Team_10Marianna.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Team_10Marianna ",
      "version": "0.3.2",
      "provenance": [],
      "collapsed_sections": []
    }
  },
  "cells": [
    {
      "metadata": {
        "id": "yljTSWJQwjW2",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# TARRAGONA DATATHON, November 2018\n",
        "## team_10 activities\n",
        "\n",
        "*   Marianna Polini: Data Scientist / SQL-Databases\n",
        "*   Christian Villavicencio: Clinician\n",
        "*   Eva Machado: Clinician\n",
        "*   Raquel Carbonell: Clinician\n",
        "*   Diana Gil: Clinician\n",
        "*   Laia Labad: Clinician\n",
        "*   Santiago Frias: Data Scientist / Statistics-Models\n",
        "\n"
      ]
    },
    {
      "metadata": {
        "id": "93B6Rgpg00jk",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "## Septic Shock query and stay time representation"
      ]
    },
    {
      "metadata": {
        "id": "rS9g4-r7uohe",
        "colab_type": "code",
        "outputId": "cdbad342-3e8f-4189-e43e-2d93c79e94de",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 68
        }
      },
      "cell_type": "code",
      "source": [
        "# Importacion Librerias\n",
        "import numpy\n",
        "print('numpy Version: ',numpy.__version__)\n",
        "import os\n",
        "import pandas\n",
        "print('Pandas Version: ',pandas.__version__)\n",
        "import matplotlib.pyplot as pyplot\n",
        "pyplot.rcParams['figure.figsize']= [20,12]\n",
        "import matplotlib.patches as patches\n",
        "import matplotlib.path as path\n",
        "import tensorflow\n",
        "print('tensorflow Version: ',tensorflow.__version__)\n",
        "# Visualización Dataframes\n",
        "from IPython.display import display, HTML\n",
        "\n",
        "# Acceso repositorio datos Datathon.\n",
        "from google.colab import auth\n",
        "from google.cloud import bigquery"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "('numpy Version: ', '1.14.6')\n",
            "('Pandas Version: ', u'0.22.0')\n",
            "('tensorflow Version: ', '1.12.0')\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "HDL3CjUKvddl",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "# Autentificacion BigQuery, generacion resumen verificacion a pegar despues de validacion.\n",
        "auth.authenticate_user()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "nx4ZDlJ6we9j",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "# Hosting solo lectura proyecto datathon-tarragona-2018\n",
        "# Creado proyecto compartido team_10 asignado en este kernel\n",
        "project_id='datathon-tarragona-2018'\n",
        "os.environ[\"GOOGLE_CLOUD_PROJECT\"]=project_id"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "DIbbCE3YxLdM",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "# Asignar configuracion de la ejecucion de sentencias SQL en BigQuery\n",
        "def run_query(query):\n",
        "  return pandas.io.gbq.read_gbq(query, project_id=project_id, verbose=True, configuration={'query':{'useLegacySql': False}})"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "cRVKD6o1KNy6",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "# consulta"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "k3mZeP98oR_w",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# Crude Data"
      ]
    },
    {
      "metadata": {
        "id": "0BKEaZ0mAS_a",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "consulta = run_query(\"SELECT patientunitstayid,activeupondischarge,diagnosisoffset FROM [physionet-data:eicu_crd.diagnosis] WHERE LOWER(diagnosisstring) LIKE '%septic shock%' ORDER BY patientunitstayid,activeupondischarge, diagnosisoffset\")"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "OLfhw6-PnmcB",
        "colab_type": "code",
        "outputId": "6be2960b-09f4-4be4-f7ef-9b1e7b7a608d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1828
        }
      },
      "cell_type": "code",
      "source": [
        "consulta"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>patientunitstayid</th>\n",
              "      <th>activeupondischarge</th>\n",
              "      <th>diagnosisoffset</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>141515</td>\n",
              "      <td>False</td>\n",
              "      <td>134</td>\n",
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              "      <th>1</th>\n",
              "      <td>141515</td>\n",
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              "      <th>7</th>\n",
              "      <td>142483</td>\n",
              "      <td>False</td>\n",
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              "      <td>142483</td>\n",
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              "      <td>122</td>\n",
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              "      <th>15</th>\n",
              "      <td>145394</td>\n",
              "      <td>False</td>\n",
              "      <td>7670</td>\n",
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              "      <td>145394</td>\n",
              "      <td>True</td>\n",
              "      <td>7671</td>\n",
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              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>145917</td>\n",
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              "      <td>146788</td>\n",
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              "      <th>35107</th>\n",
              "      <td>3352104</td>\n",
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              "    </tr>\n",
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              "      <td>True</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>35109</th>\n",
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              "      <td>False</td>\n",
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              "    <tr>\n",
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              "      <td>True</td>\n",
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              "      <td>False</td>\n",
              "      <td>80</td>\n",
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              "      <td>False</td>\n",
              "      <td>117</td>\n",
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              "      <th>35115</th>\n",
              "      <td>3352711</td>\n",
              "      <td>False</td>\n",
              "      <td>2223</td>\n",
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              "    <tr>\n",
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              "      <td>3352711</td>\n",
              "      <td>False</td>\n",
              "      <td>6212</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35117</th>\n",
              "      <td>3352711</td>\n",
              "      <td>False</td>\n",
              "      <td>6548</td>\n",
              "    </tr>\n",
              "    <tr>\n",
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              "      <td>3352711</td>\n",
              "      <td>False</td>\n",
              "      <td>7283</td>\n",
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              "    <tr>\n",
              "      <th>35119</th>\n",
              "      <td>3352711</td>\n",
              "      <td>False</td>\n",
              "      <td>9140</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35120</th>\n",
              "      <td>3352711</td>\n",
              "      <td>True</td>\n",
              "      <td>10531</td>\n",
              "    </tr>\n",
              "    <tr>\n",
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              "      <td>3352884</td>\n",
              "      <td>False</td>\n",
              "      <td>111</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35122</th>\n",
              "      <td>3352884</td>\n",
              "      <td>False</td>\n",
              "      <td>1329</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35123</th>\n",
              "      <td>3352884</td>\n",
              "      <td>True</td>\n",
              "      <td>2768</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35124</th>\n",
              "      <td>3352922</td>\n",
              "      <td>False</td>\n",
              "      <td>67</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35125</th>\n",
              "      <td>3352922</td>\n",
              "      <td>False</td>\n",
              "      <td>139</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35126</th>\n",
              "      <td>3352922</td>\n",
              "      <td>False</td>\n",
              "      <td>144</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35127</th>\n",
              "      <td>3352922</td>\n",
              "      <td>False</td>\n",
              "      <td>309</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35128</th>\n",
              "      <td>3352922</td>\n",
              "      <td>False</td>\n",
              "      <td>505</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35129</th>\n",
              "      <td>3352922</td>\n",
              "      <td>False</td>\n",
              "      <td>1386</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35130</th>\n",
              "      <td>3352922</td>\n",
              "      <td>False</td>\n",
              "      <td>3362</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35131</th>\n",
              "      <td>3352922</td>\n",
              "      <td>True</td>\n",
              "      <td>3851</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>35132 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "       patientunitstayid  activeupondischarge  diagnosisoffset\n",
              "0                 141515                False              134\n",
              "1                 141515                False             2418\n",
              "2                 141515                False             3346\n",
              "3                 141515                 True             3870\n",
              "4                 141751                False               45\n",
              "5                 141751                 True              460\n",
              "6                 141959                 True              219\n",
              "7                 142483                False             1363\n",
              "8                 142483                False             1741\n",
              "9                 142483                False            21476\n",
              "10                142483                 True            30971\n",
              "11                143466                 True             7279\n",
              "12                143599                False              217\n",
              "13                143599                 True              221\n",
              "14                143970                 True              122\n",
              "15                145394                False             7670\n",
              "16                145394                 True             7671\n",
              "17                145917                False             3371\n",
              "18                145917                 True             3912\n",
              "19                146349                False             1823\n",
              "20                146349                False             2170\n",
              "21                146349                False             3472\n",
              "22                146349                False             7858\n",
              "23                146788                 True             1749\n",
              "24                148182                False            14361\n",
              "25                148182                 True            16201\n",
              "26                148529                False               37\n",
              "27                148529                False             3136\n",
              "28                149178                False               30\n",
              "29                149178                 True               37\n",
              "...                  ...                  ...              ...\n",
              "35102            3352103                False             5731\n",
              "35103            3352103                False             6535\n",
              "35104            3352104                False               59\n",
              "35105            3352104                False              517\n",
              "35106            3352104                False              517\n",
              "35107            3352104                False              537\n",
              "35108            3352271                 True              105\n",
              "35109            3352358                False               56\n",
              "35110            3352358                False              426\n",
              "35111            3352358                False              869\n",
              "35112            3352358                 True             2120\n",
              "35113            3352711                False               80\n",
              "35114            3352711                False              117\n",
              "35115            3352711                False             2223\n",
              "35116            3352711                False             6212\n",
              "35117            3352711                False             6548\n",
              "35118            3352711                False             7283\n",
              "35119            3352711                False             9140\n",
              "35120            3352711                 True            10531\n",
              "35121            3352884                False              111\n",
              "35122            3352884                False             1329\n",
              "35123            3352884                 True             2768\n",
              "35124            3352922                False               67\n",
              "35125            3352922                False              139\n",
              "35126            3352922                False              144\n",
              "35127            3352922                False              309\n",
              "35128            3352922                False              505\n",
              "35129            3352922                False             1386\n",
              "35130            3352922                False             3362\n",
              "35131            3352922                 True             3851\n",
              "\n",
              "[35132 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "metadata": {
        "id": "nFZubIs0gtH1",
        "colab_type": "code",
        "outputId": "49ecfb19-0bea-4afd-a898-cbad78073857",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 948
        }
      },
      "cell_type": "code",
      "source": [
        "# Scatter Plot de correlacion entre eje x, eje y, de ejemplo crude data\n",
        "consulta.plot(figsize = [20,16], kind='scatter',x='patientunitstayid',y='diagnosisoffset' )"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f217e8191d0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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ePVm8eHE6Oztz/fXXZ9++fTn77LMzY8aMJMnll1+eefPmpaGhIYsXL86YMWMy\nf/78XHPNNZk7d24mTpyYW2+9NUmyePHiLFy4MEly0UUX5dRTva0JgNHLHlgAADBUw+CRbiY1Sh2q\nrVLLJbVg3lEL5l25vvKdf86Tz722PP7db/8v+dSl02pY0dFj3lEL5h21YN5RC+YdtXBMLiEEAN7Y\nYIY+W6rTZ00AALCfAAsACvOzl34xdLzjF4c4EwAA6oMACwAKs6Nvz7BjAACoNyO6iTsA8MZaWxqz\nvXf3a+NxLtcAAMei3r7+LF21Pt09u9LZ3pL5s6emtaW51mUVyR0xABTmv7ypJRu6d742bm+pYTUA\nAFTL0lXr8/i6rUmSFza/vBH6Jy4+s5YlFUuABVAwT2Tqk03cAQDqQ3fPrmHHvEaABVAwT2TqU09v\n/7BjAACODZ3tLfvv818dc3ACLICCeSJTn9zIAADUh/mzpybJkBUXHJwAC6Bggoz65EYGAKA+tLY0\nW2FRIQEWQMEEGfXJjQwAAAwlwAIomCADAAAgGVPrAgAAAABgOAIsAAAAAIpmCSEAFKa3rz9LV60f\nsvdZa0tzrcsCAICaEWABQGGWrlqfx9dtTZL9b6G0FxoAAPXMEkIAKMyWn+0cOt6+8xBnAgBAfRBg\nAUBhdvTtGXYMAAD1xhJCgILZC6k+tbY0Znvv7tfG41yuAQCob+6IAQpmL6T6dOLxE7Khe+eQMQAA\n1DMBFkDBunt2DTvm2DR/9tQkGdJ5BwAA9UyABVCwzvaW/Z1Xr4459rW2NOu0AwCA1xFgARRMJ059\nsvcZAAAMJcACKJhOnPpk7zMAABhqTK0LAACGsvcZAAAMJcACgMJMaj1u6LjtuEOcCQAA9UGABQCF\nGczg0PHg4CHOBACA+iDAAoDC/OylXwwd7/jFIc4EAID6IMACgMLs6Nsz7BgAAOqNAAsACtPaMvQl\nwa3jvDQYAID65o4YAApz4vETsqF755Axh6e3rz9LV61Pd8+udLa3ZP7sqWltaa51WQBwzNn84s7c\nuuKp7Nw1kAnjmnLNVdNz4iT3Lhx9AiwAKMz82VOTZEj4wuG55/vr8uSz25IkL2zekT179+VTl06r\ncVUAcOy5dcVT2b5jd5Kkv3d3br3vqdy2YGaNq+JYJMACgMK0tjTnExefWesyRrV//Y+eYccAwNGx\nc9fAsGM4WgRYMApYCgNwuAbfYAwAHA0TxjWlv3f3a+OWphpWw7FMgAWjwNJV6/P4uq1JXl4Kk0R3\nRp0QXtYnf+9Hbuop7XnquReHjAGAo++aq6bn1vte2QOrpSnXzJ1e65I4RgmwYBTo7tk17Jhjl/Cy\nPvl7P3If+eAZWbpyvX3EAKAi0pIeAAAgAElEQVTKTpw0wZ5XjAgBFowCne0t+3+JfXVMfRBe1id/\n70fOPmIAAMeWMZWc9KUvfemXjn32s5896sUABzd/9tT8+uldeduJbfn107t0EtSRA8NK4WV9mNR6\n3NBx23GHOBMAoLZ6+/rzF/c/nT/5xuP5i/ufTu+u/lqXxDFq2A6s//t//29WrVqVNWvWZOvWrfuP\nDwwM5Iknnqh6ccDLdBLUr1fDSsug6svgARuODw7agBwAKNM931+XJ5/dluTlrQ/27N2XT106rcZV\ncSwaNsCaNWtWOjo68vTTT+e8887bf7yhoSGf+tSnql4c8DIbOtcv4WV96untH3YMAFCKf/2PnmHH\ncLQMG2CNGzcuv/Zrv5b7778/fX192bhxY84666zs27cvY8ZUtPoQOAps6Az1xb53AMDocWCnuM5x\nqqOiTdz//u//Pn/2Z3+W5ubmfO9738uSJUvyzne+M3PmzKl2fUBs6Az1xtJRAGC0mHpKe5567sUh\nY6iGigKsr3/96/m7v/u7fOxjH0uSfOYzn8n8+fMFWDBCdGPUL8tH65OlowDAaPGRD56RpSvXe/BG\n1VUUYLW1taWl5bVfmMeNG5empqaqFQUMpRujflk+CgBAyTx4Y6RUFGBNmjQp3/3ud7N79+4888wz\nefDBB9PR0VHt2oBXuCjUL8tHAQDg2GXFReUqCrC+8IUv5Pbbb8/OnTvzuc99Lr/2a7+WL37xi9Wu\nDXiFf9Tql+WjAACUzO8qR8aKi8pVFGBNnDgx1113XRoaGrJ79+787Gc/S3u7jdlgpPhHrX5ZPlqf\n3AgCcDhcN6glv6scGSsuKldRgHXnnXdm/PjxmTNnTn7v934vEyZMyMyZM3P11VdXuz4g/lGrZ5aP\n1ic3ggAcDtcNamnLz3YOHW/feYgzORgrLipXUYD18MMPZ/ny5bn//vtzwQUX5Jprrsl/+2//rdq1\nAa/wjxrUF6E1AIejxOuGrrD6saNvz7BjhmfFReUqCrAaGxvT0NCQf/iHf9gfXO3bt6+qhQGv8Y8a\n1BehNQCHo8Trhq6w+tHa0pjtvbtfG4+rKGbgFVZcVK6imdXW1paPfexj2bx5c9797nfn4YcfTkND\nQ7VrA17hHzWoL0JrAA5HideNErvCqI4Tj5+QDd07h4yhGoYNsLZs2ZITTjgh119/fZ555pmcc845\nSZLm5ubcfPPNI1IgANQboTUAh6PE60aJXWFUR4kBKsemYQOsT3ziE1mxYkWuvfba/NVf/VUGBwez\nb9++nHfeeSNVHxB7CAAAMLoINepHiQEqx6ZhA6xTTjkl06dPz759+/LOd75z//HBwcE0NDTkX/7l\nX6peIGAPAQAADq3Eh51CDeBoGzbA+vKXv5yxY8dm0aJF+dM//dORqgk4gD0E6tfmF3fm1hVPZeeu\ngUwY15RrrpqeEyfZVwAAeI2HndRSiQEqx6ZhA6yrrroqK1asyMaNG0eqHuAg7CFQv25d8VS273j5\nrS79vbtz631P5bYFM2tcFQBQkhIfdgo1RrefbOzJLcufzMDewTSNbci1896dySe1H/Tce76/Lk8+\nuy3JywHqnr378qlLp41kudSJYQOshoaGvO9978tLL72U3/qt39p//NUlhI888kiVywMSewjUs527\nBoYdAwCU+LBTqDG63bT8yezdO5gkGdg7mJuWPZm7rrngoOf+63/0DDuGo2XYAOub3/xmtmzZkkWL\nFuWLX/ziSNUEHMAeAvVrwrim9Pfufm3c0lTDahgpnloDcDhKfNgp1BjdXg2vDjUe6sCvDXcuB3Lf\nV7lhA6wxY8bkpJNOyj333JONGzfmxz/+cRoaGvKud70rb37zm0eqRoC6dc1V03Prfa/sgdXSlGvm\nTq91SYwAe5kAcDjKfNgp1KgXU09pz1PPvThkTOXc91Vu2ADrVStWrMhXv/rVnHnmy/8Rb7rppnzy\nk5/MJZdcUtXiAI7EsfA048RJE+x5VYdK3MsEAA6HUKN+fOSDZ2TpyvVFdQCOJu77KldRgHX//ffn\n+9//fo477rgkSV9fXz784Q8LsICieZrBaFXiXiYAlKvEh3ZCjdHtsx86J7csG7qJ+6GU2QE4erjv\nq1xFAVZjY+P+8CpJxo8fn6Ym+7DASCnxpmQ08DSD0arEvUwAKFeJG6YLNUa3ySe1585DbNrO0eW+\nr3IVBVgnnnhilixZkhkzZiRJfvCDH+Skk06qamHAa3QS/Wo8zWDUsk0IAIfBhukcbT/Z2JNblg/t\nwJp80sGXgXrYfmSEvZWrKMBasmRJli5dmr/9279NQ0NDpk+fnnnz5lW7NuAVW362c+h4+85DnMnr\neZrBaCW0BuDw2DCdo+um5U/uf/PgwN7B3LTsydx1iI6sEjsAOTZVFGC1tLRk7ty5+djHPpbu7u78\n+7//e5qbJaowUnb07Rl2zMGV/jTD0yoOxfJXAA6HDdM52l4Nrw41fj0dgIyUMZWctGTJknz/+99P\nT09P5s6dm2XLlmXx4sVVLg14VWvL0Ky5dVxF2TOFe7XL5oXNO/L4uq1ZunJ9rUuiEAcud7X8FYDh\nfOSDZ+TXT+/K205sy6+f3pWPfPCMWpdEXdEByMio6LfgH//4x7nuuuuyfPnyXHzxxVmwYEE+9KEP\nVbs24BUnHj8hG7p3Dhkz+umy4VAsfwXgcJTedc6xTQfgkbEqo3IVBViDgy8nqI888kiuvvrqJEl/\nf3/1qgKG8Mvssckm8xyKX0QAgFr67IfOyS3Lhm7ifigf+eAZWbpyvd9VfkX2Pq1cRQHW2972tlx0\n0UXp6OjIGWeckfvvvz9vetObql0b8Aq/zB6bKgkmPZEBAGCkTT6pPXceYtP2A/ld5chYlVG5igKs\nG264IevXr8/kyZOTJFOmTMmtt95a1cIAjnXDXexfDa6eef7F9O3em8QTGQDg4DzwgtHLqozKDRtg\n/c3f/E0uvfTS/O///b8P+vVPf/rTVSkKGMpNSf15fSvx63kiAwAcyBIkjrbVT27IvSuf3T/+8EVv\nz6xppxz0XL+rHBnbxVRu2ABrzJiXX1I4duzYESkGODg3Jcem4S72hwqqPJEBAA5kCRJH2+vDqyS5\n58FnDxlg3fP9dXny2W1JXv5dZc/effnUpdOqXuOxwhLMyg0bYF1yySVJkk9+8pPp7e1Na2trtm3b\nlhdeeCHnnHPOiBQIuCk5Vg0XTB7YSjz+uMa869QOT2TqhCeZAByOEpcguZbVj3/9j55hx3C0VLQH\n1pIlS3L66afnwgsvzBVXXJEzzzwzDzzwQP7kT/6k2vUBKfOmhCM3XDB5sFZiN331Q9clAIejxCVI\nrmX1ZPANxnB0VBRg/fjHP851112X5cuX55JLLsmCBQvyoQ99qNq1Aa8o8aaEIzdcMKmVuL7pugTg\ncJR43+BaNrp9+KK3554Hh+6BdShTT2nPU8+9OGRM5XQrVq6iAGtw8OUE9ZFHHsnVV1+dJOnv769e\nVcAQJd6UcOQEkxyKrksARjvXstFt1rRTDrnn1YE+8sEzsnTleve0vyLdipWrKMA69dRTc9FFF6Wj\noyNnnHFG7r///rzpTW+qdm0AxzTBJIci3ARgtHMtqx/uaY+MbsXKVRRgffGLX8z69eszefLkJMmU\nKVNyyy23VLUwAKhbto4A4DCUuARJqAGV0a1YuYoCrF/84hf5f//v/+XP/uzP0tDQkOnTp2fKlCnV\nrg0A6pJWcgAOh+sGjF66FStXUYB13XXX5YQTTsgVV1yRwcHBPProo/nc5z6XL33pS9WuDwDqjlZy\nAA6H6wZH2+onN+TelUM3cT/UnlibX9yZW1c8lZ27BjJhXFOuuWp6Tpw0YaRKHfV0K1ZuTCUnbdu2\nLZ/5zGfyW7/1W7ngggvy2c9+Nlu2bKl2bQBQlw5sHddKDsBwXDc42l4fXiUZ8kbCA9264qls37E7\n/Xv2ZXvv7tx631PVLo86VVEH1q5du7Jr1660tLz8D2FfX192795d1cKA15S4rwFQPVrJATgcrhvU\n0s5dA8OO4WipKMD6/d///XzgAx/ImWeemcHBwfz4xz/Opz/96WrXBrzCvgZQX7SSA3A4SrxueABb\nPyaMa0p/72sNLhNammpYzejj/5XKVRRgXXbZZZk5c2aeeeaZNDQ05Prrr88JJ5xQ7dqAV9jX4Ffj\nYgAAUBsewI5uH77o7UOWDX74orcf8txrrpqeW+97ZQ+slqZcM3f6SJR4zPD/SuUqCrB2796dZ555\nJj//+c8zODiYH/zgB0leDraA6vNq1V+NiwGjlfAVgNFupB7A2kC8OmZNO+WQm7Yf6MRJE3LbgplV\nrujYpVmhchUFWB/96EczZsyYnHzyyUOOC7BgZNjX4FfjYsBoJXwF4HCU+OBjpB7AvrqBeJL0v7KB\nuDCF0USzQuUqCrD27NmTFStWVLsW4BBK3NdgNHAxYLQSvgJwOEp88DFSD2BtIF4dP9nYk1uWP5mB\nvYNpGtuQa+e9O5NPaj/oubrgjoxmhcpVFGBNmTIl27dvz6RJk6pdD8BR42LAaCV8BeBwlPjgY6Qe\nwNpAvDpuWv5k9u4dTJIM7B3MTcuezF3XXHDQc3XBHRnNCpWrKMDavHlzfvd3fzeTJ0/O2LFj9x//\n5je/WbXCgNeU2BY+GrgYMFoJXwE4HPX84MMG4tXxanh1qPHr6YJjpFQUYH3sYx+rdh3AMEpsC6e6\nhJb1TfgKwOEYLQ8+qnF/YwPx2tMFx0ipKMDau3fvL//BxsZs2bIlJ5xwwlEvChiqxLZwqktoCQBU\narQ8+HB/c2zSBcdIqSjA+su//MusXbs2b3vb2zJ27Ng8//zzede73pWNGzfmv//3/56rrrqq2nVC\nXavntvAjMZq7mISWAMCxxv3N6PHZD52TW5YN3cT9UHTBMVIqCrDe/OY353Of+1ze/va3J0mee+65\nLF26NPfcc0/mzZsnwIIqGy1t4aUZzU/5hJb1zdt8ADgWub8ZPSaf1J47D7FpO9RKRQHWv//7v+8P\nr5KX30r4k5/8JMcdd9yQTd2BKjn0nokMYzQ/5RNa1jdv8wHgcIyWrnP3N8CRqCjAamlpyc0335zf\n+I3fyJgxY7J27doMDAzkBz/4QcaPH1/tGqlDo+UiPFJGcydRLY3mp3yjZS8LqsPbfAA4HKPlXtH9\nzejxk409uWX50CWEk09qP+i5OscZKWMqOem2227Lcccdl29961v55je/md27d+fP//zP85a3vCW3\n3HJLtWukDr16EX5h8448vm5rlq5cX+uSamo0dxLV0vzZU/Prp3fllM4JmdR2XLZs35m/uP/p9O7q\nr3VpSV4Oav/i/qfzJ994vKi6qL0J44a+vcfbfAAYjntFjrZXw6skGdg7mFuWPXnIc1/tHO/fsy/b\nX+kch2qoqAOrvb09V1999ZBjN998cz7zmc9UpShwER5qNHcS1dKrT/n+4v6n8/i6rdm+Y3f+Y8vO\nJGU8lRwtT0sZed7mA8DhGC33ilZZjB6vhleHGr+eznFGSkUB1j/90z/ly1/+cnp6epIk/f39aW9v\nF2BRNaPlIjxS7BdwZEoNRCupy41effI2HwAOx2i5V/TwbvQYO7Yhe18XWo0d23DIcyeMa0p/7+7X\nxjrHqZKKAqzbb7891113Xf70T/80N9xwQx588MG85z3vqXZt1LHRchEeKfYLODKlBqKV1OVGDwB4\nI6PlXrHUh4r8sr0HdFwdOH49neOMlIoCrNbW1kyfPj1NTU15+9vfnk9/+tP5wz/8w8yc6ekw1TFa\nLsKU7dXupc0v7syktuPSNr4xJ0yaUEwgWklQ60YPADhWlPpQkSOjc5yRUlGAtWfPnjzxxBOZOHFi\nvvvd72by5MnZuHFjtWsDOCKv715Kkiknv6moYHS4oPbV8G3r9r4hx93oAQCjlVUWo0fT2IYh+141\nDbOEkCNjy5DKVRRgfeELX8i2bdty7bXXZsmSJdm2bVs+/vGPV7s2gCMymruXDgzfGhqS9tbjcsn5\np9awKgCgRKPlF+BqrLIYLZ99tLl23rtzy7KX30TYNLYh18579yHP9XdwZGwZUrmKAqzTTjstp512\nWpLk61//elULAjhaRnOb+paf7RwyHhxMtu/Yne+uft4FrQ5sfnFnbl3xyl4S45pyzVXTc+KkCbUu\nC4BC1fMvwPX82atp4+Yd+zuwBvYO5qfdOzL5pPaDnuvv4MiM5ofuI23YAOvqq6/O7bffnvPPPz8N\nDb/cMvjII48c9g984IEHcvfdd6exsTF/9Ed/lHe84x259tprs3fv3nR2dubWW29Nc3NzHnjggdx7\n770ZM2ZMLr/88syZMycDAwP54z/+4/z0pz/N2LFjc+ONN+aUU07JunXrsnjx4iTJO97xjnzhC184\n7LqAY89oblPf0bfnoMdd0OrDTfetzUs7X34FdX/v7ty0bG1u/9SsGlcFQKlK/AV4pLpySvzsx4J7\nVz47ZHzPg89m1rRTDnrugQ9et2zfedDzOLhJrcflhbz20H1S23E1rKZswwZY73znO3P//ffn6quv\nPio/bPv27bnjjjvyN3/zN+nr68tXvvKVrFy5MnPnzs0HPvCBfPnLX853vvOdXHzxxbnjjjvyne98\nJ01NTbnsssty4YUX5uGHH87EiRNz22235R//8R9z22235fbbb88NN9yQRYsWZdq0aVm4cGFWr16d\n888//6jUDCXQlvurGc0vA2htacz2172O+FWjqYuMX92r4dWhxgDweiV2nR+sK2f+70496ve0JX72\nenPgg9dDPYjl4AYz9A2Pg4OHfuNjvRs2wHr22Wfz7LPPpqenJ//yL/+S6dOnZ8+ePfnnf/7nvPvd\n784ll1xyWD9szZo1Oe+889La2prW1tYsWbIkv/3bv72/Y+qCCy7I17/+9Zx66qk566yz0tbWliQ5\n55xzsnbt2qxZsyYXX3xxkmTGjBlZtGhR+vv7s2nTpkybNm3/91izZo0Ai2OKttz6c+LxE7Kh+7Wn\nV+OPa8y7Tu0YVV1kAMDIKLHr/GCdUdW4py3xs9ebAx+8to6raKciXtHT2z/smNcMO7P+f/bePbqt\n6s77/sq25ItkbCVxcCABQi4kAyQOQ2C1NKXtvAMdMmtBhg6lhLQlvVIm7Qw8oayUoYX1lmbicuk1\npZ0SaDJJmHYm6cwqNFnzDKVPaV8a3th5Y4bgOE3IDceOYzmWbEuyrPcP58g6W+ccnZt0Lvp+/kmO\nJB9tnX3O3r/9/V12e3s7AODLX/4y/uu//gt1dXUAgHg8jkcffdTwl508eRJjY2P44he/iPPnz2Pd\nunUYHR1FKDSpuk+fPh39/f04e/Yspk2blvu7adOmFbxeVVWFQCCAs2fP4qKLLsp9VjoHIX6CodGV\nh2R89Q4kEB8bR2MDDYFKIlJXjfhYZuq4vtrB1hBCCHE7bow6V4qMsmrTqmUluO23Vxqi47V1Out2\nGoFRhPrRtSI6ffp0TrwCgEgkgtOnT5v6wlgshu9///s4ffo0PvnJT8rC49RC5Yy8rjfcLhptQE2N\n8oKgpaVR1zkIsROt+272xY2yQW32xY28T31OC4DHPvc+/NPP9uF3B05jcDiJ42cSqK2twVc/udy+\n7+F95Eq+/ZUP4dEfvY7hkRQaG0L4v794E1paIk43yzbKcd8NJVL40b8dwJlzI7h4WgPuv3MpLgoz\n9bqS4XhHnKCS77u1t1+Lo+9NzWWfuf1abPv125Zs2ud/tk8WwWW3XeQX7Ljvvv3lFdjww9eRHp9A\nsKYKT37pJtXz/v09f47NnHNN45frV47xTpeAtWDBAtx9991YtmwZqqqqcODAAVx++eWGv2z69OlY\ntmwZampqcNlllyEcDqO6uhpjY2Ooq6vDmTNnMHPmTMycORNnz57N/V1fXx/a2towc+ZM9Pf3Y9Gi\nRUin08hms2hpaUEsFst9VjpHMQYHRxRfb2lpRH//sOJ7hJSKYvfdXR+6EsnkeM7bdNeHruR9WiGc\nPDNccGxX33O8cy+hALDp/vfnvZL1TV+V677bvLsrt8g5fCKGZHKcHvoKhuMdcYJKv++e/2UXzg6N\nAQCSQ2P46S8PYs2tCy3ZtKW0i/yCXffdtIYgfvS/PiR7Teu8a/9qUe7/yZEk+kcKa7kSdbx+/cT7\nrlRili4B68knn8Tvf/97dHd3I5vN4nOf+xxWrDC+G9IHPvABPPLII/jc5z6HoaEhjIyM4AMf+AD2\n7NmD22+/HXv37sWKFSuwdOlSPProozh//jyqq6uxf/9+bNiwAfF4HL/+9a+xYsUKvPrqq7jxxhsR\nDAZx5ZVX4s0338T111+PvXv3Ys2aNYbbRoibYWi0P9FTnJ8hxZUJN26wDlOvCSGVhBvnDaVx2KpN\nS7uIkMpGl4AVCARw00034aabbrL0ZRdffDFuvfVW3HXXXQCARx99FNdeey2++tWv4qWXXsIll1yC\nO+64A8FgEA899BA+85nPIBAI4IEHHkBjYyNuu+02/P73v8cnPvEJhEIhbNy4EQCwYcMGPPbYY5iY\nmMDSpUvx/ve/X6sZhBDiCrQKmUqG6Km+YQSrA0AggEh9EKtunutYe0n54MYN1uEihxBSSbhx3ijF\nOMyC7eXj5/99CK/8caps0Mr3XYI7b16k+Fk3CqjEn5S9KvDdd9+Nu+++W/bali1bCj730Y9+FB/9\n6Edlr1VXV+Nb3/pWwWfnz5+P7du329tQQlwEJwV/ohUhkm+ITpLF4HASP//vI1h355IytZA4BaOH\nrMNFDiGkknDjvFGKcZhZCeUjX7wCgF/94bSqgLXllUPoODxZAuhY7zDGMxO0V0lJ4LZWhHgAN3rV\niHW0PJNqhuc7x2OKrxN/wegh63CRYw90oBDiDdw4byiNwxxT3IHd/SDapx2Hz6J3MIHWKHcjJPZC\nAYsQD+BGrxqxjpZnUjREp9C30yrxNowesg4XSfZABwoh3sAr8wbHFHdgf8RUoX3avr0TTz1grQQR\nISIUsAjxAG70qhHraEWISIbnwSP9GEtPGQUL5zSXpW3EWRg9ZB0ukuyBDhRCvIFX5g2OKe5AjJhS\nivBf+b5L8Ks/yGtgqbFwTjM6ewZkryVG0xZbSUghFLAI8QBe8aq5DS9HYEiGaHw0ha17utn3hBiE\niyR7oAOFEGInHFPcghgxVRhBdefNi1RrXomsXbkYD33/daQzU+cJ1wetNJAQRShgEeIBvOJVcxu+\niMBgxiAhpuAiyR5WfXAuek4NITGaRpg7oRJCLEKnrDsQI6asRvhH6kN4/LM3oH17Z26+WH9Pm9Vm\nElIABSxCiG/xQwSGL0Q4YhgvRw+6BS6S7GHXb49icDgJAEgNJ7HrtaMcgwhxIV6ZN+iUdQdrVy62\nPcK/NRpmzStScihgEeIBvGKUuA0/RGCcOZeQHw8mVD5J/ASFS+twkWQPfnAEEFIJcN4gRtAzRx45\nGcOmHR1IZ7IIVgfw8L3LMG+WcqQW1yqkXFDAIsQD0Cgxhx8iMM6PyAtgnk+wIGYlQNGAuAU/OAII\nqQQ4bxAj9A4k0L7zQrpfXRDrV7ehNRqWfWbjjg5kLtS0Smey2LitAz9Z/2HF84m7Gu471IcH774W\n11zRUtofQiqOKqcbQAgpDo0Sc0jepQfvWgoAePqlA9i8uwvx0ZTDLdPPWHJc85j4E1EkoGhgnN6B\nBB76wev44rd/g4e+/zp6Gb1oijW3LsTyRTNxRWsjli+a6UlHACGVAOcNYoT2nZ0YHE4iNT6BwXgS\n7ds7Cz6TyWQ1j/NR2sXwmZ0HrTeUEAFGYBHiAegBt4aXI9iqqgKax8Sf+CF60Gkk4xwAUheMc9bm\nMA5TMQnxBl6ZN5hq5g4So2nNY+MUilvch4iUAgpYhHgArxglbsXLEWx27xJDvAFFA+vYb5wTQoh7\n8cq84WWnop8I1wWRiienjuuDls4n2qsAQJcrKQVMISTEA0hGyWOfXo7777iGniqDeDmsfu3KxbL0\nnbUrFzvdJEI8QUOt3EfXUEefHSGEOI2XnYp+Yv3qNkQbaxGqqUK0sRbr72kr+MzXPnUdgtWTMlSw\nOoCvfeo61fOtXbkY8y+J5I4DAP7h7mttbzchtOYIIb7HyxFsXvGoEuI2Zrc0IJaYqnc3e0aDg60h\nhBACsCyGW2iNhoum1c+b1YznVIq2i0TqQ9jwyRvsaBohmlDAIoT4HopAhFQe8bGM5jEhhJDy42Wn\nIiHEeShgEUIIIcR30MtPCKkkvFIcnU5F73DkZAybdnQgnckiWB3Aw/cuw7xZyrVY4yMp/Pg/uvD2\nuzFMAGhqCOHhe5ehNRoub6M9ileeXzdAAYsQD8BBjZDKgs+8dejlJ4RUEiyOToxwsKcfz/7iILKY\nqld1zRUtss9s3NGBTGZyL8F0JouN2zrwE5WUwi2vHELXsVjuOJZIcfdfA/D51Q8FLEI8AAc1QioL\nPvPWoZefEFJJeKU4Oh007kASrwAgC+CZnQfx00c+IvuMJF6pHefzzvFYwWvxEe7+qxevPL9ugAIW\nIR6Ag5o5vGwkSW3vHUggPjaOxoYaXBwNe+o3EPPwmSeEEGIEr6RN00HjDkQpSl2aMntGYDwzYfms\nlYJXnl83QAGLEA/AQc0cXjaS8tsOAIPDSRw/kwDgnd9AzMNnnhBCiBG8kjZNB407CEAuOQUsnm/h\nnGZ09gwUfAfRh1eeXzdAAYsQD8BBzRxeNpLU2uql30DMw2eeEEKIEbySNm3VQePl6Ho38Q93X4tn\ndsprYIl87VPXYdM2eRF3NdauXIyHvv860nlphk2NtSVouT/xyvPrBihgEeIBOKiZw8tRLGLb818n\n/ofPPCGEED9i1UHj5eh6N3HNFS0FNa9E5s1qxnMqRdtFIvUhPP7ZG9C+vROJ0TTC9UGsv6fNjqYS\nIoMCFnEl9K4QO/ByFIvUVqUaWIQQQggh+XjFdrbqoPFydL3faY2GuesgKTkUsIgroXeF2IGXo1i8\n3HZiHa8sRAghhLiDSm3+81EAACAASURBVLGdxQj1vsFRbN7dxXmyBBw5GcOmHfIUwnmzmhU/S7uF\nlAsKWMSV0Lsih5MCIZVFpSxECCGE2EOl2M5SJPpbRwcwksxgJDmemy85T9rLxh0dyFyoaZXOZLFx\nWwd+opJSuOWVQ+g4fBbApN3Sebgfj3/2BrRGw2VrL6kMqpxuACFKiHV+Kr3uj7SYPdY7jH2H+rB1\nT7fTTSKElJBKWYgQQgixB6/YzvGRFDbv7sITL+zD5t1diI+mDP29FKE+M9oge53zpDH09EMmk9U8\nzued4zHZ8aTgtd+exhKSByOwiCvxcu2iUsDFbOXBqLvKJhqpxTFMpUhEuZMPIYQQDdxoOyvZMnZF\nGHt5ox43IEZMjWcmsO7OJRbOWChunU+kLZyPEGUoYBFXwvo/cjhJVx5MIatssoIhmM2qez0JIYQQ\nN9rOSiLJ4HBS9hmzTlk3CnZeQoyYEo+NsnBOMzp7BiydgxA9UMAixANwkq48GHVX2cTiKc1jQggh\nxO0oiSRXz51mi1PWjYKdtxAdY4WOsq996jps2iYv4q7G2pWL8ZXv/E52lkh9tT1NJSQPCliEeABO\n0pUHU8gqG0ZdEkII8T6FIgmdsu5AjJhaOKdwd8F5s5rxnErRdpFIfQjf/MKNaN/eicRoGuH6INbf\n02ZbewmRoIBFiAdgPaTKgylklQ0NfOtw3CSEVBJuHPOURBK7nLJu/L1eYu3Kxdi6p9tWO6M1GsZT\nD9xkQ+sIUYcCFiEegPWQvIkV40pMGfufY4PYvLuLBlqFwKhL63DcJIRUEm4c80ohkki48fd6CT12\nxpGTMWzaIU8hnDerMFILoKBIykeV0w0ghBSH9ZC8iWRcHesdxr5Dfdi6p1v334opY6nxCcPnIKSS\nOX02oXlMCCF+wpW2YgmDx135e32GJF4BQDqTxaZtHaqf3fLKIZnN++Xv/A5dx/rL1VRSQTACixAP\nwHo43sSKcSV5KQ/0nEVqfMLUOQipZPoGRzSPCSHET7jRVlSKklpzy0JbInXc+Hu9RO9AAu07L9Sr\nqgti/eo2tEbDss9I4pXacT5Kuxg+s/MgfvrIR+xpMCEXoIBFiAdgPRxvYsW4kkK7N+/uyhl/Rs9B\nSCUj1o1jHTlCiJ9xo62o5MizK/XPjb/XS7Tv7MTgcBIAkIon0b6902L9qsI5lrMuKQUUsAjxAKyH\n403sMK5WfXAuek4N5XZ0WXXzXLubWVZYI0EfvE7WaWyoxWA8OXUc5k6ehBAf40K1QMmRZ1fqH21j\nayRG05rHRhEL9gNAwNIZCVGGAhYhhJQIO4yrXb89OuUhG05i12tHPW2wseiqPnidrLN+dRu38yaE\nVAxunDeUHHlb93Qz9c8FhOuCSOU5ecL1wYLPBKsDsrTBYLW6JLV25WJ89+ed6DkdBzApXv3D3dfa\n12BCLkABixAPwGiMysVvRUr99ntKBa+TdbidNyGkkjhzTr5RxZlB5zeuUHLkMfXPHehx8jx87zJs\n2ibfhVCNSH0IGz55Qymb7Av01B4j2lDAIsQDuNGrRsqD34qU+u33lApeJ0IIIUY4PyJPATufsJYS\nViqY+ucO9Dh55s1qxnPrP1ymFlUG9tceqzwoYBHiARiN4U3siJzzm6fSbzW9SoXf+p0QQkhpGUuO\nax47QSkzCJidUHqOnIxh0w55BNa8Wc2Gz8O+msLu2mOVCAUsQjwAozG8iS2Rcy4symoFv9X0Khk+\n63dCCCGlpaoqoHnsBKXMIGB2gjX0pLJt3NGBzIUaWOlMFhu3deAnKhFZvQMJPPHCGxi7oMdINbCu\nuaKFfZWHntpjRJsqpxtACCnOmlsXYvmimbiitRHLF81kNIZHsCNyTpr0j/UOY9+hPmzd021X8xzB\njTU63Ijf+p0QQkhpWTinWfPYCZTsoPhICpt3d+GJF/Zh8+4uxEdTtp2b6Gfj9v0YHE4iNT6BwXgS\nG7ftL/hMJpPVPM6nfWdnTrwCJv1wz+w8CIB9lc/61W2INtYiVFOFaGMtN5gxASOwCPEArBdgDadC\nl+2InPPbpD88Mq55TCbxW78TQggpLWtXLsbWPd2uSj1XsoPsisZhdoI1xBppVmumKaXCSXIX+2oK\nbjBjHQpYhBDf41Tosh31nvw26UfqazCYFzodqeM0pITf+p0QQkhpcaOzU6me49MvHZB9xqyDhrUi\n3YWYGgdMphEC7CtiL1w5EEJ8j1PRLHbUe/LbpN86PYwT/QnZMSnEb/1OCCGk8lAS1exy0LhRsPMS\nkbpqxMcyU8f11QWf+dqnrsOmbfIi7mqsX92GJ54vrIE1eW72FbEPCliEEN/jVDSLHfWe/DbpU5jR\nh9/6nRBCCAFoB7iFDZ+6Hu3bO3NZAkq1mObNasZzKkXbRVqjYfzwoY/Y3UxCCqCARQjxPU4ZS6z3\nVAiFGUK8Bbc/J8QbeOVZtcsO8MrvdSusxUS8CgUsQojvcUo0Yb0nYhYa5sQtcPtzQryBG59VpbkM\nWdgyv7nx9/qNIydj2LRDnkI4b5b67pa9Awm077wQ1VUXxPrVbWiNhmnTEFvhaooQD8CB35uw3hMx\nCw1z4ha4IyYh3sDpZ1XJVt3yyiF0HD4LYHIuG89MoKa6ypb5zenf63XUxKZ8Nu7oQCYzuZdgOpPF\nxm0d+IlKSmHvQAIbfvJG7jgVT2Ljtv14dt0Kxftg3Z1LSvTLiN+hgEWIB+Bi1puwzgMxCw1z4ha4\nIyYh3sDpZ1XJVn3neEz2mXeOxzAzKm+X2fnN6d/rdTZu34/zicmK6/liUz6SeKV2nE/7zs6C16Tz\nK90HhJiFAhYhHoCLWW/Cek/ELDTMiVugEE+IN3D6WVW2VUXBI2vb/Ob07/U6krikdmyUxKjW3xfe\nB4SYhQIWIR6Ai1lnYOomcQoa5tbh82sPFOIJ8QZOP6tKtmpzJITOnoHcawvnNNs2vzn9e4mccF0Q\nqby6rwAQqa8GMNnv4n1AiFkoYBHiAbiYNYfVBSxTN4lj0DlpGT6/hBBSPtRs1a17Cu0wjsXOE6mr\nRnwsM3V8QWzK52ufug6btsmLuKuxfnUbnvzZm4iPTp7zonAQj9x7HQBg7crFBfcBIWahgEWIB+Bk\nbw6rC9gz5xLy48GEyicJsReKL9Zh6jUhhJQPNVuVc5c72fCp69G+/UIR9/og1t/TVvCZebOa8ZxK\n0XaR1mgY3/3KzYrvcR1THEaN64cCFiHEt1hdwA6PjGseE1IqKL5Yh6nXhJBKwosLYCtt9uLvdROt\n0TCeeuAmp5tBLkDHpX4oYPkMDubeRavv2K/mEBewfYOj2Ly7S/f1a6itwmBcflxu2PeVSTRSi2OY\nunejjbUOtsab3LJ8NjoP9+dSH265cbbTTSKEkJLhxQWwlTZ78fd6jSMnY9i0Q55COG8W61eVAmZ9\n6IcCls/Y8sohdBw+C2ByMB/PTGDdnUscbhXRg9ZEzEnaHFKO/VtHBzCSzGAkOZ67jnqu30hyQvO4\nHLDvK5OsUAQrm2VRLKP8YFcX0he2/E5nsvjBv3Xh6b/7gMOtIoSQ0uDFyF0rbfbi73UTvQMJtO+8\nkEJYF8T61W1ojYZln5HEK2ByHt20rUM1pbB3IIEntxXWwGqNhnV9V6XDrA/9lD+cgJSUd47HNI+J\ne9FS3jlJm+TCmn88I1/8671+kXq5xh+ps6b5x0dS2Ly7C0+8sA+bd3chPpoq+jfs+8okFk9pHpPi\nDCVSmseEEOInxDRpt6ZN59tCQ8LcZqTNXvm9bmXj9v0YHE4iNT6BwXgSG7ftL/hMWrCfxeN82nd2\n5sQrADifSOfO2b6zU/Zd7ds7bfoV/sHuNYef4ZXxHeLAQq+9Vzg/kpYfJ6aOWcvFHPnRS/novX6t\n08M40Z+QHdvVHr3RVOz7yoT9bp0qABnhmBBC/IpXdqwWbbNoYy2awiHDbfbK73Ur+esMpWOjJEYL\n/146p/ie0mclKrV0ht1rDj9DActnLJzTjM6eAdmx26nUgUpkLDmuesxJ2hxitFKopgpL58/Qff3s\nvu5moqnY95UJ+906iy9vRtexmOyYEEL8ild2ehNtn6ZwCI99ernh83jl91YK4bogUvGkrvfC9UHV\n81Rq6QzaffqhgOUz1q5cjK17uj118ysNVGtuWVhxolagKqB67JdJutxipVgI++q50wxdx/hIGj2n\nhpAYTWMonkJ8LG2pvWaiavzS98QY7HfrfP72azw3HxJCiN9hhLE7iNRVIz42Faccqa8u+EywOiBL\nGwxWBwo+I7F+dRs2PPeG/DsunHP96ja0b79QA6s+iPX3tKmep1JLZ9Du0w8FLJ/hxZtfaaCqRPU9\nWF2F0byEl2CN/xJeyt2vVgthSzn7AJC6kLNvZcvhVR+cmxPEwvVBrLp5rulzEX/DyFTreHE+JIQQ\nv5MfadIcCWE8M4EnXtjHua7MbPjU9UVFpYfvXYZN2+S7EKrRGg3jyS/cqHjO1mhYt/1MgZMUgwIW\ncRylgaoS1femcEhWB6upYWoC98tittz9arUQdlzI0RePjbLrt0enBLHhJHa9drToAtsvfU+MUYki\nPiGEEPN4xV7Idy5s3t1leK7zyu90O3pEpXmzmlV3HTR7zmIwlY4UgwIWcRylgWrrnu6KU9+1ivf5\nZTFbbq+K5e8TI7YMRnCJmBHw/NL3xBiVKOITQggxjxftBTvsoreOnsPVc6dRyPIJjJ4mxaCARRxH\naaCqRPVd6zf7ZTFb7n61+n0tTXU4fW5UdmwFM4KaX/qeGIMh9IQQQozgRnuhWLSUHXbRSHI8J2hR\n+NBP70AC7TsvpPvVBbF+dRtao/Kd746cjGHTDnkK4bxZyhui9A4k8OS2NxEfnSyHclE4iEfuvQ6t\n0bCu7yJELxSwiCupRPVd6zf7ZTFb7n61+n2XzmyUCViXzmy01B4zNbD80vdGYHpAZYr4hBBCzONG\ne6HYRk3NkRCWLZiBweGk7rlO/J0SbhDsvISeOq8bd3Qgc6GIezqTxcZtHfiJSkph+87OnHgFAOcT\naWzcth/Prlthe01ZUtlQwCLEJWgt2rmYdQa7r7uZGliV2PdeTIOwm0oU8QkhhJjHjfZCsY2aAGD5\nopl47NPLdZ9T+l1vHR3ASHJKMHGDYOclEkJd18HhJHoHE7LIqExGXjpDPNY6HzApYim9p/RZCTox\nSTEoYBHiErQW7VzMOoPd191MeH8l9r0b0yAIIYQQV2OtTGdJKMVGTZJdFB9NYeueblcJdl4iXBdE\nKp6UvWYlMkrpfGrvheuDquehE5MUgwIWIS6Bi3b/48bwfjfC60QPJCGEEGO4ceFfyo2aKtHBZyfr\nV7dhw3NvyF7Tiowyc75IfXXuvfbtnbkSGuvvaVM9j13rIbfaUW5tl5eggEWIS+Ci3f+4MbzfjfA6\nuXMhQgghxL240RHKjZrcS2s0jGikFoMakVFf+9R12LRNXsRd63xPfuFGRaGqNRrWHdll13rIrXaU\nW9vlJShgEeISOKFXACbC+yvRU0OvqjsXIoQQQtyLVxyhnOPdQ7HIqHmzmvGcStF2JYwIVWrYtR5y\nqx3l1nZ5CQpYxHG4teokWhN6JYoYfsSM12XLK4fQcfhs7m/GMxNYd+eS0jaUOI5XFiKEEELcQaU5\nQmkbW8cOwUlCqz+M9JVdAqdb7Si3tstLUMAijsOtVYvDcFN/YMbr8s7xmOYx8SeVthAhhBBiDa9E\nNtklPNE2Lj2vdZzAi3sO547vu20BViyZo/hZ0eHaebgfj3/2BrRGw444Y91qR7m1XV6CAhZxHCNb\nq1YqDDf1B9FILY5hyusSbazV8Vdi3qELtxki9sNuJoQQ4kPsEp5oG5eefPEKALa8fFhVwBIdrOlM\nFhu37cez61Y44ox1q6Dr1nZ5CQpYxHGMbK3qZ7Q8Ugw39QdZQZXIZourFAvnNKOzZ0B2TPwPPcuE\nEEL8iF3CE21j69hbxqXQpj2fSKu8p27/MjWUFIMCFnEcI1ur+hmtBSvDTb2F2uQbi6dknxOPlbjr\nI/Px7pl47vm46y/ml6rZFYebjSR6lgkhhPgRu4Qn2sbWsbOMi+hw1XpPyxlLBx4pBgUs4jh2FhD0\nMloLVoabegu1ydeM0bbrt0enjIvhJHa9dpT3gk242UiiZ5kQQogR3OyUyccu4Ym2sXWKlXG577YF\n2PKyvAaWGmtXLsZXvvM7WWxVpL46997WPd26+pwOPFIMCliEuAQuWP2DONke6DmLzbu7sOrmubn3\n9RptnMhLh5uvLT3LhBBCjOCVXYvtEp68Iti5mWJlXFYsmaNa80okUh/CN79wo2JWjZE+53qIFIMC\nFiEugQvWQrxonMRHUhgSUgNT4xPYd6gP6fEMgjXVhs5nrvA70YObjSR6lgkhhBih0nYtdnMUtVew\ns4xLfCSFXa8dRVM4hPmXNslsdiP2PNdDpBgUsAhxCVoLVi8KOXbgReNk695uDOZ5s/LpPhHDSDID\nQP/vMVP4nejDzUZSpT7zhBBCzFJZuxafOZeQHw8mVD5J1LCzjItos3ce7sfjn70BrdGwIXueDjxS\nDApYhHgALwo5duDmFC81RINKTkB2pOf3mCn8TvThZiOpUp95Qggh5vDKrsV2OWiGR8Y1j4l1Xus4\ngRf3yGtgqaUUivZvOpPNFYU/fVb+nnhMiBEoYBHiAbwo5NiBm1O81BANqGB1AJe2RNDSXI+x1DgO\n/ulc7j096YBevAbEOpX6zBNCCDGHkULZTmKXgyZSXyOLeI/UcVlrlGJiYr54BQBbXj6sKmApCYjx\nkcmi8H2DI7LXxWNCjMAnnRAPUKkihptTvNQQDarWaQ147NPLAQDf/cUB2Wf1pAN68RoQ67D2GSGE\nECO4Oao4H9Eh89bRATzxwj7D0Vit08M40Z+QHRNj2BntLdq/ADCemQBQaO9q2b8soUCKQQGLEJeg\nNWBXqojhFWMsHy2D6tz5Mdlnzw3Lj5Xw4jXwCkdOxrBpRwfSmSyC1QE8fO8yzJvljpQL1j4jhBDi\nR0Sn7Egyg2O9w7oFFMle7h1IINpYi8aGGlwcDVeMbWwndtYRE+1fYKpwRmNDrUzcagyrO+UqtYQC\nhTv9UMAixCVoDdgUMbzDqg/ORc+podyOLqtunpt7j/Ua3IUkXgGTtRo2bevAc+s/7HCrJmHtM0II\nIX4k3ynbNziKkeSULaQnXT7fXgaA+Zc20UY2STG79L7bFmDLy/IaWGqsuXUhOg/35+wqAGi6ED1u\nZLfDSi2hUKnCnRkoYBHiEip1wHYrZj0hu357FIPDk16m1HASu147midEGq/XQI9M6cg3spSOnaRS\n04YJIYT4m3yn7ObdXTIxSs9cR3vZPorZpSuWzFGteVV4rhAe/+wNikKVkd0OK9X+4X2tHwpYhLgE\nrQGbIkb5MesJ0ZqAZjTVy8KrZ+iYlOmRKR3B6oBMtApWBzQ+XV4qNW2YEEJI5WBmrqtUgaMU2F1H\nzIhQpUal2j+8r/VDAYsQl6A1YFPEKD9mPSFaE5CZukb0yJSOh+9dhk3b5DWw3ALThgkhhPgdM3Nd\npQocpcDOaxkfSeHH/9GFt9+NYQJAU0MID9+7DK1RY6KY3faPV4IAeF/rhwIWIS5Ba8CmiGENM5OX\nWU9I/gTUHAlhPDOR211HLNqup64RPTKlY96sZtfUvCKEEEJIceIj6Vyt0aF4CvGxtCsFCU9QxI/6\nWscJvLhHXgNLLaVwyyuH0HUsljuOJVLYuG0/nl23wlERyStBAHRc6ocCFiEuQWtwp4hhDTOTl1lP\niFpth2O9w4hG5Luu6OlHemQIIYQQQiZp39k5VWs0nkT79k7LaWuVSjH7OF+8AoAtLx9WFbDeOR4r\neO18Iq3re0oJgwD8BwUsQlyC1uBOEcMaZrYJNusJyRci+wblk2SkvgbzZzcZ6kd6ZAghhBDiR3oH\nEmjfeaHod10Q61e3FU05S4ymNY+JfuwVd9TDuYzY4XZHa3klCMArqY5ugAIWIS5BaxKpVBHDrsG8\n2DbBdiJu75zPjOb6iuxHQgghhJQWLy6AzURTheuCSOXtnBeuD5a0jX7GTnFn4ZxmdPYMyF6L1FcD\nMGaH2x2t5bYgALXn1Cupjm6AAhYhLsErHoJyYtdgXmybYDsRvUz5pNPj2Ly7y1PGpd140cAmhBBC\n3I4XF8B6o6nybYdLZ9QjiyxGxsYRrg9i/T1t5WiqL+2XYuLOfbctwJaX5TWw1Fi7cjF+/Mu8Iu7h\nEB5ePbk5jhE73K6oMLG/Hvz4Ulf0l9pzylRH/VDAIsQluM1D4AbsGszt3iZYCy2v0pHTwxhNZQBM\nTlrjmQmsu3NJydriRrxoYBNCCCFux4sLYL3RVGJ0+/JFM7HmloXYurcbP/7l/5RFUPKj/VIsw2PF\nkjmqNa+UzvXg3dcpvmfEDrfLoe/W/lJ7ThnIoB8KWIS4BK1JxI9eHz1EI7U4hqnBPNpYq/FpdcyI\ng2avuehlyic1PiE7Vip4aVc73IoXDWwn8Fu/E0IIKS1eXACvX92G9u0XamBpRFMp2Q7lFihov5jH\niB1ul0Pfrf2l9pwykEE/FLCIrZgpxkiK41YvQqnJCgUhs9ki+/2qYKaGmNlrLnqZoo21aAqH0NJc\nj4NHziIzMfUb9Pwev/W9Fw1sJ/BbvxNCCCktXlkAiw6ax9cuL+qgUbIdzGzQY4VKtF+OnIxh044O\npDNZVAeAhZc1YzSZUXSsaTne4iNp9JwaQmI0jaF4CvGxtGqf21X31639pfacVmq9YzNQwCK2wq1t\nS4NbvQil5tz5Mfnx8JjKJ+3H7DXPn5iaIyEEAoHcM5EWIrBS6UzJ2uFWvGJgO43f+p0QQkhp8coC\n2IyDRsl2+PpP98k+U8oNetTa4Hck8QoAMlng7XcnMweU+m3LK4fQcfhs7v3Ow/14/LM3oDUadmR9\n6Nb+8spz6mYoYBFb4da25tHyXLjVi1Bq7No90Ew6ltlrnj8xbd7dVWCkyQgUP5/f+p4Ttz781u+E\nEEIIYM5Bo2Q7lHODHrU2+B1JvFJC7DexLEY6k80JVU6sDyuxvyoFCljEVri1rXm0PFJu9SKUGruM\nE7u8fUYpZpRVBYorWJXa95UO+50QQogfER00Q4kUnnhhn+F6j+XcoMevWKm3WehYKxS7JKHK6fUh\nS9z4CwpYxFb0FmMkhWh5pPziRTA6gcxoqpcZJzNMRqHY5e0ziliEXqSlqa4s7SAexFy5N0IIIcTV\n5DtohhIpDA4nMTicNFzvcdUH5+bqKoXrg1h189yStdmviGl/enbHvqK1UdGxtnBOMzp7BmSvSUKV\n0+tDlrjxFxSwiK20RsMcEExSCSlDRicQu4q4m722VneCE9svcunMRt3nIpUFi7gTQgjxI/mOuSde\n2JezCwFj9R53/fbolE05nMSu145ynjSImPYnHgcg96cFADz26eWK51q7cjF+/MsuvP1uDBMAmsKh\nnFDl9PrQCyVuuPu0fihgEeIStFKG/DKoGZ1AYvGU5rFezKZjWRUR1NobqqnC0vkzKjItzC/3cqlh\nEXdCCCF+R4xUjzbW6v5bzpN2IDpa5cf/cPe1eGbnQWQxKV79w93Xqp4pUh/Cg3dfZ3sL7cDpFEY9\n0HGpHwpYhLgErVQxvwxqRicQ26LSTKZjWTWOxPZLLJ0/w5P9Zwd+uZdLTSVEZJYa1rwghBB3YyXS\nnvOkdcS0v4VzmmXvZzX2TvKSQ9LpFEY9UJDVjyMC1tjYGP76r/8aX/rSl/C+970PDz/8MDKZDFpa\nWtDe3o5QKIT/+I//wIsvvoiqqircdddd+Nu//Vuk02k88sgjOH36NKqrq/Gtb30Lc+bMwaFDh/CN\nb3wDAHDVVVfh8ccfd+JnEVIy/DKoGZ1A7CpkbVY0sWocSe091TeM/qExIBBAxEKdBi8ZC2r45V4u\nNSzibh3WvCCEEHdjJdKeNbCss3blYmzd061qazz7i4M5iTEL4JmdB/HTRz4CQNm2XrVirqLjyGn7\n1ekURj1QkNWPIwLW5s2b0dTUBAD47ne/i3vuuQd/9Vd/haeffhq/+MUvcMcdd+AHP/gBfvGLXyAY\nDOJjH/sY/vIv/xKvvvoqLrroIjz11FP43e9+h6eeegrPPvssvvnNb2LDhg1YsmQJHnroIbz22mu4\n+eabnfhpxCacHujchl8GNaMTiF0FzM2KJpZFhAuzfiyRurAVcRaDFuo0+CF6yS/3cqlh8X7reKHm\nBSGEVDJWbALWwFKmdyCBhzf/HucTqaLRx8VsDa0EQ9GWPtU3jK/95I3cZ/IdR0bs10pdA9JxqZ+y\nC1hHjhxBT08PPvShDwEA3njjjVzE1Ic//GE8//zzmDt3Lq699lo0Nk4WOL7uuuuwf/9+/OEPf8Ad\nd9wBAHj/+9+PDRs2IJVK4dSpU1iyZEnuHH/4wx8oYHkcPyzU7YSDmjXM1liwKiLk38f5mI068kP0\nEu9lUi68UPOCEEIqjXyBojkSwrIFMzA4nDRsE/jBJioFRqKPrYhFovjYPzRWIHhJjiMjfVWpa0A6\nLvVTdgHrn/7pn/CP//iP2L17NwBgdHQUodDkgzJ9+nT09/fj7NmzmDZtWu5vpk2bVvB6VVUVAoEA\nzp49i4suuij3WekcxNtU4qSkNYlU6qBmlxfGrt0MjaJ235qNOvJD9FKl3suk/Hih5gUhhFQaonNv\n+aKZqjvbaeEHm6gUGIk+3vLKIXQcPgtgUiwaz0xg3Z1LdH2P6JDs7DkLMWZLchwZ6atSrAErNarL\nr5RVwNq9ezfa2towZ84cxffVFpVGXte7MI1GG1BTU634XksLt7Z3mtkXN8oGutkXN+rul6FECj/6\ntwM4c24EF09rwP13LsVFYfcPUv/62p9kHofa2hp89ZPGJ3Q/8fzP9tlyTRLJTMFxOZ5z8T4O19dg\n2cKZpu/Jv7/nz7HZwL2t51ngeEecoBz3XUtLI372jY/aek6vzi9kEo53xAn8ft8ZHRdjiVTBsZFr\nJH1f7+AIQjVVf//wuwAAIABJREFUAICLwiF85vZr0dISMfcjfMRF4RDODo3JjtWub/fJWMFx/mdD\nNVVIjU/IjqX3WwA89rn35d6774k9su8FgL//xDK0tDQasl+trAHVsGs9QYpTjvGurALWb37zG5w4\ncQK/+c1v0Nvbi1AohIaGBoyNjaGurg5nzpzBzJkzMXPmTJw9ezb3d319fWhra8PMmTPR39+PRYsW\nIZ1OI5vNoqWlBbHY1MMnnaMYg4Mjiq+3tDSiv79w1zBSXu760JVIJsdzSvldH7pSd79s3t2VG6QO\nn4ghmRx3fcRHS0sjTp6R/76TZ4Yr/l6065o0C5Nkczik6zxWPTbifSz9fXIkif6RZPETKLD2rxbl\n/l/sPMWeBSfGO3rB7MOr19LL86wX5xcyiZfvO+JdKuG+0xoXleYp0SY7dnoId371P3XvFpv/fRJn\nh8bw018e5HgM4MG7l+LpnQcma2DVB/Hg3UtV78HsRLbgOP+z61e3YdO2DqQzWQSrA1i/uk31XA/e\nvRRfe+4NWQzWszs6cumLeu1XK2vAfPLvvb5BeRQX11ilQRzvSiVmlVXAevbZZ3P//973vodLL70U\nHR0d2LNnD26//Xbs3bsXK1aswNKlS/Hoo4/i/PnzqK6uxv79+7FhwwbE43H8+te/xooVK/Dqq6/i\nxhtvRDAYxJVXXok333wT119/Pfbu3Ys1a9aU82eRPMwsqJT+piCJ2gBeTT/UCq/16kLVKnaFh5ut\nu2Q1D9/pdDk3PguVWtugFPBalh83PlOEEAI4ZytqjYtK81S+TXaqP57b5EbvbrFq4y7H40lao2Fs\neexWXQLNwjnN6OwZkB3nM29WM55b/2HFv1W634JCxJaZzVPssp3V6tACTDf1Oo7sQpjPunXr8NWv\nfhUvvfQSLrnkEtxxxx0IBoN46KGH8JnPfAaBQAAPPPAAGhsbcdttt+H3v/89PvGJTyAUCmHjxo0A\ngA0bNuCxxx7DxMQEli5dive///0O/6rKxcyCSulvAJhemImix6n+OL6x5Q1cHA27WvjRElkqdaFq\nV8Fvs5Oh1xerbqwP4fVr6iZ4LcuPG58pQggBnLMVtcZFxXkqz0k9LkQA6RE8xO9T+l6ij7UrF2Pr\nnm5TdrbS/eamzVPUbKJoYy03EPI4jglY69aty/1/y5YtBe9/9KMfxUc/Kq9dUV1djW9961sFn50/\nfz62b99ufyOJYcwsqPT8jZGF2ZpbF6Ln1FBuB450JovjZxI4fiYBwL3Cj5bIUqkLVacjmJojIc1j\nt+PGHf8oANgHr2X5ceMzVWoqNQKYEK/hlK2oNS4qzVNakTF6BA/p/Kf6htE/NAYEAojUB7Hq5rlW\nfkZFUszOPnIyhk07plIIH753GebNmozSOnMuIfvsmcEE7rttIZ7514PIAggAuG+lc3OkuAO5RFM4\nxDnM4zgegUX8hZkFldrfmF2YRepDaAqHcgJWPl4VfrhQdYZAIKB57HacFgCVqEQBoFTwWpYfNz5T\npaZSI4AJ8Rrigj3aWFuW79UaF5XmqadfOqD42WB1AF/6m6sV31MS0rfu6cbpc6MAshgcTmLXa0c5\nNtnMxh0dyGQmo+TSmSw2buvATy6kFA6PjMs+G4un8L1/68oF2GUBbPlVN556oKWMLZ5C3IFcgmso\n70MBi9iKmQWV1t+YWZjFR1IYiqcU3yvXZG43XKg6gyiCKomipaZ3IIH2nZ1IjKZ1Fzh1M5UoAJQK\nXktSDio1ApgQryEu2PXuzF5KlOYptRTAdCaLvW+cxP13NBe8pySkc2wqPZJ4pXQcqa/BYF66YCqV\nuVDPbIr4iPEaWHYRE9aCoZoqLJ0/g2soH0ABi9iKmQWV2t+YXZht3dstG1DzccNkroZWmgYXqs5g\nNvLNzpSb9p2dOeEsFU/i6//8R1zaEmEqDyGkLDACmBBvIC7YxWO3kO+U7RscxUhyKpKnPzaqaEMp\niVUcm6yj5iSV+kCL1ulhnOifSiMUxSsAGM9MFLxWDLtsaPH+CNcH0R8bxdY93bSfPQ4FLOI7tDww\neidzJ2p+ME3DfTi1e2E+YkHTdCaLY73Dnr1HWE+HEG/BCGBCvIFTgo7ReT3fKbt5d5esHpZYI0v6\nPUq/jWOTdUQnqbQLpFadMgnx+ncdHcBoMiP7jJnCG3bZ0PntG0qkMDicxOBw0rP2M5mCAhZxHLsX\ntGqhydJ7etAzeNrdboZCuxCTAXtKhS3NIu7oko8X7xEKtfZBMZCUA0YAE+INnBJ0rMzrtyyfjc7D\n/bki4bfcOBv/suew7DP9sVE8+PGluf/nfpt7kyo8g+gklY712Jfi3PDdXxxAZ8+A7DNNJkq32LUe\nym/fEy/sk5UB8aL9TKaggEUcx+4Fbf4E3hwJIRAIYHA4aWgy1zN42t1uLc8ZF6rOYLaPxcKW4rER\n1q9uQ/v2yfDubDYrC9H2Yrg8hVr7oBhICCFEwimx2cq8/sPdb+XsmnQmix/++1uYf2lTgT2s9Nu+\n92//HzoOnwUwOQeOZyaw7s4lZn9GRSI6SaVdILWCAdRYu3IxfvzLLrz9bgwTmNztb/09bYbbVIpI\nQqab+gsKWMRxbF/Q5nlkgjXVpsQePQOdnVE2gLbnjAtVZzDbx2Jhy0id+aG2NRrGUw/cBACIj6aw\ndU+3bu+qG4VPPc+WG9vtRigGEkIIcRor4oBSBJDeSLJ3jsc0j+3Gj7ZJvpM0XB/MCU7SNRfTCIPV\nU0mBStfjwbuvs9ymUkQSMt3UX1DA8iFeG2DtVsXtEHv0DHR2RtkA2p4zLlSd4XxCXjPtvM4aamJh\ny9bp5ncNtPI8u1H41PNsubHd5ebIyRg27ejIpVU8fO8yzJsl35mJHkVCCCFOY0UcUIoA0h9JJuYQ\nljan0I+2Sb6TNB+pD255L4ZN2+S2iITS9Vi1Yq7lnbPtjiT02rqYFIcClg/x2gBrtypuh9ijZ/C0\nM8qmGFyoOsNYalzzWA0772krz7MbhU89z5Yb211uJPEKmEyr2LStA8+t/7DsM/QoEkIIcRorgsN9\nty3EM/96EFlMFvy+b6X+eWzhnGZZzaWFc5o1Pm2dSrRNTvYOy2yR0/3DOWeaUpbCxu37cT4xGVWX\niiexcdt+PLtuRXkbLeC1dTEpDgUsnxEfSeGto+dkr7l9gLVbaY9GanEMU2JPLJ7EEy/ss111tzPK\nphhcqDpDVVU1gHHhuDh23tNWDCavCp9ebbediNtRK21PzeLahBBCvEZ+RMyp/ngubioLYMuvuvHU\nAy26zrN25WJDZRWs4kfbRC06SXpdTCHc8vJhrFgyB0Bh5knfuQTG5BmhOTHLjjaZpRKFR79DActn\nbN3bjZGkfEBRG2D9GlKZFUKIY/EUYvGU7aq73aKSVn9woeoM8y69CAf/dE52XG5Eg2konkJ8NKXr\nWfWq8OnVdhNCCCFEGyVhREKsiaWFaBvHR1LYvLurZOsaP9omW145pFgIP/91NcRMFFG8MovViClx\nPSUGNhixo4k7oYDlM0RVuaG2WnWALUVIpRtEsZhGnSK9qrue32G3qMQQV/dRXRXQPC4Ha25diJ5T\nQ7ntfwfjSWzd063r3vCq8OnVdhNnccP8QwghRBstW1zaBc8Mpbaj/WibqBXC11MQX8xEUSJSry9z\nIR+rEVPifdA2fzqijbWm7GjiTihg+QwxWuPqudNVDfhShFS6QYTR2vpVb7ivE7/DrSGulbwoFMVQ\nLXFUCyvXMFIfQlM4lJt4AffcG6R0RCO1Ms9mtLHWwdZ4AzfMP4QQQrQR7fRgdQCBQEC2C54Z3GpH\nuxu1QvjKBfHvu21B7v9iRNqbh/oK/mrDJ6833CKrqZpiv8fiKTTW18jsaKs7xxNnoYDlM4yEt4oh\nlXYskNwweeRfg+ZICIFAAIPDSUPhvk78Dq0B20kRqZIXhXbVO7B6Df1Yd0GLShZNJdS2tibquGH+\nIYQQoo3SWsWOOb7SbCU7UCuEL77eNn86vvyxpfI/FtSqu/9iLnb876O54/tuW2B4B0LAeqqm0n3Q\nc3JI9hmrO8cTZ6GA5TOMhLeKtaKyWevbz7ph8rAjxNeJ36E1YDspIrl5UVhqocOuegdWr6HZdnhV\nCKpk0VQiUhvE/Eubcn0XqTOfVlEpuGH+IYQQok2pUvFKXaPKqzaVFmqF8PUUyBdttc7D8jIbu//P\n8VzBdyNYvT+U7oP27R1l2zmelB72XgVjV3pUPn4pcOjE79AasJ0Ukdy8KHR7vQPJ2DlzbkT2utFo\nR6kd0vmefumALuPJq0KQm0XTcuHVvnMSv8w/hBBCjFPqGlV+mpd7BxJo33khyrsuiPWr22TRUvnX\n8mBPP77ynd8hCyAA4B/uvhbXXNFSYJuJuyUbKchvJ0r3QTl3jielhwJWBVMKYcIvBQ7d9jucFJHc\nvCgstdBh1dumttOO2WhHo8aTV4UgN4um5cKrfeckbhu3CSGE+Ac/zcvtOztzNaFS8ST+8Sd/xHUL\nWwrs3Nc6TuDFPYdzx1kAz+w8iJ8+8hHFWmb5IlZ6fAK9gwlTaYR24+a1DDEOBawKhg+zd3Cyr9y8\nKCyl0BEfSeHrW/blJngz3jY14+bc8Jjhtmzd240DPfItjYsZT14Vgjg2ebfvCCGEEC2sOgedSuXz\n07wsRkdlJrI5B2m+nZsvXklIEpVoq8WGR3H41LDscxu37cez61YYalsp+tdNaxk/pqKWGwpYFYyb\nHma34cTgovWdldpXxfqhlELH1r3dsh1LpO8xgtqOmEaLR6pFchUznrwqBFXq/Z6PV/uOEEII0cJq\nKp5TqXx+mpfDdUGk4smC16Xd+ST7Wwmp0pVoq/3dM78t+Oz5xJRQpmXT//Gt9/Cj/3y74O/N9K/b\nBSI/paI6BQUs4jhuHGicGFw4oBVS7JqUUuhQEquMetsk46ajuw/jE1OvGy0eKbYlVFOFpfNnFDWe\nKAR5GOt7ahBCCCGuw2oqnlOpfH6yqaSdjkVHreRgVXOcApM1sJQYS2o7Z7VseiXxSsJo/7p9PeWn\nVFSnqHK6AYRIA82x3mHsO9SHrXuUFf9y4sTgwgGtEKeL1+cTbaw17G2TjJ1rr5whe32GQSFMbMvS\n+TNw/x3XOC70ktLhxnGREEIIsYpo0xh1Dlr9ewK0RsN46oGbMKdFXp9KcrCq2dv33bYA11zRovje\nhMJrkfrq3P/PnEvI3pOivYphtH/dvp6KRuQbORnd2IkwAovYjJloKjcONE7kufspt94u3Fa83qxg\nlBXCaYwWcc9vS3MkhPHMBJ54YZ9rIhaJ/bhxXCSEEOJe3JjRoLTbnVWbxqlUPjdeX6uo7c4n2t/L\nF80siGISr4cSc2c1IT6aQqQ+VFA+o1g5jStaG031r9vXU1bXBIQCFrEZM2GbbhxonJgc/ZRbbxdO\nF69fc8vC3OS8dU+3aWMlFk9pHutpy/13XGO4sLxXjS2vtttOopFaHMPUuEgPHSGEEC3cmDol7nbX\nvr0TTz1wU65dm3d3GW6zU6l8bry+VlGzs/XY30rXQ+Tgn85h657uC1kDNRjMq7uVX07j/lWLsXnX\n27Lj5VfNsvU3uQWrawJCAYvYjJmoATcONE5MjlrfWakLeqfrDdhlrNgl0hotLO9VY8ur7bYTPR66\nSh0XiHF4rxDif9wYuSvudice29nmUo9zbry+ZhGv1YMfXyq7VpL9/VrHCby453DOJmuorcajn74e\nrdFwQUrgtEg1BuOZghKeUqqgWrQXACy/ahaWP2JOsBJxeu1QDDcGbngNCljEVsw8lKUcaPxitHNB\nr0wp+zc+kkLXnwZkr+nN1xdZ9cG56Dk1NBlCXx/EqpvnmjqP0cLyXjW2vNpuO9HjoeO4QPTCe4UQ\n/+PGhbG42124Pih7385o41KPc268vmbZ8sohdBw+C2DyWnUdHcA1c6cX2NEv7jks+7uRZAYbt+3H\ns+tWFKQApjJAc2OtamF4NwYsOAGvg3UoYBFbMfNQKokQyMIWYcJLRruWGOPUgl6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vP+el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\nYII=\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f21b292cb50>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "HnV6nhGsoW8p",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# Data for patients registered on Septic Shock Diag with almost near of 3 days"
      ]
    },
    {
      "metadata": {
        "id": "esfC95WJp4QW",
        "colab_type": "code",
        "outputId": "1d631483-3539-434c-a4ba-7f748a6dacc4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1828
        }
      },
      "cell_type": "code",
      "source": [
        "consulta"
      ],
      "execution_count": 112,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>admissionheight</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>172.70</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>177.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>162.60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>173.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>165.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>165.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>160.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>170.20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>180.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>176.53</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>160.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>175.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>162.60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>157.50</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>157.50</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>172.70</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>162.60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>163.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>178.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>152.40</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>170.20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>163.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>177.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>175.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>160.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>157.50</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>152.40</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>167.60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>168.90</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>188.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200829</th>\n",
              "      <td>154.90</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200830</th>\n",
              "      <td>172.70</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200831</th>\n",
              "      <td>175.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200832</th>\n",
              "      <td>160.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200833</th>\n",
              "      <td>185.50</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200834</th>\n",
              "      <td>172.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200835</th>\n",
              "      <td>172.70</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200836</th>\n",
              "      <td>170.20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200837</th>\n",
              "      <td>162.60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200838</th>\n",
              "      <td>177.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200839</th>\n",
              "      <td>167.60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200840</th>\n",
              "      <td>170.20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200841</th>\n",
              "      <td>188.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200842</th>\n",
              "      <td>177.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200843</th>\n",
              "      <td>170.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200844</th>\n",
              "      <td>170.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200845</th>\n",
              "      <td>182.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200846</th>\n",
              "      <td>177.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200847</th>\n",
              "      <td>152.40</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200848</th>\n",
              "      <td>152.40</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200849</th>\n",
              "      <td>162.60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200850</th>\n",
              "      <td>170.20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200851</th>\n",
              "      <td>188.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200852</th>\n",
              "      <td>154.90</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200853</th>\n",
              "      <td>180.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200854</th>\n",
              "      <td>149.90</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200855</th>\n",
              "      <td>162.60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200856</th>\n",
              "      <td>190.50</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200857</th>\n",
              "      <td>175.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200858</th>\n",
              "      <td>172.70</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>200859 rows × 1 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "        admissionheight\n",
              "0                172.70\n",
              "1                177.80\n",
              "2                162.60\n",
              "3                173.00\n",
              "4                165.10\n",
              "5                165.10\n",
              "6                160.00\n",
              "7                170.20\n",
              "8                180.30\n",
              "9                176.53\n",
              "10               160.00\n",
              "11               175.30\n",
              "12               162.60\n",
              "13               157.50\n",
              "14               157.50\n",
              "15               172.70\n",
              "16               162.60\n",
              "17               163.00\n",
              "18               178.00\n",
              "19               152.40\n",
              "20               170.20\n",
              "21               163.80\n",
              "22               177.80\n",
              "23               175.30\n",
              "24               160.00\n",
              "25               157.50\n",
              "26               152.40\n",
              "27               167.60\n",
              "28               168.90\n",
              "29               188.00\n",
              "...                 ...\n",
              "200829           154.90\n",
              "200830           172.70\n",
              "200831           175.30\n",
              "200832           160.00\n",
              "200833           185.50\n",
              "200834           172.00\n",
              "200835           172.70\n",
              "200836           170.20\n",
              "200837           162.60\n",
              "200838           177.80\n",
              "200839           167.60\n",
              "200840           170.20\n",
              "200841           188.00\n",
              "200842           177.80\n",
              "200843           170.00\n",
              "200844           170.00\n",
              "200845           182.00\n",
              "200846           177.80\n",
              "200847           152.40\n",
              "200848           152.40\n",
              "200849           162.60\n",
              "200850           170.20\n",
              "200851           188.00\n",
              "200852           154.90\n",
              "200853           180.30\n",
              "200854           149.90\n",
              "200855           162.60\n",
              "200856           190.50\n",
              "200857           175.30\n",
              "200858           172.70\n",
              "\n",
              "[200859 rows x 1 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 112
        }
      ]
    },
    {
      "metadata": {
        "id": "iJHygPumnjVG",
        "colab_type": "code",
        "outputId": "38796cea-403e-41ad-e5b1-2817736c5b2a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 948
        }
      },
      "cell_type": "code",
      "source": [
        "# Scatter Plot de correlacion entre eje x, eje y, eliminados pacientes de los que tenemos datos de tres dias \n",
        "consulta.plot(figsize = [20,16], kind='scatter',x='patientunitstayid',y='diagnosisoffset' )"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f217e819a10>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        },
        {
          "output_type": "display_data",
          "data": {
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ePVm8eHE6Oztz/fXXZ9++fTn77LMzY8aMJMnll1+eefPmpaGhIYsXL86YMWMy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vP+el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\nYII=\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f21822d1190>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "iNP3ljaeJTAK",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "# We selected the best variables in the database of Eicu_crd with the scope to find the PATTERNS the first three days at the entrace in the ICU\n",
        "consulta=run_query(\"SELECT p.patientunitstayid,p.admissionweight,p.admissionheight,p.age, d.diagnosisid, ap.saps3day1, ap.cirrhosis,ap.diabetes,ap.saps3today,ap.saps3yesterday FROM `physionet-data.eicu_crd.diagnosis` as d  inner join `physionet-data.eicu_crd.patient` as p  on p.patientunitstayid = d.patientunitstayid  inner join `physionet-data.eicu_crd_demo.apachepredvar` as ap on p.patientunitstayid=ap.patientunitstayid WHERE LOWER(diagnosisstring) LIKE '%septic shock%' AND d.diagnosisoffset < 4000 ORDER BY d.patientunitstayid\")\n",
        "\n",
        "\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "A7k6SQQBTtSs",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1969
        },
        "outputId": "95770be9-8684-44f3-a6b8-9b7499cc770a"
      },
      "cell_type": "code",
      "source": [
        "consulta"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>patientunitstayid</th>\n",
              "      <th>admissionweight</th>\n",
              "      <th>admissionheight</th>\n",
              "      <th>age</th>\n",
              "      <th>diagnosisid</th>\n",
              "      <th>saps3day1</th>\n",
              "      <th>cirrhosis</th>\n",
              "      <th>diabetes</th>\n",
              "      <th>saps3today</th>\n",
              "      <th>saps3yesterday</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>143599</td>\n",
              "      <td>75.50</td>\n",
              "      <td>172.70</td>\n",
              "      <td>27</td>\n",
              "      <td>3781507</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>143599</td>\n",
              "      <td>75.50</td>\n",
              "      <td>172.70</td>\n",
              "      <td>27</td>\n",
              "      <td>4108080</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>145917</td>\n",
              "      <td>64.80</td>\n",
              "      <td>162.60</td>\n",
              "      <td>53</td>\n",
              "      <td>3853742</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>145917</td>\n",
              "      <td>64.80</td>\n",
              "      <td>162.60</td>\n",
              "      <td>53</td>\n",
              "      <td>3834782</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>151900</td>\n",
              "      <td>86.80</td>\n",
              "      <td>165.10</td>\n",
              "      <td>66</td>\n",
              "      <td>3850876</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>151900</td>\n",
              "      <td>86.80</td>\n",
              "      <td>165.10</td>\n",
              "      <td>66</td>\n",
              "      <td>3707280</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>151900</td>\n",
              "      <td>86.80</td>\n",
              "      <td>165.10</td>\n",
              "      <td>66</td>\n",
              "      <td>3892141</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>168236</td>\n",
              "      <td>121.00</td>\n",
              "      <td>193.00</td>\n",
              "      <td>16</td>\n",
              "      <td>3890667</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>168236</td>\n",
              "      <td>121.00</td>\n",
              "      <td>193.00</td>\n",
              "      <td>16</td>\n",
              "      <td>3418518</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>168236</td>\n",
              "      <td>121.00</td>\n",
              "      <td>193.00</td>\n",
              "      <td>16</td>\n",
              "      <td>3456917</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>224606</td>\n",
              "      <td>NaN</td>\n",
              "      <td>160.00</td>\n",
              "      <td>76</td>\n",
              "      <td>4261411</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>249328</td>\n",
              "      <td>95.50</td>\n",
              "      <td>170.20</td>\n",
              "      <td>87</td>\n",
              "      <td>5011179</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>249328</td>\n",
              "      <td>95.50</td>\n",
              "      <td>170.20</td>\n",
              "      <td>87</td>\n",
              "      <td>5072664</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>250719</td>\n",
              "      <td>63.51</td>\n",
              "      <td>172.72</td>\n",
              "      <td>60</td>\n",
              "      <td>4350112</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>250719</td>\n",
              "      <td>63.51</td>\n",
              "      <td>172.72</td>\n",
              "      <td>60</td>\n",
              "      <td>5186729</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>251140</td>\n",
              "      <td>98.60</td>\n",
              "      <td>167.60</td>\n",
              "      <td>77</td>\n",
              "      <td>4479888</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>251140</td>\n",
              "      <td>98.60</td>\n",
              "      <td>167.60</td>\n",
              "      <td>77</td>\n",
              "      <td>4559333</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>251140</td>\n",
              "      <td>98.60</td>\n",
              "      <td>167.60</td>\n",
              "      <td>77</td>\n",
              "      <td>4484993</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>251140</td>\n",
              "      <td>98.60</td>\n",
              "      <td>167.60</td>\n",
              "      <td>77</td>\n",
              "      <td>4533276</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>251140</td>\n",
              "      <td>98.60</td>\n",
              "      <td>167.60</td>\n",
              "      <td>77</td>\n",
              "      <td>4524967</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>251140</td>\n",
              "      <td>98.60</td>\n",
              "      <td>167.60</td>\n",
              "      <td>77</td>\n",
              "      <td>4940144</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>251140</td>\n",
              "      <td>98.60</td>\n",
              "      <td>167.60</td>\n",
              "      <td>77</td>\n",
              "      <td>4700224</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>251140</td>\n",
              "      <td>98.60</td>\n",
              "      <td>167.60</td>\n",
              "      <td>77</td>\n",
              "      <td>5088362</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>251140</td>\n",
              "      <td>98.60</td>\n",
              "      <td>167.60</td>\n",
              "      <td>77</td>\n",
              "      <td>4291424</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>251140</td>\n",
              "      <td>98.60</td>\n",
              "      <td>167.60</td>\n",
              "      <td>77</td>\n",
              "      <td>5419298</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>252804</td>\n",
              "      <td>82.20</td>\n",
              "      <td>172.70</td>\n",
              "      <td>78</td>\n",
              "      <td>4594080</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>252804</td>\n",
              "      <td>82.20</td>\n",
              "      <td>172.70</td>\n",
              "      <td>78</td>\n",
              "      <td>4445972</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>252804</td>\n",
              "      <td>82.20</td>\n",
              "      <td>172.70</td>\n",
              "      <td>78</td>\n",
              "      <td>4791939</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>253346</td>\n",
              "      <td>92.20</td>\n",
              "      <td>167.60</td>\n",
              "      <td>67</td>\n",
              "      <td>5201805</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>253346</td>\n",
              "      <td>92.20</td>\n",
              "      <td>167.60</td>\n",
              "      <td>67</td>\n",
              "      <td>4319213</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>94</th>\n",
              "      <td>304979</td>\n",
              "      <td>56.50</td>\n",
              "      <td>162.60</td>\n",
              "      <td>73</td>\n",
              "      <td>5401410</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>95</th>\n",
              "      <td>304979</td>\n",
              "      <td>56.50</td>\n",
              "      <td>162.60</td>\n",
              "      <td>73</td>\n",
              "      <td>4636569</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>96</th>\n",
              "      <td>325924</td>\n",
              "      <td>61.20</td>\n",
              "      <td>163.00</td>\n",
              "      <td>54</td>\n",
              "      <td>6234764</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>97</th>\n",
              "      <td>325924</td>\n",
              "      <td>61.20</td>\n",
              "      <td>163.00</td>\n",
              "      <td>54</td>\n",
              "      <td>6749988</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>98</th>\n",
              "      <td>325924</td>\n",
              "      <td>61.20</td>\n",
              "      <td>163.00</td>\n",
              "      <td>54</td>\n",
              "      <td>6918070</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99</th>\n",
              "      <td>325924</td>\n",
              "      <td>61.20</td>\n",
              "      <td>163.00</td>\n",
              "      <td>54</td>\n",
              "      <td>5829401</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>100</th>\n",
              "      <td>325924</td>\n",
              "      <td>61.20</td>\n",
              "      <td>163.00</td>\n",
              "      <td>54</td>\n",
              "      <td>5519167</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>101</th>\n",
              "      <td>329635</td>\n",
              "      <td>62.20</td>\n",
              "      <td>170.20</td>\n",
              "      <td>59</td>\n",
              "      <td>5837739</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>102</th>\n",
              "      <td>329635</td>\n",
              "      <td>62.20</td>\n",
              "      <td>170.20</td>\n",
              "      <td>59</td>\n",
              "      <td>5962342</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>103</th>\n",
              "      <td>386740</td>\n",
              "      <td>167.60</td>\n",
              "      <td>167.00</td>\n",
              "      <td>83</td>\n",
              "      <td>6067983</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>104</th>\n",
              "      <td>386740</td>\n",
              "      <td>167.60</td>\n",
              "      <td>167.00</td>\n",
              "      <td>83</td>\n",
              "      <td>6745508</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>105</th>\n",
              "      <td>386740</td>\n",
              "      <td>167.60</td>\n",
              "      <td>167.00</td>\n",
              "      <td>83</td>\n",
              "      <td>6355829</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>106</th>\n",
              "      <td>980063</td>\n",
              "      <td>60.80</td>\n",
              "      <td>177.80</td>\n",
              "      <td>50</td>\n",
              "      <td>12774535</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>107</th>\n",
              "      <td>980063</td>\n",
              "      <td>60.80</td>\n",
              "      <td>177.80</td>\n",
              "      <td>50</td>\n",
              "      <td>12774580</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>108</th>\n",
              "      <td>980063</td>\n",
              "      <td>60.80</td>\n",
              "      <td>177.80</td>\n",
              "      <td>50</td>\n",
              "      <td>12774233</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>109</th>\n",
              "      <td>980063</td>\n",
              "      <td>60.80</td>\n",
              "      <td>177.80</td>\n",
              "      <td>50</td>\n",
              "      <td>12774426</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>110</th>\n",
              "      <td>980063</td>\n",
              "      <td>60.80</td>\n",
              "      <td>177.80</td>\n",
              "      <td>50</td>\n",
              "      <td>12774104</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>111</th>\n",
              "      <td>998864</td>\n",
              "      <td>NaN</td>\n",
              "      <td>165.00</td>\n",
              "      <td>72</td>\n",
              "      <td>13476733</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>112</th>\n",
              "      <td>1003656</td>\n",
              "      <td>109.70</td>\n",
              "      <td>175.00</td>\n",
              "      <td>59</td>\n",
              "      <td>14747138</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>113</th>\n",
              "      <td>1003656</td>\n",
              "      <td>109.70</td>\n",
              "      <td>175.00</td>\n",
              "      <td>59</td>\n",
              "      <td>14371135</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>114</th>\n",
              "      <td>1003656</td>\n",
              "      <td>109.70</td>\n",
              "      <td>175.00</td>\n",
              "      <td>59</td>\n",
              "      <td>14078231</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>115</th>\n",
              "      <td>1003656</td>\n",
              "      <td>109.70</td>\n",
              "      <td>175.00</td>\n",
              "      <td>59</td>\n",
              "      <td>15103210</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>116</th>\n",
              "      <td>1016846</td>\n",
              "      <td>63.10</td>\n",
              "      <td>178.00</td>\n",
              "      <td>59</td>\n",
              "      <td>15046148</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>117</th>\n",
              "      <td>1016846</td>\n",
              "      <td>63.10</td>\n",
              "      <td>178.00</td>\n",
              "      <td>59</td>\n",
              "      <td>15025645</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>118</th>\n",
              "      <td>1064571</td>\n",
              "      <td>63.60</td>\n",
              "      <td>160.20</td>\n",
              "      <td>77</td>\n",
              "      <td>15141114</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>119</th>\n",
              "      <td>1066933</td>\n",
              "      <td>53.60</td>\n",
              "      <td>162.60</td>\n",
              "      <td>88</td>\n",
              "      <td>15161481</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>120</th>\n",
              "      <td>1067427</td>\n",
              "      <td>82.10</td>\n",
              "      <td>170.20</td>\n",
              "      <td>61</td>\n",
              "      <td>15161501</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>121</th>\n",
              "      <td>1112115</td>\n",
              "      <td>110.40</td>\n",
              "      <td>162.60</td>\n",
              "      <td>78</td>\n",
              "      <td>15324054</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>122</th>\n",
              "      <td>1112115</td>\n",
              "      <td>110.40</td>\n",
              "      <td>162.60</td>\n",
              "      <td>78</td>\n",
              "      <td>15324015</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>123</th>\n",
              "      <td>1112115</td>\n",
              "      <td>110.40</td>\n",
              "      <td>162.60</td>\n",
              "      <td>78</td>\n",
              "      <td>15324006</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>124 rows × 10 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     patientunitstayid  admissionweight  admissionheight age  diagnosisid  \\\n",
              "0               143599            75.50           172.70  27      3781507   \n",
              "1               143599            75.50           172.70  27      4108080   \n",
              "2               145917            64.80           162.60  53      3853742   \n",
              "3               145917            64.80           162.60  53      3834782   \n",
              "4               151900            86.80           165.10  66      3850876   \n",
              "5               151900            86.80           165.10  66      3707280   \n",
              "6               151900            86.80           165.10  66      3892141   \n",
              "7               168236           121.00           193.00  16      3890667   \n",
              "8               168236           121.00           193.00  16      3418518   \n",
              "9               168236           121.00           193.00  16      3456917   \n",
              "10              224606              NaN           160.00  76      4261411   \n",
              "11              249328            95.50           170.20  87      5011179   \n",
              "12              249328            95.50           170.20  87      5072664   \n",
              "13              250719            63.51           172.72  60      4350112   \n",
              "14              250719            63.51           172.72  60      5186729   \n",
              "15              251140            98.60           167.60  77      4479888   \n",
              "16              251140            98.60           167.60  77      4559333   \n",
              "17              251140            98.60           167.60  77      4484993   \n",
              "18              251140            98.60           167.60  77      4533276   \n",
              "19              251140            98.60           167.60  77      4524967   \n",
              "20              251140            98.60           167.60  77      4940144   \n",
              "21              251140            98.60           167.60  77      4700224   \n",
              "22              251140            98.60           167.60  77      5088362   \n",
              "23              251140            98.60           167.60  77      4291424   \n",
              "24              251140            98.60           167.60  77      5419298   \n",
              "25              252804            82.20           172.70  78      4594080   \n",
              "26              252804            82.20           172.70  78      4445972   \n",
              "27              252804            82.20           172.70  78      4791939   \n",
              "28              253346            92.20           167.60  67      5201805   \n",
              "29              253346            92.20           167.60  67      4319213   \n",
              "..                 ...              ...              ...  ..          ...   \n",
              "94              304979            56.50           162.60  73      5401410   \n",
              "95              304979            56.50           162.60  73      4636569   \n",
              "96              325924            61.20           163.00  54      6234764   \n",
              "97              325924            61.20           163.00  54      6749988   \n",
              "98              325924            61.20           163.00  54      6918070   \n",
              "99              325924            61.20           163.00  54      5829401   \n",
              "100             325924            61.20           163.00  54      5519167   \n",
              "101             329635            62.20           170.20  59      5837739   \n",
              "102             329635            62.20           170.20  59      5962342   \n",
              "103             386740           167.60           167.00  83      6067983   \n",
              "104             386740           167.60           167.00  83      6745508   \n",
              "105             386740           167.60           167.00  83      6355829   \n",
              "106             980063            60.80           177.80  50     12774535   \n",
              "107             980063            60.80           177.80  50     12774580   \n",
              "108             980063            60.80           177.80  50     12774233   \n",
              "109             980063            60.80           177.80  50     12774426   \n",
              "110             980063            60.80           177.80  50     12774104   \n",
              "111             998864              NaN           165.00  72     13476733   \n",
              "112            1003656           109.70           175.00  59     14747138   \n",
              "113            1003656           109.70           175.00  59     14371135   \n",
              "114            1003656           109.70           175.00  59     14078231   \n",
              "115            1003656           109.70           175.00  59     15103210   \n",
              "116            1016846            63.10           178.00  59     15046148   \n",
              "117            1016846            63.10           178.00  59     15025645   \n",
              "118            1064571            63.60           160.20  77     15141114   \n",
              "119            1066933            53.60           162.60  88     15161481   \n",
              "120            1067427            82.10           170.20  61     15161501   \n",
              "121            1112115           110.40           162.60  78     15324054   \n",
              "122            1112115           110.40           162.60  78     15324015   \n",
              "123            1112115           110.40           162.60  78     15324006   \n",
              "\n",
              "     saps3day1  cirrhosis  diabetes  saps3today  saps3yesterday  \n",
              "0            0          0         0           0               0  \n",
              "1            0          0         0           0               0  \n",
              "2            0          0         1           0               0  \n",
              "3            0          0         1           0               0  \n",
              "4            0          0         0           0               0  \n",
              "5            0          0         0           0               0  \n",
              "6            0          0         0           0               0  \n",
              "7            0          0         0           0               0  \n",
              "8            0          0         0           0               0  \n",
              "9            0          0         0           0               0  \n",
              "10           0          0         0           0               0  \n",
              "11           0          0         0           0               0  \n",
              "12           0          0         0           0               0  \n",
              "13           0          0         0           0               0  \n",
              "14           0          0         0           0               0  \n",
              "15           0          0         0           0               0  \n",
              "16           0          0         0           0               0  \n",
              "17           0          0         0           0               0  \n",
              "18           0          0         0           0               0  \n",
              "19           0          0         0           0               0  \n",
              "20           0          0         0           0               0  \n",
              "21           0          0         0           0               0  \n",
              "22           0          0         0           0               0  \n",
              "23           0          0         0           0               0  \n",
              "24           0          0         0           0               0  \n",
              "25           0          0         0           0               0  \n",
              "26           0          0         0           0               0  \n",
              "27           0          0         0           0               0  \n",
              "28           0          0         0           0               0  \n",
              "29           0          0         0           0               0  \n",
              "..         ...        ...       ...         ...             ...  \n",
              "94           0          0         0           0               0  \n",
              "95           0          0         0           0               0  \n",
              "96           0          0         0           0               0  \n",
              "97           0          0         0           0               0  \n",
              "98           0          0         0           0               0  \n",
              "99           0          0         0           0               0  \n",
              "100          0          0         0           0               0  \n",
              "101          0          0         1           0               0  \n",
              "102          0          0         1           0               0  \n",
              "103          0          0         0           0               0  \n",
              "104          0          0         0           0               0  \n",
              "105          0          0         0           0               0  \n",
              "106          0          0         0           0               0  \n",
              "107          0          0         0           0               0  \n",
              "108          0          0         0           0               0  \n",
              "109          0          0         0           0               0  \n",
              "110          0          0         0           0               0  \n",
              "111          0          0         0           0               0  \n",
              "112          0          0         0           0               0  \n",
              "113          0          0         0           0               0  \n",
              "114          0          0         0           0               0  \n",
              "115          0          0         0           0               0  \n",
              "116          0          0         0           0               0  \n",
              "117          0          0         0           0               0  \n",
              "118          0          0         0           0               0  \n",
              "119          0          0         0           0               0  \n",
              "120          0          0         1           0               0  \n",
              "121          0          0         0           0               0  \n",
              "122          0          0         0           0               0  \n",
              "123          0          0         0           0               0  \n",
              "\n",
              "[124 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "metadata": {
        "id": "okRsqXCUTyAc",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "# the intention is to applt the No supervised Model with K-Means Clustering Implementation in Python\n",
        "#https://www.kaggle.com/andyxie/k-means-clustering-implementation-in-python\n",
        "#https://www.kaggle.com/tonzowonzo/simple-k-means-clustering-on-the-iris-dataset\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "gGkP1qzkUlP-",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import pandas as pd\n",
        "consulta=consulta.dropna()\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "GZLaaXbDXjEl",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 729
        },
        "outputId": "e9b31d51-dad4-4b58-d51b-c47f02d8756a"
      },
      "cell_type": "code",
      "source": [
        "#Finding the optimum number of clusters for k-means classification\n",
        "\n",
        "\n",
        "from sklearn.cluster import KMeans\n",
        "wcss = []\n",
        "\n",
        "for i in range(1, 11):\n",
        "    kmeans = KMeans(n_clusters = i, init = 'k-means++', max_iter = 300, n_init = 10, random_state = 0)\n",
        "    kmeans.fit(consulta)\n",
        "    wcss.append(kmeans.inertia_)\n",
        "    \n",
        "#Plotting the results onto a line graph, allowing us to observe 'The elbow'\n",
        "plt.plot(range(1, 11), wcss)\n",
        "plt.title('The elbow method')\n",
        "plt.xlabel('Number of clusters')\n",
        "plt.ylabel('WCSS') #within cluster sum of squares\n",
        "plt.show()"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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AAAAgNKoVfUeOqG0csNsIAAAAKJ7QqEa82GskNAIAAACKJzSqEROhUb+dRgAAAEANEBrV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\nYHSPhVp5AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f62fefebcd0>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "SDdqq7Ugu6eF",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#Applying kmeans to the dataset / Creating the kmeans classifier\n",
        "kmeans = KMeans(n_clusters = 3, init = 'k-means++', max_iter = 300, n_init = 10, random_state = 0)\n",
        "y_kmeans = kmeans.fit_predict(consulta)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "uIK0HIxkfv6v",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#Visualising the clusters\n",
        "#consulta.plot(figsize = [20,16], kind='scatter',x = y_kmeans, y =y_kmeans)\n",
        "pyplot.scatter(consulta[y_kmeans == 0, 0], consulta[y_kmeans == 0, 1], s = 100)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "fwFcjVi6uGBH",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "plt.scatter(consulta[y_kmeans == 1, 0], consulta[y_kmeans == 1, 1], s = 100, c = 'blue', label = 'Iris-versicolour')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "R0c6fosyuF3o",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "plt.consulta(consulta[y_kmeans == 2, 0], consulta[y_kmeans == 2, 1], s = 100, c = 'green', label = 'Iris-virginica')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "u8K41vIst9xL",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 717
        },
        "outputId": "48b904a3-5c5e-45fd-df5f-290539af9485"
      },
      "cell_type": "code",
      "source": [
        "#Plotting the centroids of the clusters\n",
        "plt.scatter(kmeans.cluster_centers_[:, 0], kmeans.cluster_centers_[:,1], s = 100, c = 'yellow', label = 'Centroids')"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.collections.PathCollection at 0x7f62ff237290>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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WLVsIBAL09PQA0Nvby7Zt2yguLmb9+vUMDAz8ssf27dvp6+tjZmaG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\nSERERERERESkQGgQJCIiIiIiIiJSIP4CPBHlTpe0VF8AAAAASUVORK5CYII=\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f62ff315910>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "L6pC-2aGt9VH",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "plt.legend()"
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}