week2-B_Labs-Exploratory Data Analysis Exploring and Preparing Data.ipynb

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  "cells": [
    {
      "cell_type": "markdown",
      "source": "<p style=\"text-align:center\">\n    <a href=\"https://skills.network/?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDS0321ENSkillsNetwork26802033-2022-01-01\" target=\"_blank\">\n    <img src=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/assets/logos/SN_web_lightmode.png\" width=\"200\" alt=\"Skills Network Logo\"  />\n    </a>\n</p>\n",
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    },
    {
      "cell_type": "markdown",
      "source": "# **SpaceX  Falcon 9 First Stage Landing Prediction**\n",
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    },
    {
      "cell_type": "markdown",
      "source": "## Assignment: Exploring and Preparing Data\n",
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    },
    {
      "cell_type": "markdown",
      "source": "Estimated time needed: **70** minutes\n",
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    },
    {
      "cell_type": "markdown",
      "source": "In this assignment, we will predict if the Falcon 9 first stage will land successfully. SpaceX advertises Falcon 9 rocket launches on its website with a cost of 62 million dollars; other providers cost upward of 165 million dollars each, much of the savings is due to the fact that SpaceX can reuse the first stage.\n\nIn this lab, you will perform Exploratory Data Analysis and Feature Engineering.\n",
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    },
    {
      "cell_type": "markdown",
      "source": "Falcon 9 first stage will land successfully\n",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "![](https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-DS0701EN-SkillsNetwork/api/Images/landing_1.gif)\n",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "Several examples of an unsuccessful landing are shown here:\n",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "![](https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-DS0701EN-SkillsNetwork/api/Images/crash.gif)\n",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "Most unsuccessful landings are planned. Space X performs a controlled landing in the oceans.\n",
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    },
    {
      "cell_type": "markdown",
      "source": "## Objectives\n\nPerform exploratory Data Analysis and Feature Engineering using `Pandas` and `Matplotlib`\n\n*   Exploratory Data Analysis\n*   Preparing Data  Feature Engineering\n",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "### Import Libraries and Define Auxiliary Functions\n",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "We will import the following libraries the lab\n",
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": "import piplite\nawait piplite.install(['numpy'])\nawait piplite.install(['pandas'])\nawait piplite.install(['seaborn'])",
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      "execution_count": 1
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    {
      "cell_type": "code",
      "source": "# pandas is a software library written for the Python programming language for data manipulation and analysis.\nimport pandas as pd\n#NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays\nimport numpy as np\n# Matplotlib is a plotting library for python and pyplot gives us a MatLab like plotting framework. We will use this in our plotter function to plot data.\nimport matplotlib.pyplot as plt\n#Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics\nimport seaborn as sns",
      "metadata": {
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      "outputs": [],
      "execution_count": 2
    },
    {
      "cell_type": "markdown",
      "source": "## Exploratory Data Analysis\n",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "First, let's read the SpaceX dataset into a Pandas dataframe and print its summary\n",
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": "from js import fetch\nimport io\n\nURL = \"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBM-DS0321EN-SkillsNetwork/datasets/dataset_part_2.csv\"\nresp = await fetch(URL)\ndataset_part_2_csv = io.BytesIO((await resp.arrayBuffer()).to_py())\ndf=pd.read_csv(dataset_part_2_csv)\ndf.head(10)",
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      "outputs": [
        {
          "execution_count": 4,
          "output_type": "execute_result",
          "data": {
            "text/plain": "   FlightNumber        Date BoosterVersion  PayloadMass Orbit    LaunchSite  \\\n0             1  2010-06-04       Falcon 9  6104.959412   LEO  CCAFS SLC 40   \n1             2  2012-05-22       Falcon 9   525.000000   LEO  CCAFS SLC 40   \n2             3  2013-03-01       Falcon 9   677.000000   ISS  CCAFS SLC 40   \n3             4  2013-09-29       Falcon 9   500.000000    PO   VAFB SLC 4E   \n4             5  2013-12-03       Falcon 9  3170.000000   GTO  CCAFS SLC 40   \n5             6  2014-01-06       Falcon 9  3325.000000   GTO  CCAFS SLC 40   \n6             7  2014-04-18       Falcon 9  2296.000000   ISS  CCAFS SLC 40   \n7             8  2014-07-14       Falcon 9  1316.000000   LEO  CCAFS SLC 40   \n8             9  2014-08-05       Falcon 9  4535.000000   GTO  CCAFS SLC 40   \n9            10  2014-09-07       Falcon 9  4428.000000   GTO  CCAFS SLC 40   \n\n       Outcome  Flights  GridFins  Reused   Legs LandingPad  Block  \\\n0    None None        1     False   False  False        NaN    1.0   \n1    None None        1     False   False  False        NaN    1.0   \n2    None None        1     False   False  False        NaN    1.0   \n3  False Ocean        1     False   False  False        NaN    1.0   \n4    None None        1     False   False  False        NaN    1.0   \n5    None None        1     False   False  False        NaN    1.0   \n6   True Ocean        1     False   False   True        NaN    1.0   \n7   True Ocean        1     False   False   True        NaN    1.0   \n8    None None        1     False   False  False        NaN    1.0   \n9    None None        1     False   False  False        NaN    1.0   \n\n   ReusedCount Serial   Longitude   Latitude  Class  \n0            0  B0003  -80.577366  28.561857      0  \n1            0  B0005  -80.577366  28.561857      0  \n2            0  B0007  -80.577366  28.561857      0  \n3            0  B1003 -120.610829  34.632093      0  \n4            0  B1004  -80.577366  28.561857      0  \n5            0  B1005  -80.577366  28.561857      0  \n6            0  B1006  -80.577366  28.561857      1  \n7            0  B1007  -80.577366  28.561857      1  \n8            0  B1008  -80.577366  28.561857      0  \n9            0  B1011  -80.577366  28.561857      0  ",
            "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>FlightNumber</th>\n      <th>Date</th>\n      <th>BoosterVersion</th>\n      <th>PayloadMass</th>\n      <th>Orbit</th>\n      <th>LaunchSite</th>\n      <th>Outcome</th>\n      <th>Flights</th>\n      <th>GridFins</th>\n      <th>Reused</th>\n      <th>Legs</th>\n      <th>LandingPad</th>\n      <th>Block</th>\n      <th>ReusedCount</th>\n      <th>Serial</th>\n      <th>Longitude</th>\n      <th>Latitude</th>\n      <th>Class</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1</td>\n      <td>2010-06-04</td>\n      <td>Falcon 9</td>\n      <td>6104.959412</td>\n      <td>LEO</td>\n      <td>CCAFS SLC 40</td>\n      <td>None None</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>NaN</td>\n      <td>1.0</td>\n      <td>0</td>\n      <td>B0003</td>\n      <td>-80.577366</td>\n      <td>28.561857</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2</td>\n      <td>2012-05-22</td>\n      <td>Falcon 9</td>\n      <td>525.000000</td>\n      <td>LEO</td>\n      <td>CCAFS SLC 40</td>\n      <td>None None</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>NaN</td>\n      <td>1.0</td>\n      <td>0</td>\n      <td>B0005</td>\n      <td>-80.577366</td>\n      <td>28.561857</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>3</td>\n      <td>2013-03-01</td>\n      <td>Falcon 9</td>\n      <td>677.000000</td>\n      <td>ISS</td>\n      <td>CCAFS SLC 40</td>\n      <td>None None</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>NaN</td>\n      <td>1.0</td>\n      <td>0</td>\n      <td>B0007</td>\n      <td>-80.577366</td>\n      <td>28.561857</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>4</td>\n      <td>2013-09-29</td>\n      <td>Falcon 9</td>\n      <td>500.000000</td>\n      <td>PO</td>\n      <td>VAFB SLC 4E</td>\n      <td>False Ocean</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>NaN</td>\n      <td>1.0</td>\n      <td>0</td>\n      <td>B1003</td>\n      <td>-120.610829</td>\n      <td>34.632093</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>5</td>\n      <td>2013-12-03</td>\n      <td>Falcon 9</td>\n      <td>3170.000000</td>\n      <td>GTO</td>\n      <td>CCAFS SLC 40</td>\n      <td>None None</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>NaN</td>\n      <td>1.0</td>\n      <td>0</td>\n      <td>B1004</td>\n      <td>-80.577366</td>\n      <td>28.561857</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>6</td>\n      <td>2014-01-06</td>\n      <td>Falcon 9</td>\n      <td>3325.000000</td>\n      <td>GTO</td>\n      <td>CCAFS SLC 40</td>\n      <td>None None</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>NaN</td>\n      <td>1.0</td>\n      <td>0</td>\n      <td>B1005</td>\n      <td>-80.577366</td>\n      <td>28.561857</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>7</td>\n      <td>2014-04-18</td>\n      <td>Falcon 9</td>\n      <td>2296.000000</td>\n      <td>ISS</td>\n      <td>CCAFS SLC 40</td>\n      <td>True Ocean</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>NaN</td>\n      <td>1.0</td>\n      <td>0</td>\n      <td>B1006</td>\n      <td>-80.577366</td>\n      <td>28.561857</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>8</td>\n      <td>2014-07-14</td>\n      <td>Falcon 9</td>\n      <td>1316.000000</td>\n      <td>LEO</td>\n      <td>CCAFS SLC 40</td>\n      <td>True Ocean</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>NaN</td>\n      <td>1.0</td>\n      <td>0</td>\n      <td>B1007</td>\n      <td>-80.577366</td>\n      <td>28.561857</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>9</td>\n      <td>2014-08-05</td>\n      <td>Falcon 9</td>\n      <td>4535.000000</td>\n      <td>GTO</td>\n      <td>CCAFS SLC 40</td>\n      <td>None None</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>NaN</td>\n      <td>1.0</td>\n      <td>0</td>\n      <td>B1008</td>\n      <td>-80.577366</td>\n      <td>28.561857</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>10</td>\n      <td>2014-09-07</td>\n      <td>Falcon 9</td>\n      <td>4428.000000</td>\n      <td>GTO</td>\n      <td>CCAFS SLC 40</td>\n      <td>None None</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>NaN</td>\n      <td>1.0</td>\n      <td>0</td>\n      <td>B1011</td>\n      <td>-80.577366</td>\n      <td>28.561857</td>\n      <td>0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
          },
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      ],
      "execution_count": 4
    },
    {
      "cell_type": "markdown",
      "source": "First, let's try to see how the `FlightNumber` (indicating the continuous launch attempts.) and `Payload` variables would affect the launch outcome.\n\nWe can plot out the <code>FlightNumber</code> vs. <code>PayloadMass</code>and overlay the outcome of the launch. We see that as the flight number increases, the first stage is more likely to land successfully. The payload mass is also important; it seems the more massive the payload, the less likely the first stage will return.\n",
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": "sns.catplot(y=\"PayloadMass\", x=\"FlightNumber\", hue=\"Class\", data=df, aspect = 5)\nplt.xlabel(\"Flight Number\",fontsize=20)\nplt.ylabel(\"Pay load Mass (kg)\",fontsize=20)\nplt.show()",
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          "data": {
            "text/plain": "<Figure size 2558.88x500 with 1 Axes>",
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          },
          "metadata": {}
        }
      ],
      "execution_count": 6
    },
    {
      "cell_type": "markdown",
      "source": "We see that different launch sites have different success rates.  <code>CCAFS LC-40</code>, has a success rate of 60 %, while  <code>KSC LC-39A</code> and <code>VAFB SLC 4E</code> has a success rate of 77%.\n",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "Next, let's drill down to each site visualize its detailed launch records.\n",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "### TASK 1: Visualize the relationship between Flight Number and Launch Site\n",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "Use the function <code>catplot</code> to plot <code>FlightNumber</code> vs <code>LaunchSite</code>, set the  parameter <code>x</code>  parameter to <code>FlightNumber</code>,set the  <code>y</code> to <code>Launch Site</code> and set the parameter <code>hue</code> to <code>'class'</code>\n",
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": "# Plot a scatter point chart with x axis to be Flight Number and y axis to be the launch site, and hue to be the class value\nsns.set_theme(color_codes=True)\nplt.figure(figsize=(14,8))\nsns.scatterplot(x=\"FlightNumber\", y=\"LaunchSite\", hue=\"Class\", data = df)\nplt.xlabel(\"Flight Number\",fontsize=20)\nplt.ylabel(\"Launch Site\",fontsize=20)\nplt.show()",
      "metadata": {
        "trusted": true
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 1400x800 with 1 Axes>",
            "image/png": 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"
          },
          "metadata": {}
        }
      ],
      "execution_count": 7
    },
    {
      "cell_type": "markdown",
      "source": "Now try to explain the patterns you found in the Flight Number vs. Launch Site scatter point plots.\n",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "### TASK 2: Visualize the relationship between Payload and Launch Site\n",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "We also want to observe if there is any relationship between launch sites and their payload mass.\n",
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": "# Plot a scatter point chart with x axis to be Pay Load Mass (kg) and y axis to be the launch site, and hue to be the class value\nsns.scatterplot(x=\"PayloadMass\", y=\"LaunchSite\", data=df, alpha=0.5, hue=\"Class\", s=80)\nplt.xlabel(\"PayloadMass\",fontsize=10)\nplt.ylabel(\"LaunchSite\",fontsize=10)\nplt.show()",
      "metadata": {
        "trusted": true
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 640x480 with 1 Axes>",
            "image/png": 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"
          },
          "metadata": {}
        }
      ],
      "execution_count": 10
    },
    {
      "cell_type": "markdown",
      "source": "Now if you observe Payload Vs. Launch Site scatter point chart you will find for the VAFB-SLC  launchsite there are no  rockets  launched for  heavypayload mass(greater than 10000).\n",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "### TASK  3: Visualize the relationship between success rate of each orbit type\n",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "Next, we want to visually check if there are any relationship between success rate and orbit type.\n",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "Let's create a `bar chart` for the sucess rate of each orbit\n",
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": "# HINT use groupby method on Orbit column and get the mean of Class column\n# Via Matplotlib\nxh = df.groupby('Orbit')['Class'].mean()\nax = xh.plot(kind='bar', figsize=(8, 7), color='#86bf91', zorder=2, width=0.8)\nax.set_xlabel(\"Orbit\", labelpad=20, weight='bold', size=12)\nax.set_ylabel(\"Sucess rate of each orbit\", labelpad=20, weight='bold', size=12);",
      "metadata": {
        "trusted": true
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 800x700 with 1 Axes>",
            "image/png": 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"
          },
          "metadata": {}
        }
      ],
      "execution_count": 13
    },
    {
      "cell_type": "markdown",
      "source": "##### Via Seaborn",
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": "df.groupby(['Orbit']).mean().head(12).sort_values(['Class'],ascending=False)\n",
      "metadata": {
        "trusted": true
      },
      "outputs": [
        {
          "name": "stderr",
          "text": "<ipython-input-14-21d0593fb5c3>:1: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n  df.groupby(['Orbit']).mean().head(12).sort_values(['Class'],ascending=False)\n",
          "output_type": "stream"
        },
        {
          "execution_count": 14,
          "output_type": "execute_result",
          "data": {
            "text/plain": "       FlightNumber   PayloadMass   Flights  GridFins    Reused      Legs  \\\nOrbit                                                                       \nES-L1     13.000000    570.000000  1.000000  1.000000  0.000000  1.000000   \nGEO       83.000000   6104.959412  2.000000  1.000000  1.000000  1.000000   \nHEO       49.000000    350.000000  1.000000  1.000000  0.000000  1.000000   \nSSO       60.800000   2060.000000  2.400000  1.000000  0.800000  1.000000   \nVLEO      78.928571  15315.714286  3.928571  1.000000  1.000000  1.000000   \nLEO       20.000000   3882.839748  1.000000  0.571429  0.000000  0.714286   \nMEO       77.666667   3987.000000  1.000000  0.666667  0.000000  0.666667   \nPO        36.333333   7583.666667  1.333333  0.888889  0.333333  0.777778   \nISS       39.142857   3279.938095  1.238095  0.809524  0.238095  0.857143   \nGTO       35.037037   5011.994444  1.407407  0.629630  0.333333  0.629630   \nSO        73.000000   6104.959412  4.000000  0.000000  1.000000  0.000000   \n\n          Block  ReusedCount   Longitude   Latitude     Class  \nOrbit                                                          \nES-L1  1.000000     0.000000  -80.577366  28.561857  1.000000  \nGEO    5.000000     2.000000  -80.577366  28.561857  1.000000  \nHEO    4.000000     1.000000  -80.577366  28.561857  1.000000  \nSSO    4.600000     3.200000 -112.604136  33.418046  1.000000  \nVLEO   5.000000     3.928571  -80.586862  28.578358  0.857143  \nLEO    2.142857     0.428571  -80.584963  28.575058  0.714286  \nMEO    5.000000     0.666667  -80.577366  28.561857  0.666667  \nPO     3.222222     1.555556 -120.610829  34.632093  0.666667  \nISS    3.142857     1.285714  -80.583697  28.572857  0.619048  \nGTO    3.037037     0.962963  -80.586229  28.577258  0.518519  \nSO     5.000000     3.000000  -80.603956  28.608058  0.000000  ",
            "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>FlightNumber</th>\n      <th>PayloadMass</th>\n      <th>Flights</th>\n      <th>GridFins</th>\n      <th>Reused</th>\n      <th>Legs</th>\n      <th>Block</th>\n      <th>ReusedCount</th>\n      <th>Longitude</th>\n      <th>Latitude</th>\n      <th>Class</th>\n    </tr>\n    <tr>\n      <th>Orbit</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>ES-L1</th>\n      <td>13.000000</td>\n      <td>570.000000</td>\n      <td>1.000000</td>\n      <td>1.000000</td>\n      <td>0.000000</td>\n      <td>1.000000</td>\n      <td>1.000000</td>\n      <td>0.000000</td>\n      <td>-80.577366</td>\n      <td>28.561857</td>\n      <td>1.000000</td>\n    </tr>\n    <tr>\n      <th>GEO</th>\n      <td>83.000000</td>\n      <td>6104.959412</td>\n      <td>2.000000</td>\n      <td>1.000000</td>\n      <td>1.000000</td>\n      <td>1.000000</td>\n      <td>5.000000</td>\n      <td>2.000000</td>\n      <td>-80.577366</td>\n      <td>28.561857</td>\n      <td>1.000000</td>\n    </tr>\n    <tr>\n      <th>HEO</th>\n      <td>49.000000</td>\n      <td>350.000000</td>\n      <td>1.000000</td>\n      <td>1.000000</td>\n      <td>0.000000</td>\n      <td>1.000000</td>\n      <td>4.000000</td>\n      <td>1.000000</td>\n      <td>-80.577366</td>\n      <td>28.561857</td>\n      <td>1.000000</td>\n    </tr>\n    <tr>\n      <th>SSO</th>\n      <td>60.800000</td>\n      <td>2060.000000</td>\n      <td>2.400000</td>\n      <td>1.000000</td>\n      <td>0.800000</td>\n      <td>1.000000</td>\n      <td>4.600000</td>\n      <td>3.200000</td>\n      <td>-112.604136</td>\n      <td>33.418046</td>\n      <td>1.000000</td>\n    </tr>\n    <tr>\n      <th>VLEO</th>\n      <td>78.928571</td>\n      <td>15315.714286</td>\n      <td>3.928571</td>\n      <td>1.000000</td>\n      <td>1.000000</td>\n      <td>1.000000</td>\n      <td>5.000000</td>\n      <td>3.928571</td>\n      <td>-80.586862</td>\n      <td>28.578358</td>\n      <td>0.857143</td>\n    </tr>\n    <tr>\n      <th>LEO</th>\n      <td>20.000000</td>\n      <td>3882.839748</td>\n      <td>1.000000</td>\n      <td>0.571429</td>\n      <td>0.000000</td>\n      <td>0.714286</td>\n      <td>2.142857</td>\n      <td>0.428571</td>\n      <td>-80.584963</td>\n      <td>28.575058</td>\n      <td>0.714286</td>\n    </tr>\n    <tr>\n      <th>MEO</th>\n      <td>77.666667</td>\n      <td>3987.000000</td>\n      <td>1.000000</td>\n      <td>0.666667</td>\n      <td>0.000000</td>\n      <td>0.666667</td>\n      <td>5.000000</td>\n      <td>0.666667</td>\n      <td>-80.577366</td>\n      <td>28.561857</td>\n      <td>0.666667</td>\n    </tr>\n    <tr>\n      <th>PO</th>\n      <td>36.333333</td>\n      <td>7583.666667</td>\n      <td>1.333333</td>\n      <td>0.888889</td>\n      <td>0.333333</td>\n      <td>0.777778</td>\n      <td>3.222222</td>\n      <td>1.555556</td>\n      <td>-120.610829</td>\n      <td>34.632093</td>\n      <td>0.666667</td>\n    </tr>\n    <tr>\n      <th>ISS</th>\n      <td>39.142857</td>\n      <td>3279.938095</td>\n      <td>1.238095</td>\n      <td>0.809524</td>\n      <td>0.238095</td>\n      <td>0.857143</td>\n      <td>3.142857</td>\n      <td>1.285714</td>\n      <td>-80.583697</td>\n      <td>28.572857</td>\n      <td>0.619048</td>\n    </tr>\n    <tr>\n      <th>GTO</th>\n      <td>35.037037</td>\n      <td>5011.994444</td>\n      <td>1.407407</td>\n      <td>0.629630</td>\n      <td>0.333333</td>\n      <td>0.629630</td>\n      <td>3.037037</td>\n      <td>0.962963</td>\n      <td>-80.586229</td>\n      <td>28.577258</td>\n      <td>0.518519</td>\n    </tr>\n    <tr>\n      <th>SO</th>\n      <td>73.000000</td>\n      <td>6104.959412</td>\n      <td>4.000000</td>\n      <td>0.000000</td>\n      <td>1.000000</td>\n      <td>0.000000</td>\n      <td>5.000000</td>\n      <td>3.000000</td>\n      <td>-80.603956</td>\n      <td>28.608058</td>\n      <td>0.000000</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
          },
          "metadata": {}
        }
      ],
      "execution_count": 14
    },
    {
      "cell_type": "code",
      "source": "df.groupby(['Orbit']).mean()\nsns.catplot(x=\"Orbit\",y=\"Class\", kind=\"bar\",data=df, aspect=2)\nplt.xlabel(\"Orbit\",fontsize=20)\nplt.ylabel(\"Mean\",fontsize=20)\nplt.show()",
      "metadata": {
        "trusted": true
      },
      "outputs": [
        {
          "name": "stderr",
          "text": "<ipython-input-15-655832adfcc7>:1: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n  df.groupby(['Orbit']).mean()\n",
          "output_type": "stream"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 1012.22x500 with 1 Axes>",
            "image/png": 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uU1hYkBwO33y48ff3/lATFhasSpWCfVKL0+lSUlI6H7QAoJjwnuON9x0AxYVwD5RDdrtNDodd0xcn6OiJ5BJ//uysDK/HL8z4RH7+gSVeR63qoRrWJ1p2u40PWQBQTHjP+QPvOwCKE+EeKMeOnkjWoaO/l/jzurLPeT3++ViS7H4VSrwOAEDJ4T0HAIoXN9QDAAAAAMBwhHsAAAAAAAxHuAcAAAAAwHCEewAAAAAADEe4BwAAAADAcIR7AAAAAAAMR7gHAAAAcEk2u0OSLefR/x4DKC0I9wAAAAAuyWb3U1D1RpJsCqreSDa7n69LAnABXpEAAAAACqVynbaqXKetr8sAkAeO3AMAAAAAYDjCPQAAAAAAhiPcAwAAAABgOMI9AAAAAACGI9wDAAAAAGA47pYPo9jtNtnttksvWAz8/Oy5Hl88raS4XG65XG6fPDcAAACA0odwD2PY7TaFhQXJ4fBNoPb39w7TYWHBqlQp2Ce1OJ0uJSWlE/ABAAAASCLcwyB2u00Oh13TFyfo6InkEn/+7KwMr8cvzPhEfv6BJV5HreqhGtYnWna7jXAPAAAAQJLB4f7gwYN66aWXtH37dgUHBysmJkb/93//p4CAgEuOTUlJ0ZQpU7R27VolJycrIiJCffv21UMPPVQCleNKHT2RrENHfy/x53Vln/N6/POxJNn9KpR4HQAAAABwMSPDfXJysgYMGKC6detq6tSpOn78uOLi4pSRkaGxY8cWODY9PV39+vWTw+HQmDFjdNVVV+nQoUM6c+ZMCVUPAAAAAIC1jAz3S5YsUVpamqZNm6awsDBJktPp1Pjx4zVkyBBFRETkO3bWrFlKS0vTRx99pKCgIElSmzZtSqJsAAAAAACKRbGF+zNnzujIkSNKS0uTy+W65PKtWrUq9Lo3btyoqKgoT7CXpK5du2rcuHFKSEjQPffck+/Y999/Xw8++KAn2AMAAAAAYDrLw/3SpUv1zjvvaN++fXK7C3ezL5vNpu+++67Qz5GYmKh7773Xa1pISIjCw8OVmJiY77gjR47o5MmTqlKlioYOHarNmzcrKChInTt31rPPPqvgYN/c+RwAAAAAgCthWbh3Op0aMWKE1q1bJ0mFDvZFkZKSopCQkFzTQ0NDlZyc/13Uf/vtN0nShAkT1LlzZ82ePVuHDh3S5MmTlZ6ertdff73INeX3fee++tq20qyoPaGX3q6kH/TSm8n9uHjf4+dnz3d/VJqZ/G9QHHh9W4deWof3b+vQS2vQD9/j3yA3X/bEsnC/ZMkSffbZZ5KkatWq6Z577lGTJk0UGhoqu710/KPnXB5Qr149TZgwQZIUFRUlPz8/Pffccxo1apTq1Klz2eu1222qUoWj/oUVElLR1yWUCfTROib30t/f+w+pYWHBqlSJ/ZHpTN4mSxt6aR16aR16aQ36iNLIl9ulZeH+ww8/lCRdd911WrRokUJDQ61adS4hISFKTU3NNT05ObnA582Zd/EN9Nq2bStJ2r9/f5HCvcvlVkpKep7zHA47O56LpKScldN56fswXIxeeitqHyV6ebEr6aWvpaWleT1OSkpTVpbNR9UUHdukN17f1qGX1uH92zr00homv3+XFWyTuRW0XRb3AWHLwv3Bgwdls9n02GOPFWuwl6TIyMhc19anpqbq5MmTioyMzHdcnTp1FBAQkO/8c+fO5TvvUrKz2bEUltPpol8WoI/WMbmXF9ednW3u74I/mLxNljb00jr00jr00hr0EaWRL7dLy8+Xr1evntWrzOX222/Xli1blJKS4pm2du1a2e12RUdH5zsuICBA0dHR2rp1q9f0LVu2SJKaNGlSPAUDAAAAAFCMLAv3devWlSQlJSVZtcp8xcbGKjg4WMOGDdPmzZu1bNkyTZw4UbGxsV7fcT9mzBg1btzYa+zw4cN14MABPfHEE9q8ebMWLVqkCRMm6K677tI111xT7LUDAAAAAGA1y8J9t27d5Ha7tX79eqtWma/Q0FDFx8fL4XBo2LBhmjx5su677z6NHj3aazmXyyWn0+k1rWnTpp675D/66KN6++231bt3b73yyivFXjcAAAAAAMXBsmvu+/fvr5UrV2rx4sXq1KmTWrZsadWq81S/fn3NmzevwGXi4uIUFxeXa3pUVJSWLVtWTJUBAAAAAFCyLDtyHxAQoH/9619q0qSJBg0apIkTJ+r777+/opvUAQAAAACAS7PsyH2jRo08P7vdbs2dO1dz584t1FibzabvvvvOqlIAAAAAAChXLAv3bre7wMcAAAAAAKB4WBbuhw8fbtWqAAAAAADAZSDcAwAAAABgOMtuqAcAAAAAAHyDcA8AAAAAgOEI9wAAAAAAGM6ya+4v5Ha79f333+uHH37Q77//royMjEvePZ9r9gEAAAAAKBrLw/0HH3ygadOm6dixY5c1jnAPAAAAAEDRWBru//GPf2jWrFmF+o57m81WqOUAAAAAAEDBLLvm/ttvv9XMmTMlSdHR0frwww/1wQcfSDof5L///ntt3bpVs2fPVocOHeR2u3XLLbdo8+bN+uGHH6wqAwAAAACAcseycL948WJJUs2aNTVz5kzdcMMN8vP748QAm82mKlWqqF27dnrrrbc0duxYff3113r44YeVmZlpVRkAAAAAAJQ7loX77du3y2azqV+/fl6hPj99+/ZV586dtXfvXr3zzjtWlQEAAAAAQLljWbg/ceKEJOn666//Y+X2P1aflZWVa0xMTIzcbrfWrFljVRkAAAAAAJQ7loX77OxsSdJVV13lmRYUFOT5+fTp07nG1KhRQ5L0008/WVUGAAAAAADljmXhvmrVqpKkM2fOeKZdddVVcjgckqTExMRcY06ePClJSktLs6oMAAAAAADKHcvC/XXXXSfJO8QHBAR4pq9evTrXmBUrVkiSqlevblUZAAAAAACUO5aF+5YtW8rtduuLL77wmt6tWze53W4tW7ZMU6ZM0f79+7Vz5079/e9/15o1a2Sz2XT77bdbVQYAAAAAAOWOZeH+z3/+syRp3bp1Xqfm9+/fX7Vq1ZLL5dLbb7+tnj17qnfv3nr33XclSSEhIRoyZIhVZQAAAAAAUO5YFu6vv/56zZ8/X9OnT/fcXE+SKlasqPnz56tFixZyu91e/11//fWKj4/33FgPAAAAAABcvkt/If1laN26dZ7Ta9WqpXfeeUeJiYk6cOCAsrOzVbduXTVu3NjKpwcAAAAAoFyyNNxfSmRkpCIjI0vyKQEAAAAAKPMsOy0fAAAAAAD4RrEduf/555+1fft2/fbbbzp79qz69u2rqlWrFtfTAYDP2O022e02nzy3n5891+OLp5UUl8stl8vtk+cGAAAo7ywP93v27NErr7yib775xmv6nXfe6RXuFy1apGnTpqly5cpatWqV/P39rS4FAIqd3W5TWFiQHA7fBGp/f+8wHRYWrEqVgn1Si9PpUlJSOgEfAADABywN9+vWrdPIkSOVlZUlt/uPD3c2W+4jWjExMZo0aZKSkpK0fv16derUycpSAKBE2O02ORx2TV+coKMnkkv8+bOzMrwevzDjE/n5B5Z4HbWqh2pYn2jZ7TbCPQAAgA9YFu5PnDihv/71r8rMzNT111+vp59+WrfccotatGiR5/KVKlVShw4dtHr1am3cuJFwD8BoR08k69DR30v8eV3Z57we/3wsSXa/CiVeBwAAAHzLsvNI582bp7Nnz6pmzZpatGiR2rVrp6CgoALHtGnTRm63W3v27LGqDAAAAAAAyh3Lwv2mTZtks9n00EMPKSQkpFBjcr4W78iRI1aVAQAAAABAuWNZuD927JgkqVmzZoUeU6lSJUlSenq6VWUAAAAAAFDuWBbunU6nJMnlchV6TGpqqiRd8vR9AAAAAACQP8vCfbVq1SRJhw8fLvSYnTt3SpKuvvpqq8oAAAAAAKDcsSzct2zZUm63W2vXri3U8pmZmXr33Xdls9nUunVrq8oAAAAAAKDcsSzc9+rVS5L02WefKSEhocBlMzMz9cwzz+jnn3+WzWbTAw88YFUZAAAAAACUO5Z9z32bNm3UrVs3rV69WkOHDlX//v3VpUsXz/yjR48qJSVF33zzjZYuXarDhw/LZrMpNjZW119/vVVlAAAAAABQ7lgW7iUpLi5OaWlp2rBhg+bMmaM5c+bIZrNJkoYOHepZzu12S5I6d+6sv/3tb1aWAAAAAABAuWPZafmSFBAQoJkzZ+qFF15QnTp15Ha78/yvRo0aGjdunKZMmSKHw2FlCQAAAAAAlDuWHrnP8cADD+iBBx7QgQMHtHv3bp06dUpOp1NVqlRRo0aN1KRJE88RfQAAAAAAcGWKJdznuO6663TdddcV51MAAAAAAFDuWXpaPgAAAAAAKHlFOnL/5ZdfWl2HWrVqZfk6AQAAAAAoD4oU7vv162fpNfM2m03fffedZesDAAAAAKA8uaJr7nO+0g4AAAAAAPjOFYX7wMBAdezYUbfeeqvsdi7fBwAAAADAF4oU7oODg5WWlqaMjAytXr1a27ZtU48ePRQTE6MbbrjB6hoBAAAAAEABinS4fcuWLXr99dd1xx13yOFw6OTJk5o3b5569eqlmJgYzZ07VydOnLC6VgAAAAAAkIcihfsKFSqoW7dumjlzpjZu3Khnn31WjRo1ktvt1t69ezVx4kS1b99egwcP1r///W9lZGRYXTcAAAAAAPifK7rmXpKqVq2qAQMGaMCAATp48KA+/PBDrVy5Ur/88osSEhK0ZcsWVaxYUZ07d1ZMTIyioqKsqBsAAAAAAPyPpXfBq1+/vp544gmtW7dO8fHx6tWrl4KCgpSenq4PP/xQDz30kO644w794x//sPJpAQAAAAAo14rtFvdt2rTRq6++qi1btmjy5Mm6/fbb5XA4dPz4cc2bN6+4nhYAAAAAgHKn2L+/zmazef4DAAAAAADWu+Jr7vOzbds2rVixQp988onOnDkjSXK73QoPD1dMTExxPS0AAAAAAOWOpeH+4MGDWrFiheeGetL5QF+xYkX9+c9/1t13362oqCjZ7cV+wgAAAAAAAOXGFYf7U6dOaeXKlVqxYoW+//57SecDvd1uV5s2bRQTE6POnTsrKCjoiosFAAAAAAC5FSncnzt3Tp9++qlWrFihLVu2yOl0yu12S5Kuv/56xcTE6K677lJERISlxQIAAAAAgNyKFO6joqJ09uxZSeeP0lerVk09evRQTEyMGjVqZGmBAAAAAACgYEUK9+np6bLZbKpQoYI6dOig6OhoORwO7d27V3v37i1SIXfffXeRxgEAAAAAUN5d0TX3586d05o1a7RmzZorKsJmsxHuAQAAAAAooiKH+5xr7AEAAAAAgG8VKdzPnz/f6jpQTGx2hySbJLck2/8eoyjoJQAAAIDSqkjhvnXr1lbXgWJis/spqHojpZ/4XkHVG8lmv+JvPyy36CUAAACA0op0Ug5UrtNWleu09XUZZQK9BAAAAFAa2X1dAAAAAAAAuDKEewAAAAAADGdsuD948KAGDRqk5s2bKzo6WhMnTlRmZuZlrePTTz9Vw4YN1aNHj2KqEgAAAACA4mfkNffJyckaMGCA6tatq6lTp+r48eOKi4tTRkaGxo4dW6h1ZGRk6JVXXlG1atWKuVoAAAAAAIqXkeF+yZIlSktL07Rp0xQWFiZJcjqdGj9+vIYMGaKIiIhLrmPmzJmqWbOmateurd27dxdzxQAAAAAAFB8jT8vfuHGjoqKiPMFekrp27SqXy6WEhIRLjv/55581d+5cPffcc8VYJQAAAAAAJcPIcJ+YmKjIyEivaSEhIQoPD1diYuIlx7/88suKiYnRDTfcUFwlAgAAAABQYow8LT8lJUUhISG5poeGhio5ObnAsZ999pm2b9+utWvXWlqTn1/efydxOIz8+0mxKmpP6KW3K+kHvfRGL63D69sabJPWoZfW4fVtHXppDfrhe/wb5ObLnhgZ7ovq3LlzeuWVVzRixAhVrVrVsvXa7TZVqRJs2frKupCQir4uoUygj9ahl9ahl9agj9ahl9ahl9ahl9agjyiNfLldGhnuQ0JClJqammt6cnKyQkND8x0XHx8vu92u7t27KyUlRZKUlZUll8ullJQUBQYGKiAg4LLrcbncSklJz3Oew2Fnx3ORlJSzcjpdlz2OXnorah8lenkxemkdXt/WYJu0Dr20Dq9v69BLa1zJ6xvWYJvMraDtsrgPCBsZ7iMjI3NdW5+amqqTJ0/muhb/QomJifrpp58UFRWVa16rVq3097//XX369ClSTdnZ7FgKy+l00S8L0Efr0Evr0Etr0Efr0Evr0Evr0Etr0EeURr7cLo0M97fffrtmzJjhde392rVrZbfbFR0dne+4v/zlL+rVq5fXtFmzZunHH3/Uq6++qrp16xZn2QAAAAAAFAsj74AQGxur4OBgDRs2TJs3b9ayZcs0ceJExcbGen3H/ZgxY9S4cWPP4/r166tNmzZe/4WHhysoKEht2rTxGgsAAAAAgCmMDPehoaGKj4+Xw+HQsGHDNHnyZN13330aPXq013Iul0tOp9NHVQIAAAAAUDKMPC1fOn8Uft68eQUuExcXp7i4uEsuAwAAAACAyYw8cg8AAAAAAP5AuAcAAAAAwHCEewAAAAAADEe4BwAAAADAcIR7AAAAAAAMR7gHAAAAAMBwhHsAAAAAAAxHuAcAAAAAwHCEewAAAAAADEe4BwAAAADAcIR7AAAAAAAMR7gHAAAAAMBwhHsAAAAAAAxHuAcAAAAAwHCEewAAAAAADEe4BwAAAADAcIR7AAAAAAAMR7gHAAAAAMBwhHsAAAAAAAxHuAdQ4mx2hyRbzqP/PUZR0EsAAABIhHsAPmCz+ymoeiNJNgVVbySb3c/XJRmLXgIAAECS+BQIwCcq12mrynXa+rqMMoFeAgAAgCP3AAAAAAAYjnAPAAAAAIDhCPcAAAAAABiOcA8AAAAAgOEI9wAAAAAAGI5wDwAAAACA4Qj3AAAAAAAYjnAPAAAAAIDhCPcAAAAAABiOcA8AAAAAgOEI9wAAAAAAGI5wDwAAAACA4Qj3AAAAAAAYjnAPAAAAAIDhCPcAAAAAABiOcA8AAAAAgOEI9wAAAAAAGI5wDwAAAACA4Qj3AAAAAAAYjnAPAAAAAIDhCPcAAAAAABiOcA8AAAAAgOEI9wAAAAAAGI5wDwAAAACA4Qj3AAAAAAAYjnAPAAAAAIDhCPcAAAAAABiOcA8AAAAAgOEI9wAAAAAAGI5wDwAAAACA4Qj3AAAAAAAYjnAPAAAAAIDhCPcAAAAAABiOcA8AAAAAgOEI9wAAAAAAGI5wDwAAAACA4Qj3AAAAAAAYjnAPAAAAAIDhCPcAAAAAABiOcA8AAAAAgOEI9wAAAAAAGI5wDwAAAACA4Qj3AAAAAAAYjnAPAAAAAIDhjA33Bw8e1KBBg9S8eXNFR0dr4sSJyszMLHDMmTNnNHXqVN13331q2bKlbr31Vg0dOlR79+4toaoBAAAAALCekeE+OTlZAwYMUFZWlqZOnapRo0Zp6dKliouLK3DcsWPH9O677yo6OlpvvPGGXnzxRaWmpqp37946ePBgCVUPAAAAAIC1/HxdQFEsWbJEaWlpmjZtmsLCwiRJTqdT48eP15AhQxQREZHnuNq1a+s///mPKlas6JnWtm1bdejQQe+8846ef/75kigfAAAAAABLGXnkfuPGjYqKivIEe0nq2rWrXC6XEhIS8h0XFBTkFewlKTg4WNdcc41OnDhRXOUCAAAAAFCsjAz3iYmJioyM9JoWEhKi8PBwJSYmXta6UlJStH///lzrAwAAAADAFEaelp+SkqKQkJBc00NDQ5WcnHxZ63rttddks9nUp0+fK6rJzy/vv5M4HEb+/aRYFbUn9NLblfSDXnqjl9bh9W0Ntknr0Evr8Pq2Dr20Bv3wPf4NcvNlT4wM91ZZtmyZ50Z8NWrUKPJ67HabqlQJtrCysi0kpOKlF8Il0Ufr0Evr0Etr0Efr0Evr0Evr0Etr0EeURr7cLo0M9yEhIUpNTc01PTk5WaGhoYVax4YNGzR27Fg99thj6tWr1xXV43K5lZKSnuc8h8POjuciKSln5XS6LnscvfRW1D5K9PJi9NI6vL6twTZpHXppHV7f1qGX1riS1zeswTaZW0HbZXEfEDYy3EdGRua6tj41NVUnT54s1LXzO3bs0MiRI3X33Xdr5MiRltSUnc2OpbCcThf9sgB9tA69tA69tAZ9tA69tA69tA69tAZ9RGnky+3SyIskbr/9dm3ZskUpKSmeaWvXrpXdbld0dHSBYw8cOKAhQ4aobdu2Gj9+fHGXCgAAAABAsTMy3MfGxio4OFjDhg3T5s2btWzZMk2cOFGxsbFe33E/ZswYNW7c2PP41KlTGjx4sCpUqKABAwZo9+7d2rFjh3bs2KEDBw744lcBAAAAAOCKGXlafmhoqOLj4/Xiiy9q2LBhCg4O1n333adRo0Z5LedyueR0Oj2PDxw4oF9//VWSNHDgQK9lW7durQULFhR77QAAAAAAWM3IcC9J9evX17x58wpcJi4uTnFxcZ7Hbdq00d69e4u5MgAAAAAASpaRp+UDAAAAAIA/EO4BAAAAADAc4R4AAAAAAMMR7gEAAAAAMBzhHgAAAAAAwxHuAQAAAAAwHOEeAAAAAADDEe4BAAAAADAc4R4AAAAAAMMR7gEAAAAAMBzhHgAAAAAAwxHuAQAAAAAwHOEeAAAAAADDEe4BAAAAADAc4R4AAAAAAMMR7gEAAAAAMBzhHgAAAAAAwxHuAQAAAAAwHOEeAAAAAADDEe4BAAAAADAc4R4AAAAAAMMR7gEAAAAAMBzhHgAAAAAAwxHuAQAAAAAwHOEeAAAAAADDEe4BAAAAADAc4R4AAAAAAMMR7gEAAAAAMBzhHgAAAAAAwxHuAQAAAAAwHOEeAAAAAADDEe4BAAAAADAc4R4AAAAAAMMR7gEAAAAAMBzhHgAAAAAAwxHuAQAAAAAwHOEeAAAAAADDEe4BAAAAADAc4R4AAAAAAMMR7gEAAAAAMBzhHgAAAAAAwxHuAQAAAAAwHOEeAAAAAADDEe4BAAAAADAc4R4AAAAAAMMR7gEAAAAAMBzhHgAAAAAAwxHuAQAAAAAwHOEeAAAAAADDEe4BAAAAADAc4R4AAAAAAMMR7gEAAAAAMBzhHgAAAAAAwxHuAQAAAAAwHOEeAAAAAADDEe4BAAAAADAc4R4AAAAAAMMR7gEAAAAAMBzhHgAAAAAAwxHuAQAAAAAwHOEeAAAAAADDEe4BAAAAADAc4R4AAAAAAMMR7gEAAAAAMBzhHgAAAAAAwxkb7g8ePKhBgwapefPmio6O1sSJE5WZmVmose+99566dOmiG2+8UT179tS6deuKuVoAAAAAAIqPkeE+OTlZAwYMUFZWlqZOnapRo0Zp6dKliouLu+TYVatW6fnnn1fXrl01e/ZsNW/eXMOHD9eOHTuKv3AAAAAAAIqBn68LKIolS5YoLS1N06ZNU1hYmCTJ6XRq/PjxGjJkiCIiIvIdO2XKFHXv3l3/93//J0lq27at9u3bp+nTp2v27NklUD0AAAAAANYy8sj9xo0bFRUV5Qn2ktS1a1e5XC4lJCTkO+7w4cM6dOiQunbt6jW9W7du2rp1a6FP6wcAAAAAoDQxMtwnJiYqMjLSa1pISIjCw8OVmJhY4DhJqlevntf0+vXrKysrS4cPH7a+WAAAAAAAipmRp+WnpKQoJCQk1/TQ0FAlJyfnOy5n3sVjcx4XNLYgdrtNVasG5znPZjv//2cGd5DT6SrS+ssKh+P835JCQyvK7b788fTyvCvto0Qvc9BL6/D6tgbbpHXopXVMf3273W6dS7/T87hCUKhsOUWVMNN7WVpY8frO4aNNoVS5kh6yTf7Byu2yqIwM96WNzWaTw1HwniG0UmAJVVP62e1XdsIIvTzvSvso0csc9NI6vL6twTZpHXppHaNf32F5H4TxFaN7WYpY8fqGNdgm/+DL7dLIV0RISIhSU1NzTU9OTlZoaGi+43LmXTw2JSXFaz4AAAAAACYxMtxHRkbmurY+NTVVJ0+ezHUt/sXjJOUam5iYKH9/f9WpU8f6YgEAAAAAKGZGhvvbb79dW7Zs8Rxxl6S1a9fKbrcrOjo633F16tRR3bp1tXbtWq/pq1evVlRUlAICAoqtZgAAAAAAiouR4T42NlbBwcEaNmyYNm/erGXLlmnixImKjY31+o77MWPGqHHjxl5jR4wYoZUrV2rKlCn64osvNG7cOO3cuVOPPfZYSf8aAAAAAABYwsgb6oWGhio+Pl4vvviihg0bpuDgYN13330aNWqU13Iul0tOp9NrWo8ePXT27FnNnj1bs2bNUr169TRt2jTdfPPNJfkrAAAAAABgGZvb7asb9QMAAAAAACsYeVo+AAAAAAD4A+EeAAAAAADDEe4BAAAAADAc4R4AAAAAAMMR7gEAAAAAMBzhHgAAAAAAwxn5Pffl3dSpUzVnzhxt3749z/kNGzbMc3pAQIB27drlNW3jxo2aM2eOdu/eraysLNWrV0/33HOP+vbtKz+/8rV5XNzXX375RVOmTNEXX3yhkydPKjQ0VNddd5169eqlmJgYz7gdO3Zo2rRp+v7775Wamqpq1aqpadOmGjx4sG666SZf/To+N3XqVE2bNs3zuEqVKmrQoIEef/xxtWzZ0jP922+/1YwZM/TNN98oPT1dtWvXVvfu3fXwww8rMDDQF6X73IYNG7Rw4ULt2rVLqampCg0NVdOmTdWzZ09t3LhRK1asKHB869attWDBAklSRkaG5syZo5UrV+rw4cOqWLGiWrRooaFDh6p58+Yl8NsUr4u3sws98cQTeuSRR/T777/r7bff1vr16/XLL7+oUqVKqlu3rrp06aKBAwcWuP7Ro0dr9+7dWrlyZb7LTJ8+XV999ZXn3+v999/XjTfeeCW/Vqny0Ucfaf78+frxxx/ldrsVERGhFi1a6K9//auuuuoqSdLZs2f1r3/9S6tXr9bRo0cVGBio2rVr67bbbtOoUaO81nf8+HFNnz5dGzZs0KlTp1S1alXdfvvtGj58uGrUqOGLX7FEFPTeffE83sfzl/Oar169ujZs2CC73fs4VWxsrLZv365evXopLi5Oy5cv17PPPpvnunr37q0XXnjB87gs7y+HDh2qxMREffLJJ3nOX7BggV566SX95z//UadOnfTmm2/qzjvvzHPZ0aNH64MPPshz3uuvv67u3bt7HpfX13uOwuw/pbK97RVVQZ+FunXrJrvdzraYh7K314ckqV+/furRo4fXtIvfAOfMmaMJEyaoU6dOmjhxoipWrKiNGzdq4sSJ+vzzzzVt2rRcY8qLlJQUPfDAAwoNDdWIESNUs2ZN/frrr/r888+1adMmT7j/+uuv1b9/f7Vr107jx49XcHCwfvrpJ3366afauXNnuQ73khQYGKj4+HhJ0q+//qq33npLAwcO1PLly9WgQQOtXr1aTz31lFq0aKHx48erSpUq+uabbzRr1ixt3LhR8fHxqlixoo9/i5L1+uuva+bMmerUqZPGjh2r8PBw/fbbb/r000/11FNPady4cerbt69n+bfeekuJiYmaNGmSZ1qlSpUkSenp6Ro4cKD279+vhx9+WC1btlRSUpIWLlyovn37atKkSerWrVuJ/45Wu3A7u9DVV1+t7OxsDRgwQKmpqXrkkUcUGRmp3377Td98843WrVt3yXBfGO+++66uueYa3Xrrrfr444+veH2lyezZszV58mQNHDhQjz/+uNxut/bv369///vfOnHihOfD6eOPP66dO3dqyJAhatSokVJSUrRr1y59+umnXuH+4MGD6tevnwIDAzVs2DDVrVtXP/30k2bMmKHPPvtMCxYsUP369X3165YqvI/nz9/fX7///ru+/PJLtWnTxjP96NGj2rFjh4KCgnKN+ec//6nKlSt7TbswXJX1/WWPHj30xBNPaOfOnWrWrFmu+atWrVLz5s0Lvb3UqVPH630nx7XXXuv5uby/3gu7/yzr215RXOqzUGhoqNq1ayeJbTEXN4wzZcoUd/PmzfOd36BBA/c///nPAtexZ88ed6NGjdzPPPNMrnnvv/++u0GDBu758+dfca0mubCvS5cudTdo0MB99OjRXMs5nU7Pz0888YS7U6dO7uzs7AKXK4/y2k6PHj3qbtiwoXv8+PHuX3/91d28eXN3//79c/Vv69at7gYNGrhfffXVkizZ59atW+du0KCBe8qUKXnO//bbb9179uzxmvbMM8+4u3fvnufyr7zyirtBgwburVu3ek3Pzs529+/f3928eXP38ePHrSneRy61P0xISHA3aNDAvW3btlzzCvMaLai/F6/n888/dzdo0MC9c+fOS67XFO3atXOPHj06z3k5v/ehQ4fcDRo0cH/wwQf5LpOjV69e7qioKPfJkye9pp88edIdFRXl7tWrlzWFl0IFbasXz+N9PH85vXr00Ufdzz//vNe8mTNnunv06OHu2bOnpy/Lli1zN2jQwH3q1KkC11vW95fp6enu5s2bu19++eVc8w4fPuzZXnJ+XrNmTb7rKsx+0e0u3693t7tw+0+3u+xve5frcj4LsS3mVvb+nItCWbBggWw2m0aMGJFrXq9evVS3bt08j4SVF8nJybLb7V5/1c9x4V+1U1JSVLVqVTkcjgKXw3k1a9ZU1apVdeTIEb333ntKT0/XyJEjc/Wvbdu2uvXWW/Xuu+8qIyPDR9WWvLlz5yo8PFyPPvponvObNWumxo0bF2pdGRkZWrp0qaKjo9W2bVuveQ6HQ48//rjS09P13nvvXXHdpVlycrIkKTw8PNc8q16jZfm1npKSourVq+c5L+f3LmyPv/zyS+3Zs0f9+/dXtWrVvJarVq2a+vXrpz179uirr76yqvwyrby/j/fo0UMff/yxsrKyPNNWrlyZ62yHwigP+8uKFSuqY8eOWrNmjVwul9e8VatWyeFwWHp0mNd74faf5WHbu1xWfhaSyt+2WHY/kZRzLpdL2dnZXv9duDP/8ssv1bBhQ9WqVSvXWLvdrvbt2+vw4cM6fvx4SZZdajRp0kQul0tPPvmktm/fruzs7HyX2759u9544w0dPHiwhKs0z5kzZ5SUlKTq1avryy+/VFhYmFq0aJHnsh06dFB6err27NlTwlX6RnZ2tr755hu1bdvWkutkd+/erfT0dLVv3z7P+bfccovCwsLKzJvZxfu7nNdso0aNZLfb9dxzz2nr1q3KzMz0caVmadKkiZYsWaL33ntPJ0+ezHOZyMhIBQUFKS4uTuvWrVNaWlqey23btk2S8t0mO3ToIOn8+1NZlte2enHYkngfv5T27dsrMzNTCQkJkqQDBw5o7969+QbUvPrpdrsllZ/95V133aUTJ07oiy++8Jq+cuVK3XrrrXke0ChIfvtdide7VLj9Z3nZ9gqrqJ+F2Bb/wDX3ZdSkSZNyXX8SFRWlefPmSTp/U4n8btgjnb9WVTp/nXRERESx1VlaRUVFafDgwZo7d64++eQTBQYG6pZbblHPnj0VExMjm80mSRo8eLC+/fZbvf3223r77bcVFham2267TX369PG6aVx5lrOD/fXXXzVhwgQ5nU516dJFL7/8smc7y0vOvLL6wfRiSUlJyszMzNUTt9stp9PpeWy32wt1pDinb5fq8a+//lrEikuP9PR0NWnSJNf0RYsWqWXLlho9erRee+01DRw4UP7+/mrWrJm6du2qPn36lMkbjllp3LhxGj58uJ577jlJUu3atdW+fXsNHDhQtWvXlnT+Hg8vv/yynnvuOQ0dOlQOh0M33HCDOnXqpAEDBniuf87ZJmvWrJnnc+VMLwvbZH7y21Yl5bpOnPfxglWsWFEdOnTQqlWr9Kc//UkrV67UzTffrDp16uS5fHR0dK5pEydOVExMTLnZX0ZHR6tq1apatWqVoqKiJEn79u3Tvn37NHjw4Mta1/79+/Pcljds2KAaNWrwelfh9p/lZdsrrKJ8FmJb9ManmjKqf//+6tmzp9e0nJtsoXCefvpp9enTR//973/19ddfa+vWrUpISFBCQoJee+01Sed7OmfOHO3cuVPr16/X119/rY8//lirVq3Siy++qPvvv9/Hv4VvXfxBNjQ0VGPHjvXcBAW55fzhKMfHH3+skSNHeh4/+OCDGjt2bEmXVaoFBgZq4cKFuaZHRkZKkgYMGKBu3brps88+07Zt27R161a99NJL+uSTTxQfHy+73S6n0+k5iieJ0P8/DRo00MqVK7V161Zt3rxZX375pRYsWKDly5dr0aJFatSokSSpW7duio6O1rp16/TFF1/o888/1xtvvKGPPvpIy5Yty/MGZ+VRftvq0qVLc30jA+/jl5Zzk7iMjAytXr1a/fr1y3fZefPm5epffn8IKKv8/Px05513atWqVRo7dqwCAgK0atUqVaxYUZ06dbqsdV1zzTV6/fXXc02/3KP/ZVlh95/I7XI+C7EteuPTSxlVo0aNAr+KKSIiQr/88ku+83PmlaWvhiiKOnXqaODAgRo4cKDS0tI0cuRIffTRRxo8eLBuuOEGz3LNmjXz3H328OHD6tevnyZNmlTuw33OB1mbzaYqVaro6quv9vylNSIiQj/88EO+Y3O2wbJ4xCkvYWFhCggIyPWX46ioKL3//vuSlO/1Z3nJ6dulXueXc91aaWW32y/51XPh4eHq3bu3evfuraysLI0dO1bLly/XunXr1LFjR3Xq1ElHjx71LP/f//7Xc2SlvAsICNAdd9yhO+64Q5K0adMmDRkyRNOnT/f6GsLQ0FDdfffduvvuu+V2uzVlyhS99dZbev/999W/f3/PNnns2LE8jzgfO3ZMUtl+38lvW12/fn2uabyPX9ptt90mf39/vfnmmzpy5Ii6du2a77INGzZU1apV85xXnvaXPXr00DvvvKNNmzapY8eOWrlypTp06KDg4ODLWk+FChUuuX1K5fv1Ll16/1metr3CKMpnIbZFb1xzX061atVK+/bty3Nn4na7tWHDBtWpU6fcBKvCCA4O9nwFWWJiYr7L1alTR3feeaeSkpL022+/lVR5pVLOB9mmTZuqVq1aXqeTt2rVSklJSdqxY0eeY9evX6+goKB8T2Eta/z8/NSiRQtt3brV69Sz0NBQ3XjjjbrxxhsVEBBQ6PU1bdpUQUFBeYYGSdq+fbuSkpLK5eUj/v7+nq/Ay7lXxttvv63333/f819+N0GC1K5dO91www0F3mfEZrN5TvPNWa5169aSzp8qmZecbbVVq1YWVlt28T5+/rXcuXNnzZs3T23bts11s6zCKk/7yxYtWqhWrVpatWqVduzYoSNHjhTpJoSXwus9bxfvP8vTtlcYVn8Wksrftki4L6f69esnl8ulKVOm5Jq3YsUKJSYmWvL9z6Y6ffq01ym6OQ4dOiRJng8Q+YX3Q4cOKSAgQCEhIcVWo+nuv/9+BQUF6c0338x1M6lt27Zp8+bNio2NVWBgoI8qLHmDBg3SiRMnNGPGjCteV2BgoB544AHPqYAXynntBwUFlfmzS5KSkvK8IWbOaznnDu8NGzb0fHAoyoeHsiqvfVxGRoZ++eUXz37wzJkzeX6rxcU9btWqlZo0aaL4+HidPn3aa9nTp09r/vz5atKkSbn5EHuleB8/7/7771f79u3Vv3//Iq+jPO0vbTabevTooc8++0xLly5VWFhYsVwqx+u9cPvP8rTtFZaVn4Wk8rctclq+oZxOp9auXZtres6p4b/88kueR0QbN26sgIAANW7cWE8++aQmTJigM2fO6J577lFgYKA2b96s+Ph4dezY0XOUujz64IMPtGLFCsXExKhx48ZyuVzavn27Zs+erSZNmuiWW26RJD333HNyOp3q3Lmz6tatqzNnzujjjz/WunXrNGDAAAJCASIiIvTyyy/rySef1MCBA/Xggw+qSpUq+uabbzRr1izddNNNevzxx31dZon605/+pEceeURTpkzRDz/8oK5du6p69epKTU3VV199pZMnT17WqZMjR47U9u3b9cgjj+gvf/mLWrZsqaSkJC1atEhffvmlJk2aVCaOULtcrjz3d1dddZX27NmjSZMmqVevXmrWrJn8/Pz0/fffa+bMmapZs2ahrjM9c+ZMnvvbNm3aqEqVKtq2bZtOnz6tAwcOSJI+//xzHT16VLVq1brk5QKl3V133aX27dvrtttuU/Xq1XX8+HEtXLhQv//+uwYMGCBJ+vHHH/Xoo4+qV69euuWWWxQUFKQDBw5o9uzZqly5snr16uVZ32uvvaZ+/frpgQce0JAhQ1S3bl399NNPmjlzptxut+d+JuB9vLCaNWumt95665LL7dmzR5UrV/aaVrlyZdWvX19S+dlfSudPzZ85c6aWL1+u3r17y9/fP9cy3377ba5p1apV8wSgjIyMPLfPq6++2nO2SHl/vRdm/ymVr22vMC73sxDbojebO6/DkyjVpk6d6nWd44UmTpyop59+Ot+xOXeOvPDx3LlztWvXLmVlZalevXq699571bdv33J3Q6mpU6dqzpw52r59uw4cOKDFixdr27ZtOnbsmFwul2rWrKnOnTtr0KBBniPymzZt0ocffqhvv/1WJ0+eVGBgoK655hr17t1bvXr1yvX97eXJhf0sSM63DWzfvl3p6emqVauWevToocGDB6tixYolVG3psn79ei1atEg7d+7UmTNnFBoaqiZNmqhnz57q3r271+UNo0eP1u7du3PdjCtHRkaG5syZo5UrV+rw4cOqWLGiWrRooSFDhujmm28uqV+p2BS0P7zvvvs0fPhwLVy4UFu3btWRI0d07tw51ahRQ+3atdMjjzxyyQ9Mo0eP1gcffJDnvJy78ffr18/zVTsX6tWrl+Li4i7/lypFFi1apHXr1mnfvn06ffq0qlSpooYNG+rhhx/2fCdzSkqK4uPjlZCQoEOHDiktLU0RERFq1aqVhg4dqmuvvdZrncePH9f06dO1YcMGnTp1SlWqVNEdd9yh4cOHl5lrHvNS0D7x4nkF3QW/vL+PF+a9JSYmRo0aNVJcXJyWL1+uZ599Ns/lLvz2Aans7y8v1LNnT+3du9ezH8tx5MgRdezYMc8xOf0qaL84cuRIPfbYY57H5fX1LhVu/5mjPG17hVWYz0Jsi7kR7gEAAAAAMBzX3AMAAAAAYDjCPQAAAAAAhiPcAwAAAABgOMI9AAAAAACGI9wDAAAAAGA4wj0AAAAAAIYj3AMAAAAAYDjCPQAAAAAAhiPcAwAAy33xxRdq2LChGjZsqC+++KLI65k6dapnPQAAIH9+vi4AAAAUv9TUVH300Udav369Dh48qFOnTsnPz0/VqlVT06ZN1bFjR3Xp0kUOh8PXpQIAgCIg3AMAUMYtXbpUkydPVlJSUq55Z86c0aFDh7Ry5Updd911Gj9+vFq2bFnyRRZRv379tG3bNrVu3VoLFizwdTkAAPgM4R4AgDJswoQJmjNnjiTJz89P3bp1U4cOHVSrVi1lZmbqxx9/1MqVK/X555/rwIEDGjRokF577TXdeeedPq78vBEjRmjEiBG+LgMAgFKPcA8AQBm1aNEiT7CvUaOGZsyYoUaNGnkt07JlS91///3697//rWeffVaZmZl66qmndO211+ZaFgAAlF7cUA8AgDLo6NGjmjBhgiQpKChI8+bNKzCs33XXXXrllVckSZmZmXr66afldrtLpFYAAHDlCPcAAJRB8fHxOnfunCTpscceU7169S45pmfPnmrXrp0kad++fVq3bp3X/H79+qlhw4bq16+fJOnQoUN64YUX1LlzZ910001q2LChjhw5kue6XS6Xli5dqtjYWLVu3VrNmzdXz549NXPmTE+decnvbvmjR49Ww4YNtW3bNknStm3bPMvl/NehQ4dL/s4AAJQVnJYPAEAZ43a7tWLFCklSYGCgYmNjCz12wIAB2rRpkyRp+fLl+QbkTz/9VE899ZTS09Mvuc6srCw98sgjnvXm2Lt3r/bu3auPPvpI8+bNU3h4eKHrBAAA3gj3AACUMfv37/fcGb9ly5aqXLlyocfeeuutCgwMVEZGhr7++us8lzl27JieeuopBQYG6tFHH1XLli3lcDi0a9cuBQUF5Vr+jTfe0K5du3TbbbepT58+qlGjhn799Ve98847SkhI0IEDBzR06FAtXbq00F/FN2rUKD300EN69tlntXv3bjVt2lSvvvqq1zL+/v6F/r0BADAd4R4AgDLmhx9+8PzcuHHjyxrrcDh0ww03aMeOHTp9+rSOHz+uiIgIr2WOHDmi6tWr691331XNmjU902+66aY817lr1y717t1bL7zwgmda06ZN9ec//1l/+9vf9P7772v37t1asmSJHnzwwULVGRERoYiICM8fE4KCgtSgQYPL+l0BAChLuOYeAIAy5vfff/f8XK1atcsef9VVV3l+zjkD4GJPPPGEV7AvSLVq1fTss8/mOW/MmDGqWrWqJGnx4sWXVygAAPAg3AMAUMakpaV5fs7rNPlLuXDMmTNncs339/dX165dC72+rl27qmLFinnOCw4O9qxr//79Onny5GVWCwAAJMI9AABlTnBwsOfnwtzw7mIXjqlUqVKu+XXr1lWFChUKvb6mTZsWOL9Zs2aen/ft21fo9QIAgD8Q7gEAKGOqVKni+fm333677PGnTp3y/BwWFpZrfkhIyGWt78LT/C81Pzk5+bLWDQAAziPcAwBQxlz4nfDffffdZY11Op3au3evJKlq1aq5bqYnqdB3tM9hs9kua3kAAHD5CPcAAJQxDRo08Bxx/+qrr5SamlrosVu2bNHZs2clnf8aPStc6uyBC88UCA0NteQ5AQAobwj3AACUMTabTTExMZKkjIwMLV26tNBjFy5c6Pm5V69eltSze/fuAufv2rXL8/P1119vyXMCAFDeEO4BACiD+vfvr4CAAEnStGnT9NNPP11yzKpVq7R+/XpJ54/+t2/f3pJa1q5dq4yMjDznpaena82aNZKk6667TtWrV7+sdefc2C8zM/PKigQAwHCEewAAyqDatWvr6aeflnQ+QA8cOFA//PBDvsuvXr1azzzzjKTzX3U3ceJEy66VP3nypOLi4vKcFxcX5zktv0+fPpe97vDwcEnS4cOH5Xa7i14kAACG8/N1AQAAoHj069dPP//8s+bPn69jx47p3nvvVffu3dWhQwfVrFlT2dnZSkxM1MqVK7V161ZJUkBAgF577TU1atTIsjqaNm2qxYsX68iRI4qNjdXVV1+tX375RYsXL9bmzZslSY0bN1ZsbOxlr7tFixZavny5Tp06pVdffVU9e/ZU5cqVJUl+fn6qVauWZb8HAAClGeEeAIAy7G9/+5siIyP1xhtvKCkpSStWrNCKFSvyXLZ+/fp64YUXLLuRXo5Ro0Zp7ty52rRpkzZt2pRrfmRkpGbMmCE/v8v/WNKtWzfNnDlThw8fVnx8vOLj4z3zatWqpc8+++yKagcAwBSEewAAyrg+ffqoe/fu+uijj7R+/XodOHBAp0+flsPhULVq1XTjjTeqY8eOuvPOOy/7a+4Kw9/fX7NmzdK7776rFStWKDExUVlZWapTp466deumQYMGKTAwsEjrDg4O1pIlSzRz5kwlJCTo2LFjnrv9AwBQntjcXKAGAAAAAIDRuKEeAAAAAACGI9wDAAAAAGA4wj0AAAAAAIYj3AMAAAAAYDjCPQAAAAAAhiPcAwAAAABgOMI9AAAAAACGI9wDAAAAAGA4wj0AAAAAAIYj3AMAAAAAYDjCPQAAAAAAhiPcAwAAAABgOMI9AAAAAACGI9wDAAAAAGA4wj0AAAAAAIb7/5BcM4arHsbcAAAAAElFTkSuQmCC"
          },
          "metadata": {}
        }
      ],
      "execution_count": 15
    },
    {
      "cell_type": "markdown",
      "source": "Analyze the ploted bar chart try to find which orbits have high sucess rate.\n",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "##### Explain the patterns - which orbits have high sucess rate.\n##### ES-L1, GEO, HEO, SSO has highest Sucess rates. SO has poorest.",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "### TASK  4: Visualize the relationship between FlightNumber and Orbit type\n",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "For each orbit, we want to see if there is any relationship between FlightNumber and Orbit type.\n",
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": "# Plot a scatter point chart with x axis to be FlightNumber and y axis to be the Orbit, and hue to be the class value\nsns.scatterplot(x=\"FlightNumber\", y=\"Orbit\", data=df, alpha=0.5, hue=\"Class\", s=80)\nplt.xlabel(\"FlightNumber\",fontsize=10)\nplt.ylabel(\"Orbit\",fontsize=10)\nplt.show()",
      "metadata": {
        "trusted": true
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 640x480 with 1 Axes>",
            "image/png": 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"
          },
          "metadata": {}
        }
      ],
      "execution_count": 16
    },
    {
      "cell_type": "markdown",
      "source": "#### Another better understanding",
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": "sns.set_theme(color_codes=True)\nplt.figure(figsize=(10,6))\nsns.scatterplot(x=\"Orbit\",y=\"FlightNumber\",hue=\"Class\",data = df)\nplt.xlabel(\"Orbit\",fontsize=10)\nplt.ylabel(\"Flight Number\",fontsize=10)\nplt.show()",
      "metadata": {
        "trusted": true
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 1000x600 with 1 Axes>",
            "image/png": 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"
          },
          "metadata": {}
        }
      ],
      "execution_count": 21
    },
    {
      "cell_type": "code",
      "source": "sns.set_theme(color_codes=True)\nplt.figure(figsize=(10,6))\nsns.swarmplot(x=\"Orbit\", y=\"FlightNumber\", hue=\"Class\", data=df, dodge=False, alpha=.8, size=9)\nplt.xlabel(\"Orbit\",fontsize=10)\nplt.ylabel(\"Flight Number\",fontsize=10)\nplt.show()",
      "metadata": {
        "trusted": true,
        "scrolled": true
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 1000x600 with 1 Axes>",
            "image/png": 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"
          },
          "metadata": {}
        }
      ],
      "execution_count": 24
    },
    {
      "cell_type": "markdown",
      "source": "You should see that in the LEO orbit the Success appears related to the number of flights; on the other hand, there seems to be no relationship between flight number when in GTO orbit.\n",
      "metadata": {
        "jupyter": {
          "source_hidden": true
        }
      }
    },
    {
      "cell_type": "markdown",
      "source": "### TASK  5: Visualize the relationship between Payload and Orbit type\n",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "Similarly, we can plot the Payload vs. Orbit scatter point charts to reveal the relationship between Payload and Orbit type\n",
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": "# Plot a scatter point chart with x axis to be Payload and y axis to be the Orbit, and hue to be the class value\nsns.scatterplot(x=\"PayloadMass\", y=\"Orbit\", data=df, alpha=0.5, hue=\"Class\", s=80)\nplt.xlabel(\"PayloadMass\",fontsize=10)\nplt.ylabel(\"Orbit\",fontsize=10)\nplt.show()",
      "metadata": {
        "trusted": true
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 640x480 with 1 Axes>",
            "image/png": 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"
          },
          "metadata": {}
        }
      ],
      "execution_count": 25
    },
    {
      "cell_type": "code",
      "source": "sns.set_theme(color_codes=True)\nplt.figure(figsize=(10,6))\nsns.scatterplot(x=\"Orbit\",y=\"PayloadMass\",hue=\"Class\",data = df, alpha=.8)\nplt.xlabel(\"Orbit\",fontsize=20)\nplt.ylabel(\"PayloadMass\",fontsize=20)\nplt.show()",
      "metadata": {
        "trusted": true
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 1000x600 with 1 Axes>",
            "image/png": 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"
          },
          "metadata": {}
        }
      ],
      "execution_count": 26
    },
    {
      "cell_type": "code",
      "source": "sns.set_theme(color_codes=True)\nplt.figure(figsize=(15,6))\nsns.swarmplot(x=\"Orbit\", y=\"PayloadMass\", hue=\"Class\", data=df, dodge=True)\nplt.xlabel(\"Orbit\",fontsize=20)\nplt.ylabel(\"Payload Mass\",fontsize=20)\nplt.show()",
      "metadata": {
        "trusted": true
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 1500x600 with 1 Axes>",
            "image/png": 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"
          },
          "metadata": {}
        }
      ],
      "execution_count": 29
    },
    {
      "cell_type": "markdown",
      "source": "With heavy payloads the successful landing or positive landing rate are more for Polar,LEO and ISS.\n\nHowever for GTO we cannot distinguish this well as both positive landing rate and negative landing(unsuccessful mission) are both there here.\n",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "### TASK  6: Visualize the launch success yearly trend\n",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "You can plot a line chart with x axis to be <code>Year</code> and y axis to be average success rate, to get the average launch success trend.\n",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "The function will help you get the year from the date:\n",
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": "# A function to Extract years from the date \nyear=[]\ndef Extract_year(date):\n    for i in df[\"Date\"]:\n        year.append(i.split(\"-\")[0])\n    return year\n    \n    ",
      "metadata": {
        "trusted": true
      },
      "outputs": [],
      "execution_count": 33
    },
    {
      "cell_type": "code",
      "source": "# Plot a line chart with x axis to be the extracted year and y axis to be the success rate\ndf['year']=Extract_year(df[\"Date\"])\ndf_groupby_year=df.groupby(\"year\",as_index=False)[\"Class\"].mean()\nsns.set(rc={'figure.figsize':(12,9)})\nsns.lineplot(data=df_groupby_year, x=\"year\", y=\"Class\" )\nplt.xlabel(\"Year\",fontsize=20)\nplt.title('Space X Rocket Success Rates')\nplt.ylabel(\"Success Rate\",fontsize=20)\nplt.show()",
      "metadata": {
        "trusted": true
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 1200x900 with 1 Axes>",
            "image/png": 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"
          },
          "metadata": {}
        }
      ],
      "execution_count": 34
    },
    {
      "cell_type": "markdown",
      "source": "you can observe that the sucess rate since 2013 kept increasing till 2020\n",
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": "# Plot a line chart with x axis to be the extracted year and y axis to be the success rate\ndf1 = pd.DataFrame(Extract_year(df['Date']) , columns =['year'])\ndf1['Class']=df['Class']\ndf1.groupby('year')['Class'].mean().plot(kind='line', color=[\"pink\"], alpha=0.8)",
      "metadata": {
        "trusted": true
      },
      "outputs": [
        {
          "execution_count": 35,
          "output_type": "execute_result",
          "data": {
            "text/plain": "<AxesSubplot:xlabel='year'>"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 1200x900 with 1 Axes>",
            "image/png": 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AAJg1aarC/gNSmqpbyCssFTd/l5Z1sFnaIs3SsHlus9U79922hzJGgVEjbAMAAMwYt9GU7ftKTVPtE45/pvZ6rW2WtjSU+8SMStPV476Y1cakGjhsP/jgg7riiit05plnateuXbrpppsUhuFxr+t0OvrABz6gX/u1X9Mv//Iv6wUveIE+9rGPKYqiDRUOAACAwRlRtBqE/fk5pbY9xDs3eh3NtdIszR/efWOmOK22zG5XqWkpKJeyLgfYkIGeXWu1mi6//HKdcsop2rNnjx577DHdeOON8n1f11577TGv/Xf/7t/pr/7qr/S2t71Np556qu677z595CMfUafT0dVXX72pBwEAAIB1SFMV9i/KSBJFOU9BpTz0HxHncgrLJbmNpgr7F9V4ypOYlcRg0lS5Wk2SFFTLAx9HB4yLgcL2Zz7zGbVaLd18882am5uTJMVxrOuvv15XXXWVduzYccTrkiTRV77yFb32ta/VP/tn/0ySdN555+mhhx7Sl7/8ZcI2AADACDittpx2uz8DPbzl44/XWZiX0+rICkN59UZvGTCwTrbvywpCyTC25AMhYFQG+pjorrvu0vnnn78atCXpoosuUpIkuueee456XZqmiqJI5fLaX5ZyuayUoyEAAAC2nBHHvWO51DuvOHHdLftZqWWpszAnScotLcuIaJaG9cst9/dql8ub7pIPZGmgme29e/fqkksuWXNbpVLR9u3btXfv3qNeZ1mWXvGKV+g//+f/rGc961k69dRT9b3vfU9f+MIX9MY3vnFjlR/Ctsd7aYllmWv+BKYZ4x2zhPGOSZLbf0BmkijxXEUnzMseYFZ7I2M9ma8oabZkBYGKy8vyn7h94Joxe0w/kOP7kmEo2lbN5H0+z+0YloHCdr1eV6Vy+DKgarWqWn9fxdFcd911uu666/TKV75y9barrrpKV1xxxSAlHMY0Dc3PT8ZRAJVKPusSgJFhvGOWMN4x9mpNqd2WbFP6RyfLLW5szA481r0TpR8+JLvdVt6WVJ6M92zI0N4lyTKlharmnjCXaSk8t2Ozhth+8tje//7367/9t/+m3//939cpp5yi++67Tx/96EdVqVT0ute9bsP3mySp6vX2ECsdPssyVankVa93FMdJ1uUAW4rxjlnCeMdESBIVf/ozmXGicK6iIEyksDXQXWxmrOeKRTm1hpIHH1Hr5KfQLA1HZYRdlfYvS5Ja+YKSpcHG6bDw3I7jqVTy61r5MFDYrlQqajQah91eq9VUrVaPet2PfvQj/fEf/7H+w3/4D3ruc58rSTr77LMVRZE+/OEP67LLLlOptPGW/lE0Gb8EcZxMTK3AZjHeMUsY7xhn+f2LMrpdxbatVrUqbWKsbmSst6pVVeotGUEoa7FGszQcVX5xWWmaqlvIK7TsTY3VYeC5HZs10EaEnTt3HrY3u9FoaN++fdq5c+dRr3vggQckSc94xjPW3H766acrDEM99thjg5QBAACAdbB8X169N1HSPmFbJkcopZalzrY5SSvN0qKR14DxZ8SxvEZTkhQcYxIPmCQDPeNeeOGFuvfee1Wv11dvu/POO2Wapnbt2nXU657ylKdIkv7u7/5uze3333+/DMPQk5/85EHKAAAAwPH0z9SWUoWlkqJCdvtPw1JJsefJSBIVDixlVgfGl1erS2mq2PMU5bysywGGYqCwfdlll6lYLGr37t26++67ddttt+mmm27SZZddtuaM7WuuuUann3766t+f+cxn6pnPfKauu+46ffazn9W3v/1t3XLLLfr4xz+uSy65RPk8zQcAAACGKbdckxWG/Znl+WyLWTnXW4acVkt2p5NtPRgvSbK6AsOfq7KvH1NjoD3b1WpVt956q2644Qbt3r1bxWJRl156qa6++uo135ckieL44HmKlmXpYx/7mD784Q/rlltu0YEDB/TEJz5Rr3vd63TllVcO55EAAABAkmSGoXLLvZNi2tsWxuKs4thzFVRK8uoNFfYvqn7ikwlVkCR59YaMJFHiOOpmuAIDGDYjTdM06yI2I44TLS5m06lwvWzb1Px8UUtLLZosYOox3jFLGO8YS2mq8s8flRUE6hYKau3YvulQO6yxbsSJKo/8TEYcq7Mwr2COvbkzL01VefhnMqNI7e3bFJbLWVfEczuOa2GhuK5u5JzUDgAAMEW8ekNWECg1TbVPWBir2ePUMtVZ6C1pzy/VaJYGuc2WzChSalkKN3E6ETCOCNsAAABTwuxGyi8uS5I6C/NK7YF2DI5EWCoqyuWkNFHhwGLW5SBLabq63cGvVsbqgyFgGAjbAAAA0yBNVdh/QEoTRbmcwvKYzhIaRm/GXYacVlt2m2Zps8ppd2R2u0pNU0El++XjwLARtgEAAKaA2+x3+TYMtbdvG+tZwsR1FVR74apwYFGa7BZC2CCv1pvVDirlTM6AB7YaoxoAAGDCGXGsfP/86s78nBLHybii4+vMzym1LJnd7upSYswOy/dl+4FkGMxqY2oRtgEAACZcYf+ijCRW7LoKqpWsy1kf01R724Kk3pngZpdmabMkt1yXJIWl0lj2FgCGgbANAAAwwZxWW06rJWn8l48/XrdYUJTPSWmqPM3SZoYZhnLabUmG/LkJ+XAI2ADCNgAAwKRKktWQGlQrij0v44IGZBj92W1DTrstp9XOuiKMwMqsdreYn4gtD8BGEbYBAAAmVH5xSWYUKXEcdearWZezIckhS9/zBxalJMm4ImwlI4rkNluSJH9uMscssF6EbQAAgAlkd3x59YYkqX3Ctonu5tyZryqxbZlRpFytnnU52EK9f99UUT43eSsxgAFN7rMyAADArFo5U1tSWC719j1PMtNUZ2Fe0kqztG7GBWErGHEsr96UJPlVZrUx/QjbAAAAEya3tCyz21VqWashddL1mqXlDzZL4+ztqePVG1KaKHbdyf+ACFgHwjYAAMAEsYJwtcFU+4QFpZaVcUVDYhhqn7AgGYacdkdOu5N1RRimJFnd9uDPVSeqaz6wUYRtAACASbG6fDxVt1hQt1jMuqKhShxHPs3SppLbbMmIYyW2rW6xkHU5wEgQtgEAACaEV6vLCgKlptk/Mmv6+HOHNEtbrmVdDoYhTVf/LYNqhVltzAzCNgAAwAQwu13ll5YlSZ1t80ptO9uCtoppqtP/ICFXq8sMaZY26ZxWW2YUKbUsBeVS1uUAI0PYBgAAGHcry8fT3pFJYWm6A0u3kFe3UOg9bpqlTbZDZ7Ur5Yk+og4YFKMdAABgzLnNluyO328itm36l+Eahjrb5iXDkN3pyGm1s64IG2R3fFlhKBlmL2wDM4SwDQAAMMaMKOo1C5PUmZ9T4jgZVzQaieP0ulZLKhxYolnahMrVVma1S9PTOR9YJ8I2AADAGCscWJSRJIo9r9dcaob0mqU5MuJI+SWapU0aKwh6KzJkrHaZB2YJYRsAAGBMOa12fwn1jCwffzzDUPuEeUm9TuxmGGZcEAaxch58WCpOb0M/4BgI2wAAAGPIiJP+mdqSP1dR7LkZV5SNqFDoNUtTqsJ+mqVNCrPbXd1r788xq43ZRNgGAAAYQ/nFJRlx3Nu7PD+XdTmZ6mxb6DVL8325zVbW5WAderPaqbqFghJ3Nj8oAgjbAAAAY8bu+HIbDUmazeXjj5M4tvy5OUm9DyFoljbejCiW22xK0sz1GQAORdgGAAAYJ8nB5eNBpawon8u4oPHgz1WUOI6MOFZ+aTnrcnAMXr3eOxM+5ynKeVmXA2SGsA0AADBG8ks1md2uEttWZ2E+63LGh2GovW1BkuTVGrICmqWNpSSRV++tygiq1ZlflYHZRtgGAAAYE1YQyKv1Ojh3ti1IJm/VDhUV8uoWi5LS3tnjNEsbO169ISNJlDiOuoV81uUAmeIZHAAAYBykqQr7DkhK1S0W1S0Wsq5oLLW3zUuGSbO0cZSmytV6s9r+HLPaAGEbAABgDHi1uqwwVGpaap+wkHU5Yyu1bXXmq5IOdmzHeHCbLRlxpNSyFZaKWZcDZI6wDQAAkDGz211t+tXZNq/UsrItaMwF1Ypi15URx8rRLG08pKlyyzVJkl8tM6sNiLANAACQrZXl42mqKJ9nRnA9DKO3p12SV2/KCoKMC4LT7sjsdpWapoJKOetygLFA2AYAAMiQ22jK9n3JMDlTewBRPtf/YCJVYT/N0jJ1yKx2UCnT2A/o4zcBAAAgI0YUKb+4JEnqLMwpceyMK5osnYV5paYpKwjkNppZlzOzbD/orS4wDAXVStblAGODsA0AAJCFtDcjaySJYs9j6e0GpLYtf35OkpRfXKZZWka8Wm9WOyyV6DcAHIKwDQAAkAGn1ZbTbkuGodZ2lo9vVFAp95qlJbHyi8tZlzNzzDCU0+5IMuTPMasNHIqwDQAAMGJGHKtwYFFS7zzixHUzrmiCGcbqUWluoynLp1naKOWW65KkbrGgxHEyrgYYL4RtAACAEVs5HzpxHPlz1azLmXhxLqewVJKUqnDgAM3SRsTsRnKbLUliVhs4AsI2AADACNntTr+ZF8vHh6mzbaVZWkiztBHxanVJvSPrYs/Luhxg7BC2AQAARiVJVNh/QFJ/r3Eul3FB0yO1rEOapS3RLG2LGXEsr/+hhk8HcuCICNsAAAAjkl9alhlFSmxbnYW5rMuZOgebpSWrR6pha3j1hpQmil1XUZ4PjYAjIWwDAACMgOUH8moNSVL7hG2SyduwoTOM3v+3WmmW5mdc0JRKkl7YVq/BH1shgCPjWR4AAGCrpWl/+XiqsFRSVMhnXdHUinOewnLvzPLC/kWapW0Br9HsNfizbXWLhazLAcYWYRsAAGCL5ZZrssJQqWWps20+63KmXmdhTqlpyQrD1RlYDEma9hujMasNHA9hGwAAYAuZYajcck2S1N62oNSyMq5o+qWWtbonPre0LCOKsi1oijittswoUmpZCkvFrMsBxhphGwAAYKuk6epS5m4hz5LbEQrLJcWe12+Wtpx1OdMhTVc/OAoqZfoOAMfBbwgAAMAW8eoN2b6v1DR7jbtYcjs6hqH2CQuSDLnNpuwOzdI2y+74ssJQMsxe2AZwTIRtAACALWBEkXJLy5Ikf35OqW1nW9AMij1PQaUkScofoFnaZh2c1S6xHQJYB8I2AADAsPW7jxtJoiiXYxYwQ/78nFKr3yyt39gLg7P8QLbvSzLkVytZlwNMBMI2AADAkDmttpx25+C5zywfz0yvWVqvA3x+qUaztA3K1Xqz2mGpyCoNYJ0I2wAAAENkxLEKBxYl9Y5GSlwn44oQloqKcp6UJiocWMq6nIljhl05rY4kyZ9jVhtYL8I2AADAEOUPLMmIY8Wu2zuHGNkzDHW2bZNkyGm1ZHc6WVc0UXK1uqRU3UJBietmXQ4wMQjbAAAAQ2K3O3KbTUksHx83seeu7p1fOY4Nx2dEUX9MM6sNDIqwDQAAMAxJosL+A5KkoFpWnPMyLgiP11noNUszu12apa2TV29Iaaoo5ynO5bIuB5gohG0AAIAhyC8uy4wiJbatzvxc1uXgSEzzkGZpyzRLO54k6YVtSUGVLRHAoAjbAAAAm2T5/mooaW/fJpm8xRpXvWZpud7xbP1Gdjgyr96QkSSKXVfdQj7rcoCJwysBAADAZqSpivsOSEoVlkuK8oSSsWYYap+woF6ztLbsNs3SjihN+43RpKBaof8AsAGEbQAAgE3ILddkdrtrznPGeEtcV0G13yztAM3SjsRtNGXEsRLbVlgqZl0OMJEI2wAAABtkhqFyyzVJUnvbglLLyrgirFdnfk6pZcvsdlf/DdHHrDYwFIRtAACAjVhZPp72zh/uFgtZV4RBmKba23orEVZWJ6DHabd7qzVMU0G5lHU5wMQibAMAAGyAV2/ICgKlptnbA8zs38TpFgu9PfZpqvyBpazLGQ9pqtxyf1a7UqbZH7AJ/PYAAAAMyOxGyi8uS5I6C/NKbTvbgrAxhqH2tt4HJU67LafVzrqizNl+ICsIJMPoLSEHsGGEbQAAgEGkqQr7D0hpoiiXU8gy24mWuI78fqjMH1iUkiTjirLl1Xr714NyiR4EwCYRtgEAAAbgNluyO53erOj2bSwfnwL+XFWJbcuMoplulmYFoZx2RxKz2sAwELYBAADWyYjj1b29nfk5JY6TcUUYCtNUZ6VZWq0+s83SVma1u8UCYxsYAsI2AADAOhX2L8pIYsWuy8zflOkWCuoW8v1tArN39rbZjeQ2e3vW/TnGNjAMhG0AAIB1cFptOa2WJJaPTyXDUKffLM3udOS0Z6tZmlerS0oV5fOKPS/rcoCpQNgGAAA4niTpNc+SFFQrhJEplTiO/GpVknrbBWakWZoRx/IaDUnMagPDRNgGAAA4jvzikswoUuI46sxXsy4HW8ifq8xcszSv3pDSVLHnKsrlsi4HmBqEbQAAgGOwO34vjEhqn7BNMnn7NNVMs7ecXFJuuS4zDDMuaIslibxaf1a7WmV7BDBEvFoAAAAczcqZ2pLCcllRnlm/WdAtFtQtFCSlKhyY7mZpXqMpI4mVOI66xULW5QBThbANAABwFLmlZZndrlLLUmdhPutyMEIHm6X5clpT2iwtTfuN0SS/WmFWGxgywjYAAMARWEGo3HIviLRP2KbU4m3TLEkcW/5cb39+4cDiVDZLc5stmVGk1LIUlopZlwNMHV41AAAAHm91+XjaW1LM8tqZ5M9VlTiOjDhWfmk563KG65BZ7aBSoRcBsAX4rQIAAHgcr1aXFQRKTVPtbduyLgdZMQy1+83SvFpjqpql2Z2OrDBUapoKKqWsywGmEmEbAADgEGa3uzqL2dm2oNS2si0ImYoK+f7KhlSF/dPTLG1li0RYLim1GOPAViBsAwAArFhZPp6mivJ59rFCknqz24Yp2/flNltZl7Nplh/I9n3JMHqN0QBsCcI2AABAn9tsyu70Qkj7hAW6M0OSlNq2OvO9Zmn5xSUZ8WQ3S8st1yRJYamo1LYzrgaYXoRtAAAASUYUKX9gSZLUmZ9T4jgZV4RxElQrq83SchPcLM0Mu3LaHUliVhvYYoRtAAAA9Y53MpJEsecpIITg8VZWO0jy6g1ZwWQ2S8vVapJSdQsFJa6bdTnAVCNsAwCAmee0WnJabUmG2idsY/k4jijK59UtFiWlyh84MHHN0owoWt1z7s/xgRKw1QjbAABgphlx0usyrV4AiT1m+3B07W3zSk1Tth9MXLO0XK3Ra/6XyynO5bIuB5h6hG0AADDTeg2vYiWOI39+LutyMOZS25Y/d2iztDjjitbHiBO5jYYksU0CGBHCNgAAmFl2x18NICwfx3oF1Ypi152oZmluo9HrSeC66hbyWZcDzATCNgAAmE1J0jtTW1JQKSvKs6wW62QY6mxbaZbWlBUEGRd0HGmqXK0uqT+rzYdKwEgQtgEAwEzKL9VkdrtKbFudhfmsy8GEifI5haWSpLS353+Mm6W5jWZvq4RtKywVsy4HmBmEbQAAMHOsIJDXn+nrbFuQTN4SYXCdhV6zNCsI5DaaWZdzZMxqA5nhlQUAAMyWNFVh3wFJqbrForrFQtYVYUKltrXaVC+/uDyWzdKcVltmt6vUtBSUS1mXA8wUwjYAAJgpXq0uKwyVmpbaJyxkXQ4mXFAp95qlJbHyi0tZl7PWobPalTIrOIAR4zcOAADMDDPsKt/vHt3ZNq/UsrItCJPPMFY/tHEbTVn++DRLs32/17zNMBRUy1mXA8wcwjYAAJgNadrrPp6mivJ5GkVhaOJcTmF/ifbKGBsHueX+rHa5xAdLQAYI2wAAYCa4jaZs35cMkzO1MXSrzdLCUF69kXU5soJQdqcjyeg1RgMwcoRtAAAw9YwoWt1P21mYU+LYGVeEaZNa1uoRcrml7Jul5ZZrkqRusaDEcTKtBZhVhG0AADDd0t45yEaSKPa8XqMoYAuE5ZJiz5ORJMofyK5ZmtmN5LTakiR/rppZHcCsI2wDAICp5rTactptyTDU2s7ycWwhw1B724IkQ26zKbvjZ1KGV6tJ6vUmiD03kxoAELYBAMAUM+JYhQOLknozfIlL8MDWinPearO0/IHFkTdLM+JYXqMpSfLn2KsNZImwDQAAplb+wJKMOFbsuiynxch0FuaUmlYmzdK8WkNKU8WepyiXG+nPBrAWYRsAAEwlu92R22xK6p+DzPJxjEivWdqcpH6ztCgazQ9OktVw71crjHkgY4RtAAAwfZKkd96xpKBSVswMH0ZsTbO0xdE0S/MaTRlJrMRx1C0WRvIzARwdYRsAAEyd/NKyzChSYturM4zASBn9FRUy5DZbW98sLU3l1eqSmNUGxgVhGwAATBXLD3r7ViW1T9gmmbzdQTZ6R831mqUV9h/Y0mZpbrMlM4qUWtZqgzYA2eLVBwAATI807S8fTxWWSooK+awrwozz5+eUWpbMbnd15nnomNUGxhJhGwAATI3cck1WGPYaVG2bz7ocoN8srTcW80u1LWmW5rQ7vXFvmgrL5aHfP4CNIWwDAICpYIahcss1SVJ724JSy8q4IqAnLBV7x3CliQoHht8sbWVWOyyXlVq8vQfGBb+NAABg8q0sH09TdQsFOjFjvBiGOtt6zdKcVkt2uzO0u7Z8X7bvS4Yhv8qsNjBOCNsAAGDiefWGbD9QapqcqY2xFHuugn4YLhxYHFqztNxyf1a7VFRq20O5TwDDQdgGAAATzYgi5ZaWJUmdhXkCB8ZW55BmaSsheTPMMJTTbksy5Fermy8QwFARtgEAwOTqLx83kkRRLseRRxhvpqn2tgVJUm55WWZ3c83Scv292t1CXonrbLo8AMNF2AYAABPLbbbktDuSYfTO1Gb5OMZct1joN0tLlT+wuOH7MaJIbrMlSfLnmNUGxhFhGwAATCQjjpXvd3b25+aY2cNkMIxeXwEZctpt2e32hu4mV6tLaaool1Oc84ZbI4ChIGwDAICJlD+wJCOJFbuu/LlK1uUA65a4roJqb8wW9i9JSTLQ9UYcy200JYmxD4wxwjYAAJg4drsjt9mUZKi9neXjmDyd+aoS25YZdVf3Xq+XV2/KSBLFrqson9+iCgFsFmEbAABMliTpnaktKaiWFXssocUEMk11FuYlSbnlmsxud33XJYm8ei+cB9UKHzQBY4ywDQAAJkp+cUlmFCmxbXXm57IuB9iwbrHQm5leaZa2jrO33WZLRhwrsW2FpeIIqgSwUYRtAAAwMSw/kFfv7VVtb98mmbyVwQQzjN5RYIYhp93pddY/ljRdXXLOrDYw/niFAgAAEyO/tCwpVVgqsVcVUyFxHfn9Zmn5A4vHbJbmtNoyu12lpqWAM+WBsUfYBgAAE8EKQtmdjiRDPsvHMUX8uZVmaZFyy7Ujf1OaKlfrfS2ollnVAUwAfksBAMBE8PpBIywVlDh2xtUAQ2Sa6mxbkNQ7P/tIzdJs35cVhJJhKKiUR10hgA0gbAMAgLFndiO5zbYkKahWM64GGL5uIa9uodcsrbD/8GZpueX+Xu1ySallZVEigAERtgEAwNjrHXWUKsrnFXtu1uUAw2cYvdltw5Dd6chptVe/ZAXB6hYKPmwCJgdhGwAAjDUjjlc7kK80kgKmUeI48ud6YTq/uLTaLG1lVpstFMBkIWwDAICx5tUbUpoodl1F+VzW5QBbyq9WVpul5ZdqMrvd1VluZrWByULYBgAA4ytJemFbvY7NnCuMqWeaap/Qa5bm1eq948CUqltgCwUwaQjbAABgbLnNlow4VmLb6hYLWZcDjERUKKhbKEhK5bQ7kpjVBiYRYRsAAIynNFWu1u/AXK0wq42ZstIsTZJiz1OU8zKuCMCgCNsAAGAsOe22zG5XqWkpKJeyLgcYqcSx1d62oNS01FmY58MmYALRzhAAAIyfND14rnClLJnMD2D2hJWywko56zIAbBCvXAAAYOzYfiArCCTDUFAlbAAAJs/AYfvBBx/UFVdcoTPPPFO7du3STTfdpDAM13VtvV7X7//+7+uCCy7QGWecoec973n64z/+44GLBgAA081b2atdLim1rIyrAQBgcAMtI6/Varr88st1yimnaM+ePXrsscd04403yvd9XXvttce8tt1u61/8i38hy7J0zTXXaNu2bfrJT36iZrO5qQcAAACmixmGctptSUavMRoAABNooLD9mc98Rq1WSzfffLPm5uYkSXEc6/rrr9dVV12lHTt2HPXaj3/842q1WvriF7+oQqF3dMe555678coBAMBUWtmr3S0WlDhOxtUAALAxAy0jv+uuu3T++eevBm1Juuiii5Qkie65555jXvv5z39el1xyyWrQBgAAeDwjiuQ2W5Ikf45ZbQDA5BpoZnvv3r265JJL1txWqVS0fft27d2796jXPfLII9q3b5/m5+f1+te/XnfffbcKhYKe//zn6/d+7/dULBY3Vn2fbY93nzfLMtf8CUwzxjtmCeN9+LylpgxDivN5GcU8x6aMCcY6ZgnjHcMy0GtYvV5XpXL4p8zValW1Wu2o1+3fv1+S9L73vU/Pf/7z9YlPfEI/+clP9IEPfEDtdlt/+Id/OGDZB5mmofn5zYX1UalU8lmXAIwM4x2zhPE+JFEs/bQlWabsk58orzoZr++zhLGOWcJ4x2aN5APjJEkkSU996lP1vve9T5J0/vnny7ZtvfOd79TVV1+tk046aYP3napebw+t1q1gWaYqlbzq9Y7iOMm6HGBLMd4xSxjvw+UuLssLIyWuo1YsaamVdUnoY6xjljDecTyVSn5dKx8GCtuVSkWNRuOw22u1mqrV6lGvW/na4xuinXfeeZKkH//4xxsO25IURZPxSxDHycTUCmwW4x2zhPE+BGmq4lJNaZqqU6koilNJadZV4XEY65gljHds1kAbEXbu3HnY3uxGo6F9+/Zp586dR73upJNOkuu6R/16EASDlAEAAKaM22zKiGMltq2wxPJxAMDkGyhsX3jhhbr33ntVr9dXb7vzzjtlmqZ27dp11Otc19WuXbv07W9/e83t9957ryTpH//jfzxIGQAAYJqk6epxX0G1IhlGxgUBALB5A4Xtyy67TMViUbt379bdd9+t2267TTfddJMuu+yyNWdsX3PNNTr99NPXXPumN71JDzzwgP71v/7Xuvvuu/Wnf/qnet/73qeXvOQlOvnkk4fzaAAAwMRx2h2Z3a5S01RQLmVdDgAAQzHQnu1qtapbb71VN9xwg3bv3q1isahLL71UV1999ZrvS5JEcRyvue2Zz3ymPvGJT+j973+/3vCGN6harepVr3rVYdcCAIDZ4tX6s9qVsmRy1A4AYDoYaZpOdPeROE60uDje3Upt29T8fFFLSy2aLGDqMd4xSxjvm2f5vso/f1QyDNVOeopSm5O1xxFjHbOE8Y7jWVgorqsbOR8fAwCAzKzs1Q5LJYI2AGCqELYBAEAmzLArp92RZMivVrIuBwCAoSJsAwCATORqdUmpuoW8EtfJuhwAAIaKsA0AAEbOiCK5zaYkyZ9jVhsAMH0I2wAAYOS8ekNKU0W5nOJcLutyAAAYOsI2AAAYrSTphW1JAXu1AQBTirANAABGyms0ZSSJEsdRt5DPuhwAALYEYRsAAIxOmsqr9Y778ucqkmFkXBAAAFuDsA0AAEbGbbZkRpFSy1JYKmVdDgAAW4awDQAARuPQWe0qs9oAgOlG2AYAACNhdzqywlCpaSosl7MuBwCALUXYBgAAI5Fb7s1qh+WyUou3IACA6cYrHQAA2HKWH8j2fUmG/Cqz2gCA6UfYBgAAWy7X36sdlopKbTvjagAA2HqEbQAAsKXMbldOqy2pf9wXAAAzgLANAAC2VK8DeapuoaDEdbMuBwCAkSBsAwCALWPEsbxGU5IUVJnVBgDMDsI2AADYMl6tIaWpYs9TlPOyLgcAgJEhbAMAgK2RJPLqDUn9vdqGkXFBAACMDmEbAABsCa/RlJHEShxH3UIh63IAABgpwjYAABi+NO03RpP8KrPaAIDZQ9gGAABD57TaMqNIqWUpLBWzLgcAgJEjbAMAgOFKU+WWa5KkoFKWTN5uAABmD69+AABgqOyOLysMJcPshW0AAGYQYRsAAAxVrr9XO6iUlFpWxtUAAJANwjYAABgaKwhldzqSDAWVStblAACQGcI2AAAYGq/W26sdlgpKHDvjagAAyA5hGwAADIXZjeQ225KkoFrNuBoAALJF2AYAAEPRO1c7VZTPK/bcrMsBACBThG0AALBpRhzLazQlSf4ce7UBACBsAwCATfPqDSlNFHuuolwu63IAAMgcYRsAAGxOkvTCtiS/WpUMI+OCAADIHmEbAABsittsyYhjJbatbrGQdTkAAIwFwjYAANi4NFWuVpckBdUKs9oAAPQRtgEAwIY5rbbMblepaSkol7IuBwCAsUHYBgAAG7NmVrssmbytAABgBa+KAABgQ2w/kBUEkmEoqJSzLgcAgLFC2AYAABvi1WqSpKBcUmpZGVcDAMB4IWwDAICBmWEop92RZPQaowEAgDUI2wAAYGC55d5e7W6xoMRxMq4GAIDxQ9gGAAADMaJIbrMlSfLnmNUGAOBICNsAAGAgvQ7kqaJ8TrHnZV0OAABjibANAADWzYhjuY2mJMmvVjOuBgCA8UXYBgAA6+Y2mjKSRLHrKsrnsi4HAICxRdgGAADrk6b9JeTqdSA3jIwLAgBgfBG2AQDAuriNpow4VmLbCkvFrMsBAGCsEbYBAMDxMasNAMBACNsAAOC4nHZHZrer1DQVlEtZlwMAwNgjbAMAgOPyajVJUlApSyZvHwAAOB5eLQEAwDFZvi/bDyTDUFCpZF0OAAATgbANAACOKbfc26sdlkpKbSvjagAAmAyEbQAAcFRmGMpptyUZ8qvMagMAsF6EbQAAcFQrHci7xbwS18m4GgAAJgdhGwAAHJERRXKbLUmSX61mXA0AAJOFsA0AAI7IqzekNFWUyynOeVmXAwDARCFsAwCAwyVJL2xLCtirDQDAwAjbAADgMF69ISNJlDiOuoV81uUAADBxCNsAAGCtNF2d1fbnqpJhZFwQAACTh7ANAADWcJstmVGk1LIVlopZlwMAwEQibAMAgIPSVF7/uC+/WmZWGwCADSJsAwCAVXanIysMlZqmgko563IAAJhYhG0AALAqt9yb1Q7LZcnkbQIAABvFqygAAJAkWX4g2/clw+gtIQcAABtG2AYAAJKkXK0mSQpLRaW2nXE1AABMNsI2AACQ2e3KaXUkSX61knE1AABMPsI2AADo79VO1S0UlLhu1uUAADDxCNsAAMw4I47lNpuSpIBZbQAAhoKwDQDAjPNqdSlNFXueopyXdTkAAEwFwjYAALMsSeTVe7Pa/lxFMoyMCwIAYDoQtgEAmGFeoykjiZU4jrqFQtblAAAwNQjbAADMqjTtLSFXvwM5s9oAAAwNYRsAgBnlNlsyo0ipZSksl7IuBwCAqULYBgBgFh0yqx1UmNUGAGDYCNsAAMwgu+PLCkPJMBVUmNUGAGDYCNsAAMyg3OqsdkmpZWVcDQAA04ewDQDAjLGCQHanI8noNUYDAABDR9gGAGDG5JZ7s9phqajUtjOuBgCA6UTYBgBghpjdSE6rLUkKmNUGAGDLELYBAJghXq0mKVWUzyv23KzLAQBgahG2AQCYEUYcy2s0JUn+HLPaAABsJcI2AAAzwqs3pDRV7HmKcrmsywEAYKoRtgEAmAVJIq/WkKReB3LDyLggAACmG2EbAIAZ4DZbMpJYiW2rWyxkXQ4AAFOPsA0AwLRL09XjvgJmtQEAGAnCNgAAU85ptWVGXaWmpaBcyrocAABmAmEbAIBplqbK1VZmtcuSyUs/AACjwCsuAABTzPZ9WUEgGYaCSjnrcgAAmBmEbQAAppi3MqtdLim1rIyrAQBgdhC2AQCYUlYQyml3JBm9xmgAAGBkCNsAAEyplVntbrGgxHEyrgYAgNlC2AYAYAoZUSS32ZIk+XPMagMAMGqEbQAAplCvA3mqKJ9X7HlZlwMAwMwhbAMAMGWMOJZXb0qSfPZqAwCQCcI2AABTxqs3pTRR7LqK8rmsywEAYCYRtgEAmCZpKq/eP+6rWpEMI+OCAACYTYRtAACmiNtoyohjJbatsFTMuhwAAGYWYRsAgGmRpv3GaMxqAwCQNcI2AABTwml3ZHa7Sk1LQbmUdTkAAMw0wjYAANMgTZVbrkmSgkpJMnmJBwAgS7wSAwAwBWw/kBUEkmH0lpADAIBMEbYBAJgCXn+vdlgqKbWsjKsBAACEbQAAJpwZhnLabUmG/DlmtQEAGAeEbQAAJtxKB/JuMa/EcTKuBgAASIRtAAAmmhFFcpstSZJfrWZcDQAAWEHYBgBgguVqDSlNFeVyinNe1uUAAIA+wjYAAJMqSeQ2GpLEXm0AAMYMYRsAgAnl1RsykkSx6yrK57MuBwAAHIKwDQDAJErT3hJyqXeutmFkXBAAADgUYRsAgAnkNlsy4kipZSssFbMuBwAAPA5hGwCASZOmyi3XJEl+tcysNgAAY4iwDQDAhHHaHZndrlLTVFApZ10OAAA4AsI2AAATxqvVJUlhuSyZvJQDADCOeIUGAGCCWL4v2/clw+gtIQcAAGOJsA0AwATJrcxql4pKbTvjagAAwNEQtgEAmBBmtyun1ZEk+dVKxtUAAIBjIWwDADAhcst1Sam6hYIS1826HAAAcAyEbQAAJoARxXKbTUmSP8esNgAA446wDQDABPDqdSlNFeU8xZ6XdTkAAOA4CNsAAIy7JJFXb0iSgmpVMoyMCwIAAMdD2AYAYMx5jaaMJFHiOOoW8lmXAwAA1oGwDQDAOEtTef3jvvxqhVltAAAmBGEbAIAx5jZbMqNIqWUpLJeyLgcAAKwTYRsAgHHFrDYAABOLsA0AwJiyO76sMFRqmsxqAwAwYQjbAACMqVytJkkKyyWllpVxNQAAYBCEbQAAxpAVBLI7viSjt4QcAABMFMI2AABjKLfc26sdlopKbTvjagAAwKAGDtsPPvigrrjiCp155pnatWuXbrrpJoVhONB9fP3rX9dpp52mF7/4xYP+eAAApp7Z7cpptSVJ/hyz2gAATKKBPiqv1Wq6/PLLdcopp2jPnj167LHHdOONN8r3fV177bXrug/f9/Xe975XJ5xwwoYKBgBg2vU6kKfqFvJKXDfrcgAAwAYMFLY/85nPqNVq6eabb9bc3JwkKY5jXX/99brqqqu0Y8eO497HLbfcoic/+ck68cQTdf/992+oaAAAppURx/IaTUlSUK1mXA0AANiogZaR33XXXTr//PNXg7YkXXTRRUqSRPfcc89xr//7v/97fepTn9I73/nOgQsFAGAWePWGlKaKPU9Rzsu6HAAAsEEDzWzv3btXl1xyyZrbKpWKtm/frr179x73+ve85z162ctepqc//emDVXkctj3efd4sy1zzJzDNGO+YJUMf70miXKMhwzDUXZiT7XDcF8YDz+2YJYx3DMtAYbter6tSObxRS7VaVa1/FujRfPOb39Tf/u3f6s477xyswuMwTUPz88Wh3udWqVTyWZcAjAzjHbNkaOP9F4u9Pws5lU/aLhnGcO4XGBKe2zFLGO/YrJGcJRIEgd773vfqd37nd7SwsDDU+06SVPV6e6j3OWyWZapSyate7yiOk6zLAbYU4x2zZKjjPU1VfOQXMuNEfrGo7vJ4v7ZhtvDcjlnCeMfxVCr5da18GChsVyoVNRqNw26v1WqqHqOJy6233irTNPWiF71I9Xrv3NBut6skSVSv15XL5eRuottqFE3GL0EcJxNTK7BZjHfMkmGMd6fZktHtKrEsdQoFid8fjCGe2zFLGO/YrIHC9s6dOw/bm91oNLRv3z7t3LnzqNft3btXP/3pT3X++ecf9rWzzz5b7373u/XqV796kFIAAJgeaapcfztWUClLJvsEAQCYdAOF7QsvvFAf+9jH1uzdvvPOO2Wapnbt2nXU66688kq9/OUvX3Pbxz/+cT300EP6gz/4A51yyimDVw4AwJSwfV9WEEqG2QvbAABg4g300flll12mYrGo3bt36+6779Ztt92mm266SZdddtmaM7avueYanX766at/P/XUU3Xuueeu+W/79u0qFAo699xz13U+NwAA0yq33NtiFZRLSi06kAMAMA0GCtvValW33nqrLMvS7t279YEPfECXXnqp3vGOd6z5viRJFMfxUAsFAGAaWUEou9ORZCioHn7iBwAAmExGmqZp1kVsRhwnWlxsZV3GMdm2qfn5opaWWjRZwNRjvGOWDGO8F36xX26zqW6xqNaO7UOuEBgOntsxSxjvOJ6FheK6upHTgQUAgIyY3Uhus/eBsT/HrDYAANOEsA0AQEa8el1SqiifV+x5WZcDAACGiLANAEAGjDiWV29Kknz2agMAMHUI2wAAZMCrN6U0Uey6ivK5rMsBAABDRtgGAGDUkqS/hFzy56qSYWRcEAAAGDbCNgAAI+Y2WzLiWIltq1ssZF0OAADYAoRtAABGKU2Vq/VmtYNqhVltAACmFGEbAIARctptmd2uUtNSUC5lXQ4AANgihG0AAEYlTZVb7s9qV0qSycswAADTild5AABGxPYDWUEgGUZvCTkAAJhahG0AAEbEW9mrXS4ptayMqwEAAFuJsA0AwAiYYSin3ZbErDYAALOAsA0AwAis7NXuFgtKHCfjagAAwFYjbAMAsMWMKJLbakmSfGa1AQCYCYRtAAC2WK7WkNJUUS6nOOdlXQ4AABgBwjYAAFvIiBO5jYYkyZ9jVhsAgFlB2AYAYAu5jYaMJFHsuory+azLAQAAI0LYBgBgq6SpcivHfVUrkmFkXBAAABgVwjYAAFvEbbZkxLES21ZYKmZdDgAAGCHCNgAAWyFNlVuuSZKCSplZbQAAZgxhGwCALeC0OzK7XaWm2QvbAABgphC2AQDYAt7KXu1KWTJ5uQUAYNbw6g8AwJBZvi/b9yXDYFYbAIAZRdgGAGDIcsu9We2wVFRq2xlXAwAAskDYBgBgiMywK6fdkST51WrG1QAAgKwQtgEAGKLeudqpuoWCEtfJuhwAAJARwjYAAENiRJHcZlOS5M9VMq4GAABkibANAMCQePWGlKaKcp7iXC7rcgAAQIYI2wAADEOS9MK2pIC92gAAzDzCNgAAQ+A1mjKSRInjqFvIZ10OAADIGGEbAIDNSlN5td5xX/5cRTKMjAsCAABZI2wDALBJdqMpM4qUWpbCUinrcgAAwBggbAMAsBlpKm+pJknyq8xqAwCAHsI2AACbUW/JDLtKTVNhuZx1NQAAYEwQtgEA2IzH9kuSwnJJqcXLKgAA6OFdAQAAG2T6gdRoS+ovIQcAAOgjbAMAsEEre7W75ZJS2864GgAAME54ZwAAky5JlF9alhEnWVcyc+xWS7JMhfPVrEsBAABjhrANABMuV6uvnvGMETMMqVpS4rlSxIcdAADgIMI2AEyyNJXbaEqSwnJZscPT+iiZlqnSSU+QmkHWpQAAgDHDuzIAmGBOuyMzipRaltonLHDG84jZtik5tiTCNgAAWIsGaQAwwdxGQ5IUlkoEbQAAgDFC2AaACWV2IzltX5IUVEoZVwMAAIBDEbYBYEL1ZrVTRfm8EsfJuhwAAAAcgrANAJMoTeX1G6MFZWa1AQAAxg1hGwAmkNPuyIhjpZalbrGQdTkAAAB4HMI2AEwgr95rjBaUaYwGAAAwjgjbADBhzG4ku9NrjBayhBwAAGAsEbYBYMLQGA0AAGD8EbYBYJIc2hiN474AAADGFmEbACaI02ofbIxWoDEaAADAuCJsA8AEWXPcF43RAAAAxhZhGwAmhNntyu50JBkKy+WsywEAAMAxELYBYEJ49d6sdreQU+LYGVcDAACAYyFsA8AkSFO5zV7YZlYbAABg/BG2AWACrDRGS2xb3UI+63IAAABwHIRtAJgAXr0hSQppjAYAADARCNsAMObMsCvb9yUZvS7kAAAAGHuEbQAYc16jN6vdLeSV2jRGAwAAmASEbQAYZ2kqt9GSJAUVZrUBAAAmBWEbAMaY22zJSHqN0aI8jdEAAAAmBWEbAMaY21g57ovGaAAAAJOEsA0AY8oMQxqjAQAATCjCNgCMKa8/q01jNAAAgMlD2AaAcZQkq0vIg0o542IAAAAwKMI2AIwht9WWkST9xmi5rMsBAADAgAjbADCG3P7Z2mG5TGM0AACACUTYBoAx02uMFojGaAAAAJOLsA0AY8ar92a1u8W8UtvKuBoAAABsBGEbAMZJkshttiRJQZnGaAAAAJOKsA0AY+RgYzSHxmgAAAATjLANAGNkZQl5UCnRGA0AAGCCEbYBYExYQSgrCCTDUEhjNAAAgIlG2AaAMbFy3Fe3UFBq0RgNAABgkhG2AWAcHNoYrUJjNAAAgElH2AaAMeA2W73GaI6jKOdlXQ4AAAA2ibANAGPAazQlSUGZxmgAAADTgLANABmzgoDGaAAAAFOGsA0AGfPqvVntsEhjNAAAgGlB2AaALB3SGC0s0xgNAABgWhC2ASBDbrMlpTRGAwAAmDaEbQDISprKq/fO1g4qZRqjAQAATBHCNgBkxApCWWHYa4xWKmZdDgAAAIaIsA0AGfEavVntsFikMRoAAMCUIWwDQAaM+GBjtKDCcV8AAADThrANABlwm00pTRW7rmKPxmgAAADThrANAKOWpnIb/bO1yyUaowEAAEwhwjYAjJgVBIc0RmMJOQAAwDQibAPAiHn1/qx2qajU4mkYAABgGvEuDwBGyIhjua1+Y7RyOeNqAAAAsFUI2wAwQm6zdUhjNDfrcgAAALBFCNsAMCppKq/eO1s7qJRpjAYAADDFCNsAMCK2H8jsdiXDVFgqZl0OAAAAthBhGwBGZPW4r1JRMnn6BQAAmGa82wOAEVjTGK3CcV8AAADTjrANACPgNpq9xmieq9jzsi4HAAAAW4ywDQBbLU3l9ZeQc9wXAADAbCBsA8AWW2mMlpo0RgMAAJgVhG0A2GIrx311izRGAwAAmBW86wOALWTEsZx2W1L/bG0AAADMBMI2AGyhg43RPMWem3U5AAAAGBHCNgBslUMbo3HcFwAAwEwhbAPAFrF9/2BjtCKN0QAAAGYJYRsAtohX781qhyUaowEAAMwa3v0BwBYwolhOq9cYLeRsbQAAgJlD2AaALeA2m5JSRTkaowEAAMwiwjYADFuarp6tzaw2AADAbCJsA8CQ2R1fZhT1G6MVsi4HAAAAGSBsA8CQeY3+rHapRGM0AACAGcW7QAAYIiOK5LQ6kjhbGwAAYJYRtgFgiLzGSmO0nBKXxmgAAACzirANAMOSpnIb/bO1y8xqAwAAzDLCNgAMid3p9BujWQpLxazLAQAAQIYI2wAwJF59ZVa7KBlGxtUAAAAgS4RtABgCI4rktPuN0ThbGwAAYOYRtgFgCNY2RnOyLgcAAAAZI2wDwGYd0hgtqDCrDQAAAMI2AGya0+43RrMsdYuFrMsBAADAGCBsA8AmuY2GJCkslWiMBgAAAEmEbQDYFLMbyWn7kqSgwtnaAAAA6CFsA8Am9Ga1U0X5vBKHxmgAAADoIWwDwEalab8LuRSUmdUGAADAQYRtANggp92REcc0RgMAAMBhCNsAsEFevdcYLSjTGA0AAABrEbYBYAPMbld2pyNJCllCDgAAgMchbAPABrj9vdo0RgMAAMCRELYBYFCHNkbjuC8AAAAcwcBh+8EHH9QVV1yhM888U7t27dJNN92kMAyPeU2z2dSePXt06aWX6p/8k3+iZz/72Xr961+vH/7whxsuHACy4rTaBxujFWiMBgAAgMMNFLZrtZouv/xydbtd7dmzR1dffbX+4i/+QjfeeOMxr/v5z3+uz372s9q1a5c+9KEP6YYbblCj0dCrXvUqPfjgg5t6AAAwamuO+6IxGgAAAI7AHuSbP/OZz6jVaunmm2/W3NycJCmOY11//fW66qqrtGPHjiNed+KJJ+prX/ua8vn86m3nnXeenvvc5+rP/uzP9K53vWvjjwAARuhgYzRDYbmcdTkAAAAYUwPNbN911106//zzV4O2JF100UVKkkT33HPPUa8rFAprgrYkFYtFnXzyyfrFL34xWMUAkCGv3pvV7hZySpyBPq8EAADADBnoneLevXt1ySWXrLmtUqlo+/bt2rt370A/uF6v68c//rGe/exnD3Tdkdj2ePd5syxzzZ/ANJvq8Z6k8lpNGYaheK4y9s892HpTPd6BQzDWMUsY7xiWgcJ2vV5XpVI57PZqtaparTbQD/73//7fyzAMvfrVrx7ousczTUPz88VN3ceoVCr5438TMCWmcrwv9p/n8q7KJ25nvzZWTeV4B46AsY5ZwnjHZmWyBvK2225bbaz2xCc+cVP3lSSp6vX2kCrbGpZlqlLJq17vKI6TrMsBttQ0j/fCz/bJihMF+YLC5fF+3sFoTPN4Bw7FWMcsYbzjeCqV/LpWPgwUtiuVihqNxmG312o1VavVdd3HX//1X+vaa6/VG9/4Rr385S8f5McfVRRNxi9BHCcTUyuwWdM23s2wK7PdUSpDnWJR6RQ9NmzetI134GgY65gljHds1kAbEXbu3HnY3uxGo6F9+/Zp586dx73+vvvu01ve8hZdfPHFestb3jJYpQCQIa//QWO3kFdq0xgNAAAAxzZQ2L7wwgt17733ql6vr9525513yjRN7dq165jXPvDAA7rqqqt03nnn6frrr99YtQCQhTSV22hJkoJKKeNiAAAAMAkGCtuXXXaZisWidu/erbvvvlu33XabbrrpJl122WVrzti+5pprdPrpp6/+/cCBA3rta18rz/N0+eWX6/7779d9992n++67Tw888MDwHg0AbAG32ZKRxEpsW1GeZikAAAA4voHWQlarVd1666264YYbtHv3bhWLRV166aW6+uqr13xfkiSK43j17w888IAeffRRSdK//Jf/cs33nnPOOfr0pz+9wfIBYOu5jd7Z2mG5RAdyAAAArIuRpmmadRGbEceJFhdbWZdxTLZtan6+qKWlFk0WMPWmbbybYajKIz+XZKh28lPYr401pm28A0fDWMcsYbzjeBYWiuvqRs5J7QBwDF69N6tNYzQAAAAMgrANAEeTJHKbvbAdVMoZFwMAAIBJQtgGgKNwW20ZSdJvjJbLuhwAAABMEMI2AByF2z9bOyyXaYwGAACAgRC2AeAIzDCU7QeSDAVlztYGAADAYAjbAHAEXr03q90t5pXaVsbVAAAAYNIQtgHg8ZJEbrN3pGBQpjEaAAAABkfYBoDHOdgYzaExGgAAADaEsA0Aj7OyhDyolGiMBgAAgA0hbAPAIawglBUEkmEopDEaAAAANoiwDQCHWDnuq1soKLVojAYAAICNIWwDwIpDG6NVmNUGAADAxhG2AaDPbbZ6jdEcR1GOxmgAAADYOMI2APR5/SXkQZnGaAAAANgcwjYASLKCQFYQ0hgNAAAAQ0HYBgBJXr0pSQqLNEYDAADA5hG2AeCQxmhhuZxxMQAAAJgGhG0AM89ttqR0pTGal3U5AAAAmAKEbQCzLU3l1fuN0SplGqMBAABgKAjbAGaaFYSywn5jtFIx63IAAAAwJQjbAGbaynFfYbFIYzQAAAAMDWEbwMwy4oON0YIKx30BAABgeAjbAGaW22xKaarYdRV7NEYDAADA8BC2AcymNJXb6J+tXS7RGA0AAABDRdgGMJOsIDikMRpLyAEAADBchG0AM8mr92e1S0WlFk+FAAAAGC7eYQKYOUYcy231G6OVyxlXAwAAgGlE2AYwc9xm65DGaG7W5QAAAGAKEbYBzJY0lVfvna0dVMo0RgMAAMCWIGwDmCm2H8jsdiXDVFgqZl0OAAAAphRhG8BMcRu9We2wVJRMngIBAACwNXinCWBm9BqjtSVJQYXjvgAAALB1CNsAZobbaPYao3muYs/LuhwAAABMMcI2gNmQpvIavbO1Oe4LAAAAW42wDWAmrDRGS00aowEAAGDrEbYBzISV4766RRqjAQAAYOvxjhPA1DPiWE57pTEaS8gBAACw9QjbAKbewcZonmLPzbocAAAAzADCNoDpdmhjNI77AgAAwIgQtgFMNdv3DzZGK9IYDQAAAKNB2AYw1bx6b1Y7LNEYDQAAAKPDO08AU8uIYjmtXmO0kLO1AQAAMEKEbQBTq7dXm8ZoAAAAGD3CNoDplKZyG72ztTnuCwAAAKNG2AYwleyOLzOK+o3RClmXAwAAgBlD2AYwlbx6b1Y7LJVojAYAAICR4x0ogKljRJGcdkcSZ2sDAAAgG4RtAFNnpTFalMspcWmMBgAAgNEjbAOYLmkqt9E/W7vMrDYAAACyQdgGMFXsTqffGM1SWCpmXQ4AAABmFGEbwFTx6iuz2kXJMDKuBgAAALOKsA1gaqxpjFbmbG0AAABkh7ANYGqsbYzmZF0OAAAAZhhhG8B0OKQxWlBhVhsAAADZImwDmApOu98YzbLULRayLgcAAAAzjrANYCq4jYYkKSyVaIwGAACAzBG2AUw8sxvJafuSpKDC2doAAADIHmEbwMTrzWqnivI5JQ6N0QAAAJA9wjaAyZam/S7kHPcFAACA8UHYBjDRnHZbRhzTGA0AAABjhbANYKJ59ZVZbRqjAQAAYHwQtgFMLLPbld3pSJLCMo3RAAAAMD4I2wAmltvfqx3l8zRGAwAAwFghbAOYTIc2RuO4LwAAAIwZwjaAieS0DmmMVqAxGgAAAMYLYRvARDp43BeN0QAAADB+CNsAJs7BxmiGQs7WBgAAwBgibAOYOCvHfXULOSWOnXE1AAAAwOEI2wAmS5rKbfbCNrPaAAAAGFeEbQATZaUxWmLb6hbyWZcDAAAAHBFhG8BE8eoNSVJIYzQAAACMMcI2gIlhhl3Zvi/J6HUhBwAAAMYUYRvAxPAavVntbiGv1KYxGgAAAMYXYRvAZEhTuY2WpP4ScgAAAGCMEbYBTAS32ZKR0BgNAAAAk4GwDWAiuI2V475ojAYAAIDxR9gGMPbMMKQxGgAAACYKYRvA2PPqvVltGqMBAABgUhC2AYy3JJHb7IXtoFLOuBgAAABgfQjbAMaa22rLSBIltq0on8u6HAAAAGBdCNsAxprbP1s7LJdpjAYAAICJQdgGMLZ6jdEC0RgNAAAAk4awDWBsefXerHa3mFdqWxlXAwAAAKwfYRvAeEoSuc2WJCko0xgNAAAAk4WwDWAsHWyM5tAYDQAAABOHsA1gLK0sIQ8qJRqjAQAAYOIQtgGMHSsIZQWBZBgKaYwGAACACUTYBjB2VhujFQpKLRqjAQAAYPIQtgGMlySR0+o3Rqswqw0AAIDJRNgGMFbcZqvXGM1xFOVojAYAAIDJRNgGMFa8Rr8xWpnGaAAAAJhchG0AY8MKAllBSGM0AAAATDzCNoCx4dWbkqSwSGM0AAAATDbCNoDxkCRym73GaGG5nHExAAAAwOYQtgGMBbfZktKVxmhe1uUAAAAAm0LYBpC9NF09WzuolGmMBgAAgIlH2AaQOSsIZYX9xmilYtblAAAAAJtG2AaQuZXjvsJikcZoAAAAmAqEbQCZMuKDjdGCCsd9AQAAYDoQtgFkym02pTRV7LqKPRqjAQAAYDoQtgFkJ03lNvpna5dLNEYDAADA1CBsA8iMFQSHNEZjCTkAAACmB2EbQGa8en9Wu1RUavF0BAAAgOnBu1sAmTDiWG6r3xitXM64GgAAAGC4CNsAMuE2W4c0RnOzLgcAAAAYKsI2gNFLU3n13tnaQaVMYzQAAABMHcI2gJGz/UBmtysZpsJSMetyAAAAgKEjbAMYObfRm9UOS0XJ5GkIAAAA04d3uQBGqtcYrS1JCioc9wUAAIDpRNgGMFJuo9lrjOa5ij0v63IAAACALUHYBjA6aSqv0Ttbm+O+AAAAMM0I2wBGZqUxWmrSGA0AAADTjbANYGRWjvvqFmmMBgAAgOnGu10AI2HEsZz2SmM0lpADAABguhG2AYzEwcZonmLPzbocAAAAYEsRtgFsvTSVV+83RuO4LwAAAMwAwjaALWd3fJlRvzFakcZoAAAAmH6EbQBbzmv0GqOFJRqjAQAAYDbwrhfAljKiWE6rI0kKOVsbAAAAM4KwDWBLeY2mJBqjAQAAYLYQtgFsnTSV219CznFfAAAAmCWEbQBbptcYLeo3RitkXQ4AAAAwMoRtAFvGq680RivRGA0AAAAzhXe/ALaEEUVy2r3GaJytDQAAgFlD2AawJZxaQ1KqKJdT4tIYDQAAALOFsA1g+NJU7soS8jKz2gAAAJg9hG0Aw1dvyohipaalsFTMuhoAAABg5AYO2w8++KCuuOIKnXnmmdq1a5duuukmhWG4rms/97nP6QUveIHOOOMMvfSlL9W3vvWtgQsGMAH2LUuSwnJRMoxsawEAAAAyMFDYrtVquvzyy9XtdrVnzx5dffXV+ou/+AvdeOONx732y1/+st71rnfpoosu0ic+8QmdeeaZetOb3qT77rtvo7UDGENGN5L6S8iDMmdrAwAAYDbZg3zzZz7zGbVaLd18882am5uTJMVxrOuvv15XXXWVduzYcdRrP/KRj+hFL3qR3vrWt0qSzjvvPP3oRz/SRz/6UX3iE5/Y8AMAMF6cekNKpTifU+I6WZcDAAAAZGKgsH3XXXfp/PPPXw3aknTRRRfpuuuu0z333KNXvOIVR7zu4Ycf1k9+8hP97u/+7prbX/jCF64uQ3enuFuxGXalWkNWy5fiJOtygC212hityqw2AAAAZtdAYXvv3r265JJL1txWqVS0fft27d2795jXSdJTn/rUNbefeuqp6na7evjhh3XqqacOUsoatj2+fd6MKFbp738mmYaKcaI064KALWZIkucorZRkM+Ax5SzLXPMnMK0Y65gljHcMy0Bhu16vq1KpHHZ7tVpVrVY76nUrX3v8tSt/P9a1x2Oahubnx7jbcZpKzTkpCGVlXQswKk9YUGVujH8vgSGrVPJZlwCMBGMds4Txjs0aKGyPoyRJVa+3sy7jmKxtC6pU8qrXO4pZRo4pZ1km4x0zg/GOWcFYxyxhvON4KpX8ulY+DBS2K5WKGo3GYbfXajVVq9WjXrfytUajoe3bt6/eXq/X13x9o6JoMn4J4jiZmFqBzWK8Y5Yw3jErGOuYJYx3bNZAGxF27tx52N7sRqOhffv2aefOnce8TtJh1+7du1eO4+ikk04apAwAAAAAAMbaQGH7wgsv1L333rs6Iy1Jd955p0zT1K5du4563UknnaRTTjlFd95555rb77jjDp1//vlT3YkcAAAAADB7Bgrbl112mYrFonbv3q27775bt912m2666SZddtlla87Yvuaaa3T66aevufZ3fud39KUvfUkf+chH9N3vflfXXXedvv/97+uNb3zjcB4JAAAAAABjYqA929VqVbfeeqtuuOEG7d69W8ViUZdeeqmuvvrqNd+XJIniOF5z24tf/GJ1Oh194hOf0Mc//nE99alP1c0336yzzjpr848CAAAAAIAxYqRpOtEn4cZxosXFVtZlHJNtm5qfL2ppqUWTBUw9xjtmCeMds4KxjlnCeMfxLCwU19WNnJPaAQAAAAAYMsI2AAAAAABDRtgGAAAAAGDICNsAAAAAAAwZYRsAAAAAgCEjbAMAAAAAMGSEbQAAAAAAhoywDQAAAADAkBG2AQAAAAAYMsI2AAAAAABDRtgGAAAAAGDICNsAAAAAAAwZYRsAAAAAgCEjbAMAAAAAMGSEbQAAAAAAhoywDQAAAADAkBG2AQAAAAAYMsI2AAAAAABDRtgGAAAAAGDICNsAAAAAAAwZYRsAAAAAgCEjbAMAAAAAMGRGmqZp1kVsRpqmSpLxfwiWZSqOk6zLAEaC8Y5ZwnjHrGCsY5Yw3nEspmnIMIzjft/Eh20AAAAAAMYNy8gBAAAAABgywjYAAAAAAENG2AYAAAAAYMgI2wAAAAAADBlhGwAAAACAISNsAwAAAAAwZIRtAAAAAACGjLANAAAAAMCQEbYBAAAAABgywjYAAAAAAENG2AYAAAAAYMgI2wAAAAAADBlhGwAAAACAISNsH8NXvvIVveENb9CFF16oM888Uy972cv0+c9/Xmmarvm+b37zm3rpS1+qM844Qy94wQt02223HXZff/qnf6qrrrpK5513nk477TTdeeedR/yZjUZD11xzjc455xydddZZevOb36xf/OIXW/L4gEONerw//PDDuuqqq3ThhRfqjDPO0AUXXKA3v/nNeuihh7bsMQIrRj3eH3nkEZ122mmH/febv/mbW/YYgRWjHu979uw54ng/7bTTdO21127Z4wSkbN6/P/jgg7ryyit15pln6uyzz9bv/u7vanFxcUseHyaLnXUB4+xP/uRP9JSnPEXveMc7ND8/r3vvvVfvete79Oijj+pNb3qTJOlv/uZv9KY3vUmXXnqprrnmGn3nO9/Rv/23/1bFYlG/8Ru/sXpfX/jCFyRJv/Irv6L/+l//61F/5lvf+lY98MADeve73y3P8/ShD31IV155pW677TbZNv9c2DqjHu+tVksnnHCC3va2t+lJT3qS9u3bp1tuuUWvec1r9IUvfEELCwtb/pgxu7J4fpekt73tbTr33HNX/14sFof/4IDHGfV4f+UrX6nnPOc5a277n//zf+r973+/Lrzwwq15kEDfqMd7s9nU5Zdfrh07duj973+/fN/XH/7hH+qqq67SZz/7WZkmc5szLcVRHThw4LDb3vnOd6bPetaz0jiO0zRN09/+7d9OX/WqV635nre97W3pRRddtOa2le9/+OGH06c97WnpV77ylcPu+3//7/+dPu1pT0v/+3//76u3Pfjgg+lpp52WfvnLX9704wGOZdTj/Ugeeuih9GlPe1r6xS9+cSMPAVi3UY/3QX8XgGEah+f3t7/97enZZ5+dBkGwkYcArNuox/stt9yS/tIv/VK6b9++1du+//3vp0972tPSv/qrv9r048Fk46OWYzjSzNoznvEMNZtNtdtthWGo7373u2s+AZOkF77whXrwwQf1yCOPrN62nk+17rrrLlUqFe3atWv1tp07d+oZz3iG7rrrrk08EuD4Rj3ej2Rubk6S1O12N3Q9sF7jMN6BUcl6vAdBoK997Wt6wQteINd1B38AwABGPd5/8IMf6OlPf7pOOOGE1dvOOOMMzc3N6Zvf/OYmHgmmAe8QBvS//tf/0o4dO1QqlfT3f//36na72rlz55rvOfXUUyVJe/fuHei+9+7dq6c+9akyDGPN7Tt37hz4voBh2MrxviJJEnW7XT3yyCO64YYb9KQnPUm//uu/vunagUGNYry/+93v1jOe8Qydf/75euc736nl5eXNlg1syCjG+4pvfetbajabevGLX7yp+wE2aivHexAER/wQyXVd3r+DPduD+Ju/+Rvdcccdevvb3y5JqtVqkqRKpbLm+1b+vvL19arX6yqXy4fdXq1Wdf/992+kZGDDtnq8r/g3/+bf6Pbbb5cknXzyyfrUpz51xN8DYCtt9Xh3XVevfvWrdcEFF6hSqeh73/uePvaxj+n+++/X5z73OTmOM4RHAazPqJ7fV3zpS1/Sjh07dPbZZ2/qfoCN2Orxfsopp+i//Jf/It/3lcvlJEk///nPtW/fPhUKhc2WjwnHzPY6Pfroo7r66qt17rnn6jWveU3W5QBbapTj/S1veYs+97nP6SMf+Yi2b9+uK664Qj//+c+39GcChxrFeH/CE56gd7/73Xre856nc845R1deeaU+8IEP6P/+3/+rr33ta1vyM4EjGfX7mXq9rr/+67/Wi170IrZcYORGMd5f+cpXqtls6tprr9Vjjz2mn/70p3rHO94h0zQPW62K2cOz3jrU63VdeeWVmpub0549e1ZfLKrVqqTecV2P//5Dv75elUpFzWbzsNtrtdrA9wVs1KjG+4qTTjpJv/RLv6QXvOAF+o//8T8qjmN98pOf3MQjANZv1OP9UL/yK7+iQqGgv/u7v9v0fQHrkcV4/+pXv6owDPWSl7xkw/cBbMSoxvvOnTv1nve8R9/61rd04YUX6vnPf76q1aouvPBCbd++fQiPBJOMsH0cvu/rqquuUqPR0Cc/+ck1y1tPPvlkOY5z2H6Mlb8/fi/I8ezcuVMPPfTQYecAPvTQQwPfF7ARoxzvR5LP53Xqqafqpz/96abvCzierMc7MEpZjfcvfelL2rlzp04//fQN3wcwqFGP94svvlj33HOPbr/9dt11113as2ePHn74YZ155pmbehyYfITtY4iiSG9961u1d+9effKTn9SOHTvWfN11XZ177rn66le/uub2O+64Q6eeeqpOPPHEgX7ehRdeqFqtpm9/+9urtz300EP6wQ9+wLmU2HKjHu9H0mw29cMf/lAnnXTSpu8LOJZxGO/f+ta31G63dcYZZ2z6voBjyWq8/+IXv9D/+B//g8ZoGKmsxrvrunra056mHTt26Nvf/rZ+8pOf6OUvf/mGHwemAw3SjuH666/Xt771Lb3jHe9Qs9nUfffdt/q1008/Xa7r6g1veINe85rX6N3vfrcuuugiffe739WXvvQlffCDH1xzX//n//wf/exnP9Pi4qIk6Xvf+56k3vEE55xzjiTprLPO0gUXXKBrrrlGb3/72+V5nj74wQ/qtNNO0/Of//zRPGjMrFGP9z179qjRaOhZz3qWFhYW9LOf/Uyf/vSnFYahLr/88tE8aMysUY/3G2+8UYZh6Mwzz1SlUtH3v/993XLLLXrmM5+p5z3veaN50JhZox7vK+644w4lScIScozUqMd7u93Wnj17dPbZZ8vzPN133336+Mc/rje96U2sgoKM9PFrlrHquc99rn72s58d8Wvf+MY3Vj/5+sY3vqEPfehDeuihh/TkJz9Z/+pf/Stdeumla77/He94h/7yL//ysPs555xz9OlPf3r1741GQ3/wB3+gr33ta4qiSBdccIHe+c53HvapHDBsox7v3/jGN/Qnf/In+tGPfqR2u73aqfaNb3wjM9vYcqMe75/73Of053/+5/rpT38q3/e1Y8cOPe95z9Ob3/xmlUqlIT86YK0s3s9I0iWXXCLTNPW5z31uSI8EOL5Rj3ff97V7927df//9arfb2rlzpy6//HK94hWvGPIjwyQibAMAAAAAMGTs2QYAAAAAYMgI2wAAAAAADBlhGwAAAACAISNsAwAAAAAwZIRtAAAAAACGjLANAAAAAMCQEbYBAAAAABgywjYAAAAAAENG2AYAAAAAYMgI2wAAAAAADBlhGwAAAACAISNsAwCADQuCQEmSZF0GAABjh7ANAMCE+c53vqPTTjtNX/va1w772u23367TTjtNf/u3fytJevDBB/XmN79Z55xzjs444wy94hWv0De+8Y011ywvL+t973ufXvKSl+iss87Ss571LL3uda/T//t//2/N9333u9/Vaaedpi9/+cv64Ac/qOc85zn65V/+ZTWbza17sAAATCg76wIAAMBgzj33XD3pSU/S7bffrl//9V9f87Xbb79dJ598ss466yz9+Mc/1qtf/Wrt2LFDV155pQqFgr7yla9o9+7d2rNnz+q1Dz/8sL7+9a/rN37jN3TiiSdq//79+uxnP6t//s//ub785S9rx44da37GH/3RH8lxHL32ta9VGIZyHGdkjx0AgElB2AYAYMIYhqGXvvSl+tSnPqVGo6FyuSxJWlxc1D333KPXv/71kqT3vOc9etKTnqTbbrtNrutKkn7rt35Lr371q/X+979/NWyfdtpp+upXvyrTPLjg7WUve5kuuugiff7zn9fu3bvX/PwgCHTbbbcpl8uN4uECADCRWEYOAMAEetnLXqYwDHXnnXeu3nbHHXcoiiK99KUv1fLysr7zne/ooosuUrPZ1OLiohYXF7W0tKQLLrhAP/nJT/TYY49JklzXXQ3acRxraWlJhUJBT33qU/WDH/zgsJ998cUXE7QBADgOZrYBAJhAp556qs444wzdfvvteuUrXympt4T8zDPP1D/4B/9A3//+95WmqT784Q/rwx/+8BHv48CBA9qxY4eSJNF/+k//SX/2Z3+mRx55RHEcr37P3NzcYdedeOKJW/KYAACYJoRtAAAm1MUXX6z3vOc9evTRRxWGoe677z5de+21krTaIfy3f/u39ZznPOeI15988smSpI997GP68Ic/rEsuuURvectbVK1WZZqm3vve9ypN08OuY1YbAIDjI2wDADChXvjCF+rGG2/Ul770Jfm+L8dxdNFFF0mSTjrpJEmS4zh69rOffcz7+epXv6pzzz1X733ve9fcXq/XNT8/vzXFAwAw5dizDQDAhFpYWNBznvMcffGLX9Ttt9+uCy64QAsLC5Kkbdu26ZxzztFnP/tZ/eIXvzjs2sXFxdX/bVnWYTPYX/nKV1b3dAMAgMExsw0AwAS7+OKL9eY3v1mS9Ja3vGXN16677jr91m/9ll7ykpfoN3/zN3XSSSdp//79uu+++/Too4/qi1/8oiTpn/7Tf6qPfvSj+r3f+z2dddZZ+tGPfqTbb799dXYcAAAMjrANAMAE+9Vf/VVVq1UlSaJf+7VfW/O1f/gP/6Fuu+023XzzzfrLv/xLLS8va2FhQaeffvqa47xe//rXq9Pp6Pbbb9cdd9yh008/Xbfccos+8IEPjPrhAAAwNYz0SJ1PAADARIiiSM95znP0q7/6q4ftuQYAANlhzzYAABPs61//uhYXF3XxxRdnXQoAADgEy8gBAJhA3/ve9/TDH/5Qf/RHf6TTTz9d55xzTtYlAQCAQxC2AQCYQH/+53+uL37xi3r605+uG2+8MetyAADA47BnGwAAAACAIWPPNgAAAAAAQ0bYBgAAAABgyAjbAAAAAAAMGWEbAAAAAIAhI2wDAAAAADBkhG0AAAAAAIaMsA0AAAAAwJARtgEAAAAAGLL/H8TsiIU3lxKHAAAAAElFTkSuQmCC"
          },
          "metadata": {}
        }
      ],
      "execution_count": 35
    },
    {
      "cell_type": "markdown",
      "source": "By now, you should obtain some preliminary insights about how each important variable would affect the success rate, we will select the features that will be used in success prediction in the future module.\n",
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": "features = df[['FlightNumber', 'PayloadMass', 'Orbit', 'LaunchSite', 'Flights', 'GridFins', 'Reused', 'Legs', 'LandingPad', 'Block', 'ReusedCount', 'Serial']]\nfeatures.head()",
      "metadata": {
        "trusted": true
      },
      "outputs": [
        {
          "execution_count": 36,
          "output_type": "execute_result",
          "data": {
            "text/plain": "   FlightNumber  PayloadMass Orbit    LaunchSite  Flights  GridFins  Reused  \\\n0             1  6104.959412   LEO  CCAFS SLC 40        1     False   False   \n1             2   525.000000   LEO  CCAFS SLC 40        1     False   False   \n2             3   677.000000   ISS  CCAFS SLC 40        1     False   False   \n3             4   500.000000    PO   VAFB SLC 4E        1     False   False   \n4             5  3170.000000   GTO  CCAFS SLC 40        1     False   False   \n\n    Legs LandingPad  Block  ReusedCount Serial  \n0  False        NaN    1.0            0  B0003  \n1  False        NaN    1.0            0  B0005  \n2  False        NaN    1.0            0  B0007  \n3  False        NaN    1.0            0  B1003  \n4  False        NaN    1.0            0  B1004  ",
            "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>FlightNumber</th>\n      <th>PayloadMass</th>\n      <th>Orbit</th>\n      <th>LaunchSite</th>\n      <th>Flights</th>\n      <th>GridFins</th>\n      <th>Reused</th>\n      <th>Legs</th>\n      <th>LandingPad</th>\n      <th>Block</th>\n      <th>ReusedCount</th>\n      <th>Serial</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1</td>\n      <td>6104.959412</td>\n      <td>LEO</td>\n      <td>CCAFS SLC 40</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>NaN</td>\n      <td>1.0</td>\n      <td>0</td>\n      <td>B0003</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2</td>\n      <td>525.000000</td>\n      <td>LEO</td>\n      <td>CCAFS SLC 40</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>NaN</td>\n      <td>1.0</td>\n      <td>0</td>\n      <td>B0005</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>3</td>\n      <td>677.000000</td>\n      <td>ISS</td>\n      <td>CCAFS SLC 40</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>NaN</td>\n      <td>1.0</td>\n      <td>0</td>\n      <td>B0007</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>4</td>\n      <td>500.000000</td>\n      <td>PO</td>\n      <td>VAFB SLC 4E</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>NaN</td>\n      <td>1.0</td>\n      <td>0</td>\n      <td>B1003</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>5</td>\n      <td>3170.000000</td>\n      <td>GTO</td>\n      <td>CCAFS SLC 40</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>NaN</td>\n      <td>1.0</td>\n      <td>0</td>\n      <td>B1004</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
          },
          "metadata": {}
        }
      ],
      "execution_count": 36
    },
    {
      "cell_type": "markdown",
      "source": "### TASK  7: Create dummy variables to categorical columns\n",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "Use the function <code>get_dummies</code> and <code>features</code> dataframe to apply OneHotEncoder to the column <code>Orbits</code>, <code>LaunchSite</code>, <code>LandingPad</code>, and <code>Serial</code>. Assign the value to the variable <code>features_one_hot</code>, display the results using the method head. Your result dataframe must include all features including the encoded ones.\n",
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": "# HINT: Use get_dummies() function on the categorical columns\nfeatures_one_hot = features\n\nfeatures_one_hot = pd.concat([features_one_hot,pd.get_dummies(df['Orbit'])], axis=1)\nfeatures_one_hot.drop(['Orbit'], axis = 1,inplace=True)\n\nfeatures_one_hot = pd.concat([features_one_hot,pd.get_dummies(df['LaunchSite'])], axis=1)\nfeatures_one_hot.drop(['LaunchSite'], axis = 1,inplace=True)\n\nfeatures_one_hot = pd.concat([features_one_hot,pd.get_dummies(df['LandingPad'])], axis=1)\nfeatures_one_hot.drop(['LandingPad'], axis = 1,inplace=True)\n\nfeatures_one_hot = pd.concat([features_one_hot,pd.get_dummies(df['Serial'])], axis=1)\nfeatures_one_hot.drop(['Serial'], axis = 1,inplace=True)\n\nfeatures_one_hot.head()\n",
      "metadata": {
        "trusted": true
      },
      "outputs": [
        {
          "execution_count": 37,
          "output_type": "execute_result",
          "data": {
            "text/plain": "   FlightNumber  PayloadMass  Flights  GridFins  Reused   Legs  Block  \\\n0             1  6104.959412        1     False   False  False    1.0   \n1             2   525.000000        1     False   False  False    1.0   \n2             3   677.000000        1     False   False  False    1.0   \n3             4   500.000000        1     False   False  False    1.0   \n4             5  3170.000000        1     False   False  False    1.0   \n\n   ReusedCount  ES-L1  GEO  ...  B1048  B1049  B1050  B1051  B1054  B1056  \\\n0            0      0    0  ...      0      0      0      0      0      0   \n1            0      0    0  ...      0      0      0      0      0      0   \n2            0      0    0  ...      0      0      0      0      0      0   \n3            0      0    0  ...      0      0      0      0      0      0   \n4            0      0    0  ...      0      0      0      0      0      0   \n\n   B1058  B1059  B1060  B1062  \n0      0      0      0      0  \n1      0      0      0      0  \n2      0      0      0      0  \n3      0      0      0      0  \n4      0      0      0      0  \n\n[5 rows x 80 columns]",
            "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>FlightNumber</th>\n      <th>PayloadMass</th>\n      <th>Flights</th>\n      <th>GridFins</th>\n      <th>Reused</th>\n      <th>Legs</th>\n      <th>Block</th>\n      <th>ReusedCount</th>\n      <th>ES-L1</th>\n      <th>GEO</th>\n      <th>...</th>\n      <th>B1048</th>\n      <th>B1049</th>\n      <th>B1050</th>\n      <th>B1051</th>\n      <th>B1054</th>\n      <th>B1056</th>\n      <th>B1058</th>\n      <th>B1059</th>\n      <th>B1060</th>\n      <th>B1062</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1</td>\n      <td>6104.959412</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>1.0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2</td>\n      <td>525.000000</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>1.0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>3</td>\n      <td>677.000000</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>1.0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>4</td>\n      <td>500.000000</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>1.0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>5</td>\n      <td>3170.000000</td>\n      <td>1</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>1.0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows × 80 columns</p>\n</div>"
          },
          "metadata": {}
        }
      ],
      "execution_count": 37
    },
    {
      "cell_type": "markdown",
      "source": "### TASK  8: Cast all numeric columns to `float64`\n",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "Now that our <code>features_one_hot</code> dataframe only contains numbers cast the entire dataframe to variable type <code>float64</code>\n",
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": "# HINT: use astype function\nfeatures_one_hot.astype(float)",
      "metadata": {
        "trusted": true
      },
      "outputs": [
        {
          "execution_count": 38,
          "output_type": "execute_result",
          "data": {
            "text/plain": "    FlightNumber   PayloadMass  Flights  GridFins  Reused  Legs  Block  \\\n0            1.0   6104.959412      1.0       0.0     0.0   0.0    1.0   \n1            2.0    525.000000      1.0       0.0     0.0   0.0    1.0   \n2            3.0    677.000000      1.0       0.0     0.0   0.0    1.0   \n3            4.0    500.000000      1.0       0.0     0.0   0.0    1.0   \n4            5.0   3170.000000      1.0       0.0     0.0   0.0    1.0   \n..           ...           ...      ...       ...     ...   ...    ...   \n85          86.0  15400.000000      2.0       1.0     1.0   1.0    5.0   \n86          87.0  15400.000000      3.0       1.0     1.0   1.0    5.0   \n87          88.0  15400.000000      6.0       1.0     1.0   1.0    5.0   \n88          89.0  15400.000000      3.0       1.0     1.0   1.0    5.0   \n89          90.0   3681.000000      1.0       1.0     0.0   1.0    5.0   \n\n    ReusedCount  ES-L1  GEO  ...  B1048  B1049  B1050  B1051  B1054  B1056  \\\n0           0.0    0.0  0.0  ...    0.0    0.0    0.0    0.0    0.0    0.0   \n1           0.0    0.0  0.0  ...    0.0    0.0    0.0    0.0    0.0    0.0   \n2           0.0    0.0  0.0  ...    0.0    0.0    0.0    0.0    0.0    0.0   \n3           0.0    0.0  0.0  ...    0.0    0.0    0.0    0.0    0.0    0.0   \n4           0.0    0.0  0.0  ...    0.0    0.0    0.0    0.0    0.0    0.0   \n..          ...    ...  ...  ...    ...    ...    ...    ...    ...    ...   \n85          2.0    0.0  0.0  ...    0.0    0.0    0.0    0.0    0.0    0.0   \n86          2.0    0.0  0.0  ...    0.0    0.0    0.0    0.0    0.0    0.0   \n87          5.0    0.0  0.0  ...    0.0    0.0    0.0    1.0    0.0    0.0   \n88          2.0    0.0  0.0  ...    0.0    0.0    0.0    0.0    0.0    0.0   \n89          0.0    0.0  0.0  ...    0.0    0.0    0.0    0.0    0.0    0.0   \n\n    B1058  B1059  B1060  B1062  \n0     0.0    0.0    0.0    0.0  \n1     0.0    0.0    0.0    0.0  \n2     0.0    0.0    0.0    0.0  \n3     0.0    0.0    0.0    0.0  \n4     0.0    0.0    0.0    0.0  \n..    ...    ...    ...    ...  \n85    0.0    0.0    1.0    0.0  \n86    1.0    0.0    0.0    0.0  \n87    0.0    0.0    0.0    0.0  \n88    0.0    0.0    1.0    0.0  \n89    0.0    0.0    0.0    1.0  \n\n[90 rows x 80 columns]",
            "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>FlightNumber</th>\n      <th>PayloadMass</th>\n      <th>Flights</th>\n      <th>GridFins</th>\n      <th>Reused</th>\n      <th>Legs</th>\n      <th>Block</th>\n      <th>ReusedCount</th>\n      <th>ES-L1</th>\n      <th>GEO</th>\n      <th>...</th>\n      <th>B1048</th>\n      <th>B1049</th>\n      <th>B1050</th>\n      <th>B1051</th>\n      <th>B1054</th>\n      <th>B1056</th>\n      <th>B1058</th>\n      <th>B1059</th>\n      <th>B1060</th>\n      <th>B1062</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1.0</td>\n      <td>6104.959412</td>\n      <td>1.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>1.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>...</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2.0</td>\n      <td>525.000000</td>\n      <td>1.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>1.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>...</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>3.0</td>\n      <td>677.000000</td>\n      <td>1.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>1.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>...</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>4.0</td>\n      <td>500.000000</td>\n      <td>1.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>1.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>...</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>5.0</td>\n      <td>3170.000000</td>\n      <td>1.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>1.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>...</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>85</th>\n      <td>86.0</td>\n      <td>15400.000000</td>\n      <td>2.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>5.0</td>\n      <td>2.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>...</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>1.0</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>86</th>\n      <td>87.0</td>\n      <td>15400.000000</td>\n      <td>3.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>5.0</td>\n      <td>2.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>...</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>1.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>87</th>\n      <td>88.0</td>\n      <td>15400.000000</td>\n      <td>6.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>5.0</td>\n      <td>5.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>...</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>1.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>88</th>\n      <td>89.0</td>\n      <td>15400.000000</td>\n      <td>3.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>5.0</td>\n      <td>2.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>...</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>1.0</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>89</th>\n      <td>90.0</td>\n      <td>3681.000000</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>0.0</td>\n      <td>1.0</td>\n      <td>5.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>...</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>1.0</td>\n    </tr>\n  </tbody>\n</table>\n<p>90 rows × 80 columns</p>\n</div>"
          },
          "metadata": {}
        }
      ],
      "execution_count": 38
    },
    {
      "cell_type": "markdown",
      "source": "We can now export it to a <b>CSV</b> for the next section,but to make the answers consistent, in the next lab we will provide data in a pre-selected date range.\n",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "<code>features_one_hot.to_csv('dataset_part\\_3.csv', index=False)</code>\n",
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": "features_one_hot.to_csv('dataset_part_3.csv', index=False)\n",
      "metadata": {
        "trusted": true
      },
      "outputs": [],
      "execution_count": 39
    },
    {
      "cell_type": "markdown",
      "source": "## Authors\n",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "[Pratiksha Verma](https://www.linkedin.com/in/pratiksha-verma-6487561b1/?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDS0321ENSkillsNetwork865-2022-01-01)\n",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "## Change Log\n",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "| Date (YYYY-MM-DD) | Version | Changed By      | Change Description      |\n| ----------------- | ------- | -------------   | ----------------------- |\n| 2022-11-09        | 1.0     | Pratiksha Verma | Converted initial version to Jupyterlite|\n",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "### <h3 align=\"center\"> IBM Corporation 2022. All rights reserved. <h3/>\n",
      "metadata": {}
    }
  ]
}