Team_10.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Team_10_Santi",
      "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",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 68
        },
        "outputId": "2c4e04cf-beea-41ae-a6dd-031885e26090"
      },
      "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": 36,
      "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': True}})"
      ],
      "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",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 2057
        },
        "outputId": "f74c1f99-46aa-4534-dcb7-c531adc98852"
      },
      "cell_type": "code",
      "source": [
        "consulta"
      ],
      "execution_count": 41,
      "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>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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>141515</td>\n",
              "      <td>False</td>\n",
              "      <td>2418</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>141515</td>\n",
              "      <td>False</td>\n",
              "      <td>3346</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>141515</td>\n",
              "      <td>True</td>\n",
              "      <td>3870</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>141751</td>\n",
              "      <td>False</td>\n",
              "      <td>45</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>141751</td>\n",
              "      <td>True</td>\n",
              "      <td>460</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>141959</td>\n",
              "      <td>True</td>\n",
              "      <td>219</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>142483</td>\n",
              "      <td>False</td>\n",
              "      <td>1363</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>142483</td>\n",
              "      <td>False</td>\n",
              "      <td>1741</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>142483</td>\n",
              "      <td>False</td>\n",
              "      <td>21476</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>142483</td>\n",
              "      <td>True</td>\n",
              "      <td>30971</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>143466</td>\n",
              "      <td>True</td>\n",
              "      <td>7279</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>143599</td>\n",
              "      <td>False</td>\n",
              "      <td>217</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>143599</td>\n",
              "      <td>True</td>\n",
              "      <td>221</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>143970</td>\n",
              "      <td>True</td>\n",
              "      <td>122</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>145394</td>\n",
              "      <td>False</td>\n",
              "      <td>7670</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>145394</td>\n",
              "      <td>True</td>\n",
              "      <td>7671</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>145917</td>\n",
              "      <td>False</td>\n",
              "      <td>3371</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>145917</td>\n",
              "      <td>True</td>\n",
              "      <td>3912</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>146349</td>\n",
              "      <td>False</td>\n",
              "      <td>1823</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>146349</td>\n",
              "      <td>False</td>\n",
              "      <td>2170</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>146349</td>\n",
              "      <td>False</td>\n",
              "      <td>3472</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>146349</td>\n",
              "      <td>False</td>\n",
              "      <td>7858</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>146788</td>\n",
              "      <td>True</td>\n",
              "      <td>1749</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>148182</td>\n",
              "      <td>False</td>\n",
              "      <td>14361</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>148182</td>\n",
              "      <td>True</td>\n",
              "      <td>16201</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>148529</td>\n",
              "      <td>False</td>\n",
              "      <td>37</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>148529</td>\n",
              "      <td>False</td>\n",
              "      <td>3136</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>149178</td>\n",
              "      <td>False</td>\n",
              "      <td>30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>149178</td>\n",
              "      <td>True</td>\n",
              "      <td>37</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35102</th>\n",
              "      <td>3352103</td>\n",
              "      <td>False</td>\n",
              "      <td>5731</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35103</th>\n",
              "      <td>3352103</td>\n",
              "      <td>False</td>\n",
              "      <td>6535</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35104</th>\n",
              "      <td>3352104</td>\n",
              "      <td>False</td>\n",
              "      <td>59</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35105</th>\n",
              "      <td>3352104</td>\n",
              "      <td>False</td>\n",
              "      <td>517</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35106</th>\n",
              "      <td>3352104</td>\n",
              "      <td>False</td>\n",
              "      <td>517</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35107</th>\n",
              "      <td>3352104</td>\n",
              "      <td>False</td>\n",
              "      <td>537</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35108</th>\n",
              "      <td>3352271</td>\n",
              "      <td>True</td>\n",
              "      <td>105</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35109</th>\n",
              "      <td>3352358</td>\n",
              "      <td>False</td>\n",
              "      <td>56</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35110</th>\n",
              "      <td>3352358</td>\n",
              "      <td>False</td>\n",
              "      <td>426</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35111</th>\n",
              "      <td>3352358</td>\n",
              "      <td>False</td>\n",
              "      <td>869</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35112</th>\n",
              "      <td>3352358</td>\n",
              "      <td>True</td>\n",
              "      <td>2120</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35113</th>\n",
              "      <td>3352711</td>\n",
              "      <td>False</td>\n",
              "      <td>80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35114</th>\n",
              "      <td>3352711</td>\n",
              "      <td>False</td>\n",
              "      <td>117</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35115</th>\n",
              "      <td>3352711</td>\n",
              "      <td>False</td>\n",
              "      <td>2223</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35116</th>\n",
              "      <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",
              "      <th>35118</th>\n",
              "      <td>3352711</td>\n",
              "      <td>False</td>\n",
              "      <td>7283</td>\n",
              "    </tr>\n",
              "    <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",
              "      <th>35121</th>\n",
              "      <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": 41
        }
      ]
    },
    {
      "metadata": {
        "id": "nFZubIs0gtH1",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 949
        },
        "outputId": "f7995138-bf09-49b4-b07b-b0487726fe36"
      },
      "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": 42,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fd6d7f2cc90>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 42
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAABLAAAAOTCAYAAACvvvrZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYII=\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7fd6d3d09310>"
            ]
          },
          "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": "EiPORXw3plwO",
        "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%' AND diagnosisoffset > 4000 ORDER BY patientunitstayid,activeupondischarge,diagnosisoffset\")"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "esfC95WJp4QW",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 2057
        },
        "outputId": "64a96fed-4d6e-4b5f-9405-38d1efd749a2"
      },
      "cell_type": "code",
      "source": [
        "consulta"
      ],
      "execution_count": 44,
      "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>activeupondischarge</th>\n",
              "      <th>diagnosisoffset</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>142483</td>\n",
              "      <td>False</td>\n",
              "      <td>21476</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>142483</td>\n",
              "      <td>True</td>\n",
              "      <td>30971</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>143466</td>\n",
              "      <td>True</td>\n",
              "      <td>7279</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>145394</td>\n",
              "      <td>False</td>\n",
              "      <td>7670</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>145394</td>\n",
              "      <td>True</td>\n",
              "      <td>7671</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>146349</td>\n",
              "      <td>False</td>\n",
              "      <td>7858</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>148182</td>\n",
              "      <td>False</td>\n",
              "      <td>14361</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>148182</td>\n",
              "      <td>True</td>\n",
              "      <td>16201</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>151023</td>\n",
              "      <td>True</td>\n",
              "      <td>4057</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>153170</td>\n",
              "      <td>False</td>\n",
              "      <td>19286</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>153170</td>\n",
              "      <td>False</td>\n",
              "      <td>20594</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>153170</td>\n",
              "      <td>False</td>\n",
              "      <td>25981</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>153170</td>\n",
              "      <td>True</td>\n",
              "      <td>26664</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>154134</td>\n",
              "      <td>False</td>\n",
              "      <td>6161</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>154134</td>\n",
              "      <td>True</td>\n",
              "      <td>6706</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>155503</td>\n",
              "      <td>False</td>\n",
              "      <td>8792</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>156476</td>\n",
              "      <td>False</td>\n",
              "      <td>6617</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>156476</td>\n",
              "      <td>False</td>\n",
              "      <td>11474</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>156476</td>\n",
              "      <td>False</td>\n",
              "      <td>13080</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>156476</td>\n",
              "      <td>True</td>\n",
              "      <td>16626</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>156843</td>\n",
              "      <td>False</td>\n",
              "      <td>5737</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>156843</td>\n",
              "      <td>False</td>\n",
              "      <td>16968</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>156843</td>\n",
              "      <td>False</td>\n",
              "      <td>17365</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>156843</td>\n",
              "      <td>False</td>\n",
              "      <td>37000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>156843</td>\n",
              "      <td>False</td>\n",
              "      <td>48816</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>156843</td>\n",
              "      <td>True</td>\n",
              "      <td>49040</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>159901</td>\n",
              "      <td>False</td>\n",
              "      <td>4239</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>159901</td>\n",
              "      <td>False</td>\n",
              "      <td>5805</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>159901</td>\n",
              "      <td>True</td>\n",
              "      <td>14323</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>160592</td>\n",
              "      <td>False</td>\n",
              "      <td>6465</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16090</th>\n",
              "      <td>3350978</td>\n",
              "      <td>False</td>\n",
              "      <td>65607</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16091</th>\n",
              "      <td>3350978</td>\n",
              "      <td>False</td>\n",
              "      <td>67052</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16092</th>\n",
              "      <td>3350978</td>\n",
              "      <td>False</td>\n",
              "      <td>68553</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16093</th>\n",
              "      <td>3350978</td>\n",
              "      <td>False</td>\n",
              "      <td>71023</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16094</th>\n",
              "      <td>3350978</td>\n",
              "      <td>False</td>\n",
              "      <td>78210</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16095</th>\n",
              "      <td>3350978</td>\n",
              "      <td>False</td>\n",
              "      <td>83047</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16096</th>\n",
              "      <td>3350978</td>\n",
              "      <td>False</td>\n",
              "      <td>84113</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16097</th>\n",
              "      <td>3350978</td>\n",
              "      <td>True</td>\n",
              "      <td>85877</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16098</th>\n",
              "      <td>3351293</td>\n",
              "      <td>False</td>\n",
              "      <td>4034</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16099</th>\n",
              "      <td>3351293</td>\n",
              "      <td>False</td>\n",
              "      <td>4035</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16100</th>\n",
              "      <td>3351293</td>\n",
              "      <td>True</td>\n",
              "      <td>4317</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16101</th>\n",
              "      <td>3351413</td>\n",
              "      <td>False</td>\n",
              "      <td>8355</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16102</th>\n",
              "      <td>3351413</td>\n",
              "      <td>False</td>\n",
              "      <td>14657</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16103</th>\n",
              "      <td>3351413</td>\n",
              "      <td>False</td>\n",
              "      <td>20518</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16104</th>\n",
              "      <td>3351414</td>\n",
              "      <td>False</td>\n",
              "      <td>6041</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16105</th>\n",
              "      <td>3351414</td>\n",
              "      <td>False</td>\n",
              "      <td>6041</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16106</th>\n",
              "      <td>3351414</td>\n",
              "      <td>False</td>\n",
              "      <td>7505</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16107</th>\n",
              "      <td>3351414</td>\n",
              "      <td>False</td>\n",
              "      <td>8653</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16108</th>\n",
              "      <td>3351414</td>\n",
              "      <td>False</td>\n",
              "      <td>8880</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16109</th>\n",
              "      <td>3351414</td>\n",
              "      <td>False</td>\n",
              "      <td>11037</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16110</th>\n",
              "      <td>3351414</td>\n",
              "      <td>False</td>\n",
              "      <td>12443</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16111</th>\n",
              "      <td>3351414</td>\n",
              "      <td>False</td>\n",
              "      <td>13984</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16112</th>\n",
              "      <td>3352103</td>\n",
              "      <td>False</td>\n",
              "      <td>5091</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16113</th>\n",
              "      <td>3352103</td>\n",
              "      <td>False</td>\n",
              "      <td>5731</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16114</th>\n",
              "      <td>3352103</td>\n",
              "      <td>False</td>\n",
              "      <td>6535</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16115</th>\n",
              "      <td>3352711</td>\n",
              "      <td>False</td>\n",
              "      <td>6212</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16116</th>\n",
              "      <td>3352711</td>\n",
              "      <td>False</td>\n",
              "      <td>6548</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16117</th>\n",
              "      <td>3352711</td>\n",
              "      <td>False</td>\n",
              "      <td>7283</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16118</th>\n",
              "      <td>3352711</td>\n",
              "      <td>False</td>\n",
              "      <td>9140</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16119</th>\n",
              "      <td>3352711</td>\n",
              "      <td>True</td>\n",
              "      <td>10531</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>16120 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "       patientunitstayid  activeupondischarge  diagnosisoffset\n",
              "0                 142483                False            21476\n",
              "1                 142483                 True            30971\n",
              "2                 143466                 True             7279\n",
              "3                 145394                False             7670\n",
              "4                 145394                 True             7671\n",
              "5                 146349                False             7858\n",
              "6                 148182                False            14361\n",
              "7                 148182                 True            16201\n",
              "8                 151023                 True             4057\n",
              "9                 153170                False            19286\n",
              "10                153170                False            20594\n",
              "11                153170                False            25981\n",
              "12                153170                 True            26664\n",
              "13                154134                False             6161\n",
              "14                154134                 True             6706\n",
              "15                155503                False             8792\n",
              "16                156476                False             6617\n",
              "17                156476                False            11474\n",
              "18                156476                False            13080\n",
              "19                156476                 True            16626\n",
              "20                156843                False             5737\n",
              "21                156843                False            16968\n",
              "22                156843                False            17365\n",
              "23                156843                False            37000\n",
              "24                156843                False            48816\n",
              "25                156843                 True            49040\n",
              "26                159901                False             4239\n",
              "27                159901                False             5805\n",
              "28                159901                 True            14323\n",
              "29                160592                False             6465\n",
              "...                  ...                  ...              ...\n",
              "16090            3350978                False            65607\n",
              "16091            3350978                False            67052\n",
              "16092            3350978                False            68553\n",
              "16093            3350978                False            71023\n",
              "16094            3350978                False            78210\n",
              "16095            3350978                False            83047\n",
              "16096            3350978                False            84113\n",
              "16097            3350978                 True            85877\n",
              "16098            3351293                False             4034\n",
              "16099            3351293                False             4035\n",
              "16100            3351293                 True             4317\n",
              "16101            3351413                False             8355\n",
              "16102            3351413                False            14657\n",
              "16103            3351413                False            20518\n",
              "16104            3351414                False             6041\n",
              "16105            3351414                False             6041\n",
              "16106            3351414                False             7505\n",
              "16107            3351414                False             8653\n",
              "16108            3351414                False             8880\n",
              "16109            3351414                False            11037\n",
              "16110            3351414                False            12443\n",
              "16111            3351414                False            13984\n",
              "16112            3352103                False             5091\n",
              "16113            3352103                False             5731\n",
              "16114            3352103                False             6535\n",
              "16115            3352711                False             6212\n",
              "16116            3352711                False             6548\n",
              "16117            3352711                False             7283\n",
              "16118            3352711                False             9140\n",
              "16119            3352711                 True            10531\n",
              "\n",
              "[16120 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 44
        }
      ]
    },
    {
      "metadata": {
        "id": "iJHygPumnjVG",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 949
        },
        "outputId": "f4bcf0a1-173f-4b15-9020-79a63aa17703"
      },
      "cell_type": "code",
      "source": [
        "# Scatter Plot de correlacion entre eje x, eje y, eliminados pacientes de los que no tenemos datos de tres dias\n",
        "consulta.plot(figsize = [20,16], kind='scatter',x='patientunitstayid',y='diagnosisoffset' )"
      ],
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fd6d5b2eb50>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 45
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAABLAAAAOTCAYAAACvvvrZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nIqK6xgAWERERERERERHVtf8HIQqahasNUvsAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7fd6d251cd50>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "cFjKXdowWY9Z",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# Number of unique id's to profile  load balancing"
      ]
    },
    {
      "metadata": {
        "id": "CpDTYYfkBXqU",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "consulta = run_query(\"SELECT patientunitstayid FROM [physionet-data:eicu_crd.diagnosis] WHERE LOWER(diagnosisstring) LIKE '%septic shock%' AND diagnosisoffset > 4000 GROUP BY patientunitstayid  ORDER BY patientunitstayid\")\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "7bRuCY8DF4Fr",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1969
        },
        "outputId": "da69481a-9899-4684-c7f5-6deb2cae7638"
      },
      "cell_type": "code",
      "source": [
        "consulta"
      ],
      "execution_count": 47,
      "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",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>142483</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>143466</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>145394</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>146349</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>148182</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>151023</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>153170</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>154134</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>155503</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>156476</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>156843</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>159901</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>160592</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>160594</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>162584</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>166423</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>167200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>171473</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>173420</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>173816</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>179106</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>181292</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>186706</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>188579</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>189265</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>189727</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>191474</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>192042</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>192236</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>197356</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2496</th>\n",
              "      <td>3338010</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2497</th>\n",
              "      <td>3338553</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2498</th>\n",
              "      <td>3341407</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2499</th>\n",
              "      <td>3341539</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2500</th>\n",
              "      <td>3342584</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2501</th>\n",
              "      <td>3342614</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2502</th>\n",
              "      <td>3342840</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2503</th>\n",
              "      <td>3343918</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2504</th>\n",
              "      <td>3344197</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2505</th>\n",
              "      <td>3345448</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2506</th>\n",
              "      <td>3346127</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2507</th>\n",
              "      <td>3346199</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2508</th>\n",
              "      <td>3346656</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2509</th>\n",
              "      <td>3346845</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2510</th>\n",
              "      <td>3346870</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2511</th>\n",
              "      <td>3347072</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2512</th>\n",
              "      <td>3347760</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2513</th>\n",
              "      <td>3347821</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2514</th>\n",
              "      <td>3347822</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2515</th>\n",
              "      <td>3348896</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2516</th>\n",
              "      <td>3349231</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2517</th>\n",
              "      <td>3350110</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2518</th>\n",
              "      <td>3350292</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2519</th>\n",
              "      <td>3350812</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2520</th>\n",
              "      <td>3350978</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2521</th>\n",
              "      <td>3351293</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2522</th>\n",
              "      <td>3351413</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2523</th>\n",
              "      <td>3351414</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2524</th>\n",
              "      <td>3352103</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2525</th>\n",
              "      <td>3352711</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2526 rows × 1 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "      patientunitstayid\n",
              "0                142483\n",
              "1                143466\n",
              "2                145394\n",
              "3                146349\n",
              "4                148182\n",
              "5                151023\n",
              "6                153170\n",
              "7                154134\n",
              "8                155503\n",
              "9                156476\n",
              "10               156843\n",
              "11               159901\n",
              "12               160592\n",
              "13               160594\n",
              "14               162584\n",
              "15               166423\n",
              "16               167200\n",
              "17               171473\n",
              "18               173420\n",
              "19               173816\n",
              "20               179106\n",
              "21               181292\n",
              "22               186706\n",
              "23               188579\n",
              "24               189265\n",
              "25               189727\n",
              "26               191474\n",
              "27               192042\n",
              "28               192236\n",
              "29               197356\n",
              "...                 ...\n",
              "2496            3338010\n",
              "2497            3338553\n",
              "2498            3341407\n",
              "2499            3341539\n",
              "2500            3342584\n",
              "2501            3342614\n",
              "2502            3342840\n",
              "2503            3343918\n",
              "2504            3344197\n",
              "2505            3345448\n",
              "2506            3346127\n",
              "2507            3346199\n",
              "2508            3346656\n",
              "2509            3346845\n",
              "2510            3346870\n",
              "2511            3347072\n",
              "2512            3347760\n",
              "2513            3347821\n",
              "2514            3347822\n",
              "2515            3348896\n",
              "2516            3349231\n",
              "2517            3350110\n",
              "2518            3350292\n",
              "2519            3350812\n",
              "2520            3350978\n",
              "2521            3351293\n",
              "2522            3351413\n",
              "2523            3351414\n",
              "2524            3352103\n",
              "2525            3352711\n",
              "\n",
              "[2526 rows x 1 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 47
        }
      ]
    },
    {
      "metadata": {
        "id": "G_Lwu68doKw7",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# Intake Output Balance events to calculate overload. Crude Data."
      ]
    },
    {
      "metadata": {
        "id": "r2JqE0qHoIl8",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "consulta = run_query(\"SELECT patientunitstayid,nettotal,intakeoutputentryoffset FROM [physionet-data:eicu_crd.intakeoutput] ORDER BY patientunitstayid\")"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "bqO4dLhasqhH",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1969
        },
        "outputId": "abc8be5c-3fd7-4380-f465-2717a6658463"
      },
      "cell_type": "code",
      "source": [
        "consulta"
      ],
      "execution_count": 49,
      "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>nettotal</th>\n",
              "      <th>intakeoutputentryoffset</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>141168</td>\n",
              "      <td>1075.00</td>\n",
              "      <td>1746</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>141168</td>\n",
              "      <td>540.00</td>\n",
              "      <td>1129</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>141168</td>\n",
              "      <td>1075.00</td>\n",
              "      <td>1746</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>141168</td>\n",
              "      <td>993.00</td>\n",
              "      <td>2346</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>141168</td>\n",
              "      <td>0.00</td>\n",
              "      <td>1066</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>141168</td>\n",
              "      <td>0.00</td>\n",
              "      <td>25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>141168</td>\n",
              "      <td>500.00</td>\n",
              "      <td>546</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>141168</td>\n",
              "      <td>0.00</td>\n",
              "      <td>895</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>141168</td>\n",
              "      <td>0.00</td>\n",
              "      <td>25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>141168</td>\n",
              "      <td>993.00</td>\n",
              "      <td>2346</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>141168</td>\n",
              "      <td>500.00</td>\n",
              "      <td>706</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>141168</td>\n",
              "      <td>500.00</td>\n",
              "      <td>546</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>141168</td>\n",
              "      <td>993.00</td>\n",
              "      <td>2346</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>141168</td>\n",
              "      <td>993.00</td>\n",
              "      <td>2346</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>141168</td>\n",
              "      <td>0.00</td>\n",
              "      <td>1146</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>141168</td>\n",
              "      <td>0.00</td>\n",
              "      <td>1146</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>141178</td>\n",
              "      <td>0.00</td>\n",
              "      <td>-276</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>141178</td>\n",
              "      <td>0.00</td>\n",
              "      <td>-276</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>141179</td>\n",
              "      <td>0.00</td>\n",
              "      <td>1506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>141179</td>\n",
              "      <td>120.00</td>\n",
              "      <td>1722</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>141179</td>\n",
              "      <td>300.00</td>\n",
              "      <td>1962</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>141179</td>\n",
              "      <td>1000.00</td>\n",
              "      <td>351</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>141179</td>\n",
              "      <td>-500.00</td>\n",
              "      <td>933</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>141179</td>\n",
              "      <td>1332.00</td>\n",
              "      <td>1889</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>141179</td>\n",
              "      <td>790.00</td>\n",
              "      <td>822</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>141179</td>\n",
              "      <td>-700.00</td>\n",
              "      <td>1420</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>141179</td>\n",
              "      <td>1800.00</td>\n",
              "      <td>1302</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>141179</td>\n",
              "      <td>-1000.00</td>\n",
              "      <td>1703</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>141179</td>\n",
              "      <td>0.00</td>\n",
              "      <td>1506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>141179</td>\n",
              "      <td>545.00</td>\n",
              "      <td>282</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12030259</th>\n",
              "      <td>3353254</td>\n",
              "      <td>5.00</td>\n",
              "      <td>3826</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12030260</th>\n",
              "      <td>3353254</td>\n",
              "      <td>-400.00</td>\n",
              "      <td>5326</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12030261</th>\n",
              "      <td>3353254</td>\n",
              "      <td>240.00</td>\n",
              "      <td>3743</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12030262</th>\n",
              "      <td>3353254</td>\n",
              "      <td>-250.00</td>\n",
              "      <td>5196</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12030263</th>\n",
              "      <td>3353254</td>\n",
              "      <td>-850.00</td>\n",
              "      <td>2101</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12030264</th>\n",
              "      <td>3353254</td>\n",
              "      <td>-397.00</td>\n",
              "      <td>2386</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12030265</th>\n",
              "      <td>3353254</td>\n",
              "      <td>3.00</td>\n",
              "      <td>4306</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12030266</th>\n",
              "      <td>3353254</td>\n",
              "      <td>240.00</td>\n",
              "      <td>4665</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12030267</th>\n",
              "      <td>3353254</td>\n",
              "      <td>500.00</td>\n",
              "      <td>-170</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12030268</th>\n",
              "      <td>3353254</td>\n",
              "      <td>-400.00</td>\n",
              "      <td>766</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12030269</th>\n",
              "      <td>3353254</td>\n",
              "      <td>-850.00</td>\n",
              "      <td>2401</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12030270</th>\n",
              "      <td>3353254</td>\n",
              "      <td>0.00</td>\n",
              "      <td>-219</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12030271</th>\n",
              "      <td>3353263</td>\n",
              "      <td>155.24</td>\n",
              "      <td>410</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12030272</th>\n",
              "      <td>3353263</td>\n",
              "      <td>0.00</td>\n",
              "      <td>-352</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12030273</th>\n",
              "      <td>3353263</td>\n",
              "      <td>125.00</td>\n",
              "      <td>170</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12030274</th>\n",
              "      <td>3353263</td>\n",
              "      <td>16.67</td>\n",
              "      <td>50</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12030275</th>\n",
              "      <td>3353263</td>\n",
              "      <td>0.00</td>\n",
              "      <td>24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12030276</th>\n",
              "      <td>3353263</td>\n",
              "      <td>0.00</td>\n",
              "      <td>24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12030277</th>\n",
              "      <td>3353263</td>\n",
              "      <td>136.09</td>\n",
              "      <td>290</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12030278</th>\n",
              "      <td>3353263</td>\n",
              "      <td>155.24</td>\n",
              "      <td>590</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12030279</th>\n",
              "      <td>3353263</td>\n",
              "      <td>163.30</td>\n",
              "      <td>830</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12030280</th>\n",
              "      <td>3353263</td>\n",
              "      <td>155.24</td>\n",
              "      <td>650</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12030281</th>\n",
              "      <td>3353263</td>\n",
              "      <td>155.24</td>\n",
              "      <td>470</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12030282</th>\n",
              "      <td>3353263</td>\n",
              "      <td>155.24</td>\n",
              "      <td>710</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12030283</th>\n",
              "      <td>3353263</td>\n",
              "      <td>155.24</td>\n",
              "      <td>350</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12030284</th>\n",
              "      <td>3353263</td>\n",
              "      <td>125.00</td>\n",
              "      <td>230</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12030285</th>\n",
              "      <td>3353263</td>\n",
              "      <td>155.24</td>\n",
              "      <td>530</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12030286</th>\n",
              "      <td>3353263</td>\n",
              "      <td>159.27</td>\n",
              "      <td>770</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12030287</th>\n",
              "      <td>3353263</td>\n",
              "      <td>0.00</td>\n",
              "      <td>-352</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12030288</th>\n",
              "      <td>3353263</td>\n",
              "      <td>125.00</td>\n",
              "      <td>110</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>12030289 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "          patientunitstayid  nettotal  intakeoutputentryoffset\n",
              "0                    141168   1075.00                     1746\n",
              "1                    141168    540.00                     1129\n",
              "2                    141168   1075.00                     1746\n",
              "3                    141168    993.00                     2346\n",
              "4                    141168      0.00                     1066\n",
              "5                    141168      0.00                       25\n",
              "6                    141168    500.00                      546\n",
              "7                    141168      0.00                      895\n",
              "8                    141168      0.00                       25\n",
              "9                    141168    993.00                     2346\n",
              "10                   141168    500.00                      706\n",
              "11                   141168    500.00                      546\n",
              "12                   141168    993.00                     2346\n",
              "13                   141168    993.00                     2346\n",
              "14                   141168      0.00                     1146\n",
              "15                   141168      0.00                     1146\n",
              "16                   141178      0.00                     -276\n",
              "17                   141178      0.00                     -276\n",
              "18                   141179      0.00                     1506\n",
              "19                   141179    120.00                     1722\n",
              "20                   141179    300.00                     1962\n",
              "21                   141179   1000.00                      351\n",
              "22                   141179   -500.00                      933\n",
              "23                   141179   1332.00                     1889\n",
              "24                   141179    790.00                      822\n",
              "25                   141179   -700.00                     1420\n",
              "26                   141179   1800.00                     1302\n",
              "27                   141179  -1000.00                     1703\n",
              "28                   141179      0.00                     1506\n",
              "29                   141179    545.00                      282\n",
              "...                     ...       ...                      ...\n",
              "12030259            3353254      5.00                     3826\n",
              "12030260            3353254   -400.00                     5326\n",
              "12030261            3353254    240.00                     3743\n",
              "12030262            3353254   -250.00                     5196\n",
              "12030263            3353254   -850.00                     2101\n",
              "12030264            3353254   -397.00                     2386\n",
              "12030265            3353254      3.00                     4306\n",
              "12030266            3353254    240.00                     4665\n",
              "12030267            3353254    500.00                     -170\n",
              "12030268            3353254   -400.00                      766\n",
              "12030269            3353254   -850.00                     2401\n",
              "12030270            3353254      0.00                     -219\n",
              "12030271            3353263    155.24                      410\n",
              "12030272            3353263      0.00                     -352\n",
              "12030273            3353263    125.00                      170\n",
              "12030274            3353263     16.67                       50\n",
              "12030275            3353263      0.00                       24\n",
              "12030276            3353263      0.00                       24\n",
              "12030277            3353263    136.09                      290\n",
              "12030278            3353263    155.24                      590\n",
              "12030279            3353263    163.30                      830\n",
              "12030280            3353263    155.24                      650\n",
              "12030281            3353263    155.24                      470\n",
              "12030282            3353263    155.24                      710\n",
              "12030283            3353263    155.24                      350\n",
              "12030284            3353263    125.00                      230\n",
              "12030285            3353263    155.24                      530\n",
              "12030286            3353263    159.27                      770\n",
              "12030287            3353263      0.00                     -352\n",
              "12030288            3353263    125.00                      110\n",
              "\n",
              "[12030289 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 49
        }
      ]
    },
    {
      "metadata": {
        "id": "X3wIz05Npt15",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 898
        },
        "outputId": "0fc307ab-2b04-4890-9000-8c09a74071ec"
      },
      "cell_type": "code",
      "source": [
        "# Scatter Plot exploratorio para detectar eventos con valores imposibles a eliminar.\n",
        "consulta.plot(figsize = [19,15], kind='scatter',x='patientunitstayid',y='nettotal' )"
      ],
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fd6d5b58dd0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 50
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAABIQAAANgCAYAAABdoLMsAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSUVORK5CYII=\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7fd6d3d0a810>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "kUJrnCh4QBIk",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        ""
      ]
    },
    {
      "metadata": {
        "colab_type": "text",
        "id": "3GM-Po8WQBiN"
      },
      "cell_type": "markdown",
      "source": [
        "# Intake Output Balance events to calculate overload. Cleaned Data"
      ]
    },
    {
      "metadata": {
        "id": "x4vpHsmDQDzk",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "consulta = run_query(\"SELECT f.patientunitstayid , f.nettotal, f.intakeoutputentryoffset FROM [physionet-data:eicu_crd.intakeoutput] AS f WHERE (f.nettotal < 5000) AND (f.nettotal > -5000) ORDER BY f.patientunitstayid, f.intakeoutputentryoffset\") "
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "lh4qEPznRZU5",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1969
        },
        "outputId": "9226b1ad-9e24-4ad1-d878-9c38bf3fbf67"
      },
      "cell_type": "code",
      "source": [
        "consulta"
      ],
      "execution_count": 52,
      "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>f_patientunitstayid</th>\n",
              "      <th>f_nettotal</th>\n",
              "      <th>f_intakeoutputentryoffset</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>141168</td>\n",
              "      <td>0.00</td>\n",
              "      <td>25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>141168</td>\n",
              "      <td>0.00</td>\n",
              "      <td>25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>141168</td>\n",
              "      <td>500.00</td>\n",
              "      <td>546</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>141168</td>\n",
              "      <td>500.00</td>\n",
              "      <td>546</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>141168</td>\n",
              "      <td>500.00</td>\n",
              "      <td>706</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>141168</td>\n",
              "      <td>0.00</td>\n",
              "      <td>895</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>141168</td>\n",
              "      <td>0.00</td>\n",
              "      <td>1066</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>141168</td>\n",
              "      <td>540.00</td>\n",
              "      <td>1129</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>141168</td>\n",
              "      <td>0.00</td>\n",
              "      <td>1146</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>141168</td>\n",
              "      <td>0.00</td>\n",
              "      <td>1146</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>141168</td>\n",
              "      <td>1075.00</td>\n",
              "      <td>1746</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>141168</td>\n",
              "      <td>1075.00</td>\n",
              "      <td>1746</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>141168</td>\n",
              "      <td>993.00</td>\n",
              "      <td>2346</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>141168</td>\n",
              "      <td>993.00</td>\n",
              "      <td>2346</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>141168</td>\n",
              "      <td>993.00</td>\n",
              "      <td>2346</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>141168</td>\n",
              "      <td>993.00</td>\n",
              "      <td>2346</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>141178</td>\n",
              "      <td>0.00</td>\n",
              "      <td>-276</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>141178</td>\n",
              "      <td>0.00</td>\n",
              "      <td>-276</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>141179</td>\n",
              "      <td>545.00</td>\n",
              "      <td>282</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>141179</td>\n",
              "      <td>1000.00</td>\n",
              "      <td>351</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>141179</td>\n",
              "      <td>100.00</td>\n",
              "      <td>402</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>141179</td>\n",
              "      <td>-700.00</td>\n",
              "      <td>678</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>141179</td>\n",
              "      <td>790.00</td>\n",
              "      <td>822</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>141179</td>\n",
              "      <td>-500.00</td>\n",
              "      <td>933</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>141179</td>\n",
              "      <td>1800.00</td>\n",
              "      <td>1302</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>141179</td>\n",
              "      <td>-700.00</td>\n",
              "      <td>1420</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>141179</td>\n",
              "      <td>720.00</td>\n",
              "      <td>1482</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>141179</td>\n",
              "      <td>0.00</td>\n",
              "      <td>1506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>141179</td>\n",
              "      <td>0.00</td>\n",
              "      <td>1506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>141179</td>\n",
              "      <td>-1000.00</td>\n",
              "      <td>1703</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12022478</th>\n",
              "      <td>3353254</td>\n",
              "      <td>3.00</td>\n",
              "      <td>4786</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12022479</th>\n",
              "      <td>3353254</td>\n",
              "      <td>240.00</td>\n",
              "      <td>4913</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12022480</th>\n",
              "      <td>3353254</td>\n",
              "      <td>-250.00</td>\n",
              "      <td>5196</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12022481</th>\n",
              "      <td>3353254</td>\n",
              "      <td>5.00</td>\n",
              "      <td>5255</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12022482</th>\n",
              "      <td>3353254</td>\n",
              "      <td>-300.00</td>\n",
              "      <td>5291</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12022483</th>\n",
              "      <td>3353254</td>\n",
              "      <td>-400.00</td>\n",
              "      <td>5326</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12022484</th>\n",
              "      <td>3353254</td>\n",
              "      <td>-200.00</td>\n",
              "      <td>5491</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12022485</th>\n",
              "      <td>3353254</td>\n",
              "      <td>240.00</td>\n",
              "      <td>5806</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12022486</th>\n",
              "      <td>3353254</td>\n",
              "      <td>-600.00</td>\n",
              "      <td>5926</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12022487</th>\n",
              "      <td>3353254</td>\n",
              "      <td>-361.00</td>\n",
              "      <td>6106</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12022488</th>\n",
              "      <td>3353254</td>\n",
              "      <td>-361.00</td>\n",
              "      <td>6106</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12022489</th>\n",
              "      <td>3353254</td>\n",
              "      <td>-361.00</td>\n",
              "      <td>6106</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12022490</th>\n",
              "      <td>3353263</td>\n",
              "      <td>0.00</td>\n",
              "      <td>-352</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12022491</th>\n",
              "      <td>3353263</td>\n",
              "      <td>0.00</td>\n",
              "      <td>-352</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12022492</th>\n",
              "      <td>3353263</td>\n",
              "      <td>0.00</td>\n",
              "      <td>24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12022493</th>\n",
              "      <td>3353263</td>\n",
              "      <td>0.00</td>\n",
              "      <td>24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12022494</th>\n",
              "      <td>3353263</td>\n",
              "      <td>16.67</td>\n",
              "      <td>50</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12022495</th>\n",
              "      <td>3353263</td>\n",
              "      <td>125.00</td>\n",
              "      <td>110</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12022496</th>\n",
              "      <td>3353263</td>\n",
              "      <td>125.00</td>\n",
              "      <td>170</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12022497</th>\n",
              "      <td>3353263</td>\n",
              "      <td>125.00</td>\n",
              "      <td>230</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12022498</th>\n",
              "      <td>3353263</td>\n",
              "      <td>136.09</td>\n",
              "      <td>290</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12022499</th>\n",
              "      <td>3353263</td>\n",
              "      <td>155.24</td>\n",
              "      <td>350</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12022500</th>\n",
              "      <td>3353263</td>\n",
              "      <td>155.24</td>\n",
              "      <td>410</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12022501</th>\n",
              "      <td>3353263</td>\n",
              "      <td>155.24</td>\n",
              "      <td>470</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12022502</th>\n",
              "      <td>3353263</td>\n",
              "      <td>155.24</td>\n",
              "      <td>530</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12022503</th>\n",
              "      <td>3353263</td>\n",
              "      <td>155.24</td>\n",
              "      <td>590</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12022504</th>\n",
              "      <td>3353263</td>\n",
              "      <td>155.24</td>\n",
              "      <td>650</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12022505</th>\n",
              "      <td>3353263</td>\n",
              "      <td>155.24</td>\n",
              "      <td>710</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12022506</th>\n",
              "      <td>3353263</td>\n",
              "      <td>159.27</td>\n",
              "      <td>770</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12022507</th>\n",
              "      <td>3353263</td>\n",
              "      <td>163.30</td>\n",
              "      <td>830</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>12022508 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "          f_patientunitstayid  f_nettotal  f_intakeoutputentryoffset\n",
              "0                      141168        0.00                         25\n",
              "1                      141168        0.00                         25\n",
              "2                      141168      500.00                        546\n",
              "3                      141168      500.00                        546\n",
              "4                      141168      500.00                        706\n",
              "5                      141168        0.00                        895\n",
              "6                      141168        0.00                       1066\n",
              "7                      141168      540.00                       1129\n",
              "8                      141168        0.00                       1146\n",
              "9                      141168        0.00                       1146\n",
              "10                     141168     1075.00                       1746\n",
              "11                     141168     1075.00                       1746\n",
              "12                     141168      993.00                       2346\n",
              "13                     141168      993.00                       2346\n",
              "14                     141168      993.00                       2346\n",
              "15                     141168      993.00                       2346\n",
              "16                     141178        0.00                       -276\n",
              "17                     141178        0.00                       -276\n",
              "18                     141179      545.00                        282\n",
              "19                     141179     1000.00                        351\n",
              "20                     141179      100.00                        402\n",
              "21                     141179     -700.00                        678\n",
              "22                     141179      790.00                        822\n",
              "23                     141179     -500.00                        933\n",
              "24                     141179     1800.00                       1302\n",
              "25                     141179     -700.00                       1420\n",
              "26                     141179      720.00                       1482\n",
              "27                     141179        0.00                       1506\n",
              "28                     141179        0.00                       1506\n",
              "29                     141179    -1000.00                       1703\n",
              "...                       ...         ...                        ...\n",
              "12022478              3353254        3.00                       4786\n",
              "12022479              3353254      240.00                       4913\n",
              "12022480              3353254     -250.00                       5196\n",
              "12022481              3353254        5.00                       5255\n",
              "12022482              3353254     -300.00                       5291\n",
              "12022483              3353254     -400.00                       5326\n",
              "12022484              3353254     -200.00                       5491\n",
              "12022485              3353254      240.00                       5806\n",
              "12022486              3353254     -600.00                       5926\n",
              "12022487              3353254     -361.00                       6106\n",
              "12022488              3353254     -361.00                       6106\n",
              "12022489              3353254     -361.00                       6106\n",
              "12022490              3353263        0.00                       -352\n",
              "12022491              3353263        0.00                       -352\n",
              "12022492              3353263        0.00                         24\n",
              "12022493              3353263        0.00                         24\n",
              "12022494              3353263       16.67                         50\n",
              "12022495              3353263      125.00                        110\n",
              "12022496              3353263      125.00                        170\n",
              "12022497              3353263      125.00                        230\n",
              "12022498              3353263      136.09                        290\n",
              "12022499              3353263      155.24                        350\n",
              "12022500              3353263      155.24                        410\n",
              "12022501              3353263      155.24                        470\n",
              "12022502              3353263      155.24                        530\n",
              "12022503              3353263      155.24                        590\n",
              "12022504              3353263      155.24                        650\n",
              "12022505              3353263      155.24                        710\n",
              "12022506              3353263      159.27                        770\n",
              "12022507              3353263      163.30                        830\n",
              "\n",
              "[12022508 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 52
        }
      ]
    },
    {
      "metadata": {
        "id": "9T966n76Rbja",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 894
        },
        "outputId": "8a5c4620-3905-47e8-c530-8a26e4a389f3"
      },
      "cell_type": "code",
      "source": [
        "# Scatter Plot exploratorio de la topologia del balance de fluidos por estancia del paciente\n",
        "consulta.plot(figsize = [19,15], kind='scatter',x='f_patientunitstayid',y='f_intakeoutputentryoffset' )"
      ],
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fd6d3eaab90>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 53
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAABH4AAANcCAYAAAApdmiqAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7fd6d728be50>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "lSWl88j0WN_p",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}