K_Means_Clustering_on_blood_cell_data.ipynb

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      "cell_type": "markdown",
      "source": [
        "Load and analyze blodd cell data"
      ],
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      "source": [
        "#import necessary libraries\n",
        "import pandas\n",
        "from sklearn.preprocessing import StandardScaler, MinMaxScaler\n",
        "from sklearn.decomposition import PCA\n",
        "from sklearn.cluster import KMeans\n",
        "from sklearn.metrics import silhouette_score\n",
        "import numpy\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#read file\n",
        "dataframe = pandas.read_table('/content/drive/MyDrive/AI_resources/flow-cytometry-40k.txt', sep = ' ', header = None)"
      ],
      "metadata": {
        "id": "g29tDOcNcjKo"
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      "execution_count": 2,
      "outputs": []
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      "source": [
        "#drop first column\n",
        "column_to_drop = 0\n",
        "column_axis = 1\n",
        "\n",
        "dataframe = dataframe.drop([column_to_drop], column_axis)"
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      "execution_count": 3,
      "outputs": [
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          "text": [
            "<ipython-input-3-77624bf3177b>:5: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n",
            "  dataframe = dataframe.drop([column_to_drop], column_axis)\n"
          ]
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              "        FITC-CD3     PE-CD8   ECD-CD19    PC5-CD45     PC7-CD3\n",
              "0       4.315380   5.301481   3.892902  116.485707   11.284839\n",
              "1       2.034189   3.378871   3.017428   63.537658    7.094390\n",
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              "...          ...        ...        ...         ...         ...\n",
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              "      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",
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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-dc5ac210-dcc0-4737-a2bb-dd1f20ce8592 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-dc5ac210-dcc0-4737-a2bb-dd1f20ce8592');\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": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Clean data with missing values"
      ],
      "metadata": {
        "id": "WWOxAcmKhd1F"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#drop row with NULL value\n",
        "dataframe_copy = dataframe.copy()\n",
        "\n",
        "row_axis = 0\n",
        "\n",
        "dataframe_copy.dropna(axis = row_axis,\n",
        "                      inplace = True)\n",
        "\n",
        "dataframe_copy"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "z3Qvt_vphgsl",
        "outputId": "b1bca31a-1b22-4997-c748-aa4c51fa19fc"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        FITC-CD3     PE-CD8   ECD-CD19    PC5-CD45     PC7-CD3\n",
              "0       4.315380   5.301481   3.892902  116.485707   11.284839\n",
              "1       2.034189   3.378871   3.017428   63.537658    7.094390\n",
              "2      19.018191  11.923801   5.848890  194.091982   98.327730\n",
              "3      18.117922  14.278425   6.015783  227.966526  145.721575\n",
              "4       6.203657   5.125051   2.734187   95.794769   12.134564\n",
              "...          ...        ...        ...         ...         ...\n",
              "39995   2.020838   2.534869   1.887323   59.295711    9.926805\n",
              "39996   3.795627   6.340987   3.256801  145.446916   14.008535\n",
              "39997   1.364709   2.271654   2.296450   27.221706    2.868655\n",
              "39998   2.260210  17.645853  27.465847  264.618172   25.784517\n",
              "39999   2.911570  21.318456  10.092745  195.862003   70.831366\n",
              "\n",
              "[40000 rows x 5 columns]"
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              "      <th>FITC-CD3</th>\n",
              "      <th>PE-CD8</th>\n",
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              "      <td>11.284839</td>\n",
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              "      <th>1</th>\n",
              "      <td>2.034189</td>\n",
              "      <td>3.378871</td>\n",
              "      <td>3.017428</td>\n",
              "      <td>63.537658</td>\n",
              "      <td>7.094390</td>\n",
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              "      <th>2</th>\n",
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              "      <td>11.923801</td>\n",
              "      <td>5.848890</td>\n",
              "      <td>194.091982</td>\n",
              "      <td>98.327730</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>18.117922</td>\n",
              "      <td>14.278425</td>\n",
              "      <td>6.015783</td>\n",
              "      <td>227.966526</td>\n",
              "      <td>145.721575</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>6.203657</td>\n",
              "      <td>5.125051</td>\n",
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              "      <td>95.794769</td>\n",
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              "      <th>39995</th>\n",
              "      <td>2.020838</td>\n",
              "      <td>2.534869</td>\n",
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              "      <td>59.295711</td>\n",
              "      <td>9.926805</td>\n",
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              "    <tr>\n",
              "      <th>39996</th>\n",
              "      <td>3.795627</td>\n",
              "      <td>6.340987</td>\n",
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              "      <td>145.446916</td>\n",
              "      <td>14.008535</td>\n",
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              "    <tr>\n",
              "      <th>39997</th>\n",
              "      <td>1.364709</td>\n",
              "      <td>2.271654</td>\n",
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              "      <td>27.221706</td>\n",
              "      <td>2.868655</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39998</th>\n",
              "      <td>2.260210</td>\n",
              "      <td>17.645853</td>\n",
              "      <td>27.465847</td>\n",
              "      <td>264.618172</td>\n",
              "      <td>25.784517</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39999</th>\n",
              "      <td>2.911570</td>\n",
              "      <td>21.318456</td>\n",
              "      <td>10.092745</td>\n",
              "      <td>195.862003</td>\n",
              "      <td>70.831366</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>40000 rows × 5 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-2b347bc3-b9b1-471d-ad87-789630c7c1a5')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "\n",
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              "\n",
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              "      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-2b347bc3-b9b1-471d-ad87-789630c7c1a5 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-2b347bc3-b9b1-471d-ad87-789630c7c1a5');\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": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#replace NULL value by the mean of the column\n",
        "dataframe_copy = dataframe.copy()\n",
        "\n",
        "average = dataframe_copy['FITC-CD3'].mean()\n",
        "\n",
        "dataframe_copy.fillna(average, inplace = True)\n",
        "\n",
        "dataframe_copy"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "OTfYkwcSlJI3",
        "outputId": "c0c679f9-cc7f-48c5-81a5-c7e26e5ba8da"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        FITC-CD3     PE-CD8   ECD-CD19    PC5-CD45     PC7-CD3\n",
              "0       4.315380   5.301481   3.892902  116.485707   11.284839\n",
              "1       2.034189   3.378871   3.017428   63.537658    7.094390\n",
              "2      19.018191  11.923801   5.848890  194.091982   98.327730\n",
              "3      18.117922  14.278425   6.015783  227.966526  145.721575\n",
              "4       6.203657   5.125051   2.734187   95.794769   12.134564\n",
              "...          ...        ...        ...         ...         ...\n",
              "39995   2.020838   2.534869   1.887323   59.295711    9.926805\n",
              "39996   3.795627   6.340987   3.256801  145.446916   14.008535\n",
              "39997   1.364709   2.271654   2.296450   27.221706    2.868655\n",
              "39998   2.260210  17.645853  27.465847  264.618172   25.784517\n",
              "39999   2.911570  21.318456  10.092745  195.862003   70.831366\n",
              "\n",
              "[40000 rows x 5 columns]"
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2.034189</td>\n",
              "      <td>3.378871</td>\n",
              "      <td>3.017428</td>\n",
              "      <td>63.537658</td>\n",
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              "      <th>2</th>\n",
              "      <td>19.018191</td>\n",
              "      <td>11.923801</td>\n",
              "      <td>5.848890</td>\n",
              "      <td>194.091982</td>\n",
              "      <td>98.327730</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>18.117922</td>\n",
              "      <td>14.278425</td>\n",
              "      <td>6.015783</td>\n",
              "      <td>227.966526</td>\n",
              "      <td>145.721575</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>6.203657</td>\n",
              "      <td>5.125051</td>\n",
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              "      <th>39998</th>\n",
              "      <td>2.260210</td>\n",
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              "      <th>39999</th>\n",
              "      <td>2.911570</td>\n",
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              "<p>40000 rows × 5 columns</p>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-49427ab2-a99e-4905-8adc-08ecb47d1850')\"\n",
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              "      </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-49427ab2-a99e-4905-8adc-08ecb47d1850 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-49427ab2-a99e-4905-8adc-08ecb47d1850');\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",
      "source": [
        "dataframe.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qn3PIYwploZf",
        "outputId": "376e5865-993f-4dc2-93a4-af19b42ec322"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 40000 entries, 0 to 39999\n",
            "Data columns (total 5 columns):\n",
            " #   Column    Non-Null Count  Dtype  \n",
            "---  ------    --------------  -----  \n",
            " 0   FITC-CD3  40000 non-null  float64\n",
            " 1   PE-CD8    40000 non-null  float64\n",
            " 2   ECD-CD19  40000 non-null  float64\n",
            " 3   PC5-CD45  40000 non-null  float64\n",
            " 4   PC7-CD3   40000 non-null  float64\n",
            "dtypes: float64(5)\n",
            "memory usage: 1.5 MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#check for outlier\n",
        "dataframe.hist(bins = 50,\n",
        "               figsize = (15, 10))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 728
        },
        "id": "5dZ3XFLBlw_8",
        "outputId": "6bce71de-76c0-4c81-bd81-0550fe5a15f7"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7fde3dcee4c0>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7fde3dcbd910>],\n",
              "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7fde3dc6ed30>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7fde3dc26160>],\n",
              "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7fde3dc54550>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7fde3dc019a0>]],\n",
              "      dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 9
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x720 with 6 Axes>"
            ],
            "image/png": 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Y5EmSJElSj5jkSZIkSVKPmORJkiRJUo+Y5EmSJElSj5jkSZIkSVKPmORJkiRJUo+Y5EmSJElSj5jkSZIkSVKPmORJkiRJUo+Y5EmSJElSj5jkSZIkSVKPmORJkiRJUo+Y5EmSJElSj5jkSZIkSVKPmORJkiRJUo+Y5EmSJElSj5jkSZIkSVKPmORJkiRJUo+Y5EmSJElSj5jkSZIkSVKPmORJkiRJUo+Y5EmSJElSj5jkSZIkSVKPmORJkiRJUo+Y5EmSJElSj+w0yUuyLskDSW4ZKNs/yYYkd7a/+7XyJHl3kk1JbkryooFtVrX6dyZZNVD+4iQ3t23enSQzfZCSJEmSNCx25U7excDKcWVrgI1VtQzY2JYBTgCWtc9q4ELokkLgXOAo4Ejg3LHEsNV53cB2439LkqTe8mKqJGmm7TTJq6pPAw+NKz4JuKR9vwR45UD5pdW5Ftg3yRLgeGBDVT1UVQ8DG4CVbd0zquraqirg0oF9SZI0DC7Gi6mSpBm05zS3G6mqe9v3+4CR9v1A4J6Beptb2Y7KN09QPqEkq+k6NUZGRhgdHZ1m82Fkbzj78G0Trtud/S42W7duHarj3RFj0TEOHePQMQ6zr6o+nWTpuOKTgBXt+yXAKPA7DFxMBa5NMnYxdQXtYipAkrGLqaO0i6mtfOxi6tWzd0SSpPk23STvCVVVSWomGrMLv7UWWAuwfPnyWrFixbT39Z7LruTtN098+HefOv39Ljajo6PsThz7xFh0jEPHOHSMw7yZ84upXkideV4k2c5YdIxDxzh0ZjMO003y7k+ypKrubVcQH2jlW4CDB+od1Mq2sP2K5Fj5aCs/aIL6kiSJubuY6oXUmedFku2MRcc4dIxDZzbjMN1XKKwHxh7qXgVcOVB+Wnsw/Gjg0XYl8hrguCT7tWcEjgOuaeseS3J0exD8tIF9SZI0rO5vF1GZwsXUycq9mCpJQ2ZXXqHwAeBfgB9LsjnJGcD5wMuT3Am8rC0DXAV8EdgE/AXweoD2jMB5wPXt85ax5wZanfe3be7C5wQkSfJiqiRp2nY6XLOqTplk1bET1C3gzEn2sw5YN0H5DcBhO2uHJEl91C6mrgAOSLKZbpbM84Er2oXVLwOvbtWvAk6kuzD6DeC10F1MTTJ2MRW+/2LqxcDedBdSvZgqST232xOvSJKk6fNiqiRppk33mTxJkiRJ0gJkkidJkiRJPWKSJ0mSJEk9YpInSZIkST1ikidJkiRJPWKSJ0mSJEk9YpInSZIkST1ikidJkiRJPWKSJ0mSJEk9YpInSZIkST1ikidJkiRJPWKSJ0mSJEk9YpInSZIkST1ikidJkiRJPWKSJ0mSJEk9YpInSZIkST1ikidJkiRJPWKSJ0mSJEk9YpInSZIkST1ikidJkiRJPWKSJ0mSJEk9YpInSZIkST1ikidJkiRJPbLnfDdgIVq65hMTlt99/s/OcUskSZIkaWq8kydJkiRJPWKSJ0mSJEk94nBNSZI0ZyZ7JAJ8LEKSZop38iRJkiSpR0zyJEmSJKlHFkySl2RlkjuSbEqyZr7bI0lSX9jHStJwWRBJXpI9gPcBJwCHAqckOXR+WyVJ0uJnHytJw2dBJHnAkcCmqvpiVf0XcDlw0jy3SZKkPrCPlaQhs1Bm1zwQuGdgeTNw1PhKSVYDq9vi1iR37MZvHgB8bSob5G278WsL15Tj0GPGomMcOsahMxNxeM5MNETTtij6WOhlP+t/R7YzFh3j0DEOnVnrYxdKkrdLqmotsHYm9pXkhqpaPhP7WsyMw3bGomMcOsahYxyGh33szDMO2xmLjnHoGIfObMZhoQzX3AIcPLB8UCuTJEm7xz5WkobMQknyrgeWJTkkyV7AycD6eW6TJEl9YB8rSUNmQQzXrKptSc4CrgH2ANZV1a2z/LMzMiSlB4zDdsaiYxw6xqFjHBY5+9h5ZRy2MxYd49AxDp1Zi0Oqarb2LUmSJEmaYwtluKYkSZIkaQaY5EmSJElSjwxlkpdkZZI7kmxKsma+2zObkhyc5FNJbktya5I3tvL9k2xIcmf7u18rT5J3t9jclORF83sEMyvJHkn+NcnH2/IhSa5rx/vBNikBSZ7Slje19Uvns90zKcm+ST6U5AtJbk9yzDCeD0l+s/07cUuSDyR56rCcD0nWJXkgyS0DZVM+B5KsavXvTLJqPo5FC499rH2sfax9rH3s/PexQ5fkJdkDeB9wAnAocEqSQ+e3VbNqG3B2VR0KHA2c2Y53DbCxqpYBG9sydHFZ1j6rgQvnvsmz6o3A7QPLbwMuqKrnAg8DZ7TyM4CHW/kFrV5fvAv4u6r6ceAFdPEYqvMhyYHAG4DlVXUY3WQUJzM858PFwMpxZVM6B5LsD5xL91LtI4FzxzotDS/7WPtY7GPtY+1jL2Yh9LFVNVQf4BjgmoHlc4Bz5rtdc3j8VwIvB+4AlrSyJcAd7fufA6cM1H+i3mL/0L0baiPwUuDjQICvAXuOPzfoZqE7pn3fs9XLfB/DDMTgmcCXxh/LsJ0PwIHAPcD+7Z/vx4Hjh+l8AJYCt0z3HABOAf58oPx76vkZzo99rH2sfax9rH3swuhjh+5OHttPvDGbW1nvtdvfLwSuA0aq6t626j5gpH3vc3zeCfw28N22/Czgkara1pYHj/WJOLT1j7b6i90hwFeB/9OG1Lw/yT4M2flQVVuAPwH+A7iX7p/vjQzf+TBoqudAL88N7bahPS/sY+1jsY8F7GMnMed97DAmeUMpydOADwO/UVWPDa6r7hJBr9+lkeTngAeq6sb5bss82xN4EXBhVb0QeJztQwaAoTkf9gNOouuQfwjYh+8fWjG0huEckGaSfax9bGMfi33szszVOTCMSd4W4OCB5YNaWW8leTJd53NZVX2kFd+fZElbvwR4oJX3NT4vAX4+yd3A5XTDSd4F7Jtkz1Zn8FifiENb/0zgwbls8CzZDGyuquva8ofoOqRhOx9eBnypqr5aVd8GPkJ3jgzb+TBoqudAX88N7Z6hOy/sYwH72DH2sR372O83533sMCZ51wPL2gw/e9E9CLp+nts0a5IEuAi4vareMbBqPTA2U88quucIxspPa7P9HA08OnB7edGqqnOq6qCqWkr3z/wfqupU4FPAq1q18XEYi8+rWv1Ff+Wtqu4D7knyY63oWOA2hux8oBtCcnSSH2j/jozFYajOh3Gmeg5cAxyXZL921fa4VqbhZh/bGar/ptrHduxjn2Af+/3mvo+d7wcT5+MDnAj8O3AX8Lvz3Z5ZPtafpLslfBPw+fY5kW6s80bgTuCTwP6tfuhmRrsLuJluZqR5P44ZjskK4OPt+48AnwU2AX8DPKWVP7Utb2rrf2S+2z2Dx38EcEM7Jz4G7DeM5wPwB8AXgFuAvwSeMiznA/ABuuckvk135fmM6ZwDwK+0mGwCXjvfx+VnYXzsY+1j7WPtY+1j57+PTduJJEmSJKkHhnG4piRJkiT1lkmeJEmSJPWISZ4kSZIk9YhJniRJkiT1iEmeJEmSJPWISZ4kSZIk9YhJniRJkiT1iEmeJEmSJPWISZ4kSZIk9YhJniRJkiT1iEmeJEmSJPWISZ4kSZIk9YhJniRJkiT1iEmeJEmSJPWISZ40gSR3J/lmkq0Dn/e2dUuSXJTk3iRfT/KFJH+QZJ+2vpI83rZ5MMnGJL+0C7+52/tN8uok/5zkG0lGJ/iNVyS5pe3jn5McOiMBkyRpCsb1s/cnuTjJ09q645N8uvWFX03yj0l+vq1bkeS74/rnVTv5recl+ZskX0vyaJKbkvxWkj2SLG3969aBtnw8ycsn2deyJP+Z5K8GyqbcJmm2meRJk3tFVT1t4HNWkv2BfwH2Bo6pqqcDLwf2BX50YNsXVNXTgB8DLgbem+TcyX5oBvf7EPBO4PwJfmMZcBnw622/fwusT7LnrgZEkqQZ9IrWp70IWA68OcmrgL8BLgUOAkaA3wNeMbDdV8b1z5dM9gNJfhS4DrgHOLyqngn8Yvu9pw9U3be15QXABuCjSU6fYJfvA66foHyX2yTNBf/nTpqa3wK+Dvy/VfVdgKq6B3jjRJWr6mvAXyb5JvBXSd5bVQ/O1n6r6pMASX51gs2OB/6pqj7T6ryNruP8aWDjrh2+JEkzq6q2JLkaOBz4ZeC8qnr/QJV/bJ/p+APgn6vqtwZ+7472OyTZd1xb7gPeleTJwNuSXDrWLyc5GXgE+GfgudNsjzQnvJMnTc3LgI+M/Qd/Cq6ku6hy5Bzvd7yM+x7gsCn+piRJMybJwcCJwDeAg4EP7WSTH2zDKr+U5IKxxxom8bJd2N9EPgL8IN3IGZI8A3gL3UXZ3W2TNOtM8qTJfSzJIwOf1wHPAu6d6o6q6tvA14D9J6kyW/sd9Engp9uzA3sBbwL2An5gqr8rSdIM+FiSR4DP0N2pe2cr31F/+AXgCGAJ8FLgxcA7dlB/Wv0r8JX2d6x/PQ+4qKo2z0CbpFlnkidN7pVVte/A5y+AB+n+Iz4lbdjHs4GHkvzUwIPZt7Yqu73fndWtqi8Aq4D30nV4BwC3ARN1WJIkzbaxfvY5VfV6ur4QdtAfVtV9VXVbVX23qr4E/DbwPwCSnDrQv17dNplW/woc2P4+lOQIujuCF0y1TdJ8McmTpuaTwC8kmeq/OycB24DPVtU/DTyY/fyZ2u+uVK6qD1XVYVX1LOBcYCkTP0AuSdJcu4NugpSpJEhF+//ZqrpsoH89oa3/5BT3N+YXgAdam1bQ9Zf/keQ+4H8C/yPJ53bWJmm+eAJKU/MO4BnAJUmeA5DkwCTvSPLfx1dOsn+SU+lm43rbJJOuzNh+23TQT6V7Tu9JSZ7a7vaNbffiVufZwFpgfbvDJ0nSvKqqonvm7X8leW2SZyR5UpKfTLIWIMnPJHlOOgfTzSZ95Q52ey7wE0n+d5L/1vbx3CR/NX7SlbZuJMlZbbtz2rPya+lmuj6iff4M+ATdhGbTaZM060zypMn97bh33ny0qh4CfgL4NnBdkq/TzUz5KLBpYNt/S7K1lf0q8JtV9XuT/dAM7vc1wDeBC4Gfat//YmD9u+hmBrsDeBh43ZQiIknSLKqqDwG/BPwK3XNx9wN/yPak6YV0s1s+3v7eDLxhB/u7CziG7k7crUkeBT4M3EA3q/WYR5I83vZ3IvCLVbWu7eMbbUjmfW32za3Af1bVV6fTJmkupLtoIkmSJEnqA+/kSZIkSVKPmORJkiRJUo+Y5EmSJElSj5jkSZIkSVKPmORJkiRJUo/sOd8NmK4DDjigli5dOu3tH3/8cfbZZ5+Za9AiZRy2MxYd49AxDp2ZiMONN974tap69gw1SXPAPnZmGIftjEXHOHSMQ2c2+9hFm+QtXbqUG264Ydrbj46OsmLFiplr0CJlHLYzFh3j0DEOnZmIQ5Ivz0xrNFfsY2eGcdjOWHSMQ8c4dGazj3W4piRJkiT1iEmeJEmSJPWISZ4kSZIk9YhJniRJkiT1iEmeJEmSJPXIop1dc3fdvOVRTl/ziQnX3X3+z85xayRJGg5LJ+l7wf5XkmaKd/IkSZIkqUdM8iRJkiSpR0zyJEmSJKlHTPIkSZIkqUdM8iRJkiSpR0zyJEmSJKlHTPIkSZonSdYleSDJLQNl/zvJF5LclOSjSfZt5UuTfDPJ59vnzwa2eXGSm5NsSvLuJGnl+yfZkOTO9ne/uT9KSdJcM8mTJGn+XAysHFe2ATisqv478O/AOQPr7qqqI9rn1wfKLwReByxrn7F9rgE2VtUyYGNbliT1nEmeJEnzpKo+DTw0ruzvq2pbW7wWOGhH+0iyBHhGVV1bVQVcCryyrT4JuKR9v2SgXJLUY3vOdwMkSdKkfgX44MDyIUn+FXgMeHNV/RNwILB5oM7mVgYwUlX3tu/3ASOT/VCS1cBqgJGREUZHR6fd6K1bt066/dmHb5uwHNit31yIdhSHYWMsOsahYxw6sxkHkzxJkhagJL8LbAMua0X3Aj9cVQ8meTHwsSTP39X9VVUlqR2sXwusBVi+fHmtWLFi2m0fHR1lsu1PX/OJSbe7+9Tp/+ZCtKM4DBtj0TEOHePQmc04mORJkrTAJDkd+Dng2DYEk6r6FvCt9v3GJHcBzwO28L1DOg9qZQD3J1lSVf1k+zcAACAASURBVPe2YZ0PzNEhSJLmkc/kSZK0gCRZCfw28PNV9Y2B8mcn2aN9/xG6CVa+2IZjPpbk6Dar5mnAlW2z9cCq9n3VQLkkqce8kydJ0jxJ8gFgBXBAks3AuXSzaT4F2NDehHBtm0nz/wHekuTbwHeBX6+qsUlbXk83U+fewNXtA3A+cEWSM4AvA6+eg8OSJM0zkzxJkuZJVZ0yQfFFk9T9MPDhSdbdABw2QfmDwLG700ZJ0uLjcE1JkiRJ6hGTPEmSJEnqEZM8SZIkSeoRkzxJkiRJ6hGTPEmSJEnqEZM8SZIkSeoRkzxJkiRJ6hGTPEmSJEnqEZM8SZIkSeoRkzxJkiRJ6pGdJnlJnprks0n+LcmtSf6glR+S5Lokm5J8MMlerfwpbXlTW790YF/ntPI7khw/UL6ylW1KsmbmD1OSJEmShsOu3Mn7FvDSqnoBcASwMsnRwNuAC6rqucDDwBmt/hnAw638glaPJIcCJwPPB1YCf5pkjyR7AO8DTgAOBU5pdSVJkiRJU7TTJK86W9vik9ungJcCH2rllwCvbN9Pasu09ccmSSu/vKq+VVVfAjYBR7bPpqr6YlX9F3B5qytJkiRJmqI9d6VSu9t2I/BcurtudwGPVNW2VmUzcGD7fiBwD0BVbUvyKPCsVn7twG4Ht7lnXPlRk7RjNbAaYGRkhNHR0V1p/oRG9oazD9824brd2e9is3Xr1qE63h0xFh3j0DEOHeMgSdLis0tJXlV9Bzgiyb7AR4Efn9VWTd6OtcBagOXLl9eKFSumva/3XHYlb7954sO/+9Tp73exGR0dZXfi2CfGomMcOsahYxwkSVp8pjS7ZlU9AnwKOAbYN8lYlnQQsKV93wIcDNDWPxN4cLB83DaTlUuSJEmSpmhXZtd8druDR5K9gZcDt9Mle69q1VYBV7bv69sybf0/VFW18pPb7JuHAMuAzwLXA8vabJ170U3Osn4mDk6SJEmShs2uDNdcAlzSnst7EnBFVX08yW3A5Un+EPhX4KJW/yLgL5NsAh6iS9qoqluTXAHcBmwDzmzDQElyFnANsAewrqpunbEjlCRJkqQhstMkr6puAl44QfkX6WbGHF/+n8AvTrKvtwJvnaD8KuCqXWivJEm9kmQd8HPAA1V1WCvbH/ggsBS4G3h1VT3cZqt+F3Ai8A3g9Kr6XNtmFfDmtts/rKpLWvmLgYuBven62je2ETaSpJ6a0jN5kiRpxl1M9/7YQWuAjVW1DNjYlqF7p+yy9lkNXAhPJIXn0s1OfSRwbpL92jYXAq8b2G78b0mSesYkT5KkeVRVn6Z7vGHQ4Dtnx7+L9tL2Dttr6SZBWwIcD2yoqoeq6mFgA7CyrXtGVV3b7t5dOrAvSVJP7dIrFCRJ0pwaqap72/f7gJH2/Yl30TZj75zdUfnmCcq/z0y+i3ZH71ec7B210L/31Pqeye2MRcc4dIxDZzbjYJInSdICVlWVZNafoZvJd9Hu6P2Kp6/5xKTb9e09tb5ncjtj0TEOHePQmc04OFxTkqSF5/421JL294FWPtV3zm5p38eXS5J6zCRPkqSFZ/Cds+PfRXtaOkcDj7ZhndcAxyXZr024chxwTVv3WJKj28ycpw3sS5LUUw7XlCRpHiX5ALACOCDJZrpZMs8HrkhyBvBl4NWt+lV0r0/YRPcKhdcCVNVDSc4Drm/13lJVY5O5vJ7tr1C4un0kST1mkidJ0jyqqlMmWXXsBHULOHOS/awD1k1QfgNw2O60UZK0uDhcU5IkSZJ6xCRPkiRJknrEJE+SJEmSesQkT5IkSZJ6xCRPkiRJknrEJE+SJEmSesQkT5IkSZJ6xCRPkiRJknrEJE+SJEmSesQkT5IkSZJ6xCRPkiRJknrEJE+SJEmSesQkT5IkSZJ6xCRPkiRJknrEJE+SJEmSesQkT5IkSZJ6xCRPkiRJknpkz/lugCRJ+l5Jfgz44EDRjwC/B+wLvA74ait/U1Vd1bY5BzgD+A7whqq6ppWvBN4F7AG8v6rOn5ODmIalaz4xYfnd5//sHLdEkhY3kzxJkhaYqroDOAIgyR7AFuCjwGuBC6rqTwbrJzkUOBl4PvBDwCeTPK+tfh/wcmAzcH2S9VV125wciCRpXpjkSZK0sB0L3FVVX04yWZ2TgMur6lvAl5JsAo5s6zZV1RcBklze6prkSVKPmeRJkrSwnQx8YGD5rCSnATcAZ1fVw8CBwLUDdTa3MoB7xpUfNdGPJFkNrAYYGRlhdHR02g3eunXrpNufffi2Ke9vd9oyn3YUh2FjLDrGoWMcOrMZh50meUkOBi4FRoAC1lbVu5LsT/e8wFLgbuDVVfVwusuM7wJOBL4BnF5Vn2v7WgW8ue36D6vqklb+YuBiYG/gKuCNVVUzdIySJC1KSfYCfh44pxVdCJxH1x+fB7wd+JWZ+K2qWgusBVi+fHmtWLFi2vsaHR1lsu1Pn+S5ux25+9Tpt2U+7SgOw8ZYdIxDxzh0ZjMOuzK75ja6K4WHAkcDZ7ax/2uAjVW1DNjYlgFOAJa1z2q6DomWFJ5LdwXxSODcJPu1bS6ke5B8bLuVu39okiQteicAn6uq+wGq6v6q+k5VfRf4C7YPydwCHDyw3UGtbLJySVKP7TTJq6p7x+7EVdXXgdvphoCcBFzSql0CvLJ9Pwm4tDrXAvsmWQIcD2yoqofa0JINwMq27hlVdW27e3fpwL4kSRpmpzAwVLP1mWN+AbilfV8PnJzkKUkOobtg+lngemBZkkPaXcGTW11JUo9N6Zm8JEuBFwLXASNVdW9bdR/dcE7oEsDx4/8P3En55gnKJ/r9GXteYGTvyZ8LGKYxwo6J3s5YdIxDxzh0jMP8SbIP3ayYvzZQ/MdJjqAbrnn32LqqujXJFXQTqmwDzqyq77T9nAVcQ/cKhXVVdeucHYQkaV7scpKX5GnAh4HfqKrHBmf4qqpKMuvP0M3k8wLvuexK3n7zxIe/WMf+T4djorczFh3j0DEOHeMwf6rqceBZ48pes4P6bwXeOkH5VXTPu0uShsSuPJNHkifTJXiXVdVHWvH9Y8NG2t8HWvlUnwvY0r6PL5ckSZIkTdFOk7w2W+ZFwO1V9Y6BVeuBVe37KuDKgfLT0jkaeLQN67wGOC7Jfm3CleOAa9q6x5Ic3X7rtIF9SZIkSZKmYFeGa74EeA1wc5LPt7I3AecDVyQ5A/gy8Oq27iq61ydsonuFwmsBquqhJOfRPQQO8Jaqeqh9fz3bX6FwdftIkiRJkqZop0leVX0GyCSrj52gfgFnTrKvdcC6CcpvAA7bWVskSZIkSTu2S8/kSZIkSZIWB5M8SZIkSeoRkzxJkiRJ6hGTPEmSJEnqEZM8SZIkSeoRkzxJkiRJ6hGTPEmSJEnqEZM8SZIkSeoRkzxJkiRJ6hGTPEmSJEnqEZM8SZIkSeoRkzxJkiRJ6hGTPEmSJEnqEZM8SZIkSeoRkzxJkhagJHcnuTnJ55Pc0Mr2T7IhyZ3t736tPEnenWRTkpuSvGhgP6ta/TuTrJqv45EkzR2TPEmSFq6fqaojqmp5W14DbKyqZcDGtgxwArCsfVYDF0KXFALnAkcBRwLnjiWGkqT+MsmTJGnxOAm4pH2/BHjlQPml1bkW2DfJEuB4YENVPVRVDwMbgJVz3WhJ0tzac74bIEmSJlTA3ycp4M+rai0wUlX3tvX3ASPt+4HAPQPbbm5lk5V/nySr6e4CMjIywujo6LQbvnXr1km3P/vwbVPe3+60ZT7tKA7Dxlh0jEPHOHRmMw4meZIkLUw/WVVbkvwgsCHJFwZXVlW1BHBGtCRyLcDy5ctrxYoV097X6Ogok21/+ppPTHl/d586/bbMpx3FYdgYi45x6BiHzmzGweGakiQtQFW1pf19APgo3TN197dhmLS/D7TqW4CDBzY/qJVNVi5J6jGTPEmSFpgk+yR5+th34DjgFmA9MDZD5irgyvZ9PXBam2XzaODRNqzzGuC4JPu1CVeOa2WSpB5zuKYkSQvPCPDRJND11X9dVX+X5HrgiiRnAF8GXt3qXwWcCGwCvgG8FqCqHkpyHnB9q/eWqnpo7g5DkjQfTPIkSVpgquqLwAsmKH8QOHaC8gLOnGRf64B1M91GSdLC5XBNSZIkSeoRkzxJkiRJ6hGTPEmSJEnqEZM8SZIkSeoRkzxJkiRJ6hGTPEmSJEnqkZ0meUnWJXkgyS0DZfsn2ZDkzvZ3v1aeJO9OsinJTUleNLDNqlb/ziSrBspfnOTmts27014KJEmSJEmaul25k3cxsHJc2RpgY1UtAza2ZYATgGXtsxq4ELqkEDgXOAo4Ejh3LDFsdV43sN3435IkSZIk7aKdJnlV9WngoXHFJwGXtO+XAK8cKL+0OtcC+yZZAhwPbKiqh6rqYWADsLKte0ZVXdte5HrpwL4kSZIkSVO05zS3G6mqe9v3+4CR9v1A4J6Beptb2Y7KN09QPqEkq+nuEDIyMsLo6Og0mw8je8PZh2+bcN3u7Hex2bp161Ad744Yi45x6BiHjnGQJGnxmW6S94SqqiQ1E43Zhd9aC6wFWL58ea1YsWLa+3rPZVfy9psnPvy7T53+fheb0dFRdieOfWIsOsahYxw6xkGSpMVnurNr3t+GWtL+PtDKtwAHD9Q7qJXtqPygCcolSZIkSdMw3SRvPTA2Q+Yq4MqB8tPaLJtHA4+2YZ3XAMcl2a9NuHIccE1b91iSo9usmqcN7EuSJEmSNEU7Ha6Z5APACuCAJJvpZsk8H7giyRnAl4FXt+pXAScCm4BvAK8FqKqHkpwHXN/qvaWqxiZzeT3dDJ57A1e3jyRJkiRpGnaa5FXVKZOsOnaCugWcOcl+1gHrJii/AThsZ+2QJEmSJO3cdIdrSpIkSZIWIJM8SZIkSeoRkzxJkiRJ6hGTPEmSFpgkByf5VJLbktya5I2t/PeTbEny+fY5cWCbc5JsSnJHkuMHyle2sk1J1szH8UiS5tZuvwxdkiTNuG3A2VX1uSRPB25MsqGtu6Cq/mSwcpJDgZOB5wM/BHwyyfPa6vcBLwc2A9cnWV9Vt83JUUiS5oVJniRJC0x7j+y97fvXk9wOHLiDTU4CLq+qbwFfSrIJOLKt21RVXwRIcnmra5InST1mkidJ0gKWZCnwQuA64CXAWUlOA26gu9v3MF0CeO3AZpvZnhTeM678qEl+ZzWwGmBkZITR0dFpt3nr1q2Tbn/24dumvL/dact82lEcho2x6BiHjnHozGYcTPIkSVqgkjwN+DDwG1X1WJILgfOAan/fDvzKTPxWVa0F1gIsX768VqxYMe19jY6OMtn2p6/5xJT3d/ep02/LfNpRHIaNsegYh45x6MxmHEzyJElagJI8mS7Bu6yqPgJQVfcPrP8L4ONtcQtw8MDmB7UydlAuSeopZ9eUJGmBSRLgIuD2qnrHQPmSgWq/ANzSvq8HTk7ylCSHAMuAzwLXA8uSHJJkL7rJWdbPxTFIkuaPd/IkSVp4XgK8Brg5yedb2ZuAU5IcQTdc827g1wCq6tYkV9BNqLINOLOqvgOQ5CzgGmAPYF1V3TqXBzIMlk4yBPXsw7dNOjz17vN/djabJGnImeRJkrTAVNVngEyw6qodbPNW4K0TlF+1o+0kSf3jcE1JkiRJ6hHv5EmSpN6ZbAglOFRSUv+Z5EmSpEVrR8mcJA0rkzxJkrSg9TGR806jpNnkM3mSJEmS1CPeyZMkSdqJPt5NlNRf3smTJEmSpB7xTp4kSZpRN295dNKXgEuSZp9JniRJGipOeiKp70zyJEmSFpDJklATUEm7yiRPkiSpcYIVSX3gxCuSJEmS1CMmeZIkSZLUIyZ5kiRJktQjPpM3AR94liRJC42zgkraVd7JkyRJkqQe8U6eJEnSIuddPkmDFsydvCQrk9yRZFOSNfPdHkmS+sI+VpKGy4K4k5dkD+B9wMuBzcD1SdZX1W3z2zJJkhY3+1g514A0fBZEkgccCWyqqi8CJLkcOAlYUB2QQyEkSYvQouhjNff8/xqpvxZKkncgcM/A8mbgqHlqy7Ts6D+UC9nZh2/j9EXa9pk2k7HYUec4l+fKQu6kpxOHuYzrxSv3mdH9TcdMx2g6v7MQ4qDdtuj7WM29mf5vqv+/0TEOnYUeh8n60sX0/xqpqlnb+S43InkVsLKqfrUtvwY4qqrOGldvNbC6Lf4YcMdu/OwBwNd2Y/u+MA7bGYuOcegYh85MxOE5VfXsmWiMps4+dl4Zh+2MRcc4dIxDZ9b62IVyJ28LcPDA8kGt7HtU1Vpg7Uz8YJIbqmr5TOxrMTMO2xmLjnHoGIeOcegF+9h5Yhy2MxYd49AxDp3ZjMNCmV3zemBZkkOS7AWcDKyf5zZJktQH9rGSNGQWxJ28qtqW5CzgGmAPYF1V3TrPzZIkadGzj5Wk4bMgkjyAqroKuGoOf3JGhqT0gHHYzlh0jEPHOHSMQw/Yx84b47CdsegYh45x6MxaHBbExCuSJEmSpJmxUJ7JkyRJkiTNgKFM8pKsTHJHkk1J1sx3e2ZTkoOTfCrJbUluTfLGVr5/kg1J7mx/92vlSfLuFpubkrxofo9gZiXZI8m/Jvl4Wz4kyXXteD/YJiUgyVPa8qa2ful8tnsmJdk3yYeSfCHJ7UmOGcbzIclvtn8nbknygSRPHZbzIcm6JA8kuWWgbMrnQJJVrf6dSVbNx7Fo4bGPtY+1j7WPtY+d/z526JK8JHsA7wNOAA4FTkly6Py2alZtA86uqkOBo4Ez2/GuATZW1TJgY1uGLi7L2mc1cOHcN3lWvRG4fWD5bcAFVfVc4GHgjFZ+BvBwK7+g1euLdwF/V1U/DryALh5DdT4kORB4A7C8qg6jm4ziZIbnfLgYWDmubErnQJL9gXPpXqp9JHDuWKel4WUfax+Lfax9rH3sxSyEPraqhuoDHANcM7B8DnDOfLdrDo//SuDldC+5XdLKlgB3tO9/DpwyUP+Jeov9Q/duqI3AS4GPA6F7AeWe488Nulnojmnf92z1Mt/HMAMxeCbwpfHHMmznA3AgcA+wf/vn+3Hg+GE6H4ClwC3TPQeAU4A/Hyj/nnp+hvNjH2sfax9rH2sfuzD62KG7k8f2E2/M5lbWe+329wuB64CRqrq3rboPGGnf+xyfdwK/DXy3LT8LeKSqtrXlwWN9Ig5t/aOt/mJ3CPBV4P+0ITXvT7IPQ3Y+VNUW4E+A/wDupfvneyPDdz4Mmuo50MtzQ7ttaM8L+1j7WOxjAfvYScx5HzuMSd5QSvI04MPAb1TVY4PrqrtE0OtpVpP8HPBAVd04322ZZ3sCLwIurKoXAo+zfcgAMDTnw37ASXQd8g8B+/D9QyuG1jCcA9JMso+1j23sY7GP3Zm5OgeGMcnbAhw8sHxQK+utJE+m63wuq6qPtOL7kyxp65cAD7TyvsbnJcDPJ7kbuJxuOMm7gH2TjL0vcvBYn4hDW/9M4MG5bPAs2Qxsrqrr2vKH6DqkYTsfXgZ8qaq+WlXfBj5Cd44M2/kwaKrnQF/PDe2eoTsv7GMB+9gx9rEd+9jvN+d97DAmedcDy9oMP3vRPQi6fp7bNGuSBLgIuL2q3jGwaj0wNlPPKrrnCMbKT2uz/RwNPDpwe3nRqqpzquqgqlpK98/8H6rqVOBTwKtatfFxGIvPq1r9RX/lraruA+5J8mOt6FjgNobsfKAbQnJ0kh9o/46MxWGozodxpnoOXAMcl2S/dtX2uFam4WYf2xmq/6bax3bsY59gH/v95r6Pne8HE+fjA5wI/DtwF/C7892eWT7Wn6S7JXwT8Pn2OZFurPNG4E7gk8D+rX7oZka7C7iZbmakeT+OGY7J/9/e/Qf7Vdd3Hn++mgAiqIDYOzTJGlyydVBWpBnA1e5koULAtsFdqri0pEgbZ4Sptuxso7NbqsiO7CzaBSm7qaQES0WKP5KxWDal3Fpnlp9iDQEZbjFskkVQwq+oq0bf+8f5RL7Em+T+Cjf33Odj5jv3e97ncz7fz/l4YvLinO/nLgG+2N6/BrgLGAH+Cjio1V/Stkfa/tdM97in8PyPB+5p18QXgMNn4/UAfAj4BnA/8CngoNlyPQCfpvuexI/o/svzBRO5BoB3tzkZAc6f7vPytX+8/DvWv2P9O9a/Y/07dvr/jk3rRJIkSZLUA7PxcU1JkiRJ6i1DniRJkiT1iCFPkiRJknrEkCdJkiRJPWLIkyRJkqQeMeRJkiRJUo8Y8iRJkiSpRwx5kiRJktQjhjxJkiRJ6hFDniRJkiT1iCFPkiRJknrEkCdJkiRJPWLIkyRJkqQeMeRJkiRJUo8Y8iRJkiSpRwx50hgk2ZTk+0m2J3k8yXVJDm37Tk/y5STPJfl2kr9P8utt3wfbMTtf30/ykyRH7uGzjkpybZLHWp/fSPKhJIe0/ZXku62/J5PcluSdu/TxX5NsTvJskkeTfHBfzo8kSZL2H4Y8aex+raoOBU4AFgP/KcnZwF8B1wPzgSHgj4BfA6iq/1JVh+58AZcDw1X1ndE+IMkRwP8GDgbeVFUvA94KHAb884Gmb2j9/SJwHfCJJJcM7L8WeG1VvRz4V8C5Sf7tVEyCJEmS9m9zp3sA0kxTVVuTfAk4Dvj3wKVV9cmBJn/fXi+QJMB5wIf20P0fAM8Bv1lVP2mftxl4327G8h3gU0m+D/xFkk9U1ZNV9dAuTX8CHDOmE5QkSdKM5p08aZySLADOBL4HLABuHuOhvwz8PPDZPbT5FeBzOwPeOKyl+482Jw6Mc2WS7cAW4BDgL8fZpyRJkmYgQ540dl9I8jTwFbo7dX/S6o+N8fjlwM1VtX0PbV45jv5+qqp+BHwHOGKg9lHgZXSPl34KeGa8/UqSJGnmMeRJY3dWVR1WVa+uqvcCT7b6UXs7MMlLgd8A1gzUfnlgQZaNrfzkWPobpf8DgFcB2wbr1bkP+D57fkxUkiRJPWHIkybuIWAz8O/G0PbtdAFseGehqv5hYFGW17Xy3wJvTzLeP5vLgB3AXbvZP5cXLtwiSZKknjLkSRNUVUW3UMp/TnJ+kpcn+bkkb0myapfmy4Hr2zF78jHg5cCaJK8GSDIvyceS/MtdGyc5Ism5wNXA5VX1ZBvDe5Icns6JwIXAbZM8ZUmSJM0AhjxpEqrqZuCdwLuB/ws8DnyEbiEUoAtpwCl0v2Zhb/1to/uVBz8C7kzyHF04ewYYGWj6j21RlRHgd4Dfr6o/Gtj/duCf6Fbq/AvgqvaSJElSz2XvNxYkSZIkSTOFd/IkSZIkqUcMeZIkSZLUI4Y8SZIkSeoRQ54kSZIk9cjc6R7ARB155JG1cOHCCR//3e9+l0MOOWTqBjRDOQ/Pcy46zkPHeehMxTzce++936mqV03RkCRJ0l7M2JC3cOFC7rnnngkfPzw8zJIlS6ZuQDOU8/A856LjPHSch85UzEOSR6dmNJIkaSx8XFOSJEmSesSQJ0mSJEk9YsiTJEmSpB4x5EmSJElSj+w15CV5SZK7kvxjko1JPtTqRye5M8lIks8kObDVD2rbI23/woG+PtDqDyU5faC+tNVGkqyc+tOUJEmSpNlhLKtr/gA4paq2JzkA+EqSLwF/AHy8qm5M8j+AC4Br2s+nquqYJOcAlwPvTHIscA7wOuAXgL9N8i/aZ1wNvBXYAtydZF1VPTCF5/kzNmx9ht9e+dej7tv00bfty4+WJEmSpH1mr3fyqrO9bR7QXgWcAtzc6muAs9r7ZW2btv/UJGn1G6vqB1X1TWAEOLG9Rqrqkar6IXBjaytJkiRJGqcx/Z68JHOAe4Fj6O66/RPwdFXtaE22APPa+3nAZoCq2pHkGeCVrX7HQLeDx2zepX7SbsaxAlgBMDQ0xPDw8FiGP6qhg+Hi43aMum8y/c4027dvn1XnuyfORcd56DgPHedBkqSZZ0whr6p+DByf5DDg88Br9+modj+OVcAqgMWLF9dkfkHvVTes5YoNo5/+pnMn3u9M4y98fp5z0XEeOs5Dx3mQJGnmGdfqmlX1NHA78CbgsCQ7U9J8YGt7vxVYAND2vwJ4crC+yzG7q0uSJEmSxmksq2u+qt3BI8nBdAukPEgX9s5uzZYDa9v7dW2btv/vqqpa/Zy2+ubRwCLgLuBuYFFbrfNAusVZ1k3FyUmSJEnSbDOWxzWPAta07+X9HHBTVX0xyQPAjUk+AtwHXNvaXwt8KskIsI0utFFVG5PcBDwA7AAubI+BkuQi4FZgDrC6qjZO2RlKkiRJ0iyy15BXVV8H3jhK/RG6lTF3rf8/4Dd209dlwGWj1G8BbhnDeCVJkiRJezCu7+RJkiRJkvZvhjxJkiRJ6hFDniRJkiT1iCFPkiRJknrEkCdJkiRJPWLIkyRJkqQeMeRJkiRJUo8Y8iRJkiSpRwx5kiRJktQjhjxJkiRJ6hFDniRJkiT1iCFPkiRJknrEkCdJkiRJPWLIkyRJkqQeMeRJkiRJUo/sNeQlWZDk9iQPJNmY5H2t/sdJtib5WnudOXDMB5KMJHkoyekD9aWtNpJk5UD96CR3tvpnkhw41ScqSZIkSbPBWO7k7QAurqpjgZOBC5Mc2/Z9vKqOb69bANq+c4DXAUuBP00yJ8kc4GrgDOBY4F0D/Vze+joGeAq4YIrOT5IkSZJmlb2GvKp6rKq+2t4/BzwIzNvDIcuAG6vqB1X1TWAEOLG9Rqrqkar6IXAjsCxJgFOAm9vxa4CzJnpCkiRJkjSbzR1P4yQLgTcCdwJvBi5Kch5wD93dvqfoAuAdA4dt4flQuHmX+knAK4Gnq2rHKO13/fwVwAqAoaEhhoeHxzP8Fxg6GC4+bseo+ybT70yzffv2WXW+e+JcdJyHjvPQcR4kSZp5xhzykhwKfBZ4f1U9m+Qa4FKg2s8rgHfvk1E2VbUKWAWwePHiWrJkyYT7uuqGtVyxYfTT33TuxPudaYaHh5nMPPaJc9FxHjrOQ8d5kCRp5hlTyEtyAF3Au6GqPgdQVY8P7P8zeU5uHgAAEP5JREFU4IttcyuwYODw+a3GbupPAoclmdvu5g22lyRJkiSNw1hW1wxwLfBgVX1soH7UQLO3A/e39+uAc5IclORoYBFwF3A3sKitpHkg3eIs66qqgNuBs9vxy4G1kzstSZIkSZqdxnIn783AbwEbknyt1T5Itzrm8XSPa24C3gNQVRuT3AQ8QLcy54VV9WOAJBcBtwJzgNVVtbH194fAjUk+AtxHFyolSZIkSeO015BXVV8BMsquW/ZwzGXAZaPUbxntuKp6hG71TUmSJEnSJIzl9+RJkiRJkmYIQ54kSZIk9YghT5IkSZJ6xJAnSZIkST1iyJMkSZKkHjHkSZIkSVKPGPIkSZIkqUcMeZIkSZLUI4Y8SZIkSeoRQ54kSZIk9YghT5IkSZJ6xJAnSZIkST1iyJMkSZKkHjHkSZIkSVKP7DXkJVmQ5PYkDyTZmOR9rX5EkvVJHm4/D2/1JLkyyUiSryc5YaCv5a39w0mWD9R/KcmGdsyVSbIvTlaSJEmS+m4sd/J2ABdX1bHAycCFSY4FVgK3VdUi4La2DXAGsKi9VgDXQBcKgUuAk4ATgUt2BsPW5ncHjls6+VOTJEmSpNlnryGvqh6rqq+2988BDwLzgGXAmtZsDXBWe78MuL46dwCHJTkKOB1YX1XbquopYD2wtO17eVXdUVUFXD/QlyRJkiRpHOaOp3GShcAbgTuBoap6rO36FjDU3s8DNg8ctqXV9lTfMkp9tM9fQXd3kKGhIYaHh8cz/BcYOhguPm7HqPsm0+9Ms3379ll1vnviXHSch47z0HEeJEmaecYc8pIcCnwWeH9VPTv4tbmqqiS1D8b3AlW1ClgFsHjx4lqyZMmE+7rqhrVcsWH009907sT7nWmGh4eZzDz2iXPRcR46zkPHeZAkaeYZ0+qaSQ6gC3g3VNXnWvnx9qgl7ecTrb4VWDBw+PxW21N9/ih1SZIkSdI4jWV1zQDXAg9W1ccGdq0Ddq6QuRxYO1A/r62yeTLwTHus81bgtCSHtwVXTgNubfueTXJy+6zzBvqSJEmSJI3DWB7XfDPwW8CGJF9rtQ8CHwVuSnIB8CjwjrbvFuBMYAT4HnA+QFVtS3IpcHdr9+Gq2tbevxe4DjgY+FJ7SZIkSZLGaa8hr6q+Auzu99adOkr7Ai7cTV+rgdWj1O8BXr+3sUiSJEmS9mxM38mTJEmSJM0MhjxJkiRJ6hFDniRJkiT1iCFPkiRJknrEkCdJkiRJPWLIkyRJkqQeMeRJkiRJUo8Y8iRJkiSpRwx5kiRJktQjhjxJkiRJ6hFDniRJkiT1iCFPkiRJknrEkCdJkiRJPWLIkyRJkqQeMeRJkiRJUo/sNeQlWZ3kiST3D9T+OMnWJF9rrzMH9n0gyUiSh5KcPlBf2mojSVYO1I9OcmerfybJgVN5gpIkSZI0m4zlTt51wNJR6h+vquPb6xaAJMcC5wCva8f8aZI5SeYAVwNnAMcC72ptAS5vfR0DPAVcMJkTkiRJkqTZbK8hr6q+DGwbY3/LgBur6gdV9U1gBDixvUaq6pGq+iFwI7AsSYBTgJvb8WuAs8Z5DpIkSZKkZu4kjr0oyXnAPcDFVfUUMA+4Y6DNllYD2LxL/STglcDTVbVjlPY/I8kKYAXA0NAQw8PDEx780MFw8XE7Rt03mX5nmu3bt8+q890T56LjPHSch47zIEnSzDPRkHcNcClQ7ecVwLunalC7U1WrgFUAixcvriVLlky4r6tuWMsVG0Y//U3nTrzfmWZ4eJjJzGOfOBcd56HjPHScB0mSZp4Jhbyqenzn+yR/BnyxbW4FFgw0nd9q7Kb+JHBYkrntbt5ge0mSJEnSOE3oVygkOWpg8+3AzpU31wHnJDkoydHAIuAu4G5gUVtJ80C6xVnWVVUBtwNnt+OXA2snMiZJkiRJ0hju5CX5NLAEODLJFuASYEmS4+ke19wEvAegqjYmuQl4ANgBXFhVP279XATcCswBVlfVxvYRfwjcmOQjwH3AtVN2dpIkSZI0y+w15FXVu0Yp7zaIVdVlwGWj1G8Bbhml/gjd6puSJEmSpEma0OOakiRJkqT9kyFPkiRJknrEkCdJkiRJPWLIkyRJkqQeMeRJkiRJUo8Y8iRJkiSpRwx5kiRJktQjhjxJkiRJ6hFDniRJkiT1iCFPkiRJknrEkCdJkiRJPWLIkyRJkqQeMeRJkiRJUo8Y8iRJkiSpRwx5kiRJktQjew15SVYneSLJ/QO1I5KsT/Jw+3l4qyfJlUlGknw9yQkDxyxv7R9Osnyg/ktJNrRjrkySqT5JSZIkSZotxnIn7zpg6S61lcBtVbUIuK1tA5wBLGqvFcA10IVC4BLgJOBE4JKdwbC1+d2B43b9LEmSJEnSGO015FXVl4Ftu5SXAWva+zXAWQP166tzB3BYkqOA04H1VbWtqp4C1gNL276XV9UdVVXA9QN9SZIkSZLGae4Ejxuqqsfa+28BQ+39PGDzQLstrban+pZR6qNKsoLuDiFDQ0MMDw9PcPgwdDBcfNyOUfdNpt+ZZvv27bPqfPfEueg4Dx3noeM8SJI080w05P1UVVWSmorBjOGzVgGrABYvXlxLliyZcF9X3bCWKzaMfvqbzp14vzPN8PAwk5nHPnEuOs5Dx3noOA+SJM08E11d8/H2qCXt5xOtvhVYMNBufqvtqT5/lLokSZIkaQImGvLWATtXyFwOrB2on9dW2TwZeKY91nkrcFqSw9uCK6cBt7Z9zyY5ua2qed5AX5IkSZKkcdrr45pJPg0sAY5MsoVulcyPAjcluQB4FHhHa34LcCYwAnwPOB+gqrYluRS4u7X7cFXtXMzlvXQreB4MfKm9JEmSJEkTsNeQV1Xv2s2uU0dpW8CFu+lnNbB6lPo9wOv3Ng5JkiRJ0t5N9HFNSZIkSdJ+yJAnSZIkST1iyJMkSZKkHjHkSZIkSVKPGPIkSZIkqUcMeZIkSZLUI4Y8SZIkSeoRQ54kSZIk9YghT5IkSZJ6xJAnSZIkST1iyJMkSZKkHjHkSZIkSVKPGPIkSZIkqUcMeZIkSZLUI5MKeUk2JdmQ5GtJ7mm1I5KsT/Jw+3l4qyfJlUlGknw9yQkD/Sxv7R9OsnxypyRJkiRJs9dU3Mn7N1V1fFUtbtsrgduqahFwW9sGOANY1F4rgGugC4XAJcBJwInAJTuDoSRJkiRpfPbF45rLgDXt/RrgrIH69dW5AzgsyVHA6cD6qtpWVU8B64Gl+2BckiRJktR7cyd5fAH/K0kB/7OqVgFDVfVY2/8tYKi9nwdsHjh2S6vtrv4zkqyguwvI0NAQw8PDEx740MFw8XE7Rt03mX5nmu3bt8+q890T56LjPHSch47zIEnSzDPZkPeWqtqa5OeB9Um+MbizqqoFwCnRQuQqgMWLF9eSJUsm3NdVN6zlig2jn/6mcyfe70wzPDzMZOaxT5yLjvPQcR46zoMkSTPPpB7XrKqt7ecTwOfpvlP3eHsMk/bzidZ8K7Bg4PD5rba7uiRJkiRpnCYc8pIckuRlO98DpwH3A+uAnStkLgfWtvfrgPPaKpsnA8+0xzpvBU5LcnhbcOW0VpMkSZIkjdNkHtccAj6fZGc/f1lVf5PkbuCmJBcAjwLvaO1vAc4ERoDvAecDVNW2JJcCd7d2H66qbZMYlyRJkiTNWhMOeVX1CPCGUepPAqeOUi/gwt30tRpYPdGxSJIkSZI6++JXKEiSJEmSpokhT5IkSZJ6xJAnSZIkST1iyJMkSZKkHjHkSZIkSVKPGPIkSZIkqUcMeZIkSZLUI4Y8SZIkSeoRQ54kSZIk9cjc6R7A/mjhyr8etb7po297kUciSZIkSeNjyHsR7C407omBUpIkSdJE+LimJEmSJPWId/L2U3u6++ddPkmSJEm7Y8ibIhN5JFOSJEmSppohbwZyYRhJkiRJu7PffCcvydIkDyUZSbJyuscjSZIkSTPRfnEnL8kc4GrgrcAW4O4k66rqgekd2Qvt749k+j0+SZIkSftFyANOBEaq6hGAJDcCy4D9KuTNZLsLgBcft4Pf9lc8SJIkSb2xv4S8ecDmge0twEm7NkqyAljRNrcneWgSn3kk8J1JHN8LvzfBecjl+2Aw089rouM8dJyHzlTMw6unYiCSJGls9peQNyZVtQpYNRV9JbmnqhZPRV8zmfPwPOei4zx0nIeO8yBJ0syzvyy8shVYMLA9v9UkSZIkSeOwv4S8u4FFSY5OciBwDrBumsckSZIkSTPOfvG4ZlXtSHIRcCswB1hdVRv38cdOyWOfPeA8PM+56DgPHeeh4zxIkjTDpKqmewySJEmSpCmyvzyuKUmSJEmaAoY8SZIkSeqRWRnykixN8lCSkSQrp3s8+1KSBUluT/JAko1J3tfqRyRZn+Th9vPwVk+SK9vcfD3JCdN7BlMryZwk9yX5Yts+Osmd7Xw/0xb+IclBbXuk7V84neOeSkkOS3Jzkm8keTDJm2bj9ZDk99ufifuTfDrJS2bL9ZBkdZInktw/UBv3NZBkeWv/cJLl03EukiTpZ826kJdkDnA1cAZwLPCuJMdO76j2qR3AxVV1LHAycGE735XAbVW1CLitbUM3L4vaawVwzYs/5H3qfcCDA9uXAx+vqmOAp4ALWv0C4KlW/3hr1xf/Hfibqnot8Aa6+ZhV10OSecDvAYur6vV0Cz6dw+y5Hq4Dlu5SG9c1kOQI4BLgJOBE4JKdwVCSJE2vWRfy6P4xMlJVj1TVD4EbgWXTPKZ9pqoeq6qvtvfP0f2Dfh7dOa9pzdYAZ7X3y4Drq3MHcFiSo17kYe8TSeYDbwM+2bYDnALc3JrsOg875+dm4NTWfkZL8grgXwPXAlTVD6vqaWbh9UC3uvDBSeYCLwUeY5ZcD1X1ZWDbLuXxXgOnA+uraltVPQWs52eDoyRJmgazMeTNAzYPbG9ptd5rj5i9EbgTGKqqx9qubwFD7X2f5+dPgP8I/KRtvxJ4uqp2tO3Bc/3pPLT9z7T2M93RwLeBP2+PrX4yySHMsuuhqrYC/w34P3Th7hngXmbf9TBovNdAL68NSZL6YDaGvFkpyaHAZ4H3V9Wzg/uq+z0avf5dGkl+FXiiqu6d7rFMs7nACcA1VfVG4Ls8/1geMGuuh8Pp7lAdDfwCcAjehfqp2XANSJLUZ7Mx5G0FFgxsz2+13kpyAF3Au6GqPtfKj+987K79fKLV+zo/bwZ+Pckmukd0T6H7btph7XE9eOG5/nQe2v5XAE++mAPeR7YAW6rqzrZ9M13om23Xw68A36yqb1fVj4DP0V0js+16GDTea6Cv14YkSTPebAx5dwOL2ip6B9IttrBumse0z7TvDV0LPFhVHxvYtQ7YuRrecmDtQP28tqLeycAzA49wzVhV9YGqml9VC+n+N/+7qjoXuB04uzXbdR52zs/Zrf2Mv7NRVd8CNif5xVY6FXiAWXY90D2meXKSl7Y/IzvnYVZdD7sY7zVwK3BaksPbndHTWk2SJE2z9O/fKXuX5Ey672fNAVZX1WXTPKR9JslbgH8ANvD8d9E+SPe9vJuAfwY8Cryjqra1f/B+gu7Rte8B51fVPS/6wPehJEuA/1BVv5rkNXR39o4A7gN+s6p+kOQlwKfovsO4DTinqh6ZrjFPpSTH0y0+cyDwCHA+3X/wmVXXQ5IPAe+kW4H2PuB36L5T1vvrIcmngSXAkcDjdKtkfoFxXgNJ3k33/ycAl1XVn7+Y5yFJkkY3K0OeJEmSJPXVbHxcU5IkSZJ6y5AnSZIkST1iyJMkSZKkHjHkSZIkSVKPGPIkSZIkqUcMeZIkSZLUI4Y8SZIkSeqR/w8uAl/gnnmXBwAAAABJRU5ErkJggg==\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dataframe.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "tmkhPnXImMAt",
        "outputId": "48776cd2-51a7-4c68-d59c-1ee1fd082a40"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "           FITC-CD3        PE-CD8      ECD-CD19      PC5-CD45       PC7-CD3\n",
              "count  40000.000000  40000.000000  40000.000000  40000.000000  40000.000000\n",
              "mean       8.245865      7.956326      6.102041     97.956974     30.004937\n",
              "std       40.784917     27.655936     23.554925     94.014033     53.123582\n",
              "min        0.000000      0.000000      0.000000      0.000000      0.000000\n",
              "25%        1.321794      2.037050      1.556398     34.118685      5.251889\n",
              "50%        2.033236      3.025535      2.521517     49.346971      8.089073\n",
              "75%        3.604177      8.543738      5.148893    161.842501     18.673915\n",
              "max      999.970436    999.970436    999.970436    999.970436    999.970436"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-a42df6b8-05c1-42fd-91de-ef69bfb37953\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>FITC-CD3</th>\n",
              "      <th>PE-CD8</th>\n",
              "      <th>ECD-CD19</th>\n",
              "      <th>PC5-CD45</th>\n",
              "      <th>PC7-CD3</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>40000.000000</td>\n",
              "      <td>40000.000000</td>\n",
              "      <td>40000.000000</td>\n",
              "      <td>40000.000000</td>\n",
              "      <td>40000.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>8.245865</td>\n",
              "      <td>7.956326</td>\n",
              "      <td>6.102041</td>\n",
              "      <td>97.956974</td>\n",
              "      <td>30.004937</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>40.784917</td>\n",
              "      <td>27.655936</td>\n",
              "      <td>23.554925</td>\n",
              "      <td>94.014033</td>\n",
              "      <td>53.123582</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>1.321794</td>\n",
              "      <td>2.037050</td>\n",
              "      <td>1.556398</td>\n",
              "      <td>34.118685</td>\n",
              "      <td>5.251889</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>2.033236</td>\n",
              "      <td>3.025535</td>\n",
              "      <td>2.521517</td>\n",
              "      <td>49.346971</td>\n",
              "      <td>8.089073</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>3.604177</td>\n",
              "      <td>8.543738</td>\n",
              "      <td>5.148893</td>\n",
              "      <td>161.842501</td>\n",
              "      <td>18.673915</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>999.970436</td>\n",
              "      <td>999.970436</td>\n",
              "      <td>999.970436</td>\n",
              "      <td>999.970436</td>\n",
              "      <td>999.970436</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a42df6b8-05c1-42fd-91de-ef69bfb37953')\"\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-a42df6b8-05c1-42fd-91de-ef69bfb37953 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-a42df6b8-05c1-42fd-91de-ef69bfb37953');\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": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#remove outliers\n",
        "dataframe = dataframe[dataframe[\"FITC-CD3\"] < 20]\n",
        "\n",
        "dataframe = dataframe[dataframe[\"PE-CD8\"] < 50]\n",
        "\n",
        "dataframe = dataframe[dataframe[\"ECD-CD19\"] < 50]\n",
        "\n",
        "dataframe = dataframe[dataframe[\"PC5-CD45\"] < 400]\n",
        "\n",
        "dataframe = dataframe[dataframe[\"PC7-CD3\"] < 200]\n",
        "\n",
        "dataframe"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "O2nypFq1mZIj",
        "outputId": "29b10eeb-3bf6-48a1-b4bf-47b7cdbcd888"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        FITC-CD3     PE-CD8   ECD-CD19    PC5-CD45     PC7-CD3\n",
              "0       4.315380   5.301481   3.892902  116.485707   11.284839\n",
              "1       2.034189   3.378871   3.017428   63.537658    7.094390\n",
              "2      19.018191  11.923801   5.848890  194.091982   98.327730\n",
              "3      18.117922  14.278425   6.015783  227.966526  145.721575\n",
              "4       6.203657   5.125051   2.734187   95.794769   12.134564\n",
              "...          ...        ...        ...         ...         ...\n",
              "39995   2.020838   2.534869   1.887323   59.295711    9.926805\n",
              "39996   3.795627   6.340987   3.256801  145.446916   14.008535\n",
              "39997   1.364709   2.271654   2.296450   27.221706    2.868655\n",
              "39998   2.260210  17.645853  27.465847  264.618172   25.784517\n",
              "39999   2.911570  21.318456  10.092745  195.862003   70.831366\n",
              "\n",
              "[36597 rows x 5 columns]"
            ],
            "text/html": [
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              "  <div id=\"df-7c2baaaf-ca82-47aa-bf30-33564c992a7f\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>FITC-CD3</th>\n",
              "      <th>PE-CD8</th>\n",
              "      <th>ECD-CD19</th>\n",
              "      <th>PC5-CD45</th>\n",
              "      <th>PC7-CD3</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>4.315380</td>\n",
              "      <td>5.301481</td>\n",
              "      <td>3.892902</td>\n",
              "      <td>116.485707</td>\n",
              "      <td>11.284839</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2.034189</td>\n",
              "      <td>3.378871</td>\n",
              "      <td>3.017428</td>\n",
              "      <td>63.537658</td>\n",
              "      <td>7.094390</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>19.018191</td>\n",
              "      <td>11.923801</td>\n",
              "      <td>5.848890</td>\n",
              "      <td>194.091982</td>\n",
              "      <td>98.327730</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>18.117922</td>\n",
              "      <td>14.278425</td>\n",
              "      <td>6.015783</td>\n",
              "      <td>227.966526</td>\n",
              "      <td>145.721575</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>6.203657</td>\n",
              "      <td>5.125051</td>\n",
              "      <td>2.734187</td>\n",
              "      <td>95.794769</td>\n",
              "      <td>12.134564</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39995</th>\n",
              "      <td>2.020838</td>\n",
              "      <td>2.534869</td>\n",
              "      <td>1.887323</td>\n",
              "      <td>59.295711</td>\n",
              "      <td>9.926805</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39996</th>\n",
              "      <td>3.795627</td>\n",
              "      <td>6.340987</td>\n",
              "      <td>3.256801</td>\n",
              "      <td>145.446916</td>\n",
              "      <td>14.008535</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39997</th>\n",
              "      <td>1.364709</td>\n",
              "      <td>2.271654</td>\n",
              "      <td>2.296450</td>\n",
              "      <td>27.221706</td>\n",
              "      <td>2.868655</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39998</th>\n",
              "      <td>2.260210</td>\n",
              "      <td>17.645853</td>\n",
              "      <td>27.465847</td>\n",
              "      <td>264.618172</td>\n",
              "      <td>25.784517</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39999</th>\n",
              "      <td>2.911570</td>\n",
              "      <td>21.318456</td>\n",
              "      <td>10.092745</td>\n",
              "      <td>195.862003</td>\n",
              "      <td>70.831366</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>36597 rows × 5 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7c2baaaf-ca82-47aa-bf30-33564c992a7f')\"\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",
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              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\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-7c2baaaf-ca82-47aa-bf30-33564c992a7f 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-7c2baaaf-ca82-47aa-bf30-33564c992a7f');\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": "markdown",
      "source": [
        "Process data for machine learning"
      ],
      "metadata": {
        "id": "u_TTWIfgn49W"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#standardize data\n",
        "scaler = StandardScaler()\n",
        "\n",
        "dataframe_standardized = scaler.fit_transform(dataframe)\n",
        "\n",
        "dataframe_standardized"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iLPmuyycn7ys",
        "outputId": "ee7592d4-e1d7-4425-956a-a6bf037daf63"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ 0.24223226,  0.02134713, -0.04862649,  0.43899562, -0.26972265],\n",
              "       [-0.29129674, -0.33236866, -0.18684457, -0.27777208, -0.3907205 ],\n",
              "       [ 3.68095151,  1.23970151,  0.260181  ,  1.48956637,  2.2436127 ],\n",
              "       ...,\n",
              "       [-0.4478759 , -0.53607106, -0.30067122, -0.76938797, -0.51273723],\n",
              "       [-0.23843454,  2.29242707,  3.67302323,  2.44429268,  0.14895087],\n",
              "       [-0.08609328,  2.96810143,  0.93019238,  1.51352748,  1.44966408]])"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#normalize data\n",
        "normalization = MinMaxScaler()\n",
        "\n",
        "dataframe_normalized = normalization.fit_transform(dataframe)\n",
        "\n",
        "dataframe_normalized"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xnl_uYJel1fK",
        "outputId": "953a1cb3-ab58-4189-aa1f-5e32b8badb0b"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[0.21581533, 0.15552261, 0.07792456, 0.29260253, 0.0565934 ],\n",
              "       [0.10173129, 0.09912153, 0.06040012, 0.15960138, 0.03557832],\n",
              "       [0.95111365, 0.34979297, 0.11707773, 0.48754312, 0.49311295],\n",
              "       ...,\n",
              "       [0.06825011, 0.06664056, 0.04596823, 0.06837869, 0.01438629],\n",
              "       [0.11303477, 0.51765331, 0.54978619, 0.66469912, 0.12930919],\n",
              "       [0.14560977, 0.62539167, 0.20202734, 0.49198927, 0.35521886]])"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "average_dataframe = dataframe.describe().loc[\"mean\"].values\n",
        "\n",
        "average_dataframe"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0ZEoAnxlmVPV",
        "outputId": "e9f64711-f572-455c-d7d9-d204fffa0edc"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 3.27967646,  5.18544905,  4.20090265, 84.05684422, 20.62598756])"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#compute averages of standardized dataframe\n",
        "standardized_averages = []\n",
        "\n",
        "number_of_features = 5\n",
        "\n",
        "for feature in range(number_of_features):\n",
        "  standardized_averages.append(dataframe_standardized[:, feature].mean())\n",
        "\n",
        "standardized_averages"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ISLWNvutmnut",
        "outputId": "6a3c453c-209f-4b9e-bdc8-6abd52c79ae4"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[-1.2891777373683814e-16,\n",
              " 3.533589581341045e-17,\n",
              " -3.261774998160965e-17,\n",
              " 2.9899604149808845e-17,\n",
              " -4.5043559498413327e-17]"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#compute averages of normalized dataframe\n",
        "normalized_averages = []\n",
        "\n",
        "number_of_features = 5\n",
        "\n",
        "for feature in range(number_of_features):\n",
        "  normalized_averages.append(dataframe_normalized[:, feature].mean())\n",
        "\n",
        "normalized_averages"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "G5PkHm1NnNqR",
        "outputId": "a5c4ec15-6b63-4eca-b5b3-b5d27d239c1c"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0.1640190178635346,\n",
              " 0.15211873993825842,\n",
              " 0.0840898270384112,\n",
              " 0.21114388997103622,\n",
              " 0.10343919741667634]"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Reduce data dimensionality with principal component analysis"
      ],
      "metadata": {
        "id": "DNQ__Xkpnjr0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "number_of_dimensions = 2\n",
        "\n",
        "pca = PCA(n_components = number_of_dimensions)"
      ],
      "metadata": {
        "id": "Cnx6M5zWnqhC"
      },
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "scaler = StandardScaler()\n",
        "\n",
        "normalized_data = scaler.fit_transform(dataframe)\n",
        "\n",
        "data_reduced = pca.fit_transform(normalized_data)\n",
        "\n",
        "data_reduced"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Yu0ib8AsqEG9",
        "outputId": "1634e980-c587-42c3-c25b-0ff6c83f9f83"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ 0.17861723, -0.0154594 ],\n",
              "       [-0.6639843 ,  0.12160097],\n",
              "       [ 3.80886246, -2.624901  ],\n",
              "       ...,\n",
              "       [-1.17366861,  0.09652186],\n",
              "       [ 3.80259956,  3.13084176],\n",
              "       [ 3.28702832,  0.88094509]])"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#check information retained\n",
        "information_retained = pca.explained_variance_ratio_\n",
        "\n",
        "information_retained"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BkQCyx85qgVD",
        "outputId": "562b804c-75a3-4bad-be39-f2ec1e73ddaa"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0.6667969 , 0.23149491])"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "numpy.sum(information_retained)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wSxcYu89qvaM",
        "outputId": "b5693c90-4b39-4de5-ebfa-00b6a4a6f346"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.8982918118292859"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Build a K Means clustering"
      ],
      "metadata": {
        "id": "DvQnonNZrb2j"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#determine optimal number of clusters\n",
        "minimum_clusters = 2\n",
        "maximum_clusters = 15\n",
        "iteration_value = 1\n",
        "distortions = []\n",
        "silhouette_scores = []\n",
        "\n",
        "for cluster in range(minimum_clusters, maximum_clusters, iteration_value):\n",
        "  model = KMeans(n_clusters = cluster,\n",
        "                 init = \"k-means++\",\n",
        "                 n_init = 10,\n",
        "                 max_iter = 100,\n",
        "                 random_state = 0)\n",
        "\n",
        "  model.fit(normalized_data)\n",
        "\n",
        "  distortions.append(model.inertia_)\n",
        "\n",
        "  silhouette_scores.append(silhouette_score(normalized_data,\n",
        "                                            model.labels_,\n",
        "                                            metric = \"euclidean\"))"
      ],
      "metadata": {
        "id": "gtbqvDG86f9T"
      },
      "execution_count": 30,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#plot distortions to find optimal number of clusters\n",
        "plt.rcParams[\"figure.figsize\"] = (15, 8)\n",
        "plt.rcParams.update({\"font.size\": 20})\n",
        "plt.plot(range(minimum_clusters, maximum_clusters, iteration_value), distortions, marker = 'o')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 514
        },
        "id": "o-HDscxr8jJe",
        "outputId": "ee4674fc-331b-4a9c-ed44-9b1baa749ff7"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7fde33d67be0>]"
            ]
          },
          "metadata": {},
          "execution_count": 33
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x576 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#plot silhouettes to find optimal number of clusters\n",
        "plt.rcParams[\"figure.figsize\"] = (15, 8)\n",
        "plt.rcParams.update({\"font.size\": 20})\n",
        "plt.plot(range(minimum_clusters, maximum_clusters, iteration_value), silhouette_scores, marker = 'o')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 509
        },
        "id": "BCkEoIoN9ny8",
        "outputId": "0b4a4fa9-bf33-4c9b-cd73-25ffdf5ac95b"
      },
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7fde31b0e610>]"
            ]
          },
          "metadata": {},
          "execution_count": 53
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x576 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Visualize clusters"
      ],
      "metadata": {
        "id": "QXuLhwtr-Fd2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Use 5 clusters to classify data\n",
        "optimal_clusters = 5\n",
        "model = KMeans(n_clusters = optimal_clusters,\n",
        "               init = \"k-means++\",\n",
        "               n_init = 10,\n",
        "               max_iter = 100,\n",
        "               random_state = 0)\n",
        "\n",
        "model.fit(normalized_data)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WQnrHyu2-IC7",
        "outputId": "534337a9-7d70-42e3-8688-94c10fb6d96c"
      },
      "execution_count": 54,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "KMeans(max_iter=100, n_clusters=5, random_state=0)"
            ]
          },
          "metadata": {},
          "execution_count": 54
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "clusters = model.labels_"
      ],
      "metadata": {
        "id": "3f5RnhGO-3H1"
      },
      "execution_count": 55,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#add clusters to initial dataframe\n",
        "dataframe[\"Cluster\"] = clusters\n",
        "\n",
        "dataframe"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "pXi8JmFy--zp",
        "outputId": "6d31282c-b84b-4164-ea44-0a4ed3cc47d1"
      },
      "execution_count": 56,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        FITC-CD3     PE-CD8   ECD-CD19    PC5-CD45     PC7-CD3  Cluster\n",
              "0       4.315380   5.301481   3.892902  116.485707   11.284839        3\n",
              "1       2.034189   3.378871   3.017428   63.537658    7.094390        0\n",
              "2      19.018191  11.923801   5.848890  194.091982   98.327730        1\n",
              "3      18.117922  14.278425   6.015783  227.966526  145.721575        1\n",
              "4       6.203657   5.125051   2.734187   95.794769   12.134564        3\n",
              "...          ...        ...        ...         ...         ...      ...\n",
              "39995   2.020838   2.534869   1.887323   59.295711    9.926805        0\n",
              "39996   3.795627   6.340987   3.256801  145.446916   14.008535        3\n",
              "39997   1.364709   2.271654   2.296450   27.221706    2.868655        0\n",
              "39998   2.260210  17.645853  27.465847  264.618172   25.784517        4\n",
              "39999   2.911570  21.318456  10.092745  195.862003   70.831366        2\n",
              "\n",
              "[36597 rows x 6 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-f1607d7c-8816-497c-bb8d-a6dbc5406964\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>FITC-CD3</th>\n",
              "      <th>PE-CD8</th>\n",
              "      <th>ECD-CD19</th>\n",
              "      <th>PC5-CD45</th>\n",
              "      <th>PC7-CD3</th>\n",
              "      <th>Cluster</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>4.315380</td>\n",
              "      <td>5.301481</td>\n",
              "      <td>3.892902</td>\n",
              "      <td>116.485707</td>\n",
              "      <td>11.284839</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2.034189</td>\n",
              "      <td>3.378871</td>\n",
              "      <td>3.017428</td>\n",
              "      <td>63.537658</td>\n",
              "      <td>7.094390</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>19.018191</td>\n",
              "      <td>11.923801</td>\n",
              "      <td>5.848890</td>\n",
              "      <td>194.091982</td>\n",
              "      <td>98.327730</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>18.117922</td>\n",
              "      <td>14.278425</td>\n",
              "      <td>6.015783</td>\n",
              "      <td>227.966526</td>\n",
              "      <td>145.721575</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>6.203657</td>\n",
              "      <td>5.125051</td>\n",
              "      <td>2.734187</td>\n",
              "      <td>95.794769</td>\n",
              "      <td>12.134564</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39995</th>\n",
              "      <td>2.020838</td>\n",
              "      <td>2.534869</td>\n",
              "      <td>1.887323</td>\n",
              "      <td>59.295711</td>\n",
              "      <td>9.926805</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39996</th>\n",
              "      <td>3.795627</td>\n",
              "      <td>6.340987</td>\n",
              "      <td>3.256801</td>\n",
              "      <td>145.446916</td>\n",
              "      <td>14.008535</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39997</th>\n",
              "      <td>1.364709</td>\n",
              "      <td>2.271654</td>\n",
              "      <td>2.296450</td>\n",
              "      <td>27.221706</td>\n",
              "      <td>2.868655</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39998</th>\n",
              "      <td>2.260210</td>\n",
              "      <td>17.645853</td>\n",
              "      <td>27.465847</td>\n",
              "      <td>264.618172</td>\n",
              "      <td>25.784517</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39999</th>\n",
              "      <td>2.911570</td>\n",
              "      <td>21.318456</td>\n",
              "      <td>10.092745</td>\n",
              "      <td>195.862003</td>\n",
              "      <td>70.831366</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>36597 rows × 6 columns</p>\n",
              "</div>\n",
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              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "    .colab-df-convert:hover {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "    [theme=dark] .colab-df-convert:hover {\n",
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              "\n",
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              "        const buttonEl =\n",
              "          document.querySelector('#df-f1607d7c-8816-497c-bb8d-a6dbc5406964 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-f1607d7c-8816-497c-bb8d-a6dbc5406964');\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",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 56
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#convert data_reduced array to dataframe to use for plotting\n",
        "data_reduced = pandas.DataFrame(data_reduced,\n",
        "                                columns = [\"Principal Component 1\", \"Principal Component 2\"])\n",
        "\n",
        "data_reduced[\"Cluster\"] = clusters"
      ],
      "metadata": {
        "id": "MLOYU9Lw_360"
      },
      "execution_count": 57,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#visualize clusters\n",
        "seaborn.pairplot(x_vars = \"Principal Component 1\",\n",
        "                 y_vars = \"Principal Component 2\",\n",
        "                 data = data_reduced,\n",
        "                 hue = \"Cluster\",\n",
        "                 size = 10,\n",
        "                 plot_kws = dict(alpha = 0.5, s = 30))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 789
        },
        "id": "a-_oz2Gg_StZ",
        "outputId": "d17be982-8329-4626-c9c0-268db3c19022"
      },
      "execution_count": 58,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/seaborn/axisgrid.py:2076: UserWarning: The `size` parameter has been renamed to `height`; please update your code.\n",
            "  warnings.warn(msg, UserWarning)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.PairGrid at 0x7fde31b36760>"
            ]
          },
          "metadata": {},
          "execution_count": 58
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 807.25x720 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}