visualization_solutions.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "[YCMI_CBDS Summer Course] visualization-solutions",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xKxNt70jQrmc",
        "colab_type": "text"
      },
      "source": [
        "Let's begin by loading our three main libraries: pandas, plotnine, and sqlite3:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ud_JJC0werYu",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import pandas as pd\n",
        "import plotnine as p9\n",
        "import sqlite3"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "L4dO88CIQ2yg",
        "colab_type": "text"
      },
      "source": [
        "Let's go ahead and mount the google drive to get easy-access to the course data:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cfVnrT3SdEiG",
        "colab_type": "code",
        "outputId": "b5cd6d7d-d13e-4da8-9abc-0fa9b1079025",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 122
        }
      },
      "source": [
        "#mount google drive\n",
        "from google.colab import drive\n",
        "drive.mount('/content/gdrive')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Go to this URL in a browser: https://accounts.google.com/o/oauth2/auth?client_id=947318989803-6bn6qk8qdgf4n4g3pfee6491hc0brc4i.apps.googleusercontent.com&redirect_uri=urn%3aietf%3awg%3aoauth%3a2.0%3aoob&response_type=code&scope=email%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdocs.test%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive.photos.readonly%20https%3a%2f%2fwww.googleapis.com%2fauth%2fpeopleapi.readonly\n",
            "\n",
            "Enter your authorization code:\n",
            "··········\n",
            "Mounted at /content/gdrive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xD7V2lSaRANz",
        "colab_type": "text"
      },
      "source": [
        "Let's create a database."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tbZ1foRYdFVc",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "conn = sqlite3.connect('exercises.db')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8CaWtcndRNvk",
        "colab_type": "text"
      },
      "source": [
        "Now populate the database with data from MIMIC and the Pima Indian diabetes dataset:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GTQyJM8zdZ23",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "for filename, table in [\n",
        "          (\"mimic_iii/PATIENTS.csv\", \"patients\"),\n",
        "          (\"mimic_iii/DIAGNOSES_ICD.csv\", \"diagnoses\"),\n",
        "          (\"mimic_iii/D_ICD_DIAGNOSES.csv\", \"d_diagnoses\"),\n",
        "          (\"diabetes.csv\",\"diabetes\")\n",
        "]:\n",
        "  data = pd.read_csv(f'/content/gdrive/My Drive/[YCMI_CBDS Summer Course] Data/{filename}')\n",
        "  data.to_sql(table, conn, if_exists='replace', index=False)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FSZOuutPTssy",
        "colab_type": "text"
      },
      "source": [
        "## Exercise 1\n",
        "Do a SQL query using `pd.read_sql_query` to get all the gender information from the `patients` table and plot it in a bar chart:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ETeD9XKtUehc",
        "colab_type": "code",
        "outputId": "6ecfc351-e3e3-48c5-f0e5-60abffc38d9a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 464
        }
      },
      "source": [
        "p9.ggplot(pd.read_sql_query('SELECT gender FROM patients', conn), p9.aes(x='gender')) + p9.geom_bar()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<ggplot: (8791079446988)>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "T6msvUuuU931",
        "colab_type": "text"
      },
      "source": [
        "If all went well, you should have reproduced a figure from Monday. Let's select `gender` and `icd9_code` information from the combination of the `patients` and `diagnoses` tables where their `subject_id`s coincides:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6LWF9W33U9Gn",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "diagnoses_by_gender = pd.read_sql_query('''\n",
        "  SELECT gender, icd9_code\n",
        "  FROM patients, diagnoses\n",
        "  WHERE patients.subject_id == diagnoses.subject_id\n",
        "''', conn)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "G_7UOY_nVuKo",
        "colab_type": "text"
      },
      "source": [
        "Your data frame should have 1761 rows and 2 columns.\n",
        "\n",
        "Now plot just the `icd9_code` information in a bar graph:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Z_jAMOkiVzHB",
        "colab_type": "code",
        "outputId": "5d7202c8-8852-4305-e8de-dafce35ff623",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 465
        }
      },
      "source": [
        "p9.ggplot(diagnoses_by_gender, p9.aes(x='icd9_code')) + p9.geom_bar()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<ggplot: (8791078479245)>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vnP737j0WXPM",
        "colab_type": "text"
      },
      "source": [
        "Whoa, that's way too many codes. Use `.value_counts()` to find out how many distinct `icd9_code` values there are."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7kofTIDWWGdi",
        "colab_type": "code",
        "outputId": "4673cc90-bef0-4a0f-bb67-187ba4a2f11c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 221
        }
      },
      "source": [
        "diagnoses_by_gender['icd9_code'].value_counts()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "4019     53\n",
              "42731    48\n",
              "5849     45\n",
              "4280     39\n",
              "51881    31\n",
              "         ..\n",
              "79094     1\n",
              "51189     1\n",
              "28984     1\n",
              "78791     1\n",
              "53082     1\n",
              "Name: icd9_code, Length: 581, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5HfCwyRrXTMx",
        "colab_type": "text"
      },
      "source": [
        "Compare the `.value_counts()` to 10 and `sum` the result to find the number of diagnoses that appeared more than 10 times. Repeat for more than 20."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JUaAsGNhXiJ1",
        "colab_type": "code",
        "outputId": "1c46bbc4-922c-4fdf-e695-bc4dc337d225",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "sum(diagnoses_by_gender['icd9_code'].value_counts() > 10)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "28"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fX67woy9XiTS",
        "colab_type": "code",
        "outputId": "f2fb0302-135b-4a87-f5b5-0e94b0cc514f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "sum(diagnoses_by_gender['icd9_code'].value_counts() > 20)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "13"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jfjO74PqXi7n",
        "colab_type": "text"
      },
      "source": [
        "Add this additional condition to your `WHERE` clause with an `AND` to  extract the data only for diagnoses given more than 20 times:\n",
        "```\n",
        "icd9_code IN (\n",
        "    SELECT icd9_code\n",
        "    FROM diagnoses \n",
        "    GROUP BY icd9_code\n",
        "    HAVING COUNT (icd9_code) > 20\n",
        "  )\n",
        "  ```\n",
        "\n",
        "This SELECT inside the parentheses is constructing a one column table listing only those icd9_codes that appear more than 20 times."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "m3ZUYzV0WzlQ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "diagnoses_by_gender = pd.read_sql_query('''\n",
        "  SELECT gender, icd9_code\n",
        "  FROM patients, diagnoses\n",
        "  WHERE patients.subject_id == diagnoses.subject_id AND icd9_code IN (\n",
        "    SELECT icd9_code\n",
        "    FROM diagnoses \n",
        "    GROUP BY icd9_code\n",
        "    HAVING COUNT (icd9_code) > 20\n",
        "  )\n",
        "''', conn)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tqIIECznYclA",
        "colab_type": "text"
      },
      "source": [
        "Using this smaller dataset, make a bar chart comparing the frequencies of various `icd9_code`s:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BZ0z4jioZHG_",
        "colab_type": "code",
        "outputId": "897aac84-1d6b-4710-edc3-99374c1fcca5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 465
        }
      },
      "source": [
        "p9.ggplot(diagnoses_by_gender, p9.aes(x='icd9_code')) + p9.geom_bar()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<ggplot: (-9223363245780904809)>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yWQ_2kwqZONJ",
        "colab_type": "text"
      },
      "source": [
        "Apply a `fill` aesthetic argument, based on the `gender`:\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FmEoRPPhZX9_",
        "colab_type": "code",
        "outputId": "4b8e9088-33c1-4978-98d9-df49c91cb301",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 465
        }
      },
      "source": [
        "p9.ggplot(diagnoses_by_gender, p9.aes(x='icd9_code', fill='gender')) + p9.geom_bar()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<ggplot: (8791074032367)>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "odg-zJGiZqkg",
        "colab_type": "text"
      },
      "source": [
        "It's clear that `icd9_code` 99592 is assigned to males more than to females, but what about `icd9_code` 2859? It's hard to tell with stacked bar-charts. Recall that we can make the colors appear side-by-side using a `position='dodge'` parameter to `p9.geom_bar()`. Do that:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_eIwdS3nW4SA",
        "colab_type": "code",
        "outputId": "f0c87f4e-23a7-4572-c3d6-36827437c665",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 465
        }
      },
      "source": [
        "p9.ggplot(diagnoses_by_gender, p9.aes(x='icd9_code', fill='gender')) + p9.geom_bar(position='dodge')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<ggplot: (-9223363245780900699)>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NAf3UuEQaaIe",
        "colab_type": "text"
      },
      "source": [
        "We now see clearly that more females got diagnosis code 2859 than males. What do these codes mean though? To find out, redo your SQL query again, this time also pulling in the `short_title` field from `d_diagnoses` where `d_diagnoses.icd9_code == diagnoses.icd9_code`."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3QU47UYgg1wL",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "diagnoses_by_gender = pd.read_sql_query('''\n",
        "  SELECT gender, diagnoses.icd9_code, short_title\n",
        "  FROM patients, diagnoses, d_diagnoses\n",
        "  WHERE patients.subject_id == diagnoses.subject_id AND d_diagnoses.icd9_code == diagnoses.icd9_code and diagnoses.icd9_code in (\n",
        "    SELECT icd9_code\n",
        "    FROM diagnoses \n",
        "    GROUP BY icd9_code\n",
        "    HAVING COUNT (icd9_code) > 20\n",
        "  )\n",
        "''', conn)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TngCPM_9bAH-",
        "colab_type": "text"
      },
      "source": [
        "Check the query results to make sure that it looks like what you expect. Strictly speaking, you don't need to have `icd9_code` in your table, but I kept it in, giving me three columns and 426 rows."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ROz-0TunhRHR",
        "colab_type": "code",
        "outputId": "5d5f4eb0-e5d1-4df3-c8b5-e68b726e3308",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        }
      },
      "source": [
        "diagnoses_by_gender"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>gender</th>\n",
              "      <th>icd9_code</th>\n",
              "      <th>short_title</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>F</td>\n",
              "      <td>42731</td>\n",
              "      <td>Atrial fibrillation</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>F</td>\n",
              "      <td>4280</td>\n",
              "      <td>CHF NOS</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>F</td>\n",
              "      <td>25000</td>\n",
              "      <td>DMII wo cmp nt st uncntr</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>F</td>\n",
              "      <td>0389</td>\n",
              "      <td>Septicemia NOS</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>F</td>\n",
              "      <td>486</td>\n",
              "      <td>Pneumonia, organism NOS</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>421</th>\n",
              "      <td>M</td>\n",
              "      <td>2724</td>\n",
              "      <td>Hyperlipidemia NEC/NOS</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>422</th>\n",
              "      <td>F</td>\n",
              "      <td>486</td>\n",
              "      <td>Pneumonia, organism NOS</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>423</th>\n",
              "      <td>F</td>\n",
              "      <td>99592</td>\n",
              "      <td>Severe sepsis</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>424</th>\n",
              "      <td>F</td>\n",
              "      <td>2449</td>\n",
              "      <td>Hypothyroidism NOS</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>425</th>\n",
              "      <td>F</td>\n",
              "      <td>2859</td>\n",
              "      <td>Anemia NOS</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>426 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "    gender icd9_code               short_title\n",
              "0        F     42731       Atrial fibrillation\n",
              "1        F      4280                   CHF NOS\n",
              "2        F     25000  DMII wo cmp nt st uncntr\n",
              "3        F      0389            Septicemia NOS\n",
              "4        F       486   Pneumonia, organism NOS\n",
              "..     ...       ...                       ...\n",
              "421      M      2724    Hyperlipidemia NEC/NOS\n",
              "422      F       486   Pneumonia, organism NOS\n",
              "423      F     99592             Severe sepsis\n",
              "424      F      2449        Hypothyroidism NOS\n",
              "425      F      2859                Anemia NOS\n",
              "\n",
              "[426 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5RpA_rzFbfA2",
        "colab_type": "text"
      },
      "source": [
        "Now plot it, putting the `short_title` on the x-axis."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FxXZDNJ8OPkZ",
        "colab_type": "code",
        "outputId": "52c83166-4630-4e74-cd5c-83e0ca799f12",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 465
        }
      },
      "source": [
        "p9.ggplot(diagnoses_by_gender, p9.aes(x='short_title', fill='gender')) + p9.geom_bar(position='dodge')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<ggplot: (8791073780088)>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sFc3hYoNb1Rr",
        "colab_type": "text"
      },
      "source": [
        "Remember that adding `p9.theme(axis_text_x=p9.element_text(angle=90))` will rotate the x-axis labels by 90 degrees, making things easier to read. Do that:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Wv0Lnx94lwpX",
        "colab_type": "code",
        "outputId": "4089962b-5b8e-42d0-96ba-aff7b38d9992",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 616
        }
      },
      "source": [
        "p9.ggplot(diagnoses_by_gender, p9.aes(x='short_title', fill='gender'))+ p9.geom_bar(position='dodge') + p9.theme(axis_text_x=p9.element_text(angle=90))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<ggplot: (-9223363245780925829)>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1HlQOUmnbyiN",
        "colab_type": "text"
      },
      "source": [
        "Visually, you can now quickly find the names of the four common diagnosis codes that are assigned to females more than to males."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5hbNg6jKdCOd",
        "colab_type": "text"
      },
      "source": [
        "## Exercise 2"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SjGpiu5lpgHB",
        "colab_type": "text"
      },
      "source": [
        "Get solely the `pregnancy`, `Glucose`, `BMI` and `Outcome` from the `diabetes` table (each row representing a single observation of a patient)."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tANLOt4iqTAs",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "diabetes_subset = pd.read_sql_query('''\n",
        "SELECT Pregnancies, Glucose, BMI, Outcome from diabetes\n",
        "''',conn)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sR6flM0YqmVD",
        "colab_type": "text"
      },
      "source": [
        "`Pregnancies` is the number of pregnancies for each subject, we want to recode the value of a new variable, `Pregnancy` to be True if the patient has been pregnant, and False if not.\n",
        "We also want to recode `Outcome` to replace with a descriptive variable (\"diabetes\" or \"no diabetes\").\n",
        "We also want to alter the `Glucose` and `BMI` variables to set those at 0 to be NA, as they represent missingness rather than actual 0 values."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "G0sQ2bzgqz6R",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "diabetes_subset['Pregnancy'] = diabetes_subset['Pregnancies']>0\n",
        "diabetes_subset['Outcome'] = diabetes_subset['Outcome'].replace({0: \"No Diabetes\", 1: \"Diabetes\"})\n",
        "diabetes_subset = diabetes_subset.replace({\n",
        "    'Glucose': {0: float('nan')},\n",
        "    'BMI': {0: float('nan')},\n",
        "})"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "s_5xUirqfcWC",
        "colab_type": "text"
      },
      "source": [
        "Look at your data frame to see if it looks the way you expect:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6lDQms963yux",
        "colab_type": "code",
        "outputId": "1ebcc0c7-13ad-466e-9f14-7b3b66a1a66d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        }
      },
      "source": [
        "diabetes_subset"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Pregnancies</th>\n",
              "      <th>Glucose</th>\n",
              "      <th>BMI</th>\n",
              "      <th>Outcome</th>\n",
              "      <th>Pregnancy</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>6</td>\n",
              "      <td>148.0</td>\n",
              "      <td>33.6</td>\n",
              "      <td>Diabetes</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>85.0</td>\n",
              "      <td>26.6</td>\n",
              "      <td>No Diabetes</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>8</td>\n",
              "      <td>183.0</td>\n",
              "      <td>23.3</td>\n",
              "      <td>Diabetes</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>89.0</td>\n",
              "      <td>28.1</td>\n",
              "      <td>No Diabetes</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0</td>\n",
              "      <td>137.0</td>\n",
              "      <td>43.1</td>\n",
              "      <td>Diabetes</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>763</th>\n",
              "      <td>10</td>\n",
              "      <td>101.0</td>\n",
              "      <td>32.9</td>\n",
              "      <td>No Diabetes</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>764</th>\n",
              "      <td>2</td>\n",
              "      <td>122.0</td>\n",
              "      <td>36.8</td>\n",
              "      <td>No Diabetes</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>765</th>\n",
              "      <td>5</td>\n",
              "      <td>121.0</td>\n",
              "      <td>26.2</td>\n",
              "      <td>No Diabetes</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>766</th>\n",
              "      <td>1</td>\n",
              "      <td>126.0</td>\n",
              "      <td>30.1</td>\n",
              "      <td>Diabetes</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>767</th>\n",
              "      <td>1</td>\n",
              "      <td>93.0</td>\n",
              "      <td>30.4</td>\n",
              "      <td>No Diabetes</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>768 rows × 5 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     Pregnancies  Glucose   BMI      Outcome  Pregnancy\n",
              "0              6    148.0  33.6     Diabetes       True\n",
              "1              1     85.0  26.6  No Diabetes       True\n",
              "2              8    183.0  23.3     Diabetes       True\n",
              "3              1     89.0  28.1  No Diabetes       True\n",
              "4              0    137.0  43.1     Diabetes      False\n",
              "..           ...      ...   ...          ...        ...\n",
              "763           10    101.0  32.9  No Diabetes       True\n",
              "764            2    122.0  36.8  No Diabetes       True\n",
              "765            5    121.0  26.2  No Diabetes       True\n",
              "766            1    126.0  30.1     Diabetes       True\n",
              "767            1     93.0  30.4  No Diabetes       True\n",
              "\n",
              "[768 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 80
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JqHfk6dWgmkX",
        "colab_type": "text"
      },
      "source": [
        "We don't need to, but go ahead and drop the `Pregnancies` column, then check to see if your dataframe changed the way you expected."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dh-r8wHY0GB0",
        "colab_type": "code",
        "outputId": "9324783e-4a62-48fe-8e71-1a9f89251ecd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        }
      },
      "source": [
        "diabetes_subset = diabetes_subset.drop('Pregnancies', axis=1)\n",
        "diabetes_subset"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Glucose</th>\n",
              "      <th>BMI</th>\n",
              "      <th>Outcome</th>\n",
              "      <th>Pregnancy</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>148.0</td>\n",
              "      <td>33.6</td>\n",
              "      <td>Diabetes</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>85.0</td>\n",
              "      <td>26.6</td>\n",
              "      <td>No Diabetes</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>183.0</td>\n",
              "      <td>23.3</td>\n",
              "      <td>Diabetes</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>89.0</td>\n",
              "      <td>28.1</td>\n",
              "      <td>No Diabetes</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>137.0</td>\n",
              "      <td>43.1</td>\n",
              "      <td>Diabetes</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>763</th>\n",
              "      <td>101.0</td>\n",
              "      <td>32.9</td>\n",
              "      <td>No Diabetes</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>764</th>\n",
              "      <td>122.0</td>\n",
              "      <td>36.8</td>\n",
              "      <td>No Diabetes</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>765</th>\n",
              "      <td>121.0</td>\n",
              "      <td>26.2</td>\n",
              "      <td>No Diabetes</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>766</th>\n",
              "      <td>126.0</td>\n",
              "      <td>30.1</td>\n",
              "      <td>Diabetes</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>767</th>\n",
              "      <td>93.0</td>\n",
              "      <td>30.4</td>\n",
              "      <td>No Diabetes</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>768 rows × 4 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     Glucose   BMI      Outcome  Pregnancy\n",
              "0      148.0  33.6     Diabetes       True\n",
              "1       85.0  26.6  No Diabetes       True\n",
              "2      183.0  23.3     Diabetes       True\n",
              "3       89.0  28.1  No Diabetes       True\n",
              "4      137.0  43.1     Diabetes      False\n",
              "..       ...   ...          ...        ...\n",
              "763    101.0  32.9  No Diabetes       True\n",
              "764    122.0  36.8  No Diabetes       True\n",
              "765    121.0  26.2  No Diabetes       True\n",
              "766    126.0  30.1     Diabetes       True\n",
              "767     93.0  30.4  No Diabetes       True\n",
              "\n",
              "[768 rows x 4 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 81
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4GcfiPvxhh-1",
        "colab_type": "text"
      },
      "source": [
        "Make box plots comparing the `Glucose` distribution  by `Diabetes`."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dH6S5AGo0PYB",
        "colab_type": "code",
        "outputId": "7e22db67-37ce-48e9-be0b-ecf8121a287d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 498
        }
      },
      "source": [
        "p9.ggplot(diabetes_subset, p9.aes(y='Glucose', x='Outcome')) + p9.geom_boxplot()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/plotnine/layer.py:360: PlotnineWarning: stat_boxplot : Removed 5 rows containing non-finite values.\n",
            "  data = self.stat.compute_layer(data, params, layout)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<ggplot: (8791073849899)>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 82
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wvOWnZMehspm",
        "colab_type": "text"
      },
      "source": [
        "**INTERPRET YOUR RESULTS**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NHl5lmKph246",
        "colab_type": "text"
      },
      "source": [
        "Using `p9.facet_wrap`, facet this data by whether or not the patient has been pregnant with `Pregnancy`."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AwTzZPir5A1q",
        "colab_type": "code",
        "outputId": "206570fd-6ba9-420e-cedb-f045f5fa6eff",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 518
        }
      },
      "source": [
        "p9.ggplot(diabetes_subset, p9.aes(y='Glucose', x='Outcome')) + p9.geom_boxplot() + p9.facet_wrap('~Pregnancy')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/plotnine/layer.py:360: PlotnineWarning: stat_boxplot : Removed 5 rows containing non-finite values.\n",
            "  data = self.stat.compute_layer(data, params, layout)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<ggplot: (-9223363245780631871)>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 83
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ijBrRioJiOqk",
        "colab_type": "text"
      },
      "source": [
        "**INTERPRET THIS GRAPH** How does prior preganancy  affect the likelihood a diabetic has high glucose? A non-diabetic? How does it affect the glucose value?"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "x-L6Q4B2jEJQ",
        "colab_type": "text"
      },
      "source": [
        "By specifying aesthetic maps for `x`, `y`, and `fill` create a box plot figure without faceting that compares the `BMI` for different `Outcome` and `Pregnancy` states."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-jbSOhan5k2u",
        "colab_type": "code",
        "outputId": "5dfb6b07-5bc0-4e08-a231-e823218ea9bb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 498
        }
      },
      "source": [
        "p9.ggplot(diabetes_subset, p9.aes(y='BMI', x='Outcome', fill='Pregnancy')) + p9.geom_boxplot()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/plotnine/layer.py:360: PlotnineWarning: stat_boxplot : Removed 11 rows containing non-finite values.\n",
            "  data = self.stat.compute_layer(data, params, layout)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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AaVFWAQAAYFqUVQAAAJgWZRUAAACmRVkFAACAaVFWAQBAhTVp0iRZLJbAv/j4eN1yyy368MMPjY6G/4+yCgAAKrSIiAht3rxZmzdv1jPPPKPDhw+rbdu2+uabb4yOBkkhRgcAAAAwktVqVfPmzQPXmzVrpsTERC1YsEBpaWlFlvX7/crLy5Pdbi/rmBUWR1YBADgNt9ut5cuXy+12Gx0FZaxWrVqKj4/Xrl27lJqaqoYNG2r9+vVq3Lix7Ha71q5dK0navHmzbrnlFjkcDsXExKh///46ePBgkXXt3btXXbp0UaVKlVSzZk09+eSTGjVqlBITEwPLLFmyRBaLRZ9//rk6duwoh8OhK6+8UsuWLSuyrnXr1qldu3ZKSEhQdHS0brrpJr399ttFljnfdRWur0WLFqpUqZLi4uKUkpKizz//XPn5+apWrZomTJhQ7DZ9+vRRs2bNLnTTXhDKKgAAp+F2u7Vy5UrKagV07NgxHT58WJdffrkkad++fXrggQc0evRovf3227ruuuu0efNmpaSkKCYmRi+++KIWLVqkrVu3qmvXroH1+P1+de3aVV988YUWLlyo+fPna82aNVqzZs1p73fAgAFq3769XnvtNV1//fVKTU3Vd999F5i/a9cu3X777Vq+fLkyMjLUokULderUSR988EGJ1/Xiiy/q9ttvV0JCglatWqWVK1eqRYsW+vXXXxUaGqrU1FQtW7ZMBQUFgdscOXJEr7/+uu6+++6L3cQlwjAAAABQ4Xm9Xkm/Hwn929/+Jp/Pp549e2r16tXKysrSW2+9pZtuuimw/N13362mTZtqzZo1slgskqRGjRoFjsJ26tRJb731lv7v//5PGzduVHJysiTplltuUY0aNRQbG1ssw8iRIzVixAhJUlJSktatW6eMjAw9/PDDgfmFCgoK1KZNG23fvl2LFi1SSkrKea/L7/frwQcfVPv27fXqq68GbtOpU6fA5XvuuUczZ87UO++8o44dO0qSVq5cKavVqn79+l3YRr5AHFkFAAAVmtvtVmhoqEJDQ1WnTh1t2LBBaWlpuu222yRJVapUKVJUT5w4oU2bNqlXr17y+Xzyer3yer2qX7++atasqa1bt0qStm7dqtjY2EBRlaTIyEi1bdv2tDnat28fuOxwOFS7dm3t3bs3MG3v3r0aPHiwqlevrpCQEIWGhurdd9/VDz/8UKJ17dixQ3v37tWQIUPOuE2uuOIKpaSk6Pnnnw9Me+GFF9SzZ09FR0ef8XalgSOrAACgQouIiNDGjRtlsVjkdDpVs2ZNWa3/O55XtWrVIstnZWXJ5/Np9OjRGj16dLH1/fLLL5Kk3377TfHx8cXmJyQknDbHH4+2hoWF6eTJk5J+P5J6xx13KDs7W5MnT9YVV1whh8OhiRMnas+ePSVa1+HDhyUpMMzhTO69916lpqbK5XLp119/1eeff67Zs2ef9TalgbIKAAAqNKvVqqZNm55xfuHb/IViY2NlsVg0fvx4devWrdjyTqdTknTZZZfp0KFDxeb/8UNY5+Onn37S559/rtdee63IuNjc3NwSr6tKlSqSfh+Lezbdu3fX/fffrxUrVmjnzp2qV6+eWrduXeL7u1iUVQAAgBJwOBy6+eab9d1332nq1KlnXO7GG2/U0aNHtXHjRrVq1UqSlJOTo//85z+nHbN6NoWlNCwsLDAtMzNTmzZtUv369Uu0rquuuko1atTQCy+8oN69e59xObvdroEDB2rx4sU6cOCARo8eXay4lwXKKgAAQAk9/vjjuuWWW9SnTx/17dtXcXFx2rt3r9577z3dddddSklJUceOHdWkSRP1799f06dPV2xsrGbOnKmoqKgiwwzOx9VXX60aNWroH//4h3w+n3JycvTII4+oevXqJc5usVg0a9Ys9evXTz169NCgQYNkt9u1efNm3XjjjerSpUtg2XvvvVdz5syRzWZTampqie/rUuADVgAAACWUlJSkjz76SDk5ObrrrrvUqVMnTZ48WZUqVdIVV1wh6fdS+Prrr6tx48YaOnSo7rvvPnXu3Fm33nqrYmJiSnR/drtda9askd1uV69evTRx4kRNmDDhgt+W79Onj15//XX9+uuv6tu3r/r166ePPvpINWrUKLJcgwYNVL9+fbVv3/6CivGlYPH7/X5D7rmUuVwuoyNUKAcPHtSgQYO0bNmyMw4cNwObzaa4uLjA4HizCpbtCfMIludMsOyDUvBs0/KmcLxneZWXl6cGDRooOTlZL7zwgtFxzunnn3/WlVdeqZdfflk9evQwJAPDAAAAAErJokWLVFBQoKuuukpZWVl65plntHv3bqWnpxsd7awOHz6sHTt2aPLkyapdu3aRD3WVNcoqAABAKQkPD9eMGTO0e/duSVLjxo21bt26s559wAzWrl2rIUOG6Morr9SKFSsUEmJcZSy3ZTUsLEx2u93oGBVG4dcROhwORUVFGZzmzAo/xehwOGTmETDBsj1hHsHynAmWfVAKnm0Kcxs0aJAGDRpkdIwSS01NNewDVX9UbstqXl6e8vLyjI5RYRS+qLvdbh0/ftzgNGdms9kUFhYmt9tt6vFywbI9YR7B8pwJln1QCp5tWt6U5YGm0vq98sfNpcXZAAAAAGBalFUAAICzyMnJ0ZIlS5STk2N0lAqpRMMAHnjggfNe1mKxaO7cuSUOBAAAYCZut1tLly5Vx44dFRkZaXScCqdEZXXt2rXnvSxlFQAAABerRGV1165dpZUDAADAEG3atDmv5fr27XvW+Rs2bLgUcSRJkyZN0vfff2/687GWhXJ7NgAAAIDzld7wiou6fd9vfjrr/JSUFG3ZsqXI+UpXrFihbt26XdT9VgQlKqt79uwp0cpr1apVouUBAADKqzlz5mjYsGFGxwg6JTobQJ06dc7rX2JiourUqVNamQEAAILemDFjVKtWLUVFRalJkyb673//e9rlTp48qdTUVFWpUkUxMTFq3Lixvv32W0m/n1d+/PjxqlOnjpxOp/r376+srKyyfBilrkRHVv1+v6KiotStWzd17tyZb4gCAAC4QDfccIPGjx+v2NhYpaWlqVevXtq9e7cqVapUZLmlS5fq66+/1s8//6yYmBh9//33iouLkySNGzdO27dv1yeffKKoqCgNHz5cI0eO1MqVK414SKWiRGX13Xff1erVq7VmzRq98cYbuvPOO9W/f3+1bds28BV6AAAAwcaVl1/q9zFmzBj94x//kCRFRkZq7969gXmjRo3So48+qu+++0433HBDkduFhYXp+PHj+v7779WsWTNdc801kn4/iLhgwQJt27ZNCQkJkqQpU6aoXr16WrZsmWw2W6k/prJQorJ666236tZbb9UzzzyjdevWKT09XV27dlV0dLR69+6tfv36qXnz5qWVFQAAoFSM/CGz1O9j9uzZRcaszpo1S88995z27dsni8WiY8eOyeVyFbvdwIEDtW/fPg0dOlT79u1T9+7dNWvWLJ08eVInTpzQzTffXGR5q9Wq/fv3q3r16qX+mMrCBZ0NICwsTHfeeafuvPNOud1uvfbaa1q1apWSk5M1YMAALVmy5BLHxKmys7Pl8XiMjlFE4c51up3MaHa7XTExMUbHAACYWFr92hd1+5KW3Q8//FDTp0/Xhg0b1LBhQ1mtVsXFxcnv9xdbNiQkRBMmTNCECRP022+/qVevXnr88cf16KOPKiIiQl988YUSExMvKr+ZXfSpqw4ePKjMzExlZmaqoKBATqfzUuTCGWRnZ6tf374qOM2T2QzGjBljdIRirBaLVqenU1gBAGfkDAst0/s7fvy4QkJC5HQ65fV69fjjj+vYsWOnXXbDhg2qXLmyGjZsqMjISNntdtlsNlmtVt13330aPXq0nn76aV122WU6ePCgNm/erK5du5bp4ylNF1RWf/vtN7344otatWqVtm3bphtuuEFDhgxRnz59ys0hZ7PyeDwq8Ps1uW51VQ7hNLnncsTr1cSdv5ruSDQAoGK77bbb1LlzZ1199dVyOBwaPXq0atasedpl9+/fr+HDh2vv3r2qVKmSOnTooLFjx0qSZsyYoenTpys5OVkHDhxQ1apV1adPn4pbVhctWqT09HR9+OGHql+/vvr27atVq1bpiisu7kS6KLnKISFl/lcgAAC4MB988EGR6zabTc8//7yef/75wLSHHnoocHnSpEmBy/369VO/fv1Ou1673a5JkyYVWb68KVFZHTZsmKKiotSvXz9dd911kqQ33njjtMtaLBaNHj364hMCAACUsnN9AxWMU+L3kY8fP64VK1ZoxYoVZ12OsgoAAILBhg0bzjr/wIED6tu3r9LT01W1atUySoVCJSqrBQUFpZUDAAAAKOaSfULn22+/1fbt2xUfH6/k5ORycyJaAAAAGMdakoX9fr9mzpyp5s2b64YbbtCMGTPk9/t19913q1GjRurTp4/atm2r66+/3pTn2wQAACgph8OhwYMHy+FwGB2lQipRWZ01a5bGjRunyy+/XA0bNtTUqVM1YMAArVmzRrNmzdL69es1Y8YM7dmzR5MnTy6tzAAAAGUmMjJSqampioyMNDpKhVSiYQAvvPCC/vnPfwZOj9CjRw/deeedmjt3rkaOHClJ6tChg0JCQjR//nw99dRTlzwwAADApRAVFWV0BJyHEh1Z3bVrl9q0aRO4fsstt8jv9+uGG24oslzTpk31yy+/XJqEAAAAqLBKVFY9Ho8iIiIC1wsv2+32IsuFhYXJ6/VegngAAACoyEp8NgCLxXJe0wAAAMzs+PHjpbJehhdcWiUuq23atJHVWvSAbHJycpFpnI8VAAAAl0KJyuojjzxSWjkAAABMKScnR6+88op69uzJGQEMQFkFAAA4C7fbraVLl6pjx46UVQNcsm+wuhSOHTum4cOH67LLLtOsWbMkSZmZmZo3b552796tqlWraujQoWrcuLHBSQEAAFAWTFVWX3jhBdWsWTNwJgGv16spU6aoffv2mj59urZs2aLp06drwYIFio2NNTgtAAAoD049LefZ9O3b96zzN2zYcCni4A9MU1a/+eYb7du3T+3atdPbb78tSfr666/l8XjUs2dPWa1WJScna+3atdq0aZM6d+5scGIAAFBeXLEk/aJu/1PqmYvsqUMHcnNzFRoaqpCQ3yvY+PHjNX78+Iu67/LOFGU1Pz9fCxcu1JgxY7Rz587A9D179igxMbHImQbq1q2rzMzMYutwuVxyuVyB61arVfHx8aUb3AA2m83oCEHJZrMF/hVeN7NTc5o9K8whWJ4zwbIPSsGzTWF+OTk5gcvNmzfXsGHDlJqaWmw5r9cbKLH4H1NskYyMDDVu3Fh16tQpUlZzc3PlcDiKLOtwOHTw4MHTrmPx4sWB66mpqYGvgC1PPB6P0RGCUkxMjOLi4gLXo6OjDUxzboW/5z/mBs4k2J4zZt8HpeDbpgg+u3fvVp06dfTCCy/o0UcfVUREhNavX686deooNzdX4eHhkn4ffnD11VcHvu7+nXfe0YQJE/TTTz+pbt26mjt3rpKTkw18JKXL8LK6b98+/ec//9HcuXOLzYuIiJDb7S4yze12F/kWrUI9evRQ69atA9etVquysrIufWCDZWdnGx0hKGVnZ8tut8tmsyk6OlrHjh2Tz+czOtYZFf6eC3PDXLKzs033h2PhO0s///yz6V4n7Ha7YmJiJClo9kGJ/dAoFfEPg7fffltffvmlQkNDdeDAgbMu++WXX6p///56/fXXlZSUpPXr16tbt27asWOHnE5nGSUuW4aX1e+++05ZWVkaNmyYJCkvL095eXkaNGiQRowYoczMTBUUFASGAuzatUutWrUqth6n01nkl+RyuUz/QnghyuNjKgs+n6/ItvvjdbMpzGb2nBVRdna2+vXtqwK/3+gop/XXv/7V6AjFWC0WrU5PDxRWKTie2+yHFUv+Yde5FyolkyZNOu93GxYuXKh77rlHLVu2lCR16dJF1113ndavX69BgwaVZkzDGF5WW7ZsqSZNmgSuf/jhh9qwYYMmTpyoqKgohYWFac2aNeratas++eQTZWZmqkWLFgYmBlCReTweFfj9mly3uioztuycjni9mrjzV9MdiQb+KPNvxg0drF279nkvu3v3blm3iU0AAB6TSURBVH3wwQdauHBhYFp+fr7atWtXGtFMwfBXWrvdXuTtFYfDIZvNFngb4OGHH1ZaWprS09OVkJCgcePGcdoqAIarHBIiZ1io0TEAXCK1n0i7qNtfTNm1WCyBy4VnDjhx4kRgzOr+/ft19dVXS5Jq1aqlhx56KDB+tSIwvKz+Udu2bdW2bdvA9cTExMAXBAAAAJSG0CrmGO/pdDpVo0YNLV26VA888IDefPNNbd68WSkpKZKkoUOHqkuXLrr11luVlJQkj8ejLVu26Morr1SNGjWMDV9KrOdeBAAAAGXlueeeU1pamipXrqx169bp9ttvD8xr0qSJli5dqrFjx6pKlSqqXbu2nnjiCRUUFBiYuHSZ7sgqAABAebVly5bA5cTERPlP82HN9u3b6+effz7jOtq1a1eux6j+EWUVAABUeGf7BioYi7IKAAAqtA0bNpx1/oEDB9S3b1+lp6eratWqZZQKhRizCgAAANOirAIAAMC0GAaACs/MX51Z+NNMTv3qTACoCBwOhwYPHiyHw2F0lAqJsooKLTs7W3379ZPfpKf8GDNmjNERirFYrUpfvZrCCqDCiIyMVGpqqtExKizKKio0j8cjf0GBqj88WSFxlY2OY3rerCP6depE0x2JBoALERUVZXQEnAfKKiApJK6yab69BAAA/A8fsAIAAIBpUVYBAABgWpRVAAAAmBZjVoPUz7kndTjfa3QM0zvqZRsBABDMKKtB6slfDhgdAQAAoNQxDAAAAACmxZHVIDW6ZlXFhvDrO5ejXi9HoQEACGK0nSBVLyJczrBQo2OYnisv3+gIAADgIjAMAAAAAKZFWQUAAIBpUVYBAABgWpRVAAAAmBZlFQAAAKZFWQUAAIBpUVYBAABgWpRVAAAAmBZlFQAAAKZFWQUAAIBpUVYBAABgWiFGBygtYWFhstvtRse45Nxut9ERgpLD4VBUVJQsFkvgut/vZ3teoMLtWRHxnLkwZ9oHzazwd12Rn++AGZTbspqXl6e8vDyjY1xy/Ed5Ydxut44fPy6bzaawsDC53W75fD625wUq3J4VEc+ZC3OmfbBQdna2PB6PgQmLc7lckqTMzEzT/d7tdrtiYmKMjlEqyuOBJlyccltWAQDBITs7W3379ZO/oMDoKKc1ZswYoyMUY7Falb56dbktrMCpKKsAAEN5PB75CwpU/eHJComrbHQc0/NmHdGvUyea7kg0UFooqwAAUwiJq6zQKk6jYwAwGc4GAAAAANPiyCog6eSun+U9ctjoGKbnzT5qdAQAQAVDWQ1SR7xeoyMEhfPdTgfSnizlJAAA4EJQVoOM3W6X1WLRxJ2/Gh0laFgtFk6FAgBAkKKsBpmYmBitTk833adAXS6XxowZo9mzZ8vpNNcHJM7nfIRVR45WSExsGSUKXt7soxyFBgCUKcpqEDLzefWcTqcSEhKMjlFi4XXq8Snk85B/2GV0BABABcPZAAAAAGBalFUAAACYFmUVAAAApkVZBQAAgGlRVgEAAGBanA0AAC7Az7kndTifL+c4l6N8gQmAi0RZBYAL8OQvB4yOAAAVAsMAAAAAYFocWQWACzC6ZlXFhvASei5HvV6OQgO4KLzSAsAFqBcRLmdYqNExTM+Vl290BABBjmEAAAAAMC3KKgAAAEyLsgoAAADToqwCAADAtCirAAAAMC3KKgAAAEyLsgoAAADToqwCAADAtEzxpQBpaWnatm2bcnNzFRUVpfbt26t3796SpMzMTM2bN0+7d+9W1apVNXToUDVu3NjgxAAAACgLpiird9xxh+69917Z7XYdOnRIkyZN0uWXX67mzZtrypQpat++vaZPn64tW7Zo+vTpWrBggWJjY42OjXLEm3XE6AhBge0EAChrpiirtWrVKnLdYrFo3759+vrrr+XxeNSzZ09ZrVYlJydr7dq12rRpkzp37mxQWpQndrtdFqtVv06daHSUoGGxWmW3242OAQCoIExRViVp6dKlevPNN+XxeJSQkKA2bdro448/VmJioqzW/w2trVu3rjIzMw1MivIkJiZG6atXy+PxGB2lCJfLpTFjxmj27NlyOp1GxynCbrcrJibG6BgAgArCNGV18ODBGjRokH766Sdt2bJFDodDubm5cjgcRZZzOBw6ePBgsdu7XC65XK7AdavVqvj4+FLPjd/ZbLbAz8LLZnRqzkKVK1c2Ks4ZFearWrWqEhISDE6DU5n5+W1mha8Np9sHCy+f3PWzvEcOG5IvmHizj0oy/+stcKmYpqxKv7/9f+WVV+qzzz7T6tWr5XQ65Xa7iyzjdrsVERFR7LYZGRlavHhx4HpqaqpGjhxZ6pnxu8IjkzExMYqLizM4zblFR0cbHeGsgm17ViRmOwofLP74XD51HyzcpgfSnizzXMGM1wdUFKYqq4UKCgr022+/qUmTJsrIyFBBQUFgKMCuXbvUqlWrYrfp0aOHWrduHbhutVqVlZVVZpkruuzs7MBPM49ntNlsio6O1rFjx+Tz+YyOc0bBsj0rosLfDUqm8Ll8un2QbXphyuvrAwUcf2R4Wc3JydHWrVt10003KTw8XN9//73eeust9enTR40aNVJYWJjWrFmjrl276pNPPlFmZqZatGhRbD1Op7PI2D6Xy2XqMlLeFG5rn88XFNvd7DmDbXtWJPw+Lswfn8unXi/8WXXkaIXEcKaXc/FmH9WBtCd5fUCFYXhZlaR///vfWrRokQoKClS5cmV169ZNnTt3lsVi0cMPP6y0tDSlp6crISFB48aN47RVAFAOhdepp9Aq5vpAoRnlH3adeyGgHDG8rEZGRmratGlnnJ+YmKhZs2aVYSIAAACYBV+3CgAAANOirAIAAMC0KKsAAAAwLcoqAAAATIuyCgAAANOirAIAAMC0KKsAAAAwLcoqAAAATIuyCgAAANOirAIAAMC0KKsAAAAwLcoqAAAATIuyCgAAANOirOKScDgcGjBggBwOh9FRAABAORJidACUDw6HQwMHDjQ6BgAAKGc4sgoAAADToqwCAADAtCirAAAAMC3KKgAAAEyLD1gBwAU44vUaHSEosJ0AXCzKKgCUgN1ul9Vi0cSdvxodJWhYLRbZ7XajYwAIUpRVACiBmJgYrU5Pl8fjMTpKES6XS2PGjNHs2bPldDqNjlOE3W5XTEyM0TEABCnKKgCUkJmLl9PpVEJCgtExAOCS4QNWAAAAMC2OrAIATMGbdcToCEGB7YSKhrIKADCU3W6XxWrVr1MnGh0laFisVj60hgqDsgoAMFRMTIzSV6/mQ2slwIfWUJFQVgEAhjNz8eJDa4Cx+IAVAAAATKvcHlkNCwtjPA+KsVgskiSHwyG/329wmjNzu92Sfs8ZFRVlcBoEg2B5zgTLPigFzzYFyrtyW1bz8vKUl5dndAyYjM1mU1hYmNxut3w+n9FxzqjwP0m3263jx48bnAbBIFieM8GyD0rBs03LGw404Y8YBgAAAADToqwCAADAtCirAAAAMC3KKgAAAEyLsgoAAADToqwCAADAtCirAAAAMC3KKgAAAEyLsgoAAADToqwCAADAtCirAAAAMC3KKgAAAEyLsgoAAADToqwCJuRwODRgwAA5HA6jowAAYKgQowMAKM7hcGjgwIFGxwAAwHAcWQUAAIBpUVYBAABgWpRVAAAAmBZlFQAAAKZFWQUAAIBpUVYBAABgWpRVAAAAmBZlFQAAAKZFWQUAAIBpUVYBAABgWpRVAAAAmBZlFQAAAKZFWQUAAIBphRgdID8/XwsWLNCXX36p48ePy+l0qnfv3mrdurUkKTMzU/PmzdPu3btVtWpVDR06VI0bNzY4NQAAAMqC4UdWfT6fKleurKlTpyo9PV1/+ctf9Mwzz+j777+X1+vVlClT1KxZM61evVp9+/bV9OnTdfToUaNjAwAAoAwYXlbDw8M1YMAAVatWTRaLRQ0aNNA111yj7777Tl9//bU8Ho969uyp0NBQJScnq1atWtq0aZPRsQEAAFAGDC+rf3Ty5En99NNPql27tvbs2aPExERZrf+LWbduXWVmZhqYEAAAAGXF8DGrpyooKNCcOXN05ZVX6vrrr9cPP/wgh8NRZBmHw6GDBw8Wu63L5ZLL5Qpct1qtio+PL/XMCC42m63IT6C8OPW5bebndzDtg8GyTYHyzjRl1e/36+mnn9aRI0f06KOPymKxKCIiQm63u8hybrdbERERxW6fkZGhxYsXB66npqZq5MiRpZ4bwSk6OtroCMAl5fF4JEkxMTGKi4szOM25BcM+GGzbFCivTFFW/X6/FixYoF27dmnKlCmBMlqrVi1lZGSooKAgMBRg165datWqVbF19OjRI3AGAen3I6tZWVll8wAQNGw2m6Kjo3Xs2DH5fD6j4wCXTHZ2duCn3W43OM2ZBdM+GCzbtLzhDwP8kSnK6sKFC7Vjxw5NnTpVlSpVCkxv1KiRwsLCtGbNGnXt2lWffPKJMjMz1aJFi2LrcDqdcjqdgesul8v0L4Qwjs/n4/mBcqXw+Rwsz+1gyBls2xQorwwvqwcPHtT69esVGhqqIUOGBKb37NlTvXv31sMPP6y0tDSlp6crISFB48aNU2xsrIGJAQAAUFYML6sJCQl64403zjg/MTFRs2bNKsNEAAAAMAvTnboKAAAAKERZBQAAgGlRVgEAAGBalFUAAACYFmUVAAAApkVZBQAAgGlRVgGgHHA4HBowYIAcDofRUQDgkjL8PKsAgIvncDg0cOBAo2OUK/wBAJgDZRUAgNPgDwDAHBgGAAAAANOirAIAAMC0KKsAAAAwLcoqAAAATIuyCgAAANOirAIAAMC0KKsAAAAwLcoqAAAATIuyCgAAANOirAIAAMC0KKsAAAAwLcoqAAAATIuyCgAAANOirAIAAMC0KKsAAAAwLYvf7/cbHQIoKy6XSxkZGerRo4ecTqfRcYAKh30QQElxZBUVisvl0uLFi+VyuYyOAlRI7IMASoqyCgAAANOirAIAAMC0KKuoUJxOp+69917GygEGYR8EUFJ8wAoAAACmxZFVAAAAmBZlFUHjgw8+0IQJE85r2VWrVunxxx8v5UQAzmbSpEl69913z2vZe+65R5999lkpJwIQjEKMDgAUGj9+vHbs2KGQkBBZLBbFx8frpptuUvfu3VWpUiWlpKQoJSWl1HN8/fXXevzxx7Vs2bJSvy+gLIwfP17ffvut5s+fr+rVq0uS9u7dqxEjRuiNN94o8foOHDige++9V+Hh4bJYLAoLC1OdOnXUoUMHJSUlBZabNGnSpXoIZzVnzhzFxcVp8ODBZXJ/AMoWZRWmcs8996hjx44qKCjQrl27tHTpUv3973/XrFmzZLfbjY4HBC2Hw6GVK1fqoYceumTrXLFihcLCwnTy5Elt27ZNTz/9tH755Rf16dPnkt0HAFBWYUpWq1X16tXT3//+dw0fPlz//ve/FR4errfeekuzZs2SJD333HPatGmT3G63LrvsMt1zzz1q2LBhYB35+fl64okn9Omnn8rpdGr48OGB+SdOnNCSJUu0detW+Xw+JSUlaciQIcrPz9ejjz6q/Px89e7dW5L0xBNPqGbNmtqwYYMyMjJ0+PBh1a5dWyNGjFCtWrUkSa+++qrWrl0rt9ut6OhoDRw4UK1atSrjrQacWefOnfX666/r559/Vr169YrNP3HihJ599llt27ZNNptNLVu21KBBgxQaGnrOdYeHh6tly5by+/2aM2eOOnXqpKioKI0fP17Jycnq2LGj9u/fr7S0NO3atUuSdN1112n48OGKjIwMrGfnzp1asmSJDh06pMaNG+v+++8PzP/xxx/13HPPKTMzU3Fxcfrzn/+spKQkrV+/Xv/9739lsVi0bt061a1bVzNmzDjjPh4WFqZjx47pqaee0vbt2yVJ1atX18SJExUdHX0pNjWAS4wxqzA1h8Oh6667LvCfyqnq1aunOXPmaNWqVWrTpo0ee+wxeTyewPxPP/1UTZo00apVq9S9e3dNmzZNOTk5kqS5c+cqLy9P8+fP19NPP63ffvtNL774ohwOhx555BHFxMTopZde0ksvvaSaNWvq008/1cqVK/Xggw9qxYoVSklJ0ZQpU5Sfn6+9e/dq5cqVmjx5sl588UU99thjSkxMLKtNBJyXuLg4denSRcuXLz/t/EWLFunw4cN6+umnNXv2bH333XdKT08v0X00b95cPp9PP/zww2nn9+jRQ0uWLNEzzzyjrKwsrVixosj8999/XxMmTNDzzz+v/Px8LV68WJJ05MgRTZo0Sd26ddOKFSv017/+VWlpafrll1/UqVMntW7dWl27dtVLL72kGTNmSDrzPi79/sel3+/XkiVLtGLFCg0bNuy8SjkAY1BWYXqVK1fW8ePHi01PSUlRdHS0bDabunbtKq/Xq19++SUwv06dOmrTpo1sNpvatm2rhIQEbd26VUePHtWnn36qoUOHqlKlSoqMjFTv3r21cePGM2Z466231L17dyUmJspms6lDhw6yWCzasWOHbDabJGnPnj3yeDyqXLly4IgrYCZ33nmnfvzxR33zzTdFpvt8Pm3cuFGpqamKjIxUXFyc+vXrpw0bNpRo/aGhoYqKijrt/lqtWjVdf/31Cg0NVXR0tO64445if4R27txZ1apVU6VKlTRw4EB9+OGHKigo0IYNG9S4cWM1b95cNptNV111lZo3b65NmzadNse59vHQ0FAdP35c+/btk81m0xVXXKGIiIgSPVYAZYdhADC9I0eOKCoqqtj0V199Ve+9956OHDkii8WiEydO6NixY4H58fHxRZZPSEjQkSNHdPDgQRUUFOjuu+8OzPP7/SooKDhjhoMHD2rJkiVFjkrl5+fr8OHDatiwoUaNGqW1a9dq7ty5+tOf/qQhQ4aoRo0aF/OwgUsuMjJS3bt317Jly/TAAw8Eph87dkxer1cJCQmBaVWrVtWRI0fk9/tlsVjOa/35+fk6fvz4affXrKwsPfvss9q+fbtyc3Pl9/uLFcRTvyggPj5eXq9X2dnZOnjwoD755BP169cvMN/n853xA5fn2sfvvPNOeTwezZgxQx6PR61bt9bAgQMVEsJ/iYAZsWfC1E6cOKEvv/wyMH600Pbt2/XKK69o6tSpql27tqxWq/r166dTv+Pi0KFDRW5z6NAhJSUlKT4+XjabTcuWLTvtW3+n+4/Z6XSqe/fuatu27WlztmzZUi1btpTH49HSpUuVlpYWeDsSMJMuXbpo7dq12rp1a2BadHS0QkJCdPDgQdWpU0fS75/4r1y58nkXVUn65JNPZLPZVL9+/WLzli9froKCAj311FOKjo7Wli1b9PTTTxdZxuVyBS4fOnRIISEhiomJUXx8vJKTkzVq1KjT3u8fM55rH4+IiNBdd92lu+66S7/99pseffRRVa9eXe3btz/vxwqg7DAMAKbk9/u1a9cuzZw5U1FRUbr11luLzM/NzZXValV0dLR8Pp9eeukl5ebmFllm165d+u9//yufz6cNGzZo//79atq0qeLi4tS0aVMtXrxYOTk58vv9OnToUOAcj7GxscrJyQmMb5Wkjh076pVXXtGuXbvk9/uVm5urTz/9VCdOnNDevXv1xRdfKC8vTyEhIQoPD5fVyq4Fc7Lb7erbt69eeeWVwDSbzabk5GQtW7ZMOTk5ysrKUnp6+nmfKs7j8WjTpk1auHChevbsedojq7m5uQoPD5fD4dDhw4f12muvFVtm/fr12r9/v06cOKGVK1eqZcuWslqtSklJ0WeffaZPP/1UPp9P+fn52rFjR2DYT2xsrPbv3x9Yz7n28a1bt+rXX39VQUGBKlWqJJvNFhjOA8B8OLIKU3n22We1ZMmSwHlWmzVrprFjxxY7bdX111+vpk2basSIEQoPD9cdd9xR7LvGmzVrFjidjtPp1Lhx4wL/iY4aNSrwQY2cnBw5nU516NBBN9xwg2rUqKGUlBTdd999Kigo0MyZM9W8eXN5PB7NmTNHBw4ckN1uV4MGDdSwYUPl5+drxYoV+uWXX2S1WlW3bl2NGDGizLYZUFLt2rXTq6++WmRs6dChQ/Xss89q+PDhstlsatGihfr27XvW9fz5z3+WxWJRaGio6tSpo/vuu08tW7Y87bL9+vXTk08+qX79+umyyy5TSkqKXn311SLLtGnTRtOmTdOhQ4d07bXX6t5775X0+zsbjzzyiJYsWaK5c+dKkhITEwNv87dr106PPfaY+vXrp7p162ratGln3cf37dunRYsW6ejRo6pUqZKSk5PL5BzOAC6MxX/q+6YAAACAifBeJQAAAEyLsgoAAADToqwCAADAtCirAAAAMC3KKgAAAEyLsgoAAADToqwCAADAtCirAAAAMC3KKgAAAEyLsgrgtFauXKmkpCRFRUUpMjJSN998s5YvX35B65o0aZI+/vjjS5wQAFARUFYBFHP//fdr4MCBatCggV5++WVlZGSoYcOGGjx4sO6///4Sr+/RRx+lrAIALkiI0QEAmMsbb7yhtLQ0PfLII5o0aVJg+m233abLL79ckydPVvv27XX77bcbFxIAUGFwZBVAEXPmzFFcXJwefPDBYvPGjh2ruLg4zZkzR5KUkpKiLl26FFnmiy++kMVi0QcffCBJslgsgdtaLJYi8woKCjR79mxdc801stvtqlatmnr16qXs7OzA+jZu3KikpCRFRETI6XRqyJAhOnLkSGD+7t27ZbFYtHz5cg0bNkyxsbFKSEjQ7NmzJUnp6em66qqrFB0dre7du+vo0aNF8h49elQjRozQZZddJrvdrhtuuEHvvvvuxW1EAMAlQ1kFEOD1evXxxx+rTZs2ioyMLDY/MjJSbdq00ccffyyv13te69y8ebOk34cWbN68WZs3b1aTJk0C0x566CF16dJFa9eu1fz58xUVFaWcnBxJ0meffaZ27dopKipKL7/8sh577DGtXbtWHTt2lM/nK3I/EyZMUEREhF5++WX16tVLf/vb3zRu3DjNnTtXM2fO1Pz58/X+++/roYceCtwmLy9P7dq105tvvqlp06bpjTfeUIMGDdS5c2d9/fXXF7QNAQCXFsMAAAS4XC55PB7VqlXrjMvUqlVLJ0+e1OHDh89rnc2bNw/crvCyJP3www965plnNG3aNI0bNy4wvUePHoHL06ZNU7Vq1fTmm28qNDRUklSzZk3ddtttWr9+fZGhCDfffLOefPJJSdItt9yijIwMzZs3T5mZmapSpYok6csvv9Rzzz2nRYsWSfr9Q2RffPGFvvzySzVo0EDS78MdfvzxR02ZMkUvvfTSeT1GAEDp4cgqAEO8//778vv9uvvuu8+4zIcffqiuXbsGiqoktW/fXrGxsfroo4+KLNuuXbvAZZvNprp16+q6664LFFVJql+/vo4ePRo4cvvuu++qUaNGql+/vrxeb+Bfu3bttHXr1kv1UAEAF4EjqwACnE6n7Ha79uzZc8Zl9uzZo/Dw8CIl8EIcPnxYISEhSkhIOOMyWVlZqlq1arHpVatWLTJuVZJiY2OLXA8LCys2lCEsLEySdPLkSUVGRsrlcunzzz8vUoYL2Wy2834sAIDSQ1kFEBASEqKkpCR98MEHcrvdcjgcRea73W598MEHSkpKUkhIiMLDw5WXl1dkmaysrPO6rypVqsjr9ergwYNnLKyVK1fWwYMHi00/cOCAKleufJ6P6swqV66sa6+9Vs8999xFrwsAUDoYBgCgiFGjRunIkSN64oknis174okndOTIEY0aNUqSVKNGDe3YsUN+vz+wzOk+SR8aGqqTJ08WmXbLLbfIYrHohRdeOGOWli1b6rXXXivyYa733ntPR48eVcuWLUv82P7o1ltv1c6dO3X55ZeradOmxf4BAIzHkVUARdxxxx0aOXKkJk2apF9++UW9evWSJGVkZGjx4sUaOXJk4INNPXv21HPPPaf7779f3bp108cff6xXXnml2DqvueYavf7660pOTpbD4dBVV12l+vXra9iwYXr44Yd15MgRtW3bVidOnNC6des0adIkVa9eXRMmTFBSUpK6dOmi+++/XwcOHNA//vEPNWvWTJ06dbroxzpo0CAtXLhQKSkpevDBBwNjWj///HPl5eVp+vTpF30fAICLw5FVAMXMmzdPy5cv1/bt29W9e3d1795dX331lZYuXap58+YFluvQoYNmzpypN954Q926ddM333yjBQsWFFvf/PnzVVBQoI4dO+rGG2/UZ599JklKS0vTv/71L7366qvq0qWLhg8fruPHjysqKkqSAuc8PXbsmHr06KGxY8eqc+fOeuutty7JmFK73a73339fXbp00bRp09S+fXuNGDFC27ZtuyRHbgEAF8/iP/X9OwAAAMBEOLIKAAAA06KsAgAAwLQoqwAAADAtyioAAABMi7IKAAAA06KsAgAAwLQoqwAAADAtyioAAABMi7IKAPh/7daxAAAAAMAgf+tp7CiKALZkFQCALVkFAGArQ4UXtmALW/oAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<ggplot: (8791071131852)>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 85
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "to0OSoo3j3Rf",
        "colab_type": "text"
      },
      "source": [
        "How does the median `BMI` compare between pregnant and non-pregnant women in each case? What happens if you switch `fill` and `x`? Does that make it easier or harder to answer this question?\n",
        "\n",
        "Now, repeat the above, but make a violin plot instead."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AQCNKU2lkdXE",
        "colab_type": "code",
        "outputId": "98279467-11af-4a6f-9a03-9c627c08cd98",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 498
        }
      },
      "source": [
        "p9.ggplot(diabetes_subset, p9.aes(y='BMI', x='Outcome', fill='Pregnancy')) + p9.geom_violin()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/plotnine/layer.py:360: PlotnineWarning: stat_ydensity : Removed 11 rows containing non-finite values.\n",
            "  data = self.stat.compute_layer(data, params, layout)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<ggplot: (8791071238734)>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 86
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "duUB02nOkqTY",
        "colab_type": "text"
      },
      "source": [
        "Compare the violin plot with the box plot. Can you find an advantage for each type of graph?"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0e0qSIwclZOS",
        "colab_type": "text"
      },
      "source": [
        "Plot `Glucose` vs `BMI` in a way that allows comparing the two `Outcome` cases. How do the values of `Glucose` for those with diabetes compare to those not having diabetes?"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "okf0T8G-6j5V",
        "colab_type": "code",
        "outputId": "832c6fba-95cf-4a83-eb7d-998dfcc239b9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 518
        }
      },
      "source": [
        "p9.ggplot(diabetes_subset, p9.aes(y='Glucose', x='BMI')) + p9.geom_point() + p9.facet_wrap('Outcome')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/plotnine/layer.py:452: PlotnineWarning: geom_point : Removed 16 rows containing missing values.\n",
            "  self.data = self.geom.handle_na(self.data)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<ggplot: (-9223363245780951401)>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 92
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cvXfCIOZj11z",
        "colab_type": "text"
      },
      "source": [
        "Use `p9.geom_smooth` to compare trend lines for how `Glucose` changes as `BMI` changes by `Outcome`. Is this a valid trendline?"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gDujGNWcIRTK",
        "colab_type": "code",
        "outputId": "bb851e9b-ea48-4a5c-e780-d86a820286a2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 532
        }
      },
      "source": [
        "p9.ggplot(diabetes_subset, p9.aes(y='Glucose', x='BMI',color='Outcome',shape='Outcome')) + p9.geom_point() + p9.geom_smooth()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/plotnine/stats/smoothers.py:168: PlotnineWarning: Confidence intervals are not yet implementedfor lowess smoothings.\n",
            "  \"for lowess smoothings.\", PlotnineWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/plotnine/layer.py:452: PlotnineWarning: geom_point : Removed 16 rows containing missing values.\n",
            "  self.data = self.geom.handle_na(self.data)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<ggplot: (-9223363245780563873)>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 97
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Bkj2WC9snZel",
        "colab_type": "text"
      },
      "source": [
        "Do diabetics and non-diabetics show different body mass indices? Start by making a box-plot to compare them:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lpKdGZoOnwIp",
        "colab_type": "code",
        "outputId": "b69e0ee8-8c52-4ebe-eee3-b952772a6070",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 498
        }
      },
      "source": [
        "p9.ggplot(diabetes_subset, p9.aes(y='BMI', x='Outcome')) + p9.geom_boxplot()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/plotnine/layer.py:360: PlotnineWarning: stat_boxplot : Removed 11 rows containing non-finite values.\n",
            "  data = self.stat.compute_layer(data, params, layout)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<ggplot: (-9223363245776303188)>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 98
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "l7DflMtTn6hZ",
        "colab_type": "text"
      },
      "source": [
        "Non-diabetics have an slightly lower median, but the ranges mostly overlap. We know what the subdivision looks like for pregnancy from our previous plot, with those women, with pregnancies having a slightly lower BMI irrespective of diabetic outcome.\n",
        "When we swap our `fill` and `x`, we observe that the division between diabetics and non-diabetics is clearer within the pregnancy categories."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lfRCDiZPqZRt",
        "colab_type": "code",
        "outputId": "603b3068-31bc-4b66-c3fd-c046a30f6d4e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 498
        }
      },
      "source": [
        "p9.ggplot(diabetes_subset, p9.aes(y='BMI', fill='Outcome', x='Pregnancy')) + p9.geom_boxplot()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/plotnine/layer.py:360: PlotnineWarning: stat_boxplot : Removed 11 rows containing non-finite values.\n",
            "  data = self.stat.compute_layer(data, params, layout)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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AAEyFAgwAAABToQADAADAVCjAAAAAMBUKMAAAAEyFAgwAAABToQADAADAVCjAAAAAMBUKMAAAAEyFAgwAAABToQADAADAVCjAAAAAMBUKMAAAML3XX39dTZs2VXR0tKKionT99ddr8eLFZ7WuyZMn6/PPPy/jhChLFGAAAGBqo0aN0u233666devqrbfe0rJly3TllVdq0KBBGjVqVKnX99hjj1GAg1yY0QEAAACMsmLFCs2ZM0ePPvqoJk+eHJjevn17ValSRY8//rjatWunLl26GBcSZY4jwAAAnIDH49HixYvl8XiMjoLzaObMmYqPj9f9999fYt64ceMUHx+vmTNnSpJatWqlzp07F1vm66+/lsVi0SeffCJJslgsgcdaLJZi83w+n5599lldfvnlcjgcqly5snr16qW8vLzA+tavX6+mTZsqMjJSLpdLd9xxh7KzswPzd+7cKYvFosWLF2v48OGKi4tTYmKinn32WUlSenq6Lr30UsXExKh79+7Kzc0tljc3N1cjRozQRRddJIfDocaNG+uDDz44t40YgijAAACcgMfj0euvv04BLseKior0+eefq3Xr1oqKiioxPyoqSq1bt9bnn3+uoqKiM1rnxo0bJf01rGLjxo3auHGjGjVqFJj2wAMPqHPnzlq5cqXmzp2r6OhoHTx4UJL01VdfqW3btoqOjtZbb72lp556SitXrlTHjh3l9XqLPc+ECRMUGRmpt956S7169dJ9992n8ePH67nnntOMGTM0d+5cffzxx3rggQcCjyksLFTbtm21atUqTZs2TStWrFDdunXVqVMnfffdd2e1DUMVQyAAAIApud1uFRQUKDk5+aTLJCcn68iRI9q/f/8ZrfO6664LPO7YbUn66aefNG/ePE2bNk3jx48PTO/Ro0fg9rRp01S5cmWtWrVK4eHhkqTq1aurffv2WrNmTbFhGNdff73+8Y9/SJJuvPFGLVu2TLNnz1ZmZqYqVaokSfrmm2+0cOFCvfjii5L++qDf119/rW+++UZ169aV9NdQj59//llTpkzRm2++eUavsTzgCDAAAMB59vHHH8vv92vIkCEnXebTTz9V165dA+VXktq1a6e4uDh99tlnxZZt27Zt4LbNZlOtWrV01VVXBcqvJNWpU0e5ubmBI8wffPCB6tWrpzp16qioqCjwr23bttq8eXNZvdSQwBFgAABgSi6XSw6HQ7t27TrpMrt27VJERESxYnk29u/fr7CwMCUmJp50mZycHCUlJZWYnpSUVGwcsCTFxcUVu2+320sM47Db7ZKkI0eOKCoqSm63W1u2bClWsI+x2Wxn/FrKAwowAAAwpbCwMDVt2lSffPKJPB6PnE5nsfkej0effPKJmjZtqrCwMEVERKiwsLDYMjk5OWf0XJUqVVJRUZGysrJOWoIrVqyorKysEtP37dunihUrnuGrOrmKFSuqfv36Wrhw4TmvK9QxBAIAAJjW6NGjlZ2drWeeeabEvGeeeUbZ2dkaPXq0JKlatWr68ccf5ff7A8uc6AwK4eHhOnLkSLFpN954oywWixYtWnTSLDfccIPeeeedYh+4+/DDD5Wbm6sbbrih1K/t72666Sbt2LFDVapU0dVXX13in5lwBBgAAJjWLbfcopEjR2ry5Mn67bff1KtXL0nSsmXLtGDBAo0cOTLw4bOePXtq4cKFGjVqlLp166bPP/9cb7/9dol1Xn755Xr33XfVvHlzOZ1OXXrppapTp46GDx+uiRMnKjs7W23atNGhQ4e0evVqTZ48WVWrVtWECRPUtGlTde7cWaNGjdK+ffv00EMPqUmTJrr55pvP+bUOHDhQL7zwglq1aqX7778/MEZ4y5YtKiws1PTp08/5OUIFR4ABAICpzZ49W4sXL9bWrVvVvXt3de/eXd9++61eeeUVzZ49O7Bchw4dNGPGDK1YsULdunXT999/r/nz55dY39y5c+Xz+dSxY0ddc801+uqrryRJc+bM0RNPPKF//etf6ty5s+6++24dOHBA0dHRkhQ4J29+fr569OihcePGqVOnTnrvvffKZIyuw+HQxx9/rM6dO2vatGlq166dRowYoS+//LJMjjCHEov/+OP45Yjb7TY6gqlkZWVp4MCBevXVV085wN9oNptN8fHxysnJKXFOxWASKtsTwSNU3jOhsg9KobNNyxuXy2V0BJgAR4ABAABgKhRgAAAAmEq5/RCc3W6Xw+EwOoZpHLtUqNPpDIxlCkbHrtHudDoVzKN/QmV7IniEynsmVPZBKXS2KYDSK7cFuLCwsMS5+nD+HPuPwuPx6MCBAwanOTmbzSa73S6PxxPU4w9DZXsieITKeyZU9kEpdLZpeXMhD16dr+8rvzAFP4ZAAAAAwFQowAAAAKdw8OBBvfzyyzp48KDRUVBGSjUE4p577jnjZS0Wi5577rlSBwIAAAgmHo9Hr7zyijp27KioqCij46AMlKoAr1y58oyXpQADAAAgGJWqAGdkZJyvHAAAAIZo3br1GS3Xt2/fU85ft27dWWd4/fXXtXDhQn388cenXXby5Mnavn270tPTz/r5zK7cngUCAADgTKVfefE5Pb7v97+ccn6rVq20adMmhYeHy2q1qkaNGurataseeOABRUdHa8CAARowYMA5ZTgTn3zyifr27as//vjjvD9XMCtVAd61a1epVp6cnFyq5QEAAMqrmTNnavjw4fL5fPrmm2/04IMPqlmzZtq0aZMqVKhgdDxTKdVZIGrWrHlG/1JSUlSzZs3zlRkAACBkWa1WNWzYUG+99ZaysrK0aNEivfzyy7ruuusCy4wdO1bJycmKjo5Wo0aN9P/+3/8rto7CwkLddtttio6O1hVXXFFsfn5+voYPH65q1aqpcuXKGjlypI4cOaK8vDx17NhRWVlZioqKUlRUlLZt2yZJeu2113TllVcqLi5OzZs319atWwPrS0tLU/Xq1RUdHa1atWqVi6EXpToC7Pf7FR0drW7duqlTp05caQ0AAOAsxcbGqm3btlq/fr06duxYbF7jxo318MMPKy4uTnPmzFGvXr20c+fOwJHiFStWBIrz66+/rq5duyojI0Px8fEaPHiwoqOj9cMPP8jn86lPnz6aMmWKpk2bpvfee6/EEIiVK1dq4sSJWrlyperWrauXXnpJXbp00fbt25WRkaFJkyZpy5YtuvTSS/X7778rJyfngm6n86FUBfiDDz7Q0qVLtXz5cq1YsUK33nqr+vfvrzZt2gQubwkAABBq3IVHDXneKlWq6L///W+J6cePBx49erQee+wxbdu2TY0bN5YkNWjQQLfffrskadCgQZo5c6ZWr16tdu3aacWKFcrOzg5ckW7ixIkaNGiQpk2bdsIM8+bN04MPPqh69epJku666y7NmDFDmzZtUtWqVeX3+/X9998rOTlZF110kS666KIy3QZGKFUBvummm3TTTTdp3rx5Wr16tdLT09W1a1fFxMSod+/e6tevX7HD9wAAAKFg5E+Zhjzv3r17VbFixRLT09LStHDhQu3du1cWi0X5+flyu92B+X//nFWNGjW0Z88e7dy5U16vV9WrVw/M8/v9p7z0+M6dOzVu3DiNHz8+MK2wsFB79uxRixYt9Morr2jWrFkaPHiwmjdvrmeeeUaXXXbZubxsw53VWSDsdrtuvfVW3XrrrfJ4PHrnnXe0ZMkSNW/eXAMGDNDLL79cxjFxvLy8PBUUFBgdo5hjO+XxO2ewcDgcio2NNToGACCIzalT45wefzYFOj8/X//+9781ceLEYtM//fRTTZ8+XevWrdOVV14pq9Wq+Ph4+f3+wDJ/PzHBrl271LNnTyUnJyssLExZWVmy2+0lnvNEf7FPTk7WAw88oNTU1BPm7N27t3r37q1Dhw7poYce0tChQ/Xpp5+W+vUGk3M+DVpWVpYyMzOVmZkpn88nl8tVFrlwEnl5eerXt698x+0EwWTs2LFGRyjBarFoaXo6JRgAcFIue/gFey6/369vv/1WDz30kCpVqqTBgwfrzTffDMw/cOCAwsLC5HK5VFRUpKefflr5+fnF1vHNN99oyZIl6t27t5YuXapff/1VN998sypWrKhOnTrp3nvv1RNPPKG4uDjt3r1bW7duVYcOHZSUlKScnBzl5OQoPj5eknT33XfrwQcfVMOGDVW/fn15PB6tW7dOrVq10t69e/Xbb7/phhtukMPhUFRUlGw22wXbVufLWRXg33//XW+88YaWLFmiL7/8Uo0bN9Ydd9yhPn36qGrVqmWdEccpKCiQz+/X47WqqmIYp3E+neyiIk3asSfojpgDAMxn9OjRGjduXOA8wF26dFF6enqJU6C1b99enTp10mWXXSan06kxY8YUG9IgSbfccovWrFmju+66S9WrV9e//vWvwFCKV155RRMnTtRVV12lnJwcVatWTcOHD1eHDh102WWX6bbbbtPFF18sr9erjRs3qmvXrjp06JAGDRqkjIwMVahQQc2bN1erVq1UUFCgCRMm6IcffpDNZlOjRo00f/78C7bNzpdSNagXX3xR6enp+vTTT1WnTh317dtXS5Ys0cUXn9vJo1F6FcPCLuhvqwAA4Ox98sknp5yfmpoaGIJgs9n0z3/+U//85z8D8x944IHA7cmTJ59yXTExMZo1a5ZmzZp1wvkLFy7UwoULi03r16+f+vXrV2LZ+vXr64svvjjl84WiUhXg4cOHKzo6Wv369dNVV10l6a/TcJyIxWLRmDFjzj0hAADAeXa6K7mhfCn139APHDig1157Ta+99topl6MAAwCAULBu3bpTzt+3b5/69u2r9PR0JSUlXaBUOJ9KVYB9Pt/5ygEAAABcEGX2KaoffvhBW7duVUJCgpo3b14uPiEIAACA8sdamoX9fr9mzJih6667To0bN9aTTz4pv9+vIUOGqF69eurTp4/atGmjhg0bBuX5YAEAAErL6XRq0KBBcjqdRkdBGSlVAU5LS9P48eNVpUoVXXnllZo6daoGDBig5cuXKy0tTWvWrNGTTz6pXbt26fHHHz9fmQEAAC6YqKgopaamKioqyugoKCOlGgKxaNEiPfLII4HTb/To0UO33nqrnnvuOY0cOVKS1KFDB4WFhWnu3LknPf0GAACA0aKjo42OAIOU6ghwRkaGWrduHbh/4403yu/3q3HjxsWWu/rqq/Xbb7+VTUIAAACgDJWqABcUFCgyMjJw/9hth8NRbDm73a6ioqIyiAcAAACUrVKfBcJisZzRNAAAgGB24MCB87JehlYEv1IX4NatW8tqLX7guHnz5sWmcb5gAAAABKtSFeBHH330fOUAAAAISgcPHtTbb7+tnj17ciaIcoICDAAAcAoej0evvPKKOnbsSAEuJ8rsSnBlIT8/X3fffbcuuugipaWlSZIyMzM1e/Zs7dy5U0lJSRo2bJgaNGhgcFIAAACEqqAqwIsWLVL16tUDZ5AoKirSlClT1K5dO02fPl2bNm3S9OnTNX/+fMXFxRmcFgAAlAfHn+L1VPr27XvK+evWrSuLOGWqY8eO6tmzp4YMGXLaZVNSUjR//nx16NDhAiQzVtAU4O+//1579+5V27ZttXbtWknSd999p4KCAvXs2VNWq1XNmzfXypUrtWHDBnXq1MngxAAAoLy4+OX0c3r8L6mnLsetWrXSZ599ph9++EF16tSRJG3fvl2XX365/H5/qZ9v586dqlmzppxOp6xWqyIiInTVVVfprrvuUo8ePQLLvffee6Ve99lITU1V5cqV9eSTT16Q5ztXQVGAjx49qhdeeEFjx47Vjh07AtN37dqllJSUYmeYqFWrljIzM0usw+12y+12B+5brVYlJCSc3+AGsNlsRkcISTabLfDv2P1gdnzOYM+K4BAq75lQ2Qel0NmmCB2xsbF65JFH9MYbb5TZOt1utyIiIuTxeLR69WoNHz5c27Zt08SJE8vsOcqjoCjAy5YtU4MGDVSzZs1iBfjw4cNyOp3FlnU6ncrKyjrhOhYsWBC4n5qaGrg8c3lSUFBgdISQFBsbq/j4+MD9mJgYA9Oc3rHv899zAycTau+ZYN8HpdDbpgh+o0aN0jPPPKMtW7aoYcOGJebn5+drzJgxWr16tcLCwtS7d29Nnz69xAXHTsTpdKp373IBs1MAAB+mSURBVN7y+/0aNGiQRowYoYoVK6pVq1bq27evhg8froyMDN155536+uuvZbFY1LZtWz3//PPF3t9btmzRuHHjtGvXLt10001auHBhYNjp5s2bdd999+m7775T5cqVNW3aNHXv3l3PP/+8Xn/9dVksFs2ZM0eNGjXS+vXrlZ+frwceeECrVq1SUVGRevbsqbS0NEVERGj//v264447tH79eklSnTp1tHr1arlcrjLa2qdmeAHeu3evPvroIz333HMl5kVGRsrj8RSb5vF4il2N7pgePXqoZcuWgftWq1U5OTllH9hgeXl5RkcISXl5eXI4HLLZbIqJiVF+fr68Xm9gXrD9YnHsrxm//vpr0H3PHQ6HYmNjjY6Bvzn2Pjn2Xg9WJ9oHg1WobNPypjz/slG5cmXdc889evjhh084NOGee+7RH3/8oe3bt+vIkSPq2rWrHn/8cU2bNu2Mn+PWW29V//799cUXX6hjx47F5vn9fj344INq2bKlDhw4oJ49e+qRRx7RnDlzAsu8/PLLeu+995SQkKB+/frpnnvu0auvvqrff/9dHTp00MKFC9WlSxd9+eWX6tixoy6//HKNGDFC//nPf0oMgRg8eLCio6P1ww8/yOfzqU+fPpoyZYqmTZumtLQ0+Xw+7dmzRw6HQ19//bUiIiLOYqueHcML8LZt25STk6Phw4dLkgoLC1VYWKiBAwdqxIgRyszMlM/nCwyDyMjIUIsWLUqsx+VyFfutwe12B/0P17NRHl/TheD1eottu2P38/Ly1LdfP/mD9OIt9957r9ERSrBYrUpfupQSHGSOvb///l4PVqGQM9S2Kc7N0f3u0y9UBsaNG6fatWtr/fr1SkxMDEz3er1aunSp/vOf/wSOuD722GMaOnRoqQqw3W6Xy+VSdnZ2iXm1atVSrVq1JP11MGPMmDElhkqMHDkysMy0adPUpEkTvfzyy1q8eLFuuukmdevWTZJ07bXX6tZbb9Vbb72lSZMmlXiurKwsrVixQtnZ2YEr402cOFGDBg3StGnTZLfbtX//fv3yyy+qX7++GjdufMavsSwYXoBvuOEGNWrUKHD/008/1bp16zRp0iRFR0fLbrdr+fLl6tq1q7744gtlZmaqWbNmBiZGeVJQUCC/z6eqEx9XWHxFo+MEvaKcbO2ZOinojpgDwLnKvO/CDJuMi4vTgw8+qPHjx2vhwoWB6W63W4WFhUpJSQlMS0lJ0e+//y6/3y+LxXJG6y8sLJTb7VbFiiX/T9u3b5/uvfdeffrppzpw4IB8Pl+JyzYnJycHbteoUUOFhYX6888/tXPnTr377rvFzsJVVFSk22+//YQ5du7cKa/Xq+rVqwem+f3+wC+T48aN0+HDh9WjRw95PB7ddtttmjZtmsLDw8/odZ4rwwuww+Eo9qclp9Mpm80W+BPIxIkTNWfOHKWnpysxMVHjx4/nFGgoc2HxFRVe6cKMOwIABJ8az8w5/UKnUJoCPWrUKD333HNatWpVYJrL5ZLdbtfOnTsD1zvYuXOnLrroojMuv5L0zjvvKDw8XNdee22JeQ8//LB8Pp++/fZbVapUSe+++67uuuuuYsvs2rWr2O3w8HAlJCQoOTlZffv21csvv3zC5/17xuTkZIWFhSkrK0t2u73E8lFRUZoxY4ZmzJihX3/9VR07dtSll156RqdrKwuGF+C/a9Omjdq0aRO4n5KSErgoBgAAwPlwIQ+CREZGatKkSZowYUJgms1mU9++fTV+/HgtWbJEBQUFeuyxx056hPXvDh06pDVr1mjUqFEaP378CY8AHzhwQE6nU7Gxsdq7d+8J+9Xzzz+vzp07y+VyaeLEierTp4+sVqtuu+02NW7cWCtXrlTHjh3l8/m0ZcsWxcTE6PLLL1dSUlKxExlUrlxZnTp10r333qsnnnhCcXFx2r17t7Zu3aoOHTpo1apVqlOnji6++GLFxMQoPDz8gp5txXr6RQAAAFCWhgwZUuIDf7NmzVJSUpIuvfRSNWzYUE2aNDnh+NrjuVwuxcTEqEaNGpo/f75mz56tRx999ITLPvroo/r2228VFxenm2++OTCe93gDBw7ULbfcomrVqslmswVOUlCtWjWtWbNGM2fOVFJSkqpUqaLx48cHhsQNGTJEP//8s+Lj4wMXFnnllVcUHh6uq666SrGxsWrfvr1++uknSdIvv/yiDh06KDo6WvXr11e7du3OuOyXhaA7AgwAAFDefPLJJ8Xuh4WF6eeffy42LTY2VosWLTqj9aWkpJzRBTSOf94rrrhCX331VbH59913X+D2zp07JUnjx48/4boaN26sjz766ITzLrnkEm3ZsqXYtJiYGM2aNUuzZs0qsfzo0aM1evTo0+Y/XyjAAADA9E53JTeULxRgAABgauvWrTvl/H379qlv375KT09XUlLSBUqF84kxwAAAADAVCjAAAABMhSEQAFBKwXz57GNfgwmXz0aoczqdGjRokJxOp9FRUEYowABQCnl5eerXt698Z/DpayOMHTvW6AglWC0WLU1PpwQjZEVFRSk1NdXoGChDFGAAKIWCggL5/H49XquqKobxI/R0souKNGnHnqA7Yg5IKnEZYJgHP70B4CxUDAuTy35hrlkPAChbfAgOAAAApkIBBgAAgKlQgAEAAGAqjAEOUb8ePqL9R4uMjhH0covYRgAAoDgKcIj6x2/7jI4AAAAQkhgCAQAAAFPhCHCIGlM9SXGcg/S0couKOFoOAACKoUGFqNqREZyD9Ay4C48aHQEAAAQZhkAAAADAVCjAAAAAMBUKMAAAAEyFAgwAAABToQADAADAVCjAAAAAMBUKMAAAAEyFAgwAAABToQADAADAVCjAAAAAMBUKMAAAAEwlzOgA54vdbpfD4TA6RpnzeDxGRwhJTqdT0dHRslgsgft+v5/teZaObU8z4j1zdk62DwazY99rM7/fgfKq3BbgwsJCFRYWGh2jzPGf79nxeDw6cOCAbDab7Ha7PB6PvF4v2/MsHdueZsR75uycbB88Ji8vTwUFBQYmLMntdkuSMjMzg+777nA4FBsba3SM86I8HrxC8Cm3BRgAEBry8vLUt18/+X0+o6Oc0NixY42OUILFalX60qXltgQD5xsFGABgqIKCAvl9PlWd+LjC4isaHSfoFeVka8/USUF3xBwIJRRgAEBQCIuvqPBKLqNjADABzgIBAAAAU+EIMACchV8PH9H+o0VGxwh6uUVsIwDBhwIcorL5T+WMsJ1wvvzjt31GRwAAnCUKcIhxOByyWiyatGOP0VFChtVi4bQ6AAAggAIcYmJjY7U0PT3oPv3rdrs1duxYPfvss3K5gutDLOX5fJkwzpjqSYoL40fo6eQWFXG0HEDQ4ad3CArmMudyuZSYmGh0DOC8qx0ZIZc93OgYQc9deNToCABQAmeBAAAAgKlQgAEAAGAqFGAAAACYCgUYAAAApkIBBgAAgKlwFghA0pGMX1WUvd/oGEGvKC/X6AgAAJwzCjAgad+cfxgdAQAAXCAMgQAAAICpcAQYkJQ0cozCYuOMjhH0ivJyOVoOAAh5FGBAUkTN2gqvFFyXcA5GR/e7jY4AAMA5YwgEAAAATIUCDAAAAFOhAAMAAMBUKMAAAAAwFQowAAAATIUCDAAAAFOhAAMAAMBUKMAAAAAwlaC4EMacOXP05Zdf6vDhw4qOjla7du3Uu3dvSVJmZqZmz56tnTt3KikpScOGDVODBg0MTgwAAIBQFRQF+JZbbtHQoUPlcDj0559/avLkyapSpYquu+46TZkyRe3atdP06dO1adMmTZ8+XfPnz1dcHJetBWCc7KIioyOEBLYTgGAUFAU4OTm52H2LxaK9e/fqu+++U0FBgXr27Cmr1armzZtr5cqV2rBhgzp16mRQWgBm5nA4ZLVYNGnHHqOjhAyrxSKHw2F0DAAICIoCLEmvvPKKVq1apYKCAiUmJqp169b6/PPPlZKSIqv1f0OVa9WqpczMTAOTAjCz2NhYLU1PV0FBgdFRinG73Ro7dqyeffZZuVwuo+MU43A4FBsba3QMAAgImgI8aNAgDRw4UL/88os2bdokp9Opw4cPy+l0FlvO6XQqKyurxOPdbrfcbnfgvtVqVUJCwnnPjb/YbLbA12O3g9HxOY//itIJ9u/z+VaxYkWjI5Rw7PuRlJSkxMREg9Oc3In2vWO3j2T8qqLs/YbkCiVFebmS2A+BcxE0BVj6a+jDJZdcoq+++kpLly6Vy+WSx+MptozH41FkZGSJxy5btkwLFiwI3E9NTdXIkSPPe2b85djRsNjYWMXHxxuc5vRiYmIkKeiO4oWKUPk+m0mo7oPS/7Lvm/MPo+KEpFD5XgPBKKgK8DE+n0+///67GjVqpGXLlsnn8wWGQWRkZKhFixYlHtOjRw+1bNkycN9qtSonJ+eCZTa7vLy8wNdgHutns9kUExOj/Px8eb3eQG6UTrB/n80oVPdBSeyHZynYv9dni1KPC8HwAnzw4EFt3rxZ1157rSIiIrR9+3a999576tOnj+rVqye73a7ly5era9eu+uKLL5SZmalmzZqVWI/L5So27s3tdgd+uOL8O7atvV5vSGz3YzlDIWswYtsFn1DdB4/dlqSkkWMUFssZfk6nKC9X++b8I2S+10AwMrwAS9K///1vvfjii/L5fKpYsaK6deumTp06yWKxaOLEiZozZ47S09OVmJio8ePHcwo0ACiHImrWVnil4PoAXzA6ut99+oUAnJLhBTgqKkrTpk076fyUlBSlpaVdwEQAAAAoz7gUMgAAAEyFAgwAAABToQADAADAVCjAAAAAMBUKMAAAAEyFAgwAAABToQADAADAVCjAAAAAMBUKMAAAAEyFAgwAAABToQADAADAVCjAAAAAMBUKMAAAAEyFAowy4XQ6NWDAADmdTqOjAAAAnFKY0QFQPjidTt1+++1GxwAAADgtjgADAADAVCjAAAAAMBUKMAAAAEyFAgwAAABT4UNwgKSinGyjI4QEthMAoDygAMPUHA6HLFar9kydZHSUkGGxWuVwOIyOAQDAWaMAw9RiY2OVvnSpCgoKjI5SjNvt1tixY/Xss8/K5XIZHacYh8Oh2NhYo2MAAHDWKMAwvWAucy6XS4mJiUbHAACgXOFDcAAAADAVjgADAIICH7I8M2wn4NxRgAEAhuLDqKXHh1GBc0MBBgAYig+jlh4fRgXODQUYAGC4YC5zfBgVKH/4EBwAAABMpdweAbbb7YyPQgkWi0WS5HQ65ff7DU5zch6PR9JfOaOjow1Og1AQKu+ZUNkHpdDZpgBKr9wW4MLCQhUWFhodA0HGZrPJbrfL4/HI6/UaHeekjv3H6/F4dODAAYPTIBSEynsmVPZBKXS2aXnDwStcCAyBAAAAgKlQgAEAAGAqFGAAAACYCgUYAAAApkIBBgAAgKlQgAEAAGAqFGAAAACYCgUYAAAApkIBBgAAgKlQgAEAAGAqFGAAAACYCgUYAAAApkIBBgAAgKlQgAGgHHA6nRowYICcTqfRUQAg6IUZHQAAcO6cTqduv/12o2MAQEjgCDAAAABMhQIMAAAAU6EAAwAAwFQowAAAADAVCjAAAABMhQIMAAAAU6EAAwAAwFQowAAAADAVCjAAAABMhQIMAAAAU6EAAwAAwFQowAAAADAVCjAAAABMJczoAEePHtX8+fP1zTff6MCBA3K5XOrdu7datmwpScrMzNTs2bO1c+dOJSUladiwYWrQoIHBqQEAABCqDD8C7PV6VbFiRU2dOlXp6en6v//7P82bN0/bt29XUVGRpkyZoiZNmmjp0qXq27evpk+frtzcXKNjAwAAIEQZXoAjIiI0YMAAVa5cWRaLRXXr1tXll1+ubdu26bvvvlNBQYF69uyp8PBwNW/eXMnJydqwYYPRsQEAABCiDC/Af3fkyBH98ssvqlGjhnbt2qWUlBRZrf+LWatWLWVmZhqYEAAAAKHM8DHAx/P5fJo5c6YuueQSNWzYUD/99JOcTmexZZxOp7Kysko81u12y+12B+5brVYlJCSc98wILTabrdjXYHV8zmDPCpRGqOyDEvshUJ4FTQH2+/16/vnnlZ2drccee0wWi0WRkZHyeDzFlvN4PIqMjCzx+GXLlmnBggWB+6mpqRo5cuR5z43QFBMTY3SEUyooKJAkxcbGKj4+3uA0QNkL9n1QYj8EyrOgKMB+v1/z589XRkaGpkyZEii4ycnJWrZsmXw+X2AYREZGhlq0aFFiHT169AicOUL66whwTk7OhXkBCBk2m00xMTHKz8+X1+s1Os5J5eXlBb46HA6D0wBlJ1T2QYn90Cj8soELISgK8AsvvKAff/xRU6dOVYUKFQLT69WrJ7vdruXLl6tr16764osvlJmZqWbNmpVYh8vlksvlCtx3u91B/8MVxvF6vUH9/jiWLdhzAmcrFN7b7IdA+WV4Ac7KytKaNWsUHh6uO+64IzC9Z8+e6t27tyZOnKg5c+YoPT1diYmJGj9+vOLi4gxMDAAAgFBmeAFOTEzUihUrTjo/JSVFaWlpFzARAAAAyrOgOw0aAAAAcD5RgAEAAGAqFGAAAACYCgUYAAAApkIBBgAAgKlQgAEAAGAqFGAgCDmdTg0YMEBOp9PoKAAAlDuGnwcYQElOp1O333670TEAU+MXUaD8ogADAHAC/CIKlF8MgQAAAICpUIABAABgKhRgAAAAmAoFGAAAAKZCAQYAAICpUIABAABgKhRgAAAAmAoFGAAAAKZCAQYAAICpUIABAABgKhRgAAAAmAoFGAAAAKZCAQYAAICpUIABAABgKhRgAAAAmIrF7/f7jQ4BXChut1vLli1Tjx495HK5jI4DmA77IIBgwBFgmIrb7daCBQvkdruNjgKYEvsggGBAAQYAAICpUIABAABgKhRgmIrL5dLQoUMZewgYhH0QQDDgQ3AAAAAwFY4AAwAAwFQowDCNJUuW6OmnnzY6BgAAMFiY0QGAs/Xwww/rxx9/lM1mC0wbO3asrrvuOgNTAebSu3fvwO3CwkLZbLbAPtmzZ89i8wEgWFCAEdLuvPNOdezY0egYgGm9+eabgdv333+/OnbsqDZt2pRYzuv1FvtlFQCMRAFGubJw4UJt2LBBHo9HF110ke68805deeWVJZYrLCzU888/r82bN8vr9SoxMVH333+/kpOTdfToUS1dulTr16/X4cOH1bBhQw0fPlxRUVEGvCIgNO3bt09Dhw7Vvffeq6VLl8rhcGjSpEkaOnSo3n77bdntdknS008/rapVq6p///6SpP/+97967bXX9PvvvyspKUlDhw7VFVdcYeRLAVAOUYBRrtSuXVu9evWS0+nUqlWr9NRTT+mll16Sw+EottzHH3+szMxMvfDCC3I6ndq9e3eg4L766qvatWuX0tLSFBkZqXnz5umFF17QfffdZ8RLAkLaf//7X82aNUs2m025ubmnXDYjI0PPPPOMJkyYoMsuu0xfffWVnnjiCc2bN08xMTEXKDEAM+BDcAhpCxcuVL9+/dSvXz8NHjxYrVq1UkxMjGw2m7p27aqioiL99ttvJR4XFhamw4cPa/fu3fL7/apevbri4+Pl9/u1du1a3XnnnYqLi5PD4dCAAQO0YcMGeb1eA14hENr69eunChUqlPgl9ETWrl2rtm3bqm7durJarbrmmmtUs2ZNffnllxcgKQAz4QgwQtqQIUOKjQH+17/+pQ8//FDZ2dmyWCw6dOiQ8vPzSzyudevWys7O1ty5c5Wdna3rr79ed9xxhwoLC1VQUKAHHnig2PIWi0W5ubmqVKnSeX9NQHmSkJBwxstmZWXpu+++0/vvvx+YVlRUpKuuuup8RANgYhRglBtbt27V22+/ralTp6pGjRqyWq3q16+fTnStF5vNpt69e6t3797Kzs7WU089peXLl6t///6y2+2aOXOmkpKSDHgVQPlisVgCtyMjIyVJBQUFgTHAOTk5qlq1qqS/ynL37t0D44EB4HxhCATKjcOHD8tqtSomJkZer1dvvvmmDh8+fMJlv/32W2VkZMjr9SoiIkLh4eGyWq2yWq3q0KGDFi5cqOzsbElSbm6uNm3adCFfClAuxcTEyOVy6eOPP5bX69WmTZu0ffv2wPz27dvrgw8+0A8//CCfz6eCggJ9++23crvdBqYGUB5xBBjlRsOGDXX11VdrxIgRioiI0C233CKXy3XCZXNycjRv3jzt379fDodDjRo1Uvfu3SVJgwYN0ltvvaWHHnpIeXl5io2NVfPmzTm/MFAGRo0apXnz5mnp0qW64YYb1KRJk8C82rVr695779WiRYu0e/duhYWF6ZJLLtHdd99tYGIA5ZHFf6K/DwMAAADlFEMgAAAAYCoUYAAAAJgKBRgAAACmQgEGAACAqVCAAQAAYCoUYAAAAJgKBRgAAACmQgEGAACAqVCAAQAAYCoUYMCkJk+eLIvFEviXkJCgG2+8UZ9++qnR0QAAOK8owICJRUZGauPGjdq4caPmzZun/fv3q02bNvr++++NjgYAwHkTZnQAAMaxWq267rrrAvebNGmilJQUzZ8/X3PmzCm2rN/vV2FhoRwOx4WOCQBAmeIIMICA5ORkJSQkKCMjQ6mpqbryyiu1Zs0aNWjQQA6HQytXrpQkbdy4UTfeeKOcTqdiY2PVv39/ZWVlFVvX7t271blzZ1WoUEHVq1fXP/7xD40ePVopKSmBZV5++WVZLBZt2bJFHTt2lNPp1CWXXKJXX3212LpWr16ttm3bKjExUTExMbr22mu1du3aYsuc6bqOra9Zs2aqUKGC4uPj1apVK23ZskVHjx5V5cqVNWHChBKP6dOnj5o0aXK2mxYAEEQowAAC8vPztX//flWpUkWStHfvXt1zzz0aM2aM1q5dq6uuukobN25Uq1atFBsbqzfeeEMvvviiNm/erK5duwbW4/f71bVrV3399dd64YUXNHfuXC1fvlzLly8/4fMOGDBA7dq10zvvvKOGDRsqNTVV27ZtC8zPyMhQly5dtHjxYi1btkzNmjXTzTffrE8++aTU63rjjTfUpUsXJSYmasmSJXr99dfVrFkz7dmzR+Hh4UpNTdWrr74qn88XeEx2drbeffddDRky5Fw3MQAgGPgBmNKjjz7qdzqd/qNHj/qPHj3qz8jI8Hfv3t0vyb927Vr/oEGD/JL8mzZtKva4Fi1a+Js2ber3+XyBaVu3bvVbLBb/6tWr/X6/37969Wq/JP/69esDyxw4cMAfGxvrr1GjRmDaokWL/JL8c+fODUw7ePCgv0KFCv4pU6acMLfX6/UfPXrU365dO3+/fv1KtS6fz+evVq2av3379ifdLj///LPfYrH416xZE5g2a9Ysf2RkpD8vL++kjwMAhA6OAAMm5vF4FB4ervDwcNWsWVPr1q3TnDlz1L59e0lSpUqVdO211waWP3TokDZs2KBevXrJ6/WqqKhIRUVFqlOnjqpXr67NmzdLkjZv3qy4uDg1b9488NioqCi1adPmhDnatWsXuO10OlWjRg3t3r07MG337t0aNGiQqlatqrCwMIWHh+uDDz7QTz/9VKp1/fjjj9q9e7fuuOOOk26Tiy++WK1atdI///nPwLRFixapZ8+eiomJOenjAAChgw/BASYWGRmp9evXy2KxyOVyqXr16rJa//d7cVJSUrHlc3Jy5PV6NWbMGI0ZM6bE+n777TdJ0u+//66EhIQS8xMTE0+YIy4urth9u92uI0eOSJJ8Pp9uueUW5eXl6fHHH9fFF18sp9OpSZMmadeuXaVa1/79+yUpMMTjZIYOHarU1FS53W7t2bNHW7Zs0bPPPnvKxwAAQgcFGDAxq9Wqq6+++qTzLRZLsftxcXGyWCx6+OGH1a1btxLLu1wuSdJFF12kP//8s8T8v39Q7kz88ssv2rJli955551i44wPHz5c6nVVqlRJ0l9jm0+le/fuGjVqlF577TXt2LFDtWvXVsuWLUv9fACA4EQBBnDGnE6nrr/+em3btk1Tp0496XLXXHONcnNztX79erVo0UKSdPDgQX300UcljtCezrGia7fbA9MyMzO1YcMG1alTp1TruvTSS1WtWjUtWrRIvXv3PulyDodDt99+uxYsWKB9+/ZpzJgxJX4ZAACELgowgFJ5+umndeONN6pPnz7q27ev4uPjtXv3bn344YcaPHiwWrVqpY4dO6pRo0bq37+/pk+frri4OM2YMUPR0dHFhlicicsuu0zVqlXTQw89JK/Xq4MHD+rRRx9V1apVS53dYrEoLS1N/fr1U48ePTRw4EA5HA5t3LhR11xzjTp37hxYdujQoZo5c6ZsNptSU1NL/VwAgODFh+AAlErTpk312Wef6eDBgxo8eLBuvvlmPf7446pQoYIuvvhiSX8VzXfffVcNGjTQsGHDdNddd6lTp0666aabFBsbW6rnczgcWr58uRwOh3r16qVJkyZpwoQJZz0koU+fPnr33Xe1Z88e9e3bV/369dNnn332/9u5YxMFgjAMw9/BBRYhGK3CJlZgagN2YClGdiCYmBgIhmIxBsI2IOYG7sUmHhwnK87zxBP80fAG/0z6/f7DubquMxwOM51O/xTbALyvr7Zt266HAD7f7XZLXdeZTCbZbDZdj/Or8/mcqqqy3+8zm826HgeAf2QFAniJ9Xqd+/2e0WiU6/Wa1WqVpmmy2+26Hu2py+WS0+mUxWKRwWDw8PAOgM8ggIGX6PV6WS6XaZomSTIej3M8Hp/+OvEODodD5vN5qqrKdrvN97drEuDTWIEAAKAoHsEBAFAUAQwAQFEEMAAARRHAAAAURQADAFAUAQwAQFEEMAAARRHAAAAU5QdYgIJorkhw6QAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<ggplot: (8791071491781)>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 104
        }
      ]
    }
  ]
}