vehicle_query.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "vehicle_query.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "Q4JuRZVm173s"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BzmOEAnO60Zn",
        "outputId": "2454d585-0bb2-4ccf-fc57-bfc6c4d2770c"
      },
      "source": [
        "!apt-get update"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\r0% [Working]\r            \rHit:1 http://ppa.launchpad.net/c2d4u.team/c2d4u4.0+/ubuntu bionic InRelease\n",
            "\r0% [Waiting for headers] [Connecting to security.ubuntu.com (91.189.91.38)] [Co\r                                                                               \rHit:2 http://archive.ubuntu.com/ubuntu bionic InRelease\n",
            "\r0% [Waiting for headers] [Connecting to security.ubuntu.com (91.189.91.38)] [Wa\r                                                                               \rGet:3 http://archive.ubuntu.com/ubuntu bionic-updates InRelease [88.7 kB]\n",
            "\r0% [1 InRelease gpgv 15.9 kB] [3 InRelease 15.6 kB/88.7 kB 18%] [Connecting to \r                                                                               \rHit:4 https://cloud.r-project.org/bin/linux/ubuntu bionic-cran40/ InRelease\n",
            "\r0% [1 InRelease gpgv 15.9 kB] [3 InRelease 15.6 kB/88.7 kB 18%] [Connecting to \r                                                                               \rHit:5 http://ppa.launchpad.net/cran/libgit2/ubuntu bionic InRelease\n",
            "\r0% [1 InRelease gpgv 15.9 kB] [3 InRelease 15.6 kB/88.7 kB 18%] [Connecting to \r0% [1 InRelease gpgv 15.9 kB] [Waiting for headers] [Connecting to security.ubu\r                                                                               \rHit:6 http://ppa.launchpad.net/deadsnakes/ppa/ubuntu bionic InRelease\n",
            "\r0% [1 InRelease gpgv 15.9 kB] [Waiting for headers] [Connecting to security.ubu\r                                                                               \rGet:7 http://archive.ubuntu.com/ubuntu bionic-backports InRelease [74.6 kB]\n",
            "Hit:8 http://ppa.launchpad.net/graphics-drivers/ppa/ubuntu bionic InRelease\n",
            "Get:9 http://security.ubuntu.com/ubuntu bionic-security InRelease [88.7 kB]\n",
            "Ign:10 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64  InRelease\n",
            "Ign:11 https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64  InRelease\n",
            "Hit:12 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64  Release\n",
            "Hit:13 https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64  Release\n",
            "Fetched 252 kB in 3s (101 kB/s)\n",
            "Reading package lists... Done\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JvkE7jfJ6web"
      },
      "source": [
        "!apt-get install openjdk-8-jdk-headless -qq > /dev/null"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CDJolzSS7nbt"
      },
      "source": [
        "!wget -q https://downloads.apache.org/spark/spark-3.1.1/spark-3.1.1-bin-hadoop2.7.tgz"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VG8HeLjM73Qy"
      },
      "source": [
        "!tar xf spark-3.1.1-bin-hadoop2.7.tgz"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ea3FH4Jz7_rX"
      },
      "source": [
        "!pip install -q findspark"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7jV1-NWH8EjD"
      },
      "source": [
        "import os\n",
        "os.environ[\"JAVA_HOME\"] = \"/usr/lib/jvm/java-8-openjdk-amd64\"\n",
        "os.environ[\"SPARK_HOME\"] = \"/content/spark-3.1.1-bin-hadoop2.7\""
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jUaRyzqm8KJ7"
      },
      "source": [
        "import findspark\n",
        "findspark.init()"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fy_ShFBd8N2m"
      },
      "source": [
        "!wget -O veh -q https://data.cityofnewyork.us/api/views/bm4k-52h4/rows.csv?accessType=DOWNLOAD\n"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Phla8zV0S0Eb",
        "outputId": "59febd26-8d8c-46b2-d80b-ea39efaf550c"
      },
      "source": [
        "!wget https://bin.equinox.io/c/4VmDzA7iaHb/ngrok-stable-linux-amd64.zip\n",
        "!unzip -y ngrok-stable-linux-amd64.zip\n",
        "get_ipython().system_raw('./ngrok http 4050 &')\n",
        "!curl -s http://localhost:4040/api/tunnels"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "--2021-05-07 15:34:02--  https://bin.equinox.io/c/4VmDzA7iaHb/ngrok-stable-linux-amd64.zip\n",
            "Resolving bin.equinox.io (bin.equinox.io)... 52.45.2.52, 3.216.86.20, 34.235.106.23, ...\n",
            "Connecting to bin.equinox.io (bin.equinox.io)|52.45.2.52|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 13832437 (13M) [application/octet-stream]\n",
            "Saving to: ‘ngrok-stable-linux-amd64.zip.1’\n",
            "\n",
            "ngrok-stable-linux- 100%[===================>]  13.19M  13.5MB/s    in 1.0s    \n",
            "\n",
            "2021-05-07 15:34:04 (13.5 MB/s) - ‘ngrok-stable-linux-amd64.zip.1’ saved [13832437/13832437]\n",
            "\n",
            "UnZip 6.00 of 20 April 2009, by Debian. Original by Info-ZIP.\n",
            "\n",
            "Usage: unzip [-Z] [-opts[modifiers]] file[.zip] [list] [-x xlist] [-d exdir]\n",
            "  Default action is to extract files in list, except those in xlist, to exdir;\n",
            "  file[.zip] may be a wildcard.  -Z => ZipInfo mode (\"unzip -Z\" for usage).\n",
            "\n",
            "  -p  extract files to pipe, no messages     -l  list files (short format)\n",
            "  -f  freshen existing files, create none    -t  test compressed archive data\n",
            "  -u  update files, create if necessary      -z  display archive comment only\n",
            "  -v  list verbosely/show version info       -T  timestamp archive to latest\n",
            "  -x  exclude files that follow (in xlist)   -d  extract files into exdir\n",
            "modifiers:\n",
            "  -n  never overwrite existing files         -q  quiet mode (-qq => quieter)\n",
            "  -o  overwrite files WITHOUT prompting      -a  auto-convert any text files\n",
            "  -j  junk paths (do not make directories)   -aa treat ALL files as text\n",
            "  -U  use escapes for all non-ASCII Unicode  -UU ignore any Unicode fields\n",
            "  -C  match filenames case-insensitively     -L  make (some) names lowercase\n",
            "  -X  restore UID/GID info                   -V  retain VMS version numbers\n",
            "  -K  keep setuid/setgid/tacky permissions   -M  pipe through \"more\" pager\n",
            "  -O CHARSET  specify a character encoding for DOS, Windows and OS/2 archives\n",
            "  -I CHARSET  specify a character encoding for UNIX and other archives\n",
            "\n",
            "See \"unzip -hh\" or unzip.txt for more help.  Examples:\n",
            "  unzip data1 -x joe   => extract all files except joe from zipfile data1.zip\n",
            "  unzip -p foo | more  => send contents of foo.zip via pipe into program more\n",
            "  unzip -fo foo ReadMe => quietly replace existing ReadMe if archive file newer\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "s-KSInllV-rn"
      },
      "source": [
        "from pyspark.sql import SparkSession\n",
        "\n",
        "spark = SparkSession.builder\\\n",
        "        .master(\"local\")\\\n",
        "        .appName(\"Collision\")\\\n",
        "        .config('spark.ui.port', '4050')\\\n",
        "        .getOrCreate()"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SRqcpdVuWBF7"
      },
      "source": [
        "col=spark.read.option(\"header\",True).csv(\"./veh\",inferSchema=True);"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "t1Nh4VnyWF33",
        "outputId": "68a72845-ea09-4dd2-bdb1-f84233102302"
      },
      "source": [
        "col.cache()"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DataFrame[UNIQUE_ID: int, COLLISION_ID: int, CRASH_DATE: string, CRASH_TIME: string, VEHICLE_ID: string, STATE_REGISTRATION: string, VEHICLE_TYPE: string, VEHICLE_MAKE: string, VEHICLE_MODEL: string, VEHICLE_YEAR: int, TRAVEL_DIRECTION: string, VEHICLE_OCCUPANTS: int, DRIVER_SEX: string, DRIVER_LICENSE_STATUS: string, DRIVER_LICENSE_JURISDICTION: string, PRE_CRASH: string, POINT_OF_IMPACT: string, VEHICLE_DAMAGE: string, VEHICLE_DAMAGE_1: string, VEHICLE_DAMAGE_2: string, VEHICLE_DAMAGE_3: string, PUBLIC_PROPERTY_DAMAGE: string, PUBLIC_PROPERTY_DAMAGE_TYPE: string, CONTRIBUTING_FACTOR_1: string, CONTRIBUTING_FACTOR_2: string]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8TQDWRQOWXB0",
        "outputId": "20c32a2a-4839-46b6-eca9-08a79dde241d"
      },
      "source": [
        "col.count() - col.distinct().count()"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4U64EpA_bdzg",
        "outputId": "1f3540ed-a520-4106-c515-dde99c80da8d"
      },
      "source": [
        "len(col.columns) "
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "25"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "R3UkmrNObpS4",
        "outputId": "d3d829ad-ce82-4d6e-97c5-98f6ee21840b"
      },
      "source": [
        "col.printSchema() "
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "root\n",
            " |-- UNIQUE_ID: integer (nullable = true)\n",
            " |-- COLLISION_ID: integer (nullable = true)\n",
            " |-- CRASH_DATE: string (nullable = true)\n",
            " |-- CRASH_TIME: string (nullable = true)\n",
            " |-- VEHICLE_ID: string (nullable = true)\n",
            " |-- STATE_REGISTRATION: string (nullable = true)\n",
            " |-- VEHICLE_TYPE: string (nullable = true)\n",
            " |-- VEHICLE_MAKE: string (nullable = true)\n",
            " |-- VEHICLE_MODEL: string (nullable = true)\n",
            " |-- VEHICLE_YEAR: integer (nullable = true)\n",
            " |-- TRAVEL_DIRECTION: string (nullable = true)\n",
            " |-- VEHICLE_OCCUPANTS: integer (nullable = true)\n",
            " |-- DRIVER_SEX: string (nullable = true)\n",
            " |-- DRIVER_LICENSE_STATUS: string (nullable = true)\n",
            " |-- DRIVER_LICENSE_JURISDICTION: string (nullable = true)\n",
            " |-- PRE_CRASH: string (nullable = true)\n",
            " |-- POINT_OF_IMPACT: string (nullable = true)\n",
            " |-- VEHICLE_DAMAGE: string (nullable = true)\n",
            " |-- VEHICLE_DAMAGE_1: string (nullable = true)\n",
            " |-- VEHICLE_DAMAGE_2: string (nullable = true)\n",
            " |-- VEHICLE_DAMAGE_3: string (nullable = true)\n",
            " |-- PUBLIC_PROPERTY_DAMAGE: string (nullable = true)\n",
            " |-- PUBLIC_PROPERTY_DAMAGE_TYPE: string (nullable = true)\n",
            " |-- CONTRIBUTING_FACTOR_1: string (nullable = true)\n",
            " |-- CONTRIBUTING_FACTOR_2: string (nullable = true)\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IzZ-dCuHbtve",
        "outputId": "a949228a-d5ee-4da4-b4c6-15ea7f5bc121"
      },
      "source": [
        "col.select(\"UNIQUE_ID\").distinct().count()-col.select(\"COLLISION_ID\").distinct().count()"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1784711"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_0jjddzjgyxU"
      },
      "source": [
        "from pyspark.sql.types import DateType\n",
        "from pyspark.sql.functions import to_timestamp\n",
        "from pyspark.sql.types import IntegerType\n",
        "from pyspark.sql.functions import to_date\n",
        "import pandas as pd\n",
        "\n",
        "col= col.withColumn('CRASH_TIME',to_timestamp(col[\"CRASH_TIME\"], 'H:mm'))\n"
      ],
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "s5PrD7SDhGzk"
      },
      "source": [
        "col= col.withColumn('CRASH_DATE',to_date(col[\"CRASH_DATE\"], 'MM/dd/yyyy'))"
      ],
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "y5BAM6_NhXVW"
      },
      "source": [
        "col=col.fillna(value=\"NOT PROVIDED\",subset=[\"PUBLIC_PROPERTY_DAMAGE\"])"
      ],
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Vh10DEINhjD-"
      },
      "source": [
        "col=col.fillna(value=\"NOT PROVIDED\",subset=[\"PUBLIC_PROPERTY_DAMAGE\"])"
      ],
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DFHUpuX6h3Vw"
      },
      "source": [
        "\n",
        "col=col.fillna(value=\"NOT PROVIDED\",subset=[\"CONTRIBUTING_FACTOR_1\"])"
      ],
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZQEh8br1h8OG"
      },
      "source": [
        "\n",
        "col=col.fillna(value=\"NOT PROVIDED\",subset=[\"CONTRIBUTING_FACTOR_2\"])"
      ],
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0LMO-PLMiCJ-"
      },
      "source": [
        "col=col.fillna(value=\"NOT PROVIDED\",subset=[\"PUBLIC_PROPERTY_DAMAGE\"])"
      ],
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mgL68Fv8iQpD",
        "outputId": "7e7de68d-4518-45e6-cde3-df92560ea6a4"
      },
      "source": [
        "col.select(\"VEHICLE_TYPE\").distinct().show(20);"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "+------------+\n",
            "|VEHICLE_TYPE|\n",
            "+------------+\n",
            "|       trail|\n",
            "|        ELEC|\n",
            "|         BOX|\n",
            "|       PASS-|\n",
            "|       USP M|\n",
            "|       CONVE|\n",
            "|       ASTRO|\n",
            "|         NIU|\n",
            "|  HORSE CARR|\n",
            "|  truck trai|\n",
            "|  MOTOR DIRT|\n",
            "|  School Bus|\n",
            "|         TRK|\n",
            "|       NYC S|\n",
            "|       GOVER|\n",
            "|       FireT|\n",
            "|         VAM|\n",
            "|        BOAT|\n",
            "|       PETER|\n",
            "|    FLAT BED|\n",
            "+------------+\n",
            "only showing top 20 rows\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NT49KZ6XEexu"
      },
      "source": [
        "col.createOrReplaceTempView(\"vehicle\");\n"
      ],
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kOYS058e8gnU"
      },
      "source": [
        "v_damage=spark.sql(\"select VEHICLE_TYPE, count(unique_id) AS count from vehicle group by VEHICLE_TYPE having VEHICLE_TYPE is not null and VEHICLE_TYPE != 'UNKNOWN' order by count desc limit 10\")     "
      ],
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XxBlVaBt8vbe",
        "outputId": "4634f252-ded7-429f-e42e-49a6ac83c347"
      },
      "source": [
        "v_damage.show()"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "+--------------------+------+\n",
            "|        VEHICLE_TYPE| count|\n",
            "+--------------------+------+\n",
            "|               Sedan|801259|\n",
            "|   PASSENGER VEHICLE|770756|\n",
            "|Station Wagon/Spo...|649626|\n",
            "|SPORT UTILITY / S...|337927|\n",
            "|                Taxi| 80210|\n",
            "|          4 dr sedan| 73370|\n",
            "|                TAXI| 60785|\n",
            "|       Pick-up Truck| 56580|\n",
            "|                 VAN| 49720|\n",
            "|               OTHER| 45954|\n",
            "+--------------------+------+\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 788
        },
        "id": "HSgEY33p9q_m",
        "outputId": "6547b588-c29e-45f5-f24f-6b8d8365262d"
      },
      "source": [
        "pd.DataFrame(v_damage.collect()).plot.bar(x=0,y=1,color=[\"red\",\"silver\",\"blue\",\"violet\",\"orange\"],figsize=(15,10)\n",
        "                                                                                                          ,xlabel=\"VEHICLE_TYPE\",ylabel=\"Crash Count\"      )\n"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f9543d78550>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 28
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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pj45xO1V1blXtrKqde/bsWfcPBwAAcHdw8Jz3/x3dfWNVfXWSa6rqz1cu7O6uqp5nA6NjdPeFSS5Mkh07dsy1DwAAgGU11zOO3X3j9P6pJG/M7B7FT06XmWZ6/9S0+o1Jjl2x+fapNqpvX6WewTEAAABYp7kFx6q6d1XdZ+90klOT/FmSK5PsHRn17CRXTNNXJnnGNLrqyUk+M11uenWSU6vqyGlQnFOTXD0tu7WqTp5GU33GPvta7RgAAACs0zwvVT06yRunJ2QcnOQ3uvvNVXVdksur6pwkH03y1Gn9q5KckWRXks8neVaSdPfNVfWyJNdN6720u2+epn8kyWuTHJ7kTdMrSV6xn2MAAACwTnMLjt39kSTfukr9piSnrFLvJOftZ18XJ7l4lfrOJA9b6zEAAABYv0U8jgMAAIAlIjgCAAAwJDgCAAAwJDgCAAAwJDgCAAAwJDgCAAAwJDgCAAAwJDgCAAAwJDgCAAAwJDgCAAAwJDgCAAAwJDgCAAAwJDgCAAAwJDgCAAAwJDgCAAAwJDgCAAAwdIfBsaqOX0sNAACArWktZxx/e5XaGza6EQAAADang/e3oKoekuShSe5XVd+3YtF9kxw278YAAADYHPYbHJM8OMl3JzkiyfesqH82yXPn2RQAAACbx36DY3dfkeSKqnpMd//pAewJAACATWR0xnGvXVX1U0mOW7l+dz97Xk0BAACweawlOF6R5I+S/M8kX55vOwAAAGw2awmO9+ruF829EwAAADaltTyO4/eq6oy5dwIAAMCmtJbg+PzMwuM/VNWtVfXZqrp13o0BAACwOdzhpardfZ8D0QgAAACb0x0Gx6p63Gr17v7DjW8HAACAzWYtg+P85Irpw5I8Ksm7kzxxLh0BAACwqazlUtXvWTlfVccm+cW5dQQAAMCmspbBcfa1O8k3bXQjAAAAbE5rucfxl5P0NHuPJA9P8p55NgUAAMDmsZZ7HHeumL4tyeu7+0/m1A8AAACbzFrucbykqg5N8o1T6fr5tgQAAMBmspZLVf91kkuS/HWSSnJsVZ3tcRwAAAB3D2u5VPXnk5za3dcnSVV9Y5LXJ3nkPBsDAABgc1jLqKqH7A2NSdLdf5HkkPm1BAAAwGaypsFxqurXkvw/0/y/y+0HzAEAAGALW0tw/N+SnJfkx6b5P0xywdw6AgAAYFPZb3Csqm1JtnX3h5L8wvRKVT00yX2T7DkgHQIAALBQo3scfznJA1ap3z/JL82nHQAAADabUXB80GqP3OjuP0ryLfNrCQAAgM1kFBzvM1hmVFUAAIC7iVFw3FVVZ+xbrKrTk3xkfi0BAACwmYxGVX1Bkt+vqqcmefdU25HkMUm+e96NAQAAsDns94xjd9+Q5JuTvCPJcdPrHUm+pbv/4kA0BwAAwOINn+PY3V9M8poD1AsAAACb0OgeRwAAABAcAQAAGBMcAQAAGBre45gkVfXYJP85yddN61eS7u6vn29rAAAAbAZ3GByTXJTkxzN7JMeX59sOAAAAm81aguNnuvtNc+8EAACATWm/wbGqTpom315VP5fkd5J8ce/y7n7PnHsDAABgExidcfz5feZ3rJjuJE/c+HYAAADYbPY7qmp3P2HwWnNorKqDquq9VfV70/zxVfXOqtpVVb9ZVYdO9XtO87um5cet2MdLpvr1VfWkFfXTptquqnrxivqqxwAAAGD97vBxHFX1/Kq6b838WlW9p6pOXccxnp/kwyvmfzbJK7v7QUluSXLOVD8nyS1T/ZXTeqmqE5OcleShSU5L8qtTGD0oyauTnJ7kxCRPm9YdHQMAAIB1WstzHJ/d3bcmOTXJUUmenuQVa9l5VW1P8m+S/No0X5ld4vqGaZVLkjx5mj5zms+0/JRp/TOTXNbdX+zuv0qyK8mjpteu7v5Id38pyWVJzryDYwAAALBOawmONb2fkeTS7v7gitod+cUk/3uSf5rmj0ry6e6+bZrfneSYafqYJB9Lkmn5Z6b1/7m+zzb7q4+OAQAAwDqtJTi+u6rekllwvLqq7pOvBMH9qqrvTvKp7n73Xexxbqrq3KraWVU79+zZs+h2AAAANqW1PMfxnCQPT/KR7v58VR2V5Flr2O6xSb63qs5IcliS+yb5pSRHVNXB0xnB7UlunNa/McmxSXZX1cFJ7pfkphX1vVZus1r9psExbqe7L0xyYZLs2LGj1/AzAQAA3O3c4RnH7v6nJH+V5Bur6nGZDVJzxBq2e0l3b+/u4zIb3OZt3f3DSd6e5Pun1c5OcsU0feU0n2n527q7p/pZ06irxyc5Icm7klyX5IRpBNVDp2NcOW2zv2MAAACwTnd4xrGqnpPZyKjbk7wvyclJ/jR3/jmOL0pyWVX91yTvTXLRVL8oyeuqaleSmzMLgunuD1bV5Uk+lOS2JOd195en3p6X5OokByW5eLr/cnQMAAAA1mktl6o+P8m3Jbm2u59QVQ9J8jPrOUh3/0GSP5imP5LZiKj7rvOFJD+wn+1fnuTlq9SvSnLVKvVVjwEAAMD6rWVwnC9MoS5Vdc/u/vMkD55vWwAAAGwWaznjuLuqjkjy/ya5pqpuSfLR+bYFAADAZnGHwbG7nzJN/ueqentmo52+ea5dAQAAsGkMg2NVHZTkg939kCTp7ncckK4AAADYNIb3OE6jl15fVf/qAPUDAADAJrOWexyPTPLBqnpXks/tLXb3986tKwAAADaNtQTHn557FwAAAGxa+w2OVfWgJEfve19jVX1Hko/PuzEAAAA2h9E9jr+Y5NZV6p+ZlgEAAHA3MAqOR3f3B/YtTrXj5tYRAAAAm8ooOB4xWHb4RjcCAADA5jQKjjur6rn7FqvqOUnePb+WAAAA2ExGo6q+IMkbq+qH85WguCPJoUmeMu/GAAAA2Bz2Gxy7+5NJvr2qnpDkYVP597v7bQekMwAAADaFO3yOY3e/PcnbD0AvAAAAbEKjexwBAABAcAQAAGBMcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGDo4EU3ALDsbnnZLYtuYU2O/OkjF90CALCknHEEAABgSHAEAABgSHAEAABgSHAEAABgSHAEAABgSHAEAABgSHAEAABgSHAEAABgSHAEAABgSHAEAABgSHAEAABgSHAEAABgSHAEAABgSHAEAABgSHAEAABgSHAEAABgSHAEAABgSHAEAABgSHAEAABgSHAEAABgaG7BsaoOq6p3VdX/qqoPVtV/merHV9U7q2pXVf1mVR061e85ze+alh+3Yl8vmerXV9WTVtRPm2q7qurFK+qrHgMAAID1m+cZxy8meWJ3f2uShyc5rapOTvKzSV7Z3Q9KckuSc6b1z0lyy1R/5bRequrEJGcleWiS05L8alUdVFUHJXl1ktOTnJjkadO6GRwDAACAdZpbcOyZv59mD5leneSJSd4w1S9J8uRp+sxpPtPyU6qqpvpl3f3F7v6rJLuSPGp67eruj3T3l5JcluTMaZv9HQMAAIB1mus9jtOZwfcl+VSSa5L8ZZJPd/dt0yq7kxwzTR+T5GNJMi3/TJKjVtb32WZ/9aMGxwAAAGCd5hocu/vL3f3wJNszO0P4kHkeb72q6tyq2llVO/fs2bPodgAAADalAzKqand/OsnbkzwmyRFVdfC0aHuSG6fpG5McmyTT8vsluWllfZ9t9le/aXCMffu6sLt3dPeObdu23aWfEQAAYKua56iq26rqiGn68CTfleTDmQXI759WOzvJFdP0ldN8puVv6+6e6mdNo64en+SEJO9Kcl2SE6YRVA/NbACdK6dt9ncMAAAA1ungO17lTntgkkum0U/vkeTy7v69qvpQksuq6r8meW+Si6b1L0ryuqraleTmzIJguvuDVXV5kg8luS3Jed395SSpqucluTrJQUku7u4PTvt60X6OAQAAwDrNLTh29/uTPGKV+kcyu99x3/oXkvzAfvb18iQvX6V+VZKr1noMAAAA1u+A3OMIAADA8hIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGBIcAQAAGJpbcKyqY6vq7VX1oar6YFU9f6rfv6quqaobpvcjp3pV1auqaldVvb+qTlqxr7On9W+oqrNX1B9ZVR+YtnlVVdXoGAAAAKzfPM843pbkJ7r7xCQnJzmvqk5M8uIkb+3uE5K8dZpPktOTnDC9zk1yQTILgUnOT/LoJI9Kcv6KIHhBkueu2O60qb6/YwAAALBOcwuO3f3x7n7PNP3ZJB9OckySM5NcMq12SZInT9NnJrm0Z65NckRVPTDJk5Jc0903d/ctSa5Jctq07L7dfW13d5JL99nXascAAABgnQ7IPY5VdVySRyR5Z5Kju/vj06JPJDl6mj4mycdWbLZ7qo3qu1epZ3CMffs6t6p2VtXOPXv2rP8HAwAAuBuYe3Csqq9K8ttJXtDdt65cNp0p7Hkef3SM7r6wu3d0945t27bNsw0AAIClNdfgWFWHZBYaf727f2cqf3K6zDTT+6em+o1Jjl2x+fapNqpvX6U+OgYAAADrNM9RVSvJRUk+3N2/sGLRlUn2jox6dpIrVtSfMY2uenKSz0yXm16d5NSqOnIaFOfUJFdPy26tqpOnYz1jn32tdgwAAADW6eA57vuxSZ6e5ANV9b6p9lNJXpHk8qo6J8lHkzx1WnZVkjOS7Ery+STPSpLuvrmqXpbkumm9l3b3zdP0jyR5bZLDk7xpemVwDAAAANZpbsGxu/84Se1n8SmrrN9JztvPvi5OcvEq9Z1JHrZK/abVjgEAAMD6HZBRVQEAAFhegiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDcwuOVXVxVX2qqv5sRe3+VXVNVd0wvR851auqXlVVu6rq/VV10optzp7Wv6Gqzl5Rf2RVfWDa5lVVVaNjAAAAcOfM84zja5Octk/txUne2t0nJHnrNJ8kpyc5YXqdm+SCZBYCk5yf5NFJHpXk/BVB8IIkz12x3Wl3cAwAAADuhLkFx+7+wyQ371M+M8kl0/QlSZ68on5pz1yb5IiqemCSJyW5prtv7u5bklyT5LRp2X27+9ru7iSX7rOv1Y4BAADAnXCg73E8urs/Pk1/IsnR0/QxST62Yr3dU21U371KfXQMAAAA7oSFDY4znSnsRR6jqs6tqp1VtXPPnj3zbAUAAGBpHejg+MnpMtNM75+a6jcmOXbFetun2qi+fZX66Bj/Qndf2N07unvHtm3b7vQPBQAAsJUd6BIEoAoAACAASURBVOB4ZZK9I6OeneSKFfVnTKOrnpzkM9PlplcnObWqjpwGxTk1ydXTslur6uRpNNVn7LOv1Y4BAADAnXDwvHZcVa9P8q+TPKCqdmc2OuorklxeVeck+WiSp06rX5XkjCS7knw+ybOSpLtvrqqXJbluWu+l3b13wJ0fyWzk1sOTvGl6ZXAMAAAA7oS5Bcfuftp+Fp2yyrqd5Lz97OfiJBevUt+Z5GGr1G9a7RgAAADcOQsbHAcAAIDlIDgCAAAwJDgCAAAwJDgCAAAwJDgCAAAwJDgCAAAwJDgCAAAwJDgCAAAwdPCiGwCA2/mNWnQHd+yHetEdAMAB5YwjAAAAQ4IjAAAAQ4IjAAAAQ+5xBICtqpbgftEkafeMAmx2zjgCAAAwJDgCAAAwJDgCAAAwJDgCAAAwJDgCAAAwJDgCAAAwJDgCAAAw5DmOAABr8I53vGPRLazJ4x//+EW3AGxBzjgCAAAwJDgCAAAw5FJVAAAOuKpFd7A23YvuADYHZxwBAAAYEhwBAAAYEhwBAAAYco8jAAAssVtedsuiW1iTI3/6yEW3wF3gjCMAAABDgiMAAABDLlUFAADY6zeW5FkxP3RgnxXjjCMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDgiMAAABDWzY4VtVpVXV9Ve2qqhcvuh8AAIBltSWDY1UdlOTVSU5PcmKSp1XViYvtCgAAYDltyeCY5FFJdnX3R7r7S0kuS3LmgnsCAABYSls1OB6T5GMr5ndPNQAAANbp4EU3sEhVdW6Sc6fZv6+q6xfZzxo9IMnfbegeqzZ0d0tk4z/Lu7cN/zzvvr+aSebx+/l/bOjelsnGf5Y/fLf+5fQ9tLF8F20s30Ubx/fQxlqW76Kv29+CrRocb0xy7Ir57VPtdrr7wiQXHqimNkJV7ezuHYvuYyvwWW4sn+fG8nluHJ/lxvJ5biyf58byeW4cn+XG2gqf51a9VPW6JCdU1fFVdWiSs5JcueCeAAAAltKWPOPY3bdV1fOSXJ3koCQXd/cHF9wWAADAUtqSwTFJuvuqJFctuo85WKpLazc5n+XG8nluLJ/nxvFZbiyf58byeW4sn+fG8VlurKX/PKu7F90DAAAAm9hWvccRAACADSI4crdWVVv2cm0A2Oqq6v6r1I5fRC+w1blUlS2vqv64u79jmn5ddz99xbL3dPdJi+tueVXV0Ul+JsnXdvfpVXViksd090ULbm2pVNXoqVbd3S87YM0suap6Yne/raq+b7Xl3f07B7qnraKqvj3JcVkxNkJ3X7qwhmBSVX+S5PTuvnWaPzHJ5d39sMV2BluPsy1LwBf2XXbvFdMP3WfZ3fexvnfda5O8Jsl/nOb/IslvJhEc1+dzq9TuleQ5SY5KIjiu3eOTvC3J96yyrJMIjndCVb0uyTckeV+SL0/lTuJ7aB2q6rOZfW7/YlFmfyS67wFuaav4mSS/W1X/JsmDM/u9/OHFtrRcquo1Wf13M5n9bp5zIPvZCqrqoCRHdvffTfOHJnlmkh/v7m9aZG93heC4yfnC3hCj0+pOud95D+juy6vqJck/Pwbny3e0EbfX3T+/d7qq7pPk+UmeneSyJD+/v+34l7r7/On9WYvuZYvZkeTEdonSXdLd91l0D1tRd/9+VR2S5C1J7pPkKd39Fwtua9n83iq1Y5P8eGaPtWMdquqsJP89yeeq6oYkL09ycWbPmV/qP2oIjpufL+y77oiqekpm9/QeseIytkpyv8W1tfQ+V1VHZQrfVXVyks8stqXlNN2j88LMvlAuSXJSd9+y2K6W1/QHt+d192em+a/L7Hm+pyy2s6X1Z0m+JsnHF93IMquqb+vu6/az7Ond/boD3dMyq6pfzu3/+Hu/JH+Z5HlVle7+scV0tny6+7f3TlfV1yf5qSSPS/KKuIrozvhPSR7Z3buq6qQkf5rk+7v7dxfc110mOG5+vrDvunck+d4V0ysvY/vDA9/OlvHCJFcm+YbpHpNtSb5/sS0tn6r6uSTfl9nznb65u/9+wS1tBX+c5J1V9cIkxyT5ySQ/sdiWltoDknyoqt6V5It7i939vfvfhFVcNP1b+ZLu/nSSVNXDkvxqkpuTCI7rs3Of+XcvpIstoqoeklngeUSSn0vyH7r7tsV2tbS+1N27kqS731NVN2yF0JgYHGfTq6q3J3l4El/Yc1BV/3blX9pYn2lU2gdndvb2+u7+xwW3tHSq6p8y+2/7ttz+r+fue7oLquo7krw9yd8leUR3f2LBLS2tqnr8avXufseB7mWZTf9e/mSSczO7d/mbk5yR5Ce6e7VLBVmDqrp3ki9095en+YOS3LO7P7/YzpZHVf1WkkdmdnvE5fnKrVFJku6+eRF9Lauq2p3kF1aUXrhyvrt/4V9stCQEx03OF/Z8VdXfdPe/WnQfy2R/I1buZeRKFq2qnp7kp5Ocn+RbkjwpybO6+38ttDFIUlU/meRnk/xtkkd1998uuKWlVlXXJvnOvVdrVNVXJXlLd3/7YjtbHlX11/nKHy73vu8dPLC7++sPeFNLrKrOHy3v7v9yoHrZaC5V3eQExLkzqur6rTZi5V5GrryTquoJ+cqov3/W3X+wwHaW3b9N8h3d/akkr6+qN2Z27+jDF9vWcpruX/7lJN+U5NDMBsv4nLPh61NV35Dk1Zn9O/lNSU5P8odV9fLufs1Cm1tuh628xL+7/76q7rXIhpZNdx+36B62kmUOhnfEGcdNzhf2fDnjyKJV1TGZhe0v5Cv36DwyyeGZjQ5446J620qq6tDu/tKi+1hGVbUzyVlJfiuzAduekeQbu/slC21syVTVriQv7u43rKh9bWaXsB3b3Y9dWHNLbLpv9Ee7+z3T/COT/Ep3P2axnS236Q8dP5TkrO7e91FmDFTV5d391Gn6Z7v7RSuWvaW7T11cd3eNM46b369klS/shXa0ZKrqA9n/s7OOPsDtbBlV9TNJ/tuKQR6OzOxenf+02M6Wzq8kuaC7X7uyWFXPyGzQjDMX0dQyq6rDkpyT2Rncw1YsevZiOlp+0+iAB033kb2mqt6bRHBcn4fvO/jVdJnqWVX1nQvqaSt4QZLfqqq/zex7/WuS/OBiW1pO0x8yfjCzwPjNSf7PzP4flPU5YcX0dyV50Yr5bQe4lw0lOC4BX9h32XcvuoEt6vTu/qm9M919S1WdkdmobKzdid39lH2L3X1pVf3HRTS0BbwuyZ9ndm/jSzN7zMmHF9rRcvv89PDq91XVf8tslO97LLinpbPaiMkrz+rkK5eqsw7dfd00IuiDp5KB2tapqs5N8rTMRqG+PLM/vF2xlS+5nLMt+/xwwXHz84V91x2S5Oju/pOVxap6bBIjLd55B1XVPbv7i0lSVYcnueeCe1pGq/73XFX3iAcvr0tVHTwNH/+g7v6Bqjqzuy+pqt9I8keL7m+JPT2z38XnZfZA8GMzu4+UO8FZnY01XZ2x0knTcxwvXUhDy+lXMnvW4A91984kqaqlDjgLdq+qekRm3++HT9M1vQ5faGd3keC4+fnCvut+Maufob11WjYa7IX9+/Ukb62qvYM6PCuzAUhYn9+rqv+R5AXd/bnkn4eXf2WSqxba2fJ5V5KTkuw92/Dp6Tl5n0jy1Qvrasl190enyX9I4gzEneSsztx824rpw5KckuQ9SQTHtXtgkh9I8vNV9TWZ/X4estiWlton8pXHb6yc3ju/tAyOw5ZXVdd197ftZ9kHuvubD3RPW0VVnZ7Zl3SSXNPdVy+yn2VUVYdkdsbhmUk+mtlfJI/NLIT/lAFd1q6q3tPdJ1XVc5L8dmZnc16b5KuS/HR3//dF9rdsBveHJ0m6+1sOYDtLr6q+lNlZnZ9YcVbnIx51sLGq6ogkl3X3aYvuZVlU1auTvL67/7iqtmd2RvxpSe6d5I0rb0vh7k1w3KR8YW+cqrqhu0/Yz7Jd3f2gA90T7Gu61Hfv7+Jfenj1+q3y0OXk9s8iW9qHLi9CVX3dNHne9P666f3fZfZ5vvjAd7W8qmpbZlcMPS2zAVwuT/LM7j52oY1tMdMf4/6sux98hyuTJKmq52d2ufQDM/u9fH13v7eqTkjytO5+6UIbXDJb+XnXguMm5Qt741TV65O8rbv/xz715yT5ru42+to6VNUfd/d3VNVnc/s/blRmv5seFbMOVXXfzO7BvWGa/4F85R6Iq7v7kwtrbslU1ceTXJDVn8/a/ufnzqmq93b3I/apvae7T1pUT8to5WfmrM7GqarfzVe+i+6R5MQkl/v/pPWb/t/zrOl1eJLXZxYi/2KhjS2ZFbfwJLPboX53xXx399KO8C04bnK+sO+6qjo6yRuTfClfeU7ejsyei/mU7l7q681ZblV1YZL/b+/jOKZnvb0psy/t27r7PyywvaXi38b5qKr3JTlv7wBjVfXtSX61ux++2M6Wy2rf51PdWZ27oKoev2L2tiQf7e7di+pnq5gGdLk4ybd0t4Ha7qT9/Xe/rAyOs/lVVT12ny9so6quw3TG5tur6glJHjaVf7+737bAtraEqjoos2dh/vO/Jd39N4vraCl9W5J/v2L+s939o8ns7O5iWlpaq51p/P/bu/MozarybOPXTQMCMgjBREFUEEeQ2QhClCFGiDNqkASJU9Q4ABqHxOGLyWeMURzRKBhB8Ys4oYIaECMz4kAzY4yiiDggAjKIyNA83x/nFP1SVBdd1d2167x1/daqxTn7VFfdXaupqufdez9bK+5FwJFJNujvr8MzMWfjvkles4xndzuqQ/es/xn01qrao3WWcZBkdWAfuhnHvYBTgbc2jDQOxmqGzsJx/vMH9gpKslF/eUH/dpfxqrq2Ra6hS/Iq4B+BXwF39MMFuP92Zlavuy79eN7I9X3mOszA7XXP76KZqqrFwLYTP4eq6vrGkYZqEV2jpimXUs9xlrFQVUuS3JFkA/9dzl6SJ9Itm/5zuu7UnwZeMtHpW5rgUtWB8Af27CW5jO6Hclj6w3m0YYYd7WahX1L52Kq6pnWWIUtyAfCkyUumk2wKnGAjLLXWL/d/O7BJVe2T5FHALlX1scbRBsWl1CtXkp2r6ltJjgO2B74O3FnoVNVBzcINTJKTgU8Bx1bVb1rnGbpJ+24fD5w++ryqnjbnoVYSC8d5zh/Ymq+SnELXXOj21lmGLMkBwMHA3wHn9cM7AIcCH6iqTy7rz0pzIckJwFHAm6pq234523keZTQz47bXqbWR43f+eqrnVeW5wmpi0r7bu6mq0+Yqy8pm4TjP+QN7xSWZ9hXeqjp3rrKMg5E9OlsBDwe+Ctwy8dwjD2Yuyd7AG+m+pgAXA++oqhPapZI6E2fhjhY+Sc63Oc7MJNnIrRErjzO4mq+SfLyqnt86x6rgHsf5b+Oq+mySfwCoqtuTLGkdamDePXK9I0s7q0K3lGDPuY0zeOv1//1p/7Zm/6ZZqqoTgRNHx5KsleQ5VfW5RrGkCTcl+QP6pVdJdgbcNjFDFo0r3RZJjl/WwyEvB9Tgje0WEwvH+c8f2CtotNta/4q53ddWQFX90+h9knU8rH7l6DsEPomuScGfAWcAFo5q7TXA8cBDkpwF3Bd4dttIEr/mri8MS/PFOv1xJlN2+h7ySjeXqs5z/TLLw+iOkbiY/gd2VV3YNNhAubRl5UmyC/AxYN2qemCSbYGXVtXLG0cbnH4/xF+ytKPdrsAWFuSaL/ptEg+n+0Xof6vqtsaRtMD581zzVZIbge+yjA7KVTXYlW7OOM5TSR4DXFFV5/a/VL4UeBZwEuDBtpoP3kc3O3Y8QFVdkOTxbSMNT5Kf0S35/TDw2qq6McllFo2aL5I8Bzixqi5J8mZghyRvG/Kr5hoLP2kdQFqGS4dcHE7HwnH+Ohz40/76ccCbgFcB2wFH4DKh5ZbkMJa2RX5Akg+MPrdl9+xV1RXJXV5Qc//tzH0eeAawH7Ckby3vUhDNJ2+pqs8l2Y3urMxD6V7oeGzbWFrIqmrf1hmk6SRZC9iyv720qn7fMs/KYOE4fy0a2Ui/H3BEVR0LHJvk/Ia5huickevFy3wvzdQVSR4HVJI16I6U+J/GmQanqg5J8mpgd7q9je8ENkjyF8B/VdVvW+aTWPqC0JOBj1bVV5O8rWUgSZrH3pDk34AXAZfTLVndLMnEKQmDXervHsd5KsnFwHZ9F9XvAy+pqtMnnlXV1m0Tjockq3sO4cwkWaOqbkuyMfB+upnx0C2jPriqrmkacOD6Inxv4LnAk6pq48aRtMAl+Qrwc+CJdGeM3gx8p6q2bRpMkuahJO8D1gVeXVU39mPr063WuLmqDm6Zb0VYOM5TSd5E1yjjauCBwA5VVUm2BD5RVbs2DTggSc6sqt36609W1fNGnrm5foaSXEW3r/EY4OTym8gKSXIBcFb/9s2qumzk2dpVdXOzcBJd52S6FzMuqqofJrk/8OiqOqlxNAmAJPsCu9Et8z+zqr7YOJIWsCQ/BB42+fejvnP696vqoW2SrTgLx3msP3rj/sBJVXVTP/Ywui6WNiVYTpMOrb5LoTj6TMunPx7m2XQzYg8FjgU+VVXfbhpsoJJsTbePeeLt3sDZ9MVkVX2nYTxJmteS/DvdPrJj+qH9gB9V1SvapdJCluQHVfWwmT4bAgtHjb3RYnGKwtEZxxWQZBPgOXRF5B8Cn66qN7VNNWz9EuDnAocAm1fVosaRJGne6rfzPHJidifJasAlVfXItsm0UCX5EvCFqjp60vgBwF9U1dPaJFtxNsfRQnCfJM8EVuuvJzqxBdigXazhq6pfJPkY8Bu6Q8JfTNcBWMupX7qyPd1s467AQ+j2k/0H3cyjJGnZLqXb0nN5f79ZPya18grgC0leyNKmjDsBawPPbJZqJXDGUWOv72K1TFX1grnKMi76FtNPpesC+jjgRODTwNeryiM5ZiDJ74DvAR8CTh3d4yi11r+w8d9VtUfrLNJUkpwGPAb4Dt0exz+m66Z+PcCQZ3c0bEn2BLbqb79XVd9omWdlsHDU2Etyv6q6snWOcZHkU3SdVE+jKxa/Og5nE7WSZH9gF2BHumMPvks303h2Vf28ZTYJIMk3gH2r6vrWWaTJkjxhuudVddpcZZHGnYWjxl6SK4GL6TbOH1tV1zWONGhJDgS+ONFiWitP373yj+lmcV8ArFlVD2qbSgtdkuPollN/HbhpYryqDmoWSpI05ywcNfb6pVZ/Stdw5M+Bb9EVkcd51IHmgyT3Bh7L0n2OjwGuoOuq+sqW2aQkfz3VeFV9Yq6zSJMluZFuiSrAmsAawE1VtX67VNJ4snDUgpJkTWAfuiJyD+AbVfVXbVNpIUtyHl0zh3OAb/Zv36qq3zYNJkkDkyTA04Gdq+rvW+eRxo2FoxacJA+la+pyAPBbj+NQS0m2oTtY3W/GmleSXMTSmZy7qapt5jCOtNw8o1laNTyOQwtCks3oZhn3pztg/RjgaVX1/abBBizJYuBI4FNV9ZvWeYaqqi5snUFahqf0/504SP2T/X8PYJqCUppLI0dsQXfs1k6ADdukVcAZR429JN8ENgU+S3dA/eJ7+CNaDkm2pGvgsh/dMsujgJOcOZPGy1SzN0nOdbWG5oNJR27dDvwE+GhVXdUmkTS+LBw19pI8HjjDgmbVSLIa3czEh+mOkzgKeH9VXds0mKSVIsn5wCuq6qz+/nHAv1fVdm2TSZLmkoWjpFnr9+e9gK5b7deA/wR2A57nL5XLp39hY5mq6vS5yiJNJcmOdMvSN+iHrgNeWFXntksl3Z0z4dKqZeEoaVb6PY7XAR+jOx/zlpFnX6iqfZf5h3WnJF+eYriAbYDNqmrRHEeSppRkA4Cqur51FmkqNsWRVi2b40iaredU1Y9HB5JsXlWXWTQuv6p66uh9kl2BNwNXAq9qEkqaggWjBuCrrQNI42y11gGkuZBkUZKNR+7XTPKSJP/TMtfAfX45x7QckuyV5FTgbcB7qmrnqppqNlKS1Euyz8R1Vb25H3tZu0TS+HLGUWMvyXOBw4GbkvwQ+Be6/TrfBf6qZbYhSvIIYCtgg0lt0NcH1mqTariSPBl4E3A98OaqOrNxJEkakrckuaWqTgZI8npgD+AjbWNJ48c9jhp7SS4GnlFVlybZATgbeLazObOT5OnAM4CnAcePPLqR7riTbzYJNlBJ7gB+BlzAFGfjVdXT5jyUtAxJjq6qA1vnkCb0q4m+ArwO2Bt4BLB/Vd3aNJg0hiwcNfYmd1lLcnFVbd0y0zhIsktVnd06x9AlecJ0z6vqtLnKIo1KcvzkIbqZnJPBFzU0fyT5Q+C/gcV0HX/95VZaBSwcNfaS/Ax4z8jQa0bvq+o9d/tDWqYkr6+qdyY5jKlnyA5qEGvwkqwFbNnfXlpVv2+ZR0pyLvA94D/o/l8PcAzwXPBFDbWV5EaW/rssYE3g9v66qmr9hvGkseQeRy0EHwXWm+ZeMzPRUOicpinGRJLVgbcDLwQup/slaLMkRwFvqqrbWubTgrYTcDDdHtzXVdX5SW62YNR8UFX+HJfmmDOOktRQkvfSvZDx6qq6sR9bHzgUuLmqDm6ZT0ryAOC9wK+Ap1XVAxtHku6U5JnAyRPHxSS5D7B7VX2pbTJp/Fg4auwl+WxV/UV//W9V9YaRZydV1Z+1Szc8/YH1y/zG4b6nmek7/T5s8p6cJIuA71fVQ9skk+6q7wC8a1W9sXUWaUKS86tqu0lj51XV9q0ySePKpapaCEZ/8X4i8IaR+/vOcZZxcGjrAGOmpmrkUFVLkvjKnuaNqvoqHrCu+WeqM8n9/VZaBfwfSwvBdL98+4v5DLm/aaX7XpIDq+ro0cEkBwDfb5RJkobinCTvAT7U37+CrruqpJXMwlELwTpJtqd7VXLt/jr929pNkw3QxNLfJBcxdVfVbRrEGrJXAF9I8kKW/rKzE92/zWc2SyVJw/Aq4C3AZ/r7r9N9X5W0krnHUWMvySnTPa+qPeYqyzhIcv+q+mWSB031vKoun+tM4yDJnsBW/e33quobLfNIkiSNsnCUNCuTGw0ta0zTS7LRdM+r6tq5yiJJQ5HkfVV1yLIattmoTVr5LBw19vqjDf6oqn7Y3z+HpUtUv1ZVv2oWbsCSnFtVO0wau9ClqjOT5DLueoj1nY/oGuds0SSYJM1jSXasqsVJnjDVc/fjSyufhaPGXpIjgG9W1cf7+0uBE+iKx9ur6mUN4w1Okr8FXg5sAfxo5NF6wFlVdUCTYAOV5EEu75WkmUmyFvAyYEvgIuBjVXV721TSeLNw1NhLch6ww8SRB6PnOyU5s6p2axpwYJJsAGwI/Cvw9yOPbnRZ5cxNNXMrSZpeks8AtwFnAPsAl1fVwW1TSePNrqpaCFafdE7e80au7zPXYcbAIuAGlnatK+C6qc4i1HJJ6wCSNECPqqpHAyT5GPCdxnmksWfhqIXgjiT3q6orAarqYoAkmwJ3NE02TItZuhdvouhZN8kFwIur6idNUg3Xpkk+sKyHVXXQXIaRpIG4beKiqm5PfA1OWtUsHLUQvAv4cpK/A87rx3YADu2faQaqavOpxpPsC3wE2HtuEw3ezXhYtSTN1LZJbuivQ3dO8w0sbSy2frto0nhyj6MWhCR7A29k6Tl5FwPvqKoT2qUaP+7Xmzm/ZpIkaQiccdSCUFUnAie2zjHOkqwLrNY6xwDdOtVgkt2A/avqFVM9lyRJmksWjhp7Sf7PNI+rqv7vnIUZA0leM8XwhsDTgA/OcZzBq6qdJ66TbA/8JfAc4DLgC61ySZIkjbJw1EJw0xRj9wZeBPwBYOE4M+tNui/gSuCAqrqoQZ5BS/IwYP/+7WrgM3TbCPZoGkySJGmEexy1oCRZDziYrmj8LPDuqrqqbSotZEnuoDuH7EVVdWk/9uOq2qJtMkmSpKXcj6QFIclGSd4GXEg3075DVb3BolHzwL7AL4FTknw0yV54tqMkSZpnnHHU2EvyLrpfzo8APlRVv20cSbqbJPcGnk63ZHVP4Gjgi1V1UtNgkiRJWDhqAeiXAt4C3M7Sg+vBs55WSJJdq+qsexrT9JJ8vKqeP2lsQ7oGOftV1V5NgkmSJI2wcJQ0K1OdP+iZhDPn10ySJA2BXVU19pLsWVUn99ebV9VlI8/2rSqPPJiBJLsAjwPuO+lojvWBRW1SDdo6/TEcU+5rrKpz5ziPJEnS3Vg4aiE4FJiY0Tl25BrgzXhW3kytCaxL9/1j9GiOG4BnN0k0bJsC72bqwrHo9jtKkiQ1ZeGohSDLuJ7qXvegqk5LciawTVX9U+s8Y+DSqrI4lCRJ85rHcWghqGVcT3Wv5VBVS4BNWueQJEnS3HDGUQvBFkmOp5tdnLimv9+8XazBO7//Wn4OuGli0D2jM/aG0ZskawBbAz/3nFFJkjRf2FVVYy/JE6Z7XlWnzVWWcZLkqCmGq6peOOdhBizJR4DDquqSJBsAZwNLgI2A11bVMU0DSpIkYeGoBcgZHc0nSS6pqq3660OA3avqGUnuB5xQVdu3TShJkuQeRy0AST6SZOIX8w2AC4CjgfOS7N803IAleUCSLya5qn87NskDWucaoFtHrp8IfAmgqq5sE0eSJOnuLBy1EPxJVV3SX78A+EFVPRrYEXh9u1iDdxRwPF2TnE2AL/djmpnrkjylP8txV+BEgCSrA2s3TSZJktSzcNRC4IzOqnHfqjqqqm7v3z4O3Ld1qAF6KfBKuqL7kJF/l3sBX22WSpIkaYRdVbUQXJfkKcDP6WZ0XgTO6KwE1yQ5AJho3rI/cE3DPINUVT8A9p5i/GvA1+Y+kSRJ0t1ZOGoheCnwAeB+OKOzMr0QOAx4b39/ir7R0AAADw9JREFUFt1SYEmSJI0Zu6pKkiRJkqblHkeNvSR/k+Sh/XWSHJXkhiQX9g1JNAtJtkjy5SS/7ruqHpdki9a5hibJLknSOockSdJ0LBy1EBwM/KS/3h/YBtgceA3dElbNzqeAzwL3p+uq+jmW7nfU8jsQWJzk00me35/fKEmSNK+4VFVjL8n5VbVdf/0p4NtV9f7+/tyq2qFpwIFKcmFVbTNp7IKq2rZVpiFL8ghgH+BJwAbAKXRHc5xVVUtaZpMkSbJw1NhLci7wZOA3wOXAnhPnOib5n6p6ZMt8Q5Xk3+i+pp8GCtgP2BB4F0BVXdsu3bAlWRvYg66Q3KWqdmocSZIkLXAWjhp7/VEchwOLgC9X1d/0408AXl9VT26Zb6iSXDbN46oq9ztKkiSNCQtHLQj9mY3rVdVvRsbWARZV1Y3tkkmSJEnzn81xtCBU1e0TRWPfWXUvujMIL22bbHiSPGa0gUuSA/uOqh9IslHLbJIkSVo1LBy1YCTZOckH6PY5HgecDjyibapBOhy4FSDJ44F3AEcD1wNHNMw1SEk+nGT91jkkSZKmY+GosZfk7Ul+CPwLcCGwPfDrqvrE6NJVLbdFI41v9gOOqKpjq+otwJYNcw3Vj+mO4/jL1kEkSZKWxT2OGntJrgJ+ALyPrjnOLUl+bPOW2UlyMbBdVd2e5PvAS6rq9IlnVbV124TDk2RT4D3AxsCHgTsmnlXVF1rlkiRJmrB66wDSHLg/8ERgf+B9SU4B1k6yelXd3jbaIB0DnJbkauBm4AyAJFvSLVfVDFXVz5N8lW5W/KksLRwLsHCUJEnNOeOoBSXJvYCn0BWRfwJ8o6pcIjhDSXamK8hPqqqb+rGHAetW1blNww1Mkq3oZhl/Aby6qn7ZOJIkSdLdOOOosZdkLeBldPvvLgSOrKpj+4Ykz2gaboCSLAbOBE4AlkyMV9UPmoUats8Bh1TVSa2DSJIkLYszjhp7ST4D3Ea3pHIf4CdVdUjbVMPVn4m5G7A3sAdwDfA14ASLx5lL8vWqemLrHJIkSdOxcNTYS3JRVT26v14d+E5V7dA41thIsgldEbk33azut6rq5W1TDUeSc/33KEmS5juXqmohuG3iou8E2jLL2KmqXwBHAkcmWQ3YpXGkoblPkn2X9dCuqpIkaT5wxlFjL8kS4KaJW2Bt4Hf9dVWVh6/PQt8M53XAgxh5Eaqq9mwWaoCSXAMcR/fvcbKqqhfOcSRJkqS7sXCUNCtJLgA+Aizmrk1yFjcLNUAuVZUkSUPgUlVJs3V7VX24dYgx4NppSZI07znjKGlWkrwVuAr4InDLxHhVXdsq0xAl2aqqLmmdQ5IkaToWjpJmJcllUwxXVW0x52EGLMmNwFTfiN2DK0mS5g0LR0mSJEnStNzjKGlWkqwB/C3w+H7oVODwqrptmX9IM5Lkp1X1wNY5JEmSnHGUNCtJ/gNYA/hEP/Q8YElVvbhdqvGS5Iqq2qx1DkmSJGccJc3WY6pq25H7k/sjOrTy+MqeJEmaFywcJc3WkiQPqaofASTZgpHzHLV8krxmWY+AdecyiyRJ0rJYOEqardcBpyT5MV2R8yDgBW0jDdJ60zx7/5ylkCRJmoZ7HCXNWpJ7AQ/vb/+3qm6Z7v0lSZI0TBaOkmYlyb5TDF8PXFRVV811nqFKchjT7GWsqoPmMI4kSdKUXKoqabZeBOwCnNLf7w4sBjZP8s9V9clWwQbmnNYBJEmS7omFo6TZWh14ZFX9CiDJHwFHA48FTgcsHJfPw6vqja1DSJIkTWe11gEkDdZmE0Vj76p+7FrgtkaZhmjv1gEkSZLuiTOOkmbr1CRfAT7X3z+rH7s3cF27WIOzKMmGdJ1p76YvxCVJkpqyOY6kWUkSumJx137oLODY8pvKjCS5Bfg5UxeOVVVbzHEkSZKku7FwlKSGkpxXVdu3ziFJkjQd9zhKmpUkOyf5bpLfJrk1yZIkN7TOJUmSpJXPwlHSbH0Q2B/4IbA28GLgQ00TDdP7WweQJEm6Jy5VlTQrSc6pqp2SXFhV2/RjLrucoSRfBka/ERdwNXBKVf2/NqkkSZLuyq6qkmbrd0nWBM5P8k7gl7iKYTYOnWJsI+CAJFtX1d/PdSBJkqTJnHGUNCtJHgT8ClgTeDWwAfDvVXVp02BjIskiYHFVbdc6iyRJkoWjpBlJcg3wbbrjN74JfLuqftc21XhKcr6FoyRJmg9cqipppjYHdgYeB/wDsGOSy+gKybOq6rMtww1Nko2mGN4QOBC4ZI7jSJIkTckZR0krJMm9gRcAhwCbV9WixpEGpS+6C0g/NNEc51TgbVXlESeSJKk5C0dJM5JkE7rZxscBj+mHFwPfAs6uqstbZZMkSdKqYeEoaUaS3AGcC7wX+FxV3do4kiRJklYxC0dJM5JkF2AXuhnHzYGfAGf3b+dU1S3t0kmSJGlVsHCUtEKSPBh4KnAw8ICqWqtpoIFJ8sCq+mnrHJIkSdOxq6qkGUvyCJbuc9wVuA/dHsePtMw1UF8CdmgdQpIkaToWjpJmJMnVwC/olqaeDryjqi5tm2rQcs/vIkmS1JZLVSXNSJINqur61jnGRZKrgE8v63lVHTSHcSRJkqbkjKOkGbFoXOlupjvORJIkad5yxlGSGkpyblW5x1GSJM1rq7UOIEkL3JTnYCZZLclfzXUYSZKkqTjjKGlWktwLeBbwYEaWvVfVP7fKNERJNgBeDmwKHA98HXgl8HfABVX19IbxJEmSAAtHSbOU5ETgerr9eUsmxqvq3c1CDVCS44Df0HWp3Qv4Q7pOqwdX1fkts0mSJE2wcJQ0K0kurqqtW+cYuiQXVdWj++tFwC+BB1bV79smkyRJWso9jpJm65tJHt06xBi4beKiqpYAP7NolCRJ840zjpJmJcn3gC2By4Bb6JZXVlVt0zTYwCRZAtxE9/UDWBv4HUu/nuu3yiZJkjTBwlHSrCR50FTjVXX5XGeRJEnSqmXhKGnWkmwL/El/e0ZVXdAyz5Al2QPYqr+9uKpObRhHkiTpLiwcJc1KkoOBvwG+0A89Eziiqg5rl2p4kmxK9zX8PV2HWoAd6ZasPrOqft4qmyRJ0gQLR0mzkuRCYJequqm/vzdwtnscZybJF4Hjqurjk8YPBJ7lOY6SJGk+sKuqpNkKI+c39tdZxvtq2R41uWgEqKqjgUfMfRxJkqS7W711AEmDdRTw7X7GDOAZwMca5hmqKV/AS7IasGiOs0iSJE3JpaqSZi3JDsBu/e0ZVXVeyzxDlOS9wLrAIZOW/b4X+H1VHdQynyRJElg4SpqhJOtX1Q1JNprqeVVdO9eZhizJGsC/As8HJo4yeSDwCeCNVXVro2iSJEl3snCUNCNJvlJVT0lyGTD6DWTiwPotGkUbtCRrA1v2tz+qqt+1zCNJkjTKwlGSGkryUOBQ4CHARcBrPYJDkiTNN3ZVlTQrSb6xPGO6R0cCXwGeBZwLeA6mJEmad+yqKmlGkqwFrANsnGRDlh7BsT6wabNgw7VeVX20v35XknObppEkSZqChaOkmXopcAiwCbCYpYXjDcAHW4UasLWSbM/Sr+Pao/dVZSEpSZKac4+jpFlJ8qqqclnlCkpyKndtMjSqqmrPOYwjSZI0JQtHSbOWZGvgUcBaE2NVdXS7RJIkSVoVLBwlzUqSfwR2pysc/wvYBzizqp7dMtfQJHkMcEVVXdnfH0jXKOdy4K2eiylJkuYDu6pKmq1nA3sBV1bVC4BtgQ3aRhqkw4FbAZI8HngHcDRwPXBEw1ySJEl3sjmOpNm6uaruSHJ7kvWBq4DNWocaoEUjs4r7AUdU1bHAsUnOb5hLkiTpTs44Spqtc5LcB/goXXfVc4Gz20YapEVJJl7E2ws4eeSZL+5JkqR5wT2OklZYkgcD61fVhY2jDE6SNwF/DlwNPBDYoaoqyZbAJ6pq16YBJUmSsHCUNEtJvlFVe93TmO5Zkp2B+wMnVdVN/djDgHU9x1GSJM0HLoOSNCNJ1gLWATZOsiFLD65fH9i0WbABq6pvTTH2gxZZJEmSpmLhKGmmXgocAmxCt7dxonC8Afhgq1CSJEladVyqKmlWkryqqg5rnUOSJEmrnoWjpBnxwHpJkqSFx+M4JM2UB9ZLkiQtMO5xlDRTHlgvSZK0wDjjKGmmPLBekiRpgfGXPEkzdQxwWpKrgZuBMwD6A+uvbxlMkiRJq4bNcSTNmAfWS5IkLSwWjpIkSZKkabnHUZIkSZI0LQtHSZIkSdK0LBwlSZIkSdOycJQkLVhJTknypEljhyQ5IcnNSc4feTuwf/6TJBuPvP/uSb7SXz8/yQdHnh2Y5OIkFyU5L8lr+/GPJ3n2pM/74GV9zilyf7t//tMkvx55//9M8rcj7/fYJBcmWaPPfVF/f1KS+438fS4a+RgfWPGvrCRp3HgchyRpITsGeC7wtZGx5wKvBzarqu1m+4GT7AMcAvxZVf0iyb2AKQvBET9ans9ZVY/tP8fzgZ2q6pX9/R8BZyf5PHAN8EHg5VV1WxKAParq6iRvB94IHNR/yD2q6uoZ/yUlSQuGM46SpIXs88CTk6wJ3awfsAlwxUr42P8AvLaqfgFQVbdU1UdXwsddpqr6FXAo8E7gZcCFVXXmFO96OrDlqswiSRovzjhKkhasqro2yXeAfYDj6GYbPwsU8JAk54+8+6uq6oz++pQkS/rrdYHvT/HhtwYWzzDSdJ9zeX0E+Gtgd2CnZbzPU4CLRu5H/z6fqKr3zvBzSpLGnIWjJGmhm1iuOlE4vqgfn27Z6J1LO5PsDrx2JWVZrqWq06mqO5IcTreE9ZpJjycKxAuBN4+Mu1RVkjQtl6pKkha644C9kuwArFNVM50lXJZLgB1X0seaqTv6t8n2qKrtqurAqrpurkNJkobLwlGStKBV1W+BU4Aj6WYfV5Z/Bd410r10zSQvXokfX5KkOeNSVUmSuoLxi3RLVSdM3m94ZFUt91EVVfVffZfT/07X0rToitMJhyd5X399BbD/in7OFTC6x/HCqrqn7q+SpAUmVdU6gyRJkiRpHnOpqiRJkiRpWi5VlSRpHkvybeBek4afV1UXTfX+kiStCi5VlSRJkiRNy6WqkiRJkqRpWThKkiRJkqZl4ShJkiRJmpaFoyRJkiRpWhaOkiRJkqRp/X82vN0oFmMaOQAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 1080x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Z2UJmbpr-ydK"
      },
      "source": [
        "driving_liscence=spark.sql(\"select DRIVER_LICENSE_STATUS ,count(unique_id) AS count from vehicle group by DRIVER_LICENSE_STATUS having DRIVER_LICENSE_STATUS is not null and DRIVER_LICENSE_STATUS != 'UNKNOWN' order by count desc\")     "
      ],
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 173
        },
        "id": "uO3xIYeQJVrY",
        "outputId": "9514587c-d5c5-4427-82ed-819277aa0f4e"
      },
      "source": [
        "driving_liscence=pd.DataFrame(driving_liscence.collect());\n",
        "driving_liscence=driving_liscence.set_index(0)\n",
        "driving_liscence"
      ],
      "execution_count": 30,
      "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>1</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Licensed</th>\n",
              "      <td>1465770</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Unlicensed</th>\n",
              "      <td>24770</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Permit</th>\n",
              "      <td>10234</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                  1\n",
              "0                  \n",
              "Licensed    1465770\n",
              "Unlicensed    24770\n",
              "Permit        10234"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 606
        },
        "id": "vwj4h336KD6K",
        "outputId": "b2289529-20e7-4551-d871-d095fdf41b63"
      },
      "source": [
        "driving_liscence.plot.pie(y=1, figsize=(10, 15))"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f9543ba5810>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x1080 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "92MtPcs8M0i7",
        "outputId": "3f1aa994-6125-4c91-b6fe-4d33a9afe908"
      },
      "source": [
        "col.select(\"VEHICLE_YEAR\").distinct().show()"
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "+------------+\n",
            "|VEHICLE_YEAR|\n",
            "+------------+\n",
            "|        1959|\n",
            "|        7993|\n",
            "|        1990|\n",
            "|        2811|\n",
            "|        2996|\n",
            "|        3000|\n",
            "|        2711|\n",
            "|        2821|\n",
            "|        1975|\n",
            "|        2025|\n",
            "|        2096|\n",
            "|        1977|\n",
            "|        2914|\n",
            "|        2027|\n",
            "|        3028|\n",
            "|        2200|\n",
            "|        4321|\n",
            "|        2003|\n",
            "|        4992|\n",
            "|        2007|\n",
            "+------------+\n",
            "only showing top 20 rows\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dqgZgn4BOmz-"
      },
      "source": [
        "reasonsForAccidents=spark.sql(\"select PRE_CRASH,count(unique_id) AS count from vehicle group by PRE_CRASH having PRE_CRASH is not null and PRE_CRASH != 'Other*' order by count desc limit 5\")     "
      ],
      "execution_count": 33,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 732
        },
        "id": "1VxfJ-13dB1b",
        "outputId": "a7d362d2-ffbc-4670-cca9-7cdc8473f22e"
      },
      "source": [
        "pd.DataFrame(reasonsForAccidents.collect()).plot.bar(x=0,y=1,color=[\"red\",\"silver\",\"blue\",\"violet\",\"orange\"],figsize=(15,10)\n",
        "                                                                                                          ,xlabel=\"VEHICLE_TYPE\",ylabel=\"Crash Count\"      )\n"
      ],
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f9543c1eb10>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 34
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MxHU60-Hd3wh"
      },
      "source": [
        "reasonsForAccidents=spark.sql(\"select PRE_CRASH,count(unique_id) AS count from vehicle group by PRE_CRASH having PRE_CRASH is not null and PRE_CRASH != 'Other*' order by count desc\")     "
      ],
      "execution_count": 35,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yeFjeYpoe2Ra",
        "outputId": "0cd9da55-805e-4302-efa9-c72f1f84a004"
      },
      "source": [
        "col.select(\"DRIVER_LICENSE_STATUS\").distinct().show(10);"
      ],
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "+---------------------+\n",
            "|DRIVER_LICENSE_STATUS|\n",
            "+---------------------+\n",
            "|                 null|\n",
            "|           Unlicensed|\n",
            "|               Permit|\n",
            "|             Licensed|\n",
            "+---------------------+\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Iwz7AYDdgUfz"
      },
      "source": [
        "reasonsForAccidentsPublicProperty=spark.sql(\"select PRE_CRASH as reason,count(unique_id) AS count from vehicle where PUBLIC_PROPERTY_DAMAGE='Y' group by PRE_CRASH having PRE_CRASH is not null and PRE_CRASH != 'Other*' order by count desc\")     "
      ],
      "execution_count": 37,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "-Jqhw5VCg_B7",
        "outputId": "644b5930-0861-43e1-9f79-d1a4baec61a7"
      },
      "source": [
        "pd.DataFrame(reasonsForAccidentsPublicProperty.collect()).plot.bar(yticks=range(0,6300,200),x=0,y=1,figsize=(20,15)\n",
        "                                                                                                          ,xlabel=\"VEHICLE_TYPE\",ylabel=\"Crash Count\"      )\n"
      ],
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f9542c3fcd0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 38
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x1080 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "7gXZAn39hM0W",
        "outputId": "3a9ffe4a-db44-452b-873f-3daafa14280b"
      },
      "source": [
        "pd.DataFrame(reasonsForAccidentsPublicProperty.collect()).plot.bar(yticks=range(0,6300,200),x=0,y=1,figsize=(20,15)\n",
        "                                                                                                          ,xlabel=\"VEHICLE_TYPE\",ylabel=\"Crash Count\"      )\n"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f9542aef990>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 39
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x1080 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4wRHyQ3cnbNc",
        "outputId": "3b22ca87-86c9-463b-f330-fff6139659c5"
      },
      "source": [
        "col.select(\"PUBLIC_PROPERTY_DAMAGE_TYPE\").distinct().show()"
      ],
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "+---------------------------+\n",
            "|PUBLIC_PROPERTY_DAMAGE_TYPE|\n",
            "+---------------------------+\n",
            "|       THREE ORANGE CONS...|\n",
            "|                   BUS STOP|\n",
            "|       FENCING DIVIDING ...|\n",
            "|       POLICE/FIRE CALL ...|\n",
            "|       LANDSCAPE AND FRO...|\n",
            "|       CEMENT PILLAR INS...|\n",
            "|       LAMP POST, BRICK ...|\n",
            "|       NEWS STAND BEARS ...|\n",
            "|       BLACK METAL FENCE...|\n",
            "|       BLACK LIGHT POLE ...|\n",
            "|       GRASS BETWEEN CUR...|\n",
            "|       DAMAGE TO SUBWAY ...|\n",
            "|       DAMAGE TO CAMERA ...|\n",
            "|       THE FENCE/WALL OF...|\n",
            "|        BRICK RETAINER WALL|\n",
            "|       GATE OF 8 ROCKAWA...|\n",
            "|       CHAIN LINK FENCE ...|\n",
            "|       AT T/P/O D1 DID C...|\n",
            "|       FENCE (PARKS DEPA...|\n",
            "|       MONA<quote>S CUISINE|\n",
            "+---------------------------+\n",
            "only showing top 20 rows\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "S6SPfb9cnfjT",
        "outputId": "13048a0f-6ec4-4d2d-d60a-29df5f8e28c7"
      },
      "source": [
        "!pip install chord"
      ],
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting chord\n",
            "  Downloading https://files.pythonhosted.org/packages/de/01/9bd20aedb94840f83e8d40fefabe9baefd6223185f72f476a06c3c929ced/chord-1.0.1-py3-none-any.whl\n",
            "Installing collected packages: chord\n",
            "Successfully installed chord-1.0.1\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GbTzOU-Gpa7h"
      },
      "source": [
        "import chord\n",
        "cordDig=spark.sql(\"select DRIVER_LICENSE_STATUS,PRE_CRASH,count(unique_id) from vehicle group by PRE_CRASH,DRIVER_LICENSE_STATUS having PRE_CRASH is not null\");    "
      ],
      "execution_count": 42,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CRrp5SxLq45C"
      },
      "source": [
        "# Contributing factors for Public Property damage."
      ],
      "execution_count": 43,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "O-q8CbulJOa6"
      },
      "source": [
        "FactorsForAccidentsPublicProperty=spark.sql(\"select CONTRIBUTING_FACTOR_1 as factor,count(unique_id) AS count from vehicle where PUBLIC_PROPERTY_DAMAGE='Y' group by factor  having factor!='Unspecified' order by count desc limit 5\")     "
      ],
      "execution_count": 44,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 759
        },
        "id": "CC-wT5xfKGlH",
        "outputId": "83b5b9ef-f327-4dce-e554-ed332e1c4b75"
      },
      "source": [
        "pd.DataFrame(FactorsForAccidentsPublicProperty.collect()).plot.bar(color=[\"#9999ff\"],x=0,y=1,figsize=(10,10)\n",
        "                                                                                                          ,xlabel=\"Factors\",ylabel=\"Crash Count\",label='Crashes Damaged Public Property')\n"
      ],
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f95427aeb50>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 45
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dBQsnVvyKURg"
      },
      "source": [
        "\n",
        "TypesForAccidentsPublicProperty=spark.sql(\"select PUBLIC_PROPERTY_DAMAGE_TYPE as type,count(unique_id) AS count from vehicle group by type having type is not null order by count desc limit 5\")     "
      ],
      "execution_count": 46,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FAGWdnq5QEse",
        "outputId": "2ef0cdb6-9b1b-4428-8f7c-da871038aea0"
      },
      "source": [
        "TypesForAccidentsPublicProperty.show();"
      ],
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "+------------+-----+\n",
            "|        type|count|\n",
            "+------------+-----+\n",
            "|       FENCE|  554|\n",
            "|  LIGHT POLE|  315|\n",
            "|UTILITY POLE|  195|\n",
            "|FIRE HYDRANT|  169|\n",
            "|        TREE|  138|\n",
            "+------------+-----+\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 686
        },
        "id": "8N4QtV07Q7aL",
        "outputId": "a4597b73-62f1-4fd4-8818-377e9a57c3df"
      },
      "source": [
        "pd.DataFrame(TypesForAccidentsPublicProperty.collect()).plot.bar(color=[\"#9999ff\"],x=0,y=1,figsize=(10,10)\n",
        "                                                                                                          ,xlabel=\"Type\",ylabel=\"Crash Count\",label='Crashes Damaged Public Property')\n"
      ],
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f9542747ad0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 48
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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07dBau3uw/aMkOwy2n5jkh6Nee+egDQBgg7bxFL//s1trd1XV45NcWlXfHt3ZWmtV1dbkDQfBblGS7LLLLuuvUgCATqZ0hKy1dtfg80+SXJxk/yQ/XnEpcvD5J4PD70qy86iX7zRoG/ue57fWFrbWFs6bN28qywcAmBZTFsiqaouq2mrFdpIXJrkxySVJThocdlKSzw22L0ly4uBuywOSLB11aRMAYIM1lZcsd0hycVWt+DqfaK39S1V9I8k/VNWpSe5I8vLB8f+U5MgktyZ5IMkpU1gbAMDQmLJA1lq7Lck+q2hfkuTQVbS3JK+dqnoAAIaVlfoBADoTyAAAOhPIAAA6E8gAADoTyAAAOhPIAAA6E8gAADoTyAAAOhPIAAA6E8gAADoTyAAAOhPIAAA6E8gAADoTyAAAOhPIAAA6E8gAADoTyAAAOhPIAAA6E8gAADoTyAAAOhPIAAA6E8gAADoTyAAAOhPIAAA6E8gAADoTyAAAOhPIAAA6E8gAADoTyAAAOhPIAAA6E8gAADoTyAAAOhPIAAA6E8gAADoTyAAAOhPIAAA6E8gAADoTyAAAOhPIAAA6E8gAADoTyAAAOhPIAAA6E8gAADoTyAAAOhPIAAA6E8gAADoTyAAAOhPIAAA6E8gAADoTyAAAOhPIAAA6E8gAADoTyAAAOhPIAAA6E8gAADoTyAAAOhPIAAA6E8gAADoTyAAAOhPIAAA6E8gAADoTyAAAOhPIAAA6E8gAADoTyAAAOhPIAAA6E8gAADoTyAAAOhPIAAA6E8gAADoTyAAAOhPIAAA6E8gAADoTyAAAOhPIAAA6E8gAADoTyAAAOhPIAAA6E8gAADoTyAAAOhPIAAA6E8gAADoTyAAAOhPIAAA6m/JAVlUbVdV/VNXnB/tPqqr/XVW3VtWnqmrTQftmg/1bB/27TnVtAADDYDpGyN6Q5Fuj9v88yTtba7+V5GdJTh20n5rkZ4P2dw6OAwDY4E1pIKuqnZK8KMkHBvuV5JAkFw4O+WiSYwbbRw/2M+g/dHA8AMAGbapHyM5N8pYkywf72ye5t7W2bLB/Z5InDrafmOSHSTLoXzo4HgBggzZlgayqjkryk9batev5fRdV1TVVdc0999yzPt8aAKCLqRwhOzDJS6rq9iSfzMilyncl2aaqNh4cs1OSuwbbdyXZOUkG/VsnWTL2TVtr57fWFrbWFs6bN28KywcAmB5TFshaa29tre3UWts1ySuT/Ftr7fgkX07y0sFhJyX53GD7ksF+Bv3/1lprU1UfAMCw6LEO2e8leVNV3ZqROWIfHLR/MMn2g/Y3JTm7Q20AANNu49Ufsu5aa5cnuXywfVuS/VdxzINJXjYd9QAADBMr9QMAdCaQAQB0JpABAHQmkAEAdCaQAQB0JpABAHQmkAEAdCaQAQB0JpABAHQmkAEAdCaQAQB0JpABAHQmkAEAdCaQAQB0JpABAHQmkAEAdCaQAQB0JpABAHQmkAEAdCaQAQB0JpABAHQmkAEAdCaQAQB0JpABAHQmkAEAdCaQAQB0JpABAHQmkAEAdCaQAQB0JpABAHQmkAEAdCaQAQB0JpABAHQmkAEAdCaQAQB0JpABAHQmkAEAdCaQAQB0JpABAHQmkAEAdCaQAQB0JpABAHQmkAEAdCaQAQB0JpABAHQmkAEAdCaQAQB0JpABAHQmkAEAdCaQAQB0JpABAHQmkAEAdCaQAQB0JpABAHQmkAEAdCaQAQB0JpABAHQmkAEAdCaQAQB0JpABAHQmkAEAdCaQAQB0JpABAHQmkAEAdCaQAQB0JpABAHQmkAEAdLbaQFZVT5pMGwAAa2cyI2QXraLtwvVdCADAbLXxeB1V9fQk85NsXVXHjup6bJK5U10YAMBsMW4gS7JbkqOSbJPkxaPaf57kNVNZFADAbDJuIGutfS7J56rqv7bWrpzGmgAAZpWJRshWuLWqfj/JrqOPb629eqqKAgCYTSYTyD6X5KtJvpTkkaktBwBg9plMIHtMa+33prwSmGLnn9+7gqmzaFHvCgBYF5NZ9uLzVXXklFcCADBLTSaQvSEjoez/VNV9VfXzqrpvqgsDAJgtVnvJsrW21XQUAgAwW602kFXVc1bV3lq7Yv2XAwAw+0xmUv+bR23PTbJ/kmuTHDIlFQEAzDKTuWQ5epX+VNXOSc6dsooAAGaZyUzqH+vOJLuv70IAAGarycwhOy9JG+zOSbIgyXVTWRQAwGwymTlk14zaXpbk71trX5+iegAAZp3JzCH7aFVtmuRpg6bvTOaNq2pukiuSbDb4Ohe21v57VT0pySeTbJ+RmwNOaK39sqo2S3JBkv2SLEnyitba7Wv45wEAmHFWO4esqg5OckuS9yT5myTfHW8pjDEeSnJIa22fjFzmPLyqDkjy50ne2Vr7rSQ/S3Lq4PhTk/xs0P7OwXEAABu8yUzq/6skL2ytPbe19pwkh2UkME2ojfjFYHeTwUfLyHIZFw7aP5rkmMH20YP9DPoPraqa1J8CAGAGm0wg26S1tvIyZWvtuxkJV6tVVRtV1eIkP0lyaZLvJbm3tbZscMidSZ442H5ikh8OvsayJEszclkTAGCDNqlJ/VX1gSR/N9h/VR490X9crbVHkiyoqm2SXJzk6WtV5ShVtSjJoiTZZZdd1vXtAAC6m8wI2f+d5OYkrx983Dhom7TW2r1JvpzkvybZpqpWBMGdktw12L4ryc5JMujfOiOT+8e+1/mttYWttYXz5s1bkzIAAIbSuIGsquZV1R6ttYdaa3/dWju2tXZsRi49PnZ1bzx4/TaD7c2TvCDJtzISzF46OOykJJ8bbF8y2M+g/99aay0AABu4iUbIzkvyuFW0b5fkXZN47x2TfLmqbkjyjSSXttY+n+T3krypqm7NyByxDw6O/2CS7Qftb0py9uT+CAAAM9tEc8h+q7V2xdjG1tpXq+q9q3vj1toNSZ6xivbbMvKA8rHtDyZ52ereFwBgQzPRCNlWE/RN6i5LAABWb6JAdmtVHTm2saqOSHLb1JUEADC7THTJ8qwkX6iql2fkEUdJsjAjd0oeNdWFAQDMFuOOkLXWbkmyV5KvJNl18PGVJHsPFocFAGA9mHBh2NbaQ0k+PE21AADMSpNZGBYAgCkkkAEAdCaQAQB0ttqHi1fVgUneluQ3B8dXktZae/LUlgYAMDusNpBl5JFGb8zI0hePTG05AACzz2QC2dLW2j9PeSUAALPUuIGsqvYdbH65qs5J8pkkD63ob61dN8W1AQDMChONkP3VmP2Fo7ZbkkPWfzkAALPPuIGstfa86SwEAGC2Wu2yF1X1hqp6bI34QFVdV1UvnI7iAABmg8msQ/bq1tp9SV6YZPskJyR5x5RWBQAwi0wmkNXg85FJLmit3TSqDQCAdTSZQHZtVf1rRgLZF6tqqyTLp7YsAIDZYzLrkJ2aZEGS21prD1TV9klOmdqyAABmj9UGstba8qr6fpKnVdXcaagJAGBWmcyzLE9L8oYkOyVZnOSAJFfGOmQAAOvFZOaQvSHJM5PcMVib7BlJ7p3SqgAAZpHJBLIHW2sPJklVbdZa+3aS3aa2LACA2WMyk/rvrKptknw2yaVV9bMkd0xtWQAAs8dkJvX/9mDzbVX15SRbJ/mXKa0KAGAWmTCQVdVGSW5qrT09SVprX5mWqgAAZpEJ55C11h5J8p2q2mWa6gEAmHUmM4ds2yQ3VdXVSe5f0dhae8mUVQUAMItMJpD90ZRXAQAwi40byKrqt5LsMHbeWFU9O8ndU10YAMBsMdEcsnOT3LeK9qWDPgAA1oOJAtkOrbVvjm0ctO06ZRUBAMwyEwWybSbo23x9FwIAMFtNFMiuqarXjG0cPGz82qkrCQBgdpnoLsuzklxcVcfnVwFsYZJNk/z2uK8CAGCNjBvIWms/TvKsqnpekj0HzV9orf3btFQGADBLTOZZll9O8uVpqAUAYFaa8NFJAABMPYEMAKAzgQwAoDOBDACgM4EMAKAzgQwAoDOBDACgM4EMAKAzgQwAoDOBDACgM4EMAKAzgQwAoDOBDACgM4EMAKAzgQwAoDOBDACgM4EMAKAzgQwAoDOBDACgM4EMAKAzgQwAoDOBDACgM4EMAKAzgQwAoDOBDACgM4EMAKAzgQwAoDOBDACgM4EMAKAzgQwAoDOBDACgM4EMAKAzgQwAoDOBDACgM4EMAKAzgQwAoDOBDACgM4EMAKAzgQwAoDOBDACgM4EMAKAzgQwAoDOBDACgM4EMAKAzgQwAoDOBDACgM4EMAKAzgQwAoLMpC2RVtXNVfbmqbq6qm6rqDYP27arq0qq6ZfB520F7VdW7q+rWqrqhqvadqtoAAIbJVI6QLUvyu621PZIckOS1VbVHkrOTXNZae2qSywb7SXJEkqcOPhYlee8U1gYAMDSmLJC11u5urV032P55km8leWKSo5N8dHDYR5McM9g+OskFbcRVSbapqh2nqj4AgGExLXPIqmrXJM9I8r+T7NBau3vQ9aMkOwy2n5jkh6NeduegDQBggzblgayqtkxyUZKzWmv3je5rrbUkbQ3fb1FVXVNV19xzzz3rsVIAgD6mNJBV1SYZCWMfb619ZtD84xWXIgeffzJovyvJzqNevtOg7VFaa+e31ha21hbOmzdv6ooHAJgmU3mXZSX5YJJvtdb+elTXJUlOGmyflORzo9pPHNxteUCSpaMubQIAbLA2nsL3PjDJCUm+WVWLB22/n+QdSf6hqk5NckeSlw/6/inJkUluTfJAklOmsDYAgKExZYGstfa1JDVO96GrOL4lee1U1QMAMKymcoQMYL04//zeFUytRYt6VwD05tFJAACdCWQAAJ0JZAAAnQlkAACdCWQAAJ0JZAAAnQlkAACdCWQAAJ0JZAAAnQlkAACdCWQAAJ0JZAAAnQlkAACdCWQAAJ0JZAAAnQlkAACdCWQAAJ0JZAAAnQlkAACdCWQAAJ0JZAAAnQlkAACdCWQAAJ1t3LsAADZs55/fu4KptWhR7wrYEBghAwDoTCADAOhMIAMA6EwgAwDoTCADAOhMIAMA6EwgAwDoTCADAOhMIAMA6EwgAwDoTCADAOhMIAMA6EwgAwDoTCADAOhMIAMA6EwgAwDoTCADAOhMIAMA6EwgAwDoTCADAOhMIAMA6EwgAwDoTCADAOhMIAMA6EwgAwDoTCADAOhMIAMA6EwgAwDobOPeBQAAw+n883tXMLUWLepdwa8YIQMA6EwgAwDoTCADAOhMIAMA6EwgAwDoTCADAOhMIAMA6EwgAwDoTCADAOhMIAMA6EwgAwDoTCADAOhMIAMA6EwgAwDoTCADAOhMIAMA6EwgAwDoTCADAOhMIAMA6EwgAwDoTCADAOhMIAMA6EwgAwDoTCADAOhMIAMA6EwgAwDoTCADAOhMIAMA6EwgAwDoTCADAOhsygJZVX2oqn5SVTeOatuuqi6tqlsGn7cdtFdVvbuqbq2qG6pq36mqCwBg2EzlCNlHkhw+pu3sJJe11p6a5LLBfpIckeSpg49FSd47hXUBAAyVKQtkrbUrkvx0TPPRST462P5okmNGtV/QRlyVZJuq2nGqagMAGCbTPYdsh9ba3YPtHyXZYbD9xCQ/HHXcnYM2AIANXrdJ/a21lqSt6euqalFVXVNV19xzzz1TUBkAwPSa7kD24xWXIgeffzJovyvJzqOO22nQ9mtaa+e31ha21hbOmzdvSosFAJgO0x3ILkly0mD7pCSfG9V+4uBuywOSLB11aRMAYIO28VS9cVX9fZKDkzyuqu5M8t+TvCPJP1TVqUnuSPLyweH/lOTIJLcmeSDJKVNVFwDAsJmyQNZa+51xug5dxbEtyWunqhYAgGFmpX4AgM4EMgCAzgQyAIDOBDIAgM4EMgCAzgQyAIDOBDIAgM4EMgCAzgQyAIDOBDIAgM4EMgCAzgQyAIDOBDIAgM4EMgCAzgQyAIDOBDIAgM4EMgCAzgQyAIDOBDIAgM4EMgCAzgQyAIDOBDIAgM4EMgCAzgQyAIDOBDIAgM4EMgCAzgQyAIDOBDIAgM4EMgCAzgQyAIDOBDIAgM4EMgCAzgQyAIDOBDIAgM4EMgCAzgQyAIDOBDIAgM4EMgCAzgQyAIDOBDIAgM4EMvPqhdIAAA+nSURBVACAzgQyAIDOBDIAgM4EMgCAzgQyAIDOBDIAgM4EMgCAzgQyAIDOBDIAgM4EMgCAzgQyAIDOBDIAgM4EMgCAzgQyAIDOBDIAgM4EMgCAzgQyAIDOBDIAgM4EMgCAzgQyAIDOBDIAgM4EMgCAzgQyAIDOBDIAgM4EMgCAzgQyAIDOBDIAgM4EMgCAzgQyAIDOBDIAgM4EMgCAzgQyAIDOBDIAgM4EMgCAzgQyAIDOBDIAgM4EMgCAzgQyAIDOBDIAgM4EMgCAzgQyAIDOBDIAgM4EMgCAzgQyAIDOBDIAgM6GKpBV1eFV9Z2qurWqzu5dDwDAdBiaQFZVGyV5T5IjkuyR5Heqao++VQEATL2hCWRJ9k9ya2vtttbaL5N8MsnRnWsCAJhywxTInpjkh6P27xy0AQBs0Kq11ruGJElVvTTJ4a210wb7JyT5L621M8cctyjJosHubkm+M62FTq/HJfnP3kWwVpy7mc35m9mcv5lrQz93v9lam7eqjo2nu5IJ3JVk51H7Ow3aHqW1dn6S86erqJ6q6prW2sLedbDmnLuZzfmb2Zy/mWs2n7thumT5jSRPraonVdWmSV6Z5JLONQEATLmhGSFrrS2rqjOTfDHJRkk+1Fq7qXNZAABTbmgCWZK01v4pyT/1rmOIzIpLsxso525mc/5mNudv5pq1525oJvUDAMxWwzSHDABgVhLIAJiRqmqopt3AuhDIZgDfdIZXVb1l1PbLxvT9z+mviDXh/M14V/cugLVTVeeO2n7DmL6PTHtBQ0AgGxJV9bVR2x8b0+2bzvB65ajtt47pO3w6C2GtOH8zW/UugLX2nFHbJ43p23s6CxkWRl6GxxajtueP6fNNZ3jVONur2mf4OH8z27yqetN4na21v57OYlgjE/3fm5UEsuEx0e2uboUdXm2c7VXtM3ycv5ltoyRbxg/0mWhOVW2bkSt1K7ZXnMeN+pXVj0A2PLapqt/OyD/Obarq2EF7Jdm6X1msxj5VdV9GztPmg+0M9uf2K4tJcv5mtrtba3/auwjWytZJrs2vQth1o/pm5S9D1iEbElX14Yn6W2unTFctADNBVf1Ha+0ZveuA9UEggylSVT9ore3Suw7WjvM3/Kpq29baz3rXwZqrqle11v5usH1ga+3ro/rObK39r37V9eEuyyFRVW+qqlNX0X5qVZ3VoybWmXktM5vzN/x+UFX3DT5+Pvi4r6oeqKplvYtjQqNvxjhvTN+rp7OQYSGQDY/jk1ywivaPZZb+49wAGH6e2Zy/Idda26q19tjBx1ZJdkzy/yb5UZJ39a2O1XCH8xgm9Q+PjVtrD49tbK39sqpm5T/OmWCCW+4rI3d/McScvw1DVW2T5KwkJyb5RJJnttaW9K2K1XCH8xgC2fCYU1U7tNZ+PLqxqnboVRCTstUEfX5DH37O3wxWVY9L8rtJXpHkQ0me0Vpb2rcqJunpVXVDRn75ecpgO4P9J/crqx+T+odEVZ2Y5PUZ+eay4vbf/ZKck+R/tdY+2qs2gGFUVfcnuSfJh5P8fGy/hWGHV1X95kT9rbU7pquWYWGEbEi01i6oqnuS/GmSPQfNNyb549baP/erjNWpqiMy8tidPQZNNyX589baP/Wrisly/ma0c/Kry1tjRzuNNgyx8QJXVc1J8jtJZl0gM0IG66CqXpPkvyV5S5JrBs0Lk7wjyQdaa+f3qo3Vc/42XFX1zNbaN3rXwapV1WOTvDbJE5NckuTSJGdm5CrR9a21ozuW14VANiSq6o8n6G6ttf8xbcUwaVV1c5Jnt9Z+OqZ9+yRfa63t3qcyJsP527BU1R4ZGV35nST3ttYWdi6JcVTV55L8LMmVSQ5N8viMzB97Q2ttcc/aenHJcnjcv4q2LZKcmmT7JALZcKqxP8yTpLW2xM2xM4LzN8NV1a75VQh7OMlvJlnYWru9X1VMwpNba3slSVV9IMndSXZprT3Yt6x+BLIh0Vr7qxXbVbVVkjckOSXJJ5P81Xivo7v7qmqf1tr1oxurap+sYpIxQ8f5m8Gq6sokj83I98njWmu3VNX3hbEZYeUyT621R6rqztkcxhKBbKhU1XYZWb34+CQfTbKvx4IMvd9NcsngWaTXDtoWJjkpyau6VcVkOX8z248zMgdphyTzktwSk/lnigVVdd9gu5JsPtivjEzTeWy/0vowh2xIVNU5SY5Ncn6S97TWftG5JCZpsFbca5PMHzTdnJFz+KN+VTFZzt/MVlVbZ+R75+8keWqSbZIc1lq7umthTMiD4X+dQDYkqmp5koeSLMujf8Obtb8tzBRVtSDJbyW5qbX2rd71sGacvw1HVT0+I4vEvjIj85F27lwS46iq61pr+/auY5gIZLAOBnfHviojl7v+S5I/a629v29VTJbzt2Gqqm2TvLa19vbetbBqVXVnknEX7p2Ni/p6uPiQqKpDRm0/aUzfsdNfEZP0iiQLWmu/k+SZSRZ1roc14/zNYFW1c1WdX1Wfr6rTqmqLqvqrJN/JyJwyhtdGGXle7FbjfMw6JvUPj79MsmL49qJR20nyh0k+M+0VMRkPtdYeSFYuleCXnJnF+ZvZLkjylYx8zzw8I4v7Lk6ytzmAQ+/u1tqf9i5imAhkw6PG2V7VPsPjyVV1yWB7xUNyV+yntfaSPmUxSc7fzLZda+1tg+0vVtXLkhzfWlvesSYmx8+1MQSy4dHG2V7VPsNj7OM9/rJLFawt52+GG8wXW/HDfUmSrWuwqu+qFv1laBzau4BhY1L/kKiqe5NckZFvLAcNtjPYf3ZrbdtetQEMo6q6PcnyrHq0pbXWnjy9FcHaE8iGRFU9d6L+1tpXpqsWAGB6uWQ5PL7fWvtB7yIAZpKq2jjJEUmePmi6OckXW2vL+lUFa84dRcPjsys2quqinoUweVX1P3vXwNqrqlf0roG1V1VPTHJTRh6B9RsZeYzSW5LcVFW/0bM2WFMuWQ6J0Y+R8EiJmcNq0zNbVX0+I1cKzmit3da7HtZMVX0kyeLW2rlj2l+fZL/W2kldCoO14JLl8JjoLkuG10Zj7vJ6FHd5DbfW2lFVdUySL1TVJ5K8NyOTxFf0O3/D7YDW2sljG1tr766q73SoB9aaEbIhUVWPJLk/g6feJ3lgRVc8y3JoVdVDSe6Ku7xmtKraJyN3Nv8sv/qFyPkbchNdTXClgZnGCNmQaK1t1LsG1srNvunPXFW1WUaehPHSjCwo+vnOJbFmth7n0XKVxC+xzCgCGTCb3ZDBo8paa/+ndzGssa8kefE4fVeM0w5DSSCDdfOu3gWwTq5vrf1+7yJYa3/SWru9dxGwPphDBuugqv4xE9yE4VmIw81dsjNbVd2a5ANJ/tK6Y8x0Rshg3ax49mEleX+S0zrWwppzl+zM9owkf5rk2qo6s7X21d4FwdoyQgbribu6Zh53yW4Yqmq/JJcluTO/erZla63t3bUwWANGyGD98dvNzOMu2Rmuqg7JyFzODyR5T0atIwcziUAG66Cqthu1+2uXv1zygqlTVZ9MslOS/6u19s3e9cC6EMhg3VybkZGxFSHsulF9LYlLXsPNXbIz25daax/oXQSsD+aQAbOWu2Rntqr63Ux8/v56GsuBdWKEDNZBVW2UZPPW2i8G+wck2XTQ/R+ttZ93K47J+MvVH8IQ23LU9n9L8re9CoF1ZYQM1kFV/WWSn7TW/mKw//0kNyaZm+S61trv9ayPtVdVn2qtvaJ3HUyOu5yZ6YyQwbo5NMkzR+3f21p7cVVVEmsizWz/tXcBrBGjC8xoc3oXADPcnDErhP9eMrIAUh59OQUAxmWEDNbNplW11Yq5Yq21f02Sqto6I5ctGWJVNd5jkyrJJtNZC2uuqr6ZX42M/VZV3bCiKxaGZYYRyGDdvD/Jp6rq9NbaD5Kkqn4zyXszslAlw+2vJuj79rRVwdo6qncBsL6Y1A/rqKpOT/L7SbbIyG/mP0/yjtbae7sWBsCMIZDBelJVWyWJpS5mjqo6dqL+1tpnpqsWYHZzyRLWQVW9aRVtK7ctTDn0XjxBX0sikAHTQiCDdbPVBH2Gn4ffPxoFm7mq6rGttfvG6dtlxbxOmAlcsoQpUlVntdbO7V0H46uq61pr491pyZAbff6q6rLW2qGr6oOZwDpkMHV+7XImsF7VqO3tJuiDoeeSJUwdPxCG39NHrV01mnWsZoY2zvaq9mGoCWQwdfxAGH7fz8QT+xlujx/cWFOjtjPYn9evLFhzAhmsg6r6eVYdvCrJ5tNcDmvul621O3oXwVp7f351Y83o7cTCzMwwAhmsg9baRHdZMvy+3rsA1l5r7U/G66uqLaazFlhX7rIEZq2q+t38+jyk/0zytdba9/tUxZqoqicm2THJDa21X1bV45OcleTk1tpv9K0OJs9dlsBstmVGLnOt+HhskoVJ/rmqXtmzMFavqs5KsjjJeUmuqqrTknwrI9MF9utZG6wpI2QAY1TVdkm+ZB2r4VZVNyd5dmvtp1W1S5LvJjmwtXZt59JgjRkhAxijtfbTWLZkJnhwcK4yWJX/O8IYM5VJ/QBjVNXzkvysdx2s1k5V9e5R+zuO3m+tvb5DTbBWBDJg1qqqb+bXly3ZLsn/l+TE6a+INfTmMftGx5ixzCEDZq2q+s0xTS3Jktba/T3qAWYvgQyAGamq/jETPBGjtfaSaSwH1olLlgDMVH/ZuwBYXwQyAGaq7w/uroQZz7IXAMxUn12xUVUX9SwE1pVABsBMNXqtuCd3qwLWA4EMgJlq7HNIYcZylyUAM1JVPZLk/oyMlG2e5IEVXUlaa+2xvWqDNSWQAQB05pIlAEBnAhkAQGcCGQBAZxaGBWaFqto+yWWD3SckeSTJPYP9/Vtrv+xSGEBM6gdmoap6W5JftNY8egcYCi5ZArPV5lX1/araJEmq6rEr9qvq8qp6V1Utrqobq2r/wTFbVNWHqurqqvqPqjq67x8B2FAIZMBs9X+SXJ7kRYP9Vyb5TGvt4cH+Y1prC5KckeRDg7Y/SPJvrbX9kzwvyTlVtcX0lQxsqAQyYDb7QJJTBtunJPnwqL6/T5LW2hVJHltV2yR5YZKzq2pxRsLc3CS7TFu1wAbLpH5g1mqtfb2qdq2qg5Ns1Fq7cXT32MMzsgL8ca2170xXjcDsYIQMmO0uSPKJPHp0LElekSRV9ewkS1trS5N8McnrqqoGfc+YzkKBDZdABsx2H0+ybQaXKEd5sKr+I8n7kpw6aPsfSTZJckNV3TTYB1hnlr0AZrWqemmSo1trJ4xquzzJ/9Nau6ZbYcCsYg4ZMGtV1XlJjkhyZO9agNnNCBkAQGfmkAEAdCaQAQB0JpABAHQmkAEAdCaQAQB0JpABAHT2/wPbmimMsci9pwAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iPqaOmeBRaiz"
      },
      "source": [
        "#POINT_OF_IMPACT : Top 5 point of Impacts.\n",
        "top5impacts=spark.sql(\"select POINT_OF_IMPACT as impact,count(unique_id) AS count from vehicle group by impact having impact is not null order by count desc limit 5\")     \n",
        "\n",
        "\n"
      ],
      "execution_count": 49,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XbHgze0NRfuV",
        "outputId": "7c018a65-e75d-4a70-dba9-9e0eeac10835"
      },
      "source": [
        "top5impacts.show()"
      ],
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "+--------------------+------+\n",
            "|              impact| count|\n",
            "+--------------------+------+\n",
            "|    Center Front End|309123|\n",
            "|   Left Front Bumper|238516|\n",
            "|     Center Back End|232245|\n",
            "|  Right Front Bumper|212700|\n",
            "|Right Front Quart...|142785|\n",
            "+--------------------+------+\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 739
        },
        "id": "IGZQTfpHS0vY",
        "outputId": "555162ee-28ed-461d-c2e9-0c29953769e6"
      },
      "source": [
        "pd.DataFrame(top5impacts.collect()).plot.bar(color=[\"#9999ff\"],x=0,y=1,figsize=(10,10)\n",
        "                                                                                                          ,xlabel=\"Impact Type\",ylabel=\"Crash Count\",label='Impact location in Vehicles')\n"
      ],
      "execution_count": 51,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f95426a7d10>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 51
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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RsUlV37R6vriaP7Kvvk9JkqR20pd77lYBf5+ZewL7A6dGxJ7VvPMyc2L1mA9QzXsfMBaYBvxrRAyNiKHABcBhwJ7AjKb1fLFa15uBZ4CTqvpJwDNV/bxqOUmSpOL1WbjLzCcy865qegWwCNi5m5dMB67MzBcz8xfAYmBK9VicmY9m5h+BK4HpERHAVOCa6vVzgSOb1jW3mr4GOKhaXpIkqWj9cs5ddVh0EnBbVTotIu6LiEsi4vVVbWfgV00vW1rVuqpvBzybmavWqq+xrmr+c9XykiRJRevzcBcRrwOuBf42M58HLgTeBEwEngD+pa976Ka3WRGxMCIWPv3003W1IUmStMH0abiLiI1pBLsrMvM7AJn5ZGa+nJmvAF+ncdgV4HFgl6aXj6hqXdWXAdtExEZr1ddYVzV/62r5NWTm7MycnJmThw8fvr7friRJUu36crRsABcDizLz3Kb6Tk2LvQf4WTU9D3hfNdJ1FDAauB24AxhdjYzdhMagi3mZmcDNwFHV62cC1zWta2Y1fRRwU7W8JElS0TZa9yK99jbgA8D9EXFPVfs0jdGuE4EElgB/DZCZD0TEt4Gf0xhpe2pmvgwQEacBNwBDgUsy84FqfZ8EroyIzwF30wiTVF8vj4jFwHIagVCSJKl4fRbuMvMnQGcjVOd385rPA5/vpD6/s9dl5qO8eli3ub4SOLon/UqSJJXAO1RIkiQVxHAnSZJUEMOdJElSQQx3kiRJBTHcSZIkFcRwJ0mSVBDDnSRJUkEMd5IkSQUx3EmSJBXEcCdJklQQw50kSVJBDHeSJEkFMdxJkiQVxHAnSZJUkI3qbkAaaGbPrruDvjVrVt0dSJLWh3vuJEmSCmK4kyRJKojhTpIkqSCGO0mSpIIY7iRJkgpiuJMkSSqI4U6SJKkghjtJkqSCGO4kSZIK4h0qJA0q3mFEUunccydJklQQw50kSVJBDHeSJEkFMdxJkiQVxHAnSZJUEMOdJElSQQx3kiRJBTHcSZIkFcRwJ0mSVBDDnSRJUkEMd5IkSQUx3EmSJBXEcCdJklQQw50kSVJBDHeSJEkFMdxJkiQVxHAnSZJUEMOdJElSQQx3kiRJBTHcSZIkFcRwJ0mSVBDDnSRJUkEMd5IkSQUx3EmSJBXEcCdJklQQw50kSVJBDHeSJEkFMdxJkiQVxHAnSZJUEMOdJElSQQx3kiRJBTHcSZIkFWSjuhuQJKlVs2fX3UHfmTWr7g5UCvfcSZIkFcRwJ0mSVBDDnSRJUkEMd5IkSQUx3EmSJBXEcCdJklQQw50kSVJBDHeSJEkFMdxJkiQVxHAnSZJUEMOdJElSQQx3kiRJBTHcSZIkFcRwJ0mSVBDDnSRJUkEMd5IkSQUx3EmSJBWkz8JdROwSETdHxM8j4oGIOL2qbxsRCyLi4err66t6RMRXI2JxRNwXEXs3rWtmtfzDETGzqb5PRNxfvearERHdbUOSJKl0fbnnbhXw95m5J7A/cGpE7AmcAdyYmaOBG6vnAIcBo6vHLOBCaAQ14CxgP2AKcFZTWLsQOLnpddOqelfbkCRJKlqfhbvMfCIz76qmVwCLgJ2B6cDcarG5wJHV9HTgsmz4KbBNROwEHAosyMzlmfkMsACYVs3bKjN/mpkJXLbWujrbhiRJUtH65Zy7iBgJTAJuA3bMzCeqWb8BdqymdwZ+1fSypVWtu/rSTup0s421+5oVEQsjYuHTTz/d829MkiSpzfR5uIuI1wHXAn+bmc83z6v2uGVfbr+7bWTm7MycnJmThw8f3pdtSJIk9Ys+DXcRsTGNYHdFZn6nKj9ZHVKl+vpUVX8c2KXp5SOqWnf1EZ3Uu9uGJElS0fpytGwAFwOLMvPcplnzgI4RrzOB65rqx1ejZvcHnqsOrd4AHBIRr68GUhwC3FDNez4i9q+2dfxa6+psG5IkSUXbqA/X/TbgA8D9EXFPVfs08AXg2xFxEvAYcEw1bz5wOLAYeAH4IEBmLo+IzwJ3VMudk5nLq+lTgDnAZsD11YNutiFJklS0Pgt3mfkTILqYfVAnyydwahfrugS4pJP6QmCvTurLOtuGJElS6bxDhSRJUkEMd5IkSQUx3EmSJBXEcCdJklQQw50kSVJBDHeSJEkFMdxJkiQVxHAnSZJUEMOdJElSQQx3kiRJBTHcSZIkFcRwJ0mSVBDDnSRJUkEMd5IkSQUx3EmSJBXEcCdJklQQw50kSVJBDHeSJEkFMdxJkiQVxHAnSZJUEMOdJElSQQx3kiRJBTHcSZIkFcRwJ0mSVBDDnSRJUkEMd5IkSQUx3EmSJBXEcCdJklSQdYa7iBjVSk2SJEn1a2XP3bWd1K7Z0I1IkiRp/W3U1YyI+FNgLLB1RLy3adZWwLC+bkySJEk912W4A8YARwDbAH/RVF8BnNyXTUmSJKl3ugx3mXkdcF1EvCUz/6sfe5IkSVIvdbfnrsPiiPg0MLJ5+cw8sa+akiRJUu+0Eu6uA34M/BB4uW/bkSRJ0vpoJdxtnpmf7PNOJEmStN5auRTK9yLi8D7vRJIkSeutlXB3Oo2A94eIeD4iVkTE833dmCRJknpunYdlM3PL/mhEkiRJ62+d4S4i/qyzemb+x4ZvR5IkSeujlQEVH2+aHgZMAe4EpvZJR5IkSeq1Vg7LNt+dgojYBfhyn3UkSZKkXmtlQMXalgJ7bOhGJEmStP5aOefufCCrp0OAicBdfdmUJEmSeqeVc+4WNk2vAr6Vmf/ZR/1IkiRpPbRyzt3ciNgE2L0qPdS3LUmSJKm3Wjks+w5gLrAECGCXiJjppVAkSZLaTyuHZf8FOCQzHwKIiN2BbwH79GVjkiRJ6rlWRstu3BHsADLzv4GN+64lSZIk9VZLAyoi4t+Ab1TPj2PNQRaSJElqE62Eu78BTgU+Wj3/D+DCPutIkiRJvdZluIuI4cDwzPw5cG71ICLGAlsBT/dLh5IkSWpZd+fcnQ9s30l9W+ArfdOOJEmS1kd34e7NnV3uJDN/DIzvu5YkSZLUW92Fuy27medoWUmSpDbUXbhbHBGHr12MiMOAR/uuJUmSJPVWd6Nl/xb4fkQcA9xZ1SYDbwGO6OvGJEmS1HNd7rnLzIeBccAtwMjqcQswvrqQsSRJktpMt9e5y8wXgUv7qRdJkiStp1ZuPyZJkqQBwnAnSZJUEMOdJElSQdZ5b9mIeBtwNrBrtXwAmZm79W1rkiRJ6ql1hjvgYuDvaFwO5eW+bUeSJEnro5Vw91xmXt/nnUiSJGm9dRnuImLvavLmiPhn4DvAix3zM/OuPu5NkiRJPdTdnrt/Wev55KbpBKZu+HYkSZK0ProMd5n5zv5sRJIkSetvnZdCiYjTI2KraPi3iLgrIg7pj+YkSZLUM61c5+7EzHweOATYDvgA8IU+7UqSJEm90kq4i+rr4cBlmflAU02SJEltpJVwd2dE/IBGuLshIrYEXunbtiRJktQbrVzn7iRgIvBoZr4QEdsBH+zbtiRJktQb6wx3mflKRPwC2D0ihvVDT5IkSeqlVu4t+yHgdGAEcA+wP/BfeJ07SZKkttPKOXenA/sCj1XXvpsEPLuuF0XEJRHxVET8rKl2dkQ8HhH3VI/Dm+Z9KiIWR8RDEXFoU31aVVscEWc01UdFxG1V/aqI2KSqb1o9X1zNH9nC9yhJklSEVsLdysxcCY3glJkPAmNaeN0cYFon9fMyc2L1mF+td0/gfcDY6jX/GhFDI2IocAFwGLAnMKNaFuCL1breDDxD49xAqq/PVPXzquUkSZIGhVbC3dKI2Ab4LrAgIq4DHlvXizLzP4DlLfYxHbgyM1/MzF8Ai4Ep1WNxZj6amX8ErgSmR0TQOCx8TfX6ucCRTeuaW01fAxxULS9JklS8dYa7zHxPZj6bmWcDZwIX82qQ6o3TIuK+6rDt66vazsCvmpZZWtW6qm8HPJuZq9aqr7Guav5z1fKvERGzImJhRCx8+umn1+NbkiRJag/dhrvq0OiDHc8z85bMnFftReuNC4E30bi0yhPAv/RyPRtEZs7OzMmZOXn48OF1tiJJkrRBdBvuMvNl4KGIeOOG2FhmPpmZL2fmK8DXaRx2BXgc2KVp0RFVrav6MmCbiNhorfoa66rmb10tL0mSVLxWzrl7PfBARNwYEfM6Hr3ZWETs1PT0PUDHSNp5wPuqka6jgNHA7cAdwOhqZOwmNAZdzMvMBG4GjqpePxO4rmldM6vpo4CbquUlSZKK18odKs7szYoj4lvAO4DtI2IpcBbwjoiYCCSwBPhrgMx8ICK+DfwcWAWcWu01JCJOA24AhgKXVPe2BfgkcGVEfA64m8a5gFRfL4+IxTQGdLyvN/1LkiQNRF2Gu4h4M7BjZt6yVv3tNM6X61ZmzuikfHEntY7lPw98vpP6fGB+J/VHefWwbnN9JXD0uvqTJEkqUXeHZb8MPN9J/blqniRJktpMd+Fux8y8f+1iVRvZZx1JkiSp17oLd9t0M2+zDd2IJEmS1l934W5hRJy8djEiPgTc2XctSZIkqbe6Gy37t8C/R8SxvBrmJgOb0LiMiSRJktpMl+EuM58E3hoR7wT2qsrfz8yb+qUzSZIk9dg6r3OXmTfTuGCwJElSr8yeXXcHfWvWrLo7eFUrd6iQJEnSAGG4kyRJKojhTpIkqSCGO0mSpIIY7iRJkgpiuJMkSSqI4U6SJKkghjtJkqSCGO4kSZIKYriTJEkqiOFOkiSpIIY7SZKkghjuJEmSCmK4kyRJKojhTpIkqSCGO0mSpIIY7iRJkgpiuJMkSSqI4U6SJKkghjtJkqSCGO4kSZIKYriTJEkqiOFOkiSpIIY7SZKkghjuJEmSCmK4kyRJKojhTpIkqSCGO0mSpIIY7iRJkgpiuJMkSSqI4U6SJKkghjtJkqSCGO4kSZIKYriTJEkqiOFOkiSpIIY7SZKkghjuJEmSCmK4kyRJKojhTpIkqSCGO0mSpIIY7iRJkgpiuJMkSSqI4U6SJKkghjtJkqSCGO4kSZIKYriTJEkqiOFOkiSpIIY7SZKkghjuJEmSCmK4kyRJKojhTpIkqSCGO0mSpIIY7iRJkgpiuJMkSSqI4U6SJKkghjtJkqSCGO4kSZIKYriTJEkqiOFOkiSpIIY7SZKkghjuJEmSCmK4kyRJKojhTpIkqSCGO0mSpIIY7iRJkgpiuJMkSSqI4U6SJKkgfRbuIuKSiHgqIn7WVNs2IhZExMPV19dX9YiIr0bE4oi4LyL2bnrNzGr5hyNiZlN9n4i4v3rNVyMiutuGJEnSYNCXe+7mANPWqp0B3JiZo4Ebq+cAhwGjq8cs4EJoBDXgLGA/YApwVlNYuxA4uel109axDUmSpOL1WbjLzP8Alq9Vng7MrabnAkc21S/Lhp8C20TETsChwILMXJ6ZzwALgGnVvK0y86eZmcBla62rs21IkiQVr7/PudsxM5+opn8D7FhN7wz8qmm5pVWtu/rSTurdbUOSJKl4tQ2oqPa4ZZ3biIhZEbEwIhY+/fTTfdmKJElSv+jvcPdkdUiV6utTVf1xYJem5UZUte7qIzqpd7eN18jM2Zk5OTMnDx8+vNfflCRJUrvo73A3D+gY8ToTuK6pfnw1anZ/4Lnq0OoNwCER8fpqIMUhwA3VvOcjYv9qlOzxa62rs21IkiQVb6O+WnFEfAt4B7B9RCylMer1C8C3I+Ik4DHgmGrx+cDhwGLgBeCDAJm5PCI+C9xRLXdOZnYM0jiFxojczYDrqwfdbEOSJKl4fRbuMnNGF7MO6mTZBE7tYj2XAJd0Ul8I7NVJfVln25AkSRoMvEOFJElSQQx3kiRJBTHcSZIkFcRwJ0mSVBDDnSRJUkEMd5IkSQUx3EmSJBXEcCdJklQQw50kSVJBDHeSJEkFMdxJkiQVxHAnSZJUEMOdJElSQQx3kiRJBTHcSZIkFcRwJ0mSVBDDnSRJUkEMd5IkSQUx3EmSJBXEcCdJklQQw50kSVJBDHeSJEkFMdxJkiQVxHAnSZJUEMOdJElSQQx3kiRJBTHcSZIkFcRwJ0mSVBDDnSRJUkEMd5IkSQUx3EmSJBXEcCdJklQQw50kSVJBDHeSJEkFMdxJkiQVxHAnSZJUEMOdJElSQQx3kiRJBTHcSZIkFcRwJ0mSVBDDna47qV4AACAASURBVCRJUkEMd5IkSQUx3EmSJBXEcCdJklQQw50kSVJBDHeSJEkFMdxJkiQVxHAnSZJUEMOdJElSQQx3kiRJBTHcSZIkFcRwJ0mSVBDDnSRJUkEMd5IkSQUx3EmSJBXEcCdJklQQw50kSVJBDHeSJEkFMdxJkiQVxHAnSZJUEMOdJElSQQx3kiRJBTHcSZIkFcRwJ0mSVBDDnSRJUkEMd5IkSQUx3EmSJBXEcCdJklQQw50kSVJBDHeSJEkFMdxJkiQVxHAnSZJUEMOdJElSQQx3kiRJBTHcSZIkFaSWcBcRSyLi/oi4JyIWVrVtI2JBRDxcfX19VY+I+GpELI6I+yJi76b1zKyWfzgiZjbV96nWv7h6bfT/dylJktT/6txz987MnJiZk6vnZwA3ZuZo4MbqOcBhwOjqMQu4EBphEDgL2A+YApzVEQirZU5uet20vv92JEmS6tdOh2WnA3Or6bnAkU31y7Lhp8A2EbETcCiwIDOXZ+YzwAJgWjVvq8z8aWYmcFnTuiRJkopWV7hL4AcRcWdEzKpqO2bmE9X0b4Adq+mdgV81vXZpVeuuvrSTuiRJUvE2qmm7b8/MxyNiB2BBRDzYPDMzMyKyr5uoguUsgDe+8Y19vTlJkqQ+V8ueu8x8vPr6FPDvNM6Ze7I6pEr19alq8ceBXZpePqKqdVcf0Um9sz5mZ+bkzJw8fPjw9f22JEmSatfv4S4itoiILTumgUOAnwHzgI4RrzOB66rpecDx1ajZ/YHnqsO3NwCHRMTrq4EUhwA3VPOej4j9q1GyxzetS5IkqWh1HJbdEfj36uokGwHfzMz/FxF3AN+OiJOAx4BjquXnA4cDi4EXgA8CZObyiPgscEe13DmZubyaPgWYA2wGXF89JEmSitfv4S4zHwUmdFJfBhzUST2BU7tY1yXAJZ3UFwJ7rXezkiRJA0w7XQpFkiRJ68lwJ0mSVBDDnSRJUkEMd5IkSQUx3EmSJBXEcCdJklQQw50kSVJBDHeSJEkFMdxJkiQVxHAnSZJUEMOdJElSQQx3kiRJBTHcSZIkFcRwJ0mSVBDDnSRJUkEMd5IkSQUx3EmSJBXEcCdJklQQw50kSVJBDHeSJEkFMdxJkiQVxHAnSZJUEMOdJElSQQx3kiRJBTHcSZIkFcRwJ0mSVBDDnSRJUkEMd5IkSQUx3EmSJBXEcCdJklQQw50kSVJBDHeSJEkFMdxJkiQVxHAnSZJUEMOdJElSQQx3kiRJBTHcSZIkFcRwJ0mSVBDDnSRJUkEMd5IkSQUx3EmSJBXEcCdJklQQw50kSVJBDHeSJEkFMdxJkiQVxHAnSZJUEMOdJElSQQx3kiRJBTHcSZIkFcRwJ0mSVBDDnSRJUkEMd5IkSQUx3EmSJBXEcCdJklQQw50kSVJBDHeSJEkFMdxJkiQVxHAnSZJUEMOdJElSQQx3kiRJBTHcSZIkFcRwJ0mSVBDDnSRJUkEMd5IkSQUx3EmSJBXEcCdJklQQw50kSVJBDHeSJEkFMdxJkiQVxHAnSZJUEMOdJElSQQx3kiRJBTHcSZIkFcRwJ0mSVBDDnSRJUkGKDXcRMS0iHoqIxRFxRt39SJIk9Yciw11EDAUuAA4D9gRmRMSe9XYlSZLU94oMd8AUYHFmPpqZfwSuBKbX3JMkSVKfi8ysu4cNLiKOAqZl5oeq5x8A9svM09ZabhYwq3o6BnioXxvtX9sDv627CfWKP7uBzZ/fwObPb+Aq/We3a2YO72zGRv3dSTvJzNnA7Lr76A8RsTAzJ9fdh3rOn93A5s9vYPPnN3AN5p9dqYdlHwd2aXo+oqpJkiQVrdRwdwcwOiJGRcQmwPuAeTX3JEmS1OeKPCybmasi4jTgBmAocElmPlBzW3UbFIefC+XPbmDz5zew+fMbuAbtz67IARWSJEmDVamHZSVJkgYlw50kSVJBDHdSG4mIoRHxpbr7kAajaNhl3UtK7a3IARXSQJWZL0fE2+vuQz0XEdt2Nz8zl/dXL+qdzMyImA+Mq7sXtS4iPtbd/Mw8t796aReGu8JExAqgy1EymblVP7aj3rk7IuYBVwO/7yhm5nfqa0ktuJPGey+ANwLPVNPbAL8ERtXXmnrgrojYNzPvqLsRtWzLuhtoN4a7wmTmlgAR8VngCeByGh8wxwI71diaWjcMWAZMbaolYLhrY5k5CiAivg78e2bOr54fBhxZZ2/qkf2AYyPiMRp/XAWNnXrj621LXcnMz9TdQ7vxUiiFioh7M3PCumqSNqyIuD8zx62rpvYUEbt2Vs/Mx/q7F/VMROwOXAjsmJl7RcR44N2Z+bmaW+t3Dqgo1+8j4tjqBP0hEXEsTYf41L4iYveIuDEiflY9Hx8R/7PuvtSyX0fE/4yIkdXjH4Bf192UWlOFuF2AqdX0C/hZOVB8HfgU8BJAZt5H4w5Vg47/Ycv1fuAY4MnqcXRVU/vzF9TANgMYDvx79dihqmkAiIizgE/SeA8CbAx8o76O1AObZ+bta9VW1dJJzTznrlCZuQSYXncf6pXNM/P2iGiuDcpfUANRNSr29Lr7UK+9B5gE3AWQmb+OCE/YHxh+GxFvohpUGBFH0Tj3fNAx3BUqIoYDJwMjafo5Z+aJdfWklvkLagCrzvv5H7z2vTe1q9eorfyxuiRKx/tvi7obUstOpXE/2T+NiMeBXwDH1dtSPQx35boO+DHwQ+DlmntRz3T2C+rYeltSD1wNXAT8G773BqJvR8T/AbaJiJOBE2mcKqE2l5mPAu+qAvmQzFxRd091cbRsoSLinsycWHcf6j1/QQ1MEXFnZu5Tdx/qvYg4GDikevqDzFxQZz9qTURsCvwlr91rfk5dPdXFPXfl+l5EHN5xrS0NHBGxHXAW8HYgI+InwDmZuazeztSi/xsRp9AYTPFiR9E7VAwo9wOb0Tg14v6ae1HrrgOeo3FB8RfXsWzR3HNXqOpOFVvQ+A/+Eq9eiNM7VLS5iFgA/AevjtA7FnhHZr6rvq7Uqoj4RSflzMzd+r0Z9VhEfAj4X8BNNH5vHkjjj6tLam1M6xQRP8vMveruox0Y7qQ209kvKC+CK/WPiHgIeGvHnvJqT/qtmTmm3s60LhExGzg/Mwf93lavc1eYiDiuafpta807rf87Ui/8ICLeV118ekhEHAPcUHdT6l5EfKJp+ui15v1j/3ekXloGNJ/nuqKqqf29HbgzIh6KiPsi4v6IuK/upurgnrvCRMRdmbn32tOdPVd7ajqk/kpVGsKrdxfx0Hqb8r1Xhoi4DBhH4/ytpHG90PuqB5l5bn3dqTveOu5VDqgoT3Qx3dlztaHM9IKpA5PvvTI8Uj06XFd99X3Z5jpCXETsAAyruZ1aGe7Kk11Md/Zcbaq64fVI1hzO/53aGlIrfO8VIDM/U3cP6p2IeDfwL8AbgKeAXYFFwNg6+6qDh2ULExEvAItp7Cl4UzVN9Xy3zPRq620uIi4BxgMP8Oqh2fTuIu0tIl6mcfg8aFxG44WOWcCwzNy4rt7UuoiYDPwDjWDQ/MfV+NqaUksi4l5gKvDDzJwUEe8EjsvMk2purd+55648e9TdgNbb/pm5Z91NqGcyc2jdPWiDuAL4OI3r272yjmXVXl7KzGUdg9Ey8+aI+HLdTdXBcFeYwXjiaIH+KyL2zMyf192INAg9nZnz6m5CvfJsRLyOxnVCr4iIp3h1MNqg4mFZqc1ExIHAPOA3NC5C3XEBag8LSX0sIg4CZgA3suYdRjzntc1FxObAShpXGDgW2Bq4YjDe3cdwJ7WZiFgMfIy1Dgu5V1bqexHxDeBP8ZzXASMi9gNm0zjP/H7gpMF+5MNwV6iIOD0zv7KumtpPRPxXZr6l7j7UOxFxWGZev1btw5l5UV09qXUR8ZB3oxhYImIh8Ckah2PfDXwoMw+tt6t6eYeKcs3spHZCfzehXrk7Ir4ZETMi4r0dj7qbUsvOjIipHU+qO1dMr7Ef9cytEeGApoFlSGYuyMwXM/NqYHjdDdXNARWFiYgZwPuBURHRfFLwlsDyerpSD21G41yfQ5pqCXjOz8DwbuB7EfFxYBqNQ3yGu4Fjf+CeiPgFnvM6UGyz1h/AazwfjOdLeli2MNXtV0YB/wSc0TRrBXBfZq6qpTFpEKmukP9D4E7gxPQX7YDhLawGnoi4tJvZg/J8ScOd1GaqX1SveWMOxl9QA0l1T+Ck2tMDbAKsqqa9J/AAERFv7Kyemb/s716k3vKwbKGqXdJfBHag8WHTcWjBD5j2972m6WHAe4Bf19SLWuQ9gYvxfV4N6cNoHAl5iEF4CysNXO65K1R1OY2/yMxFdfei9RMRQ4CfZOZb6+5F6xYR7wFuysznqufbAO/IzO/W25l6IyL2Bk7JzA/V3YvUKkfLlutJg10xRtPYA6uB4ayOYAeQmc8CZ9XYj9ZDZt4F7Fd3H+pedcsx/wCueFi2XAsj4irgu3iV9QGl6dytDr8BPllTO+q5zv5o9nftABERH2t6OgTYG0+LaHuZ+UpEXABMqruXduAvnHJtBbyAl9MYcDx3a8BbGBHnAhdUz0+lMWpWA0Pz+28VjXPwrq2pF/XMjRHxl8B3BvsIdc+5k9pIRGwEvJyZGRG70DgctDgz76m5NbUoIrYAzgTeVZUWAJ/LzEF5A3Opv1RHPbYAXgb+wCAeSGi4K1REjADOB95WlX4MnJ6ZS+vrSt2JiJNpjHD+HfBZ4OPAXTQOM1ySmV+ssT2paBGxPY29rM8AlwD/DBwAPAL8fWYurrE9qUcMd4WKiAXAN4HLq9JxwLGZeXB9Xak7EfEA8HYah4UWAbtm5m8jYnPgjsz0UgwDQEQMBz5B49IZwzrqmTm1yxepdhHxA2AhjfffQcClwP+lEfCOzcx31NedWhERARwLjMrMz1ZHP3bKzNtrbq3fOVq2XMMz89LMXFU95uD99trdHzPzmepiqYsz87cAmfkC8Md6W1MPXAE8SOP6aJ8BlgB31NmQWrJjZn4a+Cjwusz858x8MDO/DmxTc29qzb8Cb6FxC05oHAW5oOvFy+WAinIti4jjgG9Vz2cAy2rsR+u2WURMovFH1ybVdMcFqId1+0q1k+0y8+KIOD0zbwFuiQjDXft7GRonaEXEb9ea90oN/ajn9svMvSPiboDMfCYiNqm7qToY7sp1Io1z7s6jMUr2VuCDtXakdXkCOLea/k3TdMdzDQwvVV+fiIg/p3EZjW1r7Eet2S0i5tH4Y6pjmur5qPraUg+8FBFDqS4lVZ0iMSiDuefcFaj6z31ZZh5bdy/SYBMRR9AYwLQLjT+wtgI+k5nzun2hahURB3Y3v9oLqzYWEccCf0Xj2oRzgaOAMzPz27U2VgPDXaEi4ifA1Mz0XC1J0qAQEX9KY0BMADcO1js1eVi2XI8C/1kdWlh9fa3MPLfrl0jqrYgYRmOvwTM0Rll+glcvpfHZjgEykvpGRFyemR+gMaBp7dqgYrgr1yPVYwhrXnFdUt+4jMb5dlsAfw/8DPgajcvbzAGOqK0zaXBY43JR1SlK+9TUS608LFuYiJiTmSdU0zMzc27NLamHIuLGzDxoXTW1l4j4WWbuVd1lZGlm/knTvHszc0KN7alFEXF0Zl69rpraR0R8Cvg0sBmN225C47DsH4HZmfmpunqri9e5K0/zB8jptXWhHouIYRGxLbB9RLw+IratHiOBnevtTi34I0BmruK1N5p/uf/bUS91FgQGXTgYSDLzn4CtaQwk3Kp6bJmZ2w3GYAceli2Ru2IHrr8G/hZ4A40bzUdVf57G4T21txER8VUaP7eOaarnhvM2FxGHAYcDOzf97KAx2nlVPV2pVZn5SkTsW3cf7cLDsoWJiKeAK2l8oPxVNb1aZn60jr7Uuoj4SGaeX3cf6pmImNndfE+RaG8RMQGYCJwD/K+mWSuAmzPzmVoaU8siYi7wtcwc9BcNN9wVxg+YMkTEW4GRNO1dz8zLamtIGiQiYuPMfGndS6rdRMSDwJuBx2hcJSJo3HRkfK2N1cBwJ7WZiLgceBNwD6+eq5XudZX6XkS8DTgb2JXGH1cdAWG3OvvSukXErp3VM/Ox/u6lboY7qc1ExCJgz/TNKfW7au/P39E473X1QJjM9N7cA0RE7EDT/bgz85c1tlMLR8tK7ednwJ+scym1nYgYGhF/V3cfWi/PZeb1mflUZi7reNTdlNYtIt4dEQ8DvwBuAZYA19faVE3cc1eg6sKNH83M8+ruRT0XETfTOLH7duDFjnpmvru2ptSyiLg9M6fU3Yd6JyK+AAwFvsOa77+7amtKLYmIe4GpwA8zc1JEvBM4LjNPqrm1fme4K5QfMANXVzcw98blA0NEnAdsDFzFmrf+MxwMANUfV2vLzJza782oRyJiYWZOrkLepOryKIPyAuKGu0L5ATOwRcSOQMc1m27PzKfq7EetMxxI9YiIHwJHAv8EbA88BeybmW+ttbEaGO4K5QfMwBURxwD/DPyIxki9A4CPZ+Y1dfYlDQYRsTVwFvBnVekW4JzMfK6+rtSKiNgCWEnj9+axNO5accVgPGfScCe1meqQwsEde+siYjiNc0gG3aGFgaja6/qPwBsy87CI2BN4S2ZeXHNrakFEXEtjUFPHNUE/AEzIzPfW15XUM46WLVRE7BgRF0fE9dXzPSNi0J1UOkANWesw7DJ8rw4kc4AbaNxGDuC/adxWTgPDmzLzrMx8tHp8BvAadwNARKyIiOerx8qIeDkinq+7rzr4gVGuOfgBM1D9v4i4ISJOiIgTgO8D82vuSa3bPjO/DbwCkJmraLpemtreHyLi7R1Pqosa/6HGftSizNwyM7fKzK2AzYC/BP615rZqYbgrlx8wA1BEBPBV4P8A46vH7Mz8ZK2NqSd+HxHbAQkQEfsDnq81cHwYuCAilkTEEuBrwF/X25J6Khu+Cxxady912Gjdi2iA8gNmAMrMjIj5mTmOxnW2NPB8DJgHvCki/hMYDhxdb0tqRXWN0A9k5oSI2AogMwflYb2BKCKaz4scAkymMcBi0DHclcsPmIHrrojYNzPvqLsR9coDwIHAGBqj9h7CoyQDQma+3HFI1lA3IP1F0/QqGneomF5PK/VytGyhImJTGodh1/iAycwXu32halfd23I0jV9Mv+fVG5ePr7MvtSYi7srMvddVU3uKiAuBnYGrWfMaoe5J14Dhnrty/Vf1YfJARyEi7gL8gGlTEfHG6gbXg/IckYEuIv6ERijYLCIm0QjlAFsBm9fWmHpqGI0R6s3XBE08TaKtRcR04BPAHlVpIY3rE/4kIrYebNcpNNwVxg+YAe27wN6Z+VhEXJuZf1l3Q+qRQ4ETgBHAuU31FcCn62hIrYuIf8zMT2fmByPi4MxcUHdPak1E/A1wEo1wt7AqTwb+d0R8hcb7b1BdJ9TDsoWJiJk0PmAm8+p/cmh8wMzx0EL7ioi7M3PS2tMaWCLiLzPz2rr7UM80Hzr3MPrAEhGLgLdl5vK16tsBS4G/y8yLammuJu65K0xmzgXm+gEzIGUX0xpYvhcR7wdG0vQ7NjPPqa0jqXBrB7uqtiwiHhtswQ4MdyXzA2bgmVBdTT1oHFbvGK3XMaBiq/paUw9cR+OyQ3cCDmAaOHaIiI/ReL91TK+Wmed2/jK1gecjYkJm3ttcjIgJDNJLgBnuyuUHzACTmUPr7kEbxIjMnFZ3E+qxrwNbdjKt9vf3wLyIuJTGZx40Tk2aCRxXW1c18py7QkXEzzJzr7r7kAabiJgNnJ+Z99fdizRYRMSOwKnA2Kr0c+CCzPxNfV3Vx3BXKD9gpHpExM+BNwO/oLHX3OsUSupXhrtC+QEj1SMidu2snpmP9XcvkgYnb4lTrsNo3OXgEBq3ZDmCNW/NojYVEV9spab2VIW4Xf5/e/ceI1dZh3H8+xQVCrIlRiCogXIR8VIopUKAxsilJuAFRC6SggKRhKuioqRERf0DgT+MAeRiMCARg0irNagIYiBYIdCQQmlREQiEsGJEU4u0XMrjH+cMna3T7W7BeeeceT7JZs+8ZzrztJvO+e173gtwcH38AvmsbQxJO0+kLWKQ5QOnpXKBabS5PdoO63uK2CSSLgDOA+bXTW8GflwuUUxSryWkbu57ipg0Sf+zf3qvtmGQ2bItVV9gZlPtLXst6y4wB5bMFRtWr7J+BrCrpIe6Tm0NLC6TKjbBJ4G9gQcAbD8jKTMvB5ykPagG40+TdFTXqRGqLcli8M2n2hN4Y22tl+KuvXKBaZ6HqG6dX0TV89OxqtcCnTGwXrJtSQaQtFXpQDEh76EavrINY4ewrAJOLZIoJkTSYcDhwDslXdp1agR4pUyqslLctVcuMM1zqe19JO2ewfeNdpOkq4FtJJ0KnEK1bloMMNuLgEWS9rd9T+k8MSnPUG23+QnWrXMHVWH+xSKJCsts2ZaSdC7VhIq5wHeoLjA/sX1Z0WCxQZLupeq9OwL46frnbX++76Fik0iaSzWZScBvswl9c0jalqqnbjpjd/c5pVSmmBhJb7b9cukcgyDFXYvlAtMskt4OHApcDHxj/fP1vsExoCTtBmxve/F67XOAUduPlUkWkyHpj8DdVD1Aazvt2at78Ek6EPgmsBNVYd5ZAmyXkrlKSHHXMrnANF+vPRJj8Em6BZi//sLhkmYAF9rOUkQNIGmp7Zmlc8TkSfoT1W3Y9Qvz54qFKiRLY7TP94B/92hfWZ+Lwbda0h2SHgaQtKekr5UOFRu1fa8dYeq26f2PE5voFkmHlw4Rm2Sl7d/Y/rvt5zpfpUOVkJ67lpF0v+0PbuDcMtsz+p0pJkfSXcBXgKtt7123Za/gASfpUdvv3sC5v9rerd+ZYuIkrQJMdStvK6qdfV5m3a29kYLxYgIkXQRsBiyk+vkBYPuBYqEKyWzZ9tlmnHNT+5YiXo8tbd8nqbttKKfzN8wSSafaHjMzVtLnGDuDLwaQ7SwV1Xz71d9nd7UZOLhAlqJS3LVPLjDN9w9Ju1J9KCHpaGC0bKSYgHOAn0uax7r/a7OBt1CtOxkNIGlWj+aVwJO280vWALN9UOkMgyK3ZVtG0vbAz4GX6HGBsf23UtliYiTtAvwAOAD4F/AEMC9r3zWDpIOAzi305bZ/XzJPTE69JNEsoDN+cgbwMDANON32baWyxfgkTQMuAD5UN90FfNv2ynKpykhx11K5wDRfvfD0FNurJJ1jOxNiIv7PJC0Evm57ef34fcC3ga8CCzOTdnBJWkBViHeWjToR2Mv2URv+U+2U4i6iASQ9ZXvH0jki2q7X5KVOW5ZJGWy9fj7D+jPLmLuIZtDGnxIRb4Dlkq4EbqwfHweskLQ51ezZGFyrJc2x/Qd4bVHj1YUzFZGeu4gGSM9dRH9ImgqcAcypmxYDVwBrqGayP18qW4xP0l7A9VTjI6Eas/xZ2w+VS1VGiruIAdG1ztb/nAKm2k5Pe0RED5I2Ay62fa6kEQDbvRb0Hwq5WEQMiKyzFVGOpJtsHytpGT1+ybK9Z4FYMUG219bbbA51UdeRnruIiBh6knawPSppp17nsxTR4KvHSr4T+Bnwn0677YXFQhWSnruIiBh6tkfr72OKOElTgOOBFHeDbwvgOcbuSGGq7ciGSnruIiJi6NXjtM6k6vn5JXA7cBbwZeBB20cUjBfjkHSh7fPr47m2by+dqbQUdxERMfQkLaKaXXkPcAiwHdVkpi/YXloyW4xP0gO2Z61/PMxyWzYiIgJ2sT0DQNI1VPs572h7TdlYEZOX4i4iIqJrgeJ65uXTKewaYztJX6Lqae0cv8b2d8vEKie3ZSMiYuhJWsu6GZYCpgIv1Me2PVIqW4xP0gXjnbf9rX5lGRQp7iIiIiJaZErpABERERHxxklxFxEREdEiKe4iIiKi8STtPJG2YZDiLiIiItpgQY+2m/ueYgBkKZSIiIhoLEl7AO8Hpkk6quvUCNWWZEMnxV1EREQ02XuAjwHbAB/val8FnFokUWFZCiUiIiIaT9L+tu8pnWMQpLiLiIiIxpO0LVVP3XS67kzaPqVUplJyWzYiIiLaYBFwN/A7YG3hLEWl5y4iIiIaT9JS2zNL5xgEWQolIiIi2uAWSYeXDjEI0nMXERERjSVpFWBAwFbAi8DL9WPbHikYr4gUdxEREREtkgkVERER0XiSZvVoXgk8afuVfucpKT13ERER0XiS7gVmAcvqphnAw8A04HTbt5XK1m+ZUBERERFt8Aywt+19bO8DzAQeB+YClxRN1mcp7iIiIqINdre9vPPA9gpgD9uPF8xURMbcRURERBssl3QlcGP9+DhghaTNqWbPDo2MuYuIiIjGkzQVOAOYUzctBq4A1gBb2n6+VLZ+S3EXERER0SK5LRsRERGNJekm28dKWka1mPEYtvcsEKuo9NxFREREY0nawfaopJ16nbf9ZL8zlZaeu4iIiGgs26P19zFFnKQpwPHA0BV3WQolIiIiGkvSiKT5ki6X9BFVzqZa4+7Y0vlKyG3ZiIiIaCxJi4B/AfcAhwDbAQK+YHtpyWylpLiLiIiIxpK0zPaM+ngzYBTY0faassnKyW3ZiIiIaLLXFii2vRZ4epgLO0jPXURERDSYpLXAfzoPganAC/WxbY+UylZKiruIiIiIFslt2YiIiIgWSXEXERER0SIp7iIiIiJaJMVdRAwNSc8Xet+TJL2jR/v3JS2VtELS6vp4qaSjS+SMiHbIhIqIGBqSnrf91gLveydwru0lGzg/HbjF9gf6GCsiWio9dxExdCR9WNJdkhZJelzSRZLmSbpP0jJJu9bPu07SVZKWSPqLpI/V7dMl3S3pgfrrgK7XPq9+jQfr1z0amA3cUPfKTd1ItuslHdn1+AZJR9S9f4sk3SnpUUkXdD3nhDr7UklX1wu5RsSQSnEXEcNqL+A04L3AicDutvcFrgHO7nredGBf4KPAVZK2AP4OzLU9CzgOuBRA0mHAEcB+tvcCLrF9M7AEmGd7pu3VG8n1v4HWSAAAAdpJREFUQ+Ck+vWmAQcAv6rP7Qt8CtgTOEbSbEnvrTMcaHsmsBaYt0n/IhHRCm8qHSAiopD7bY8CSHoMuK1uXwYc1PW8m2y/Cjwq6XFgD+AJ4HJJnWJq9/q5hwLX2n4BwPY/JxvK9l2SrpC0LVUht8D2K5IAbrf9XJ15ITAHeAXYB7i/fs5UquIzIoZUiruIGFYvdh2/2vX4VcZ+Nq4/MNnAF4FnqXr/pgBv9FZH1wMnAJ8GTt5IFgE/sj3/Dc4QEQ2V27IREeM7RtKUehzeLsCfgWnAaN2jdyLQGeN2O3CypC0BJL2tbl8FbD2J97wOOAfA9oqu9rmS3laP2zsSWAzcARwtabvOe0raafJ/zYhoi/TcRUSM7yngPmAEOM32GklXAAskfQa4lXpfS9u31rdql0h6Cfg1cD5VsXaVpNXA/hsbd2f7WUmPAL9Y79R9wALgXcCPO7NvJX0NuE3SFKpN1M8Ennz9f/WIaKIshRIRsQGSrqNaouTmPr/vllRj/2bZXlm3nQTMtn1WP7NERPPktmxExACRdCjwCHBZp7CLiJiM9NxFREREtEh67iIiIiJaJMVdRERERIukuIuIiIhokRR3ERERES2S4i4iIiKiRVLcRURERLTIfwFlYmw8eBNzWAAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}