KI_Workshop_Datenanalyse.ipynb

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    "colab": {
      "name": "KI-Workshop_Datenanalyse.ipynb",
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  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "v3IFXRAM7eln"
      },
      "source": [
        "# Datenanalyse für Maschinelles Lernen\n",
        "Die Ausgangsdaten beim maschinellen Lernen sind üblicherweise nicht speziell für das Ziel, welches mit dem dem maschinellen Lernen verfolgt wird, erfasst worden. Daher sind die folgenden Schritte vor dem Einsatz von maschinellen Lernverfahren notwendig (vgl. Frochte 2019, S. 16):\n",
        "1. Verstehen der Anwendungsdomäne\n",
        "2. Analyse der verfügbaren Daten\n",
        "3. Auswahl geeigneter Daten\n",
        "4. Bereinigung der Daten\n",
        "5. Transformation der Daten\n",
        "6. evtl. Reduktion der Daten\n",
        "\n",
        "In dieser Veranstaltung wird detailliert auf Schritt 2 eingegangen und durch Beispiele illustriert. Falls Interesse an den anderen Schritten besteht, können diese gerne in (indivudellen) Veranstaltungen vorgestellt werden."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Gbd4SrpN7elo"
      },
      "source": [
        "## Datenanalyse\n",
        "Für die Datenanalyse liegt uns ein Datensatz der Webseite Kaggle.com als CSV-Datei vor. Bei CSV-Dateien muss man vorsichtig sein, da aus Excel generierte CSV-Dateien in Deutschland andere Trennzeichen verwendet als in anderen Ländern (Trennung zwischen Spalten mit Semikolon und als Dezimaltrennung das Komma). Der Datensatz hier verwendet zur  Trennung aber das Komma und den Punkt.\n",
        "Der Beispieldatensatz stammt aus einem kontinuierlichen Prozess. Dieser besteht aus 3 parallel arbeitende Maschinen in der ersten Stufe. Der Output der einzelnen Maschinen wird durch eine weitere Maschine zusammengefügt. In der zweiten Prozessstufe gibt es nun zwei weitere Maschinen, die parallel den Output der ersten Stufe verarbeiten. \n",
        "Nachfolgend wird der Code zum Laden dieses Datensatzes für die Datenanalyse vorgestellt.\n",
        "\n",
        "---\n",
        "**Importierte Bibliotheken**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6BG2pgzf7elp",
        "outputId": "0974325b-de97-4208-89d2-8a9210d83dbe",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "import pandas as pd\n",
        "!git clone https://github.com/Hahn-Schickard/KI-Trainer\n",
        "!echo $CWD\n",
        "!cp -rf /content/KI-Trainer/* /content/"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "fatal: destination path 'KI-Trainer' already exists and is not an empty directory.\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iQqgKKW-7elp"
      },
      "source": [
        "**Parameter**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JyPi_ZDg7elq"
      },
      "source": [
        "pd.set_option('display.max_rows', None) # Anzahl der Zeilen wird bei der Ausgabe nicht begrenzt\n",
        "pd.set_option('display.max_columns', None) # Anzahl der Spalten wird bei der Ausgabe nicht begrenzt\n",
        "filepath='KI-Workshop_Daten.csv' # Pfad in der die Daten zu finden sind\n",
        "separator=',' # Trennungszeichen zwischen Elementen\n",
        "decimalseparator='.' # Dezimaltrennzeichen"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Yr3Vvz_p7elq"
      },
      "source": [
        "**Code**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FTvUv0bw7elq"
      },
      "source": [
        "rawData = pd.read_csv(filepath, sep=separator, encoding='latin1', decimal=decimalseparator)"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "m7meF87X7elr"
      },
      "source": [
        "---\n",
        "Jetzt stehen die Daten zur Analyse zur Verfügung."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ASXJLmPk7elr"
      },
      "source": [
        "### Struktur Tabelle\n",
        "Zuerst werden die grundlegenden Strukturen der Daten ermittelt. Dazu wird sich die geladene Tabelle mit Hilfe des Befehls display() angeschaut um die verfügbaren Parameter und ihren Datentyp zu identifizieren.\n",
        "\n",
        "---\n",
        "**Code**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Z4uDEEyo7els",
        "outputId": "14d82509-f9da-4053-ced5-02ff6f872621",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "display(rawData.columns.values.tolist()) # Zeigt alle verfügbaren Parameter an"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "['time_stamp',\n",
              " 'AmbientConditions.AmbientHumidity.U.Actual',\n",
              " 'AmbientConditions.AmbientTemperature.U.Actual',\n",
              " 'Machine1.RawMaterial.Property1',\n",
              " 'Machine1.RawMaterial.Property2',\n",
              " 'Machine1.RawMaterial.Property3',\n",
              " 'Machine1.RawMaterial.Property4',\n",
              " 'Machine1.RawMaterialFeederParameter.U.Actual',\n",
              " 'Machine1.Zone1Temperature.C.Actual',\n",
              " 'Machine1.Zone2Temperature.C.Actual',\n",
              " 'Machine1.MotorAmperage.U.Actual',\n",
              " 'Machine1.MotorRPM.C.Actual',\n",
              " 'Machine1.MaterialPressure.U.Actual',\n",
              " 'Machine1.MaterialTemperature.U.Actual',\n",
              " 'Machine1.ExitZoneTemperature.C.Actual',\n",
              " 'Machine2.RawMaterial.Property1',\n",
              " 'Machine2.RawMaterial.Property2',\n",
              " 'Machine2.RawMaterial.Property3',\n",
              " 'Machine2.RawMaterial.Property4',\n",
              " 'Machine2.RawMaterialFeederParameter.U.Actual',\n",
              " 'Machine2.Zone1Temperature.C.Actual',\n",
              " 'Machine2.Zone2Temperature.C.Actual',\n",
              " 'Machine2.MotorAmperage.U.Actual',\n",
              " 'Machine2.MotorRPM.C.Actual',\n",
              " 'Machine2.MaterialPressure.U.Actual',\n",
              " 'Machine2.MaterialTemperature.U.Actual',\n",
              " 'Machine2.ExitZoneTemperature.C.Actual',\n",
              " 'Machine3.RawMaterial.Property1',\n",
              " 'Machine3.RawMaterial.Property2',\n",
              " 'Machine3.RawMaterial.Property3',\n",
              " 'Machine3.RawMaterial.Property4',\n",
              " 'Machine3.RawMaterialFeederParameter.U.Actual',\n",
              " 'Machine3.Zone1Temperature.C.Actual',\n",
              " 'Machine3.Zone2Temperature.C.Actual',\n",
              " 'Machine3.MotorAmperage.U.Actual',\n",
              " 'Machine3.MotorRPM.C.Actual',\n",
              " 'Machine3.MaterialPressure.U.Actual',\n",
              " 'Machine3.MaterialTemperature.U.Actual',\n",
              " 'Machine3.ExitZoneTemperature.C.Actual',\n",
              " 'FirstStage.CombinerOperation.Temperature1.U.Actual',\n",
              " 'FirstStage.CombinerOperation.Temperature2.U.Actual',\n",
              " 'FirstStage.CombinerOperation.Temperature3.C.Actual',\n",
              " 'Stage1.Output.Measurement0.U.Actual',\n",
              " 'Stage1.Output.Measurement0.U.Setpoint',\n",
              " 'Stage1.Output.Measurement1.U.Actual',\n",
              " 'Stage1.Output.Measurement1.U.Setpoint',\n",
              " 'Stage1.Output.Measurement2.U.Actual',\n",
              " 'Stage1.Output.Measurement2.U.Setpoint',\n",
              " 'Stage1.Output.Measurement3.U.Actual',\n",
              " 'Stage1.Output.Measurement3.U.Setpoint',\n",
              " 'Stage1.Output.Measurement4.U.Actual',\n",
              " 'Stage1.Output.Measurement4.U.Setpoint',\n",
              " 'Stage1.Output.Measurement5.U.Actual',\n",
              " 'Stage1.Output.Measurement5.U.Setpoint',\n",
              " 'Stage1.Output.Measurement6.U.Actual',\n",
              " 'Stage1.Output.Measurement6.U.Setpoint',\n",
              " 'Stage1.Output.Measurement7.U.Actual',\n",
              " 'Stage1.Output.Measurement7.U.Setpoint',\n",
              " 'Stage1.Output.Measurement8.U.Actual',\n",
              " 'Stage1.Output.Measurement8.U.Setpoint',\n",
              " 'Stage1.Output.Measurement9.U.Actual',\n",
              " 'Stage1.Output.Measurement9.U.Setpoint',\n",
              " 'Stage1.Output.Measurement10.U.Actual',\n",
              " 'Stage1.Output.Measurement10.U.Setpoint',\n",
              " 'Stage1.Output.Measurement11.U.Actual',\n",
              " 'Stage1.Output.Measurement11.U.Setpoint',\n",
              " 'Stage1.Output.Measurement12.U.Actual',\n",
              " 'Stage1.Output.Measurement12.U.Setpoint',\n",
              " 'Stage1.Output.Measurement13.U.Actual',\n",
              " 'Stage1.Output.Measurement13.U.Setpoint',\n",
              " 'Stage1.Output.Measurement14.U.Actual',\n",
              " 'Stage1.Output.Measurement14.U.Setpoint',\n",
              " 'Machine4.Temperature1.C.Actual',\n",
              " 'Machine4.Temperature2.C.Actual',\n",
              " 'Machine4.Pressure.C.Actual',\n",
              " 'Machine4.Temperature3.C.Actual',\n",
              " 'Machine4.Temperature4.C.Actual',\n",
              " 'Machine4.Temperature5.C.Actual',\n",
              " 'Machine4.ExitTemperature.U.Actual',\n",
              " 'Machine5.Temperature1.C.Actual',\n",
              " 'Machine5.Temperature2.C.Actual',\n",
              " 'Machine5.Temperature3.C.Actual',\n",
              " 'Machine5.Temperature4.C.Actual',\n",
              " 'Machine5.Temperature5.C.Actual',\n",
              " 'Machine5.Temperature6.C.Actual',\n",
              " 'Machine5.ExitTemperature.U.Actual',\n",
              " 'Stage2.Output.Measurement0.U.Actual',\n",
              " 'Stage2.Output.Measurement0.U.Setpoint',\n",
              " 'Stage2.Output.Measurement1.U.Actual',\n",
              " 'Stage2.Output.Measurement1.U.Setpoint',\n",
              " 'Stage2.Output.Measurement2.U.Actual',\n",
              " 'Stage2.Output.Measurement2.U.Setpoint',\n",
              " 'Stage2.Output.Measurement3.U.Actual',\n",
              " 'Stage2.Output.Measurement3.U.Setpoint',\n",
              " 'Stage2.Output.Measurement4.U.Actual',\n",
              " 'Stage2.Output.Measurement4.U.Setpoint',\n",
              " 'Stage2.Output.Measurement5.U.Actual',\n",
              " 'Stage2.Output.Measurement5.U.Setpoint',\n",
              " 'Stage2.Output.Measurement6.U.Actual',\n",
              " 'Stage2.Output.Measurement6.U.Setpoint',\n",
              " 'Stage2.Output.Measurement7.U.Actual',\n",
              " 'Stage2.Output.Measurement7.U.Setpoint',\n",
              " 'Stage2.Output.Measurement8.U.Actual',\n",
              " 'Stage2.Output.Measurement8.U.Setpoint',\n",
              " 'Stage2.Output.Measurement9.U.Actual',\n",
              " 'Stage2.Output.Measurement9.U.Setpoint',\n",
              " 'Stage2.Output.Measurement10.U.Actual',\n",
              " 'Stage2.Output.Measurement10.U.Setpoint',\n",
              " 'Stage2.Output.Measurement11.U.Actual',\n",
              " 'Stage2.Output.Measurement11.U.Setpoint',\n",
              " 'Stage2.Output.Measurement12.U.Actual',\n",
              " 'Stage2.Output.Measurement12.U.Setpoint',\n",
              " 'Stage2.Output.Measurement13.U.Actual',\n",
              " 'Stage2.Output.Measurement13.U.Setpoint',\n",
              " 'Stage2.Output.Measurement14.U.Actual',\n",
              " 'Stage2.Output.Measurement14.U.Setpoint']"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "X6NhIm-z7els",
        "outputId": "ccdf9346-b6fa-4dc2-87e0-0ad3549e0e5a"
      },
      "source": [
        "display(rawData.dtypes) # Zeigt den Datentyp der Parameter an"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "time_stamp                                             object\n",
              "AmbientConditions.AmbientHumidity.U.Actual            float64\n",
              "AmbientConditions.AmbientTemperature.U.Actual         float64\n",
              "Machine1.RawMaterial.Property1                        float64\n",
              "Machine1.RawMaterial.Property2                          int64\n",
              "Machine1.RawMaterial.Property3                        float64\n",
              "Machine1.RawMaterial.Property4                          int64\n",
              "Machine1.RawMaterialFeederParameter.U.Actual          float64\n",
              "Machine1.Zone1Temperature.C.Actual                    float64\n",
              "Machine1.Zone2Temperature.C.Actual                    float64\n",
              "Machine1.MotorAmperage.U.Actual                       float64\n",
              "Machine1.MotorRPM.C.Actual                            float64\n",
              "Machine1.MaterialPressure.U.Actual                    float64\n",
              "Machine1.MaterialTemperature.U.Actual                 float64\n",
              "Machine1.ExitZoneTemperature.C.Actual                 float64\n",
              "Machine2.RawMaterial.Property1                        float64\n",
              "Machine2.RawMaterial.Property2                          int64\n",
              "Machine2.RawMaterial.Property3                        float64\n",
              "Machine2.RawMaterial.Property4                          int64\n",
              "Machine2.RawMaterialFeederParameter.U.Actual          float64\n",
              "Machine2.Zone1Temperature.C.Actual                    float64\n",
              "Machine2.Zone2Temperature.C.Actual                    float64\n",
              "Machine2.MotorAmperage.U.Actual                       float64\n",
              "Machine2.MotorRPM.C.Actual                            float64\n",
              "Machine2.MaterialPressure.U.Actual                    float64\n",
              "Machine2.MaterialTemperature.U.Actual                 float64\n",
              "Machine2.ExitZoneTemperature.C.Actual                 float64\n",
              "Machine3.RawMaterial.Property1                        float64\n",
              "Machine3.RawMaterial.Property2                          int64\n",
              "Machine3.RawMaterial.Property3                        float64\n",
              "Machine3.RawMaterial.Property4                          int64\n",
              "Machine3.RawMaterialFeederParameter.U.Actual          float64\n",
              "Machine3.Zone1Temperature.C.Actual                    float64\n",
              "Machine3.Zone2Temperature.C.Actual                    float64\n",
              "Machine3.MotorAmperage.U.Actual                       float64\n",
              "Machine3.MotorRPM.C.Actual                            float64\n",
              "Machine3.MaterialPressure.U.Actual                    float64\n",
              "Machine3.MaterialTemperature.U.Actual                 float64\n",
              "Machine3.ExitZoneTemperature.C.Actual                 float64\n",
              "FirstStage.CombinerOperation.Temperature1.U.Actual    float64\n",
              "FirstStage.CombinerOperation.Temperature2.U.Actual    float64\n",
              "FirstStage.CombinerOperation.Temperature3.C.Actual    float64\n",
              "Stage1.Output.Measurement0.U.Actual                   float64\n",
              "Stage1.Output.Measurement0.U.Setpoint                 float64\n",
              "Stage1.Output.Measurement1.U.Actual                   float64\n",
              "Stage1.Output.Measurement1.U.Setpoint                 float64\n",
              "Stage1.Output.Measurement2.U.Actual                   float64\n",
              "Stage1.Output.Measurement2.U.Setpoint                 float64\n",
              "Stage1.Output.Measurement3.U.Actual                   float64\n",
              "Stage1.Output.Measurement3.U.Setpoint                 float64\n",
              "Stage1.Output.Measurement4.U.Actual                   float64\n",
              "Stage1.Output.Measurement4.U.Setpoint                 float64\n",
              "Stage1.Output.Measurement5.U.Actual                   float64\n",
              "Stage1.Output.Measurement5.U.Setpoint                 float64\n",
              "Stage1.Output.Measurement6.U.Actual                   float64\n",
              "Stage1.Output.Measurement6.U.Setpoint                 float64\n",
              "Stage1.Output.Measurement7.U.Actual                   float64\n",
              "Stage1.Output.Measurement7.U.Setpoint                 float64\n",
              "Stage1.Output.Measurement8.U.Actual                   float64\n",
              "Stage1.Output.Measurement8.U.Setpoint                 float64\n",
              "Stage1.Output.Measurement9.U.Actual                   float64\n",
              "Stage1.Output.Measurement9.U.Setpoint                 float64\n",
              "Stage1.Output.Measurement10.U.Actual                  float64\n",
              "Stage1.Output.Measurement10.U.Setpoint                float64\n",
              "Stage1.Output.Measurement11.U.Actual                  float64\n",
              "Stage1.Output.Measurement11.U.Setpoint                float64\n",
              "Stage1.Output.Measurement12.U.Actual                  float64\n",
              "Stage1.Output.Measurement12.U.Setpoint                float64\n",
              "Stage1.Output.Measurement13.U.Actual                  float64\n",
              "Stage1.Output.Measurement13.U.Setpoint                float64\n",
              "Stage1.Output.Measurement14.U.Actual                  float64\n",
              "Stage1.Output.Measurement14.U.Setpoint                float64\n",
              "Machine4.Temperature1.C.Actual                        float64\n",
              "Machine4.Temperature2.C.Actual                        float64\n",
              "Machine4.Pressure.C.Actual                            float64\n",
              "Machine4.Temperature3.C.Actual                        float64\n",
              "Machine4.Temperature4.C.Actual                        float64\n",
              "Machine4.Temperature5.C.Actual                        float64\n",
              "Machine4.ExitTemperature.U.Actual                     float64\n",
              "Machine5.Temperature1.C.Actual                        float64\n",
              "Machine5.Temperature2.C.Actual                        float64\n",
              "Machine5.Temperature3.C.Actual                        float64\n",
              "Machine5.Temperature4.C.Actual                        float64\n",
              "Machine5.Temperature5.C.Actual                        float64\n",
              "Machine5.Temperature6.C.Actual                        float64\n",
              "Machine5.ExitTemperature.U.Actual                     float64\n",
              "Stage2.Output.Measurement0.U.Actual                   float64\n",
              "Stage2.Output.Measurement0.U.Setpoint                 float64\n",
              "Stage2.Output.Measurement1.U.Actual                   float64\n",
              "Stage2.Output.Measurement1.U.Setpoint                 float64\n",
              "Stage2.Output.Measurement2.U.Actual                   float64\n",
              "Stage2.Output.Measurement2.U.Setpoint                   int64\n",
              "Stage2.Output.Measurement3.U.Actual                   float64\n",
              "Stage2.Output.Measurement3.U.Setpoint                 float64\n",
              "Stage2.Output.Measurement4.U.Actual                   float64\n",
              "Stage2.Output.Measurement4.U.Setpoint                 float64\n",
              "Stage2.Output.Measurement5.U.Actual                   float64\n",
              "Stage2.Output.Measurement5.U.Setpoint                 float64\n",
              "Stage2.Output.Measurement6.U.Actual                   float64\n",
              "Stage2.Output.Measurement6.U.Setpoint                 float64\n",
              "Stage2.Output.Measurement7.U.Actual                   float64\n",
              "Stage2.Output.Measurement7.U.Setpoint                 float64\n",
              "Stage2.Output.Measurement8.U.Actual                   float64\n",
              "Stage2.Output.Measurement8.U.Setpoint                 float64\n",
              "Stage2.Output.Measurement9.U.Actual                   float64\n",
              "Stage2.Output.Measurement9.U.Setpoint                 float64\n",
              "Stage2.Output.Measurement10.U.Actual                  float64\n",
              "Stage2.Output.Measurement10.U.Setpoint                float64\n",
              "Stage2.Output.Measurement11.U.Actual                  float64\n",
              "Stage2.Output.Measurement11.U.Setpoint                float64\n",
              "Stage2.Output.Measurement12.U.Actual                  float64\n",
              "Stage2.Output.Measurement12.U.Setpoint                float64\n",
              "Stage2.Output.Measurement13.U.Actual                  float64\n",
              "Stage2.Output.Measurement13.U.Setpoint                float64\n",
              "Stage2.Output.Measurement14.U.Actual                  float64\n",
              "Stage2.Output.Measurement14.U.Setpoint                float64\n",
              "dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Iu-7qMm67elt",
        "outputId": "be8fba7d-0902-4aa6-d301-08446d6e7c6c"
      },
      "source": [
        "display(rawData.isnull().sum()) # Zeigt die Anzahl ungültiger Datensätze für einzelne Parameter an"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "time_stamp                                            0\n",
              "AmbientConditions.AmbientHumidity.U.Actual            3\n",
              "AmbientConditions.AmbientTemperature.U.Actual         1\n",
              "Machine1.RawMaterial.Property1                        1\n",
              "Machine1.RawMaterial.Property2                        0\n",
              "Machine1.RawMaterial.Property3                        0\n",
              "Machine1.RawMaterial.Property4                        0\n",
              "Machine1.RawMaterialFeederParameter.U.Actual          0\n",
              "Machine1.Zone1Temperature.C.Actual                    0\n",
              "Machine1.Zone2Temperature.C.Actual                    1\n",
              "Machine1.MotorAmperage.U.Actual                       0\n",
              "Machine1.MotorRPM.C.Actual                            0\n",
              "Machine1.MaterialPressure.U.Actual                    0\n",
              "Machine1.MaterialTemperature.U.Actual                 0\n",
              "Machine1.ExitZoneTemperature.C.Actual                 0\n",
              "Machine2.RawMaterial.Property1                        0\n",
              "Machine2.RawMaterial.Property2                        0\n",
              "Machine2.RawMaterial.Property3                        0\n",
              "Machine2.RawMaterial.Property4                        0\n",
              "Machine2.RawMaterialFeederParameter.U.Actual          0\n",
              "Machine2.Zone1Temperature.C.Actual                    0\n",
              "Machine2.Zone2Temperature.C.Actual                    0\n",
              "Machine2.MotorAmperage.U.Actual                       0\n",
              "Machine2.MotorRPM.C.Actual                            0\n",
              "Machine2.MaterialPressure.U.Actual                    0\n",
              "Machine2.MaterialTemperature.U.Actual                 0\n",
              "Machine2.ExitZoneTemperature.C.Actual                 0\n",
              "Machine3.RawMaterial.Property1                        0\n",
              "Machine3.RawMaterial.Property2                        0\n",
              "Machine3.RawMaterial.Property3                        0\n",
              "Machine3.RawMaterial.Property4                        0\n",
              "Machine3.RawMaterialFeederParameter.U.Actual          0\n",
              "Machine3.Zone1Temperature.C.Actual                    0\n",
              "Machine3.Zone2Temperature.C.Actual                    0\n",
              "Machine3.MotorAmperage.U.Actual                       0\n",
              "Machine3.MotorRPM.C.Actual                            0\n",
              "Machine3.MaterialPressure.U.Actual                    0\n",
              "Machine3.MaterialTemperature.U.Actual                 0\n",
              "Machine3.ExitZoneTemperature.C.Actual                 0\n",
              "FirstStage.CombinerOperation.Temperature1.U.Actual    0\n",
              "FirstStage.CombinerOperation.Temperature2.U.Actual    0\n",
              "FirstStage.CombinerOperation.Temperature3.C.Actual    0\n",
              "Stage1.Output.Measurement0.U.Actual                   0\n",
              "Stage1.Output.Measurement0.U.Setpoint                 0\n",
              "Stage1.Output.Measurement1.U.Actual                   0\n",
              "Stage1.Output.Measurement1.U.Setpoint                 0\n",
              "Stage1.Output.Measurement2.U.Actual                   0\n",
              "Stage1.Output.Measurement2.U.Setpoint                 0\n",
              "Stage1.Output.Measurement3.U.Actual                   0\n",
              "Stage1.Output.Measurement3.U.Setpoint                 0\n",
              "Stage1.Output.Measurement4.U.Actual                   0\n",
              "Stage1.Output.Measurement4.U.Setpoint                 0\n",
              "Stage1.Output.Measurement5.U.Actual                   0\n",
              "Stage1.Output.Measurement5.U.Setpoint                 0\n",
              "Stage1.Output.Measurement6.U.Actual                   0\n",
              "Stage1.Output.Measurement6.U.Setpoint                 0\n",
              "Stage1.Output.Measurement7.U.Actual                   0\n",
              "Stage1.Output.Measurement7.U.Setpoint                 0\n",
              "Stage1.Output.Measurement8.U.Actual                   0\n",
              "Stage1.Output.Measurement8.U.Setpoint                 0\n",
              "Stage1.Output.Measurement9.U.Actual                   0\n",
              "Stage1.Output.Measurement9.U.Setpoint                 0\n",
              "Stage1.Output.Measurement10.U.Actual                  0\n",
              "Stage1.Output.Measurement10.U.Setpoint                0\n",
              "Stage1.Output.Measurement11.U.Actual                  0\n",
              "Stage1.Output.Measurement11.U.Setpoint                0\n",
              "Stage1.Output.Measurement12.U.Actual                  0\n",
              "Stage1.Output.Measurement12.U.Setpoint                0\n",
              "Stage1.Output.Measurement13.U.Actual                  0\n",
              "Stage1.Output.Measurement13.U.Setpoint                0\n",
              "Stage1.Output.Measurement14.U.Actual                  0\n",
              "Stage1.Output.Measurement14.U.Setpoint                0\n",
              "Machine4.Temperature1.C.Actual                        0\n",
              "Machine4.Temperature2.C.Actual                        0\n",
              "Machine4.Pressure.C.Actual                            0\n",
              "Machine4.Temperature3.C.Actual                        0\n",
              "Machine4.Temperature4.C.Actual                        0\n",
              "Machine4.Temperature5.C.Actual                        0\n",
              "Machine4.ExitTemperature.U.Actual                     0\n",
              "Machine5.Temperature1.C.Actual                        0\n",
              "Machine5.Temperature2.C.Actual                        0\n",
              "Machine5.Temperature3.C.Actual                        0\n",
              "Machine5.Temperature4.C.Actual                        0\n",
              "Machine5.Temperature5.C.Actual                        0\n",
              "Machine5.Temperature6.C.Actual                        0\n",
              "Machine5.ExitTemperature.U.Actual                     0\n",
              "Stage2.Output.Measurement0.U.Actual                   0\n",
              "Stage2.Output.Measurement0.U.Setpoint                 0\n",
              "Stage2.Output.Measurement1.U.Actual                   0\n",
              "Stage2.Output.Measurement1.U.Setpoint                 0\n",
              "Stage2.Output.Measurement2.U.Actual                   0\n",
              "Stage2.Output.Measurement2.U.Setpoint                 0\n",
              "Stage2.Output.Measurement3.U.Actual                   0\n",
              "Stage2.Output.Measurement3.U.Setpoint                 0\n",
              "Stage2.Output.Measurement4.U.Actual                   0\n",
              "Stage2.Output.Measurement4.U.Setpoint                 0\n",
              "Stage2.Output.Measurement5.U.Actual                   0\n",
              "Stage2.Output.Measurement5.U.Setpoint                 0\n",
              "Stage2.Output.Measurement6.U.Actual                   0\n",
              "Stage2.Output.Measurement6.U.Setpoint                 0\n",
              "Stage2.Output.Measurement7.U.Actual                   0\n",
              "Stage2.Output.Measurement7.U.Setpoint                 0\n",
              "Stage2.Output.Measurement8.U.Actual                   0\n",
              "Stage2.Output.Measurement8.U.Setpoint                 0\n",
              "Stage2.Output.Measurement9.U.Actual                   0\n",
              "Stage2.Output.Measurement9.U.Setpoint                 0\n",
              "Stage2.Output.Measurement10.U.Actual                  0\n",
              "Stage2.Output.Measurement10.U.Setpoint                0\n",
              "Stage2.Output.Measurement11.U.Actual                  0\n",
              "Stage2.Output.Measurement11.U.Setpoint                0\n",
              "Stage2.Output.Measurement12.U.Actual                  0\n",
              "Stage2.Output.Measurement12.U.Setpoint                0\n",
              "Stage2.Output.Measurement13.U.Actual                  0\n",
              "Stage2.Output.Measurement13.U.Setpoint                0\n",
              "Stage2.Output.Measurement14.U.Actual                  0\n",
              "Stage2.Output.Measurement14.U.Setpoint                0\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oiTnAtJg7elt",
        "outputId": "3398a936-cc95-45fc-b0c6-4f12bf5f9a73"
      },
      "source": [
        "pd.set_option('display.max_rows', 11) # Anzahl der Zeilen wird bei der Ausgabe auf 11 begrenzt\n",
        "pd.set_option('display.max_columns', 11) # Anzahl der Spalten wird bei der Ausgabe auf 11 begrenzt\n",
        "display(rawData) # Darstellung einer verkürzten Tabelle "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>time_stamp</th>\n",
              "      <th>AmbientConditions.AmbientHumidity.U.Actual</th>\n",
              "      <th>AmbientConditions.AmbientTemperature.U.Actual</th>\n",
              "      <th>Machine1.RawMaterial.Property1</th>\n",
              "      <th>Machine1.RawMaterial.Property2</th>\n",
              "      <th>...</th>\n",
              "      <th>Stage2.Output.Measurement12.U.Setpoint</th>\n",
              "      <th>Stage2.Output.Measurement13.U.Actual</th>\n",
              "      <th>Stage2.Output.Measurement13.U.Setpoint</th>\n",
              "      <th>Stage2.Output.Measurement14.U.Actual</th>\n",
              "      <th>Stage2.Output.Measurement14.U.Setpoint</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2019-03-06 10:52:33</td>\n",
              "      <td>NaN</td>\n",
              "      <td>23.53</td>\n",
              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2019-03-06 10:52:34</td>\n",
              "      <td>17.24</td>\n",
              "      <td>23.53</td>\n",
              "      <td>11.54</td>\n",
              "      <td>200</td>\n",
              "      <td>...</td>\n",
              "      <td>1.85</td>\n",
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              "      <td>0.00</td>\n",
              "      <td>11.71</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2019-03-06 10:52:35</td>\n",
              "      <td>17.24</td>\n",
              "      <td>23.53</td>\n",
              "      <td>11.54</td>\n",
              "      <td>200</td>\n",
              "      <td>...</td>\n",
              "      <td>1.85</td>\n",
              "      <td>0.00</td>\n",
              "      <td>2.89</td>\n",
              "      <td>0.00</td>\n",
              "      <td>11.71</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2019-03-06 10:52:36</td>\n",
              "      <td>17.24</td>\n",
              "      <td>23.53</td>\n",
              "      <td>11.54</td>\n",
              "      <td>200</td>\n",
              "      <td>...</td>\n",
              "      <td>1.85</td>\n",
              "      <td>0.00</td>\n",
              "      <td>2.89</td>\n",
              "      <td>0.00</td>\n",
              "      <td>11.71</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2019-03-06 10:52:37</td>\n",
              "      <td>17.24</td>\n",
              "      <td>23.53</td>\n",
              "      <td>11.54</td>\n",
              "      <td>200</td>\n",
              "      <td>...</td>\n",
              "      <td>1.85</td>\n",
              "      <td>0.00</td>\n",
              "      <td>2.89</td>\n",
              "      <td>0.00</td>\n",
              "      <td>11.71</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14083</th>\n",
              "      <td>2019-03-06 14:47:16</td>\n",
              "      <td>13.84</td>\n",
              "      <td>24.43</td>\n",
              "      <td>12.22</td>\n",
              "      <td>201</td>\n",
              "      <td>...</td>\n",
              "      <td>1.85</td>\n",
              "      <td>3.80</td>\n",
              "      <td>2.89</td>\n",
              "      <td>7.56</td>\n",
              "      <td>11.71</td>\n",
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              "    <tr>\n",
              "      <th>14084</th>\n",
              "      <td>2019-03-06 14:47:17</td>\n",
              "      <td>13.84</td>\n",
              "      <td>24.43</td>\n",
              "      <td>12.22</td>\n",
              "      <td>201</td>\n",
              "      <td>...</td>\n",
              "      <td>1.85</td>\n",
              "      <td>3.79</td>\n",
              "      <td>2.89</td>\n",
              "      <td>7.76</td>\n",
              "      <td>11.71</td>\n",
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              "    <tr>\n",
              "      <th>14085</th>\n",
              "      <td>2019-03-06 14:47:18</td>\n",
              "      <td>13.84</td>\n",
              "      <td>24.43</td>\n",
              "      <td>12.22</td>\n",
              "      <td>201</td>\n",
              "      <td>...</td>\n",
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              "      <td>3.83</td>\n",
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              "      <td>7.66</td>\n",
              "      <td>11.71</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14086</th>\n",
              "      <td>2019-03-06 14:47:19</td>\n",
              "      <td>13.84</td>\n",
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              "    <tr>\n",
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              "      <td>7.87</td>\n",
              "      <td>11.71</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>14088 rows × 116 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                time_stamp  AmbientConditions.AmbientHumidity.U.Actual  \\\n",
              "0      2019-03-06 10:52:33                                         NaN   \n",
              "1      2019-03-06 10:52:34                                       17.24   \n",
              "2      2019-03-06 10:52:35                                       17.24   \n",
              "3      2019-03-06 10:52:36                                       17.24   \n",
              "4      2019-03-06 10:52:37                                       17.24   \n",
              "...                    ...                                         ...   \n",
              "14083  2019-03-06 14:47:16                                       13.84   \n",
              "14084  2019-03-06 14:47:17                                       13.84   \n",
              "14085  2019-03-06 14:47:18                                       13.84   \n",
              "14086  2019-03-06 14:47:19                                       13.84   \n",
              "14087  2019-03-06 14:47:20                                       13.84   \n",
              "\n",
              "       AmbientConditions.AmbientTemperature.U.Actual  \\\n",
              "0                                              23.53   \n",
              "1                                              23.53   \n",
              "2                                              23.53   \n",
              "3                                              23.53   \n",
              "4                                              23.53   \n",
              "...                                              ...   \n",
              "14083                                          24.43   \n",
              "14084                                          24.43   \n",
              "14085                                          24.43   \n",
              "14086                                          24.43   \n",
              "14087                                          24.43   \n",
              "\n",
              "       Machine1.RawMaterial.Property1  Machine1.RawMaterial.Property2  ...  \\\n",
              "0                                 NaN                             200  ...   \n",
              "1                               11.54                             200  ...   \n",
              "2                               11.54                             200  ...   \n",
              "3                               11.54                             200  ...   \n",
              "4                               11.54                             200  ...   \n",
              "...                               ...                             ...  ...   \n",
              "14083                           12.22                             201  ...   \n",
              "14084                           12.22                             201  ...   \n",
              "14085                           12.22                             201  ...   \n",
              "14086                           12.22                             201  ...   \n",
              "14087                           12.22                             201  ...   \n",
              "\n",
              "       Stage2.Output.Measurement12.U.Setpoint  \\\n",
              "0                                        1.85   \n",
              "1                                        1.85   \n",
              "2                                        1.85   \n",
              "3                                        1.85   \n",
              "4                                        1.85   \n",
              "...                                       ...   \n",
              "14083                                    1.85   \n",
              "14084                                    1.85   \n",
              "14085                                    1.85   \n",
              "14086                                    1.85   \n",
              "14087                                    1.85   \n",
              "\n",
              "       Stage2.Output.Measurement13.U.Actual  \\\n",
              "0                                      0.00   \n",
              "1                                      0.00   \n",
              "2                                      0.00   \n",
              "3                                      0.00   \n",
              "4                                      0.00   \n",
              "...                                     ...   \n",
              "14083                                  3.80   \n",
              "14084                                  3.79   \n",
              "14085                                  3.83   \n",
              "14086                                  3.83   \n",
              "14087                                  3.83   \n",
              "\n",
              "       Stage2.Output.Measurement13.U.Setpoint  \\\n",
              "0                                        2.89   \n",
              "1                                        2.89   \n",
              "2                                        2.89   \n",
              "3                                        2.89   \n",
              "4                                        2.89   \n",
              "...                                       ...   \n",
              "14083                                    2.89   \n",
              "14084                                    2.89   \n",
              "14085                                    2.89   \n",
              "14086                                    2.89   \n",
              "14087                                    2.89   \n",
              "\n",
              "       Stage2.Output.Measurement14.U.Actual  \\\n",
              "0                                      0.00   \n",
              "1                                      0.00   \n",
              "2                                      0.00   \n",
              "3                                      0.00   \n",
              "4                                      0.00   \n",
              "...                                     ...   \n",
              "14083                                  7.56   \n",
              "14084                                  7.76   \n",
              "14085                                  7.66   \n",
              "14086                                  7.87   \n",
              "14087                                  7.87   \n",
              "\n",
              "       Stage2.Output.Measurement14.U.Setpoint  \n",
              "0                                       11.71  \n",
              "1                                       11.71  \n",
              "2                                       11.71  \n",
              "3                                       11.71  \n",
              "4                                       11.71  \n",
              "...                                       ...  \n",
              "14083                                   11.71  \n",
              "14084                                   11.71  \n",
              "14085                                   11.71  \n",
              "14086                                   11.71  \n",
              "14087                                   11.71  \n",
              "\n",
              "[14088 rows x 116 columns]"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LlCxmSph7elu"
      },
      "source": [
        "Diese vier Befehle geben einem einen ersten Überblick über die Daten:  \n",
        "1. Der Befehl display(rawData.columns.values.tolist()) listet die Namen aller Spalten auf. Hilfreich ist es für die Datenanalyse kryptische Spaltenbezeichnungen umzubenennen (z.B. 'data21' in 'Umdrehungsgeschwindigkeit'), wobei dies entsprechend dokumentiert werden sollte.\n",
        "2. Der Befehl display(rawData.dtypes) gibt die Datentypen für alle Spalten an. Damit kann man schnell feststellen, ob man Datentypen umcodieren muss (z.B. String in Int).\n",
        "3. Der Befehl display(rawData.isnull().sum()) summiert für jede Spalte leere Einträge auf. Falsche Einträge können so zwar nicht erkannt werden. Die Auflistung unvollständiger Datensätze hilft jedoch bei der späteren Datenaufbereitung. Bei vielen fehlerhaften Datensätze hat man die Wahl entsprechende Spalten mit vielen fehlenden Datensätzen nicht zu berücksichtigen (Schritt 3 Auswahl geeigneter Daten) oder mehr Aufwand in Schritt 4 Bereinigung der Daten in Kauf nehmen. \n",
        "4. Der Befehl display(rawData) zeigt die kompletten Daten an. Man sollte die Anzahl der angezeigten Spalten und Zeilen aber begrenzen.\n",
        "\n",
        "---"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BzJXM0bu7elu"
      },
      "source": [
        "### Struktur Daten\n",
        "Nachdem wir die Struktur der Tabelle verstanden haben, müssen wir die Struktur der Parameter identifizieren. Was dabei wichtig ist, sind das Wissen über die Verteilung der Daten, Ausreißer, Median, Mittelwert, Quantilen sowie Minimal- und Maximalwert. Neben der Produktionstabelle wird ein weiteres Beispiel mit bekannten Beziehungen präsentiert. Bei der Reihenmessung SizeGermany (Frauen) wurden unter anderem das Gewicht und die Körpergröße erfasst und daraus der BMI berechnet (BMI = KH/(Gewicht)^2). \n",
        "\n",
        "---\n",
        "**Importierte Bibliotheken**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DhsjOAJR7elv"
      },
      "source": [
        "import matplotlib.pyplot as plt"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "b4TZDECI7elv"
      },
      "source": [
        "**Parameter**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vEievFB67elv"
      },
      "source": [
        "columns=['Machine4.Pressure.C.Actual', \n",
        "         'AmbientConditions.AmbientTemperature.U.Actual', \n",
        "         'FirstStage.CombinerOperation.Temperature1.U.Actual']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sjrs72_g7elv"
      },
      "source": [
        "**Code**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wbmjFrY57elw",
        "outputId": "d3bb3ea4-0f5b-4f93-cfd0-bfb559fb30c1"
      },
      "source": [
        "print('Median')\n",
        "display(rawData[columns].median()) # Median berechnen\n",
        "print('')\n",
        "\n",
        "print('Mittelwert')\n",
        "display(rawData[columns].mean()) # Mittelwert berechnen"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Median\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Machine4.Pressure.C.Actual                             17.00\n",
              "AmbientConditions.AmbientTemperature.U.Actual          23.93\n",
              "FirstStage.CombinerOperation.Temperature1.U.Actual    105.50\n",
              "dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "Mittelwert\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Machine4.Pressure.C.Actual                             17.226269\n",
              "AmbientConditions.AmbientTemperature.U.Actual          23.843629\n",
              "FirstStage.CombinerOperation.Temperature1.U.Actual    108.917970\n",
              "dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_n2moxJT7elw"
      },
      "source": [
        "Hier das Beispiel für den BMI\n",
        "\n",
        "**Parameter**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mUjRCfgc7elw"
      },
      "source": [
        "filepath2='KI-Workshop_Daten2.csv' # Pfad in der die Daten zu finden sind\n",
        "separator=';' # Trennungszeichen zwischen Elementen\n",
        "decimalseparator=',' # Dezimaltrennzeichen\n",
        "\n",
        "columns2=['BMI',\n",
        "         'Gewicht',\n",
        "         'KH']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7J0-xrO47elw"
      },
      "source": [
        "**Code**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Vf70wZlA7elx",
        "outputId": "a5a8f937-ba4c-4b57-b7a8-37564b623fd3"
      },
      "source": [
        "rawData2 = pd.read_csv(filepath2, sep=separator, encoding='latin1', decimal=decimalseparator)\n",
        "print('Median')\n",
        "display(rawData2[columns2].median()) # Median berechnen\n",
        "print('')\n",
        "\n",
        "print('Mittelwert')\n",
        "display(rawData2[columns2].mean()) # Mittelwert berechnen"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Median\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "BMI         26.3205\n",
              "Gewicht     68.9000\n",
              "KH         161.4000\n",
              "dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "Mittelwert\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "BMI         27.819662\n",
              "Gewicht     72.066716\n",
              "KH         159.678063\n",
              "dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JMm2rQb97elx"
      },
      "source": [
        "Interessant ist auch die Verteilung für die einzelnen Werte. Dabei hilft der Boxplot, in dem er visuell hilft Ausreißer zu entdecken.\n",
        "\n",
        "**Code**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HDunXRmQ7elx",
        "outputId": "4779e7a2-455e-472b-ff7e-0180e6963ca1"
      },
      "source": [
        "fig, axs = plt.subplots(nrows=1, ncols=3, figsize=(16,10), constrained_layout=True) # Grafik bestehend aus 3 Teilgrafiken in 3 Spalten und einer Zeile erstellen\n",
        "fig.suptitle('Boxplots', fontsize=16) # Titel für die Grafiken festlegen\n",
        "for i, ax in enumerate(axs.flat): # Iterieren über die 3 Teilgrafiken \n",
        "    rawData.boxplot(column=columns[i], vert=True, ax=ax) # Erstellung eines Boxplots für die 3 Tabellenspalten"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x720 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VOrTA7ZR7ely"
      },
      "source": [
        "Hier die Darstellung für die Parameter des BMI-Beispiels.\n",
        "\n",
        "**Code**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9DglDOyM7ely",
        "outputId": "a3eb1c14-a899-4d00-f678-4649e44ee753"
      },
      "source": [
        "fig, axs = plt.subplots(nrows=1, ncols=3, figsize=(16,10), constrained_layout=True) # Grafik bestehend aus 3 Teilgrafiken in 3 Spalten und einer Zeile erstellen\n",
        "fig.suptitle('Boxplots', fontsize=16) # Titel für die Grafiken festlegen\n",
        "for i, ax in enumerate(axs.flat): # Iterieren über die 3 Teilgrafiken \n",
        "    rawData2.boxplot(column=columns2[i], vert=True, ax=ax) # Erstellung eines Boxplots für die 3 Tabellenspalten"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x720 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5NNBnFkp7elz"
      },
      "source": [
        "Ein weitere Darstellungsvariante ist die Kerndichteschätzung. Damit kann man beispielsweise ermitteln, ob die Daten einer Normalverteilung folgen oder nicht. Dies ist für einige KI-Ansätze wichtig zu wissen, da im Bedarfsfall die Daten transformiert werden müssen.\n",
        "\n",
        "**Code**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_KhjVoye7elz",
        "outputId": "f9fbc8df-cdda-47d0-b38c-7b1667e3f54d"
      },
      "source": [
        "fig, axs = plt.subplots(nrows=1, ncols=3, figsize=(16,10), constrained_layout=True) # Grafik bestehend aus 3 Teilgrafiken in 3 Spalten und einer Zeile erstellen\n",
        "fig.suptitle('Grafik für Kerndichteschätzung', fontsize=16) # Titel für die Grafiken festlegen\n",
        "for i, ax in enumerate(axs.flat): # Iterieren über die 3 Teilgrafiken\n",
        "    ax.title.set_text(columns[i]) # Titel für die Teilgrafiken festlegen\n",
        "    rawData[columns[i]].plot.kde(ax=ax) # Grafik für Kerndichteschätzung erstellen"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x720 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qAp2yAje7el0"
      },
      "source": [
        "Hier die Darstellung für die Parameter des BMI-Beispiels.\n",
        "\n",
        "**Code**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2NF2z7Qh7el0",
        "outputId": "c16452ff-830d-4cc3-d399-06de1519ff3b"
      },
      "source": [
        "fig, axs = plt.subplots(nrows=1, ncols=3, figsize=(16,10), constrained_layout=True) # Grafik bestehend aus 3 Teilgrafiken in 3 Spalten und einer Zeile erstellen\n",
        "fig.suptitle('Grafik für Kerndichteschätzung', fontsize=16) # Titel für die Grafiken festlegen\n",
        "for i, ax in enumerate(axs.flat): # Iterieren über die 3 Teilgrafiken\n",
        "    ax.title.set_text(columns2[i]) # Titel für die Teilgrafiken festlegen\n",
        "    rawData2[columns2[i]].plot.kde(ax=ax) # Grafik für Kerndichteschätzung erstellen"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x720 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "n9ILz3Pu7el1"
      },
      "source": [
        "---"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7N1DMP537el1"
      },
      "source": [
        "### Struktur zwischen Daten\n",
        "Nachdem wir jetzt die Struktur der einzelnen Parameter kennen, geht es jetzt um die Beziehungen zwischen den einzelnen Parametern. Die Korrelationsmatrix bietet eine einfache Möglichkeit um lineare Zusammenhänge zwischen Parametern zu identifizieren.\n",
        "\n",
        "---\n",
        "**Importierte Bibliotheken**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "u94nd3wP7el1"
      },
      "source": [
        "import pandas as pd\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7kYtlca77el1"
      },
      "source": [
        "**Parameter**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "E7I-pY067el2"
      },
      "source": [
        "columns=['Machine1.RawMaterial.Property1',\n",
        "         'Machine1.RawMaterial.Property2',\n",
        "         'Machine1.RawMaterial.Property3',\n",
        "         'Machine1.RawMaterial.Property4',\n",
        "         'Stage2.Output.Measurement0.U.Actual']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yUmFtmHq7el2"
      },
      "source": [
        "**Code**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LtKfxV2q7el2",
        "outputId": "a99dfd22-8725-4983-a38f-642caf1b51ce"
      },
      "source": [
        "plt.figure(figsize=(10, 10), constrained_layout=True)\n",
        "corrSet = pd.DataFrame(rawData[columns])\n",
        "heatmap = sns.heatmap(corrSet.corr(),\n",
        "    annot=True, linewidth=0.2)\n",
        "plt.title('Korrelationsmatrix', fontsize=16); # Titel für die Grafiken festlegen, Strichpunkt unterdrückt Textausgabe von letztem Kommando"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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n/5Fr/+HjptOxWT0AZi9aToPa1SheLI0iqSk0PqwGX03Kfdv9TdMOzRn9/igAZkz6nRLpJTmoYpmYfikpKVx6d1def2RQjvbqdWsw9dufAVg4awEVqlekdPmD8jzugmzarPnUqFSO6hXLklakCB2Pa8Don37N0ccMNmzcjLuzYdMWSpcsTmpKCmZGiQOKAZCRmUlGRhZg+XAUBU/xBoex5a+FbJ23GLZmsPazsZRql/OTrMyVa9g0dQaeEVsusXH8NDLXrNtb4e59WVl5+yiECsMEG2A4cGr4/ELg7ewVZtbMzL4zs0nh18PD9lQze9LMpprZFDO7PmK868Ps5FQzOyLs39XM+obPB5nZs+F4syMzmGZ2m5mND8e8P7vd3ccCu5yacvcVwEygSjjuveG408xsgAUqmtlP4fqGYVb64HB5VkT2+SPgzLC9NrAGWBYR8wtmNsHMfsmO2cxuAKoCo8xsVNh2kpl9H56bd83swLB9ThjfN8D5kdnpeHHvxjn4FcgAypvZaDN72MzGADeaWbvwezo1/HSgWEQsj5nZuPBRJ2yvYGbvh7GMN7MWYXvvMK6RwGvAA0DnMIPe2cxmmFmFsG+Kmc00s/LuPsfdpwCF8ydbkmbp6vVULpu+bblSmVIsXR3/D+XGzVv5btps2jc+HIA61Srw0x9zWb1+Axs3b+WbqbNYsnLtXom7MChXuRwrFm77VcXKxSsoV6lcTL+Ol53KhC/GsXrpqhztf02fQ/OwXKdOw7pUqFaRcpVjt9+fLF21hsplS29brli2NEtW5XzNdelwPLMXLqX9dY9y3l3Pcvulp5GSEkwHMrOyuOCf/6XtNQ9zXP06NKiTjBxQ4VekcjkyFm3/5Grr4uUUifNaFclWWCbYg4EuZnYA0AD4MWLdb0Ardz8GuBd4OGzvDtQCjnH3BsCbEdssd/djgReAW3PZZxXgBOA04FEIJqBAXaAZQSa0sZm1SuSAwonyAcCUsKmvuzd196OB4sBp7r4UOMDM0oGWwASgpZkdAix19w3htmuBeWZ2NMEbkCFRu7vb3ZsQnLvWZtbA3Z8FFgJt3b2tBWUz9wDtw3MzAbg5YoxN7n6Cuw+OGjsm7t04B80JJrDZf2EPcvfWwHMEnwh0dvf6BNcKRH52vNbdmwF9gafDtmcIMuNNgXOBlyL6NwbOdPeLCF4jQ9y9kbsPAd4ALg77tQd+dvecn//Lfs3dY9osl6ze2CkzaFSnOqVLBh+41a5Snss7Hk+PPoO59pkhHFa9EqmpheXX7l4Q5zRGn+8yFcty/KktGDYotirwwxfeo2T6gTwx7Gk6dT2NP3+ZTWbm/n2xVZyXa8xp/m7qHxxxSFW+7Hsn7/z7eh557RPWb9gEQGpKCu88fD0jn72DabPmMWPe4rwPulCI+2Ld+2EUVCoRiVEoLnJ09ylmVpNg8jgsanVp4FUzqws4kBa2twf6uXtGOEZkdjn7yoOfgHNy2e1H7p4FTDezSmHbSeFjUrh8IMGEe+xuHE5nM2sLHA5c5e6bwva2ZnY7QclGWeAX4BPgO4JyklYEbx46Evykfx017mCCMpGTgXbA5RHrLjCz7gTf7ypAPbZP7LMdF7Z/GyahiwLfR6yPnrRnyy3uHellZpcA6wgm0R7uM3sfhwN/unv2Z+mvAteyfTL9dsTXPuHz9kC9iAR6upll10MMdfeNucQyEPg4HPsK4JWdxJ5DeF67Azz/n4e48h8X7s7mUghUKlOKxRFZ5yWr1lHhoAPj9h0x7tdt5SHZzm7ZkLNbNgTg2Q9GU6nM/l2m0/Efp9Cuy0kAzJoyg3JVKwBBCUPZyuVYuTTnB4G1jq5N5UOq0HdMfwCKFS/Gf8f05/rWV7Nx/Uaev+3ZbX2f/+ZFls7LWW+8v6lUtjSLV67Ztrx05RoqlknP0efjMRO54vRWmBkHVy5HtQpl+HPRMuofuj1bnV6yOE2PrM13U2ZQt0blvRZ/QZWxeDlFqmy/fCutcnkylup6CsldYUqlDAWeJKI8JPQgMCrMoJ5OkBWGYBKa29vLzeHXTHJ/k7E54rlFfH0kzH42cvc67v7ybhwDBNnTowgy0v8xs8phZv554LwwY/tixHF8HfY9hGAi2JAgsx49qf8EuBSY6+7bZgNmVosgS98uzOR/FjF2JAO+iDi2eu7eLWL93zEb7DjuHekT7qOlu0e+Ucjex87KTDzO8xTg+Ij4q7l79uf4MbFv29h9HrDEzE4EmhOUI+0ydx/g7k3cvYkm1/umo2pWZe7SVSxYtpqtGZl8Pv5XWjesG9Nv3YZN/PTHXNo2yrlu5drg5bdoxRq+mvQ7naIm4PubEa8N47ZTbuK2U25i3MgfaXNuWwDqHnM4G9ZtiCkDmfjVBK5qehnXnHAV15xwFZs3bub61lcDUCK9JEXSgl/h7bucxK/jfmHj+tzeS+8fjqpdjbmLlzN/6Uq2ZmQw4ocptD72yBx9KpcvzY+/zAJgxZp1zFm0nOoVy7Jy7XrW/h2cv01btvLDtJnUrFphrx9DQbRx6h8UrVmVtOqVIK0I6ae2Yt3/fsjvsAoO1WDHKBQZ7NBAYI27TzWzNhHtpdl+0WPXiPaRQA8zG+3uGWZWNiqLnYjPgQfN7E13X29m1YCtYSnHbnH37y24O8qNwGNh8/Kw7vk84L2wbSzwEDDW3bPMbCXBRXp3RY230czuAKKvoEonmGCuCTPxnYDR4bp1QClgOfAD8JyZ1XH3mWF9d/WILHI82ZPpeHHvid+AmtmxELxxGBOxvjNB2U5ntmfZRwLXAU9AcLcQd58cZ+zsY470EkGpyOvuvs9+vnzbfY8yftIUVq9eS7uzLuGabpdy7ukn53dYBV6R1BTuvKgDPZ8eTJY7Z7ZoQJ1qFXh39EQAzm9zLABfTfqD44+qRfFiRXNsf8sLH7Dm740USU3lrotOJr1k8Zh97K8mfjWBY9s2pu/Y/mzeuJnnb92ejf7noHt54fa+rNpBlrB6nepc/1QvsjKzmD9zXo5s9v6qSGoqd112Bj0ff4WsLOes1o2pU70S7/wvqKy8oF1zup91Iv/q/x7n3vkMjnNT55MpU6okf8xdxD393yMry8nyLE5qXp/WxxyRz0dUQGRmsfj+F6gx8KHgNn3vjWTLzLkcdGFwzfzqt4eRWr4MtT58hpQDS0BWFmW7nsXsTleTtX4jVfvcTslmDUgtk06dr19j2TNvsOa9kfl8UJKXCs0E293nE9TZRnucoETkZuCriPaXgMOAKWa2lSC72ncPYxhpZkcC34elCOuBS4ClZvY20Ibggr35wH3u/rKZ9Qi3jXfj4ceAiQSlHy8S3A1kDjA+Yp9zwn1lZ6y/IZj45kzzBH2j66Nx95/NbBJB6cZs4NuI1QOA4Wa2KKzD7gq8nX1BIUFNdq4TbHdfbWZx445kZg8AE9x9aG5jRY27ycwuB9614M4f44HI81fMzH4kyFpnp41vIHiDMIXgdT0W6BFn+FHAnWY2meDTiCEEn468QkR5iJk1BT4EygCnm9n94ScPhdYT9yd8F8r9Xsv6dWhZv06OtuyJdbYzWzTgzBYNYrZ95Y5L8zS2wu6lf/WP2/5w1wfitmffAxvgj4m/c32beD/m+7eWjQ6nZaPDc7Rd0K75tucVy6TT/84rYrY77OAqvPPv62PaJfD3mAnMHjMhR9vqt7dXrWYuX8XMlv+Iu+3CXo/naWz5rpBmmfOSxbuAR6SgMrM5QJNkXohowf3C+7h7yz0ZZ+vy2fphSrK08rXZOHZQfoexzyneqivnHbJXb0G/X3jvr6FsGh97D2TZMwc0PZdf6+7K3VVlVx05Yxgk8R6Mm75+PU///h3Q8tJCd7/IQpPBFskLFvxzoZ5sv5OIiIiI7IZ9uLoyYYXpIkcR3L1mMrPX7v6oux/i7t8ka0wRERHZvymDLSIiIiKJUw12DGWwRURERESSSBlsEREREUlcIf1vi3lJGWwRERERkSRSBltEREREEqca7BjKYIuIiIhIoWZmHc3sdzObGd6CN3r9bWY2OXxMM7NMMysbrptjZlPDdRNiR999ymCLiIiISOLyuQbbzFKB54AOwHxgvJkNdffp2X3c/QngibD/6UAvd18ZMUzbZN4GWBlsERERESnMmgEz3X22u28BBgNn7qD/hcDbeRmQJtgiIiIikrisrLx97Fw1YF7E8vywLYaZlQA6Au9HNDsw0sx+MrPuCZ6FHFQiIiIiIiIFVjjpjZz4DnD3AZFd4mzmuQx3OvBtVHlIC3dfaGYVgS/M7Dd3H7snMWuCLSIiIiKJy+Ma7HAyPWAHXeYDNSKWqwMLc+nbhajyEHdfGH5damYfEpSc7NEEWyUiIiIiIlKYjQfqmlktMytKMIkeGt3JzEoDrYGPI9pKmlmp7OfAScC0PQ1IGWwRERERSVw+3wfb3TPM7DrgcyAVGOjuv5hZj3B9v7Dr2cBId/87YvNKwIdmBsG8+C13H7GnMWmCLSIiIiKFmrsPA4ZFtfWLWh4EDIpqmw00THY8mmCLiIiISOL0nxxjaIItIiIiIonL5380UxDpIkcRERERkSRSBltEREREEqcSkRjKYIuIiIiIJJEy2CIiIiKSONVgx1AGW0REREQkiZTBFhEREZHEqQY7hjLYIiIiIiJJpAy2iIiIiCRONdgxlMEWEREREUkiZbBFREREJHGqwY6hDLaIiIiISBIpgy0iIiIiiVMGO4Yy2CIiIiIiSaQMtoiIiIgkzj2/IyhwlMEWEREREUkiZbBFREREJHGqwY6hDLaIiIiISBIpgy0iIiIiiVMGO4Yy2CIiIiIiSaQMtoiIiIgkzpXBjqYMtoiIiIhIEimDLSIiIiKJUw12DGWwRURERESSSBlsEREREUmc/pNjDGWwRURERESSSBlsEREREUmcarBjmCutL5Is+mESEZHCwpI10MaXb83Tv3/Fuz2ZtFj3FmWwRZJk49hB+R3CPqd4q65sXT47v8PY56SVr02RotXyO4x9TsaWBWyZMyG/w9jnFK3ZhOmHnprfYexT6s36LL9D2Odpgi0iIiIiidM/momhixxFRERERJJIGWwRERERSZhn6RKkaMpgi4iIiIgkkTLYIiIiIpI43aYvhjLYIiIiIiJJpAy2iIiIiCROdxGJoQy2iIiIiEgSKYMtIiIiIonTXURiKIMtIiIiIpJEymCLiIiISOJ0F5EYymCLiIiIiCSRMtgiIiIikjhlsGMogy0iIiIikkTKYIuIiIhI4lx3EYmmDLaIiIiISBIpgy0iIiIiiVMNdgxlsEVEREREkkgZbBERERFJnP6TYwxlsEVEREREkkgZbBERERFJnKsGO5oy2CIiIiIiSaQMtoiIiIgkTjXYMTTBFhEREZGEuW7TF0MlIiIiIiIiSaQMtoiIiIgkTiUiMZTBFhEREZFCzcw6mtnvZjbTzO6Ms76Nma0xs8nh495d3TYRymCLiIiISOLy+TZ9ZpYKPAd0AOYD481sqLtPj+r6tbufluC2u0UZbBEREREpzJoBM919trtvAQYDZ+6FbXOlCbaIiIiIJC7L8/RhZt3NbELEo3tUBNWAeRHL88O2aMeb2c9mNtzMjtrNbXeLSkREREREpMBy9wHAgB10sXibRS1PBA5x9/VmdgrwEVB3F7fdbZpgi4iIiEji8v8+2POBGhHL1YGFkR3cfW3E82Fm9ryZld+VbROhEhERERERKczGA3XNrJaZFQW6AEMjO5hZZTOz8Hkzgjnwil3ZNhHKYIuIiIhI4vL5PtjunmFm1wGfA6nAQHf/xcx6hOv7AecBPc0sA9gIdHF3B+Juu6cxaYItIiIiIoWauw8DhkW19Yt43hfou6vb7ilNsEVEREQkcfl8H+yCSDXYIiIiIiJJpAy2iIiIiCQun2uwCyJlsEVEREREkkgZbBERERFJmOf/fbALHGWwRURERESSSBlsEREREUmcarBjKIMtIiIiIpJEymCL7EO+nTaLxwd/SVZWFme3bMQVnY7PsX7Q5z8w7IfgH1RlZmXx56IVjOpzI6VLFufNL8fzwdeTcYdzWjXkkvbN8uMQCp17Hn6Ksd+Oo2yZg/jojX4730By1eepB+jU8UQ2bNxIt269mDR5Wkyftm1a8Nhj//SkacEAACAASURBVKJo0TQmTpzKVd1vITMzMx+iLbi+Gf8zj/V7nczMLM7p1IYrO5+RY/2adX9z71MDmLdoCcXS0njglu7UrVlj2/rMzCy6XH8PFcuV4bkHb9vb4RdYJVs1pvK/umOpKawaMpIV/d/Nsb5o7epUfewmDjiqDsueeo0VL32wbV2VR2+k1InNyFixmtmdrt3boec9ZbBjFPgMtpm5mb0esVzEzJaZ2acJjjfHzMrHaT/DzO7cgzgHmtlSM4v9i7C9T9cw9slm9puZ9Up0fxFj9g7PUZ2Itl5hW5OdbHuTmZVIYJ8PmFn7nfQZZGbn5RLvgvAcTDOzM+Jtn1fMrJGZnbIL/W42s+lmNsXM/mdmh+yN+PZEZlYWj7w1kuduvIAPHujOiHHTmbVweY4+XU8+jnfu68Y793XjhnPa0PiwgyldsjgzFyzjg68n88Y/u/LOfd34esos/lqyMp+OpHA565QO9HvqofwOo9Dr1PFE6tapxRH1TqBnzzt4ru8jMX3MjIEvP83Fl1xDo2PaMXfufP5x6fn5EG3BlZmZxb+fG8TzD93Oxy8+zvBR3zPrr/k5+rw0+GOOOPRgPuj3KP++rSePvfB6jvVvfDSCWjWq7s2wC76UFKr07sncK+5j5sk9KX16K4rWqZGjS+aadSx+oD8rXv4gZvM173/J3Mvv3VvRSgFQ4CfYwN/A0WZWPFzuACxI9k7cfai7P7oHQwwCOu5CvyHu3ghoAdxtZjV2tsEumAp0iVg+D5i+C9vdBOzWBNvMUt39Xnf/cne2i9InPAfnAwPNLMfr0Mzy5JOVcNxGwE4n2MAkoIm7NwDeAx7Pi5iSadqfC6lRoQzVK5QhrUgqJzc9ktGT/8i1//Bx0+nYrB4Asxctp0HtahQvlkaR1BQaH1aDryblvq1s16RRfUqnl8rvMAq9008/mdfffA+AH8dNpPRBpalcuWKOPuXKlWHz5s3MmDEbgC+/HMs5Z+/Kj/P+Y+rvszi4aiVqVKlIWloROrU5jlHf/5Sjz6y5C2je6GgAah9clQVLlrF81RoAFi9bwdfjJnNup7Z7PfaCrHjDw9jy10K2zlsMWzNY8+lYSrU/LkefzBVr2DR1BmzNiNl+w/hfyFy9bm+Fu/d5Vt4+CqHCMMEGGA6cGj6/EHg7e4WZNTOz78xsUvj18LA91cyeNLOpYRby+ojxrjezieG6I8L+Xc2sb/h8kJk9G443OzITa2a3mdn4cMz7s9vdfSywyyk/d18BzASqhOPeG447zcwGWKCimf0Urm8YZqUPDpdnRWSfPwLODNtrA2uAZRExv2BmE8zsl+yYzewGoCowysxGhW0nmdn34bl518wODNvnhPF9A5wfmZ2OF/dunINfgQygvJmNNrOHzWwMcKOZtQu/p1PDTweKRcTymJmNCx91wvYKZvZ+GMt4M2sRtvcO4xoJvAY8AHQOM+idzWyGmVUI+6aY2UwzK+/uo9x9QxjqD0D1XT2u/LJ09Xoql03ftlypTCmW5vILfePmrXw3bTbtGx8OQJ1qFfjpj7msXr+BjZu38s3UWSxZuXavxC0CUK1qZebPW7htecH8RVSrWjlHn+XLV5KWlkbjYxsAcM45p1JdmdYclq5YSeUK5bYtVypfliXLV+Xoc3itg/ny2/EATP1tFouWLGfJ8uDP1+P9XqfXlReSsuu/yvcLRSqVY+ui7Z8IZixeTlqlcjvYQvZ3hWWCPRjoYmYHAA2AHyPW/Qa0cvdjgHuBh8P27kAt4JgwC/lmxDbL3f1Y4AXg1lz2WQU4ATgNeBSCCShQF2hGkAltbGatEjmgcKJ8ADAlbOrr7k3d/WigOHCauy8FDjCzdKAlMAFoGZYrLI2YAK4F5pnZ0QRvQIZE7e5ud29CcO5am1kDd38WWAi0dfe2FpTN3AO0D8/NBODmiDE2ufsJ7j44auyYuHfjHDQHstj+ZuAgd28NPEfwiUBnd69PcK1Az4hN17p7M6Av8HTY9gxBZrwpcC7wUkT/xsCZ7n4RwWtkiLs3cvchwBvAxWG/9sDP7p6zrgK6EbzJK9DcY2vgjPh/JMdOmUGjOtUpXTL4YKh2lfJc3vF4evQZzLXPDOGw6pVITS0svx5kXxDvvXm81/TFl1zDf57szffffsr69X+TkaH660hxTlnMue3W+XTWrvub83rexVtDP+eIOjUpkpLCmB8mUvag0hxVt9ZeirYQ0RuOHcvyvH0UQoXiIkd3n2JmNQkmj8OiVpcGXjWzuoADaWF7e6Cfu2eEY0Rml7MLpH4Czslltx+5exYw3cwqhW0nhY9J4fKBBBPusbtxOJ3NrC1wOHCVu28K29ua2e0EJRtlgV+AT4DvCMpJWhG8eegIGPB11LiDCcpETgbaAZdHrLvAzLoTfL+rAPXYPrHPdlzY/m34y7go8H3E+uhJe7bc4t6RXmZ2CbCOYBLt4T6z93E48Ke7Z9covApcy/bJ9NsRX/uEz9sD9SL+kKSbWfbn9kPdfWMusQwEPg7HvgJ4JXJlGGcToHW8jcPz2h3gv7dcRrcz2uR+1HmsUplSLI7IOi9ZtY4KBx0Yt++Icb9uKw/JdnbLhpzdsiEAz34wmkplVPYgeatnj8vo1i14fzthwuQc2ehq1auwcNGSmG1++PEn2pwY/Nru0L4VdevW3jvBFhKVypdl8bIV25aXLF9JxXIH5ehzYMkSPHTr1UDwJqbjZTdRrXIFho/5nlE//MTX4yezectW/t6wkTsfe55H77hmrx5DQZSxeDlpVbZfvlWkcnm2Llmxgy32L15IJ8F5qTClqIYCTxJRHhJ6EBgVZlBPJ8gKQzAJze07vjn8mknubzI2Rzy3iK+PhNnPRu5ex91f3o1jgCB7ehRBRvo/ZlY5zMw/D5wXZmxfjDiOr8O+hxBMBBsSZNajJ/WfAJcCc9192yzLzGoRZOnbhZn8zyLGjmTAFxHHVs/du0Ws/ztmgx3HvSN9wn20dPfINwrZ+9hZqsDjPE8Bjo+Iv5q7Z9dHxMS+bWP3ecASMzsRaE5EptqCCznvBs5w9825bD/A3Zu4e5P8nFwDHFWzKnOXrmLBstVszcjk8/G/0rph3Zh+6zZs4qc/5tK2Uc51K9cGp2nRijV8Nel3OkVNwEWS7YV+r9Kk6Uk0aXoSQ4d+zqUXB9V4zZsdy9o1a1m8eGnMNhXC8oeiRYty263XMmDA6zF99mdHH16bvxYsZv7ipWzdmsHw0T/Q5rjGOfqsXf83W8M64feHj6Lx0UdwYMkS3HRFF/73Zl8+f+0ZnrjrOpo1rKfJdWjjlD8oWrMaadUrQVoRSp/WivX/+3HnG8p+q1BksEMDgTXuPtXM2kS0l2b7RY9dI9pHAj3MbLS7Z5hZ2agsdiI+Bx40szfdfb2ZVQO2hqUcu8Xdv7fg7ig3Ao+FzcvDuufzCC6sg2Ai/RAw1t2zzGwlwUV6d0WNt9HM7gCir0xLJ5hgrgkz8Z2A0eG6dUApYDlBnfFzZlbH3WeG9d3VI7LI8WRPpuPFvSd+A2pmx0LwxmFMxPrOBGU7ndmeZR8JXAc8AcHdQtx9cpyxs4850ksEpSKvu3tmuP0xQH+gYyLf3/xQJDWFOy/qQM+nB5PlzpktGlCnWgXeHT0RgPPbHAvAV5P+4PijalG8WNEc29/ywges+XsjRVJTueuik0kvWTxmHxLrtvseZfykKaxevZZ2Z13CNd0u5dzTT87vsAqdYcP/R8eOJ/L7r9+yYeNGrrxye4XaJx+/Rvcet7Fo0RJuvbknp5zanpSUFPr3f41Ro7/Nx6gLniKpqfzz2q70+OdjZGZlcfZJralTszrvfBpcl37Bae2ZPXchdz/xAikpKRx6SDXu79U9n6MuBDKzWHz/Cxw86EEsJYXV733B5hlzKXNhJwBWvT2c1PJlqP3R06QcWAI8i7Jdz2RWxx5krd9Itadvp0Tz+hQpk07db15l2TNvsvrdkfl8UEmkDHaMQjPBdvf5BHW20R4nKBG5Gfgqov0l4DBgipltJciu9t3DGEaa2ZHA92EpwnrgEmCpmb0NtCG4YG8+cJ+7v2xmPcJt490g9zFgIkHpx4sEdwOZA4yP2OeccF/ZGetvCCa+Oa9aCfpG10fj7j+b2SSC0o3ZQORfowHAcDNbFNZhdwXezr6gkKAmO9cJtruvNrO4cUcysweACe4+NLexosbdZGaXA+9acOeP8UDk+StmZj8SZK0vDNtuIHiDMIXgdT0W6BFn+FHAnWY2meDTiCEEn468Qs7ykCcISoDeDc//XHffq7cUTETL+nVoWb9OjrbsiXW2M1s04MwWDWK2feWOS/M0tn3VE/cnfHdPiXLDjXfHbT/9zH9se37HXQ9xx126LeKOtGrWiFbNGuVou+C07XdWbVSvLp+98tQOx2jasB5NG+pTrEjrR09g/egJOdpWvb398pzM5auYccJlcbddcFOBvxGVJJnFu4hEpKAyszkEt8+LvhBxT8ZsQlC20nJPxtk4dpB+mJKseKuubF0+O7/D2Oekla9NkaLV8juMfU7GlgVsmTNh5x1ltxSt2YTph566846yy+rN+gx2Xo65y9Zdd0qe/v0r1XdYobvKtNBksEXyggX/XKgn2+8kIiIiIrJHNMGWQsXdayZ5vEcJb8MoIiIiCVANdozCdBcREREREZECTxlsEREREUmcMtgxlMEWEREREUkiZbBFREREJGG6I10sZbBFRERERJJIGWwRERERSZxqsGMogy0iIiIikkTKYIuIiIhI4pTBjqEMtoiIiIhIEimDLSIiIiIJc2WwYyiDLSIiIiKSRMpgi4iIiEjilMGOoQy2iIiIiEgSKYMtIiIiIonLyu8ACh5lsEVEREREkkgZbBERERFJmO4iEksZbBERERGRJFIGW0REREQSpwx2DE2wRURERCRxusgxhkpERERERESSSBlsEREREUmYLnKMpQy2iIiIiEgSKYMtIiIiIolTDXYMZbBFRERERJJIGWwRERERSZhqsGMpgy0iIiIikkTKYIuIiIhI4lSDHUMZbBERERGRJFIGW0REREQS5spgx1AGW0REREQkiZTBFhEREZHEKYMdQxlsEREREZEkUgZbRERERBKmGuxYymCLiIiIiCSRMtgiIiIikjhlsGMogy0iIiIihZqZdTSz381sppndGWf9xWY2JXx8Z2YNI9bNMbOpZjbZzCYkIx5lsEVEREQkYfldg21mqcBzQAdgPjDezIa6+/SIbn8Crd19lZl1AgYAzSPWt3X35cmKSRlsERERESnMmgEz3X22u28BBgNnRnZw9+/cfVW4+ANQPS8D0gRbRERERBLmWXn72AXVgHkRy/PDttx0A4ZHHgIw0sx+MrPuu3v88ahEREREREQKrHDSGznxHeDuAyK7xNnMcxmrLcEE+4SI5hbuvtDMKgJfmNlv7j52T2LWBFtEREREEpbXNdjhZHrADrrMB2pELFcHFkZ3MrMGwEtAJ3dfETH+wvDrUjP7kKDkZI8m2OYed4IvIrtPP0wiIlJYxMv6JmRJ29Z5+vev0qgxO4zVzIoAfwDtgAXAeOAid/8los/BwFfAP9z9u4j2kkCKu68Ln38BPODuI/YkZmWwRZLkvEPOyO8Q9jnv/TWUIkV3VEYnicjYsoCty2fndxj7nLTytSmfflh+h7HPWb72D0ZU6pLfYexTOi4ZnNwBPWlz9cR2755hZtcBnwOpwEB3/8XMeoTr+wH3AuWA580MIMPdmwCVgA/DtiLAW3s6uc4eSERERESk0HL3YcCwqLZ+Ec+vBK6Ms91soGF0+57SBFtEREREEpbf98EuiDTBFhEREZGEeVb+logURLoPtoiIiIhIEimDLSIiIiIJU4lILGWwRURERESSSBlsEREREUmY5/Nt+goiZbBFRERERJJIGWwRERERSZhqsGMpgy0iIiIikkTKYIuIiIhIwnQf7FjKYIuIiIiIJJEy2CIiIiKSMPf8jqDgUQZbRERERCSJlMEWERERkYSpBjuWMtgiIiIiIkmkDLaIiIiIJEwZ7FjKYIuIiIiIJJEy2CIiIiKSMN1FJJYy2CIiIiIiSaQMtoiIiIgkTDXYsZTBFhERERFJImWwRURERCRh7spgR1MGW0REREQkiZTBFhEREZGEeVZ+R1DwKIMtIiIiIpJEymCLiIiISMKyVIMdQxNsEREREUmYLnKMpRIREREREZEkUgZbRERERBKmfzQTSxlsEREREZEkUgZbRERERBLmnt8RFDzKYIuIiIiIJJEy2CIiIiKSMNVgx1IGW0REREQkiZTBFhEREZGE6R/NxFIGW0REREQkiZTBFhEREZGE6T85xlIGW0REREQkiZTBFhEREZGE6T7YsZTBFhERERFJImWwRURERCRhuotILGWwRURERESSSBlsEREREUmY7iISSxlskX3MFb2v4r9j+vOfEc9S6+jaO+57f3denz5k23LJ9JLc1v8u/jPiWR75+ElqHHZwXodbKPV56gF+m/4NE3/6gmMaHR23T9s2LRj34wgmT/ofA19+mtTU1L0cZeF2z8NP0erULpx1SY/8DqVQevjxexg3+QvGfDeUBg3rxe3TsvXxfDX2Q0Z98zGffv42tWoHP+916tZm+JdDWLBsGtdef8XeDLvAOfLfl9Hyh6dpMeox0uvXjNun+MEVOG74Q7T8vg8NB9yIpeX8WU9vVJuTF75FpdOaA5BSLI3jRjzE/331GC3GPEGd287L68OQfFDgJ9hm5mb2esRyETNbZmafJjjeHDMrH6f9DDO7cw/iHGhmS81s2g76dA1jn2xmv5lZr0T3FzFm7/Ac1Ylo6xW2NdnJtjeZWYkE9vmAmbXfSZ9BZhbzWyOMd0F4DqaZ2Rm7u/89YWaNzOyUXejXw8ymhnF+Y2bx/0IVMMe0bUyVWlW5vvXV9LvrObo/1DPXvofWr0PJ9JI52s657nzmTP+TWzrewH9v7sMVva/K65ALnU4dT6RunVocUe8Eeva8g+f6PhLTx8wY+PLTXHzJNTQ6ph1z587nH5eenw/RFl5nndKBfk89lN9hFErtT2pN7UNr0qxRB26+8V880ef+uP2e7NObq6+8lbYnnMn7737CzbddA8DqVav55+0P8dyzL+/NsAuc8u0aUaJWFb4+7iam3foi9R6/Mm6/w+65iDn9P+Pr43uxdfV6ql904vaVKcbh/7qI5aN+3taUtXkr4895kO9OvIPv2t1J+RMbUbpxnTgjFx7uefsojAr8BBv4GzjazIqHyx2ABcneibsPdfdH92CIQUDHXeg3xN0bAS2Au82sxh7sM9tUoEvE8nnA9F3Y7iZgtybYZpbq7ve6+5e7s12UPuE5OB8YaGY5XodmlielS+G4jYCdTrCBt9y9fhjn48BTeRFTsjXt0JzR748CYMak3ymRXpKDKpaJ6ZeSksKld3fl9UcG5WivXrcGU78N/hAsnLWACtUrUrr8QXked2Fy+ukn8/qb7wHw47iJlD6oNJUrV8zRp1y5MmzevJkZM2YD8OWXYznn7F152Um2Jo3qUzq9VH6HUSh1OqUd77z9IQA/jf+Z0qVLUalShZh+7k6p8E12enopFi9aCsDy5SuZNHEqGRkZey/oAqhSxyYsfHcsAGt+mklaegmKVYz9fVjuhKNY8smPACx8ZyyVOm3PbR1yZUeWfDqOLcvX5tgmc8NmACwtFSuSCoV0Eim5KwwTbIDhwKnh8wuBt7NXmFkzM/vOzCaFXw8P21PN7MkwCznFzK6PGO96M5sYrjsi7N/VzPqGzweZ2bPheLMjM7FmdpuZjQ/H3JYWcPexwMpdPSB3XwHMBKqE494bjjvNzAZYoKKZ/RSubxhmpQ8Ol2dFZJ8/As4M22sDa4BlETG/YGYTzOyX7JjN7AagKjDKzEaFbSeZ2ffhuXnXzA4M2+eE8X0DnB+ZnY4X926cg1+BDKC8mY02s4fNbAxwo5m1C7+nU8NPB4pFxPKYmY0LH3XC9gpm9n4Yy3gzaxG29w7jGgm8BjwAdA4z053NbIaZVQj7ppjZTDMr7+6Rvw1LUkh+/ZWrXI4VC7d961m5eAXlKpWL6dfxslOZ8MU4Vi9dlaP9r+lzaN7peADqNKxLhWoVKVc5dvv9WbWqlZk/b+G25QXzF1GtauUcfZYvX0laWhqNj20AwDnnnEr1GlX3apyy/6pStRIL5i/etrxwwRKqVK0U0++m6+5h8HsvMuXXsVzQ5Uye6dN/b4ZZ4BWrUpaNC1ZsW960aCXFqpTN0SetbCm2rt2AZ2YFfRZu71OschkqdWrK3Fe/iB08xfi//z3Kib8MYMWYqayZODPvDmQvyHLL00dhVFgm2IOBLmZ2ANAA+DFi3W9AK3c/BrgXeDhs7w7UAo5x9wbAmxHbLHf3Y4EXgFtz2WcV4ATgNOBRCCagQF2gGUEmtLGZtUrkgMKJ8gHAlLCpr7s3dfejgeLAae6+FDjAzNKBlsAEoKWZHQIsdfcN4bZrgXlmdjTBG5Ah5HS3uzchOHetzayBuz8LLATauntbC8pm7gHah+dmAnBzxBib3P0Edx8cNXZM3LtxDpoDWWx/M3CQu7cGniP4RKCzu9cnuBg3stZhrbs3A/oCT4dtzxBkxpsC5wIvRfRvDJzp7hcRvEaGuHsjdx8CvAFcHPZrD/zs7svD+K41s1kEGewbcjmG7uGblwmz1/+1q4eed+L8HvKoz9fKVCzL8ae2YNig2CqrD194j5LpB/LEsKfp1PU0/vxlNpmZmXkVbaEU7z1k9DkGuPiSa/jPk735/ttPWb/+bzIydB5l79jV12iPa7vS5byraHBkK95+430eevifeyO8wi36PMab+4V9jnzwMn5/6C3IipOfyXK+a3cnoxtdQ+ljD+XAI6onP1bJV4XiLiLuPsXMahJMHodFrS4NvGpmdQmyjGlhe3ugn7tnhGNEZpc/CL/+BJyTy24/cvcsYLqZZb/1Pyl8TAqXDySYcI/djcPpbGZtgcOBq9x9U9je1sxuJyjZKAv8AnwCfEdQTtKK4M1DR4If6a+jxh1MUCZyMtAOuDxi3QVm1p3g+10FqMf2iX2248L2b8NfzkWB7yPWR0/as+UW9470MrNLgHUEk2gP95m9j8OBP939j3D5VeBatk+m34742id83h6oF/GHJd3Msj9fHuruG3OJZSDwcTj2FcAr2Svc/TngOTO7iODNx2XRG7v7AGAAwHmHnJEvWe6O/ziFdl1OAmDWlBmUq1oB+BWAspXLsXJpzg9Wah1dm8qHVKHvmCBbVax4Mf47pj/Xt76ajes38vxtz27r+/w3L7J03pK9cyAFWM8el9GtW/A+bMKEyTmy0dWqV2Hhothz9MOPP9HmxODXS4f2rahbd8cXnIrsiSuuuphLL7sAgMkTp1Kt+vZPVapWq7St/CNbuXJlOKr+EUycEPwp+PCDYbzzwf5dcw1w8OUnUf2SoIZ6zeRZFK9WjtXhugOqlGXz4pyf+m1dsY609BJYagqemcUBVbf3SW9Um0b9bgQgrVwpyrdvhGdmsnT4hG3bZ6zdwMpvp1O+bSPW/zY/7w8wj+guIrEKxQQ7NBR4EmgDRH5m/SAwyt3PDifho8N2I/eP9TeHXzPJ/RxsjnhuEV8fcfc9+RxtiLtfZ2bHA5+Z2XBgNfA80MTd55lZb4LsNgQT6ZbAIQQTwTsIjis6/fgJ8AQwwd3XZk80zawWQZa+qbuvMrNBEWNHMuALd78wl7j/jtkg+EQht7h3pI+7P7mDfezsJ9XjPE8Bjo+eSIfnISb2bRsHcS8xsxOB5mzPZkcaTPBpR4E04rVhjHgteN957IlN6HTZqXw7dCx1jzmcDes2xJSBTPxqAlc13f5e4fXpQ7i+9dUAlEgvyZaNm8nYmkH7Lifx67hf2Lg+t/cm+48X+r3KC/1eBeCUTu24pmdXhgz5mObNjmXtmrUsXrw0ZpsKFcqxbNkKihYtym23Xssjjz4b00ckWQa++CYDXww+qO1wchu6db+ED977jMZNG7J27XqWLFmWo//q1WtJTy/FoXVqMmvmHNq0bcEfv8/Kj9ALlLmvjGTuKyMBqND+GA6+4mQWffgdpRvXYeu6DWxeujpmm5XfTqfS6c1Z/NH3VL2gFUtGBBPosU23f/BZ/5meLP1iIkuHTyCtXCl8ayYZazeQckAa5VrV58++Q/fOAcpeU1hKRCDIND7g7lOj2kuz/aLHrhHtI4EeFl4wZ2b/z959x0lVX28c/zwL2GhSBCkqAmo0FhRrjAU1RlGjRmNJ9GcNdqOJxhKTGKPGFk2Mxt6TGGsS7CVBMcaCooK9IhaKoAKKhd09vz/uXRh2FliGuXt3dp63r3ntzG1z5rjsfOfMud/bnSX3AHBwQW9yP0m9FrFPkyLiCeAm4CfMG5ROS49dOPvGaGA/4I20ov4xyUl6jzc63hckg++zGj1VF5IB5oy0Er9jwbpZQEOV90lg84Ke5uUkrb6Il7GwuJfEq8AAzZsZZX/g0YL1exf8bKiyPwgc3bCBpCELOHbha25wNUmryK0RUZfuv1rB+p2ANxbzNeRi7H+eYcrEyVwy+goOP+corj7t8rnrTr3+V3TrtfB/Bv0H9+eihy7hj//+M+sPG8q1p1+VdcgV5977/s3b70zktVce5/LLz+PoY+Z9rX7Xv26kT5/kC68TfnoE48c9wnNjH+buex5i1COPL+iQ1oQTf30OPzrseCZMfJ9td9uPO+56IO+QKsZDDzzCuxPeY8wLD3PRxWfy85+ePnfdzbdfxYor9qKuro7jjzmN6276E488PpK99tmV0395HgC9evVk3CujOeKog/jpiUcy7pXRdOrccQHP1nZ99PBzzH53Cls+9UfW/v0IXj7p2rnrhv71JJbunZxA/tqZf2PA4TuxxZN/YKlunXn/b6MWetyle3dj4zt/yeajzmWzB85m+qPj+OihsZm+lqy5B7uYMC+HDAAAIABJREFUmurLak0kfRYRnRot2xo4ISJ2TivBN5D08f4H2D8iBqQD6/NIWirmAFdFxCWSJpBUXKcpmcbugojYWtKB6fKj0yrv3RFxe+MYJP0EaJir5zNgv4h4S9LNJNX1nsAU4NcRcY2kwwEi4vLC50iP1RcYS9JmchJJi8cE4D3g3Yg4Pd1uInBmRFwp6VRgn7SvnLRq/FnjirCkR9IcPZO+nk2At0kq8yMj4nolJ34eBUxK+7C3Ac4Flk4Pc1pEjCzMWXrsufmRdGZTcTfa5gySyvrI5sSbPt6W5BuL9sAY4IiI+CqN5TqSDxk1wL4R8WbaQ34psGa6z+iIOLzx86UftB4gaSX6XUTcIqkDMB3YOCJeTbf7I0nbyRzgE+DoiHiJhcirRaQtu/3dkbRfql/eYbQ5tV9/wJxpb+cdRpvToedAenZZVF3CFte0ma9zf+99Fr2hNdsOU/4Oi/62uNme7Pv9TN//Nv3wzoobZbf6AbZZocaD/TIdc0OStpUtluQ4HmCXnwfY2fAAOxseYGfDA+zy8wA7e5XUg21WdkouLnQETfdem5mZ2SJUahtHliqpB9uMiBhQzup1RJwTEatExH/LdUwzMzOrbq5gm5mZmVnJPE1fMVewzczMzKyiSdpB0mvpFZlPbmK9lFyl+00lV+PeoLn7lsIDbDMzMzMrWX3Gt0WR1I5kJrEdSS6at6+ktRpttiPJrG2rkVzt+7LF2HexeYBtZmZmZpVsY+DNiHg7Ir4muUDcro222RW4MRJPAstL6tPMfRebB9hmZmZmVrJAmd6aoR/JtTgavJ8ua842zdl3sXmAbWZmZmatlqQRkp4puI1ovEkTuzWem3tB2zRn38XmWUTMzMzMrGT1GV9mLSKuBK5cyCbvAysVPO4PfNjMbZZqxr6LzRVsMzMzM6tkY4DVJK0qaSlgH2Bko21GAv+XziayKTAjIiY1c9/F5gq2mZmZmZWsvnxXXS9JRNRKOhp4AGgHXBsRL0k6PF1/OXAvMBx4E5gNHLSwfZc0Jg+wzczMzKyiRcS9JIPowmWXF9wP4Kjm7rukPMA2MzMzs5I1c6aPquIebDMzMzOzMnIF28zMzMxK1pyrLVYbV7DNzMzMzMrIFWwzMzMzK5l7sIu5gm1mZmZmVkauYJuZmZlZydyDXcwVbDMzMzOzMnIF28zMzMxK5gp2MVewzczMzMzKyBVsMzMzMyuZZxEp5gG2mZmZmZWs3uPrIm4RMTMzMzMrI1ewzczMzKxk9W4RKeIKtpmZmZlZGbmCbWZmZmYli7wDaIVcwTYzMzMzKyNXsM3MzMysZL7QTDFXsM3MzMzMysgVbDMzMzMrWb08i0hjrmCbmZmZmZWRK9hmZmZmVjLPIlLMFWwzMzMzszJyBdvMzMzMSuZZRIq5gm1mZmZmVkauYJuZmZlZyeo9iUgRV7DNzMzMzMrIFWwzMzMzK1k9LmE35gq2mZmZmVkZuYJtZmZmZiXzPNjFXME2MzMzMysjRfhzh1mZ+B+TmZlVirI1Tt/Yb79M3//+74O/VFyTt1tEzMrkyzF35B1Cm7PMRnvw9YRn8g6jzVlqwIb07LJ63mG0OdNmvs6caW/nHUab06HnQF5fc4e8w2hTVn/l/rxDaPM8wDYzMzOzkvlKjsXcg21mZmZmVkauYJuZmZlZyXwCUjEPsM3MzMysZL5UejG3iJiZmZmZlZEr2GZmZmZWMp/kWMwVbDMzMzOzMnIF28zMzMxK5gp2MVewzczMzMzKyBVsMzMzMytZeBaRIq5gm5mZmZmVkSvYZmZmZlYy92AXcwXbzMzMzKyMXME2MzMzs5K5gl3MFWwzMzMzszJyBdvMzMzMShZ5B9AKuYJtZmZmZlZGrmCbmZmZWcnqPQ92EVewzczMzMzKyBVsMzMzMyuZZxEp5gq2mZmZmVkZuYJtZmZmZiVzBbuYK9hmZmZmZmXkAbaZmZmZlSwyvi0pSd0lPSTpjfRntya2WUnSKEmvSHpJ0k8K1p0u6QNJz6e34Yt6Tg+wzczMzKwtOxn4d0SsBvw7fdxYLfCziFgT2BQ4StJaBesviogh6e3eRT2hB9hmZmZmVrJ6ZXsrg12BG9L7NwC7Nd4gIiZFxNj0/izgFaBfqU/oAbaZmZmZtWW9I2ISJANpoNfCNpY0AFgfeKpg8dGSxkm6tqkWk8Y8wDYzMzOzktVnfJM0QtIzBbcRjWOQ9LCkF5u47bo4r0VSJ+AO4LiImJkuvgwYBAwBJgG/X9RxPE2fmZmZmbVaEXElcOUittluQeskTZHUJyImSeoDTF3Adh1IBtd/jYg7C449pWCbq4C7FxWzK9hmZmZmVrLWPosIMBI4IL1/APCvxhtIEnAN8EpEXNhoXZ+Ch7sDLy7qCV3BNjMzM7OS1ZdrGJydc4BbJR0CTAR+ACCpL3B1RAwHNgf2B8ZLej7d79R0xpDzJA0hGe9PAA5b1BN6gG1mZmZmbVZETAe2bWL5h8Dw9P5/gSbnLImI/Rf3OT3ANjMzM7OS+VLpxdyDbWZmZmZWRq5gm5mZmVnJWn0Hdg5cwTYzMzMzKyNXsM3MzMysZO7BLuYKtpmZmZlZGbmCbWZmZmYlq29ycrvq5gq2mZmZmVkZuYJtZmZmZiWrgCs5tjhXsM3MzMzMysgVbDMzMzMrmevXxTzANmtDHn/hdc696W7q6+vZfeuNOOR7W823ftbsLzn1sluZPP1TauvqOWD4Fuy21VC++noOB515FXNqa6mtq+c7G6/NkXtsl9OraH3+O+YFzr38Jurq6vn+jltz6N7fm2/9jFmf86sLr+S9SVNYukMHzvjZCFYbsNLc9XV19exzzGn06tGNS397YkuH36qdfd5pbLf9Vnwx+wuOOeJkxr3wctE2W2y1Gb/57c9RTQ2ffz6bY444iXfensjg1Qbyp8t+x7rrfZOzz7iQS/90bQ6voLKcdvaFjH78abp3W55//uXyvMOpKMt9eyi9Tj0CamqYcfv9fHL1rfOt77Bqf1Y8+2csvdYgpv/hBj657o75D1BTw8q3XUzt1Ol8eMSvWzByy0OrbxGRFJJuKnjcXtJHku4u8XgTJPVsYvn3JJ28BHFeK2mqpBcXss2BaezPS3pV0vGlPl/BMU9PczS4YNnx6bINF7HvcZKWK+E5z5C00NGXpOsl7bmAeD9Ic/CipO81tX9WJA2RNHwxtt+zOblsDerq6zn7hpH8+ecH8o/zjuP+J1/grQ+mzLfNLQ89ycB+vbjt7GO55heH8vu/3cuc2lqW6tCeq089hNvOPpZbzzqGx8e9zrg3J+b0SlqXurp6zrr0ev585s/511Xncd+oJ3jr3ffn2+bqv/+LbwxamTsvP4ezTjyCcy+7ab71f/nn/ay6Ut+WDLsibLf9VgwcNICNh3yHn/7kl5x/0W+a3O6Ci07nsENPYNi3d+WO2+7ipyceCcCnn3zKqT8/k0svvqYlw65ouw3/DpdfeGbeYVSemhp6/fIoPhhxGhN2GUGXnbZmqUErz7dJ/YxZTD3rMj659o4mD7H8/rvx9dvvtUS0La4+41slavUDbOBzYG1Jy6aPvwN8UO4niYiREXHOEhziemCHZmx3S0QMATYHfiFppUXt0AzjgX0KHu8JFJeBih0HLNYAW1K7iPhVRDy8OPs1clGagx8A10qa7/dQUibfrKTHHQI0a4AtqTNwLPBUFvGU24tvvc9KvXvQv1d3OrRvzw6brssjz74y3zYSzP7iKyKC2V9+TdeOy9KupgZJLLfM0gDU1tVRW1sPeN4lgPGvvcXKfXuzUp9edOjQnh233pRRTzw73zZvTfyATYasDcDAlfvywZSPmPbJDAAmfzSdx55+nj12HNbisbd2Ow7flltv/gcAz455ga5dO9O79wpF20UEnbt0BKBLl85MnjQVgGnTPua5seOpra1tuaAr3IZD1qFrl855h1Fxlll3DeZMnMSc9yfDnFpm3vsoHbfZbL5t6j6ewVcvvg61dUX7t+/dk05bbcSM2+9vqZAtZ5UwwAa4D9gpvb8vcHPDCkkbS/qfpOfSn2uky9tJukDSeEnjJB1TcLxjJI1N130j3f5ASZek96+XdHF6vLcLK7GSTpQ0Jj3m3HJLRIwGPm7uC4qI6cCbQJ/0uL9Kj/uipCuV6CXp2XT9emkldeX08VsF1ed/ArumywcCM4CPCmK+TNIzkl5qiFnSsUBfYJSkUemy7SU9kebmNkmd0uUT0vj+C/ygsDrdVNyLkYNXgFqgp6RHJJ0t6VHgJ5K2Tf+fjk+/HVi6IJZzJT2d3gany1eQdEcayxhJm6fLT0/jehC4ETgD2DutoO8t6Q1JK6Tb1kh6U/O+4fgtcB7wZXNfU56mfjKDFbt3nfu4V/euTPlk5nzb7POdzXj7w6lsd/Q57HnKxfx8/52pqUn+DNTV17PXqX9i2JFns+k6g1l3cDk++1W+qdM/ZsUVesx93Ltnd6ZM+2S+bdZYdWUefnwMAONffYtJU6YxZVry5+C8y2/i+EP3pab5/zSqRp++vfng/clzH3/4wRT69O1dtN1xR5/G32+/inGvjGavfXbljxdd0ZJhmtG+Vw9qJ899W6V2yjQ69O6xkD3mt8Iph/HRBddAfdvsVq4nMr1VokoZYP8d2EfSMsC6zF9RfBXYMiLWB34FnJ0uHwGsCqwfEesCfy3YZ1pEbABcBpywgOfsA3wb2Bk4B5IBKLAasDFJJXSopC1LeUHpQHkZYFy66JKI2Cgi1gaWBXaOiKnAMpK6AFsAzwBbSFoFmBoRs9N9ZwLvSVqb5APILY2e7hcRsSFJ7raStG5EXAx8CAyLiGHpoPI0YLs0N88APy04xpcR8e2I+HujYxfFvRg52ITk25+Gv1rLR8RWwKUk3wjsHRHrkJwrcETBrjMjYmPgEuAP6bI/klTGNwL2AK4u2H4osGtE/JDkd+SWiBgSEbcAfwF+lG63HfBCREyTtD6wUkSU1IqUh2jib1DjId3/xr/ON1bpy8OXnMytZx3D7268i89mJ58f2tXUcOvZx/DgxSfx4lvv8cZ7k4sPWIWazGujwfIhe+/CzFmfs+cRp/C3kQ/wjcEDaF9Tw6NPjqX78l355mqrtlC0laWpz+PRRMIPP+pA9tnzx6y75pbc/Jc7OPPsU1siPLN5mvm72pSOW29M3cef8tXLb5Y7KmvFKuIkx4gYJ2kAyeDx3karuwI3SFqN5ETWDuny7YDLI6I2PUZhdfnO9OezwPcX8LT/jIh64GVJDSWV7dPbc+njTiQD7tGL8XL2ljQMWAP4cUQ0VEeHSfo5SctGd+Al4C7gfyTtJFuSfHjYgWTc9Fij4/6dpE3ku8C2wEEF6/aSNILk/3cfYC3mDewbbJoufzx901sKeKJgfeNBe4MFxb0wx0vaD5hFMoiO9DkbnmMN4J2IeD19fANwFPMG0zcX/Lwovb8dsFbBG3aXtMUDYGREfLGAWK4F/pUe+2DgurRl5SLgwEW8DtK8jgC45JTDOGT37yxql8z07t6VyR/PmPt46scz6NWty3zb/OvRsRy8y5ZIYuUVe9BvhW68M+kj1hk0r1rdpeOybLTmQP437g1WW2nFFou/terdszuTP5o+9/GUaR/Tq8fy823TqeNynHnCYUDyprvDAcfRb8UVuO/RJxj15LM8NuZ5vvp6Dp/P/oKTz/0z55x0ZIu+htbk4B//iP0P2AuA58eOp1//eb9jffv1ntv+0aBHj258c51vMPaZ5E/WP+68l1vvdM+1tazaKdNov+K89qX2vXtSO7V5X1ovu/436ThsU1bdcmO0VAdqOi3Hiuf+nMknnZdVuC2uMmvM2aqUCjbASOACCtpDUr8FRqUV1F1IqsKQDEIX9P/8q/RnHQv+kPFVwX0V/PxdWv0cEhGDI2Jx/9LfEhHfJKlI/17Simll/s/AnmnF9qqC1/FYuu0qJAPB9Ugq640H9XcB+wMTI2JuX4CkVUmq9Numlfx7Co5dSMBDBa9trYg4pGD950U7LDzuhbkofY4tIqLwg0LDcyzqu/Ro4n4NsFlB/P0iYtaCYp+7c8R7wBRJ2wCbkLQjdQbWBh6RNIHkw8dINXGiY0RcGREbRsSGeQ6uAb45sB8TJ0/j/akfM6e2lvufHMdWG6w53zYr9uzKUy+9BcD0GbOYMGka/Xt15+OZnzHz8+QzyJdfz+HJF99kQN/iXthqtPYaA3n3g8m8P3kqc+bUct8jT7L1pkPn22bmZ58zZ07SB3zHfaMYuvY36NRxOY47eB/+/ddLeODGP3L+KUez8XprVfXgGuDaq/7KsG/vyrBv78q99zzMXvvuDsDQjdZj5szPmDLlo/m2//TTmXTp0plBgwcAsPWwzXn9tbdaOmyrcl+Of40Oq/Slfb/e0KE9XYZvxeejnmzWvtMuuo53hu3PO9sdwKSfncPsp15oU4Nra1pFVLBT1wIzImK8pK0Llndl3kmPBxYsfxA4XNIjEVErqXujKnYpHgB+K+mvEfGZpH7AnLSVY7FExBNKZkf5CXBuunha2ve8J3B7umw0cCYwOiLqJX1McpLeKY2O94Wkk4DXmV8XkgHmjLQSvyPwSLpuFslgchrwJHCppMER8Wba392/oIrclIbBdFNxL4lXgQENsZB8cHi0YP3eJG07ezOvyv4gcDRwPiSzhUTE800cu+E1F7qapFXkpoioI+lhnzvTjKRHgBMi4pklfF2Zat+uHacc8D2OOO866uuD3bYayuD+vbn130lH1V7bbsKI3bbhl1fczh4n/5EgOG7v79Ktc0denziJ0664nfr6oD7q2X6Tddhq/W/k/Ipah/bt2nHqUQdy+KnnUldfz+7bb8XgAf259e7kPN+9dt6Otyd+yC/Ov4yamhoGrdKP3xw/IueoK8NDDzzCdttvxZgXHuaL2V9w7JHz/qzdfPtVHH/0L5g8eSrHH3Ma1930J+rrgxmfzuDYo5IWkV69evLwo3fSuXMn6uvrOezIA/nWxjvy2awFfqaueif++hzGPDeOTz+dyba77ceRh+zPHrt8N++wWr+6ej4688/0v/osqKlh5p0P8vWb79J17+Sc+Rm33Eu7nt1Y+baLqem0HNQHy//fbry782HUfz57EQevfJU600eWKmaAHRHvk/TZNnYeSYvIT4H/FCy/GlgdGCdpDkl19ZIljOFBSWsCT6StCJ8B+wFTJd0MbE1ywt77wK8j4hpJh6f7NjXh6LnAWJLWj6tIZgOZAIwpeM4J6XM1VKz/SzLwnf8sq2Tbxv3RRMQLkp4jad14G3i8YPWVwH2SJqV92AcCNzecUEjSk73AAXZEfCqpybgLSToDeCYiRi7oWI2O+6Wkg4DblMz8MQYozN/Skp4iqVrvmy47luQDwjiS3+vRwOFNHH4UcLKk50m+jbiF5NuR69JbRdtiyBpsMWSN+Zbtte0mc+/36taFK04+uGi/1Vfuw61nHVO03BJbbjyELTceMt+yvXaeN1PlkLVW457rLlzoMTZaby02Wm+tTOKrZCf9rOmp+fbd88dz799790Pce/dDRdtMnTqNddcs6TSYqnX+b0qejbbqfT56DJ+Pnv9tbsYt87pW66Z9wjvD9l/oMb4YM44vxjTu0LS2SM1t0jdrDdKWjQ0jYloZj7khSdvKFktynC/H3OF/TGW2zEZ78PWEVv3FQUVaasCG9Oyyet5htDnTZr7OnGlv5x1Gm9Oh50BeX7M5s+Bac63+yv1QxrlYfzpgn0zf/y6c8PeKm4apYirYZllQcnGhI5g3k4iZmZnZEvEA2ypKRAwo8/HOIZ2G0czMzBafv74t5gG2mZmZmZXMJzkWq6Rp+szMzMzMWj1XsM3MzMysZOEmkSKuYJuZmZmZlZEr2GZmZmZWMvdgF3MF28zMzMysjFzBNjMzM7OS1bsHu4gr2GZmZmZmZeQKtpmZmZmVzPXrYq5gm5mZmZmVkSvYZmZmZlYy92AXcwXbzMzMzKyMXME2MzMzs5J5HuxirmCbmZmZmZWRK9hmZmZmVrJwD3YRV7DNzMzMzMrIFWwzMzMzK5l7sIu5gm1mZmZmVkauYJuZmZlZydyDXcwVbDMzMzOzMnIF28zMzMxK5h7sYq5gm5mZmZmVkSvYZmZmZlay+nAPdmOuYJuZmZmZlZEr2GZmZmZWMtevi3mAbWZmZmYlq/cQu4hbRMzMzMzMysgVbDMzMzMrmS80U8wVbDMzMzOzMnIF28zMzMxK5gvNFHMF28zMzMysjFzBNjMzM7OSeRaRYq5gm5mZmZmVkSvYZmZmZlay1j6LiKTuwC3AAGACsFdEfNLEdhOAWUAdUBsRGy7O/oVcwTYzMzOztuxk4N8RsRrw7/TxggyLiCENg+sS9gc8wDYzMzOzJVCf8a0MdgVuSO/fAOyW9f4eYJuZmZlZqyVphKRnCm4jFvMQvSNiEkD6s9cCtgvgQUnPNnqO5u4/l3uwzczMzKxkEdn2YEfElcCVC9tG0sPAik2s+sViPNXmEfGhpF7AQ5JejYjRi7H/XB5gm5mZmVlFi4jtFrRO0hRJfSJikqQ+wNQFHOPD9OdUSf8ANgZGA83av5BbRMzMzMysZPVEprcyGAkckN4/APhX4w0kdZTUueE+sD3wYnP3b8wDbDMzMzNry84BviPpDeA76WMk9ZV0b7pNb+C/kl4AngbuiYj7F7b/wijrvhmzKuJ/TGZmVilUrgPtsvLOmb7/3TXx7rLF2lLcg21WJq+sNjzvENqcNd+4l5cH7ZR3GG3OWm/dw/2998k7jDZnhyl/5/U1d8g7jDZn9VfuZ860t/MOo03p0HNg3iG0eR5gm5mZmVnJWvuVHPPgHmwzMzMzszJyBdvMzMzMSlammT7aFFewzczMzMzKyBVsMzMzMyuZZ6Qr5gq2mZmZmVkZuYJtZmZmZiWrzzuAVsgDbDMzMzMrmafpK+YWETMzMzOzMnIF28zMzMxK5mn6irmCbWZmZmZWRq5gm5mZmVnJPE1fMVewzczMzMzKyBVsMzMzMyuZe7CLuYJtZmZmZlZGrmCbmZmZWck8D3YxV7DNzMzMzMrIFWwzMzMzK1m9ZxEp4gq2mZmZmVkZuYJtZmZmZiVz/bqYK9hmZmZmZmXkCraZmZmZlczzYBdzBdvMzMzMrIxcwTYzMzOzkrmCXcwVbDMzMzOzMnIF28zMzMxKFp4Hu4gr2GZmZmZmZeQKtpmZmZmVzD3YxVzBNjMzMzMrI1ewzczMzKxk4Qp2EVewzczMzMzKyBVsMzMzMyuZZxEp5gG2mZmZmZXMJzkWc4uImZmZmVkZuYJtZmZmZiVzi0gxV7DNzMzMzMrIFWwzMzMzK5l7sIu5gm1mZmZmVkauYJuZmZlZyXyhmWKuYJuZmZmZlZEr2GZmZmZWsnrPIlLEFWwzMzMzszJyBdvMzMzMSuYe7GKuYJuZmZmZlZEH2GZtSMcthjLwgSsZ9PDV9Bjxg6L1Sw3szyq3/p41XvoX3Q/5/nzr+vzuOFZ78m+ses+fWyrcitFxy6EMeugKBv/nKnoc1nReB9x2Ad94+Z/0OLRRXs/5Cas//VcG3ndpS4Xb6q151gFs8eQf2HzUuXRZZ0CT2yy78gpset+ZbPHERax35U9Qh3bzre8yZCDf/fBv9N55EwBqlu7Apvefybf+cy6bP3o+g0/cM+uX0Wot9+2hDLj3agbcfy3dDt2raH2HVfuz0s0XMfiFkXQ7aI/iA9TUsPIdl9D3st+0QLRtw2lnX8iWO+3DbvsdnncouaiPyPRWiZo1wJb0C0kvSRon6XlJm0g6TtJy5Q5I0nckPStpfPpzmwVsJ0mnSXpD0uuSRkn6ZjOOv5uktZYgvuUlHbmQ9RMkPdZo2fOSXiz1OSuJpCGShhc8lqSLJb2Z/v5ssID9JkjqWfB4a0l3L+R5jpf0paSuzYjp1MV9HY32P13SCUtyjBZRU8OKpx/Je4f+ird2PJwuO2/FUoNXmm+Tuk9nMeW3l/Px1XcU7f7pnQ/z3sG/bKloK0dNDX1OP4KJB/+aN797BF132bI4rzNmMfmMK5h+zZ1Fu8+442EmHvSrloq21eu57RCWW7UPj216HC+ecBVrnXdok9utftoPmXDFPTy22fHM+fQz+v+w4K2gRqzxyx8ybdQLcxfVfzWHMd//Lf/b5iT+t+3J9NxmCF2HDs765bQ+NTX0+uVRfDDiNCbsMoIuO23NUoNWnm+T+hmzmHrWZXxybfHfAYDl99+Nr99+ryWibTN2G/4dLr/wzLzDsFZkkQNsSZsBOwMbRMS6wHbAe8BxQNkH2MA0YJeIWAc4ALhpAdsdBXwLWC8iVgd+B4yUtMwijr8bUPIAG1geWOAAO9VZ0koAktZcgudaIpLy6LEfAgwveLwjsFp6GwFcVqbn2RcYA+zejG2XaIBdKZZdd3W+fvdD5rw3GebUMvOe0XTedrP5tqn7eAZfjn+DqK0r2v+LMS9SN2NWS4VbMZZdb/68zrh7NJ2323S+beqmJ3llTm3R/rPHvETdp85rg947bMiHt40GYMazb9Khy3Is3Wv5ou16fPubTLnrKQA+vHU0vXfccO66VQ7dgSl3P83X02bOt0/d7K8AUId2qH07qrEtdJl112DOxEnMeT/9O3Dvo3TcpvjvwFcvvg5N/B1o37snnbbaiBm3399SIbcJGw5Zh65dOucdRm4i4/8qUXMq2H2AaRHxFUBETAP2BPoCoySNApB0maRn0kr33O+VJA2X9Kqk/6aVzLvT5R0lXStpjKTnJO2aHv+5iPgw3f0lYBlJSzcR10nAMRExO93vQeB/wI/S439WEMOekq6X9C3ge8D5aVV5kKRHJP1B0v8kvShp43Sf+aqW6boBwDnAoHT/8xeQs1uBvdP7+wI3FxynnaTz09c9TtJh6fJOkv4taWxavd+1IE/3SHohjWHvdPnciq+kDSU9UhD3lZIeBG6UtIKkO9LnGyPTYeuCAAAgAElEQVRp84LtbpD0YHqs70s6L33u+yV1SLcbKunR9NuEByT1SZc/IulcSU+n3yBsIWkp4Axg7zQ/ewO7AjdG4klg+YZjlErSIKATcFqa34blnSRdl76GcZL2kHQOsGwaz18lDSj8NkHSCZJOT+//OM3RC2nOsvgAmZn2K/agdtK0uY/nTJ5G+949coyobWjfuwdzCvJaO3kaHZzXki3dpztffDB97uMvJ33M0n26z7dNh+6dmTNzNlFXn2zz4bxtll6xG7133IiJNzxUfPAa8a1/n8M2L13J9EfHM2Psm9m9kFaqfa8e1E7+aO7j2imL9/u6wimH8dEF10B9ZQ5qzFqL5gywHwRWSgdRf5a0VURcDHwIDIuIYel2v4iIDYF1ga0krZtWk68AdoyIbwMrFBz3F8B/ImIjYBjJoLdjo+feA3iuYXDfQFIXoGNEvNVo+2eABbaJRMT/gJHAiRExpGD/jhHxLZLK9LWLyMfJwFvp/icuYJvbgYZGzF2AuwrWHQLMSF/3RsCPJa0KfAnsHhEbkOTj95IE7AB8GBHrRcTaQHPKCkOBXSPih8AfgYvS59sDuLpgu0HATiSD4L8Ao9JvDr4AdkoH2X8C9oyIoSS5Oatg//YRsTHJtxm/joivgV8Bt6T5uQXoR/KNR4P302VLouFDy2PAGpJ6pct/SZLbddJvW/4TEScDX6Tx/GgRx70zIjaKiPWAV0j+Xy2UpBHpB8tnbp0xsfRXVBYqXlShvWutiprIq5VX49/TplKebrPmbw/gtTP/1vQAsD7437Yn88iQI+m6wSA6faN/+WNt7Zr4fY1m/h3ouPXG1H38KV+9XH0fTGzJuAe72CJbCCLiM0lDgS1IBn63SDq5iU33kjQiPWYfkjaMGuDtiHgn3eZmkjYBgO2B7xVUiZcBViYZ2KCkn/rcdLvmEqV9KXgzQESMltRFUvH3lYvnY+ATSfuQvJ7ZBeu2B9aV1HAGTleS9on3gbMlbQnUkwxCewPjgQsknQvcHRHz9XcvwMiI+CK9vx2wlub90e0iqeF7rPsiYo6k8UA75g3exwMDgDWAtYGH0v3bAZMKnqeh4fTZdPumNPlWuQTLAPYh+TBSL+lO4AfApSSvdZ+5O0d8soD9F2RtSWeStAF1Ah5Y1A4RcSVwJcArqw3P9a9A7eRptO8zt42dDiv2pHbqxzlG1DbUTp5Gh4K8tl+xJ3OmTF/IHtbYygdtT//9kh7qGc+/xbL9evBpum6ZPt35avL8/1TnTJ9Fhy7LoXY1RF09y/Sdt02XIQMZcvlPAOjQozM9txtC1NUx9b5n5u5fO3M2Hz/+Mj2HDeGzV9/P/gW2IrVTptF+xXm1rPa9m/93YNn1v0nHYZuy6pYbo6U6UNNpOVY89+dMPum8rMI1a7Oa1aMbEXXAI8Aj6WDsgML1aQX2BGCjiPhE0vUkA+aFlX4E7BERrxWtkPoD/wD+r4kqNRExU9LnkgZGxNsFqzYAHm3YrGD5ovqyGw+MAqhl/gr/oo7R2C0kg74DGy0XSWvLfIM3SQeSVPiHpoPeCcAyEfF6+gFnOPA7SQ9GxBmN4msc2+cF92uAzQoG3A3PB9DQ9lMvaU7MK3PUk/xuCHgpIuZv4Jun4ZuFOhb8u/Q+UHhGWH+Sbz8amw50I+nBB+hecL8w7nVJPpA0DPqXAt4myXVzPmAt7P/r9cBuEfFC+v9j60Ucq1X5YvzrLDWgLx3692bOlOl02WlLPvip3xiX1BfjXmepAf3m5rXrzlvywfEL6g6zpky87kEmXvcgACtstz4rH/xdJv3jf3QdOpg5s2bz1dRPi/b5+PGX6b3LJkz+5xP03WtLptyfDKBHb3Ts3G3W+eMRTH1oLFPve4YOPToTc+qonTmbmmU60GPLdXjnkpEt8wJbkS/Hv0aHVfrSvl9vaqdOp8vwrZh04rnN2nfaRdcx7aLrAFh2o3XpdvAeHlxbs1Rqn3SWmnOS4xqSVitYNAR4F5gFNFRCu5AM6mZI6k1yYhvAq8DAtHcZ5vUlQ1IdPCZtg0DS+unP5YF7gFMi4vGFhHY+cLGkZdP9tgO+DfwtXT9F0pqSapj/RLjCuBs09DV/m6TFYAYwgWTAjpKZL1ZdyP5N+QdwHsVV0AeAIwp6nFdPW2O6AlPTwfUwYJV0fV9gdkT8BbigIaY0vqHp/SbmWZrrQeDohgeShjQj9gavASsoOdEVSR206JlaGudnJPB/SmxKkt9JTez3CLB/+jztgP2AUU1sty9wekQMSG99gX6SVqH4tXZL785pyDcwBeglqYeS3v6dC47dGZiUbruodpLWp66eyb+5jJWuPZNB91/BzPse4+s3J7L8vsNZft/kvNN2Pbsx+LEb6X7w7vQ8ch8GP3YjNZ2WBaDvRT9nwK0XsvSq/Rn82I103XNxvjxqw9K8rnz9bxn8wOXMvPe/fPXGRLrtuyPd9k3+1LXr2Y3V/ntDktej9ma1/94wN6/9/vBzBtz+e5ZetT+r/fcGlv9Bdef1o4efY/a7U9jyqT+y9u9H8PJJ87ryhv71JJbunfyzfe3MvzHg8J3Y4sk/sFS3zrz/t6b+HMyzdO9ubHznL9l81Lls9sDZTH90HB89NDbT19Iq1dXz0Zl/pv/VZzHg7iuZdf9ovn7zXbruPZyue8/7O7DqqJtY/sDd6X74vqw66iZqOlbUKSetzom/PocfHXY8Eya+z7a77ccddy3yC1Br47So3qy0evonkq/Na4E3Sdo89iWZyWNSRAxLq9abkFQTvyJpU7he0i4kg+FpwNNA74j4UTow/gPJTCACJkTEzpJOA04B3igIY/uImCrpauDyiHgmHZj/imRQVgdMBo6OiPFp3HuStJi8B7wIdIqIA5Wc5HdVGuOewDXAE8BWJB8UDo6Ip9P4/gX0Ipmt4tskveQTJP2NpNf8vog4UdLzETEkfd4JwIbpyaANORxA0t6xdjrgP5OkN1vARyQzm3Qg6dXuADwPbE7yQWWNNH/1wBzgiPT1b5HGPgV4Kn3OrdMT9j6LiAvS5+5JUt1dk6TKPDoiDm9iu88iolN6f+66dEB+MckHgPbAHyLiKiUnVZ6QxtITeCYiBkjqTvIhogPJzC63ApeQ9JLPBg6KiGfS57kXODQiPlQy3d5lJD30ImlXOTmtrm8IHB4Rh0p6J/3/8GpBfi9M83Bpehua/k78JiLuTNtrvgeMTX/3jgWOBd4BPiD53Ttd0hHAz0k+QI4HOqe/M/PlakHybhFpi9Z8415eHrRT3mG0OWu9dQ/3995n0RvaYtlhyt95fc0d8g6jzVn9lfuZM+3tRW9ozdah50BYeJfBYhnUc4NM3//emja24k6GWeQAe4mfQOqU9nGLZPDzRkRclOmTLobCgWLesVhl8wC7/DzAzoYH2NnwADsbHmCXnwfY2WuJKzn+WNLzJFPudSWZVcTMzMzM2oDWPg+2pO6SHlJyccKHClpIC7dZQ8mUvg23mZKOS9edLumDgnXDi59lfplfiCStVreainVjEbF13jGYmZmZWWZOBv4dEeekM+GdTHI9lbnSSTca2n3bkbSQ/qNgk4sW1SpaKI8r/ZmZmZlZGxFRn3cIi7Ir82YGu4FkYoWTFrQxsC3JNU/eLfUJW6JFxMzMzMwsL70bZjBLf/ZaxPb7UHAV7tTRSq4SfW1TLSaNeYBtZmZmZiWrJzK9qeCqyeltROMYJD0s6cUmbrsuzmuRtBTJzGO3FSy+jOTq10NILrj3+0Udxy0iZmZmZlayrGekK7xq8kK22W5B6yRNkdQnIiZJ6gNMXcihdiSZ1ndKwbHn3pd0FXD3omJ2BdvMzMzM2rKRzLsK+QEk1zlZkH1p1B6SDsob7E5yfZWFcgXbzMzMzEpW3/ovlX4OcKukQ4CJwA9g7tWyr46I4enj5YDvAIc12v+89MJ7QXIl7cbri3iAbWZmZmZtVkRMJ5kZpPHyD4HhBY9nAz2a2G7/xX1OD7DNzMzMrGRZ92BXIvdgm5mZmZmVkSvYZmZmZlayelewi7iCbWZmZmZWRq5gm5mZmVnJovXPItLiXME2MzMzMysjV7DNzMzMrGSeRaSYK9hmZmZmZmXkCraZmZmZlawCruTY4lzBNjMzMzMrI1ewzczMzKxk7sEu5gq2mZmZmVkZuYJtZmZmZiXzlRyLuYJtZmZmZlZGrmCbmZmZWcncg13MFWwzMzMzszJyBdvMzMzMSuZ5sIu5gm1mZmZmVkauYJuZmZlZydyDXcwVbDMzMzOzMnIF28zMzMxK5nmwi3mAbWZmZmYlC5/kWMQtImZmZmZmZeQKtpmZmZmVzC0ixVzBNjMzMzMrI1ewzczMzKxknqavmCvYZmZmZmZl5Aq2mZmZmZXMs4gUcwXbzMzMzKyMXME2MzMzs5K5B7uYK9hmZmZmZmXkCraZmZmZlcwV7GKuYJuZmZmZlZEr2GZmZmZWMtevi8llfbPqI2lERFyZdxxtiXOaDec1G85rNpxXa+AWEbPqNCLvANog5zQbzms2nNdsOK8GeIBtZmZmZlZWHmCbmZmZmZWRB9hm1ck9guXnnGbDec2G85oN59UAn+RoZmZmZlZWrmCbmZmZmZWRB9hmZmZmZmXkAbaZmZmZWRl5gG1mZmZmVka+VLqZmVmVkbRBRIzNO45KJumnC1sfERe2VCzW+riCbVbFJI3PO4ZKJGklSX+X9JikUyV1KFj3zzxjq2SSviHpPkn3SBok6XpJn0p6WtKaecdXqSRt0Og2FBgpaX1JG+QdXwXrvIibVTFP02fWxkn6/oJWAZdHxAotGU9bIOkh4A7gSeAQYCiwS0RMl/RcRKyfa4AVStJo4HygE3AOcBJwC7AzcFxEbJtjeBVLUj3J7+pXBYs3TZdFRGyTS2BmbZgH2GZtnKQ5wF+Bpv6x7xkRrrQsJknPR8SQgsf7AacA3wNuiwhXBUtQ+OFE0psRMbhg3VjntTSS9gSOAc6NiHvTZe9ExKr5RtY2SFqG5IP2N4FlGpZHxMG5BWW5cw+2Wds3DrggIl5svELSdjnE0xZ0kLRMRHwJEBF/kTQZeADomG9oFa1dwf3G/atLtWQgbUlE3C7pfuC3kg4CfkbTH7itNDcBrwLfBc4AfgS8kmtEljv3YJu1fccBMxewbveWDKQNuRrYpHBBRDwM/AAo+iBjzXappE4AEfHnhoWSBgMP5xZVGxARn0XE8cDZwA0kbThWHoMj4pfA5xFxA7ATsE7OMVnO3CJiViUkdY+Ij/OOoy1xTrPhvGajIa+SBHSOiAV98LbFIOnpiNg4PYfgSGAy8HREDMw5NMuRK9hm1eMpSbdJGp6+wdqSc06z4bxm4ylJtwE7ALPyDqYNuVJSN+CXwEjgZeC8fEOyvLmCbVYl0oHKdsDBwMYkszNcHxGv5xpYBXNOs+G8ZsN5NWs5HmCbVSFJw4C/kJyQ9wJwckQ8kW9Ulc05zYbzmg3ntXwk/aqp5RFxRkvHYq2HZxExqxKSegD7AfsDU0im7RoJDAFuAzxl12JyTrPhvGbDec3M5wX3lyGZt92ziFQ5D7DNqscTJNNJ7RYR7xcsf0bS5TnFVOmc02w4r9lwXjMQEb8vfCzpApIPLlbF3CJiViUk7RURtzZa9oOIuC2vmCqdc5oN5zUbzmvLSE94fDoiVss7FsuPB9hmVaKpK+H56nhLxjnNhvOaDec1G5LGM+/CPe2AFYDfRsSf8ovK8uYWEbM2TtKOwHCgn6SLC1Z1AWrziaqyOafZcF6z4bxmbueC+7XAlIhwXqucB9hmbd+HwDPA94BnC5bPAo7PJaLK55xmw3nNhvOarTMjYv/CBZJuarzMqotbRMyqgKR2wI0R8aO8Y2krnNNsOK/ZcF6z07jNRlJ7YFxErJVjWJYzX8nRrApERB3QQ9JSecfSVjin2XBes+G8lp+kUyTNAtaVNDO9zSKZAvFfOYdnOXOLiFn1eBd4XNJICuZtjYgL8wup4jmn2XBes+G8llFE/A74naTfRcQpecdjrYsH2GbV48P0VgN0zjmWtsI5zYbzmg3nNRtPS+oaETMAJC0PbB0R/8w5LsuRe7DNqoykjhHx+aK3tOZyTrPhvGbDeS0vSc9HxJBGy56LiPXzisny5x5ssyohaTNJL5NewlfSepL+nHNYFc05zYbzmg3nNTNNjaXcIVDlPMA2qx5/AL4LTAeIiBeALXONqPI5p9lwXrPhvGbjGUkXShokaaCki5h/OkSrQh5gm1WRiHiv0aK6XAJpQ5zTbDiv2XBeM3EM8DVwC3Ab8AVwZK4RWe78FYZZ9XhP0reASKfqOpb0q2IrmXOaDec1G85rBtJ+9pMbHktaGTgKOD+3oCx3rmCbVY/DSf7o9wM+AIakj610zmk2nNdsOK8ZkdRT0hGSRgOjgN55x2T58iwiZmZmZotJUmdgd+CHwOrAP4C9I6J/roFZq+AKtlmVSE++uUvSR5KmSvqXpIF5x1XJnNNsOK/ZcF7LbipwCHAWMCgifkbSi23mAbZZFfkbcCvQB+hLcjLOzblGVPmc02w4r9lwXsvrVGAZ4DLgFEmDco7HWhEPsM2qhyLipoioTW9/AdwjtmSc02w4r9lwXssoIi6KiE2A7wEC/gn0lXSSpNXzjc7y5h5ssyoh6RzgU+DvJG+qewNLA5cCRMTH+UVXmZzTbDiv2XBesydpHWBfkl5sV7SrmAfYZlVC0jsLWR0R4V7MxeScZsN5zYbzatZyPMA2MzMzKyNJV0bEiLzjsPz4QjNmVUJSB+AI5l0a+RHgioiYk1tQFc45zYbzmg3ntUVdkXcAli9XsM2qhKSrgQ7ADemi/YG6iDg0v6gqm3OaDec1G86rWcvxANusSkh6ISLWW9Qyaz7nNBvOazac1/KSdBfzz8ISwDRgVDpDi1Uxt4iYVY86SYMi4i1ILjoB1OUcU6VzTrPhvGbDeS2vC5pY1h3YT9LaEXFySwdkrYcr2GZVQtI2wPXA2yRztq4CHBQRo/KMq5I5p9lwXrPhvLYMSe2AZyNiSN6xWH5cwTarAukf/PWA1YA1SN5cX42Ir3INrII5p9lwXrPhvLaciKiTlHcYljNXsM2qhKRRETEs7zjaEuc0G85rNpzX8pLUvYnF3YD/AwZHxI9aOCRrRTzANqsSks4CugK3AJ83LI+IsbkFVeGc02w4r9lwXssrvXBPkHwbAPNOcnwEODMiZuYUmrUCHmCbVQlJTfVZRkRs0+LBtBHOaTac12w4r2YtxwNssyohqWdETMs7jrbEOc2G85oN57XlSFoxIibnHYflpybvAMwsW5J2kfQRME7S+5K+lXdMlc45zYbzmg3nNRfX5B2A5csVbLM2TtI4YK+IeFXSJsB5EbFV3nFVMuc0G85rNpxXs5bnafrM2r7aiHgVICKektQ574DaAOc0G85rNpzXDEnqDfQjOcnxw4iYknNI1gp4gG3W9vWS9NMFPY6IC3OIqdI5p9lwXrPhvGZA0hDgcpKZWT5IF/eX9ClwpGdnqW4eYJu1fVcBnRfy2Bafc5oN5zUbzms2rgcOi4inChdK2hS4juTCPlal3INtZmZmtpgkvRERqy1g3ZsRMbilY7LWw7OImFUxSTvnHUNb45xmw3nNhvO6RO6TdI+kvSV9K73tLeke4P68g7N8eYBtVt02yjuANsg5zYbzmg3ntUQRcSxwCTAMOAU4Nb1/aUQcnWdslj+3iJiZmZmVSNIPIuK2RS2z6uIBtlkbJ+n7C1sfEXe2VCxthXOaDec1G85rtiSNjYgNFrXMqotnETFr+3ZZyLoA/Oa6+JzTbDiv2XBeMyBpR2A40E/SxQWrugC1+URlrYUr2GZmZmaLSdJ6wBDgDOBXBatmAaMi4pNcArNWwQNssyoiaSfgm8AyDcsi4oz8Iqp8zmk2nNdsOK/lJ6lDRMzJOw5rXdwiYlYlJF0OLEdylvvVwJ7A07kGVeGc02w4r9lwXjOzsaTTgVVIxlUCIiIG5hqV5coVbLMqIWlcRKxb8LMTcGdEbJ93bJXKOc2G85oN5zUbkl4FjgeeBeoalkfE9NyCsty5gm1WPb5If86W1BeYDqyaYzxtgXOaDec1G85rNmZExH15B2GtiwfYZtXjbknLA+cDY0lmD7g635AqnnOaDec1G85rNkZJOp9kNpavGhZGxNj8QrK8uUXErApJWhpYJiJm5B1LW+GcZsN5zYbzWj6SRjWxOCJimxYPxloND7DN2jhJ20TEfxZ0sQlfZGLxOafZcF6z4byatTy3iJi1fVsB/6Hpi034IhOlcU6z4bxmw3nNkKTewNlA34jYUdJawGYRcU3OoVmOXME2qwKSaoA9I+LWvGNpK5zTbDiv2XBesyPpPuA64BcRsZ6k9sBzEbFOzqFZjmryDsDMshcR9cDRecfRljin2XBes+G8Zqpn+sGlHiAiaimYrs+qkwfYZtXjIUknSFpJUveGW95BVTjnNBvOazac12x8LqkHSbsNkjYFfPJolXOLiFmVkPROE4t9tbEl4Jxmw3nNhvOaDUkbAH8C1gZeBFYgaccZl2tglisPsM3MzMyWQNp3vQbJZdJfi4g5OYdkOXOLiFmVkLScpNMkXZk+Xk3SznnHVcmc02w4r9lwXrMhqR0wHNgW2B44RtJP843K8uYBtln1uA74GvhW+vh94Mz8wmkTnNNsOK/ZcF6zcRdwINAD6FxwsyrmebDNqsegiNhb0r4AEfGFJOUdVIVzTrPhvGbDec1G/4hYN+8grHVxBdusenwtaVnmnek+CPgq35AqnnOaDec1G85rNu6TtH3eQVjr4gq2WfU4HbgfWEnSX4HNgYNyjajynY5zmoXTcV6zcDrOaxaeBP6RXsxnDsmJjhERXfINy/LkWUTMqkg6V+umJG8AT0bEtJxDqnjOaTac12w4r+Un6W1gN2B8eFBlKQ+wzaqEpH9HxLaLWmbN55xmw3nNhvOaDUkPADumV8s0A9wiYtbmSVoGWA7oKakbSeUKoAvQN7fAKphzmg3nNRvOa+YmAY9Iuo+CnvaIuDC/kCxvHmCbtX2HAceRvJE+y7w315nApXkFVeGc02w4r9lwXrP1TnpbKr2ZuUXErFpIOiYi/pR3HG2Jc5oN5zUbzmu2JHWMiM/zjsNaBw+wzaqIpLWBtYBlGpZFxI35RVT5nNNsOK/ZcF7LT9JmwDVAp4hYWdJ6wGERcWTOoVmOPMA2qxKSfg1sTfLmei+wI/DfiNgzz7gqmXOaDec1G85rNiQ9BewJjIyI9dNlL0bE2vlGZnnyhWbMqseewLbA5Ig4CFgPWDrfkCqec5oN5zUbzmtGIuK9RovqcgnEWg0PsM2qxxfpNFK1kroAU4GBOcdU6ZzTbDiv2XBes/GepG8BIWkpSScAr+QdlOXLs4iYVY9nJC0PXEUyk8BnwNP5hlTxnNNsOK/ZcF6zcTjwR6Af8D7wIHBUrhFZ7tyDbVaFJA0AukTEuJxDaTOc02w4r9lwXstDUjvghojYL+9YrHXxANusjZO0wcLWR8TYloqlrXBOs+G8ZsN5zVZ6JcddIuLrvGOx1sMDbLM2TlI98BLwUcOigtUREdu0fFSVzTnNhvOaDec1W5KuADYARgJz58H2lRyrm3uwzdq+nwF7AF8Afwf+ERGf5RtSxXNOs+G8ZsN5zdaH6a0G6JxzLNZKuIJtViUkrfr/7d1/8OVVXcfx52tRdlFckfyBWCusgeaawmJNCpKKRuWI6egolfljRkhMhsqUaWxQpqK0pjHGxLBxsAmIQlNBUTFFkExhWfF3qIBmo2josiIgq+/++NyvflkJ3bv3fM/33s/zMbPD9/O5szOveQ3wOd9zz+cc4FjgacD1wJ9X1da+qeabnbZhr23Yq7RynMGWRqKqrk3ydmAv4LnAwYAP191gp23Yaxv22kaSDwA/Mlvp0ptxcwZbWnBJNgLPYZi1+jLDV8QXVNWtXYPNMTttw17bsNe2khy27HIdw3KcHVX18k6RtAo4wJYW3OQFp6uBtwM3sdNMiy/i7Do7bcNe27DXlZfkkqr65d451I9LRKTFdyo/fKDu3TPIArHTNuy1DXttKMm+yy7XAIcB+3WKo1XCGWxpJJKs8yvh2bLTNuy1DXttI8m1DL/ABNgBXAucWlWXdQ2mrhxgSyOR5PPA14BLgQ8BH66qbX1TzTc7bcNe27BXaeU4wJZGJMkG4HHA4cCvA9+qqkP6pppvdtqGvbZhr7OX5FnARVW1PckrGQ6d+VNPyBy3Nb0DSFoZSX6a4aH6OOBQhpPd/rlrqDlnp23Yaxv22syfTAbXRwBHA2cBb+icSZ05gy2NxGQngY8xHC7x9t55FoGdtmGvbdhrG0muqqpDk5wGfKKqzl661zub+nGALY1EkkcBRwBHAhuAa4BLquofugabY3bahr22Ya9tJLkA+ArwJIYdRG4BPlpVj+oaTF05wJZGJMneDA/YxwG/DVRVHdA11Jyz0zbstQ17nb0k9wB+lWH2+pokDwR+vqre2zmaOnKALY1EkiuAtcDlwGXAh6rq+r6p5pudtmGvbdhrW0nuz3CSIwBV9aWOcdSZA2xpJJLcr6q+3jvHIrHTNuy1DXttI8kxwF8D+wM3MCy/+WxVbeoaTF05wJZGJMlTgE3ccZbl1H6J5p+dtmGvbdjr7CX5OPBE4OLJy45PAI6tquM6R1NHbtMnjUSSM4BnAy9lOHHsWcCDu4aac3bahr22Ya/N3F5V/wusSbKmqj4AuLf4yDnAlsbjsVX1O8A3q+rVwGOAn+mcad7ZaRv22oa9tvGtycujlwL/lOR1DEema8QcYEvjccvkn99Jsj9wO3BgxzyLwE7bsNc27LWNpwHfAU4CLgK+ADy1ayJ1d7feASStmAuS7AO8FtgCFPCmvpHmnp22Ya9t2GsDVXVzkgcDB1XVWZNt+/bonUt9+ZKjNEJJ1jK85LSjqm7unWcR2Gkb9tqGveAL/lwAAAuiSURBVM5OkhcBxwH7VtVDkhwEnFFVR3WOpo5cIiKNQJIHJXl0kj0nt+4NvILhJDdNwU7bsNc27LWplwCHAzcBVNU1wP27JlJ3DrClBZfkJGArcDrwkSTPAz4D7MVwrK92kZ22Ya9t2Gtzt1XVd5cuktyNYfmNRsw12NLiOw54aFXdmGQD8HngyKr6SOdc88xO27DXNuy1rUuS/DGwV5InAycA7+ycSZ05gy0tvlur6kb4wdG9/+WDdbfZaRv22oa9tnUy8HXgE8DxwLuAV3ZNpO58yVFacEluAM5ddus5y6+r6sQVDzXn7LQNe23DXqWV5xIRafH90U7XV3ZJsVjstA17bcNeG0hy9V19XlWPXKksWn2cwZYkSdpFSbYyvMx4NsOa61uWf15V1/fIpdXBNdjSiCU5rneGRWOnbdhrG/Y6vao6BDgW2JthkP1nwCbgKw6u5QBbGrf0DrCA7LQNe23DXndDVX22qk6pqs0Ms9hvAX6/cyytAi4RkSRJmkKSBzG8NPp04JvAecDbqurbXYOpO2ewpRFL8oLeGRaNnbZhr23Y6/SSXMIwa3134PnA84ALgT2T7NsxmlYBZ7ClEUvypara0DvHIrHTNuy1DXudXpLr+OGJjcsHUwGqqjaueCitGm7TJy24u9hKKsADVjLLorDTNuy1DXtto6oO6J1Bq5cDbGnxPQA4mmF94HIBLl/5OAvBTtuw1zbsVVphDrClxXcBsHdVbd35gyQfXPk4C8FO27DXNux1hSW5qqoO7Z1D/bgGW5IkSZohdxGRRiTJEUu7BiS5X5IDe2ead3bahr22Ya+zl+Qvf5J7GhdnsKWRSHIK8GjgoVV1cJL9gX+pqsM7R5tbdtqGvbZhr20k2TI5aGb5vaur6pG9Mqk/12BL4/F04FBgC0BV/U+Se/WNNPfstA17bcNeZyjJi4ETgI077dRyL+DDfVJptXCALY3Hd6uqkhRAknv2DrQA7LQNe23DXmfrbODdwGnAycvub6+qG/tE0mrhGmxpPM5L8kZgnyQvAi4Gzuycad7ZaRv22oa9zlBVbauq64BXMBw0s/Rn7yQe3jNyrsGWRiTJk4FfYdj/9j1V9b7OkeaenbZhr23Y6+wl+QTDwDrAOuBA4HNVtalrMHXlAFuSJGlGkmwGjq+q43tnUT8uEZFGIskzklyTZFuSm5JsT3JT71zzzE7bsNc27HVlVNUW4Bd651BfzmBLI5Hk88BTq+ozvbMsCjttw17bsNc2kvzBsss1wGbgp6rq6E6RtAq4i4g0Hl/zwTpzdtqGvbZhr20s3+pwB3AhcH6nLFolnMGWRiLJ64D9gH8Dblu6X1Vv7RZqztlpG/bahr22lWQ9UFW1vXcW9ecMtjQe64HvMOwgsKQAH67Ts9M27LUNe20gyaOBNzOZyU6yDXhhVV3ZNZi6cgZbkiRpSpNTHF9SVZdOro8A/s6j0sfNGWxpwSV5eVW9JsnpDLNVd1BVJ3aINdfstA17bcNem9u+NLgGqKrLkrhMZOQcYEuLb+mlpiu6plgsdtqGvbZhr219dHJC5jkMv8A8G/jgZD/spW37NDIuEZEkSZpSkg/cxcdVVU9csTBaNRxgSyOR5GDgZcABLPv2yv/5T89O27DXNuy1jSQbq+qLP+6exsUBtjQSST4OnAFcCXxv6b5vuk/PTtuw1zbstY0kW6pq8073rqyqw3plUn+uwZbGY0dVvaF3iAVjp23Yaxv2OkNJHgZsAu6d5BnLPloPrOuTSquFM9jSgkuy7+THE4EbgLdxx0MmbuyRa57ZaRv22oa9tpHkacBvAMcA71j20Xbg3Kq6vEswrQoOsKUFl+RahjfbcycfV1VtXOFIc89O27DXNuy1rSSPqar/6J1Dq4sDbEmSpCkleTN3vr/4CzvE0SqxpncASSsjyUuS7LPs+j5JTuiZad7ZaRv22oa9NnMBcOHkz/sZ1mB/u2sidecMtjQSSbZW1SE73buqqg7tlWne2Wkb9tqGva6MJGuAi93+cNycwZbGY02SH6zBTLIHsGfHPIvATtuw1zbsdWUcBGzoHUJ9uU2fNB7vAc5LcgbDesHfBS7qG2nu2Wkb9tqGvTaQZDs/fIm0gK8Cr+gaSt25REQaicnXlscDRzE8CN4LvKmqvneXf1H/Lzttw17bsFdp5TjAliRJmkKSPYHfYjhwpoBPA2dX1W13+Re18BxgSyOR5CDgNODhLDtlzD1wp2enbdhrG/Y6W0keznDAzIcZjp8PsBk4HDimqj7dMZ46cw22NB5vBk4B/gZ4AvAC7vzgCf3k7LQNe23DXmfrdODFVfW+5TeTPAl4PUPHGil3EZHGY6+qej/DN1fXV9WrALeR2j122oa9tmGvs/WgnQfXAFV1MbBfhzxaRZzBlsbj1slLTtck+T3gK8D9O2ead3bahr22Ya+ztSbJ2p3XWydZh+Or0XMGWxqPk4B7ACcChwHPBZ7XNdH8s9M27LUNe52ttwDnJzlg6cbk5/OAf+ySSKuGLzlKkiRNYfJNwMsZfnEBuBn4q6o6vV8qrQYOsKUFl+Qdd/V5VR2zUlkWhZ22Ya9t2Gt7Se4FUFXbe2fR6uAaIWnxPQb4MnAO8J+4a8As2Gkb9tqGvTa288A6yeaq2tIrj/pzBltacEn2AJ4MHAs8ErgQOKeqPtU12Byz0zbstQ17XXlJzqyqF/XOoX4cYEsjkmQtw0P2tcCprhPcfXbahr22Ya/SynCJiDQCk4fqUxgerAcAfwu8tWemeWenbdhrG/baTpK7V9XtO927b1V9o1cm9ecMtrTgkpwFPAJ4N3BuVX2yc6S5Z6dt2Gsb9tpGkicwbMe3FrgKOK6qrpt8tqWqNneMp84cYEsLLsn3GbaOAlj+H3yAqqr1K59qvtlpG/bahr22keRjwPOr6lNJngmcBjy3qj6S5KqqOrRzRHXkEhFpwVWVB0rNmJ22Ya9t2Gszey69KFpV/5rkM8Bbk5zMHX+R0Qg5wJYkSdp1tyfZr6q+CjCZyT4KuAB4SN9o6s3faiVJknbdycADlt+oqv8GHg/8RY9AWj1cgy1JkrQbkuwFbKiqz/XOotXBGWxJkqQpJXkqsBW4aHJ9yI87nl6LzwG2JEnS9F4F/CLwLYCq2goc2DOQ+nOALUmSNL0dVbVtp3uuvx05dxGRJEma3ieT/CawR5KDgBOByztnUmfOYEuSJE3vpcAm4DbgHOAm4KSuidSdu4hIkiRJM+QSEUmSpCkleSc/uuZ6G3AF8MaqunXlU6k3l4hIkiRN74vAt4EzJ39uAr4GHDy51gi5RESSJGlKST5UVUfe2b0kn6qqTb2yqR9nsCVJkqZ3vyQbli4mP993cvndPpHUm2uwJUmSpveHwGVJvgCE4ZCZE5LcEzirazJ14xIRSZKk3ZBkLfAwhgH2Z32xUQ6wJUmSdkOSRwAPB9Yt3auqt/RLpN4cYEuSJE0pySnA4xkG2O8Cfg24rKqe2TOX+vIlR0mSpOk9EzgK+GpVvQB4FLC2byT15gBbkiRperdU1feBHUnWAzcAGztnUmfuIiJJkjS9K5Lsw3CozJUMh858tG8k9eYabEmSpBlIcgCwvqqu7hxFnblERJIkaUpJ3r/0c1VdV1VXL7+ncXKJiCRJ0i5Ksg64B3DfJPdh2AMbYD2wf7dgWhUcYEuSJO2644GTGAbTVy67vx14fZdEWjVcIiJJkrTrLgceC7ysqjYCrwY+CVwCnN0zmPrzJUdJkqRdlGQL8KSqujHJkcC5wEuBQ4Cf86CZcXOJiCRJ0q7bo6punPz8bODvq+p84PwkWzvm0irgEhFJkqRdt0eSpYnKo4B/X/aZE5gj578AkiRJu+4c4JIk3wBuAS4FSPKzwLaewdSfa7AlSZKmkOSXgAcC762qmyf3Dgb2rqotXcOpKwfYkiRJ0gy5BluSJEmaIQfYkiRJ0gw5wJYkSZJmyAG2JEmSNEMOsCVJkqQZ+j93GofQXd0t/QAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 720x720 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wCkyvLnC7el3"
      },
      "source": [
        "**Parameter**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KOIhVcqG7el3"
      },
      "source": [
        "columns2=['BMI',\n",
        "         'Gewicht',\n",
        "         'KH']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "awIDgnQU7el3"
      },
      "source": [
        "**Code**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zBC-NPhJ7el4",
        "outputId": "62de65c9-9bc8-4f32-cf09-21c00fa8d0ba"
      },
      "source": [
        "plt.figure(figsize=(10, 10), constrained_layout=True)\n",
        "corrSet = pd.DataFrame(rawData2[columns2])\n",
        "heatmap = sns.heatmap(corrSet.corr(),\n",
        "    annot=True, linewidth=0.2)\n",
        "plt.title('Korrelationsmatrix', fontsize=16); # Titel für die Grafiken festlegen, Strichpunkt unterdrückt Textausgabe von letztem Kommando"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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/ko+99bh7r//T8X+RrTbfbBjhw7QwZ86cfOD9J+TgQ1+QJUuW5ntnn5ZT/+OM/OhHP7t3zDe+8Z2ceuoZSZJHP/qR+dxnT8rej376sEJmfbDIkdlo330enS02f/Cww4Bp5eLLrszO22+THbfbOvPnz8vBv/v4fPPci1Ybc/mSX+ZJez88SbLrwu1y7XU35IYbJ7yhF8wq+z3xcfn5z6/IL35xVVasWJHPf/5LedZhB6025rbbbr/3+W9tumlaa1MdJqxXEmyAUcuW35jtHrLlvcfbLdgyv7rhptXGPHyXhfn69y9Iklz0syuz9LpfZ9kNN957/aXv+HCe//p351+/9t2pCBmmnYcu3D5XL7n23uMl1yzNQx+6/X3GHX74wbn4om/ly1/6VP78z18zlSHCejdhi0hV/Z+JrrfW3tc3HIDppapWOz72iD/IiZ/4Qv7ktSdmz513yCN23TFz585Nknz6Ha/Otgu2yA033ZKXvv1D2WXhdtl3rz2GETYMzfifmSRrrFB/6Uun50tfOj2/99Qn5W3Hvy4HHXLkVITHVJnlu4isqwf7AfUQVNWiJIuS5CMf+Uhe8pw/eCDTAEyp7RZsuVo1etnyG7PNgs1XG7PZppvk7a98YZJB0nDIK9+WhdsuSJJsu2CLJMlDtnhwnrHfY3LxZVdKsJl1rlmyNDvt+NB7j3dcuEOWLl221vHf/s73s9tuD8tDHrJVbrjh11MRIqx3EybYrbW3PZBJW2uLkyy+53DF9Zc/kGkAptSj9tg5Vy69LkuW3ZDtFmyR0797Xt71qhetNubm227PJhttlPnz5+Xfvn52Hv/I3bPZppvk9jvvSmstv7XJg3L7nXfl7At+nJc+9+AhfRIYnnPOPT977LFrdtllp1xzzS/zvOcdnmP+9JWrjdl9913y859fkSR53D57Z6ON5kuuNzQq2GtXVR+Y6Hpr7X/3DYep8rq3vivn/PeFufHGm3PAEUfnFccekz8etwgFZpt5c+fmTcc+Ny8/4cNZNTKSI37/ydljpx3y+TO+kyR53jOfml8sWZY3f/DkzJlT2X3H7fO2lx+VJFl+0y35y/d8LMlgN5JDnvqEPPVxew3ts8CwrFq1Kq/6y7/Oaf/52cydMyef/NQ/59JLf5pFf35MkmTxRz+T5zz70Bx99HOzYsXK3HnHnTnqhS8fctTQV020creq7k5ycZLPJ7k2yWqNVa21T03iPVSw4QGYv/VuuevCrw47DJhxNn7MQZm30cJhhwEzzsq7r7lvA/0DdMfn/3ZabA2zyfPe0u0z3R/r6sHeIcmfJHl+kpVJ/jnJv7XW/B0HAIA1m+VbL064TV9r7YbW2kmttd9P8uIkWya5pKqOmYLYAABgxpnUnRyr6vFJXpDkwCRfSfLD9RkUAADMVOta5Pi2JH+U5EdJTknyxtbayqkIDACAGcouIhP6mySXJ3ns6OOdoxvIV5LWWnvM+g0PAABmlnUl2LtOSRQAAGw4VLDXrrV25fhzVbV1khvaRPv7AQDALDXhLiJV9eSqOrOqvlBVj6uqizPYF3tZVblFGQAAjLOuFpEPJnlTki2SfCPJIa2171XVI5J8Lsnp6zk+AABmmja7W0QmrGAnmddaO6O19i9Jftla+16StNZ+vP5DAwCAmWddCfbYXz/uGHdNDzYAAIyzrhaRx1bVzRlsy7fJ6POMHj9ovUYGAMDMZBeRtWutzZ2qQAAAYEMwqVulAwDApM3y3ZzX1YMNAADcDxJsAADoSIsIAAB9zfJFjirYAADQkQQbAAA60iICAEBfWkQAAIBeVLABAOirqWADAACdSLABAKAjLSIAAHTVRtwqHQAA6ESCDQAAHWkRAQCgL/tgAwAAvahgAwDQl32wAQCAXiTYAADQkRYRAAD6sg82AADQiwo2AAB92aYPAADoRYINAAAdaREBAKAvLSIAAEAvEmwAAOhIiwgAAH01+2ADAACdqGADANCXRY4AAEAvEmwAAOhIiwgAAH2NWOQIAAB0IsEGAICOtIgAANBXs4sIAADQiQo2AAB9WeQIAAD0IsEGAICOtIgAANBVc6t0AACgFwk2AAB0pEUEAIC+7CICAAD0ooINAEBf7uQIAAD0IsEGAICOtIgAANCXRY4AAEAvEmwAAOhIiwgAAH25VToAANCLCjYAAH1Z5AgAAPQiwQYAgI60iAAA0JdbpQMAAL1IsAEAoCMtIgAA9GUXEQAAoBcJNgAAXbWRkWnxmIyqOriqflJVl1XVG9ZwfYuqOrWqLqiqS6rqJeuaU4INAMCsVFVzk3woySFJ9krygqraa9ywVya5tLX22CT7J3lvVW000bwSbAAAZqv9klzWWru8tXZ3klOSHD5uTEvy4KqqJJslWZ5k5USTWuQIAEBfM2eR48IkV485XpLkSePGfDDJl5Ncm+TBSZ7f2sQbfatgAwCwQaqqRVV17pjHovFD1vCy8b8dHJTk/CQPTbJPkg9W1eYTva8KNgAAG6TW2uIkiycYsiTJTmOOd8ygUj3WS5K8q7XWklxWVb9I8ogkP1jbpBJsAAD6mjktIuck2bOqdk1yTZIjkxw1bsxVSQ5I8u2q2i7Jbye5fKJJJdgAAMxKrbWVVXVckq8mmZvk4621S6rqZaPXT0ry9iSfrKqLMmgp+avW2vUTzSvBBgCgr4nXAE4rrbXTkpw27txJY55fm+SZ92dOixwBAKAjCTYAAHSkRQQAgL5mziLH9UIFGwAAOpJgAwBAR1pEAADoqmkRAQAAelHBBgCgLxVsAACgFwk2AAB0pEUEAIC+RmbOrdLXBxVsAADoSAUbAIC+LHIEAAB6kWADAEBHWkQAAOhLiwgAANCLBBsAADrSIgIAQFetaREBAAA6UcEGAKAvixwBAIBeJNgAANCRFhEAAPrSIgIAAPQiwQYAgI6mpEVk/ta7TcXbwAZn48ccNOwQYEZaefc1ww4BZrU2y1tEpiTBvuvCr07F28AGZePHHJQV118+7DBgxpm/9W55/85HDzsMmHFeddXJww5hg2GRIwAAfc3yCrYebAAA6EiCDQAAHWkRAQCgr5FhBzBcKtgAANCRBBsAADrSIgIAQFezfR9sFWwAAOhIBRsAgL5UsAEAgF4k2AAA0JEWEQAA+rIPNgAA0IsEGwAAOtIiAgBAV/bBBgAAulHBBgCgL4scAQCAXiTYAADQkRYRAAC6ssgRAADoRoINAAAdaREBAKAvu4gAAAC9qGADANBVU8EGAAB6kWADAEBHWkQAAOhLiwgAANCLBBsAADrSIgIAQFd2EQEAALpRwQYAoC8VbAAAoBcJNgAAdKRFBACArixyBAAAupFgAwBAR1pEAADoSosIAADQjQo2AABdqWADAADdSLABAKAjLSIAAPTVatgRDJUKNgAAdKSCDQBAVxY5AgAA3UiwAQCgIy0iAAB01UYscgQAADqRYAMAQEdaRAAA6MouIgAAQDcq2AAAdNXcyREAAOhFgg0AAB1pEQEAoCuLHAEAgG4k2AAA0JEWEQAAunKrdAAAoBsJNgAAXbU2PR6TUVUHV9VPquqyqnrDGq6/rqrOH31cXFWrqmrBRHNKsAEAmJWqam6SDyU5JMleSV5QVXuNHdNae09rbZ/W2j5J3pjkW6215RPNK8EGAGC22i/JZa21y1trdyc5JcnhE4x/QZLPrWtSixwBAOhqBi1yXJjk6jHHS5I8aU0Dq2rTJAcnOW5dk6pgAwCwQaqqRVV17pjHovFD1vCytXVvH5bku+tqD0lUsAEA2EC11hYnWTzBkCVJdhpzvGOSa9cy9shMoj0kkWADANDZDGoROSfJnlW1a5JrMkiijxo/qKq2SPL0JEdPZlIJNgAAs1JrbWVVHZfkq0nmJvl4a+2SqnrZ6PWTRoc+O8kZrbXbJjOvBBsAgK4muwf1dNBaOy3JaePOnTTu+JNJPjnZOS1yBACAjiTYAADQkRYRAAC6mkGLHNcLFWwAAOhIgg0AAB1pEQEAoKvWtIgAAACdqGADANBVGxl2BMOlgg0AAB1JsAEAoCMtIgAAdDVikSMAANCLBBsAADrSIgIAQFf2wQYAALpRwQYAoKs2ooINAAB0IsEGAICOtIgAANBVa8OOYLhUsAEAoCMJNgAAdKRFBACAruwiAgAAdKOCDQBAVyPu5AgAAPQiwQYAgI60iAAA0FXTIgIAAPQiwQYAgI60iAAA0JVbpQMAAN2oYAMA0JV9sAEAgG4k2AAA0JEWEQAAurIPNgAA0I0KNgAAXc32bfok2Buo7/z3pTnxE1/IyMhInnPAU3Lssw9c7frNt96et3z4s7l62fXZeP68vO0VR2XPnR+aJDn4Fcdn0wdtnLlz5mTu3Dk55cTXDeMjwLT01+98X8767g+yYKst88WTTxp2ODBtPOzpj8nTjz8mNXdOLjnlzJz74VNXu77wyY/MYR97dW6++rokyWWnn5MfvP+LSZKNNt80f/DuP8tDHr5j0lq+9rqP5pfnXTbVHwG6kWBvgFatGsk7/+lfsvhvXpntFmyZF7zx77P/vntn9512uHfMR79wRn5714X5x9f/WX5xzbKc8LF/ycfeety91//p+L/IVptvNozwYVo74tADc9QfPytvevvfDzsUmDZqTmX/d7wo//7Cd+XWpctz5Kl/m8u/9sMs/9m1q4279pyf5Msvee99Xv/044/JlWdemNNe9oHMmT838zbZeKpCh/ViUj3YVfUnkznH9HDxZVdm5+23yY7bbZ358+fl4N99fL557kWrjbl8yS/zpL0fniTZdeF2ufa6G3LDjTcPI1yYUfbd59HZYvMHDzsMmFa222f33HTFstx81XUZWbEqPz31e9ntmU+Y1Gs32myTLNzvt3PJKWcmSUZWrMrdN9++HqNlKoy0mhaPYZnsIsc3TvIc08Cy5Tdmu4dsee/xdgu2zK9uuGm1MQ/fZWG+/v0LkiQX/ezKLL3u11l2w433Xn/pOz6c57/+3fnXr313KkIGYAbbbPutcsu1y+89vnXp8my23Vb3Gbf94/fIUaefkMM/9bosePjCJMnmO2+TO5bfkgPfuygvOO0dOeDEP1PBZsabsEWkqg5JcmiShVX1gTGXNk+ycoLXLUqyKEk+8pGP5EVPfliHUPlNVK3+W9yxR/xBTvzEF/Inrz0xe+68Qx6x646ZO3dukuTT73h1tl2wRW646Za89O0fyi4Lt8u+e+0xjLABmAnqvpXC8Yvcrrv4inziKX+ZFbfflV1+/7E57KOvzqee/trMmTc32+69S858y6ez7Pyf52nHH5N9X3FYvvfef52i4KG/dfVgX5vk3CTPSvLDMedvSfLqtb2otbY4yeJ7Du+68Ku/SYzcT9st2HK1avSy5TdmmwWbrzZms003ydtf+cIkSWsth7zybVm47YIkybYLtkiSPGSLB+cZ+z0mF192pQQbgLW6denyPPihC+493myHBbntV79ebczdt95x7/MrvnlBfv8dL86Dttosty5dnluXLs+y83+eJLnstB9k35cfNjWBs97YB3sCrbULWmufSrJHa+1TYx5faK39eqLXMjyP2mPnXLn0uixZdkNWrFiZ0797Xvbf99Grjbn5ttuzYsXgjxD/9vWz8/hH7p7NNt0kt995V267484kye133pWzL/hx9hizOBIAxlt2weXZctfts/lO22TO/Ll5+GFPzuVfO2+1MZtus8W9z7d77G6pOZU7f31rbr/uptyydHm23G3wb81Ov/uoLP/ZNVMaP/Q22V1E9quq45M8bPQ1laS11nZbX4HxwM2bOzdvOva5efkJH86qkZEc8ftPzh477ZDPn/GdJMnznvnU/GLJsrz5gydnzpzK7jtun7e9/KgkyfKbbslfvudjSQa7kRzy1CfkqY/ba2ifBaab1731XTnnvy/MjTfenAOOODqvOPaY/PFhBw07LBiqtmokZ/7Np3LEZ16fmjsnl/7zt7L8p9fk0Uc/I0ly0cnfyB6H7pfHHHNARlauyso7V+Qrx33o3tef+ZZP5eAPvDxz58/LTVf9Kl977eK1vRUzxDAXGE4H1SaxE3hV/TiDlpAfJll1z/nW2g2TeA8tIvAAbPyYg7Li+suHHQbMOPO33i3v3/noYYcBM86rrjq5W1b8/Yc+Z1rcauZJ135hKJn+ZCvYN7XWvrJeIwEAgA3AunYRefzo029W1XuSfCHJXfdcb62dt8YXAgAwa02L8vUQrauCPf52S/uOed6SPKNvOAAAMLNNmGC31n5/qgIBAIANwWRvlf7OqtpyzPFWVfWO9RYVAAAz1rBvkT5TbpV+SGvtxnsORvfAPnS9RAQAADPYZHcRmVtVG7fW7kqSqtokycbrLywAAGaq2X4nx8km2Ccn+XpVfSKDxY3/K8mn1ltUAAAwQ00qwW6tvbuqLkpyQAZ3cXx7a83dYwAAYJzJVrAzeqMZN5sBAGBCI8MOYMjWdaOZ77TWnlpVt2T1PcMrSWutbb5eowMAgBlmXftgP3X064OnJhwAAJjZJtUiUlV/m+SsJGe31m5bvyEBADCTtczuXUQmuw/2FUmOSnJuVf2gqt5bVYevv7AAAGBmmuwuIh9P8vGq2j7J85K8NsmiJFpHAABYzUhb95gN2WRbRD6WZK8ky5J8O8lzk5y3HuMCAIAZabItIg9JMjfJjUmWJ7m+tbZyfQUFAAAz1WRbRJ6dJFX1yCQHJflmVc1tre24PoMDAGDmGZnlixwn2yLyR0l+L8nTkmyV5BsZtIoAAABjTPZOjodksE3f+1tr167HeAAAYEabbIvIK6vqYRksdLy2qjZJMq+1dst6jQ4AgBnHPtiTUFV/nuRfk3xk9NSOSb64nmICAIAZa7ItIq9Msl+S7ydJa+1nVbXteosKAIAZa2TYAQzZZLfpu6u1dvc9B1U1L8ks30IcAADua7IJ9req6k1JNqmqA5P8S5JT119YAAAwM022ReQNSY5NclEGt0j/z9bax9ZbVAAAzFgWOU6gqg6vqle21kZaax9N8rAk+yZ5U1U9d0oiBACAGWRdLSKvT/LlMccbJXlCkv2TvHw9xQQAADPWulpENmqtXT3m+DutteVJllfVb63HuAAAmKHsIjKxrcYetNaOG3O4Tf9wAABgZltXgv390ZvMrKaqXprkB+snJAAAZrKRafIYlnW1iLw6yRer6qgk542ee0KSjZMcsR7jAgCAGWnCBLu19qskv1NVz0jyqNHT/9la+8Z6jwwAAGagSe2DPZpQS6oBAFgn+2ADAADdSLABAKCjyd4qHQAAJmVkdneIqGADAEBPKtgAAHQ1YpEjAADQiwQbAAA60iICAEBXbdgBDJkKNgAAdCTBBgBg1qqqg6vqJ1V1WVW9YS1j9q+q86vqkqr61rrm1CICAEBXI8MOYJKqam6SDyU5MMmSJOdU1Zdba5eOGbNlkg8nObi1dlVVbbuueVWwAQCYrfZLcllr7fLW2t1JTkly+LgxRyX5QmvtqiRprf1qXZOqYAMA0NVITY99sKtqUZJFY04tbq0tHnO8MMnVY46XJHnSuGkenmR+VZ2Z5MFJ3t9a+/RE7yvBBgBggzSaTC+eYMiafhMYvwnKvCRPSHJAkk2SnF1V32ut/XRtk0qwAQCYrZYk2WnM8Y5Jrl3DmOtba7clua2qzkry2CRrTbD1YAMA0FWbJo9JOCfJnlW1a1VtlOTIJF8eN+ZLSX6vquZV1aYZtJD8aKJJVbABAJiVWmsrq+q4JF9NMjfJx1trl1TVy0avn9Ra+1FVnZ7kwgw2SPlYa+3iieaVYAMA0NVM2aYvSVprpyU5bdy5k8YdvyfJeyY7pxYRAADoSIINAAAdaREBAKCrkemxDfbQqGADAEBHEmwAAOhIiwgAAF2NrPEGibOHCjYAAHSkgg0AQFeTvIviBksFGwAAOpJgAwBAR1pEAADoyj7YAABANxJsAADoSIsIAABdjQw7gCFTwQYAgI5UsAEA6Mo+2AAAQDcSbAAA6EiLCAAAXdkHGwAA6EaCDQAAHWkRAQCgK/tgAwAA3ahgAwDQlQo2AADQjQQbAAA60iICAEBXzT7YAABALxJsAADoSIsIAABd2UUEAADoRgUbAICuVLABAIBuJNgAANCRFhEAALpqww5gyFSwAQCgIwk2AAB0pEUEAICuRtwqHQAA6EUFGwCAruyDDQAAdCPBBgCAjrSIAADQlRYRAACgGwk2AAB0pEUEAICu3CodAADoRgUbAICu3MkRAADoRoINAAAdaREBAKAr+2ADAADdSLABAKAjLSIAAHRlH2wAAKAbFWwAALoameU17ClJsDd+zEFT8TawwZm/9W7DDgFmpFdddfKwQwBmsSlJsOdttHAq3gY2KCvvvibv3/noYYcBM86rrjo5K66/fNhhwIyjqNOPFhEAALqyDzYAANCNBBsAADrSIgIAQFezew8RFWwAAOhKBRsAgK4scgQAALqRYAMAQEdaRAAA6Gqkhh3BcKlgAwBARyrYAAB0NTLLN+pTwQYAgI4k2AAA0JEWEQAAuprdDSIq2AAA0JUEGwAAOtIiAgBAV26VDgAAdKOCDQBAV/bBBgAAupFgAwBAR1pEAADoanY3iKhgAwBAVxJsAADoSIsIAABd2QcbAADoRgUbAICu7IMNAAB0I8EGAICOtIgAANDV7G4QUcEGAGAWq6qDq+onVXVZVb1hDdf3r6qbqur80cdb1jWnCjYAALNSVc1N8qEkByZZkuScqvpya+3ScUO/3Vr7o8nOK8EGAKCrGbQP9n5JLmutXZ4kVXVKksOTjE+w7xctIgAAzFYLk1w95njJ6LnxnlJVF1TVV6rqUeuaVAUbAICu2jRZ5lhVi5IsGnNqcWtt8dgha3jZ+ODPS/Kw1tqtVXVoki8m2XOi95VgAwCwQRpNphdPMGRJkp3GHO+Y5Npxc9w85vlpVfXhqtq6tXb92ibVIgIAwGx1TpI9q2rXqtooyZFJvjx2QFVtX1U1+ny/DPLnGyaaVAUbAICuZsoix9bayqo6LslXk8xN8vHW2iVV9bLR6ycleW6Sl1fVyiR3JDmytTZhD4wEGwCAWau1dlqS08adO2nM8w8m+eD9mVOLCAAAdKSCDQBAVyPTZBeRYVHBBgCAjlSwAQDoanbXr1WwAQCgKwk2AAB0pEUEAICuLHIEAAC6kWADAEBHWkQAAOhqptwqfX1RwQYAgI5UsAEA6KpZ5AgAAPQiwQYAgI60iAAA0JVFjgAAQDcSbAAA6EiLCAAAXdlFBAAA6EYFGwCArixyBAAAupFgAwBAR1pEAADoaqRZ5AgAAHQiwQYAgI60iAAA0NXsbhBRwQYAgK5UsAEA6GpkltewVbABAKAjCTYAAHSkRQQAgK6aFhEAAKAXFWwAALoaGXYAQ6aCDQAAHUmwAQCgIy0iAAB0ZR9sAACgGwk2AAB0pEUEAICu7IMNAAB0o4INAEBX9sEGAAC6kWADAEBHWkQAAOiqNYscAQCATiTYAADQkRYRAAC6cqt0AACgGxVsAAC6sg82AADQjQQbAAA60iICAEBXzSJHAACgFwk2AAB0pEUEAICu7IMNAAB0o4INAEBXralgAwAAnUiwAQCgIy0iAAB05VbpAABANxJsAADoSIsIAABduVU6AADQjQo2AABduZMjAADQjQQbAAA60iICAEBXbpXOBu+gZ+6fSy4+Kz++9Dt5/eteeZ/rhx32zJz3w6/l3HPOyPfOPi2/+ztPHEKUMD087OmPyZ9+8z150Vnvzb6vOOw+1xc++ZF52cWLc9RXTshRXzkh+73qiHuvbbT5pjn0pP+dY77x7hzz9ROz/eP3mMLIYXr763e+L0/7wyNzxNEvG3YosN6pYG/g5syZkw+8/4QcfOgLsmTJ0nzv7NNy6n+ckR/96Gf3jvnGN76TU089I0ny6Ec/Mp/77EnZ+9FPH1bIMDQ1p7L/O16Uf3/hu3Lr0uU58tS/zeVf+2GW/+za1cZde85P8uWXvPc+r3/68cfkyjMvzGkv+0DmzJ+beZtsPFWhw7R3xKEH5qg/flbe9Pa/H3YosN6pYG/g9nvi4/Lzn1+RX/ziqqxYsSKf//yX8qzDDlptzG233X7v89/adNNZ/2cdZq/t9tk9N12xLDdfdV1GVqzKT0/9XnZ75hMm9dqNNtskC/f77VxyyplJkpEVq3L3zbdP/CKYRfbd59HZYvMHDzsMpshI2rR4DMuEFeyqWjDR9dba8r7h0NtDF26fq5f8T/VtyTVLs98TH3efcYcffnBOeMcbs+02D8mzDn/RVIYI08Zm22+VW679n/9bu3Xp8my/z+73Gbf94/fIUaefkNuW3Zhvn/DZLP/pNdl8521yx/JbcuB7F2XrR+6cX110Rb51/Gey8o67pvIjADANrKuC/cMk545+vXbM83vOM81V1X3OralC/aUvnZ69H/30/PFzj83bjn/dVIQG088af15WP77u4ivyiaf8ZT578JtzwSfPyGEffXWSZM68udl2711y4We+ns8d+tdZccdda+zhBpgN2jT5z7BMmGC31nZtre3WWts1yY/ueX7P+bW9rqoWVdW5VXXu4sWLuwfN5F2zZGl22vGh9x7vuHCHLF26bK3jv/2d72e33R6Whzxkq6kID6aVW5cuz4Mf+j9/uNtshwW57Ve/Xm3M3bfekRW3D6rSV3zzgsyZNzcP2mqz3Lp0eW5dujzLzv95kuSy036QbffeZcpiB2D6uD892JP+NaC1tri1tm9rbd9FixY9gLDo5Zxzz88ee+yaXXbZKfPnz8/znnd4Tv2PM1Ybs/vuu9z7/HH77J2NNpqfG274dWC2WXbB5dly1+2z+U7bZM78uXn4YU/O5V87b7Uxm26zxb3Pt3vsbqk5lTt/fWtuv+6m3LJ0ebbcbYckyU6/+6gs/9k1Uxo/ANODXUQ2cKtWrcqr/vKvc9p/fjZz58zJJz/1z7n00p9m0Z8fkyRZ/NHP5DnPPjRHH/3crFixMnfecWeOeuHLhxw1DEdbNZIz/+ZTOeIzr0/NnZNL//lbWf7Ta/Loo5+RJLno5G9kj0P3y2OOOSAjK1dl5Z0r8pXjPnTv6898y6dy8Adenrnz5+Wmq36Vr73WX/DgHq9767tyzn9fmBtvvDkHHHF0XnHsMfnjcYvu2XCMzPINE2qiHSOq6v+MOfw/Sd439npr7X1ZtzZvo4UPLDqYxVbefU3ev/PRww4DZpxXXXVyVlx/+bDDgBln/ta73XchygP0tIUHTIsM+6xrvt7tM90f66pgj91P56PjjqfFNw4AAKaTdSXY/9RaW7KmC1VleTwAAPcx26uw61rk+PWq2mX8yap6SZJ/XB8BAQDATLauCvark3ytqg5trf0sSarqjUmOSuJe2gAA3Mcw76I4HUyYYLfWTququ5J8paqOSPJnSZ6Y5GmtNfu4AQDAOOvcB7u19vUkL05yZpLdkhwguQYAgDWbsIJdVbdk0KdeSTZOckCSX9Xg/tuttbb5+g8RAICZRIvIBFprD57oOgAAsLr7c6t0AABgHdwqHQCAria6U/hsoIINAAAdqWADANDVbF/kqIINAMCsVVUHV9VPquqyqnrDBOOeWFWrquq565pTgg0AwKxUVXOTfCjJIUn2SvKCqtprLeNOTPLVycwrwQYAoKs2Tf4zCfsluay1dnlr7e4kpyQ5fA3j/iLJvyX51WQmlWADALBBqqpFVXXumMeicUMWJrl6zPGS0XNj51iY5NlJTprs+1rkCABAV9Nlm77W2uIkiycYUmt62bjjf0zyV621VYObma+bBBsAgNlqSZKdxhzvmOTacWP2TXLKaHK9dZJDq2pla+2La5tUgg0AwGx1TpI9q2rXJNckOTLJUWMHtNZ2ved5VX0yyX9MlFwnEmwAADqbKftgt9ZWVtVxGewOMjfJx1trl1TVy0avT7rveiwJNgAAs1Zr7bQkp407t8bEurX24snMaRcRAADoSAUbAICupssuIsOigg0AAB2pYAMA0NVMWeS4vqhgAwBARxJsAADoSIsIAABdNS0iAABALxJsAADoSIsIAABdjdgHGwAA6EUFGwCArixyBAAAupFgAwBAR1pEAADoyiJHAACgGwk2AAB0pEUEAICu7CICAAB0o4INAEBXFjkCAADdSLABAKAjLSIAAHRlkSMAANCNBBsAADrSIgIAQFd2EQEAALpRwQYAoCuLHAEAgG4k2AAA0JEWEQAAumptZNghDJUKNgAAdCTBBgCAjrSIAADQ1YhdRAAAgF5UsAEA6Kq5kyMAANCLBBsAADrSIgIAQFcWOQIAAN1IsAEAoCMtIgAAdGUXEQAAoBsVbAAAuhpRwQYAAHqRYAMAQEdaRAAA6KrZBxsAAOhFgg0AAB1pEQEAoCv7YAMAAN2oYAMA0NWIRY4AAEAvEmwAAOhIiwgAAF1Z5AgAAHSjgg0AQFcjKtgAAEAvEmwAAOhIiwgAAF1Z5AgAAHQjwQYAgI60iAAA0JVbpQMAAN2oYAMA0JVFjgAAQDcSbAAA6EiLCAAAXblVOgAA0I0EGwAAOtIiAgBAV80+2AAAQC8q2AAAdGWRIwAA0I0EGwAAOtIiAgBAV26VDgAAdCPBBgCAjrSIAADQlX2wAQCAblSwAQDoyiJHAACgGwk2AAB0pEUEAICutIgAAADdSLABAKAjLSIAAHQ1uxtEkpqCHpnZ/j0GAJgJqtdE8zZaOC3yv5V3X9PtM90fU5FgM41V1aLW2uJhxwEzjZ8deGD87DAb6MFm0bADgBnKzw48MH522OBJsAEAoCMJNgAAdCTBRh8cPDB+duCB8bPDBs8iRwAA6EgFGwAAOpJgb+CqalVVnV9VF1TVeVX1O6Pnd6mqVlVvHzN266paUVUfHD0+vqpeO6zYobeq2q6qPltVl1fVD6vq7Kp69m8453+t4/qZVbXvGs7vU1WH/ibvDdNZVd065vmhVfWzqtp5Tf+2VNUVVbX11EcJ64cEe8N3R2ttn9baY5O8Mcnfjbl2eZI/GnP8J0kumcrgYKpUVSX5YpKzWmu7tdaekOTIJDv+JvO21n7nAb50nyQSbDZ4VXVAkv+b5ODW2lXDjgemggR7dtk8ya/HHN+R5EdjqmvPT/L5KY8KpsYzktzdWjvpnhOttStba/+3quZW1Xuq6pyqurCqXpokVfXhqnrW6PN/r6qPjz4/tqreMfp8bJXu9VV10ehfjN415r3/pKp+UFU/rarfq6qNkvxtkueP/oXp+ev/48PUq6rfS/LRJH/YWvv5sOOBqTJv2AGw3m1SVecneVCSHTJIMsY6JcmRVfXLJKuSXJvkoVMaIUyNRyU5by3Xjk1yU2vtiVW1cZLvVtUZSc5K8ntJvpxkYQY/Q0ny1Ax+du5VVYckOSLJk1prt1fVgjGX57XW9httCXlra+0PquotSfZtrR3X6fPBdLNxki8l2b+19uNx115dVUePOfbvDhsUFewN3z0tIo9IcnCST4/+qfwepyc5MMkLkvzzMAKEYaiqD41Wms9J8swkfzr6y+j3kzwkyZ5Jvp3k96pqrySXJllWVTskeUqS8b3Xf5DkE62125OktbZ8zLUvjH79YZJd1s8ngmlnRQY/J8eu4do/jP7btE9rbZ8MijuwwZBgzyKttbOTbJ1kmzHn7s7gH/3XJPm3IYUGU+GSJI+/56C19sokB2Tw81BJ/mLMP/i7ttbOaK1dk2SrDH45PSuDhPt5SW5trd0ybv5KsrZ9T+8a/boq/nLI7DGSwc/LE6vqTcMOBqaSBHsWqapHJJmb5IZxl96b5K9aa+PPw4bkG0keVFUvH3Nu09GvX03y8qqanyRV9fCq+q3Ra2cn+cv8T4L92tGv452R5H9V1aajcyxYw5ixbkny4AfwOWDGGP2Lzh8leWFVramSDRsklZQN3z092Mmgwvai1tqqsV0irbVLYvcQNnCttVZVRyT5h6p6fZLrktyW5K+S/EsGrRvnjbZQXZdBP3UySKaf2Vq7rKquTLIga0iwW2unV9U+Sc6tqruTnJZkoqrdN5O8YfTn8+9aa1q02CC11pZX1cFJzqqq64cdD0wFd3IEAICOtIgAAEBHEmwAAOhIgg0AAB1JsAEAoCMJNgAAdCTBBgCAjiTYAADQkQQbAAA6+v8AwsNNn0LrM+8AAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 720x720 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "q7q-mpcz7el4"
      },
      "source": [
        "Wie man sieht, gibt es eine sehr starke Korrelation zwischen Gewicht und BMI. Die Korrelation zwischen Körpergröße und BMI ist dagegen sehr gering.\n",
        "\n",
        "---\n",
        "Eine weitere Variante sind die Streudiagramme für alle Parameterkombinationen. Nachfolgender Code kombiniert die Streudiagramme mit der Kerndichteschätzung (Diagonale).\n",
        "\n",
        "---\n",
        "**Importierte Bibliotheken**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ATQUEDbs7el4"
      },
      "source": [
        "import pandas as pd\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XloGbcSv7el4"
      },
      "source": [
        "**Parameter**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cFVoM7Wm7el4"
      },
      "source": [
        "columns=['Machine1.RawMaterial.Property1',\n",
        "         'Machine1.RawMaterial.Property2',\n",
        "         'Machine1.RawMaterial.Property3',\n",
        "         'Machine1.RawMaterial.Property4',\n",
        "         'Stage2.Output.Measurement0.U.Actual']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "65M5gSDE7el5"
      },
      "source": [
        "**Code**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vdtbhzTN7el5",
        "outputId": "c46c344f-fa7c-432c-df66-e07497877119"
      },
      "source": [
        "plt.figure(figsize=(10, 10), constrained_layout=True)\n",
        "corrSet = pd.DataFrame(rawData[columns])\n",
        "pairplot = sns.pairplot(corrSet, diag_kind='kde')\n",
        "pairplot.fig.suptitle('Streudiagramm mit Kerndichteschätzung', fontsize=16, y=1.03); # Titel für die Grafiken festlegen, Strichpunkt unterdrückt Textausgabe von letztem Kommando"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x720 with 0 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 900x900 with 30 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SCMt_aET7el5"
      },
      "source": [
        "Hier zum Vergleich nochmal das Streudiagramm für den BMI.\n",
        "\n",
        "**Parameter**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yF6BaQF37el5"
      },
      "source": [
        "columns=['BMI',\n",
        "         'Gewicht',\n",
        "         'KH']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MfmRLt4R7el6"
      },
      "source": [
        "**Code**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1PigK_7c7el6",
        "outputId": "d72da1fe-3f99-47c0-8e08-b3e8912044a3"
      },
      "source": [
        "plt.figure(figsize=(10, 10), constrained_layout=True)\n",
        "corrSet = pd.DataFrame(rawData2[columns2])\n",
        "pairplot = sns.pairplot(corrSet, diag_kind='kde')\n",
        "pairplot.fig.suptitle('Streudiagramm mit Kerndichteschätzung', fontsize=16, y=1.03); # Titel für die Grafiken festlegen, Strichpunkt unterdrückt Textausgabe von letztem Kommando"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x720 with 0 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 540x540 with 12 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8X5xDW-h7el6"
      },
      "source": [
        "Hier sieht man sehr deutlich die Korrelation zwischen Gewicht und BMI. Aber auch die Beziehung zwischen BMI und Körpergröße ist interessant. Man sieht das Kinder mit dabei waren und das eine Art Maximalwert für den BMI für die Körpergröße existiert.\n",
        "\n",
        "---\n",
        "Dies sind nur einige Möglichkeiten der Datenanalyse. "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Xa_HwILY7el6"
      },
      "source": [
        "## Literatur\n",
        "[1] Frochte, Jörg (2019), Maschinelles Lernen - Grundlagen und Algorithmen in Python, 2., aktualisierte Auflage, München"
      ]
    }
  ]
}