NAIS-2022.ipynb

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      "source": [
        "# @title Setup\n",
        "from google.colab import auth\n",
        "from google.cloud import bigquery\n",
        "from google.colab import data_table\n",
        "\n",
        "project = 'ais-data-385301' # Project ID inserted based on the query results selected to explore\n",
        "location = 'US' # Location inserted based on the query results selected to explore\n",
        "client = bigquery.Client(project=project, location=location)\n",
        "data_table.enable_dataframe_formatter()\n",
        "auth.authenticate_user()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pj42soltXW_H"
      },
      "source": [
        "## Reference SQL syntax from the original job\n",
        "Use the ```jobs.query```\n",
        "[method](https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/query) to\n",
        "return the SQL syntax from the job. This can be copied from the output cell\n",
        "below to edit the query now or in the future. Alternatively, you can use\n",
        "[this link](https://console.cloud.google.com/bigquery?j=ais-data-385301:US:bquxjob_56d440df_18decc339b8)\n",
        "back to BigQuery to edit the query within the BigQuery user interface."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "KxSqPfAeXW_K",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8876cd4e-54a3-41a3-aae5-4aebff1785ba"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "SELECT MMSI, COUNT(MMSI) AS MMSI_count FROM `ais-data-385301.uscg.nais` GROUP BY MMSI ORDER BY COUNT(MMSI);\n"
          ]
        }
      ],
      "source": [
        "# Running this code will display the query used to generate your previous job\n",
        "\n",
        "job = client.get_job('bquxjob_56d440df_18decc339b8') # Job ID inserted based on the query results selected to explore\n",
        "print(job.query)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eY-wNOGO11ON"
      },
      "source": [
        "# Result set loaded from BigQuery job as a DataFrame\n",
        "Query results are referenced from the Job ID ran from BigQuery and the query\n",
        "does not need to be re-run to explore results. The ```to_dataframe```\n",
        "[method](https://googleapis.dev/python/bigquery/latest/generated/google.cloud.bigquery.job.QueryJob.html#google.cloud.bigquery.job.QueryJob.to_dataframe)\n",
        "downloads the results to a Pandas DataFrame by using the BigQuery Storage API.\n",
        "\n",
        "To edit query syntax, you can do so from the BigQuery SQL editor or in the\n",
        "```Optional:``` sections below."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
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          "height": 290
        },
        "outputId": "862016e3-a1dd-46b4-88d6-897645ec4290"
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      "outputs": [
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              "         MMSI_count\n",
              "count       85683.0\n",
              "mean   34623.171994\n",
              "std    75018.431948\n",
              "min             1.0\n",
              "25%           304.0\n",
              "50%          4609.0\n",
              "75%         27060.0\n",
              "max        472990.0"
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              "      <th>MMSI_count</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>85683.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>34623.171994</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>75018.431948</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1.0</td>\n",
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              "      <th>25%</th>\n",
              "      <td>304.0</td>\n",
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              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
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              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
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              "        document.querySelector('#' + key + ' button');\n",
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              "summary": "{\n  \"name\": \"results\",\n  \"rows\": 8,\n  \"fields\": [\n    {\n      \"column\": \"MMSI_count\",\n      \"properties\": {\n        \"dtype\": \"Float64\",\n        \"num_unique_values\": 8,\n        \"samples\": [\n          34623.17199444464,\n          4609.0,\n          85683.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
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          "metadata": {},
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      "source": [
        "# Running this code will read results from your previous job\n",
        "\n",
        "job = client.get_job('bquxjob_56d440df_18decc339b8') # Job ID inserted based on the query results selected to explore\n",
        "results = job.to_dataframe()\n",
        "results.describe()"
      ]
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          "height": 795
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        "outputId": "8019641e-840c-4cd3-fa04-12048740c6ef"
      },
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        {
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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Convert 'MMSI_count' to a 1-dimensional numpy array\n",
        "mmsi_count = np.array(results['MMSI_count'])\n",
        "\n",
        "# Create a larger figure\n",
        "plt.figure(figsize=(15, 9))\n",
        "\n",
        "# Create a histogram using matplotlib\n",
        "plt.hist(mmsi_count, bins='auto', edgecolor='black', alpha=0.7)\n",
        "plt.xlabel(\"MMSI Count\")\n",
        "plt.ylabel(\"Frequency\")\n",
        "plt.title(\"Distribution of MMSI Count\")\n",
        "\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Convert 'MMSI_count' to a 1-dimensional numpy array\n",
        "mmsi_count = np.array(results['MMSI_count'], dtype=float)  # Convert to float\n",
        "\n",
        "# Apply log transform\n",
        "log_mmsi_count = np.log(mmsi_count)\n",
        "\n",
        "# Create a larger figure\n",
        "plt.figure(figsize=(15, 9))\n",
        "\n",
        "# Create a histogram using matplotlib\n",
        "plt.hist(log_mmsi_count, bins='auto', edgecolor='black', alpha=0.7)\n",
        "plt.xlabel(\"Log MMSI Count\")\n",
        "plt.ylabel(\"Frequency\")\n",
        "plt.title(\"Distribution of Log MMSI Count\")\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 795
        },
        "id": "iSqiNBmiyN4T",
        "outputId": "4f3ec8fe-6733-432c-e332-5e47803d61a6"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x900 with 1 Axes>"
            ],
            "image/png": 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5CxcuzNSpUzN27NiMHj063bt3z913351WrVp9Zt8zzzwzjzzySPr27Zvu3btn2rRpufrqq7PWWmtlp512SvJxUNahQ4eMGDEi7dq1S9u2bbP99tunR48e9aq3Y8eO2WmnnXLYYYdl6tSpueyyy/L1r389Rx55ZE2bI444Ir///e+z55575oc//GFef/313HjjjbU2aKhrbXvvvXd22223/PKXv8xbb72VLbfcMg888EDuuuuuDB06dKlr19dRRx2V//7v/86hhx6a8ePHZ911183vf//7PProo7nsssuWexOCZXnttddy9tlnL3V86623Tt++fTNw4MBce+21+eCDD7LLLrvkiSeeyPXXX59+/fplt912S5J07do1xxxzTC6++OLss88+2XPPPfOPf/wj9913X9ZYY416jdTacssts+WWW9a5X4sWLXLKKad8Ybvzzz8/48ePz3777ZctttgiSfL000/nt7/9bTp27JihQ4fW+d4HHHBAnnvuuZxzzjl55plncuCBB6Z79+7597//nfvvvz9jxozJzTffnGT5f6bt27fPD37wg/zqV79KWVlZ1ltvvdxzzz2ZNm1anetbonXr1tlkk01y6623ZoMNNkjHjh2z2WabZbPNNqv3NQGg2Sl4t1gAYCU1cuTIUpKaV3l5eamqqqr0H//xH6XLL7+8VF1dvVSf008/vfTJ/zwZM2ZMad999y1169atVF5eXurWrVvpwAMPLL366qu1+t11112lTTbZpNSyZctSktLIkSNLpVKptMsuu5Q23XTTZda3yy67lHbZZZea9w8++GApSemWW24pnXTSSaUuXbqUWrduXerbt29p0qRJS/W/+OKLS1/72tdKFRUVpR133LH01FNPLXXNz6tt4MCBpe7du9dqO2vWrNKxxx5b6tatW2nVVVctrb/++qULL7ywtHjx4lrtkpQGDx68VE3du3cvDRw4cJnP+0lTp04tHXbYYaU11lijVF5eXtp8881r6vr09fr27fuF11vS9pM/70++Bg0aVCqVSqUFCxaUzjjjjFKPHj1Kq666amnttdcunXTSSaWPPvqo1rUWLlxYOvXUU0tVVVWl1q1bl7797W+XXnrppVKnTp1KRx999BfW8lmfzyct+a5Nnz695tjAgQNLbdu2/dx+b775ZilJ6cILL6w59uijj5YGDx5c2myzzUrt27cvrbrqqqV11lmndOihh5Zef/31Wv0/7zu5LEv+GejSpUupZcuWpc6dO5f23nvv0l133VWr3fL+TKdPn17af//9S23atCmtvvrqpf/8z/8sPf/887W+m5/3WXz6n9FSqVR67LHHSttuu22pvLy8lKR0+umnL/fzAQClUlmp1MRXDQYAoNn74IMPsvrqq+fss8/OL3/5y6LLAQBoNNacAwCgSfnwww+XOrZkrbpdd931qy0GAOBLZs05AACalFtvvTWjRo3KXnvtldVWWy1/+9vfcsstt2SPPfbIjjvuWHR5AACNSjgHAECTssUWW6Rly5a54IILUl1dXbNJxLI2mwAAWNFZcw4AAAAACmLNOQAAAAAoiHAOAAAAAApizblGsnjx4rz77rtp165dysrKii4HAAAAgAKVSqXMmjUr3bp1S4sWnz0+TjjXSN59992svfbaRZcBAAAAQBMyefLkrLXWWp95XjjXSNq1a5fk4w+8srKy4GoAAAAAKFJ1dXXWXnvtmszoswjnGsmSqayVlZXCOQAAAACS5AuXP7MhBAAAAAAURDgHAAAAAAURzgEAAABAQYRzAAAAAFAQ4RwAAAAAFEQ4BwAAAAAFEc4BAAAAQEGEcwAAAABQEOEcAAAAABREOAcAAAAABRHOAQAAAEBBhHMAAAAAUBDhHAAAAAAURDgHAAAAAAURzgEAAABAQQoN5x555JHsvffe6datW8rKynLnnXfWnFuwYEF+8YtfZPPNN0/btm3TrVu3HHLIIXn33XdrXWPGjBkZMGBAKisr06FDhwwaNCizZ8+u1ebZZ5/Nt771rbRq1Sprr712LrjggqVquf3227PRRhulVatW2XzzzfOnP/3pS3lmAAAAAFii0HBuzpw52XLLLXPVVVctdW7u3Ll5+umnc+qpp+bpp5/OH//4x7zyyivZZ599arUbMGBAXnjhhYwePTr33HNPHnnkkRx11FE156urq7PHHnuke/fuGT9+fC688MIMHz481157bU2bxx57LAceeGAGDRqUZ555Jv369Uu/fv3y/PPPf3kPDwAAAECzV1YqlUpFF5EkZWVlueOOO9KvX7/PbPPkk0/mG9/4RiZNmpR11lknL730UjbZZJM8+eST6dmzZ5Lk/vvvz1577ZV33nkn3bp1yzXXXJNf/vKXmTJlSsrLy5MkJ554Yu688868/PLLSZIDDjggc+bMyT333FNzrx122CFbbbVVRowYsVz1V1dXp3379pk5c2YqKyvr+SkAAAAAsDJY3qxohVpzbubMmSkrK0uHDh2SJOPGjUuHDh1qgrkk6d27d1q0aJHHH3+8ps3OO+9cE8wlSZ8+ffLKK6/k/fffr2nTu3fvWvfq06dPxo0b95m1zJs3L9XV1bVeAAAAAFAXK0w499FHH+UXv/hFDjzwwJq0ccqUKenSpUutdi1btkzHjh0zZcqUmjZdu3at1WbJ+y9qs+T8spx33nlp3759zWvttddu2AMCAAAA0OysEOHcggUL8sMf/jClUinXXHNN0eUkSU466aTMnDmz5jV58uSiSwIAAABgBdOy6AK+yJJgbtKkSRk7dmytObpVVVWZNm1arfYLFy7MjBkzUlVVVdNm6tSptdosef9FbZacX5aKiopUVFTU/8EAAAAAaPaa9Mi5JcHcxIkT85e//CWdOnWqdb5Xr1754IMPMn78+JpjY8eOzeLFi7P99tvXtHnkkUeyYMGCmjajR4/OhhtumNVXX72mzZgxY2pde/To0enVq9eX9WgAAAAAUGw4N3v27EyYMCETJkxIkrz55puZMGFC3n777SxYsCDf//7389RTT+Wmm27KokWLMmXKlEyZMiXz589Pkmy88cbZc889c+SRR+aJJ57Io48+miFDhqR///7p1q1bkuSggw5KeXl5Bg0alBdeeCG33nprLr/88gwbNqymjmOOOSb3339/Lr744rz88ssZPnx4nnrqqQwZMuQr/0wAAAAAaD7KSqVSqaibP/TQQ9ltt92WOj5w4MAMHz48PXr0WGa/Bx98MLvuumuSZMaMGRkyZEj+93//Ny1atMj++++fK664IquttlpN+2effTaDBw/Ok08+mTXWWCM//elP84tf/KLWNW+//faccsopeeutt7L++uvnggsuyF577bXcz7K82+MCAAAAsPJb3qyo0HBuZSKcAwAAAGCJ5c2KmvSacwAAAACwMhPOAQAAAEBBhHMAAAAAUJCWRRdA0zZ9+vRUV1fXu39lZWU6d+7ciBUBAAAArDyEc3ym6dOn5+DDjsiMWXPrfY2O7drkxpG/FtABAAAALINwjs9UXV2dGbPmpnOv/dO2Y9c6958zY2qmj/tDqqurhXMAAAAAyyCc4wu17dg1lV3Wqlff6Y1cCwAAAMDKxIYQAAAAAFAQ4RwAAAAAFEQ4BwAAAAAFEc4BAAAAQEGEcwAAAABQEOEcAAAAABREOAcAAAAABRHOAQAAAEBBhHMAAAAAUBDhHAAAAAAURDgHAAAAAAURzgEAAABAQYRzAAAAAFAQ4RwAAAAAFEQ4BwAAAAAFEc4BAAAAQEGEcwAAAABQEOEcAAAAABREOAcAAAAABRHOAQAAAEBBhHMAAAAAUBDhHAAAAAAURDgHAAAAAAURzgEAAABAQYRzAAAAAFAQ4RwAAAAAFEQ4BwAAAAAFEc4BAAAAQEGEcwAAAABQEOEcAAAAABREOAcAAAAABRHOAQAAAEBBhHMAAAAAUBDhHAAAAAAURDgHAAAAAAURzgEAAABAQYRzAAAAAFAQ4RwAAAAAFEQ4BwAAAAAFEc4BAAAAQEGEcwAAAABQEOEcAAAAABREOAcAAAAABRHOAQAAAEBBhHMAAAAAUBDhHAAAAAAURDgHAAAAAAURzgEAAABAQYRzAAAAAFAQ4RwAAAAAFEQ4BwAAAAAFEc4BAAAAQEGEcwAAAABQEOEcAAAAABREOAcAAAAABRHOAQAAAEBBhHMAAAAAUBDhHAAAAAAURDgHAAAAAAURzgEAAABAQYRzAAAAAFAQ4RwAAAAAFEQ4BwAAAAAFEc4BAAAAQEGEcwAAAABQEOEcAAAAABREOAcAAAAABRHOAQAAAEBBhHMAAAAAUBDhHAAAAAAURDgHAAAAAAURzgEAAABAQYRzAAAAAFAQ4RwAAAAAFEQ4BwAAAAAFEc4BAAAAQEGEcwAAAABQEOEcAAAAABREOAcAAAAABRHOAQAAAEBBhHMAAAAAUBDhHAAAAAAURDgHAAAAAAURzgEAAABAQYRzAAAAAFAQ4RwAAAAAFEQ4BwAAAAAFEc4BAAAAQEGEcwAAAABQEOEcAAAAABREOAcAAAAABRHOAQAAAEBBhHMAAAAAUBDhHAAAAAAUpNBw7pFHHsnee++dbt26paysLHfeeWet86VSKaeddlrWXHPNtG7dOr17987EiRNrtZkxY0YGDBiQysrKdOjQIYMGDcrs2bNrtXn22WfzrW99K61atcraa6+dCy64YKlabr/99my00UZp1apVNt988/zpT39q9OcFAAAAgE8qNJybM2dOttxyy1x11VXLPH/BBRfkiiuuyIgRI/L444+nbdu26dOnTz766KOaNgMGDMgLL7yQ0aNH55577skjjzySo446quZ8dXV19thjj3Tv3j3jx4/PhRdemOHDh+faa6+tafPYY4/lwAMPzKBBg/LMM8+kX79+6devX55//vkv7+EBAAAAaPbKSqVSqegikqSsrCx33HFH+vXrl+TjUXPdunXLcccdl+OPPz5JMnPmzHTt2jWjRo1K//7989JLL2WTTTbJk08+mZ49eyZJ7r///uy1115555130q1bt1xzzTX55S9/mSlTpqS8vDxJcuKJJ+bOO+/Myy+/nCQ54IADMmfOnNxzzz019eywww7ZaqutMmLEiOWqv7q6Ou3bt8/MmTNTWVnZWB9LoV5//fX0P/zorNv3J6nsslad+1dPeydv3Xt1fnfdiKy33npfQoUAAAAATdPyZkVNds25N998M1OmTEnv3r1rjrVv3z7bb799xo0blyQZN25cOnToUBPMJUnv3r3TokWLPP744zVtdt5555pgLkn69OmTV155Je+//35Nm0/eZ0mbJfdZlnnz5qW6urrWCwAAAADqosmGc1OmTEmSdO3atdbxrl271pybMmVKunTpUut8y5Yt07Fjx1ptlnWNT97js9osOb8s5513Xtq3b1/zWnvttev6iAAAAAA0c002nGvqTjrppMycObPmNXny5KJLAgAAAGAF02TDuaqqqiTJ1KlTax2fOnVqzbmqqqpMmzat1vmFCxdmxowZtdos6xqfvMdntVlyflkqKipSWVlZ6wUAAAAAddFkw7kePXqkqqoqY8aMqTlWXV2dxx9/PL169UqS9OrVKx988EHGjx9f02bs2LFZvHhxtt9++5o2jzzySBYsWFDTZvTo0dlwww2z+uqr17T55H2WtFlyHwAAAAD4MhQazs2ePTsTJkzIhAkTkny8CcSECRPy9ttvp6ysLEOHDs3ZZ5+du+++O88991wOOeSQdOvWrWZH14033jh77rlnjjzyyDzxxBN59NFHM2TIkPTv3z/dunVLkhx00EEpLy/PoEGD8sILL+TWW2/N5ZdfnmHDhtXUccwxx+T+++/PxRdfnJdffjnDhw/PU089lSFDhnzVHwkAAAAAzUjLIm/+1FNPZbfddqt5vyQwGzhwYEaNGpWf//znmTNnTo466qh88MEH2WmnnXL//fenVatWNX1uuummDBkyJLvvvntatGiR/fffP1dccUXN+fbt2+eBBx7I4MGDs+2222aNNdbIaaedlqOOOqqmzTe/+c3cfPPNOeWUU3LyySdn/fXXz5133pnNNtvsK/gUAAAAAGiuykqlUqnoIlYG1dXVad++fWbOnLnSrD/3+uuvp//hR2fdvj9JZZe16ty/eto7eeveq/O760ZkvfXW+xIqBAAAAGialjcrarJrzgEAAADAyk44BwAAAAAFEc4BAAAAQEGEcwAAAABQEOEcAAAAABREOAcAAAAABRHOAQAAAEBBhHMAAAAAUBDhHAAAAAAURDgHAAAAAAURzgEAAABAQYRzAAAAAFAQ4RwAAAAAFEQ4BwAAAAAFEc4BAAAAQEGEcwAAAABQEOEcAAAAABREOAcAAAAABRHOAQAAAEBBhHMAAAAAUBDhHAAAAAAURDgHAAAAAAURzgEAAABAQYRzAAAAAFAQ4RwAAAAAFEQ4BwAAAAAFEc4BAAAAQEGEcwAAAABQEOEcAAAAABREOAcAAAAABRHOAQAAAEBBhHMAAAAAUBDhHAAAAAAURDgHAAAAAAURzgEAAABAQYRzAAAAAFAQ4RwAAAAAFEQ4BwAAAAAFEc4BAAAAQEGEcwAAAABQEOEcAAAAABREOAcAAAAABRHOAQAAAEBBhHMAAAAAUBDhHAAAAAAURDgHAAAAAAURzgEAAABAQYRzAAAAAFAQ4RwAAAAAFEQ4BwAAAAAFEc4BAAAAQEGEcwAAAABQEOEcAAAAABREOAcAAAAABRHOAQAAAEBBhHMAAAAAUBDhHAAAAAAURDgHAAAAAAURzgEAAABAQYRzAAAAAFAQ4RwAAAAAFEQ4BwAAAAAFEc4BAAAAQEGEcwAAAABQEOEcAAAAABREOAcAAAAABRHOAQAAAEBBhHMAAAAAUBDhHAAAAAAURDgHAAAAAAURzgEAAABAQYRzAAAAAFAQ4RwAAAAAFEQ4BwAAAAAFEc4BAAAAQEGEcwAAAABQEOEcAAAAABREOAcAAAAABRHOAQAAAEBBhHMAAAAAUBDhHAAAAAAURDgHAAAAAAURzgEAAABAQYRzAAAAAFAQ4RwAAAAAFEQ4BwAAAAAFEc4BAAAAQEGEcwAAAABQEOEcAAAAABREOAcAAAAABRHOAQAAAEBBhHMAAAAAUBDhHAAAAAAURDgHAAAAAAURzgEAAABAQYRzAAAAAFAQ4RwAAAAAFEQ4BwAAAAAFEc4BAAAAQEGEcwAAAABQEOEcAAAAABSkSYdzixYtyqmnnpoePXqkdevWWW+99XLWWWelVCrVtCmVSjnttNOy5pprpnXr1undu3cmTpxY6zozZszIgAEDUllZmQ4dOmTQoEGZPXt2rTbPPvtsvvWtb6VVq1ZZe+21c8EFF3wlzwgAAABA89Wkw7nzzz8/11xzTa688sq89NJLOf/883PBBRfkV7/6VU2bCy64IFdccUVGjBiRxx9/PG3btk2fPn3y0Ucf1bQZMGBAXnjhhYwePTr33HNPHnnkkRx11FE156urq7PHHnuke/fuGT9+fC688MIMHz4811577Vf6vAAAAAA0Ly2LLuDzPPbYY9l3333Tt2/fJMm6666bW265JU888USSj0fNXXbZZTnllFOy7777Jkl++9vfpmvXrrnzzjvTv3//vPTSS7n//vvz5JNPpmfPnkmSX/3qV9lrr71y0UUXpVu3brnpppsyf/78XHfddSkvL8+mm26aCRMm5JJLLqkV4gEAAABAY2rSI+e++c1vZsyYMXn11VeTJP/4xz/yt7/9Ld/5zneSJG+++WamTJmS3r171/Rp3759tt9++4wbNy5JMm7cuHTo0KEmmEuS3r17p0WLFnn88cdr2uy8884pLy+vadOnT5+88soref/995dZ27x581JdXV3rBQAAAAB10aRHzp144omprq7ORhttlFVWWSWLFi3KOeeckwEDBiRJpkyZkiTp2rVrrX5du3atOTdlypR06dKl1vmWLVumY8eOtdr06NFjqWssObf66qsvVdt5552XM844oxGeEgAAAIDmqkmPnLvtttty00035eabb87TTz+d66+/PhdddFGuv/76okvLSSedlJkzZ9a8Jk+eXHRJAAAAAKxgmvTIuRNOOCEnnnhi+vfvnyTZfPPNM2nSpJx33nkZOHBgqqqqkiRTp07NmmuuWdNv6tSp2WqrrZIkVVVVmTZtWq3rLly4MDNmzKjpX1VVlalTp9Zqs+T9kjafVlFRkYqKioY/JAAAAADNVpMeOTd37ty0aFG7xFVWWSWLFy9OkvTo0SNVVVUZM2ZMzfnq6uo8/vjj6dWrV5KkV69e+eCDDzJ+/PiaNmPHjs3ixYuz/fbb17R55JFHsmDBgpo2o0ePzoYbbrjMKa0AAAAA0BiadDi3995755xzzsm9996bt956K3fccUcuueSSfO9730uSlJWVZejQoTn77LNz991357nnnsshhxySbt26pV+/fkmSjTfeOHvuuWeOPPLIPPHEE3n00UczZMiQ9O/fP926dUuSHHTQQSkvL8+gQYPywgsv5NZbb83ll1+eYcOGFfXoAAAAADQDTXpa669+9auceuqp+clPfpJp06alW7du+c///M+cdtppNW1+/vOfZ86cOTnqqKPywQcfZKeddsr999+fVq1a1bS56aabMmTIkOy+++5p0aJF9t9//1xxxRU159u3b58HHngggwcPzrbbbps11lgjp512Wo466qiv9HkBAAAAaF7KSqVSqegiVgbV1dVp3759Zs6cmcrKyqLLaRSvv/56+h9+dNbt+5NUdlmrzv2rp72Tt+69Or+7bkTWW2+9L6FCAAAAgKZpebOiJj2tFQAAAABWZsI5AAAAACiIcA4AAAAACiKcAwAAAICCCOcAAAAAoCDCOQAAAAAoiHAOAAAAAAoinAMAAACAggjnAAAAAKAgwjkAAAAAKIhwDgAAAAAKIpwDAAAAgIII5wAAAACgIMI5AAAAACiIcA4AAAAACiKcAwAAAICCCOcAAAAAoCDCOQAAAAAoiHAOAAAAAAoinAMAAACAggjnAAAAAKAgwjkAAAAAKIhwDgAAAAAKIpwDAAAAgIII5wAAAACgIMI5AAAAACiIcA4AAAAACiKcAwAAAICCCOcAAAAAoCDCOQAAAAAoiHAOAAAAAAoinAMAAACAggjnAAAAAKAgwjkAAAAAKIhwDgAAAAAKIpwDAAAAgIII5wAAAACgIMI5AAAAACiIcA4AAAAACiKcAwAAAICCCOcAAAAAoCDCOQAAAAAoiHAOAAAAAAoinAMAAACAggjnAAAAAKAgwjkAAAAAKIhwDgAAAAAKIpwDAAAAgIII5wAAAACgIMI5AAAAACiIcA4AAAAACiKcAwAAAICCCOcAAAAAoCDCOQAAAAAoiHAOAAAAAAoinAMAAACAggjnAAAAAKAgwjkAAAAAKIhwDgAAAAAKIpwDAAAAgIII5wAAAACgIPUK5954443GrgMAAAAAmp16hXNf//rXs9tuu+XGG2/MRx991Ng1AQAAAECzUK9w7umnn84WW2yRYcOGpaqqKv/5n/+ZJ554orFrAwAAAICVWr3Cua222iqXX3553n333Vx33XV57733stNOO2WzzTbLJZdckunTpzd2nQAAAACw0mnQhhAtW7bMfvvtl9tvvz3nn39+XnvttRx//PFZe+21c8ghh+S9995rrDoBAAAAYKXToHDuqaeeyk9+8pOsueaaueSSS3L88cfn9ddfz+jRo/Puu+9m3333baw6AQAAAGCl07I+nS655JKMHDkyr7zySvbaa6/89re/zV577ZUWLT7O+nr06JFRo0Zl3XXXbcxaAQAAAGClUq9w7pprrsnhhx+eQw89NGuuueYy23Tp0iW/+c1vGlQcAAAAAKzM6hXOTZw48QvblJeXZ+DAgfW5PAAAAAA0C/Vac27kyJG5/fbblzp+++235/rrr29wUQAAAADQHNQrnDvvvPOyxhprLHW8S5cuOffccxtcFAAAAAA0B/UK595+++306NFjqePdu3fP22+/3eCiAAAAAKA5qFc416VLlzz77LNLHf/HP/6RTp06NbgoAAAAAGgO6hXOHXjggfnZz36WBx98MIsWLcqiRYsyduzYHHPMMenfv39j1wgAAAAAK6V67dZ61lln5a233sruu++eli0/vsTixYtzyCGHWHMOAAAAAJZTvcK58vLy3HrrrTnrrLPyj3/8I61bt87mm2+e7t27N3Z9AAAAALDSqlc4t8QGG2yQDTbYoLFqAQAAAIBmpV7h3KJFizJq1KiMGTMm06ZNy+LFi2udHzt2bKMUBwAAAAArs3qFc8ccc0xGjRqVvn37ZrPNNktZWVlj1wUAAAAAK716hXO/+93vctttt2WvvfZq7HoAAAAAoNloUZ9O5eXl+frXv97YtQAAAABAs1KvcO64447L5ZdfnlKp1Nj1AAAAAECzUa9prX/729/y4IMP5r777summ26aVVddtdb5P/7xj41SHAAAAACszOoVznXo0CHf+973GrsWAAAAAGhW6hXOjRw5srHrAAAAAIBmp15rziXJwoUL85e//CX//d//nVmzZiVJ3n333cyePbvRigMAAACAlVm9Rs5NmjQpe+65Z95+++3Mmzcv//Ef/5F27drl/PPPz7x58zJixIjGrhMAAAAAVjr1Gjl3zDHHpGfPnnn//ffTunXrmuPf+973MmbMmEYrDgAAAABWZvUaOffXv/41jz32WMrLy2sdX3fddfPPf/6zUQoDAAAAgJVdvUbOLV68OIsWLVrq+DvvvJN27do1uCgAAAAAaA7qFc7tscceueyyy2rel5WVZfbs2Tn99NOz1157NVZtAAAAALBSq9e01osvvjh9+vTJJptsko8++igHHXRQJk6cmDXWWCO33HJLY9cIAAAAACuleoVza621Vv7xj3/kd7/7XZ599tnMnj07gwYNyoABA2ptEAEAAAAAfLZ6hXNJ0rJlyxx88MGNWQsAAAAANCv1Cud++9vffu75Qw45pF7FAAAAAEBzUq9w7phjjqn1fsGCBZk7d27Ky8vTpk0b4RwAAAAALId67db6/vvv13rNnj07r7zySnbaaScbQgAAAADAcqpXOLcs66+/fv7rv/5rqVF1AAAAAMCyNVo4l3y8ScS7777bmJcEAAAAgJVWvdacu/vuu2u9L5VKee+993LllVdmxx13bJTCAAAAAGBlV6+Rc/369av12m+//TJ8+PBsscUWue666xq1wH/+8585+OCD06lTp7Ru3Tqbb755nnrqqZrzpVIpp512WtZcc820bt06vXv3zsSJE2tdY8aMGRkwYEAqKyvToUOHDBo0KLNnz67V5tlnn823vvWttGrVKmuvvXYuuOCCRn0OAAAAAPi0eo2cW7x4cWPXsUzvv/9+dtxxx+y2226577770rlz50ycODGrr756TZsLLrggV1xxRa6//vr06NEjp556avr06ZMXX3wxrVq1SpIMGDAg7733XkaPHp0FCxbksMMOy1FHHZWbb745SVJdXZ099tgjvXv3zogRI/Lcc8/l8MMPT4cOHXLUUUd9Jc8KAAAAQPNTr3Duq3L++edn7bXXzsiRI2uO9ejRo+b/l0qlXHbZZTnllFOy7777Jkl++9vfpmvXrrnzzjvTv3//vPTSS7n//vvz5JNPpmfPnkmSX/3qV9lrr71y0UUXpVu3brnpppsyf/78XHfddSkvL8+mm26aCRMm5JJLLvnMcG7evHmZN29ezfvq6uov4yMAAAAAYCVWr3Bu2LBhy932kksuqc8tkny8tl2fPn3ygx/8IA8//HC+9rWv5Sc/+UmOPPLIJMmbb76ZKVOmpHfv3jV92rdvn+233z7jxo1L//79M27cuHTo0KEmmEuS3r17p0WLFnn88cfzve99L+PGjcvOO++c8vLymjZ9+vTJ+eefn/fff7/WSL0lzjvvvJxxxhn1fjYAAAAAqFc498wzz+SZZ57JggULsuGGGyZJXn311ayyyirZZpttatqVlZU1qLg33ngj11xzTYYNG5aTTz45Tz75ZH72s5+lvLw8AwcOzJQpU5IkXbt2rdWva9euNeemTJmSLl261DrfsmXLdOzYsVabT47I++Q1p0yZssxw7qSTTqoVUlZXV2fttddu0PMCAAAA0LzUK5zbe++9065du1x//fU1wdX777+fww47LN/61rdy3HHHNUpxixcvTs+ePXPuuecmSbbeeus8//zzGTFiRAYOHNgo96ivioqKVFRUFFoDAAAAACu2eu3WevHFF+e8886rNaJs9dVXz9lnn52LL7640Ypbc801s8kmm9Q6tvHGG+ftt99OklRVVSVJpk6dWqvN1KlTa85VVVVl2rRptc4vXLgwM2bMqNVmWdf45D0AAAAAoLHVK5yrrq7O9OnTlzo+ffr0zJo1q8FFLbHjjjvmlVdeqXXs1VdfTffu3ZN8vDlEVVVVxowZU6u2xx9/PL169UqS9OrVKx988EHGjx9f02bs2LFZvHhxtt9++5o2jzzySBYsWFDTZvTo0dlwww2XOaUVAAAAABpDvcK5733veznssMPyxz/+Me+8807eeeed/OEPf8igQYOy3377NVpxxx57bP7+97/n3HPPzWuvvZabb7451157bQYPHpzk4zXthg4dmrPPPjt33313nnvuuRxyyCHp1q1b+vXrl+TjkXZ77rlnjjzyyDzxxBN59NFHM2TIkPTv3z/dunVLkhx00EEpLy/PoEGD8sILL+TWW2/N5ZdfXqeNLwAAAACgruq15tyIESNy/PHH56CDDqoZbdayZcsMGjQoF154YaMVt9122+WOO+7ISSedlDPPPDM9evTIZZddlgEDBtS0+fnPf545c+bkqKOOygcffJCddtop999/f1q1alXT5qabbsqQIUOy++67p0WLFtl///1zxRVX1Jxv3759HnjggQwePDjbbrtt1lhjjZx22mk56qijGu1ZAAAAAODTykqlUqm+nefMmZPXX389SbLeeuulbdu2jVbYiqa6ujrt27fPzJkzU1lZWXQ5jeL1119P/8OPzrp9f5LKLmvVuX/1tHfy1r1X53fXjch66633JVQIAAAA0DQtb1ZUr2mtS7z33nt57733sv7666dt27ZpQM4HAAAAAM1OvcK5f//739l9992zwQYbZK+99sp7772XJBk0aFCOO+64Ri0QAAAAAFZW9Qrnjj322Ky66qp5++2306ZNm5rjBxxwQO6///5GKw4AAAAAVmb12hDigQceyJ///OestVbtdcjWX3/9TJo0qVEKAwAAAICVXb1Gzs2ZM6fWiLklZsyYkYqKigYXBQAAAADNQb3CuW9961v57W9/W/O+rKwsixcvzgUXXJDddtut0YoDAAAAgJVZvaa1XnDBBdl9993z1FNPZf78+fn5z3+eF154ITNmzMijjz7a2DUCAAAAwEqpXiPnNttss7z66qvZaaedsu+++2bOnDnZb7/98swzz2S99dZr7BoBAAAAYKVU55FzCxYsyJ577pkRI0bkl7/85ZdREwAAAAA0C3UeObfqqqvm2Wef/TJqAQAAAIBmpV7TWg8++OD85je/aexaAAAAAKBZqdeGEAsXLsx1112Xv/zlL9l2223Ttm3bWucvueSSRikOAAAAAFZmdQrn3njjjay77rp5/vnns8022yRJXn311VptysrKGq86AAAAAFiJ1SmcW3/99fPee+/lwQcfTJIccMABueKKK9K1a9cvpTgAAAAAWJnVac25UqlU6/19992XOXPmNGpBAAAAANBc1GtDiCU+HdYBAAAAAMuvTuFcWVnZUmvKWWMOAAAAAOqnTmvOlUqlHHrooamoqEiSfPTRRzn66KOX2q31j3/8Y+NVCAAAAAArqTqFcwMHDqz1/uCDD27UYgAAAACgOalTODdy5Mgvqw4AAAAAaHYatCEEAAAAAFB/wjkAAAAAKIhwDgAAAAAKIpwDAAAAgIII5wAAAACgIMI5AAAAACiIcA4AAAAACiKcAwAAAICCCOcAAAAAoCDCOQAAAAAoiHAOAAAAAAoinAMAAACAggjnAAAAAKAgwjkAAAAAKIhwDgAAAAAKIpwDAAAAgIII5wAAAACgIMI5AAAAACiIcA4AAAAACiKcAwAAAICCCOcAAAAAoCDCOQAAAAAoiHAOAAAAAAoinAMAAACAggjnAAAAAKAgwjkAAAAAKIhwDgAAAAAKIpwDAAAAgIII5wAAAACgIMI5AAAAACiIcA4AAAAACiKcAwAAAICCCOcAAAAAoCDCOQAAAAAoiHAOAAAAAAoinAMAAACAggjnAAAAAKAgwjkAAAAAKIhwDgAAAAAKIpwDAAAAgIII5wAAAACgIMI5AAAAACiIcA4AAAAACiKcAwAAAICCCOcAAAAAoCDCOQAAAAAoiHAOAAAAAAoinAMAAACAggjnAAAAAKAgwjkAAAAAKIhwDgAAAAAKIpwDAAAAgIII5wAAAACgIMI5AAAAACiIcA4AAAAACiKcAwAAAICCCOcAAAAAoCDCOQAAAAAoiHAOAAAAAAoinAMAAACAggjnAAAAAKAgwjkAAAAAKIhwDgAAAAAKIpwDAAAAgIII5wAAAACgIMI5AAAAACiIcA4AAAAACiKcAwAAAICCCOcAAAAAoCDCOQAAAAAoiHAOAAAAAAoinAMAAACAggjnAAAAAKAgwjkAAAAAKIhwDgAAAAAKIpwDAAAAgIII5wAAAACgIMI5AAAAACiIcA4AAAAACiKcAwAAAICCrFDh3H/913+lrKwsQ4cOrTn20UcfZfDgwenUqVNWW2217L///pk6dWqtfm+//Xb69u2bNm3apEuXLjnhhBOycOHCWm0eeuihbLPNNqmoqMjXv/71jBo16it4IgAAAACasxUmnHvyySfz3//939liiy1qHT/22GPzv//7v7n99tvz8MMP5913381+++1Xc37RokXp27dv5s+fn8ceeyzXX399Ro0aldNOO62mzZtvvpm+fftmt912y4QJEzJ06NAcccQR+fOf//yVPR8AAAAAzc8KEc7Nnj07AwYMyP/8z/9k9dVXrzk+c+bM/OY3v8kll1ySb3/729l2220zcuTIPPbYY/n73/+eJHnggQfy4osv5sYbb8xWW22V73znOznrrLNy1VVXZf78+UmSESNGpEePHrn44ouz8cYbZ8iQIfn+97+fSy+9tJDnBQAAAKB5WCHCucGDB6dv377p3bt3rePjx4/PggULah3faKONss4662TcuHFJknHjxmXzzTdP165da9r06dMn1dXVeeGFF2rafPraffr0qbnGssybNy/V1dW1XgAAAABQFy2LLuCL/O53v8vTTz+dJ598cqlzU6ZMSXl5eTp06FDreNeuXTNlypSaNp8M5pacX3Lu89pUV1fnww8/TOvWrZe693nnnZczzjij3s8FAAAAAE165NzkyZNzzDHH5KabbkqrVq2KLqeWk046KTNnzqx5TZ48ueiSAAAAAFjBNOlwbvz48Zk2bVq22WabtGzZMi1btszDDz+cK664Ii1btkzXrl0zf/78fPDBB7X6TZ06NVVVVUmSqqqqpXZvXfL+i9pUVlYuc9RcklRUVKSysrLWCwAAAADqokmHc7vvvnuee+65TJgwoebVs2fPDBgwoOb/r7rqqhkzZkxNn1deeSVvv/12evXqlSTp1atXnnvuuUybNq2mzejRo1NZWZlNNtmkps0nr7GkzZJrAAAAAMCXoUmvOdeuXbtsttlmtY61bds2nTp1qjk+aNCgDBs2LB07dkxlZWV++tOfplevXtlhhx2SJHvssUc22WST/OhHP8oFF1yQKVOm5JRTTsngwYNTUVGRJDn66KNz5ZVX5uc//3kOP/zwjB07Nrfddlvuvffer/aBAQAAAGhWmnQ4tzwuvfTStGjRIvvvv3/mzZuXPn365Oqrr645v8oqq+See+7Jj3/84/Tq1Stt27bNwIEDc+aZZ9a06dGjR+69994ce+yxufzyy7PWWmvl17/+dfr06VPEIwEAAADQTKxw4dxDDz1U632rVq1y1VVX5aqrrvrMPt27d8+f/vSnz73urrvummeeeaYxSgQAAACA5dKk15wDAAAAgJWZcA4AAAAACiKcAwAAAICCCOcAAAAAoCDCOQAAAAAoiHAOAAAAAAoinAMAAACAggjnAAAAAKAgwjkAAAAAKIhwDgAAAAAKIpwDAAAAgIII5wAAAACgIMI5AAAAACiIcA4AAAAACiKcAwAAAICCCOcAAAAAoCDCOQAAAAAoiHAOAAAAAAoinAMAAACAggjnAAAAAKAgwjkAAAAAKIhwDgAAAAAKIpwDAAAAgIII5wAAAACgIMI5AAAAACiIcA4AAAAACiKcAwAAAICCCOcAAAAAoCDCOQAAAAAoiHAOAAAAAAoinAMAAACAggjnAAAAAKAgwjkAAAAAKIhwDgAAAAAKIpwDAAAAgIII5wAAAACgIMI5AAAAACiIcA4AAAAACiKcAwAAAICCCOcAAAAAoCDCOQAAAAAoiHAOAAAAAAoinAMAAACAggjnAAAAAKAgwjkAAAAAKIhwDgAAAAAKIpwDAAAAgIII5wAAAACgIMI5AAAAACiIcA4AAAAACiKcAwAAAICCCOcAAAAAoCDCOQAAAAAoiHAOAAAAAAoinAMAAACAggjnAAAAAKAgwjkAAAAAKIhwDgAAAAAKIpwDAAAAgIII5wAAAACgIMI5AAAAACiIcA4AAAAACiKcAwAAAICCCOcAAAAAoCDCOQAAAAAoiHAOAAAAAAoinAMAAACAggjnAAAAAKAgwjkAAAAAKIhwDgAAAAAKIpwDAAAAgIII5wAAAACgIMI5AAAAACiIcA4AAAAACtKy6AIAAABWRNOnT091dXWDrlFZWZnOnTs3UkUArIiEcwAAAHU0ffr0HHzYEZkxa26DrtOxXZvcOPLXAjqAZkw4BwAAUEfV1dWZMWtuOvfaP207dq3XNebMmJrp4/6Q6urqeodzDR29Z+QeQPGEcwAAQLPUkGBr0qRJWbhgYdp27JrKLmvVv4Z692yc0XtG7gEUTzgHAAA0Ow0Ntj76cG7e+ed7WWfBgkaubPk1dPReUxi5lxi9ByCcAwAAmp2GBlvTXn8+kyZfl0ULiwvnlmjI6L2iR+4lRu8BCOcAAIBmq77B1ux/T2mU+y+YPz+TJk2qV98lU2uL0lTW3QNY0QnnAACAQjT3zQzmzZ6Zt958I0NPHp6Kioo6928KU2uTho3cSxo2eg9gZSCcAwAAvnKNMSVytfJVcv45Z6ZTp0517lv0qLMkWTDvwywua5k1dtgvnbp1r3P/pjS1FoD6E84BAABfuYZOiZzxzmsZf9sVOeJnx6/Qo86SpM3qnQudWlu0hkztTVb8EZQAwjkAAKAwDVnzzaizhit6zbuGTu1NbCgBrPiEcwAAwAqruY86a4imsOZdQ6f22lACWBkI5wAAAJqhprTmXX1D1iR517RYYAUnnAMAAOqsoTutNoUNGfjYijz60LRYYGUgnAMAAOqkMXZabUobMrDiMi0WWBkI5wAAgDpp6E6riQ0ZaFwNmRY7vZFrAagr4RwAAFAv9d1pNWkaUyIBoCloUXQBAAAAANBcCecAAAAAoCCmtQIAQDPUkN1W7bQKAI1HOAcAAM1MQ3dbtdMqADQe4RwAADQzDd1t1U6rrEwWzJ+fSZMm1bt/ZWVlOnfu3IgVAc2NcA4AAJqp+u62aqdVVhbzZs/MW2++kaEnD09FRUW9rtGxXZvcOPLXAjqg3oRzAAAANEsL5n2YxWUts8YO+6VTt+517j9nxtS8+/Atee6559K9e937L2H0HTRvwjkAAFgB2dABGk+b1TvXaxRpY4y8S4y+g+ZOOAcAACsYGzpA09DQkXfJx6Pvpo/7Q6qrq4Vz0EwJ5wAAYAVjQwdoWuo78m6J6Y1YC7DiaVF0AZ/nvPPOy3bbbZd27dqlS5cu6devX1555ZVabT766KMMHjw4nTp1ymqrrZb9998/U6dOrdXm7bffTt++fdOmTZt06dIlJ5xwQhYurD2M/6GHHso222yTioqKfP3rX8+oUaO+7McDAIAGWbKhQ11fbTqsUXTpAMD/r0mPnHv44YczePDgbLfddlm4cGFOPvnk7LHHHnnxxRfTtm3bJMmxxx6be++9N7fffnvat2+fIUOGZL/99sujjz6aJFm0aFH69u2bqqqqPPbYY3nvvfdyyCGHZNVVV825556bJHnzzTfTt2/fHH300bnpppsyZsyYHHHEEVlzzTXTp0+fwp4fAACAld+C+fMzadKkeve3oQSs2Jp0OHf//ffXej9q1Kh06dIl48ePz84775yZM2fmN7/5TW6++eZ8+9vfTpKMHDkyG2+8cf7+979nhx12yAMPPJAXX3wxf/nLX9K1a9dstdVWOeuss/KLX/wiw4cPT3l5eUaMGJEePXrk4osvTpJsvPHG+dvf/pZLL71UOAcAAMCXpjE2lbChBKzYmnQ492kzZ85MknTs2DFJMn78+CxYsCC9e/euabPRRhtlnXXWybhx47LDDjtk3Lhx2XzzzdO16/+txdGnT5/8+Mc/zgsvvJCtt94648aNq3WNJW2GDh36mbXMmzcv8+bNq3lf352yAAAAaL4auqmEDSVgxbfChHOLFy/O0KFDs+OOO2azzTZLkkyZMiXl5eXp0KFDrbZdu3bNlClTatp8Mphbcn7Juc9rU11dnQ8//DCtW7deqp7zzjsvZ5xxRqM8GwAAAM1bQzaVsKEErNia9IYQnzR48OA8//zz+d3vfld0KUmSk046KTNnzqx5TZ48ueiSAAAAAFjBrBAj54YMGZJ77rknjzzySNZa6//+JqGqqirz58/PBx98UGv03NSpU1NVVVXT5oknnqh1vSW7uX6yzad3eJ06dWoqKyuXOWouSSoqKuq9HgAAAAAAJE185FypVMqQIUNyxx13ZOzYsenRo0et89tuu21WXXXVjBkzpubYK6+8krfffju9evVKkvTq1SvPPfdcpk2bVtNm9OjRqayszCabbFLT5pPXWNJmyTUAAAAA4MvQpEfODR48ODfffHPuuuuutGvXrmaNuPbt26d169Zp3759Bg0alGHDhqVjx46prKzMT3/60/Tq1Ss77LBDkmSPPfbIJptskh/96Ee54IILMmXKlJxyyikZPHhwzci3o48+OldeeWV+/vOf5/DDD8/YsWNz22235d577y3s2QEAAGB5LJg/P5MmTap3/8rKSptJQIGadDh3zTXXJEl23XXXWsdHjhyZQw89NEly6aWXpkWLFtl///0zb9689OnTJ1dffXVN21VWWSX33HNPfvzjH6dXr15p27ZtBg4cmDPPPLOmTY8ePXLvvffm2GOPzeWXX5611lorv/71r9OnT58v/RkBAACgvubNnpm33nwjQ08eXu+llzq2a5MbR/5aQAcFadLhXKlU+sI2rVq1ylVXXZWrrrrqM9t07949f/rTnz73OrvuumueeeaZOtcIAAAARVkw78MsLmuZNXbYL526da9z/zkzpmb6uD+kurpaOAcFadLhHAAArKymT5+e6urqevWdNGlSFi5Y2MgVASuyNqt3TmWXtb644TJMb+RagLoRzgEAwFds+vTpOfiwIzJj1tx69f/ow7l555/vZZ0FCxq5MgDgqyacAwCAr1h1dXVmzJqbzr32T9uOXevcf9rrz2fS5OuyaKFwDgBWdMI5AAAoSNuOXes1DW32v6d8CdUAzZXdXqFYwjkAAABopuz2CsUTzgEAAEAzZbdXKJ5wDgAA6qghO60mdlsFmh67vUJxhHMAAFAHDd1pNbHbKgDwf4RzAABQBw3daTWx2yoA8H+EcwAAUA/13Wk1sdsqAPB/WhRdAAAAAAA0V8I5AAAAACiIcA4AAAAACmLNOQAAAGCFNn369FRXV9e7f2VlZTp37tyIFcHyE84BAAAA9bZg/vxMmjSpQddoSDg2ffr0HHzYEZkxa26979+xXZvcOPLXAjoKIZwDAKDZacgIi0mTJmXhgoWNXBHAimne7Jl56803MvTk4amoqKj3dVYrXyXnn3NmOnXqVOe+kyZNyrQZ1Vlz5wPStmPXOvefM2Nqpo/7Q6qrq4VzFEI4BwBAs9LQERYffTg37/zzvayzYEEjVwaw4lkw78MsLmuZNXbYL526da/XNWa881rG33ZFjvjZ8fUK+Gr+XG7XMZVd1qpXDdPr1Qsah3AOAIBmpbq6OjNmzU3nXvvXa4TFtNefz6TJ12XRQuEcwBJtVu9c72Bs9r+nNCjg8+cyKzrhHAAAzVLbjl3r9Yvk7H9P+RKqAaC+AZ8/l1nRtSi6AAAAAABoroRzAAAAAFAQ4RwAAAAAFEQ4BwAAAAAFsSEEAAArnOnTp6e6urpefSdNmpSFCxY2ckUAAPUjnAMAYIUyffr0HHzYEZkxa269+n/04dy888/3ss6CBY1cGQBA3QnnAABYoVRXV2fGrLnp3Gv/tO3Ytc79p73+fCZNvi6LFgrnAIDiCecAAFghte3YNZVd1qpzv9n/nvIlVAMAUD82hAAAAACAggjnAAAAAKAgwjkAAAAAKIhwDgAAAAAKIpwDAAAAgIII5wAAAACgIMI5AAAAACiIcA4AAAAACtKy6AIAAGh+pk+fnurq6nr1nTRpUhYuWNjIFQEAFEM4BwDAV2r69Ok5+LAjMmPW3Hr1/+jDuXnnn+9lnQULGrkyAICvnnAOAIA6aciot+TjkW/TZlRnzZ0PSNuOXevcf9rrz2fS5OuyaKFwDoDGsWD+/EyaNKlB16isrEznzp0bqSKaE+EcAADLraGj3pJPjHxr1zGVXdaqc//Z/55S73sDwKfNmz0zb735RoaePDwVFRX1vk7Hdm1y48hfC+ioM+EcAADLrbq6OjNmzU3nXvvXa9RbYuQbAE3LgnkfZnFZy6yxw37p1K17va4xZ8bUTB/3h1RXVwvnqDPhHAAAdda2Y9d6jXpLjHwDoGlqs3rnev+7LUmmN2ItNC8tii4AAAAAAJor4RwAAAAAFEQ4BwAAAAAFseYcAAAAwApu+vTpqa6urnf/yspKm1kURDgHAAAAsAKbPn16Dj7siMyYNbfe11itfJWcf86Z6dSpU72vIeCrH+EcAEAz05C/WZ80aVIWLljYyBUBAA1RXV2dGbPmpnOv/dO2Y9c695/xzmsZf9sVOeJnx6eioqLedXRs1yY3jvy1gK6OhHMAAM1IQ/9m/aMP5+adf76XdRYsaOTKAICGatuxayq7rFXnfrP/PSWLy1pmjR32S6du3et17zkzpmb6uD+kurpaOFdHwjkAgGakoX+zPu315zNp8nVZtFA4BwArmzard65XuLfEu/PnZ9KkSfXu31ynxQrnAABWMI0xLbUhf7MOADS+FX3ZiXmzZ+atN9/I0JOH13tqbHOdFiucAwBYgZiWCgArn5Xh3+8L5n3YoKmxzXlarHAOAGAFYloqAKx8VqZ/vzdkauz0Rq5lRSGcAwBYAZmWCgArH/9+b56EcwAAX6GGrCeTNI01ZQAAaDzCOQCAr0hD15NJmsaaMgAANB7hHADAV6Sh68kkTWtNGQAAGk44BwDwFavvejKJNWUAAFY2LYouAAAAAACaKyPnAADqoCEbOtjMAQCATxPOAQAsp4Zu6GAzBwAAPk04BwCwnBq6oYPNHAAA+DThHABAHdV3QwebOQAA8GnCOQAAAIAGWjB/fiZNmlSvvtalbd6EcwBAs2JDBwCgsc2bPTNvvflGhp48PBUVFXXub13a5k04x0qvIb+EJUllZWU6d+7ciBUBUBQbOgAAX4YF8z7M4rKWWWOH/dKpW/c697cubfMmnGOl1tBfwpKkY7s2uXHkrwV0ACsBGzoAAF+mNqt3ti4tdSacY6XW0F/C5syYmunj/pDq6mrhHMBKxIYOAAA0FcI5moX6/hKWJNMbuRYAAACAJVoUXQAAAAAANFdGzgEAX5mGbtKTJPPnz095eXm9+tptFQCApkY4BwB8JRpjk54F8+fnn29Pylrde6TlqnX/zxi7rQIA0NQI5wCA5daQkW+TJk3KtBnVWXPnA+q1SU/y8W6pb7x1XVb/xr7p1K17vfrbbRUAgKZEOAcALJeGjnyrGbXWrmO9N+lZsltqm9U7220VAICVgnAOAFgu1dXVmTFrbjr32r9eI9+MWgMAgKUJ5wCAOmnbsatRawAA0EiEcwDQjDR0zTg7nQIAQOMSzgFAM9Foa8bZ6RQAABqNcA4AViBF7pZqzTgAAGh8wjkAWEEUvVuqNeMAAKDxCecAYDk1ZNRaklRWVqZz58717m+3VAAAWPkI5wBgOTR01FqSdGzXJjeO/HWDArrEbqkAALAyEc4B0GwUuV7bnBlT8+7Dt+S5555L9+7d612D3VIBAGDlIpyDL1lDp8ElDZ8K11BFT+WDxlD0em3zZs/MW2++kaEnD09FRUXDarBbKgAArDSEc/AlaoxpcEnjTYWrj6Y0lY9ireghbdHrtS2Y92EWl7XMGjvsl07d6jdyzppxAACw8hHOwZeooWFA8vFUuOnj/pDq6upCgo2GPkPR9dM4GiOkXa18lZx/zpnp1KlTva/RGAFf0eu1tVm9c73u35g1AAAATYdwDr4C9Q0DlpjeiLXUV0OeoSnUT8M0NKSd8c5rGX/bFTniZ8fXe0pnYhQmAACw8hHOAawgmsK00oaMOmvolM6GbqhgMwUAAKApEs4BrABWlrX/GjKls6EbKthMAQAAaIqEc8AKoSmMGiuStf8avqGCzRQAAICmSDgHNHkry6ixxmDtv/qPvrOZAgAA0BQJ52AFsGD+/EyaNKne/Y0aa9haZUnDP8OGjvxrjPXSGvI9sl4bAADAl0M4B01cQ9fZSowaK/ozbIyRfw1dL816bQAAAE2TcA6auIaus7UyrDXWUEV/hg0d+Zc0fL0067UBAAA0TcI5WEE0ZJfLlWWtsYZqyGf4biNMCW3IenGNtV6a9doAAACaFuEcwBcwJRQAAIAvi3AO4AuYEgoAAMCXRTgHfOkauttsU9kp1JRQAAAAGptwDvhSNcZOqaaFAgAAsLISzgFfqoZOCU1MCwUAAGDlJZwDvhIN2SnVtFAAAABWVi2KLgAAAAAAmivh3KdcddVVWXfdddOqVatsv/32eeKJJ4ouCQAAAICVlHDuE2699dYMGzYsp59+ep5++ulsueWW6dOnT6ZNm1Z0aQAAAACshIRzn3DJJZfkyCOPzGGHHZZNNtkkI0aMSJs2bXLdddcVXRoAAAAAKyEbQvz/5s+fn/Hjx+ekk06qOdaiRYv07t0748aNW6r9vHnzMm/evJr3M2fOTJJUV1d/+cV+RWbNmpVFCxfmg/feyoKP5ta5/5z3p2Xehx/mxRdfzKxZs76ECr/Y5MmTM/+jjwp7hobeP0mqp72T0uLFqZ4yOS3L6t6/6GdoaP2NcY0VvX9TqKHo/k2hhqL7N4Uaiu7fFGooun9TqMEz+Awao39TqKHo/k2hhqL7N4Uaiu7fFGooun9TqMEzNI3PYM7707Jo4cLMmjVrpclWljxHqVT63HZlpS9q0Uy8++67+drXvpbHHnssvXr1qjn+85//PA8//HAef/zxWu2HDx+eM84446suEwAAAIAVyOTJk7PWWmt95nkj5+rppJNOyrBhw2reL168ODNmzEinTp1SVlbPmLmJqa6uztprr53JkyensrKy6HJopnwPaQp8Dyma7yBNge8hTYHvIU2B7yHLq1QqZdasWenWrdvnthPO/f/WWGONrLLKKpk6dWqt41OnTk1VVdVS7SsqKlJRUVHrWIcOHb7MEgtTWVnpDxwK53tIU+B7SNF8B2kKfA9pCnwPaQp8D1ke7du3/8I2NoT4/5WXl2fbbbfNmDFjao4tXrw4Y8aMqTXNFQAAAAAai5FznzBs2LAMHDgwPXv2zDe+8Y1cdtllmTNnTg477LCiSwMAAABgJSSc+4QDDjgg06dPz2mnnZYpU6Zkq622yv3335+uXbsWXVohKioqcvrppy81fRe+Sr6HNAW+hxTNd5CmwPeQpsD3kKbA95DGZrdWAAAAACiINecAAAAAoCDCOQAAAAAoiHAOAAAAAAoinAMAAACAggjnWKarrroq6667blq1apXtt98+TzzxRNEl0Yycd9552W677dKuXbt06dIl/fr1yyuvvFJ0WTRz//Vf/5WysrIMHTq06FJoZv75z3/m4IMPTqdOndK6detsvvnmeeqpp4oui2Zk0aJFOfXUU9OjR4+0bt066623Xs4666zYV44v0yOPPJK999473bp1S1lZWe68885a50ulUk477bSsueaaad26dXr37p2JEycWUywrpc/7Di5YsCC/+MUvsvnmm6dt27bp1q1bDjnkkLz77rvFFcwKTTjHUm699dYMGzYsp59+ep5++ulsueWW6dOnT6ZNm1Z0aTQTDz/8cAYPHpy///3vGT16dBYsWJA99tgjc+bMKbo0mqknn3wy//3f/50tttii6FJoZt5///3suOOOWXXVVXPfffflxRdfzMUXX5zVV1+96NJoRs4///xcc801ufLKK/PSSy/l/PPPzwUXXJBf/epXRZfGSmzOnDnZcsstc9VVVy3z/AUXXJArrrgiI0aMyOOPP562bdumT58++eijj77iSllZfd53cO7cuXn66adz6qmn5umnn84f//jHvPLKK9lnn30KqJSVQVnJX3nxKdtvv3222267XHnllUmSxYsXZ+21185Pf/rTnHjiiQVXR3M0ffr0dOnSJQ8//HB23nnnosuhmZk9e3a22WabXH311Tn77LOz1VZb5bLLLiu6LJqJE088MY8++mj++te/Fl0Kzdh3v/vddO3aNb/5zW9qju2///5p3bp1brzxxgIro7koKyvLHXfckX79+iX5eNRct27dctxxx+X4449PksycOTNdu3bNqFGj0r9//wKrZWX06e/gsjz55JP5xje+kUmTJmWdddb56opjpWDkHLXMnz8/48ePT+/evWuOtWjRIr179864ceMKrIzmbObMmUmSjh07FlwJzdHgwYPTt2/fWn8uwlfl7rvvTs+ePfODH/wgXbp0ydZbb53/+Z//KbosmplvfvObGTNmTF599dUkyT/+8Y/87W9/y3e+852CK6O5evPNNzNlypRa/25u3759tt9+e7+zUJiZM2emrKwsHTp0KLoUVkAtiy6ApuVf//pXFi1alK5du9Y63rVr17z88ssFVUVztnjx4gwdOjQ77rhjNttss6LLoZn53e9+l6effjpPPvlk0aXQTL3xxhu55pprMmzYsJx88sl58skn87Of/Szl5eUZOHBg0eXRTJx44omprq7ORhttlFVWWSWLFi3KOeeckwEDBhRdGs3UlClTkmSZv7MsOQdfpY8++ii/+MUvcuCBB6aysrLoclgBCeeAJm3w4MF5/vnn87e//a3oUmhmJk+enGOOOSajR49Oq1atii6HZmrx4sXp2bNnzj333CTJ1ltvneeffz4jRowQzvGVue2223LTTTfl5ptvzqabbpoJEyZk6NCh6datm+8h0OwtWLAgP/zhD1MqlXLNNdcUXQ4rKNNaqWWNNdbIKquskqlTp9Y6PnXq1FRVVRVUFc3VkCFDcs899+TBBx/MWmutVXQ5NDPjx4/PtGnTss0226Rly5Zp2bJlHn744VxxxRVp2bJlFi1aVHSJNANrrrlmNtlkk1rHNt5447z99tsFVURzdMIJJ+TEE09M//79s/nmm+dHP/pRjj322Jx33nlFl0YzteT3Er+zULQlwdykSZMyevRoo+aoN+EctZSXl2fbbbfNmDFjao4tXrw4Y8aMSa9evQqsjOakVCplyJAhueOOOzJ27Nj06NGj6JJohnbfffc899xzmTBhQs2rZ8+eGTBgQCZMmJBVVlml6BJpBnbccce88sortY69+uqr6d69e0EV0RzNnTs3LVrU/rVhlVVWyeLFiwuqiOauR48eqaqqqvU7S3V1dR5//HG/s/CVWRLMTZw4MX/5y1/SqVOnoktiBWZaK0sZNmxYBg4cmJ49e+Yb3/hGLrvsssyZMyeHHXZY0aXRTAwePDg333xz7rrrrrRr165m7ZD27dundevWBVdHc9GuXbul1jls27ZtOnXqZP1DvjLHHntsvvnNb+bcc8/ND3/4wzzxxBO59tprc+211xZdGs3I3nvvnXPOOSfrrLNONt100zzzzDO55JJLcvjhhxddGiux2bNn57XXXqt5/+abb2bChAnp2LFj1llnnQwdOjRnn3121l9//fTo0SOnnnpqunXr9rm7aUJdfN53cM0118z3v//9PP3007nnnnuyaNGimt9ZOnbsmPLy8qLKZgVVViqVSkUXQdNz5ZVX5sILL8yUKVOy1VZb5Yorrsj2229fdFk0E2VlZcs8PnLkyBx66KFfbTHwCbvuumu22mqrXHbZZUWXQjNyzz335KSTTsrEiRPTo0ePDBs2LEceeWTRZdGMzJo1K6eeemruuOOOTJs2Ld26dcuBBx6Y0047zS+gfGkeeuih7LbbbksdHzhwYEaNGpVSqZTTTz891157bT744IPstNNOufrqq7PBBhsUUC0ro8/7Dg4fPvwzZ/c8+OCD2XXXXb/k6ljZCOcAAAAAoCDWnAMAAACAggjnAAAAAKAgwjkAAAAAKIhwDgAAAAAKIpwDAAAAgIII5wAAAACgIMI5AAAAACiIcA4AAAAACiKcAwAAAICCCOcAAApy6KGHpl+/fl/pPUeNGpWysrJsvPHGS527/fbbU1ZWlnXXXbfe7RctWpT/+q//ykYbbZTWrVunY8eO2X777fPrX/+6ps3yPHepVMq1116b7bffPquttlo6dOiQnj175rLLLsvcuXPr/NwNUcTPCQBoPoRzAADNTNu2bTNt2rSMGzeu1vHf/OY3WWeddRrU/owzzsill16as846Ky+++GIefPDBHHXUUfnggw/qVOOPfvSjDB06NPvuu28efPDBTJgwIaeeemruuuuuPPDAA3W6FgBAUyacAwBooh5++OF84xvfSEVFRdZcc82ceOKJWbhwYc35WbNmZcCAAWnbtm3WXHPNXHrppdl1110zdOjQz71uy5Ytc9BBB+W6666rOfbOO+/koYceykEHHdSg9nfffXd+8pOf5Ac/+EF69OiRLbfcMoMGDcrxxx+/3M9922235aabbsott9ySk08+Odttt13WXXfd7Lvvvhk7dmx22223JMnixYtz5plnZq211kpFRUW22mqr3H///TXXeeihh1JWVlYrGJwwYULKysry1ltvJfl4ZGCHDh3y5z//ORtvvHFWW2217LnnnnnvvfeSJMOHD8/111+fu+66K2VlZSkrK8tDDz203M8CAPBFhHMAAE3QP//5z+y1117Zbrvt8o9//CPXXHNNfvOb3+Tss8+uaTNs2LA8+uijufvuuzN69Oj89a9/zdNPP71c1z/88MNz22231UwRHTVqVPbcc8907dq1Qe2rqqoyduzYTJ8+vT6PnSS56aabsuGGG2bfffdd6lxZWVnat2+fJLn88stz8cUX56KLLsqzzz6bPn36ZJ999snEiRPrdL+5c+fmoosuyg033JBHHnkkb7/9dk2YePzxx+eHP/xhTWD33nvv5Zvf/Ga9nw0A4NOEcwAATdDVV1+dtddeO1deeWU22mij9OvXL2eccUYuvvjiLF68OLNmzcr111+fiy66KLvvvns222yzjBw5MosWLVqu62+99db5f//v/+X3v/99SqVSRo0alcMPP7zB7S+55JJMnz49VVVV2WKLLXL00Ufnvvvuq9OzT5w4MRtuuOEXtrvooovyi1/8Iv3798+GG26Y888/P1tttVUuu+yyOt1vwYIFGTFiRHr27JltttkmQ4YMyZgxY5Ikq622Wlq3bp2KiopUVVWlqqoq5eXldbo+AMDnEc4BADRBL730Unr16pWysrKaYzvuuGNmz56dd955J2+88UYWLFiQb3zjGzXn27dvv1yh1hKHH354Ro4cmYcffjhz5szJXnvt1eD2m2yySZ5//vn8/e9/z+GHH55p06Zl7733zhFHHLHcdZVKpS9sU11dnXfffTc77rhjreM77rhjXnrppeW+V5K0adMm6623Xs37NddcM9OmTavTNQAA6ks4BwDQTA0YMCB///vfM3z48PzoRz9Ky5YtG6V9ixYtst1222Xo0KH54x//mFGjRuU3v/lN3nzzzeWqa4MNNsjLL79c5+dZVh1J7bBvwYIFS7VbddVVa70vKytbroAQAKAxCOcAAJqgjTfeOOPGjasVEj366KNp165d1lprrfy///f/suqqq+bJJ5+sOT9z5sy8+uqry32Pjh07Zp999snDDz/8uVNa69t+iU022SRJMmfOnOVqf9BBB+XVV1/NXXfdtdS5UqmUmTNnprKyMt26dcujjz5a6/yjjz5ac7/OnTsnSc3mDsnHG0LUVXl5+XJPFwYAqCvhHABAgWbOnJkJEybUek2ePDk/+clPMnny5Pz0pz/Nyy+/nLvuuiunn356hg0blhYtWqRdu3YZOHBgTjjhhDz44IN54YUXMmjQoLRo0aLWVNgvMmrUqPzrX//KRhtt1Cjtv//97+fSSy/N448/nkmTJuWhhx7K4MGDs8EGGyz3PX74wx/mgAMOyIEHHphzzz03Tz31VCZNmpR77rknvXv3zoMPPpgkOeGEE3L++efn1ltvzSuvvJITTzwxEyZMyDHHHJMk+frXv5611147w4cPz8SJE3Pvvffm4osvXq4aPmndddfNs88+m1deeSX/+te/ljn6DgCgvj5/7gIAAF+qhx56KFtvvXWtY4MGDcqvf/3r/OlPf8oJJ5yQLbfcMh07dsygQYNyyimn1LS75JJLcvTRR+e73/1uKisr8/Of/zyTJ09Oq1atlvv+rVu3TuvWrRutfZ8+fXLLLbfkvPPOy8yZM1NVVZVvf/vbGT58+BdOm12irKwsN998c6699tpcd911Oeecc9KyZcusv/76OeSQQ9KnT58kyc9+9rPMnDkzxx13XKZNm5ZNNtkkd999d9Zff/0kH09XveWWW/LjH/84W2yxRbbbbrucffbZ+cEPfrDcz5skRx55ZB566KH07Nkzs2fPzoMPPphdd921TtcAAPgsZSULagAArBTmzJmTr33ta7n44oszaNCgossBAGA5GDkHALCCeuaZZ/Lyyy/nG9/4RmbOnJkzzzwzSbLvvvsWXBkAAMtLOAcAsAK76KKL8sorr6S8vDzbbrtt/vrXv2aNNdYouiwAAJaTaa0AAAAAUBC7tQIAAABAQYRzAAAAAFAQ4RwAAAAAFEQ4BwAAAAAFEc4BAAAAQEGEcwAAAABQEOEcAAAAABREOAcAAAAABfn/AI6JVTTQ5jjHAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "# Convert 'MMSI_count' to a 1-dimensional numpy array\n",
        "mmsi_count = np.array(results['MMSI_count'])\n",
        "\n",
        "# Create a larger figure\n",
        "plt.figure(figsize=(15, 9))\n",
        "\n",
        "# Create a KDE plot using seaborn\n",
        "sns.kdeplot(mmsi_count, fill=True)\n",
        "plt.xlabel(\"MMSI Count\")\n",
        "plt.ylabel(\"Density\")\n",
        "plt.title(\"Distribution of MMSI Count\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 795
        },
        "id": "6BJppa7WyTPK",
        "outputId": "235abf1b-bf63-4d73-f67d-1027a4899878"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x900 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "# Convert 'MMSI_count' to a 1-dimensional numpy array\n",
        "mmsi_count = np.array(results['MMSI_count'], dtype=float)\n",
        "\n",
        "# Apply log transform\n",
        "log_mmsi_count = np.log(mmsi_count)\n",
        "\n",
        "# Create a larger figure\n",
        "plt.figure(figsize=(15, 9))\n",
        "\n",
        "# Create a KDE plot using seaborn\n",
        "sns.kdeplot(log_mmsi_count, fill=True)\n",
        "plt.xlabel(\"Log MMSI Count\")\n",
        "plt.ylabel(\"Density\")\n",
        "plt.title(\"Distribution of Log MMSI Count\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 795
        },
        "id": "jpNQjjGhyY3L",
        "outputId": "ca49322a-a5fe-4b15-dc9b-e32285a86f2c"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x900 with 1 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    }
  ],
  "metadata": {
    "colab": {
      "cell_execution_strategy": "setup",
      "name": "BigQuery bquxjob_56d440df_18decc339b8",
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}