIQ4KIXrSYl2OYje1hY5GtSJAZ6M5RYMgqvvbtW0xmxpIXa2CpA9d27d51SoQbV6XqfIdjW5TKhO6eugLJFuY7Z9UCi1n1Ffhjqsi67jlfWeitqLUEl9nH0pIekhYfUIIsSZOkQkp5dupmxSfXMikNqseEZmBX44zV1VGqEWsb6jCyyNToe2Opcz9RPH753FwyIfhiRl4XGVo97gwNDUTpQ6h2zbab1QMiKdWkaq6hk3IiPqEDqOPtHldMVUa4qlMGNteV7/Rdzq8bjidxTg1PYve4cmQykS7pxoV5aValYl4ahg55gt2g+oTJklEYcI3PYv5BYnRyRk015QDEhidnMGKihJMzsyhvtqJgJQY8c3AXVEC3/QcVlaUos5VivGpWSwEgONTM/C6nSh2CIxO+lHtLMXcQiBlxYgciRuqT6RAod9/mklNfUJKeTRm7UK8AGCDSaPyFjPqEcbs5TW15bjx0tbQcqHda9y4untNaDtcPSKRgXEgIPHE4bFQYoZKHSJcPUK1HZ7ZHAhIrWKASq0i1fYh6gz3Xdvasa2rSTkwjpedrlKlUD3Tja112Ns7FKVcckVbHR7tHYv0yS3t2NzegN+8Op7wdQH6Ask8iShMNLvLsf/o29jxcC9qKkpx7UVrcNfjh0PlP//eM9H/1nRoCWdniQPbN7bigf3H8FcXrEFZkQNffuyPyvqtgHFDiPVYKQZquz9RcwVj9vLmzqbQYAMArr14XcS2WfUIY6aySh0iXD1CtU31iOyiynC/dU8v+obUPmD2GenKHxxSK5e8PHwy2if39qJ3eJK+QWxPIvERrtrzoQ3NoQFxsPy///oVHD8ZqSZx9xOHsbmzyVKlCUJI5rByUMx39ElizF42qjdMz8ynpB5hzFTWqUMIEXub6hHZQ6v24FO3udlnpCs/PDGj8T1z++kbxE4kEh/hiim6PlOlJhEsa5XSBCEkc3DZKBugy/APUlFWnJJ6hC5T2bhtVI8wblM9InvofMTjVre52WekK+9xlWl8z9x++gaxE4nEh1FJJVE1CSmtVZoghGQOTp+wAcbs5X0HBrBzy/L2/c8cidg2qx5hzFRWqUOEq0eotqkekV1UGe67trWjzav2AbPPSFe+w6tWLjnHUxntk1va0e6ppm8Q25NIfISr9jz0fD9uvqw1ovzn33smVlVGqkls39iKR3oGLFWaIIRkjoTVJ0InCFEPIPTnrpTy2NL+lVLKt6w1T00+ZlKHZ+yHq00EM6PXN1Ti5eGpkAJAm6cah4+fTFiJwKgssL6hOqZaRJ6qR6SKLdQnhn1+eNxOtHndCalPJKoyYVQUCdavU5+Ynp7DweGJkPpEh8eF8vIS0yoZxBKoPmGSWH1Y8NiJU7OYD0iMTsygqcaJIiEwOjkDV3kJTkzPob6qDA4HMOJbVqSorXRiRUUxxiZnUFLkwKnZBXjdTiwEgNFJtZpPHkP1iRQo9PtPM6mpTwghtgC4A0AjgFEAawAcwtKqdpkaEOcjgYDEr/80qs2EVmVK79zajnufjFSLiKVEkIxaBNUj7EVxsQNdq2vQtTqx8qpnpFOx2NLRqPTBy9c3RCiXhPtOeXkJzj+tNuKasXytQAYBJEfQ9WHB/vYrjx3CNd0tuPuJZcWJez52HmYXJK79zh8i/Lu0WODjhn2x+m/GBCH2xMzrmy8CuBDAK1LK0wBcBuB3abGqwIiXCa06vuPhaLUIq5QISP6iU7HoGfQpfaRvSL3frIoFfY3kCkEf3tzZFBoQA4u+3NOvjoeefp+p/psxQYg9MTMonpNSjgNwCCEcUsonAXSnya6CIl4mtO64UR3CKiUCkr9oVSw0PqIrb1bFgr5GcoWgD6sUJwIycRUKqvUQknuYGRSfEEJUAXgKwA+EEHcB4J+6FhAvE1p33KgOYZUSAclftCoWGh/xuq1RsaCvkVwh3IeNvlwkElehoFoPIbmHmUHxVgCnAHwewGMAXgPwwXQYVWjEy4RWHd+5NVotwiolApK/6FQsOhvdSh9p86r3m1WxoK+RXCHow/sODGD7xkjFiY5mdTx0NrtN9d+MCULsSULqE0KIIgC/llK+J/0mxceOmdTBbOWgWoTZ7GJj5v/6Bhf6fdOh+oxqEM3uchwamUhZiYCYIqvqEzp0vhdPZcLoOzofMes79LWsUJDqE6n2u7r6xk/OQEBgamYOVWUlmFsIhOoHEOXfqn1U6wFA9YmUKPT7TzPJq09IKReEEAEhhFtKmdjawgVEqtnFqoz9Xdva8fUnltUlVGoRqSoRkNxH53vvPaseew8ORqlMBBVKVL6j8xGzvkNfI5nAalUHVX3bN7bigf3H8A+b1uOC02pD9ar8m2o9hOQ+ZqZPTAE4KIT4thDi7uAnXYblEqlmF6vOv3VPpLoEs5WJCp3v9QyqVSZ0CiWE5BpWqzqo6rv7icPY3NnE/peQAsHMoPhnAP4Fi4l2z4d9Cp5Us4sTVZdgtjIxovMdnZqETqGEkFzDalWHWP0w+19CCoOEF++QUt6fTkNymWB2cXiHaia7WHe+UV2C2crEiM53vJr9OoUSQnKNVPvdROuTkv0vIYVCwm+KhRCvCyGOGD/pNC5XSDW7WHX+rm2R6hLMViYqdL7X0ehWqkzoFEoIyTWsVnVQ1bd9Yyse6Rlg/0tIgZDwm2JELtThBHAVgJWxThBCfAfAZgCjUsp2xXEB4C4AV2BR7u0TUsoXTNiUMYxZzkH1h2Bm/3vPqsej2y9JKrvY4RC4fH0DHrjhwlB96xuqsaGlJlRfS01FxPWDahS6rGurs7JJ8ph9Frryuv3vPase37/+AgxP+OF1OdHR6EZpaRG2dTWhtb5KqzKRaP2E2BGHQ2BTmwdna/pdlfoKgKh9DocI+f1ZDdV47OZLMOTzo6K0CLMLAbzzjFrMLgRw7K2TWAgAo5OMD0LyFTPTJ8YNu/5fIcTzAHbEOO27AO4BsFtz/P0AWpc+FwD4v0v/2gpjVnL3Gjeufsca7Hg4OrM/mexilfpEuNqEKitap04RHNxYmZVNksfss9CVv3x9g9JHzKpMmK2fPkPsjE7VYX4+gD0HBiLi4kt/2YHSIoG/+2lPaN/XruyEQzjwhZ9E+z2AUKzUVJTi2ovW4K7HDzM+CMljzEyf2BD26RZCfAZxBtVSyqcAvBWjyFYAu+UivwOwQgjhTdSmTGHMSr724nWhATGQemZ/vCxqs+oUVmdlk+Qx+yx05fuGfJaoTJitnz5DcpG+oei4+Of/OojDo1MR+w6PToUGxMF9Qb8Pj5UPbWgODYiN5Qgh+YMZ9Yk7wj5fBvBnAK5O8fpNAN4M2+5f2heFEOIGIcR+IcT+sbGxFC9rDmNW8vTMvKWZ/fGyqM2qU1idlU1iE8s3zT4LXfkhnzUqE2brp8/kLtnsM7ONzp8DhnUMAhJavw+PlaAChaocMU8h+2ZGcRRDCJH0p2l1S7bvIOOYmT6R1dXspJT3AbgPWFwBJ5PXNmYlV5QVW5rZHy+L2qw6hdVZ2SQ2sXzT7LPQqkm4y9U+Z1JlQl8/fSbfyGafmW108WKc6VAkENPvw48xPqyjkH0zowTmU14Rr9AwM33iFsXneiHEuSlcfwBA+LpazUv7bIUxK/n+Z45g51brMvvjZVGbVaewOiubJI/ZZ6Er3+Z1Kfd3mlSZ0Nfvps+QvKHN64qKiy/9ZQda66si9p1RX4U7rlL7fXisPPR8P26+rJXxQUieIxJdF1sI8UMsKlDsW9q1GUAPgLUAfiKl/KrmvLUAHtGoT3wAwE1YVJ+4AMDdUsrz49kSa630dGFcuz6oPmHM7Leqfp2aRLgaxbG3TyVcnpnSlhC3AVW+afZZ6Mrr9gez7BP1RbP1k5wg5oPKRp+ZbVRxASBqX1B9QuX34THhcTmxEADGphgfJkiqzwydLETKbzoTHePYESvuP6Xz//bdQGA+6fMbm1dj4M1jSZ+fZpS+aUaSrRnABinlFAAIIW4D8N8A3o3Fle2iBsVCiB8BuBTAKiFEP4DbAJQAgJTyGwAexeKA+FUsSrJ90oQ9GUWV5WzM7Le6/njHzZYn2cHss9CV1+1XqUxYWT8huYguLlT7dH6vionT6xkfpEAowOkXZgbF9QBmwrbnADRIKaeFEDOqE6SUH41VoVz8E+5GEzYQQgghhBBiOWYGxT8A8HshxMNL2x8E8EMhRCWAly23jBBCCCGEkAyR0KB4aeW57wL4OYB3Lu3+jJQyOBHor6w3jRBCCCGEkMyQ0KBYSimFEI9KKTsAFFa2BiGEEEIIyXvMyCW8IIR4R9osIYQQQgghJEuYmVN8AYC/EkIcBXASi3IWUkrZmRbLCCGEEEJIbrK0ol6yZEPSzcyg+C/SZgUhhBBCCMkfclDSzcwyz0cBQAhRD4BrWxJCCCGEkLzBzDLPW4QQhwG8DuD/A/AGFtUoCCGEEEIIsY6l6RfJfppWt5i+pJnpE18EcCGAX0spzxNCvAfAX5u+IiGEEEIIIbHIwvQLM+oTc1LKcQAOIYRDSvkkgG7TVySEEEIIIcRmmHlTfEIIUQXgKQA/EEKMYlGFghBCCCGEkJzGzJvirQCmAXwewGMAXsPiUs+EEEIIIYTkNGbUJ8LfCt+fBlsIIYQQQgjJCnEHxUKISQBSdQiLi3e4LLeKEEIIIYSQDBJ3UCylrM6EIYQQQgghhGQLM4l2JIxAQOKN8ZMYmfCjweXE2tpKOBzJL2dICEkNxmTmYFsTQvIRDoqTIBCQeKxvGLc8+BL8cwE4Sxy48+pzsanNwy8GQrIAYzJzsK0JIfmKGfUJssQb4ydDXwgA4J8L4JYHX8Ib41SoIyQbMCYzB9uaEJKvcFCcBCMT/tAXQhD/XACjk/4sWURIYcOYzBxsa0JIvsJBcRI0uJxwlkQ2nbPEgfpqZ5YsIqSwYUxmDrY1ISRf4aA4CdbWVuLOq88NfTEE59Stra3MsmWEFCaMyczBtiaE5CtpT7QTQmwCcBeAIgDfklL+q+H4JwB8DcDA0q57pJTfSrddqeBwCGxq8+Ds7ZdgdNKP+monWmoqmI1NiIWYUThQxSRjMD0Y27quyokiB/D718fZ9xESRtPqFgz2v5ltM4gJ0jooFkIUAbgXwPsA9AN4TgixV0r5sqHoA1LKm9Jpi9U4HALr6qqwrq6K2diEWEwyMRUekyS9BNt6bW0l+z5CNAz2v4lrvvlM0uc/8OmLLbSGJEK6p0+cD+BVKeURKeUsgB8D2Jrma2YcZmMTYi2MqdyAz4kQkk+ke1DcBCD8t4P+pX1GPiyE6BFC/FQIsVpVkRDiBiHEfiHE/rGxsXTYmjTMxi5s7OybuQpjKnUy4Zd8TiQZMtZnOoohhEj607S6JX22EVtih8U79gH4kZRyRgjxaQD3A9hoLCSlvA/AfQDQ3d0tM2tibILZ2OFfDszGLhzs7Ju5CmMqdTLhl3xOJBky1mcG5jl9gZgi3W+KBwCEv/ltxnJCHQBASjkupZxZ2vwWgD9Ls02Ww2xsQqyFMZUb8DkRQvKJdL8pfg5AqxDiNCwOhj8C4GPhBYQQXinl0NLmFgCH0myTJRgz4ze21uH711+A4Qk/vC4nOhrdMRNNZmcX0DPoiyhfWlqU8PWY4U3ymVhqEvPzAfQN+TDk88PrLkeb14XiYvN/3+tiSrU/EJCWXNMqGzOB6trz8wH0DPqWVCfKIAGcVV+Fn37mIvS/PQ2v24n1DS72VYSQnCStg2Ip5bwQ4iYAv8CiJNt3pJR9QoidAPZLKfcC2C6E2AJgHsBbAD6RTpuswJgZv6a2HDe+pxU7Hu4NZWDv2taObV1Nyi/O2dkF7OkZjCi/c2s7tnU2KgfGVLcghYhKTWJ+PoA9BwZw657EYk2HLqYuX9+AXx4aidh/x1XnIiAD+Luf9qR0TbNkM+5V1/7mxzdgZGI2ot/avrEVD+w/ho+8owW7nz2K0mKBz25sjXg+7KsIIblC2l91SCkflVKeKaU8XUr5paV9O5YGxJBS/qOUsk1K2SWlfI+U8o/ptilVjBnXmzubQl8UwGKiya17etE35FOe3zPoiyq/4+Fe9AyqyzPDm5BF+oZ8oQEXED/WdOhiqm/IF7X/Cz95CYdHp1K+plmyGfeqa09OL0T1W3c/cRibO5tw1+OH8aENzdjc2RT1fNhXEUJyBa5olwTGjGshoMzAHvapM7CHNRnbIxPq8szwJmSRIZ86FnSxpkMXU7r6A4ZUoGSuaZZsxr3q2idn5pX2BPs/IfR9IfsqQkguwEFxEgQzrsNRbXvc6gxsr+b8Bpe6vO56zPAmhYbXXW4q1nToYkpXv/GX/2SuaZZsxr3q2pXOYqU9Ui7/G9xnLMO+ihCSC3BQnATGjOt9Bwawc2t7RAb2rm3taPO6led3NLqjyu/c2o7ORnV5ZngTskib14Vd2xKPNR26mGrzuqL233HVuWitr0r5mmbJZtyrrl3tLIrqt7ZvbMUjPQO4+bJW/OyFfuw7MBD1fNhXEUJyBTvoFGcEYyZ1S00Fjr19SpshHSvr2+EQuHx9Ax644cJQNnrrqgqcVluB4YkZeFxl6PC6tUk4paVF2NbZiHWrKkP1d8ZQn1Bdr83rYuJKgZErCiTptLO42IEtHY1YW1uJ4Qk/PEuxU1zsMKVKEUvd4r1n1YeUZIL1OxwCLSsrMOzzw+N2oi1GfFtFLBvTTXg7vH1qFu7yEoyfnMGZDZX40acuwKDPj7rqMgDA5ec0wD+/gNNWVcLrLsf6hmpsaKnJuM2EEJIqBTEoVmVS79rWjq8/cRhHx6ejMqTjZX0HAjIqQ33n1nbc++RyffGy00tLi9C9dmXC9huvx4zuwiJXFEjSbWcgIPHrP41G1f/es+qx9+CgKVUKnbqFrp6u1TXoUq63mT5UNmaCYDt8/YnDuKa7BXc/cTjUHjdf1ordzx7F26dmcefV52LCP4ebfvhi1PPOtM2EEJIqBTF9QpVJfeueXmzubApth2dIx8v6Vh3f8XBkfVZmp1N9guSKD6TbTl39PYPWqFJYpW6R6wTbYXNnU2hADCy2R1BpItT2/T7b+yUhhCRCQQyKdVncQkRuBzOk42V9J1qfVdnpVJ8gueID6bZTV79O0cVsDFqlbpHrBNtBpyYR7Ot0yhx280tCCEmEghgU67K4pYzcDmZIx8v6TrQ+q7LTqT5BcsUH0m2nVjVCs99sDFqlbpHrhLdDrL5Op8xhN78khJBEKIhBsSqTete2djzSMxDaDs+Qjpf1rTq+c2tkfVZmp1N9guSKD6TbTl39HY1uS1QprFK3yHWC7bDvwAC2b2yNaI+g0kSw7Tub3bb3S0IISYS8TbSbnV1Az6APwxN+eF1ObGytw6NhWdzeqjKsWbmsFtHmqcbBgROhzPVLz6jF9647P3S83eOKyKj/8zNWYvd152NkYgYNrjKc5anE2tqK0HabpyoiE359QzX6fdOh85vd5Tg0MhE6flZdFf40NqnMnFdlobfUVOSEEgGxhmwqEejQqUxsbK2LiJ0O76J6g04dYnp6DgeHJ0Kx0+Fxoby8RFu/MfbaPFUoLS3CB87xoGVlRUQ9sVQpdPvD1S28Lic6GvVKE2aVNuymIGK0J7xfOm91Nb52ZRdmFxZC7e11l6HE4UDLygrUVZfBNz0Ht7ME+266CK+NTYf6OjvdIyGEJEpeDopnZxewp2cwtCRp8E3uts5GrKurUh/f0o57f7OoHrGmthw3XtqKHXsjj//60CB++fJxfOqdq3GmpybqePD84PaD+49i/1HfYn3vaY2yJ6hW0b3Gjau710TUZ8ycD89CzxUlAmIt2VIiUKHzwY2tddjbOxTl6x9s8+C/Xx6OUnV4/zn1+O/e0ahY2tzegN+8Oh5V/5+fsVJZ/v3tdfh531jC193c5sUjfUNR+7d0NCrVLVSxZTYO7Ra3RnvC+6mLTluJTR1e/GT/MXx4Qwtuf6RPqT6xfWMrHth/DDdeegZ+99pxPP/mCXx2Y2tEu7JvIoTkCnk5faJn0Bf6cgSW1SF6Bn3643uX1SM2dzaFvnTDj//VhacBAN7bpj4erj6xY28vrr143XJ9CnuC5a+9eF1UfbEy3nNFiYDkLzofPDikjr2DwxNqVYfhKWUs9Q5PKuvXlT80fNLUdQ9qVCZ6Bn0Jx5bZOLRb3BrtCe+nPvGu03Db3j5ce/G60IA4aHO4+sTdTxxe6i/7cOU7WrC5symqXdk3EUJyhbwcFOsy0Ucm/DGPBzOqdRnXJ07NAQDGJhNTn5ienY9ZX7D89My8qYz3XFEiIPmLXgViRhN79tqvs1PXN6hiy2wc2i1ujfaE91Nvn5xb7MM0fVO4+kTwvPGpGW1fx76JEJIL5OWgWJeJ3uByxjxuVI8wHl9RUQIAqK9O7Pzy0uKIbV35irJiUxnvuaJEQPIXnQ96XGWa2LPXfp2dHhOxZTYO7Ra3OnsAYGVlCZwlDm3fFK4+IeXiv7VVZRF1hJdn30QIyQXyclDc0ejGzq2RGeQ7t7ajs9GtP75lWT1i34EB7NwSffwHv3sdAPCrPvXxcPWJnVvasfuZI8v1KewJlr//mSNR9cXKeM8VJQKSv2hVILzq2OvwaFQdPFXKWGr3VCvr15Vf76k0dd0Or1qtorPRnXBsmY1Du8Wt0Z7wfuo/n34dt29pw/3PHMFtm9u06hPbN7bikZ4B7NzShp8+dwz7DgxEtSv7JkJIrpA3iXbGLOot7V6sW1UZ2u5sdKO0tAjA4hLL2zobI463NVTjLE8Vhn1+eNxOtK6qxGmrltUp1nsWtz/YtRoeVxnO9lRi7arlDPhzPJVYV7dc3zkNVVhXt5zB3uZxoXtNTUg5oNldjrMalq93Vl3k9du8+ox3OyoRkMIilg9+sM0TocQSVJNQqUOUl5fgg+0erF0VvV9X/+b2hojy7Z5qVJSXRsV0MOa3dTWhtT46tnT7E42tWG2gU5mwU9yG2zMy4UdFaRGEAL5//QU4PjWD01aVY92q9Tg5O4/d152P0ckZeFxOFAmE1CdOzs7ha1d2weMuQ0ttBW667Ey01FRgQ0uNLe6REELMkBeD4mSyuktLi9C9dmXEvq7VNehaHV2fSh0iqGZRelpR6Pzutc649oQrBwSvp9uOhZ2UCEhhovLB+fmAUu3hA+d4sK9vWKkIU15egvNPq02ofgCoKC9VllfFNAAUFzuUsaXbbya2VGXj9Ud2iluHQ2BtbSX+ODyJT373uQh7W+sXf6l6rG8Yn/n+H0KKFLftXVai2LmlHRd1rILTWYyWlcv3ZKd7JISQRMmL6RNWZ3Ub61OpQ4SrWaTbHkJyhT6NqsPB4YmYijD5RK7Ffyx7w48FFSmMyh8HNSo5hBCSa+TFoNjqrG5jfboM7KCaRbrtISRXGPLplF906hD5FxO5Fv+x7A0/FlSkMJYbmZjJmK2EEJJO8mJQbHVWt7E+XQZ2UM0i3fYQkit43eUm1SHyLyZyLf5j2Rt+LKhIYSzX4CrLmK2EEJJO8mJQbHVWt7E+lTpEuJpFuu0hJFdo82rUHjyumIow+USuxX8se8OPBRUpjMofHRqVHEIIyTXSnmgnhNgE4C4ARQC+JaX8V8PxMgC7AfwZgHEA10gp3zBzDauzulX1NVY7I9QlwtUs0m0PIblCLFUHnTpEvpFr8R/P3vBjXrcT37tuWXWnw+uG05kX+dqEEJLeQbEQogjAvQDeB6AfwHNCiL1SypfDil0P4G0p5RlCiI8A+AqAa8xey+qsblV9qsz2TNlDSK6gU3XQqUPkI7kW/7HsNR5bU5sb90QIIWZJ9/SJ8wG8KqU8IqWcBfBjAFsNZbYCuH/p/z8FcJkQwp6vVAghhBBCSF6S7kFxE4A3w7b7l/Ypy0gp5wH4AESJkAohbhBC7BdC7B8bG0uTuYSYh75J7Aj9ktgV+iaxK0IGF7FPR+VCXAlgk5TyU0vbHwdwgZTyprAyvUtl+pe2X1sqczxGvWMAjqbNcHOsAqC11QbQvtQIt++4lHJTrMJxfNPu92o1hXS/2b7XmL5pgz4z2+2TKrluP5Cde0i0zzyJ3G9fM+SDP5nBjver9M10Z0gMAAifWdi8tE9Vpl8IUQzAjcWEOy1SyjorjUwFIcR+KWV3tu3QQftSw6x9sXzT7vdqNYV0v3a/12z3mXZvn3jkuv2Afe9BSllnV9v+//buPeiKuo7j+PsTUNwUVMgxxWAaxjKdQX3Ea2YqjZWilY2WhlQzTk0q1tjFqdTMLC+pNZamRqA4UAoamoUM4F3iJne8ZaR4wzJRNG/57Y/f98j68JwLz3kOu+ec72vmzNmz57e7393z3d/+9na2UWJ+i6vRl08sBEZKGiHpvcAJwMxOZWYCJ3v3ccBca+Th6xBCCCGEEDpp6JFiM3tL0qnALNJfsk00s1WSzgMWmdlM4HfA9ZIeA14gNZxDCCGEEELYahr+B5Nmdjtwe6d+Z2e6XwO+0Og4GujqvAOoIuKrT0/GV/R57WntNL/tNK/d0ezLp9njh2LPQ5Fja4SY34Jq6I12IYQQQgghNIOWeMxzCCGEEEII9YhGcQghhBBCaHvRKK6DpLWSVkhaKmlR3vF0JmmwpJskPSRpjaQD8o6pRNJuvtxKr5cknZF3XCWSviVplaSVkqZK6tvN8QyTNE/Sah/fhJ6OtUgk9ZW0QNIyn98f5x3T1iCpl6QHJd2WdyxF0Uq53+y/b8G3BUdKeljSY5K+n3c8jSRpoqT1/nyGltas639cU1wHSWuBjkoPGsmTpMnAPWZ2rf8lXn8zezHvuDqT1Iv0f9X7mVnuD2WRtDNwL7C7mf1X0h+B281sUjfGtROwk5ktkbQNsBg4NRw4NQAACvpJREFU1sxW92jQBeGPaB9gZhsl9SEtxwlmNj/n0BpK0reBDmBbMzsq73iKoJVyv9l/36JuC7zufwQYQ3ri7ULgi82YI7WQdAiwEbjOzPbIO55Gatb1P44UtyhJg4BDSH95h5m9UYRKsIzDgb8XoUGc0Rvo5w+U6Q883Z2RmNkzZrbEu18G1rD5o85bhiUb/WMff7X0nrekXYDPANfmHUuRtEruN/vvW/BtwWjgMTN73MzeAKYBx+QcU8OY2d2kv55tec26/kejuD4G3CFpsaRT8g6mkxHA88Dv/bTftZIG5B1UGScAU/MOosTMngIuAZ4AngE2mNkd9Y5X0nBgL+Bv9Y6ryPxU81JgPTDbzFp6foHLge8Cb+cdSFE1ee43++9b5G3BzsCTmc/raIKGU9gyzbT+R6O4Pgeb2d7Ap4Bv+qmRougN7A1caWZ7kZ4tX7jrtfxU3ljgxrxjKZG0HeloxQjgA8AASSfVOc6BwHTgDDN7qf4oi8vM/mdmo0iPdR8tqWVPE0o6ClhvZovzjqWomjn3W+T3bYptQWhNzbb+R6O4Dn5EETNbD9xMOhVUFOuAdZmjdDeRKsai+RSwxMyeyzuQjCOAf5jZ82b2JjADOLC7I/Nra6cDN5jZjB6KsfD8FO084Mi8Y2mgg4Cxfn/BNOAwSVPyDak4WiD3W+H3LfK24ClgWObzLt4vtIBmXP+jUdxNkgb4xeP4qahPAoW5o9TMngWelLSb9zocKOIF7l+kQJdOuCeA/SX19xvHDiddD7XFfPjfAWvM7NIejLGQJA2VNNi7+5FuoHko36gax8zOMrNdzGw46TKguWZW11mFVtEKud8Kv2/BtwULgZGSRvhZwxOAmTnHFHpAs67/0Sjuvh2BeyUtAxYAfzazv+YcU2enATdIWg6MAi7IOZ538Z2JMaQjsYXhR1RuApYAK0jrSXcfU3kQ8GXSEabS3899umciLaSdgHmecwtJ1xQ35d9Yhbq1W+4XWSG3BWb2FnAqMIt04OGPZrYq36gaR9JU4AFgN0nrJH0t75gaqCnX//hLthBCCCGE0PbiSHEIIYQQQmh70SgOIYQQQghtLxrFIYQQQgih7UWjOIQQQgghtL1oFIcQQgghhLYXjeIQQgghhND2olFcYJK+Lmlcg6dxrKTdGzmN7pK0VtKQvONoVZI25h1DniQdKin+Q7nFtFq9KWlULf/vGvm8dbRivSlpvKQP1FBukqTjtkZMeYlGcUFJ6m1mV5nZdQ2e1LFAIRvFoTiU1FVfSOrdU/GE0JUWrTdHAYV/6EHYXBPVm+OBqo3idhCN4hpIGidpuaRlkq6XNFzSXO83R9KuXm6SpCslzZf0uO+5T5S0RtKkzPg2SrpM0ioffqj3v1PS5ZIWARMknSvpzMx3l0la5OPbV9IMSY9KOj8z7pMkLfCnx/xWUq/MNH/q8zBf0o6SDgTGAhd7+Q/5UYn5Pm83S9quwnI5XdJqLzvN+w3weV4g6UFJx3j/8ZL+5PPxqKRzMuO5RdJiXx6nlJlW1TKheyQN9DxcImlF5jcbLulhSdeRHmE+TNKPvN+9kqZ2ys8O7x4iaa13j5c0U9JcYE65aZWJa4CkP3vOrpR0vPffR9Jdng+zJO2UieGXnssrJY32/qMlPeD5eL82Pe42O62qZcKWiXqz7HIpl6eb1Z1Kjz4+Dzjeyx8f+VwMBa43h0t6SNINnvM3Serv321Wdyod+e0gPfFwqaR+ks6WtNDz82pJ6mI6Vcs0JTOLV4UX8FHgEWCIf94euBU42T9/FbjFuycB0wABxwAvAXuSdj4WA6O8nAEnevfZwBXefSfwm8y0zwXOzHx3oXdPAJ4mPVL3fcA6YAfgIx5bHy/3G2BcZppHe/dFwA8zMR+XmeZy4OPefR5weYVl8zTwPu8e7O8XACeV+vmyG0DaE33G4+xHqiw6SsvU30v9d/DPa7PLvasy8aortzf6e29gW+8eAjzmOTwceBvY37/bF1gK9AW2AR7tlJ8dmXGs9e7xnp/bV5pWmfg+D1yT+TwI6APcDwz1fscDEzMxXOPdhwArvXtboLd3HwFM9+5DgdsqlYlXt3Mr6s3yy6ZcnlaqO6/IDB/5nG9uF73eHO55e5B/ngicSfW6syMzju0z3ddn1oF38r5cmWZ/xenM6g4DbjSzfwGY2QuSDgA+599fT6osS241M5O0AnjOzFYASFpFStalpBXmD15+CjAjM/wfKG+mv68AVpnZMz7ux4FhwMHAPsBC32nrB6z3Yd4AStebLQbGdB65pEGkxu1d3msycGOFeJaT9i5vAW7xfp8Expb2hEkVwa7ePdvM/u3TmuHxLgJOl/RZLzMMGAn8u9O0aikTukfABZIOIeXmzsCO/t0/zWy+dx8E/MnMXgNek3RrjeOfbWYvVJnWs10MtwL4haQLSRv7eyTtAewBzPYc70Xa2SqZCmBmd0vaVtJg0oZosqSRpI1Fny6mNaiGMqF2UW9W1lWeVqo7s2rJ1cjnxitqvQnwpJnd591TgNOBv1K57sz6hKTvAv1JO7SrSDuOW1qm6USjuOe97u9vZ7pLn8stb8t0v1LHuAVMNrOzuhj2TfNdOuB/FWLZEp8hHek4GviBpD09hs+b2cPZgpL2493zCWCSDiUdyTjAzF6VdCdpY5AdtmqZUJcTgaHAPmb2pp/CKy3fSvmY9RabLsfq/Ntkx1FpWu9iZo9I2pt0PeX5kuYAN5MaNgeUiWOzHAN+Aswzs89KGk46KtJZLWVC47RTvQld52mlujMr8rkYCllvunL5VanuBEBSX9LZkg4ze1LSuZ2nVUuZZhXXFFc3F/iCpB0AJG1POgVxgn9/InDPFo7zPUDpDs4vAff2QJwAc4DjJL0fUqySPlhlmJdJR9Iwsw3AfyR9zL/7MnBXVwMp3TwwzMzmAd8jHZkYCMwCTitdXyRpr8xgYzymfqQbVe7z4f7jjd0PA/t3MblayoTuGwSs98r2E0C5nLkPOFpSX0kDgaMy360lHW2DTbldz7RQuhv6VTObAlwM7A08DAz1o45I6iPpo5nBStcdHwxs8JweBDzl34+vEFe1MqF2UW9W1lWelqs735mWi3wuhkLWm27XUh3JpnWlUt2ZzbFS4/ZfHm9XcdVSpilFo7gKM1sF/BS4S9Iy4FLgNOArkpaTKsAJWzjaV4DRklaSTjOe10OxrgZ+CNzhsc0mXT9XyTTgO0o3ZHwIOJl0A8ly0l3P5WLrBUzx050PAr8ysxdJRyj6AMv91OdPMsMsAKaTLruYbmaLSKd0ektaA/wcmM/maikTuu8GoMN/y3HAQ10VMrOFpFPRy4G/kE5Hb/CvLwG+IelB0jVvdU3L7QkskLQUOAc438zeIFXAF/r6uBQ4MDPMax7DVcDXvN9FwM+8f7kjfbWUCTWKerNqbF3labm6cx6wu/xGOyKfi6Ko9SakBvA3fZu5HXBllbpzEnCV17WvA9eQ7t2ZBSzsYp5erFamWWnTmaGwtUjaaGYD845ja5I0nnSq5dS8YwndJ2mgmW1Uupv5buAUM1uSd1yQ7uQm3cCyKO9YQs9rlXoz8rT9bM160y+Xuc3M9mjE+Ftd7EGGELbE1UoPLehLug6zEA3iEEIosKg3m0QcKQ5VSfo16Q7arF+a2e/ziCe0Fr/udE4XXx1e+reSEJpN1JuhkaLebIxoFIcQQgghhLYXN9qFEEIIIYS2F43iEEIIIYTQ9qJRHEIIIYQQ2l40ikMIIYQQQtv7P2DDJYzbr1GOAAAAAElFTkSuQmCC\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# pair plot 2 com Seaborn\n",
        "sns.pairplot(iris, hue = \"especie\");"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 726
        },
        "id": "-lwa4ByrLFd8",
        "outputId": "016bfca7-43b8-467d-d796-57c62371f3b4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 823.25x720 with 20 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Assim como a Matplotlib, a biblioteca Seaborn é muito extensa e seus gráficos podem ser personalizados de acordo com sua necessidade. Recomendamos que você explore mais exemplos na documentação oficial de acordo com a sua necessidade de uso."
      ],
      "metadata": {
        "id": "0f3-BQEpLHN_"
      }
    }
  ]
}