COVID19_DataAnalysis_US_upto_17_05.ipynb

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      "name": "COVID19_DataAnalysis_US_upto_17_05.ipynb",
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      "name": "python3",
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      "metadata": {
        "id": "MHFmdjLd1X39",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "t3HQpD7y2ADS",
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        }
      },
      "source": [
        "covid19 = pd.read_csv('https://raw.githubusercontent.com/nytimes/covid-19-data/master/us-counties.csv ')\n",
        "covid19"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>date</th>\n",
              "      <th>county</th>\n",
              "      <th>state</th>\n",
              "      <th>fips</th>\n",
              "      <th>cases</th>\n",
              "      <th>deaths</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-01-21</td>\n",
              "      <td>Snohomish</td>\n",
              "      <td>Washington</td>\n",
              "      <td>53061.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-01-22</td>\n",
              "      <td>Snohomish</td>\n",
              "      <td>Washington</td>\n",
              "      <td>53061.0</td>\n",
              "      <td>1</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-01-23</td>\n",
              "      <td>Snohomish</td>\n",
              "      <td>Washington</td>\n",
              "      <td>53061.0</td>\n",
              "      <td>1</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-01-24</td>\n",
              "      <td>Cook</td>\n",
              "      <td>Illinois</td>\n",
              "      <td>17031.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-01-24</td>\n",
              "      <td>Snohomish</td>\n",
              "      <td>Washington</td>\n",
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              "    <tr>\n",
              "      <th>153096</th>\n",
              "      <td>2020-05-17</td>\n",
              "      <td>Sublette</td>\n",
              "      <td>Wyoming</td>\n",
              "      <td>56035.0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>153097</th>\n",
              "      <td>2020-05-17</td>\n",
              "      <td>Sweetwater</td>\n",
              "      <td>Wyoming</td>\n",
              "      <td>56037.0</td>\n",
              "      <td>23</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>153098</th>\n",
              "      <td>2020-05-17</td>\n",
              "      <td>Teton</td>\n",
              "      <td>Wyoming</td>\n",
              "      <td>56039.0</td>\n",
              "      <td>100</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>153099</th>\n",
              "      <td>2020-05-17</td>\n",
              "      <td>Uinta</td>\n",
              "      <td>Wyoming</td>\n",
              "      <td>56041.0</td>\n",
              "      <td>10</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>153100</th>\n",
              "      <td>2020-05-17</td>\n",
              "      <td>Washakie</td>\n",
              "      <td>Wyoming</td>\n",
              "      <td>56043.0</td>\n",
              "      <td>15</td>\n",
              "      <td>0</td>\n",
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              "<p>153101 rows × 6 columns</p>\n",
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            ],
            "text/plain": [
              "              date      county       state     fips  cases  deaths\n",
              "0       2020-01-21   Snohomish  Washington  53061.0      1       0\n",
              "1       2020-01-22   Snohomish  Washington  53061.0      1       0\n",
              "2       2020-01-23   Snohomish  Washington  53061.0      1       0\n",
              "3       2020-01-24        Cook    Illinois  17031.0      1       0\n",
              "4       2020-01-24   Snohomish  Washington  53061.0      1       0\n",
              "...            ...         ...         ...      ...    ...     ...\n",
              "153096  2020-05-17    Sublette     Wyoming  56035.0      3       0\n",
              "153097  2020-05-17  Sweetwater     Wyoming  56037.0     23       0\n",
              "153098  2020-05-17       Teton     Wyoming  56039.0    100       1\n",
              "153099  2020-05-17       Uinta     Wyoming  56041.0     10       0\n",
              "153100  2020-05-17    Washakie     Wyoming  56043.0     15       0\n",
              "\n",
              "[153101 rows x 6 columns]"
            ]
          },
          "metadata": {
            "tags": []
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          "execution_count": 3
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      ]
    },
    {
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        }
      },
      "source": [
        "covid19.info()"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 153101 entries, 0 to 153100\n",
            "Data columns (total 6 columns):\n",
            " #   Column  Non-Null Count   Dtype  \n",
            "---  ------  --------------   -----  \n",
            " 0   date    153101 non-null  object \n",
            " 1   county  153101 non-null  object \n",
            " 2   state   153101 non-null  object \n",
            " 3   fips    151389 non-null  float64\n",
            " 4   cases   153101 non-null  int64  \n",
            " 5   deaths  153101 non-null  int64  \n",
            "dtypes: float64(1), int64(2), object(3)\n",
            "memory usage: 7.0+ MB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2C8Ghe252WoO",
        "colab_type": "code",
        "outputId": "862a7a24-0074-4e0f-a212-d0d1a8ed15c2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 669
        }
      },
      "source": [
        "covid19.head(20)"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <td>Illinois</td>\n",
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              "      <th>4</th>\n",
              "      <td>2020-01-24</td>\n",
              "      <td>Snohomish</td>\n",
              "      <td>Washington</td>\n",
              "      <td>53061.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>2020-01-25</td>\n",
              "      <td>Orange</td>\n",
              "      <td>California</td>\n",
              "      <td>6059.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>2020-01-25</td>\n",
              "      <td>Cook</td>\n",
              "      <td>Illinois</td>\n",
              "      <td>17031.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>2020-01-25</td>\n",
              "      <td>Snohomish</td>\n",
              "      <td>Washington</td>\n",
              "      <td>53061.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>2020-01-26</td>\n",
              "      <td>Maricopa</td>\n",
              "      <td>Arizona</td>\n",
              "      <td>4013.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>2020-01-26</td>\n",
              "      <td>Los Angeles</td>\n",
              "      <td>California</td>\n",
              "      <td>6037.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>2020-01-26</td>\n",
              "      <td>Orange</td>\n",
              "      <td>California</td>\n",
              "      <td>6059.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>2020-01-26</td>\n",
              "      <td>Cook</td>\n",
              "      <td>Illinois</td>\n",
              "      <td>17031.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>2020-01-26</td>\n",
              "      <td>Snohomish</td>\n",
              "      <td>Washington</td>\n",
              "      <td>53061.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>2020-01-27</td>\n",
              "      <td>Maricopa</td>\n",
              "      <td>Arizona</td>\n",
              "      <td>4013.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>2020-01-27</td>\n",
              "      <td>Los Angeles</td>\n",
              "      <td>California</td>\n",
              "      <td>6037.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>2020-01-27</td>\n",
              "      <td>Orange</td>\n",
              "      <td>California</td>\n",
              "      <td>6059.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>2020-01-27</td>\n",
              "      <td>Cook</td>\n",
              "      <td>Illinois</td>\n",
              "      <td>17031.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>2020-01-27</td>\n",
              "      <td>Snohomish</td>\n",
              "      <td>Washington</td>\n",
              "      <td>53061.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>2020-01-28</td>\n",
              "      <td>Maricopa</td>\n",
              "      <td>Arizona</td>\n",
              "      <td>4013.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>2020-01-28</td>\n",
              "      <td>Los Angeles</td>\n",
              "      <td>California</td>\n",
              "      <td>6037.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "</div>"
            ],
            "text/plain": [
              "          date       county       state     fips  cases  deaths\n",
              "0   2020-01-21    Snohomish  Washington  53061.0      1       0\n",
              "1   2020-01-22    Snohomish  Washington  53061.0      1       0\n",
              "2   2020-01-23    Snohomish  Washington  53061.0      1       0\n",
              "3   2020-01-24         Cook    Illinois  17031.0      1       0\n",
              "4   2020-01-24    Snohomish  Washington  53061.0      1       0\n",
              "5   2020-01-25       Orange  California   6059.0      1       0\n",
              "6   2020-01-25         Cook    Illinois  17031.0      1       0\n",
              "7   2020-01-25    Snohomish  Washington  53061.0      1       0\n",
              "8   2020-01-26     Maricopa     Arizona   4013.0      1       0\n",
              "9   2020-01-26  Los Angeles  California   6037.0      1       0\n",
              "10  2020-01-26       Orange  California   6059.0      1       0\n",
              "11  2020-01-26         Cook    Illinois  17031.0      1       0\n",
              "12  2020-01-26    Snohomish  Washington  53061.0      1       0\n",
              "13  2020-01-27     Maricopa     Arizona   4013.0      1       0\n",
              "14  2020-01-27  Los Angeles  California   6037.0      1       0\n",
              "15  2020-01-27       Orange  California   6059.0      1       0\n",
              "16  2020-01-27         Cook    Illinois  17031.0      1       0\n",
              "17  2020-01-27    Snohomish  Washington  53061.0      1       0\n",
              "18  2020-01-28     Maricopa     Arizona   4013.0      1       0\n",
              "19  2020-01-28  Los Angeles  California   6037.0      1       0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7YIdHvy74VW9",
        "colab_type": "code",
        "outputId": "bac07c4c-2499-49b2-a063-126f3d359f45",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 350
        }
      },
      "source": [
        "import seaborn as sns\n",
        "sns.barplot(x = 'cases' , y = 'deaths' , data = covid19)"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n",
            "  import pandas.util.testing as tm\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fce4c74fac8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAaQAAAEGCAYAAAAqmOHQAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+j8jraAAAcvUlEQVR4nO3df5TVdb3v8edrxiABUZAJCOTIKbSrdCLlmreuHctC4twO1O0HrhKOWdQJ76ljp0m7Z1375bqmRaWRLUqWcE9ploXcDobEbdk63UxAuYBaOv46zsAwg6ggozPM8L5/7M+evozzC9h79nczr8dae+3vfn8/3+/382W59svP9/uZ71ZEYGZmVmk1le6AmZkZOJDMzCwnHEhmZpYLDiQzM8sFB5KZmeXCCZXuwFCbMGFCnH766ZXuhplZVdmyZcueiKgr5zGGXSCdfvrpbN68udLdMDOrKpKeLvcxfMnOzMxywYFkZma54EAyM7NccCCZmVkuOJDMzCwXHEhmZpYLDiQzM8sFB5KZmeVC2QJJ0mmSfiPpYUkPSfpMqo+XtEHSY+l9XKpL0o2SGiRtk3ROZl+LU/vHJC3O1M+VtD1tc6Mklet8zMysvMo5QuoEPhcRZwHnA0slnQVcBWyMiBnAxvQZ4D3AjPRaAtwMhQADrgHeApwHXFMMsdTmE5nt5pbxfMzMrIzKFkgRsSsiHkjL+4FHgCnAfGBVarYKWJCW5wOro+A+4BRJk4GLgQ0RsTcingM2AHPTurERcV8UfvZ2dWZfZmZWIq03/8uQHGdI7iFJOh14M/AHYGJE7EqrmoGJaXkK8Exms8ZU66/e2Eu9t+MvkbRZ0ubW1tZjOhczMyuPsgeSpDHAncBnI2Jfdl0a2US5+xARKyJidkTMrqsr68NqzczsKJU1kCS9ikIY/Sgifp7Ku9PlNtJ7S6o3AadlNp+aav3Vp/ZSNzOzKlTOWXYCbgEeiYhlmVVrgeJMucXAXZn6ojTb7nzghXRpbz0wR9K4NJlhDrA+rdsn6fx0rEWZfZmZWZUp5+8hvQ24FNguaWuqfRG4DrhD0uXA08CH0rp1wDygAWgDLgOIiL2SvgpsSu2+EhF70/KngVuBE4G708vMzKpQ2QIpIv4N6Ovvgi7qpX0AS/vY10pgZS/1zcDMY+immZnlhJ/UYGZmueBAMjOzXHAgmZlZLjiQzMwsFxxIZmaWCw4kMzPLBQeSmZnlggPJzMxywYFkZma54EAyM7NccCCZmVkuOJDMzCwXHEhmZpYLDiQzM8sFB5KZmfWp9eYfD9mxHEhmZpYL5fwJ85WSWiTtyNR+Imlrej1V/CVZSadLeimz7vuZbc6VtF1Sg6Qb08+VI2m8pA2SHkvv48p1LmZmVn7lHCHdCszNFiLiwxExKyJmAXcCP8+sfry4LiI+lanfDHwCmJFexX1eBWyMiBnAxvTZzMyqVNkCKSJ+C+ztbV0a5XwIuK2/fUiaDIyNiPvST5yvBhak1fOBVWl5VaZuZmZVqFL3kC4AdkfEY5nadEkPSrpX0gWpNgVozLRpTDWAiRGxKy03AxPL2mMzMyurEyp03Es4fHS0C5gWEc9KOhdYI+nswe4sIkJS9LVe0hJgCcC0adOOsstmZlZOQz5CknQC8H7gJ8VaRLRHxLNpeQvwOHAG0ARMzWw+NdUAdqdLesVLey19HTMiVkTE7IiYXVdXV8rTMTOzEqnEJbt3AX+MiO5LcZLqJNWm5b+kMHnhiXRJbp+k89N9p0XAXWmztcDitLw4UzczsypUzmnftwG/B86U1Cjp8rRqIa+czPB2YFuaBv4z4FMRUZwQ8Wngh0ADhZHT3al+HfBuSY9RCLnrynUuZmZWfmW7hxQRl/RR/7teandSmAbeW/vNwMxe6s8CFx1bL83MLC/8pAYzM8sFB5KZmeWCA8nMzHLBgWRmZrngQDIzs1xwIJmZWS44kMzMLBccSGZmlgsOJDMzywUHkpmZ5YIDyczMcsGBZGZmueBAMjOzXHAgmZlZLjiQzMwsFxxIZmaWCw4kMzPLhXL+hPlKSS2SdmRqX5LUJGlres3LrLtaUoOkP0m6OFOfm2oNkq7K1KdL+kOq/0TSiHKdi5mZlV85R0i3AnN7qX8rImal1zoASWcBC4Gz0zbfk1QrqRZYDrwHOAu4JLUF+Hra1+uB54DLy3guZmZWZmULpIj4LbB3kM3nA7dHRHtEPAk0AOelV0NEPBERHcDtwHxJAt4J/CxtvwpYUNITMDOzIVWJe0hXSNqWLumNS7UpwDOZNo2p1lf9VOD5iOjsUe+VpCWSNkva3NraWqrzMDOzEhrqQLoZeB0wC9gFfHMoDhoRKyJidkTMrqurG4pDmpnZETphKA8WEbuLy5J+APwyfWwCTss0nZpq9FF/FjhF0glplJRtb2ZmVWhIR0iSJmc+vg8ozsBbCyyUNFLSdGAGcD+wCZiRZtSNoDDxYW1EBPAb4ANp+8XAXUNxDmZmVh5lGyFJug24EJggqRG4BrhQ0iwggKeATwJExEOS7gAeBjqBpRHRlfZzBbAeqAVWRsRD6RBfAG6X9DXgQeCWcp2LmZmVX9kCKSIu6aXcZ2hExLXAtb3U1wHreqk/QWEWnpmZHQf8pAYzM8sFB5KZmeWCA8nMzHLBgWRmZrngQDIzs1xwIJmZWS44kMzMLBccSGZmlgsOJDMzywUHkpmZ5YIDyczMcsGBZGZmueBAMjOzXHAgmZlZLjiQzMwsFxxIZmaWCw4kMzPLhbIFkqSVklok7cjUbpD0R0nbJP1C0impfrqklyRtTa/vZ7Y5V9J2SQ2SbpSkVB8vaYOkx9L7uHKdi5mZlV85R0i3AnN71DYAMyPir4BHgasz6x6PiFnp9alM/WbgE8CM9Cru8ypgY0TMADamz2ZmVqXKFkgR8Vtgb4/aPRHRmT7eB0ztbx+SJgNjI+K+iAhgNbAgrZ4PrErLqzJ1MzOrQpW8h/Qx4O7M5+mSHpR0r6QLUm0K0Jhp05hqABMjYldabgYm9nUgSUskbZa0ubW1tUTdNzOzUqpIIEn670An8KNU2gVMi4g3A1cCP5Y0drD7S6On6Gf9ioiYHRGz6+rqjqHnZmbDR+v3bhvS450wpEcDJP0d8F+Ai1KQEBHtQHta3iLpceAMoInDL+tNTTWA3ZImR8SudGmvZYhOwczMymBIR0iS5gL1wN9GRFumXiepNi3/JYXJC0+kS3L7JJ2fZtctAu5Km60FFqflxZm6mZlVobKNkCTdBlwITJDUCFxDYVbdSGBDmr19X5pR93bgK5IOAoeAT0VEcULEpynM2DuRwj2n4n2n64A7JF0OPA18qFznYmZm5TeoQJL0NmBrRByQ9FHgHOA7EfF0X9tExCW9lG/po+2dwJ19rNsMzOyl/ixw0SC6b2ZmVWCwl+xuBtokvQn4HPA4hSnYZmZmJTHYQOpMExDmA9+NiOXASeXrlpmZDTeDvYe0X9LVwEeBt0uqAV5Vvm6ZmdlwM9gR0ocpTMu+PCKaKUy/vqFsvTIzs2FnUCOkFELLMp//Hd9DMjOzEhrUCEnS+9NTtV+QtE/Sfkn7yt05MzMbPgZ7D+l64L0R8Ug5O2NmZsPXYO8h7XYYmZlZOfU7QpL0/rS4WdJPgDWkZ84BRMTPy9g3MzMbRga6ZPfezHIbMCfzOQAHkpmZlUS/gRQRl0Hh0UER8bvsuvQ4ITMzs5IY7D2kmwZZMzMzOyoD3UP6T8BbgTpJV2ZWjQVqy9kxMzMbXga6hzQCGJPaZZ9dtw/4QLk6ZWZmw89A95DuBe6VdGt/PzVhZmZ2rAb7h7Ftkm4AzgZeXSxGxDvL0iszMxt2Bjup4UfAH4HpwJeBp4BNA20kaaWkFkk7MrXxkjakRxFtkDQu1SXpRkkNkrZJOiezzeLU/jFJizP1cyVtT9vcmH7m3MzMqtBgA+nUiLgFOBgR90bEx4DBjI5uBeb2qF0FbIyIGcDG9BngPcCM9FpC4UcBkTSews+fvwU4D7imGGKpzScy2/U8lpmZVYnBBtLB9L5L0t9IejMwfqCNIuK3wN4e5fnAqrS8CliQqa+OgvuAUyRNBi4GNkTE3oh4DtgAzE3rxkbEfenHA1dn9mVmZlVmsPeQvibpZAo/X34ThWnf/3iUx5wYEbvScjMwMS1PAZ7JtGtMtf7qjb3UX0HSEgqjLqZNm3aU3TYzs3Ia7O8h/TItvgC8o1QHj4iQFKXaXz/HWQGsAJg9e3bZj2dmZkdusL+HdIakjcXJCZL+StI/H+Uxd6fLbaT3llRvAk7LtJuaav3Vp/ZSNzOzKjTYe0g/AK4m3UuKiG3AwqM85lqgOFNuMXBXpr4ozbY7H3ghXdpbD8yRNC5NZpgDrE/r9kk6P82uW5TZl5mZVZnB3kMaFRH395hV3TnQRpJuAy4EJkhqpDBb7jrgDkmXA08DH0rN1wHzgAYKTxa/DCAi9kr6Kn+eZv6ViChOlPg0hZl8JwJ3p5eZmVWhwQbSHkmvo/CTE0j6ALCr/00gIi7pY9VFvbQNYGkf+1kJrOylvhmYOVA/zMws/wYbSEspTAp4g6Qm4EngI2XrlZmZDTsDPe07+4TvdcBvKNx3OgD8V2BZ+bpmZmbDyUAjpOITvs8E/iOFSQMCLgXuL2O/zMxsmBnoad9fBpD0W+CciNifPn8J+Ney987MzIaNwU77ngh0ZD538OcnLJiZmR2zwU5qWA3cL+kX6fMCCtOtzczMSmKwjw66VtLdwAWpdFlEPFi+bpmZ2XAz2BESEfEA8EAZ+2JmZsPYYO8hmZmZlZUDyczMcsGBZGZmueBAMjOzXHAgmZlZLjiQzMwsFxxIZmaWCw4kMzPLBQeSmZnlwpAHkqQzJW3NvPZJ+qykL0lqytTnZba5WlKDpD9JujhTn5tqDZKuGupzMTOz0hn0o4NKJSL+BMwCkFQLNAG/AC4DvhUR38i2l3QWsBA4G3gt8GtJZ6TVy4F3A43AJklrI+LhITkRMzMrqSEPpB4uAh6PiKcl9dVmPnB7RLQDT0pqAM5L6xoi4gkASbentg4kM7MqVOl7SAuB2zKfr5C0TdJKSeNSbQrwTKZNY6r1VX8FSUskbZa0ubW1tXS9NzOzkqlYIEkaAfwt8NNUuhl4HYXLebuAb5bqWBGxIiJmR8Tsurq6Uu3WzMxKqJKX7N4DPBARuwGK7wCSfgD8Mn1sAk7LbDc11einbmZmVaaSl+wuIXO5TtLkzLr3ATvS8lpgoaSRkqYDM4D7gU3ADEnT02hrYWprZmZVqCIjJEmjKcyO+2SmfL2kWUAATxXXRcRDku6gMFmhE1gaEV1pP1cA64FaYGVEPDRkJ2FmZiVVkUCKiAPAqT1ql/bT/lrg2l7q64B1Je+gmZkNuUrPsjMzMwMcSGZmlhMOJDMzywUHkpmZ5YIDyczMcsGBZGZmueBAMjOzXHAgmZlZLjiQzMwsFxxIZmaWCw4kMzPLBQeSmZnlggPJzMxywYFkZma54EAyM7NccCCZmVkuVCyQJD0labukrZI2p9p4SRskPZbex6W6JN0oqUHSNknnZPazOLV/TNLiSp2PmZkdm0qPkN4REbMiYnb6fBWwMSJmABvTZ4D3ADPSawlwMxQCDLgGeAtwHnBNMcTMzKy6VDqQepoPrErLq4AFmfrqKLgPOEXSZOBiYENE7I2I54ANwNyh7rSZmR27SgZSAPdI2iJpSapNjIhdabkZmJiWpwDPZLZtTLW+6mZmVmVOqOCx/3NENEl6DbBB0h+zKyMiJEUpDpQCbwnAtGnTSrFLMzMrsYqNkCKiKb23AL+gcA9od7oUR3pvSc2bgNMym09Ntb7qPY+1IiJmR8Tsurq6Up+KmZmVQEUCSdJoSScVl4E5wA5gLVCcKbcYuCstrwUWpdl25wMvpEt764E5ksalyQxzUs3MzKpMpS7ZTQR+IanYhx9HxK8kbQLukHQ58DTwodR+HTAPaADagMsAImKvpK8Cm1K7r0TE3qE7DTMzK5WKBFJEPAG8qZf6s8BFvdQDWNrHvlYCK0vdRzMzG1p5m/ZtZmbDlAPJzMxywYFkZma54EAyM7NccCCZmVkuOJDMzCwXHEhmZpYLDiQzM8sFB5KZmeWCA8nMzHLBgWRmZrngQDIzs1xwIJmZWS44kMzMLBccSGZmlgsOJDMzywUHkpmZ5cKQB5Kk0yT9RtLDkh6S9JlU/5KkJklb02teZpurJTVI+pOkizP1uanWIOmqoT4XMzMrnUr8hHkn8LmIeEDSScAWSRvSum9FxDeyjSWdBSwEzgZeC/xa0hlp9XLg3UAjsEnS2oh4eEjOwszMSmrIAykidgG70vJ+SY8AU/rZZD5we0S0A09KagDOS+saIuIJAEm3p7YOJDOzKlTRe0iSTgfeDPwhla6QtE3SSknjUm0K8Exms8ZU66ve23GWSNosaXNra2sJz8DMzEqlYoEkaQxwJ/DZiNgH3Ay8DphFYQT1zVIdKyJWRMTsiJhdV1dXqt2amR13Wr73s4oduxL3kJD0Kgph9KOI+DlAROzOrP8B8Mv0sQk4LbP51FSjn7qZmVWZSsyyE3AL8EhELMvUJ2eavQ/YkZbXAgsljZQ0HZgB3A9sAmZImi5pBIWJD2uH4hzMzKz0KnHJ7m3ApcA7e0zxvl7SdknbgHcA/wgQEQ8Bd1CYrPArYGlEdEVEJ3AFsB54BLgjtTUzs6TlpnuOfJvv/bQMPRlYJWbZ/RugXlat62eba4Fre6mv6287MzOrHn5Sg5nZcajlpo2V7sIRcyCZmRkALd+7s6LHdyCZmVkuOJDMzCwXKvJ3SGZmVhr19fU0NzczvmMkV7/1I0z8hwsr3aWj5hGSmVkVa25upqmpida2549ou5bl/7tMPTp6HiGZmVWR4oho0qRJXH/99X2uH98xgm//t4sq0MOj50AyM8uxngFUHBH1pbi+a/R4Wm7acNi67L7+6S8u6K63LF/Da5YuKNs5DJYDycwsxwYKoJ66nn9pcPv6i8Jby/K7jqV7JeVAMjM7BgNdQiu1SZMmHfZ+PHEgmZlx9MFypCOYY9VX3/a+tI8rf72cvS/v63V9y3d/RdfzbeXs2jFzIJnZcW8wYTOYYCnuZ9++fYwdO/aIRyl99aN52cNMuvKsXtvv3LkTgD179rD7O39g4mfeAsDu7/xfUHRfouuKQzQf2MuImhOYMmUK4ztGDNifluX5+oEEB5KZ5dpgwiTb5tFHH6WtrY1Ro0axZs0a6uvr2bp1K11dXcd8/GJo1dbWsn//fvbs2UNnZ+eg9tN8w1MDT0hYtp1JV76x+3PTH58mIgDo7DjYXd/9nd/3uY/xJ45l9erV6Vl2hwbVt7xwIJlZbvQMn/r6erZs2QIURgh9yX7Rt7W10dXVxf79+1m0aBF79uzpDqPe9lE8Zl/77y9EOjs7Dwu6f1/WzLQrBx417dmzh0WLFvUbsru/9eCA+8mqVQ11o06hbtTJR7RdnjiQzGxI9Ha5qxg6xXoxTIoebfhzEHR2dlJfX8+OHYXf7pw5cya7dx8k4tnuMDnw4uEjgqamJmpqag/bR8++vPjii0QEhd8OfWVYFPe9c+dOamoKzxI4dKhwnKMddXV2dvYZct1/R9Q+mroTx9F8oO8gzhp/4liWvWspUhxVn/LAgWSWU8cye+totu1tm/r6eh544AEAxowZw5o1aw6rF7/Ix4wZw/79+7v3NXLkSEaMGHFY8PS83FWUrWe/4Ovr69n/QnP3566uru5jAmzdupVDhw4dFiYvHnj2FSFx6FDXYfv44Ps+woH252hvb6emprZ7f8X39vb2w8Kis6Oze31x38W2pdS8rPD7on/+O6IJLHvnF7h03VX9Bl/dqFMOe69mDiQ77mS/WAF27NhBR0dH95eIJM4555xjnqLb15d+z/+Lz365Z/t1pDfZ+ztez/qOHTu6v1gXLCj8wWMxBCQxYsQIZs6ceVg/isdramriXe96FzU1NYd9Ee7fv5958+bR0dEBcNgXeTZgoPCl3tnZ2X2fZdGiRd3nUtznzp07mTNnTvfn7LH27NnT6wgiGwTZ9t33WTo7ev23zNq7r5na2sKoKRtWx6rz+T/va+cNu3jt5ye/os2kSZPoeu4gu9tagcJ5Nn/zkd5/sjQZNWoUbS8e4MQTXt3r+qvfugiIzKtvdaPHdvcjj6o+kCTNBb4D1AI/jIjrKtylqtXzkkrxC6G2tpZ77rnnsHa9feEe6f6z7x0dHbS3t3e3HTlyJDNnzjymm9F9XRKJCLZs2cJFF5XmsSpNTU197qu342T71d+2fbVpampi3rx5h/17ZduddNJJh63rGRYRQXt7e/e9mZ59Krbp7d+95zH7U9y+54hjoGMAg54okHXKyZN5/oVdva6TNOCoRohIX+g1qu3+0q6pKYzcJFFDDV0xuP8ed319F5O/MJld1zciFS7xXX/99TR/43EuW7+UjkMHB9hDwZo1a9j97c0UwubYJil88W0fBILXXDHPz7IrNUm1wHLg3UAjsEnS2oh4uK9tnnzySerr64fkD9iyFixY8IovhjzL9rWrq+uIvnCPZP99/Zv0/MK0w/UXDNX031lfDh3FFbHFl3yb5T+89BWjpJqaWiZPntR9Pyk7Kip+njJlCi/v6+LZ/YVLhOPH1HV/R0yfcCbPHWhl2plTONDYwd4Drew50Ipq4FDXoe4QK2r8RvOAT60e/+pxNLe1MGHChCM/0eNYVQcScB7QEBFPAEi6HZgP9BlIBw8epLm5ua/VZdPWlu8/SDOrhN5GLqNPnkTHyy9ysP3FV7SvPWEEkybWsXPnzsO2GzlyDABjRp/6ilFScbTz0v4u2tpfZNTIMRyMA7xKo3np5cLnSZMm8cKhDva17QVg3Og6ALb+oIW/v/CLCHjjktfw8Pd3U3MIFHDm0olcsfCzNDz7JySYcGJpwmXSpEl0Pd9B3YnjSrK/aqJy3JwbKpI+AMyNiI+nz5cCb4mIK3q0WwIsSR/PHdpempkdF9ojovcbWSVS7SOkQYmIFcAKAFXznEgzs8op3QyQPlT7D/Q1AadlPk9NNTMzqzLVHkibgBmSpksaASwE8vVwJjMzG5SqvmQXEZ2SrgDWU5j2vTIiHhpgsy6qP4jNzIbaz8t9gKqe1GBmZscPjxTMzCwXHEhmZpYLVX0PaSCSXgDGVrofZmZGQ0TM6K/B8T5CWgm8xEBPHDQzs3I7daAGx/2khvQ0hzvo93m6ZmZWZi8Dp0REnw9iPN5HSGZmlg/t/YURDJ9A8ujIzKyyRkk6o78GwyWQzMyssmqANw3UYDg5tl+3MjOzo3UAeKS/Bsf7tO8DwKhMabgFsJlZXowG+v1huON+lp2ZmVUHjxjMzCwXHEhmZpYLDiQzM8sFB5KZmeWCA8nMzHLBgWRmZrngQDIzs1xwIJmViaRFkrZJ+n+S/pek90r6g6QHJf1a0sTU7q8lbU2vByWdlOqfl7Qp7ePLqTZa0r+mfe6Q9OFKnqNZKR3XT2owqxRJZwP/DLw1IvZIGk/hd7nOj4iQ9HGgHvgc8E/A0oj4naQxwMuS5gAzgPMoPBx4raS3A3XAzoj4m3Sck4f85MzKxCMks/J4J/DTiNgDEBF7ganAeknbgc8DZ6e2vwOWSfoHCr8X0wnMSa8HgQeAN1AIqO3AuyV9XdIFEfHCUJ6UWTk5kMyGzk3AdyPijcAngVcDRMR1wMeBE4HfSXoDhVHR/4yIWen1+oi4JSIeBc6hEExfk/Q/KnImZmXgQDIrj/8DfFDSqQDpkt3JQFNav7jYUNLrImJ7RHwd2ERhNLQe+Fi6hIekKZJeI+m1QFtE/AtwA4VwMjsu+B6SWRlExEOSrgXuldRF4dLbl4CfSnqOQmBNT80/K+kdFH4e5SHg7ohol/QfgN9LAngR+CjweuAGSYeAg8DfD+FpmZWVn/ZtZma54Et2ZmaWCw4kMzPLBQeSmZnlggPJzMxywYFkZma54EAyM7NccCCZmVku/H+V12tlcWZcGwAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "763ceNBs5dIb",
        "colab_type": "code",
        "outputId": "90454385-ab76-4eb1-ff7c-05e672a5c7ba",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "covid19.columns"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['date', 'county', 'state', 'fips', 'cases', 'deaths'], dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ng3JlJai5hRi",
        "colab_type": "code",
        "outputId": "d5269e90-3b02-406c-d342-ae21fdc4ee19",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        }
      },
      "source": [
        "import seaborn as sns\n",
        "sns.barplot(x = 'fips' , y = 'deaths' , data = covid19)"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fce40ad6d30>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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Qdg5EVkXBR0REglPwERGR4BR8REQkOAUfEREJTsFHRESCU/AREZHgFHw6QA91iogsT8GnAyYnJ8npt1a7SjzShH56QKQ7aIQDybz410jz+XzTUR3ikSaajTgxODhIPp9XrVUypZVjv1sp+Ejmxb9GupzBwUEqlQqDg40P+dHRUaampjqRPZGOaeXY71ZqdhMRkeAUfKQvrNTsJiJhKfh0yEC0Z5s184iI9DMFnw45983V7m6jo6Mp50REpPvosrxF+mE2yQodo5IFCj4tylo3RllsIfq9m4W6373pxYsKHauSBQo+gWW5X343ivfnStx90f+YvgORdCj4BJblfvndqFQqUalU0s6GdFAv1k5FwUekb2S11p2lvErr1NtN+k6hUEg7C6mIa92tNFN2i0KhwMTERN9+Z70sePAxs4vN7Jtm9pyZPWtmvx2ln2dmj5vZi9H/c6N0M7MvmNkRM3vGzC4PnWfpLVkqfPtdFgOmtCaNms888Lvu/jbgSuA2M3sbcAew3923Avuj1wDXAlujvz3A3eGz3H90xSkinRT8no+7vwq8Gk2fMLPngTFgN/CuaLEHgG8Bn4zSp7zaTekJMzvHzC6M1tO1ztswwJvOzu4oyeoYISKdlGqHAzPbAvwy8F3ggkRAKQEXRNNjwCuJtx2N0hYFHzPbQ7VmxCWXXNKxPLfq4//wzbzlNo2SHEoul2s50Os3faRXZLknYGrBx8w2Av8N+B13nzF749fX3N3NzJu+uQF33wvsBdi+ffuq3ivZt5oeXBpcVHpFlnsCphJ8zOxNVAPPl939q1Hyj+LmNDO7EHgtSi8CFyfevjlKE1mTXn8uqFAo1AqlZPdqkW6SRm83A+4Fnnf3zyZm7QNuiqZvAh5NpE9Evd6uBI53+/0ekTQle4apt5h0qzRqPlcBHwW+Z2ZPR2n/Evg08JCZ3QK8DNwQzXsM2AUcAWaBm8NmV0RE2i2N3m7/A7Ams3c0WN6B2zqaKZEGsjoiQCPlcln3uqSraHgd6Wnj4+PMzs6u6b291N18fn6+5+91SbYo+EhPm52d7Y9Cd2AA6n4uIovi2ubMzAwjIyPqFt/DFHwk07L8nIMsFdc2c7kcJ06cIJfLpZ0l6RAFnw7qpXsG3arV/ZrL5fqjBtTDdD71FgWfDmp0z0BX6t2hXwuy1YwE0W166R6cKPhIn6iv9WS9IFsSPFu859NvwVaW6pYLLwWfDopvliZvmoYu9NZ6oKmG1t3qjyM78yz8+Osp5qgzKpUKg4ND5PN5PSjbJt1y4aXg00HxcxVpPl+x0oHWLDjp6jicbrkS7VZnnnk+k5OTTExMpJ0VaSMFnz7XLVdBISUHse0G/fgdiCj4rJKuUrvHWr+LoaEhpk/2XhMVLO1QEE+Xy2X19pOuouCzSvVXqQpG6VlLjSGXy7Ft2zYOHXm+Q7kKr1Ao4CeOA0s7FGh062zox3JEwWcdCoUCTz/9dGauKPvxAK8Xf/arP3Bd2llpm8OHD6/Y061fv++s6MemVwWfdSiVSm0PPJ0MEP12gBcKhcxcGKxHskNL1ms2cc/QhR4YKkiWp+DTZfotQHTServmZq27eS6XS62G066LpjiQVgez7z5qPWgfBZ9VSj67Mzo6uuyyg4OD0XMKb+zmfD7P3PHpFQu0Uqm06BcpZbG4EGiU1lLBMHIGYxvPXfZ76OZ9nwyM8X6oVCpMTEws+fydKjCT623XRVN8znSDRvutFy4Ou+Wiqq+Dz1pOylOnTi3632y9r/zgpwwNbWR0dHTRlzw5Ocmhe67j8luX316lUkn1obpuv8Jr1OTZrGBoNK7b0O5fYeqf3NHRPHZS8jvZuXNnbbrR5+9Ugdloveu9aBodHa2tc3h4mNHRUcrl40xMTDAzM8PY2FiwQjONQFMulxteQLRTt5zPfR18Dh8+zNzc3KqGbY+bA5ZrFiiVSrx20snlZrnsssta+rLjwr7dQ8g3ukJuNj8p7Su8dgS/JfcPBiz1q71et56Lpka12XK5zNzcHMXiScbGxpiammpHNrvW/Px85mtWrerr4LPeEQhWChSVSqXaE6kFyaHk2ylZcDd6QrxbroLqtRr8lhsos/7+gZ11Rld+3nY3gySPy0YFersVi8W2PLhbX5vVD+D1tr4OPmthZrXCLBm0pqen2bVrF9u2bVu0/Nzc3KqaIeL7QzrpWpOsGTUaSy8Lks/itKPJZX5+flFNOsSx1K0dBNIUsum625vJG+mb4NOuL2dgYKB2Mi8sLJDL5VhYWMDdmZuba3iV2WrtB6h1YigWi23tdFAoFCiXywwPDy97hV0oFDh8+PCy97S61XprsvFnB9i2bVvwk7idTZ2dqkm3KouFYbuFbLpOu5l8Lfom+DQamaCVK8LlTqI4EK30Q2WrKQzjq3Yza2ung1KpxNzcHGNjY0s+R32vpbm5uSX5WclaC5t2FlL1vQvrnxXxn51e9v3Jz56lEZTre4gtLCyknv/1FoZm1vGeb2s59jrVU2wtwyA1GrUiS71k+yL4NGr3bvXkrD+JNmzYwIkTJ4DmD8Ll8/mGJ974+Dizs7P4QoUL/9fi5pXkwTc3Nxf0lzeTn3GtTVbxOlbbW6dZIbXSST4zM0Mul2NmZqZWY0kGTWjQFHS60nUnZrIAmT55ck3vr//cydp5UrJpuNk+WE2BHF+sJLc1PDzMzMwMJ6PPstqLl9hFF10ENO691y7xsdeswG50DDbaJyvts+UCQvK9U1NTqxoGKXnOxRe4afeSXY2+CD7JEyQuHJMnxYYNG1paT6FQWNQcFRdu9UFocnKSHTt2LHn/7OxsLR/xQZN8D1Q7BTQ64dpVQ4hPhHi6/qqp/rOs9CxTveV666zmM6w0/9SpU1QqFU6ePLlkiKNTp05RKBQW3Z8DYMEXNYG2s9a11nWtt4ZQX9DENebY4OAg+Xy+dlHTrGl4LfmZnJykUChw8P98D6uchtyb2LZtG6VSqXaBNjc3x/j4OCMjI7V90+z5mfqAWX8RlzxW43XMzMwsWvdaxAV2fb5aXd9K+6xRQEjek0tePKzl+aysdszoi+CTbMoCFrWF53I5LrvsshXX0ehAidV6U1njrrwLCwuMj48vOUDm5uZqtYR4G9PRQZwMAvVjyBUKBQ4dOoS7Y2ZcfvnlK54o8T6oVCo8/fTTDA4O1j5Lcl4nraZgi2uJGzZs4JFHHlkyf+50Ne/uviTf7s7Bgwcb9sBKNoHG+3B6ehpofCWftFxh0I42dzvrLC7auHHJMdRsu4VCYck262t7Q0NDwOLn0uLPm1x3XDjGx91yNdj6gn/owq1sWvhJrRZR7+TJk7VgBI1rybG4xh8fk8PDw7Xm4hdeeIGdO3eyYcMGRkZGaudxct2NtFqIN/oOk7VqM2Pjxo088sgjLdVQmh1PyfN5uXtyKx1TWR+KKDPBx8yuAT4P5IAvufunW31vssvtfHQSxu3JlUqFQ4cOAY0P0pUKpKShoaFFNYuYuzc9QeKTsFmTUbFYZHp6uva6XC5TKpUWPW906NCh2kkZF9T1nyVZ+MSfG1i07kamp6drV64zMzO19dQ33cRX1612VEgWenHzWXJevL9mZ2cbr6CF863R56pUKuzcuZPKwgIk9uGuXbsWfQfJ/MSaFZqlUqlWoBeLxWWbtpYrCIevey9T19+wZPlmg9e20rwSF9JJ7s6OHTvYv39/0wKu+mxNkWKxyM6dO8nn87U8J5s4q99TkfLwcO3z1wf95LHbaBvJ0UIGBwdZWFiozYslj9MTJ07UjrNG+6V+HzdrXmv0Hcf5jL/f5H1Ad68dj432W33Ajn8AL96P4+PjPPLIIw3Lk/i9yXOs0WeK59eXF3HQjs+l+guH+n2S7Fg0NDSUSgebTAQfM8sBXwT+MXAUeMrM9rn7c42Wf+GFF2rNXmNjY4u+6Ep0ADdqPosPqOSBshqnTp2qBQsDWu182qg2lZQsRJvVvCqVyqKCuv6Ea3YfYKUusu6+5MoV4ODBg4sK4PhATu7L+gJ6ZmaG4eFhyuXykntbIyMjjI+PL9lOcsiYeDvr1Wg/1O/X5YJosmBe0rQXzT948CBXX331klppfaEVB+1yuczpP/9LiIJPXFgkC93p6ekl+3Qly105N2oabqRSqSxaT6MONMm0lY6pOP/xZ5ufn68FgmbnQqN9nFQul2uBJd7H09PT7Ny5s1YziJu/4lp18jhI3jepD3z1CoVC7WJjenqajRs3MjY2xvT09KLm9Prj+cSJE0suTOM8LLfN+Fhrxt1ZWFioddKIy6Gk+gfqk0F1bm6Ow4cPB/+l2IGgW1u7K4Aj7v6Su58CHgR2t/LG5b60+ArNzHjtnv+4aF7yCie+olju3tDY2Fht2t0ZDNjDtVHz0smZ6ueOTzhj7U1qzQqTOLjFB3L9csn5xWKRkZERRkdHmZuba1iANarlmNmS7awUrBsaHGD4Y+9uefG500uDTz6fh4HGV/WNuPuKAWJycrK2T7xB09Ry+7RZbbzTv9SaHKtwUdrAGwf9cFQTSoprN/l33s7U1FStSXBwcJCRkZF15anRvaz4oszdFzVv1Qee+P2N5PP5Re89Y+CMJS0PIyMjTE1NMTBQLU7jY7vR8RzXPsbGxtr6Pbk7AwMDTc+tlR5DSGNkBcvCw2Fmdj1wjbv/VvT6o8CvuvvHEsvsAfZEL98CbIymHbAG08vN6/R0mtvulnykuW3lo3u2rXx0z7adakwI8jvzmWh2a4W77wX2xq/NLI6qyR1Zv1Obzev0dJrb7pZ8pLlt5aN7tq18dM+2gwSdWFaa3YrAxYnXm6M0ERHJoKwEn6eArWZ2qZkNATcC+1LOk4iIrFEmmt3cfd7MPgZ8nWpX6/vc/dkV3hbfUezGttU0t90t+Uhz28pH92xb+eiebTuso2fSKmWiw4GIiPSWrDS7iYhID1HwERGR4Lryno+ZHQfW99SZiIikxYFr3f3rzRbo1prPfcBxqh9ARESyxYA/iYZGa6grg4+7fwL4rbTzISIia3Y21aHRGurK4CMiIpkVt1gNAGPNFlLwERGR4BR8RESkneKHVhdYZhg0BR8REemEGeDJZjO7tav1T4HmP54jIiLdzIGPuHvT4Xo0vI6IiASnZjcREQlOwUdERIJT8BERkeAUfEREJDgFHxERCU7BR6TNzOzjZva8mb1uZneknR+RbqSu1iJtZmbfB65296Np50WkW6nmI9JGZnYP8PPA18zsE2b2x1H6/WZ2j5kdMLMXzOx9UfrbzexJM3vazJ4xs61p5l8kFAUfkTZy91uBaeDdwOt1s7dQHWL+vcA9ZnYGcCvweXf/+8B2QLUl6QtdObyOSI96yN0XgBfN7CXgrcD/Bn7PzDYDX3X3F1PNoUggqvmIhFN/g9Xd/U+A9wP/D3jMzN4TPlsi4Sn4iITzQTMbMLNfoHpf6Adm9vPAS+7+BeBR4B2p5lAkEDW7iYTzQ6pDzI8At7r7z8zsBuCjZnYaKAH/Ps0MioSirtYiAZjZ/cBfuPvDaedFpBuo2U1ERIJTzUdERIJTzUdERIJT8BERkeAUfEREJDgFHxERCU7BR0REgvv/+kgOQ9aaC4oAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "av3DZVCo5vdm",
        "colab_type": "code",
        "outputId": "5a4e63a4-2f4a-489a-8543-33d93db681c8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        }
      },
      "source": [
        "sns.countplot(x = 'state', data = covid19)"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fce3ede5390>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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2D5G+jZndbWbT4n3rSDczu8jMppvZY2a2d2lZE2L6aWY2odXbIiIi/Us7umc7gX90912B/YFTzWxX4CzgHnffGbgnhgEOB3aO18nAREhBFjgbeDewH3B2DrQiIiLN0PKg6e6z3f3P8fkV4GlgJDAWuComuwo4Jj6PBa72ZDKwlZltDxwK3O3uHe6+CLgbOKyFmyIiIv1MW28EMrNRwF7Ag8AId58do+YAI+LzSGBGabaZkdZdeqP1nGxmU8xsysKlL/dY/kVEpH9pW9A0sy2A64HT3b1LJHN3B7yn1uXul7r7GHcf86YthvbUYkVEpJ9pS9A0s01IAfOX7n5DJM+NblfifV6kzwJ2Ks2+Y6R1ly4iItIULf/JiZkZcDnwtLv/W2nULcAE4IJ4v7mU/iUzu4Z0088Sd59tZncB3y7d/HMI8LVWbENvdfdlR9SlffCzt7chJyIiG6d2/E7zPcAngMfN7NFI+zopWF5rZicBLwInxLjbgSOA6cAy4NMA7t5hZt8CHo7pznX3jtZsgoiI9EctD5rufj9g3Yw+uMH0DpzazbKuAK7oudyJSH/0p6vm16UdOGF409c75/vP1qVt94/vbPp6ZcPpMXoiIiIVKWiKiIhUpKApIiJSkR7YLiLSy8y98C91aSPO2LMNOZFaCprSJ3zxhvonJE489s425ET6st/+qv6Gn/d/rPk3/MjGQ0FT2uLb1xzaZfjr4+9qU05ERKpT0OyD7vvpkXVp7/vcbW3IiYhI/6IbgURERCpS0BQREalIQVNERKQiBU0REZGKdCOQiEg3HrlsXl3aXp/dtg05kd5CLU0REZGK1NJsglkXf7HL8MgvTWxTTkREpCeppSkiIlKRWpobaM4l59SlbXdKfZqI9B8vXjinLu0tZ2zXhpxIsyhoimzkxk66oy7t5nGHtyEnIn2fumdFREQqUtAUERGpSEFTRESkIn2nKX3a4bfU/8/mHUfrfzaluZ65ZG5d2i6njGhDTqTVFDTldZv4i0Pr0r54ov4fU0Q2PuqeFRERqUgtTRHp4sPX31+XduNxf9eGnIj0PmppioiIVKSgKSIiUpGCpoiISEX6TlPq/PLK+rthP/4p3Q0rIqKgKf3KETedVZd2+zEXtCEnItIXKWiKSJ917fUL6tJOOG5YG3Ii/YW+0xQREamozwdNMzvMzJ41s+lmVt/3JiIi0kP6dPesmQ0E/j/wQWAm8LCZ3eLuT7U3ZyKv31GTft1l+NZxH21TTqQ3mfuDh7oMjzh9vzblpH/q00ET2A+Y7u7PAZjZNcBYQEFTRPqVuRf9oS5txGnvZd6P/rMufdsvf6Db5cy75PoezdfGxty93XnYYGY2DjjM3T8bw58A3u3uX6qZ7mTg5Bh8J/BsfB4G1N9J0P/Se2OeVBa9N7035kll0dz0t7j78AbT9D/u3mdfwDjgstLwJ4CLX8P8U5TeO/Oksui96b0xTyqL1m5zf3719RuBZgE7lYZ3jDQREZEe19eD5sPAzmY22swGA+OBW9qcJxER2Uj16RuB3L3TzL4E3AUMBK5w9ydfwyIuVXrb193b0tu57r6S3s5197b0dq67ndvcb/XpG4FERERaqa93z4qIiLSMgqaIiEhV7b59t3R784XA6aXhu+j6c5LvA19ZzzIcmARcE59nAquApTH+IOBW4E/A0cBZwPKY9r0x74XA6cCvgceAZ4C5pXX8Bvgl8Hg36/8+8CbgUdJvnDqBecD8SBtcM885wJml4VGxzpuBabHMV4E58Tm/FgG/B+6LZZ8T834M+B0wNeentOwzge8CdwJLgcXAA8CHY/xmwOqYb0GkTQSeACYDs4ErgXE127BdTZnfHp9fAP4a5XAf0AHcQ/qd7NNRHnn7ZsXwLOAi4Il1lM8TsS8duKg0rhO4P+/v0j5x4Ml4/SWGX47tXxuvNTFuMPAp4GLgGOADUaY7kB6acSYwJq830n8PHBjDVwL3kn4O9QLpt26nA0NqymxplNuDFMfgHOAdMf6RyNMS4A2k4/U/SMfEC7GfVkRZ3A68I9bzfOR9SSxnDPCzXJ553TV52YF07Ofz5P9FWT0GzIh94LFvrgN+DLybdG79lnSsvhTlODHK8HRgYcy3S+y3RbFNL0f6YtIx5VEO8+l6fM+N5d5Xzn835/5BwHOx/QcBBxLXkNg2Jx3DXylt4+ooq3OBb8Y0T8e2PxV5G1DK0y4x77+Ulvf5WOdlsQ152rWxPffH/n0GuAR4iHQ8XUk6Rhpd92bHftsBmB75PwbYtTTdCOBXsc1TifOYdO5/Prb/nFJZTwO+TDrXfhZpp8SyHo39eVl5HQ3K+FzgA6Xh3wHfBj65nn3zP+dLhTiwdD3jXwCG9VDMWee6unv1ppbmH0k7GjMbQLrY7FYafyAp2K3Lq8DhsazVwB2kk97KE7n7ge5+i7tfQLoZ6n7SwTAu5n0/sC+wTyzzuZp8LHT3PcrLNLNBwErgWNJ3xe8iXWCWAP/q7sPd/V3uvqpCWbwZuMndd471/xfppHPSRcdJFyyjaxmNIp2Q2SrgWDMr/+3DeOAm4KjY7vGkn+rg7itIgc2BoWa2J/ARUiBsyMwMuJF0YVsN/AD4GumiMRDY3d2HkYLqwtKsa6KMVkY+fxLDF8a8uUwH0H2PyBp3P602S6W8HUxxERvj7ruRLniQLiaDSRfu35AuYk8B55eWdQzwHuBj7v4ScG2U0xR3P83MBkX6vcSx243TgSEN0m+M9Rup7BZT/IRqIOli+wd3Xw78O3AAKUDNjjzfCXyRVN4jSPtyAvBvpOMed58C/PM68oa7vxTHPmZ2AOnY2Dtee5FuCHmVFAT+nnTObBOz70M6VncANiGV6fmxLZACSvn5f6vcfWgsby7wRtL+3pNUaVgb0/3U3UfEukcB265rG0IHMIUUNN9D12vIPGAPimvIV0jnFO7+zZhuLXBdHCefiLydnYuJ4gEpo0gVtAWkCuCTnh6wcnmMX0s6rlcCO5POnwGk68iuwKalPD9A/XVvSOTrJdJxuhcRNGM6I53D97n7W919H0rnMWmf5ONxMvA4qbFwPqncDyZVDB4ys12AN7r7g+7+WW/wCFIzG2hmA939m+5e+3ihG9z96tp5yvL5sq5p+pSeiNg9FPV3AGbE5z2Aq0g1661JB9liUm3wYVLt+lKKG5lOI13w1pIOinGkC/F04G+R/mx87ozhaaRWT67h54trbmnl4LS2NPxyTdoKutYuczDLr7Wl6dfUpOUW1qpYzoqYZnlMs6Rm/rU162mU1lkz7DXLWFKTvobU4nklhleVxq+JsuisWcZiUiugNh/z431ZzTLy+IXABaXyrc3jmm7SG332WFYuw9r5unutbx3repWPg3I5r1jPfsnDnaTjZ01pnhcarH9ag/10OekC3ChfSxusr/bYrT22y6+VdD3WGr06a7a5dtryubG0m2kWNEjr7CZPtduyojRcu625klfet2tK85aP3drjIB/b+TgvL3dlzfoaHYsvkwLiuo6XqsdVo2N0XWWeX6tinldjP+Z9uYJ0LemMcSspjt3O2E93kXoPysfMauDPNetbRfop38uka8WiKPel8T6ZVOnM17Mlse4ZpB68g0jX2j+QKipLSQ2BPwHvbNT6A7YnVcQfJV3v31vb0iRVHKaSKgAnl5dBqiD8JfI2ItJHkyopjwPnrW9dvb6lGbWqTjN7M6mW9AApIB1Aat4/Tnraz77uvjupy+qomP0sUm1sNalGNT7Stwe+TtqZw4FTSd1JkGr5e8XnV0gX+xXA93KWSF2L+ZF7z8c0S0nBNx+o+5ICyRSKg2x5LNNiursoWkwnRX4htRaWkyoFi0jdHZuQDuoTKU7eefFeyygO9OWk1kkOvrlF6/G+jFSDzSf72lKeZsey7i8te0As75XSchaSat9vIB2UnTHfH0jdiRZls6S0nBWR921i+oGRPivKD9KJl1uISylOYIsy6YxllANErq0PoQgoxLZlL5bS88lfK6+3fNHIrYR80crrzNMPIFXI8nz5IjSVVM7E/LNJFTJIZQSpK3difH5zzJ8rKHNJJ/ZlUTadkefjYnh1zNdJKuNlpC7150rj8vGW85rLv1wOUJTTKooKDxQtxLyeNRTHQp43T5/LawBpPwF8lq7H3w8oLti5rPOFfiDFz97ysvP4nO+VpNZrrlCsJbVcc+Vyi1Jeno/5c9C4O7ZhOkVZ5v3jpO7ShZGHvA9WUZTlS6U8T4n3HEwhnat5/c/S9VF05d6tXBZ5vuWl4dqKzprSfMtK25LdBVxPUV6bkCqQ8yIvHaQGxN9I+3gR6TqTW5wLYx2DSde3XJF7mhQwFpG60y22dTkp+BwR0+dGy72kY28SMJTUU/Aw6Rj+OemYXUDRUl9J+mON/UjX85dJjaBv09jHgLui92lPUkCr9ZloZY8BTjOzN0X65sBkd9+TFAw/F+k/BCZGL+Hs17iuQrtbmDW1jF+SAt5VkfkjSDWC/0s6MI4jBdLHSRfds2K+O0k7L39HMYV0kvwulvcy6WCaSVGzfYniovD7mGY16UTKwWoVqTaUT9ipUdj5IM8nUD4Zc614DkULt4PUUqitGeYTpHzR3JHie53f0n3rolybXl8NNr8vpajZ19buc+uwttX0IkXrOHdH5dp5ed2Pk7rCPbZ3FkVNOedzKamikluz68p7uYWau+xW18z3SGn6BXStoVet1a+uOF+5bHKrZFXN+Fwu+T3X7vN2/DTmfV9pm9aSLkpLYtrzI2029fnurmchB9u8HS+TWgp5vhXdzPsSRaCZQ/3xUt7mXHnIx+NjFC3LvN7cW3NdzXLmU5wf5XXUlt8Cuh4b3R0f5VZged5ya3geqbLXUVrXGopWaX49T3F+N1pf7flQ+1pcM1y7TXn/zqpJ764noDwul3dtz8ZfqT9/87VsNakl9wSply6Xefm9fKxOpah85Mriq6VymkNR8Zsbn88h9ezdUZr2ZVIwnkmqoPwd6euC52P4INI1+ueRv3wvwePAM920NN8X854DvKs0/gWKluY5pID+F9I5tH+kr6TohfwIcW9M5HGT+Dx0fevq9S3NkL/X3IPi5pMDKL7PvIR0E8oepIvQZjHfkaS/CDPgM6TW5kCK2uEmMfwcqUbopBt9BpJqyfuQduJAilbqANKOmBbDO5C+V9mW4vun2aSD+jaKVtsA0oUifwfjpe17hXQjwGLSif17YgfH+rcmHRSU8rSConYMxYm2hKI22xGvvL7OUr7z++aRt0GksoUi8Ofa/ljSiZ8vQPmisSbyYKV1fp2iVTKS4vGFnaSWKLHsyTHPclJNOK8rd+Hkcsm18EdK27uW1OpaFq+/lrbz7aUy+QvF96Xlxyjmi0pelpfWmbe//NlL862t+fzH0vBSinJ4kqLiM4PUDbWEdJPGaooyyxWq3UknrFO0WgfHsv4UaSNinQ/Q1SpSmS6K8YtI5TmpNM0g4rsvihZp3qflbdw83geQWu15e+ZSBJlvxPrydSLPuxvFhTwvM3/XNTbe8/I2jTwNptgHVlpW3ge5kprXk8ur3GrNlalpFIEIUnnmFn0ezi3ZvA888jAjpllLaunvXspv3tedpGP7JbpaW/O+iq7HyaSa6Y3ivMnTeM34vF05/f7SdEtI+6McUJ+h2P85qP6U4jzO5buSFBRfJV3/HiOdlx0ULfY9KZ6gdgnpejaN4njNecu9Q9kg4P+QrqeTSOf4T0hlNozUyKntSXhrbMtkUnBaC3yI4hrehbvfRwpms4ArzeyT5fFmdhDpJr0DokX5SGlZqz2iYeSj/BCfcvlXWlet3hY0/0Tqcu1w9zXu3gFsRQqc+Qv8BWa2Bel7y/zl+U7ufi/pJBtE0RKcQzoxBpBOhM1IB5ABh1FcSO4k3UyxhlRr9VjOQtIdjpBO/pEx79x4H046sPchHZTZbRRdl1CU85DYnnzDxFCKC9Y04GrSTQY5/6/EvG+gOIjzsrYorW9oTLO2NM32pe2Art1jubtnIKl2mC8YZ0e+8oU+34Q0MNZXvnjm7ybyxaicv9wFPoQi2Ayl68Gb9wUUQQPSjRN5O9aQ7upbTeoWzoGcWHc2PMZB13LJFRIoWpVvKI3PF3IobqzK+y3XyvP8Q0rDQ9HtCI0AAAWhSURBVCguJNtE2kDSReddsa35+568/N0j7QJSDTsfk2sjHwMpbjTJ30O9pbTOHJgHkwKekSpYTqoo5lbgpqRKG7HMoRTlTGl78r4YWdo2SOW8SWlcuZtxk5oy6aQ4n/I+zBXAvN0PUNzoVF5/PpZyOW5dWkYet4qiUrGG1HtDbH8O+pDKtVyx3JSi6zZXGAbGuq+L4Vz+UPQgrCVVZnPZ7EQRsOeXpi9fN3PFchGpJ6zWANLd9MTyc0WprFymW5Q+b0nXY9hJFaLctZiPm50oKserSWX5xhifrx1bkCqM+ea33GC4LpZ/dAzvXMprLuM1sQ1zSN9RHhvz/C9SWe0ZwwtIgWeXBuUwKPK9JanCO5B0l3pDZvYW0q8WfkqqOO9dM8mWwCJ3XxY3M+3f3bJK/kjRKPr4a1hXV+3ukq1pmg8kNfXPK6VdCTwbn88jtTb+SLpt+hzSSXs/6UK0htTFdS1F98KfSRegZTGcuzY6SAd8J6lG9hJF7bbc1VbuFszdGLnGvIyiq8FLy51KqtHmVt8fqO9m8dKy840Ui0gH3fKaZa6muECWu46W1aSVuzFru3tquzfLy8nfFS6vWdajNetdS/2NQE7qdr22NM1C6tf/MnBFN/no7uagBXTtXiyX4cUULcfaG5gabWejV6Npupuvdv/l6VZ0k17uYlxNqly9QtG6d9JF48XSvKvp2oW4pmYZjbrka7uXl9P1uCrvq9r9Vs5zo+7ZnL6qwbq6myfns/bGnNquy9p9v7zBtlTdf8voesyVvwIp75vldO1yLd8YM7mbdeT5lzTI3yLWfSNale2pPfaXl9aZu1Rfpb5lX7ue/D3w70g9WOXpXyFd+3ILtYOi9+ivpXLI14BFMe4Vit6N71PcCLSY4tycQ+q5mk1ReTmN1OL8G+n6cRCpIv0YKbjn9Z8HvNBN9+yEWO4jpOvn6HL3LKlidAfpu9ibYrsPKi8jPo8DrvR13wjUcF3dxql2B8re+gK2iHcjdV2c0e48vYa8DwQ2i89vI323MLgF681l9qY4GbfrZrrlwLWvYblDYnlbvsb8nAl8q937o5SfHUgt931JPyVp9fqHUHzXMx64ud1lso5jqGnnXWk/DGgw7gUa/A6QBr9P7qny72P7ZRDp508fbnee2vXq0w9sb7LPmdkEUnfGI6Q++75iCHCvmeWus1O82u9DX69bzWwrUpl9y93n1E5gZufG+H+pHdeImX2AdCPVhe6+ZH3Tl+a7kVRheH/VeZopvic5n3Q33yRK3UMttA9wcfzObzGpW7e3aep5V9oPX3H3teubvod1V/59Yb+cE+fiZqSbjG5qc37aRg9sFxERqai33QgkIiLSayloioiIVKSgKSIiUpGCpkgLmdnpZtbo4e0bNJ2ItJZuBBJpITN7gfSPKwt6YjoRaS21NEWaxMw2N7PbzOwvZvaEmZ1N+o3gvWZ2b0wz0cymmNmTZvbPkXZag+kOMbMHzOzPZnZdPBVLRFpMLU2RJjGz44DD3P1zMbwl6Tm5/9OCNLNt3L3DzAaSnlt7mrs/Vm5pxv+h3gAc7u6vmtlXgU3d/dx2bJdIf6aWpkjzPA580My+Y2bv7ebhDCeY2Z9JP+TfjeJh62X7R/ofzexR0mO/3tKsTItI9/REIJEmcff/MrO9ib+4M7N7yuPNbDTpUX/7uvsiM7uSxv/6YMDd7v7RZudZRNZNLU2RJjGzHYBl7v4L4Lukf094hfQPFJD+geRVYImZjQAOL81enm4y8B4ze3ssd3Mze0cLNkFEaqilKdI8ewDfNbP87zNfJP3N3Z1m9pK7/72ZPUL6m7UZFH+jBnBpzXSfAn5tZpvG+G+QHjouIi2kG4FEREQqUvesiIhIRQqaIiIiFSloioiIVKSgKSIiUpGCpoiISEUKmiIiIhUpaIqIiFT03w1DboCsG4wyAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "J-ek-tKl59xs",
        "colab_type": "code",
        "outputId": "6808e0ff-a4de-40ca-abad-52a79e5225ad",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        }
      },
      "source": [
        "sns.boxplot(x = 'cases' , y = 'deaths', data = covid19 , palette = 'rainbow') "
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fce3ab155c0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FmA1-CHP7V8V",
        "colab_type": "code",
        "outputId": "6a023071-8548-4b37-f620-a5b7280ac68d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        }
      },
      "source": [
        "sns.barplot( x = 'cases' , y = 'deaths' , data = covid19 , estimator=np.std) "
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fce21ccebe0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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TgdOB+3pZNzMz665sg/yS/hJ4O3CypN3AnwBvl7QOCOBJ4CMAEfGIpNuAR4EZ4PKIqDZ7XzOzQVafuDAKExhyziL7QJPi6+fZ/2rg6lz1MTMrgvrEhVGYwOA7WpqZWRYOGDMzy8JrkZlZ3xT1Qk/rDgeMmfWNV2Iebu4iMxshh371IjAaM5is/9yCMeuBwnQFHarN/h+WGUyVSoWjj/ZprKj8N2PWA+4KymP23S2tWBwwZiOs3lVWP1HPvggwZ1eaWx/Dz3+7ZiNsdlfZ9PQ0Gzdu5ODBg01f7ya3PoafA8bMDjM9Pd3vKtiQcMCYDajCTBxoQ/0GYocOHep3VayHHDBmA6rVxIFmd6+kyyf4+me0Ur/fjI0WB4wNnV5/s8/9eQt9/9kBlONmYpVKxWMpNicHjA2dXk8Jzv15nuL8a52GWb1rbhC6EYeRA8asQ4M09tFKNaLfVcjKXXP9lW2pGEk3SHpW0kRD2YmS7pT0j+nn61K5JH1J0qSkhySdm6teZotVb1EMyv3r69/icy8PU6lUauM8ZknOtchuBC6cVXYlcFdEnA7clbYB3kXtNsmnA1uA6zLWy2yk1L/FL+SalkOHDlEqlRgfH28ZHtVqtRCh2+7EA8svW8BExA+BX8wq3gTclJ7fBGxuKL85an4CnCBpZa66mVl7IoIHJ58eqBabJx4UR69XUz4lIvam5xXglPR8FfB0w367U9kRJG2RtEPSjnzVNDOzxerbIH9EhKSORxgjYhuwDWD58uXDPUJp8+rXYHsv1ukyGwa9DphnJK2MiL2pC+zZVF4G1jTstzqVmc0ZJN2evlsqlZiYqM1JOeecc+YMrfpYxiAvee8r6q0Xeh0w24FLgGvSz9sbyq+QdAvwZuCFhq40G3HdCJJ2WjuVSuWVdbhyjzf0e6pz9Hh6ssdERlO2gJH0l8DbgZMl7Qb+hFqw3CbpMuAp4P1p9zuAjcAkcAC4NFe9rJg6OeHW9+2ki6pfFyvOVddu1qc+PXjQr8mx4ZMtYCLiA3O8dEGTfQO4PFddrPg6OeHW912yZEm2+nTrCvBe1LUo04Nn68b9XupdeUXv0nPIN9frWWRmTbUzcD77Qr5W3S71kFjIxX/1a0cmJiYW/B6jrlqtdjRO1ez6lXpXXq+79DpVrVbZtWuX/53M4qVirBDaGTif75t64wB943suthtqUJYaGfQ1t6ampgb++pWitiT7yQFjQ6FxgD5nd1RR9SMIu3nF/MzMzECHizXnLjIrnPmWJvG1J/1TLpfZvHnzK9uD3uKw/NyCsb6qfwtuHMSdPeDfGCq9uvakncHlarXak0UkF2Lz5s3s378f6O4U4QMHDnTtvWz4uQVjfVUPk7kGcUulUst7xLeaslzv3+/E7MHluVYKXugikrm1EwQ57nAJnbUy6+FX9FlitjBuwVihtRMMs7+hz97uRv/+MA7gzp4U0S0LCdyizxLrhmat9WHnFox1RbtLui9WtVpt+g25n2MBi/ns2S2jTv4cG/8c6nXopPWQq+XlcZnmWrXWh5FbMNYVvbxSvt0TY7NxlKmpKTZu3AjMv95YM/WpwO2cQNtdbWB2y6jVn2PjigfN/hyK2F1no8sBYwsye2HIusbrMYA5l39ZyHIvnWp2kV5jd1n9wrh2Q6aTqcCdXsHf7p9HO0FeKpWahqBbFvMbpa6rXnHADLF21vda6KKLcy0MOfskXC6X2bNnDxs2bODVr341Z5xxxisn0unp6SNOwO2MdXTrRFmkcZVuLinT7d/p0K+e7+r7FdUodV31igNmiLXzbbcXXVsRQbVa5cCBA22dSHv5TbtSqbB582aWL19eyOnGc+npRZWH3PKxhXHAjIhOWyqt9m88GXeyqGH9uKJMT60H3/79+1u2Hrox9lLvQhykMDNbKAfMiOi0pdJq/8bB5HZbHNVq9Yh95+uWmJqa4uDBg229d7tyB1qrFlq9C7Hx9WYBPXssq13VapU9e/Z0XnHri37fFyg3B8wIaJx7P9c358bpss2+gffjP8LBgwe73i/e7P162Zpqd/B9MWuL5R5L6MUEjYXq5vpovdCv+xT1Sl8CRtKTwH6gCsxExHpJJwK3AmuBJ4H3R8Rz/ahf0XV6sm88gU1PTzedOVWtVtm5cyeSiIjDvmGXSiV27drV81lIvR50LcIgby//jBcaqL24x81CeX20YulnC+YdEdH4FehK4K6IuEbSlWn7U/2pWrG1+61nvtYKzH//jcYL9xr/0861ZEqzz1jszaYG2SCc5NoOVA/y2wIV6QywidotlgFuAr7PCAXMfK2SuV5rnP77rW9964j3bHXRXTvf9mavA1a/sVKrb7/NxltsbrP/PBsDvR7Uox7aNnj6tVRMAP9X0k5JW1LZKRGxNz2vAKf0p2r9UW+VNOs/nv1avWVSn/67f//+jpZoqS+7vtA+9Gq1esS3X4fJ4szVmmi8K2Snd4g067d+fR36VxFRlvR64E5Jf9/4YkSEpKb/41IgbQFYtmxZ/pr20ezB1PrMomYzqxqDqX7cfCd9L7veX50E8iCF9yANsFt+fQmYiCinn89K+iZwHvCMpJURsVfSSuDZOY7dBmwDWL58ef9HZTOaPZg6PT3d1jpVe/bs6duAdb+va+mnIs6q6rVBCkPLr+ddZJJeI2lZ/TmwAZgAtgOXpN0uAW5v9z17tZJv0XWyWmu1Ws0SBkWYidUvMzMz7sKyrhiWC3L70YI5BfimpPrn/0VE/B9J9wO3SboMeAp4f7tvOOxzydv5VriQi+tGOQxyyd2CcwthNDS7IHcQ9TxgIuJx4I1Nyn8OXNDr+hRVpxeMOSyKwX8PZr/mOY8F09g09rdVK7Kc/z673RKsX7/VOGHG8nPAFES9i6s+kJ+6EM0G2kKDotstwfqtGepjZNPT00MxxlF0Dpg+mX3x5Oz/UO5qsSLqtNXS63/HnQTGMIxxFN1AB8zSpUtZsWJF3+feN4YFzH0Xx8Z96zfcqneJ2XBqdttmy6fTWXzuhs5roAPm1FNPZevWrX0/QU9MTLwSFieffDLlcvmw5da3bt16xDUq9S6wgwcPDvUMuFHX7LbNNjzcxTa/gQ6YIiiVSq+s19V4IWTj82arEfvEYzb4fN3T/BwwizQxMTHv6+Vy2S0UGyr97pKeSy9mXg77DcK6zQGzAKVSiYmJiSw3xLLBNSr9+UX9PXvRmhj2i7q7zQHTgXqwzF7C3szMjuSAaaHeJH7xxRc5cOBAYb+9mZkVjQNmDqVSiQceeMBdYGZmCzSyAdPY3SWJo446yq0TM7MuGrmAKZVK7Ny587Cy+p0hzcyse0YqYDZs2OAgMTPrkaEOmM2bN7N///5+V8PMbCQNdMD87Gc/44ILDr+FTH3Wl+eqm40Gr/dWXIULGEkXAl8ElgBfjYhr2j3WV82bjR4vu1RcR/W7Ao0kLQH+HHgXcBbwAUln9bdWZjYsPAbbW4UKGOA8YDIiHo+Ig8AtwKZefLCA1yxdQrPbfB177LGcPbaUGzYt56ublnHW2BKWHgXHLIGlDbeTOEo0Pd7MbBSpSM1KSRcBF0bEh9P2h4A3R8QVDftsAbakzXPxOd3MrGMRkf3cWbgxmFYiYhuwDUBScdLRzMwOU7QusjKwpmF7dSozM7MBU7SAuR84XdKpko4BLga297lOZma2AIXqIouIGUlXAN+jNk35hoh4ZJ5DngDW9qJuZmZD5GAvPqRQg/xmZjY8itZFZmZmQ8IBY2ZmWRRqDKYVT0s2MyuMV0XES/PtMGgtmAPAvL+QmZkVw0AFTES8BvjbftfDzMx4a6sdBipgzMysEAI4qdVOgxgw5/S7AmZmI07Ae1vuNGjXwUh6CTi23/UwMxtx+yLi9fPtMFAtGEnC4WJmVgRfa7XDQLVgPE3ZzKwwTouIx+fbYaACxszMBsdAdZGZmdngcMCYmVkWDhgzM8vCAWNmZlk4YMzMLAsHjJmZZeGAMTOzLBwwZm2QNC7pIUk/lfQ1Se+RdK+kByX9jaRT0n7/RtKu9HhQ0rJU/klJ96f3+Ewqe42k76T3nJD0+/38Hc26baBuOGbWD5LOBv4Y+K2ImJJ0IrXVZN8SESHpw0AJ+ATwn4HLI+LHkl4LvCRpA3A6cB61RQK3S/rXwBiwJyLenT7n+J7/cmYZuQVj1tr5wF9FxBRARPwCWA18T9LDwCeBs9O+Pwa+IOk/AidExAywIT0eBB4AzqQWOA8D75T0OUm/HREv9PKXMsvNAWO2MF8G/iwi/gXwEeA4gIi4Bvgw8Crgx5LOpNZq+a8RsS493hAR10fEz4BzqQXNZyX9l778JmaZOGDMWrsbeJ+kkwBSF9nxQDm9fkl9R0mnRcTDEfE54H5qrZXvAf8+dZkhaZWk10v6DeBARPwv4PPUwsZsaHgMxqyFiHhE0tXADyRVqXV1fRr4K0nPUQugU9PuH5P0DuAQ8Ajw3YiYlvTPgb+r3XGCXwIfBN4AfF7SIeBl4D/08Ncyy86rKZuZWRbuIjMzsywcMGZmloUDxszMsnDAmJlZFg4YMzPLwgFjZmZZOGDMzCyL/w/eMGArBZbKnAAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kc_vDrT37clx",
        "colab_type": "code",
        "outputId": "81fa3c99-ec05-432d-ba8f-5612303546aa",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 142
        }
      },
      "source": [
        "covid19.corr()"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>fips</th>\n",
              "      <th>cases</th>\n",
              "      <th>deaths</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>fips</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.017667</td>\n",
              "      <td>-0.020875</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>cases</th>\n",
              "      <td>-0.017667</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.962511</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>deaths</th>\n",
              "      <td>-0.020875</td>\n",
              "      <td>0.962511</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            fips     cases    deaths\n",
              "fips    1.000000 -0.017667 -0.020875\n",
              "cases  -0.017667  1.000000  0.962511\n",
              "deaths -0.020875  0.962511  1.000000"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "s5VGllgB72nS",
        "colab_type": "code",
        "outputId": "154bab0b-9ae5-4a01-b688-25191305a5c2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 286
        }
      },
      "source": [
        "sns.heatmap(covid19.corr())"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fce1eef5940>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QFCOvC7t8CDd",
        "colab_type": "code",
        "outputId": "11b8e8f5-737c-4696-a8a1-6d79e1bb361e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 286
        }
      },
      "source": [
        "sns.heatmap(covid19.corr(),cmap = 'coolwarm',annot=True)"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fce1eb006d8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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83lzwhV4AvLW2iu5FH7Vauxfms72itlH57RW1dIsvU5TH9ooamnPOmd15fXkl9fXOzl37+NdbuxhcXMD7WzLrp5qkn5qtW8nv2WP/en6PHtRu3daoTO22bayafD0AWe3bU3T256iv2k3Nli3sfnsNe8uibxKvWPQiRw89MbzgQxBJ817ToNFtNrNfAl8FFphZfiuODd28Be8zflIp4yeV8uri7Ywd0xOA40sK2F1dR8WOxkm3Ykcte6rrOL6kAICxY3ry6uJmX+jJlm01DBvaBYB2+VkMKTmad8uqk3A2Io1VrVhJ+379aHdMbywnh27nfoGKF19qVCanc+f9E7/0++4VlD/zh/3H5hxdQG6X6L/dziNPZs/6Zt8Y3uY4WYGXVAja0v0KMBaY7u47zawX8KPkhZU4ry2r5NQRXXlyzsj9Q8YazJ0xnPGTSgG4d/Zabpw8mPy8LBaXVrK4tBKAz44qZPLEYjp3yuWem09k7cbdTLnlX8x7bjM3TBrMY7NGALDgL+Wsf2dP+CfYxnz6sXspPHMkeUVdGLPxZdbeNpNNc59OdVhtS30966bdxQm//Hl0yNgzf6B6/QaOvfoqqlauovKll+l88gj6T74Wd2dX6XLW3XFn9NhIhA3Tf8aJD/0Cw6ha9RblT89L7fkkWLoPGbPoG4QDFIz25xa7+1wz6wZ0dPeNLR2Xiu6FI82PF05IdQgZr6CkQ6pDOCJ8dsUbh50xV6/fFDjnlAzsG3qGDtTSNbNbgBFACTAXyAV+DZyevNBERFov3Vu6QbsX/gM4CVgO4O7vNwwhExFJJ5mSdGvd3c3MAczsqCTGJCJyyCKetvf4geAjEH4XG73Q2cy+C/wFeCB5YYmIHJqMGKfr7tPN7BzgA6L9uje7+/8kNTIRkUOQEd0Lse6ERe7+P2ZWApSYWa6770tueCIireOe3kk3aPfCK0C+mR0DLAS+ATySrKBERA5VBAu8pELQpGvuXg1cAsx290uB45MXlojIoYl4VuAlFQInXTM7Ffg68FxsW3pPzy4iR6SMuJEGTAJ+DDzj7ivNbADwYvLCEhE5NOnepxt09MIrRPt1G9Y3AD9IVlAiIocq3UcvBJ3EvJuZ3WNmC8xsUcOS7OBERFrL3QIvLTGzsWa22szWmdnUZsp9yczczEa0VGfQPt3fAG8D/YGfAO8ASwMeKyISmkgrluaYWTYwCzgXGAJ8zcyGHKRcAdEu2NeDxBc06Ra6+0PAPnd/2d2vAMYEPFZEJDQJHL0wEljn7hvcvRZ4ArjoIOVuB+4CAr3BIGjSbXgI4t9mdr6ZnQR0DXisiEhoWtO9EP9qsdgSP0/qMcCmuPWy2Lb9Yu+K7OvuzxFQ0NELd5hZJ2AKMBM4Gpgc9EtERMLSmhtp8a8Way0zywJ+Bny7NccFbeleSvQBiRXufhZwDtHpHkVE0krEgy8t2Az0jVvvE9vWoAA4AXjJzN4BRgHzW7qZFrSlO9TddzasuHtlrItBRCStJHDI2FKg2Mz6E02244DL9n+P+y6gqGHdzF4Crnf3Zc1VGrSlm2VmXeIq70rwhC0iEppEDRlz9zrgGuAF4C3gd7GHw24zs0N+b33QxHkv8JqZPRVbvxT46aF+qYhIstQn8Ik0d18ALDhg281NlB0dpM6gT6Q9ambL+GiY2CXuvirIsSIiYcqIx4ABYklWiVZE0lrAF5ynjPplRSSjpPvcC0q6IpJRAgwFSyklXRHJKJGIWroiIqFJ1Wt4glLSFZGMohtpIiIhypghYyIibYFupImIhEjdCyIiIUrkY8DJoKSbAQpKOqQ6hIxXtbo61SFIQGrpioiESElXRCREEXUviIiERy1dEZEQ1bf0bvUUU9IVkYyihyNEREKk7gURkRDpiTQRkRCppSsiEiIlXRGREGn0gohIiCJKuiIi4VH3gohIiJR0RURCpCFjIiIh8lY1dcN/ek1JV0QySn19qiNonpKuiGQU9emKiIRIfboiIiFSS1dEJETeqqaubqSJiBwWPQYsIhKiSJp36malOgARkURyD760xMzGmtlqM1tnZlMPsv+HZrbKzN40s7+a2bEt1amkKyIZJVFJ18yygVnAucAQ4GtmNuSAYm8AI9x9KPA0cHdL8SnpikhGibgHXlowEljn7hvcvRZ4ArgovoC7v+ju1bHVxUCflipV0hWRjOKR4IuZTTCzZXHLhLiqjgE2xa2XxbY15TvA8y3FpxtpIpJR6uuD30hz9znAnMP9TjO7HBgBnNlSWSVdEckorZvwplmbgb5x631i2xoxs7OBG4Ez3b2mpUqVdEUkoyRwxNhSoNjM+hNNtuOAy+ILmNlJwC+Bse6+NUilSroiklFa90RaM/W415nZNcALQDbwsLuvNLPbgGXuPh+4B+gIPGVmAO+5+4XN1aukKyIZJZFzL7j7AmDBAdtujvt8dmvrPCKS7qQJAzl1eCF7a+qZNmM1a9bv/liZkoEduWFyCfl52bxWWsGMOesB+P74AZw+spB9+yK8X76XaTPeZveeeo4uyOGOqcczuLiA5/9azn2/XBf2aaWtLqefxsCpP8Kysyj//bNsemhuo/35vXox6PZbyO3ahbpdH/D21Bup3RL9ZZbfsyeDbruZ/J49cIcVV11Dzfv/TsVptFlDH5hG9/NGU7u1gldOuiDV4YROT6Sl2KjhXenbuwPjJi7hnllruP6q4oOWm/L9Yu6+fw3jJi6hb+8OjBreFYCl/9jBN69eyrd/UMqmzdV848v9AKitjfDgbzYy6+H1oZ1Lm5CVxSdumsqKq65h2YVfott5Y+kwYECjIgOuv46t859j+SVf5b3Zc+g/+dr9+0ruvJ1Nc3/Fsgu/xBvjLmdf5Y6wz6DNK/vVPJZ88cpUh5EykXoPvKRCxifdM0YVsnBROQArV1fR8agcCrvkNSpT2CWPozrksHJ1FQALF5VzxqhCAJa+sWP/BBorV39At6J8APbWRHhz1QfU7kvz2TVCVnDiCXz43ib2lm3G6+rY9vwLFI4Z3ahMh4ED2LlkCQA7lyyl8Kzo/g4DBmDZ2ex87XUAIh9+SGTv3hCjzwyVf1vGvspdqQ4jZRL4cERSZHzSLSrMZ+v2j0ZxbK2ooagw74AyeWyLL7O9lqLC/I/Vdf45vVhcWpm8YDNAfvfu1JRv2b9es2ULed27NSqzZ/UaCs8eA0Dh2WPI6diRnE6daH9cP+qqqhjyX9MZ9tTj9J8yGbIy/p+oJJi7B15SIdC/aDM73cyOin2+3Mx+FmRih0zyza/0o77e+fNLgUaFSDM2TL+PziOGM+ypx+k8Yjg15VvwSD2WnUOnYSexYfp9LB93Oe369KHnxc3eCBb5mEjEAy+pEPRG2mzgU2b2KWAK8CDwKE08fRF7lG4CwMATp9Dz2HA78y85rzcXfKEXAG+traJ70Uet1u6F+WyvqG1UfntF7f5uA4DuRXlsr/io5Xvu53pw2smFTLrpn0mOvO2r2bqV/J499q/n9+hB7dZtjcrUbtvGqsnXA5DVvj1FZ3+O+qrd1GzZwu6317C3LDr+vGLRixw99MTwgpeMkO5vjgj6263Oo23xi4D73X0WUNBUYXef4+4j3H1E2AkXYN6C9xk/qZTxk0p5dfF2xo7pCcDxJQXsrq6jYkfjpFuxo5Y91XUcXxI9pbFjevLq4goAThnWhcsu6cvU21dQU6P+25ZUrVhJ+379aHdMbywnh27nfoGKF19qVCanc2eIjmmk33evoPyZP+w/NufoAnK7dAGg88iT2bN+Q6jxS9tXXx8JvKRC0JZulZn9GLgc+KyZZQG5yQsrcV5bVsmpI7ry5JyR+4eMNZg7YzjjJ5UCcO/stdw4eTD5eVksLq3c33d73cRicnON+24fCkRvpk3/+VoAnnrwFI7qkE1OThZnjCrihze/yTubqjmi1dezbtpdnPDLn0eHjD3zB6rXb+DYq6+iauUqKl96mc4nj6D/5Gtxd3aVLmfdHXdGj41E2DD9Z5z40C8wjKpVb1H+9LzUnk8b9OnH7qXwzJHkFXVhzMaXWXvbTDbNfTrVYYUmUQ9HJIsF6Uw2s55EH39b6u6vmlk/YLS7P9rSsZ+54OX0vgIZYNrGyakOIeNVrT7C/5iG5Px9qw/7pWVXT98ZOOfMur5z6C9JC9TSdfdy4Gdx6+8R7dMVEUkrad7QDTx64RIzW2tmu8zsAzOrMrMPkh2ciEhrecQDL6kQtE/3buACd38rmcGIiByuVI2/DSpo0t2ihCsibUGqRiUE1WzSNbNLYh+XmdmTwLPA/gGs7q5byyKSVtJ99EJLLd34QbbVwOfj1h1Q0hWRtNKmk667j4foY8Du/vf4fWZ2ejIDExE5FKmayCaooE+kzQy4TUQkpdr06AUzOxU4DehmZj+M23U00ddXiIiklbY+eiGP6Pt/cmg818IHwJeTFZSIyKGqr2vDoxfc/WXgZTN7xN3fDSkmEZFD1tZbug2qzewe4HigXcNGdx+TlKhERA6RR9K7pRv0RtpvgLeB/sBPgHeIvhNeRCStpPsk5kGTbqG7PwTsc/eX3f0KQK1cEUk76f66nqDdC/ti//23mZ0PvA90TU5IIiKHLtKWb6TFucPMOhF9Vc9MokPGrktaVCIihyjiGZB03f1PsY+7gLOSF46IyOFJ98eAg86nO8jM/mpmK2LrQ83spuSGJiLSeun+RFrQG2kPAD8m1rfr7m8C45IVlIjIocqUG2kd3H2JWaPXCdUlIR4RkcMSSfNxukGT7nYzG0h0OkfM7MvAv5MWlYjIIYrU16c6hGYFTbpXA3OAwWa2GdgIfD1pUYmIHKJ0v5HW0ixj8TOLLQBeJNoPvAf4EnFvCBYRSQdtOuny0cxiJcDJwB8AA74BLEliXCIih6RNj9N1958AmNkrwDB3r4qt3wo8l/ToRERaKZEtXTMbC8wgOn/4g+7+nwfszwceBYYDFcBX3f2d5uoMOmSsB1Abt14b2yYiklY8Egm8NMfMsoFZwLnAEOBrZjbkgGLfAXa4+yeA+4C7Woov6I20R4ElZvZMbP1i4JGAx4qIhCaBoxdGAuvcfQOAmT0BXASsiitzEXBr7PPTwP1mZt7MIOCgjwH/1MyeB86IbRrv7m+0Ln4RkeRrzZSNZjYBmBC3aY67z4l9PgbYFLevDDjlgCr2l3H3OjPbBRQC25v6zqAtXdx9ObA8aHkRkVRozSTmsQQ7p8WCCRQ46YqItAUJvJG2Gegbt94ntu1gZcrMLAfoRPSGWpOC3kgTEWkT3COBlxYsBYrNrL+Z5RGdb2b+AWXmA9+Kff4ysKi5/lxQS1dEMkykLjE30mJ9tNcALxAdMvawu680s9uAZe4+H3gIeMzM1gGVBJgIzNL9zZmpYGYT4jrTJQl0jZNP1zg9qXvh4Ca0XEQOk65x8ukapyElXRGRECnpioiESEn34NQPlny6xsmna5yGdCNNRCREaumKiIRISVdEJERHZNI1sx+Y2VtmtsPMpqY6HpEgzOxWM7v+EI4bbWanxa0/EnvPoaTAkfpE2veBs929LNWBiIRgNLAb+N8UxyEcgS1dM/sFMAB43syuM7P7Y9sfMbNfmNkyM1tjZl+MbT/ezJaY2T/M7E0zK05l/OnIzL4Zuzb/NLPHzOwCM3vdzN4ws7+YWY9YuTNj1/EfsX0Fse0/MrOlsToa3lZylJk9F6tzhZl9NZXnmCpmdmPs3+PfiL42CzMbaGYLzazUzF41s8Gx7R+77mZ2HPA94LrYdW+YnvWzZva/ZrahodVrZr3M7JVYuRVxZSWR3P2IW4B3gCLg28D9sW2PAAuJ/iEqJjp3ZjtgJvD1WJk8oH2q40+nBTgeWAMUxda7Al34aGTMlcC9sc9/BE6Pfe5I9JfW54kObbLYtf8T8FmiLz59IO57OqX6XFNwbYcD/wI6AEcD64Drgb8CxbEypxCdZIVmrvutwPVx9T4CPBW73kOITtQNMAW4MfY5GyhI9TXIxOVI7V5oyu88OvXQWjPbAAwGXgNuNLM+wDx3X5vSCNPPGOApd98O4O6VZnYi8KSZ9SL6h2pjrOzfgZ+Z2W+IXssyM/s80cTbMCl+R6J/9F4F7jWzu4A/ufur4Z1S2jgDeMbdqwHMbD7RhsBpwNBlIR8AAAHmSURBVFNm1lAuP/bfPhz8uh/Ms7F/66safokQnVXrYTPLje3/R0LPRoAjsHuhBQcOWnZ3/y1wIfAhsMDMxoQfVpszk+gviBOBiUQTBR59qd+VQHvg77GfxQbc6e6fji2fcPeH3H0NMIxoS+8OM7s5JWeSfrKAnXHX69Pu/snYvoNe9ybUxH02AHd/heivjM3AI2b2zcSHL0q6jV1qZllmNpBov+9qMxsAbHD3/yb6CvqhKY0w/Swiet0KAcysK9GJnBsme26YaxQzG+ju/3L3u4i2qgYTnTbvCjPrGCtzjJl1N7PeQLW7/xq4h2gCPtK8AlxsZu1j/d8XANXARjO7FMCiPhUrf9DrDlQBBS19mZkdC2xx9weABzkyr3nSqXuhsfeAJUT7z77n7nvN7CvAN8xsH1AOTEtlgOnGo/OL/hR42czqiXYT3Er05+8Ookm5f6z4ZDM7C4gAK4Hn3b3GzD4JvBb7ubwbuBz4BHCPmUWAfcBVIZ5WWnD35Wb2JPBPYCvRP1QAXwdmm9lNQC7wRKzMrRz8uv8ReNrMLgKubeYrRwM/iv1b3w2opZsEegw4xsweIdp3+HSqYxGRzKXuBRGREKmlKyISIrV0RURCpKQrIhIiJV0RkRAp6YqIhEhJV0QkRP8fdUEMWejv9k0AAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8GdomSw38mNU",
        "colab_type": "code",
        "outputId": "3b4f80f7-a9b8-48a2-bc39-fd3e5adc1828",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 584
        }
      },
      "source": [
        "sns.pairplot(covid19)"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.PairGrid at 0x7fce3b450358>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 540x540 with 12 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "A4UeKoae9I5T",
        "colab_type": "code",
        "outputId": "ced88ff8-7e41-4559-bfdf-fd50b0ccf4ac",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 588
        }
      },
      "source": [
        "sns.PairGrid(covid19)"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.PairGrid at 0x7fce3b2a7278>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 540x540 with 9 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cNi1cW3C9wVB",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import matplotlib.pyplot as plt\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "v6oGTpq7--CY",
        "colab_type": "code",
        "outputId": "be3fd293-36fc-4b54-d6ef-1aa56798b424",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 584
        }
      },
      "source": [
        "zeph_graph = sns.PairGrid(covid19)\n",
        "zeph_graph.map_diag(plt.hist)\n",
        "zeph_graph.map_upper(plt.scatter)\n",
        "zeph_graph.map_lower(sns.kdeplot) #kdeplot --> Kernel Density Estimation"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.PairGrid at 0x7fce18a30668>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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9u3e86Phf/empbYhKasy/repEbUt4IuJI4FvABzNzZ/2x0pqTrY4hM6/LzKWZuXTevHmtvp00ZvXPas/Mo190/IM33cXaTX1tiEx6Mf+2qhO1JeGJiGnUkp2vZ+a3S/HjpauK8nNbKe8D6t9yuLCUDVe+sEG5VGkfvOkuFq++lcWrb+Xja+9pdzjSYVu8+lZe+bF17Q5DFdWOWVoBfBn4ZWZ+tu7QLcDATKuVwHfryi8us7WWATtK19d64JyIOKYMVj4HWF+O7YyIZeVeF9ddS5oUvnb7b0x61JX29qdJj1qiHS08ZwJ/BpwdEXeV7XzgauDNEXE/8K/LZ4B1wAPAFuBLwPsAymDlTwN3lu1TAwOYS53/p5zzaxywrEnom3c8MnIlqQPt7W/5iAZNQu2YpfVPwFDr4rypQf0ELhviWmuANQ3KNwKvHkeYUtfrz2Tx6lvbHcaLTAl45xmLuHLFKe0ORR1sLM/urOk9XPUnp7DitIbzVDTJudKypAl1KO1yU2vs2t/Ph//mXxzAr4ZMeCS1hV1uaoX+Q8k16ze3Owx1IBMeSW3Rn47TUGs8+syedoegDmTCI6ktenzFnVrk+Dm97Q5BHciER1JbXHTGCSNXkg5Tz5TgI+ee1O4w1IEmfJaWpMnNWVpqFWdpaTgmPFIF+NJFVYHPsVrJLi1JklR5JjySJKnyTHgkSVLlmfBIFdCJr5CQpE5iwiNVhEmPut0ZV21odwiqMBMeSVJHePzZ/e0OQRXmtHSpQoZr5Tnz5XP5+qVvmMBopMO3ePWtTk9XS9jCI00SP/n1dt71pf/W7jCkEdk9q1Yw4ZEmkZ/8enu7Q5CktjDhkSRJldeWhCci1kTEtoj4RV3Z3IjYEBH3l5/HlPKIiM9HxJaIuDsiXld3zspS//6IWFlX/vqIuKec8/kIX8ssSdJk1q4Wnq8AyweVrQZuy8wlwG3lM8B5wJKyrQKuhVqCBFwBnAGcDlwxkCSVOpfWnTf4XtKkdObL57Y7BElqi7YkPJn5Y2DwYIILgOvL/vXAirryG7LmdmBORBwHnAtsyMztmfk0sAFYXo7NzszbMzOBG+quJU1aztJSt3CWllqhk6alz8/Mx8r+b4H5ZX8B8Ehdva2lbLjyrQ3KpUnD5EaSXqiTEp7fycyMiGz1fSJiFbVuMhYtWtTq20ljVv+s9syeN2L9n/x6+wum9s6e0cPdn7RnVxNjvH9b65/dI3qCX111ftNi0+TVSbO0Hi/dUZSf20p5H3BCXb2FpWy48oUNyl8kM6/LzKWZuXTevJH/EZHapf5Z7Zl59GGfv3NfP6+54u9bEJn0Ys3827q3P3nlx9Y1KTJNZp2U8NwCDMy0Wgl8t6784jJbaxmwo3R9rQfOiYhjymDlc4D15djOiFhWZmddXHctadLaua+/3SFIY7K3v+UN/poE2tKlFRHfBM4Cjo2IrdRmW10N3BwRlwAPAxeW6uuA84EtwG7gPQCZuT0iPg3cWep9KjMHBkK/j9pMsF7g+2WTJEmTVFsSnsy8aIhDb2pQN4HLhrjOGmBNg/KNwKvHE6MkSaqOTurSktRCs2f0tDsEaUyO6HHtWI2fCY80CThLS93KWVpqlo6cli5pbExs1O1cdFCtYsJTIfVrV4yWf1yqZee+/jE9B6MxJeCdZyziyhWntOT6Eozu79i7l/kc6vDZpSVpVA4lfO323/Dxtfe0OxRNcj6HGgtbeFQZtnBNjG/e8Yj/da228znU4bKFR9Jh6U8XgVP7+RzqcNnC06FaNQ5DGq+ecIqw2s/nUIfLFh5Jh+WiM04YuZLUYj6HOly28KjlHFtTDc7SUqdwlpbGwoRHk1pVk7GeCH79GRdrU3fqhv+PqfuY8ExyVf0Hf7JzQKckvZBjeKQKckCnJL2QCY9UQQ7oVLc68+Vz2x2CKsourcNkF5A6nQM61a3OfPlcvn7pG9odhirKhEeHzTWCOosJtarCZEetZMKjjmRSNXpnXLWBOz725naHIUkdzTE8Upd7/Nn9nHHVhnaHIUkdrbIJT0Qsj4jNEbElIla3Ox6plR5/dn+7Q5CkjlbJhCcieoAvAucBJwMXRcTJ7Y1KkiS1SyUTHuB0YEtmPpCZ+4EbgQvaHJMkSWqTqiY8C4BH6j5vLWVSJc0/anq7Q5CkjjapZ2lFxCpgFcCiRYtadh9nHGm86p/VntnzXnBs/lHTnaWljjLU39aHrn7LkH8PXV5BrVbVhKcPqF9qdmEpe4HMvA64DmDp0qW+fEgda/CzutF/HNTBhvvbamKjdqlql9adwJKIODEipgPvAG5pc0ySJKlNKtnCk5kHI+L9wHqgB1iTmfe2OSxJktQmkWlPDkBEPAE8PEyVY4EnJyicZuvW2Ls1bqjF/qvMXN7sC0fEs8DmZl+3CTr1fy/jGp0nW/S8DvW3tdO+f7v5+3jeSL+LMT2rJjyjFBEbM3Npu+MYi26NvVvjhtbG3qm/F+M6PJ0a10SZ7N9/MH8fz2vV76KqY3gkSZJ+x4RHkiRVngnP6F3X7gDGoVtj79a4obWxd+rvxbgOT6fGNVEm+/cfzN/H81ryu3AMjyRJqjxbeCRJUuWZ8EiSpMoz4ZEkSZVnwiNJkirPhKdYvnx5Am5uzdxawmfVrUVbS/i8urVgGxMTnuLJJ13RW93BZ1XdxOdVncKER5IkVV7LEp6IOCEifhgR90XEvRHxgVI+NyI2RMT95ecxpTwi4vMRsSUi7o6I19Vda2Wpf39ErKwrf31E3FPO+XxExHD3kCRJk1MrW3gOAh/OzJOBZcBlEXEysBq4LTOXALeVzwDnAUvKtgq4FmrJC3AFcAZwOnBFXQJzLXBp3XkDb08d6h6SJGkSalnCk5mPZebPy/6zwC+BBcAFwPWl2vXAirJ/AXBD1twOzImI44BzgQ2ZuT0znwY2AMvLsdmZeXvWlou+YdC1Gt1DkiR1qLWb+jjz6h9w4upbOfPqH7B2U1/Trj21aVcaRkQsBk4D7gDmZ+Zj5dBvgfllfwHwSN1pW0vZcOVbG5QzzD0Gx7WKWmsSixYtOsxvJU0cn1V1E59XjcXH197D12//ze+mYfU9s4fLv30PACtOWzD0iaPU8kHLEXEk8C3gg5m5s/5YaZkZ8xSz0RjuHpl5XWYuzcyl8+bNa2UY0rj4rKqb+LzqcK3d1MfX6pKdAXsO9HPN+s1NuUdLW3giYhq1ZOfrmfntUvx4RByXmY+VbqltpbwPOKHu9IWlrA84a1D5j0r5wgb1h7uH1PWe/NefZPHqW8d07kNXv6XJ0UjS+H3sO/cMeezRZ/Y05R6tnKUVwJeBX2bmZ+sO3QIMzLRaCXy3rvziMltrGbCjdEutB86JiGPKYOVzgPXl2M6IWFbudfGgazW6hyRJ6iBrN/Wxa3//kMePn9PblPu0soXnTODPgHsi4q5S9h+Aq4GbI+IS4GHgwnJsHXA+sAXYDbwHIDO3R8SngTtLvU9l5vay/z7gK0Av8P2yMcw9JElSBxmudQfgI+ee1JT7tCzhycx/AmKIw29qUD+By4a41hpgTYPyjcCrG5Q/1egekiSpM6zd1Mfl376bPQcODVmnd9qUpgxYhgmapSVJkjTg42vv4Wu3/2bEep9562uadk9fLSFJkibMaJOdZrbugAmPJEmaIAPTz0ejma07YMIjSZImyCf/7t5R1Xv3skVNbd0BEx5JkjRBnt59YMQ67162iCtXnNL0eztoWZIktdTaTX184pbhW3dmTe/hqj85pektOwNMeCRJUssMfkdWI73TpnDvp5a3NA4THkmS1BLtmH4+FMfwSJKkplu7qY+vjyLZmdM7rWXdWPVs4ZEkSU2zdlMf16zfTN8oXvrZO62HT/zxqyYgKhMeSZLUJLXXRdzDngNDvwx0wDEzp3HFH71qQlp3wIRHkiQ1yTXrN48q2WnV1PPhmPBIkqSmGKkbK4B3tSHZARMeSZLUBGs39Q17fMGcXj5y7kkT1oU1mAmPJEkat5FeG/GT1WdPUCSNOS1dkiSNy9pNfcO+NmLBnN4JjKYxEx5JkjQu16zfPOSxAD5y7kkTF8wQ7NKSJEljMpo1d97Vgjefj4UJjyRJGrX6JCdg2Hdkzemd1pYZWY2Y8EiSpFEZvLDg8C8EnbhVlEfDhEeSJI1o7aY+Pnzzv9Cfw6U5Ne2egt6ICY8kSRrWQMvOaJOddk9Bb8RZWpIkaVijfWVE77SejpiR1YgtPJIkaUhrN/UNOwtrYOByJ3Zj1TPhkSRJDQ10ZQ2lJ4K/vPC1HZvk1LNLS5IkNTRcV1bvtJ6uSXbAFh5JkjTIaBYU/MxbT+maZAdMeCRJUp3Ba+00smBOb1clO2CXliRJqjPSjKxOnok1HFt4JEnS7zw6TDdWp8/EGk7LWngiYk1EbIuIX9SVfSIi+iLirrKdX3fs8ojYEhGbI+LcuvLlpWxLRKyuKz8xIu4o5TdFxPRSPqN83lKOL27Vd5QkqUrWbupjSkTDYwMLCnZjsgOt7dL6CrC8QfnnMvPUsq0DiIiTgXcAryrn/HVE9ERED/BF4DzgZOCiUhfgL8q1XgE8DVxSyi8Bni7lnyv1JEnSMIZbTblbu7HqtSzhycwfA9tHWf0C4MbM3JeZDwJbgNPLtiUzH8jM/cCNwAUREcDZwN+W868HVtRd6/qy/7fAm0p9SZI0hKHG7vREdN2MrEbaMWj5/RFxd+nyOqaULQAeqauztZQNVf4S4JnMPDio/AXXKsd3lPovEhGrImJjRGx84oknxv/NpBapf1bbHYs0Ev+2dpe1m/o48+ofDDkF/VBm1yc7MPEJz7XAy4FTgceAv5zg+79AZl6XmUszc+m8efPaGYo0rPpntd2xSCPxb2v3GOjGGm69nePn9E5gRK0zobO0MvPxgf2I+BLwvfKxDzihrurCUsYQ5U8BcyJiamnFqa8/cK2tETEVOLrUlyRJjG5hQajG2J0BE9rCExHH1X38E2BgBtctwDvKDKsTgSXAT4E7gSVlRtZ0agObb8nMBH4IvK2cvxL4bt21Vpb9twE/KPUlSZr0RtOqA7VZWVUYuzOgZS08EfFN4Czg2IjYClwBnBURp1J7sepDwHsBMvPeiLgZuA84CFyWmf3lOu8H1gM9wJrMvLfc4qPAjRFxJbAJ+HIp/zLw1YjYQm3Q9Dta9R0lSeoWo23VgeenoFdJyxKezLyoQfGXG5QN1L8KuKpB+TpgXYPyB6jN4hpcvhd4+2EFK0lShY3mdREDqtSNVc+VliVJqqjDadWB7l5JeSQmPJIkVdDhtupUabxOIyY8kiRV0EgvAR1Q5VadeiY8kiR1qYEuq0ef2cPxgxKX4V4CCpOjVaeeCY8kSV1ocJdV3zN7uPzb9wCw4rQFHD+nd8ixO5OlVadeO14tIUmSxqlRl9WeA/1cs34zAB859yR6p/W84HjvtB7+6k9P7eq3no+VLTySJHWhoVpvBrqyBhKaobq8JhsTHkmSuszaTX0EtVV8B6t/99WK0xZM2gRnMLu0JEnqMtes39ww2Qmo5KKBzWDCI0lSlxmqOyvBFp0hmPBIktRFBrqzGllQ152lFzLhkSSpi9idNTYmPJIkdZGhFhS0O2t4ztKSJKnD1a+oPCWC/nxxG4/dWcMz4ZEkqYMNXlG5UbLTO63H7qwRmPBIktTBhnoJaE8EhzIn/YKCo2XCI0lSBxtqzM6hTB68+i0THE33ctCyJEkd7PghxuYMVa7GTHgkSepgQ70E1DE7h2dUCU9EvD0ijir7H4+Ib0fE61obmiRJWnHaAj7z1lNYMKeXoDYb6zNvPcUxO4dptGN4/o/M/JuI+APgXwPXANcCZ7QsMkmSJqH6Kej1A5JNcMZntF1aA8PD3wJcl5m3AtNbE5IkSZPTwBT0vmf2kNTemXX5t+9h7aa+dofW9Uab8PRFxH8F/hRYFxEzDuNcSZI0Co2moO850M816ze3KaLqGG2X1oXAcuA/ZeYzEXEc8JHWhSVJUvUN7r4a6i3oQ01N1+iNqpUmM3cD24A/KEUHgftbFZQkSVXXqPtqqLegOwV9/EY7S+sK4KPA5aVoGvC1VgUlSVLVNeq+SnhR0uMU9OYYbZfWnwCnAT8HyMxHB6apS5Kk0anvwnrxG7FqkuFHNwQAACAASURBVNrU88GztDQ+o0149mdmRkQCRMSsFsYkSVLlDH4J6FAWzOnlJ6vPnqCoJo/RzrS6uczSmhMRlwL/L/Cl1oUlSVK1DPUS0Hp2X7XOqFp4MvM/RcSbgZ3AScD/mZkbWhqZJEkVMtxMqwC7r1psVAlP6cL6QWZuiIiTgJMiYlpmHhjmnDXAHwLbMvPVpWwucBOwGHgIuDAzn46IAP4zcD6wG/jzzPx5OWcl8PFy2Ssz8/pS/nrgK0AvsA74QOl2a3iPUf02JElqksFTzufMnMbTu1/8z6ZdWBNjtF1aPwZmRMQC4O+BP6OWbAznK9TW7qm3GrgtM5cAt5XPAOcBS8q2itprKwYSpCuovcLidOCKiDimnHMtcGndectHuIckSROi0ZTz5/YeZFrPC+dg2YU1cUab8ERZi+etwLWZ+XbgVcOdkJk/BrYPKr4AuL7sXw+sqCu/IWtupzZW6DjgXGBDZm4vrTQbgOXl2OzMvD0zE7hh0LUa3UOSpAnRaLzOgUPJrOlTfQlom4x2llZExBuAdwGXlLKeYeoPZX5mPlb2fwvML/sLgEfq6m0tZcOVb21QPtw9XiQiVlFrUWLRokWH+12kCVP/rL7so99rczTS8PzbOvR4nR17DnDXFedMcDSC0bfwfIDaooPfycx7I+L3gB+O58alZWaoZQiaYqR7ZOZ1mbk0M5fOmzevlaFI41L/rLY7Fmkkk/Fv69pNfZx59Q84cfWtnHn1D5gzc1rDeq6Y3D6jnaX1Y2rjeAY+PwD82zHc7/GIOC4zHyvdUttKeR9wQl29haWsDzhrUPmPSvnCBvWHu4ckSU03eH2dvmf2MG1KMK0nOND//H9zO16nvUb7aol5EXFNRKyLiB8MbGO43y3AyrK/EvhuXfnFUbMM2FG6pdYD50TEMWWw8jnA+nJsZ0QsKzO8Lh50rUb3kCSp6Ryv0x1GO4bn69Smev8h8L9SSySeGO6EiPgmtdaZYyNiK7XZVldTW8TwEuBham9hh9q08vOBLdSmpb8HIDO3R8SngTtLvU9l5sBA6Pfx/LT075eNYe4hSVLTOV6nO4w24XlJZn45Ij6Qmf8I/GNE3DncCZl50RCH3tSgbgKXDXGdNcCaBuUbgVc3KH+q0T0kSWqF4+f00tcg6XG8TmcZbcIzsFLSYxHxFuBRYG5rQpIkqXMNXlDwja+cx7d+1veCbi3H63Se0SY8V0bE0cCHgS8As4EPtiwqSZI6UKMByt/6WR//5vUL+OGvnvAN5x1stAnP24F/ysxfAG8sKyD/J+DvWhaZJEkdptEA5T0H+vnhr57w9RAdbrTr8LwmM58Z+FAGDp/WmpAkSepMQw1QHu7FoOoMo23hmRIRxwy8hLO08Iz2XEmSutJoXwDqAOXON9qk5S+B/xYRf1M+vx24qjUhSZLUfi4oWC2jXWn5hojYCAx0UL41M+9rXViSJLXXUAsKzumdxqwZUx2g3GVG3S1VEhyTHEnSpOCCgtXiOBxJ0qQ3eKzOR849yQUFK2a0s7QkSaqkgbE6fc/sIamN1bn82/fwxlfOo3dazwvqOl6ne5nwSJImteHW1vnMW0/xBaAVYZeWJGlSG25tnRWnLTDBqQgTHknSpOLaOpOTCY8kadJwbZ3JyzE8kqRJY6i1dWZNn+pYnYqzhUeSNGm4ts7kZcIjSaqURmvqDLTWuLbO5GWXliSpMoZaU2ftpj4APnLuSa6tM0mZ8EiSKmOoNXWuWb8ZgBWnLXBtnUnKLi1JUtcb6MZq1F0FLxy749o6k5MJjySpqw2eat6IY3RkwiNJ6kprN/XxiVvu5Zk9L140sJ5jdAQmPJKkLrR2Ux8fuvkuDuXw9RYMmqWlycuEp3jwwQd55zvf2e4wVCHf+MY32h2CVFmf/Lt7R5Xs/GT12RMTkDqes7QkSV2n0buv6tmNpcFMeCRJXeXja+8Z9nhPhFPN9SJ2aRV79uzhvvvua3cYkqQRfP323wx7/C8vfK3Jjl7EhKfo7e3l5JNPZt++fezbt6/d4VTeEUccwfTp09sdhqQus3ZTH8MN3Xn3skUmO2rIhKc44YQT+OlPf0rmCKPg1DTz5s1jw4YNHHXUUe0ORVIXWLupj393013D1rlyxSkTFI26jQlP8fDDDzN37tx2hzGpPPPMM1xyySVMnVrNx9BZWlLzrN3Ux4duumvY1p2Z0xyWqqG15V+aiHgIeBboBw5m5tKImAvcBCwGHgIuzMynIyKA/wycD+wG/jwzf16usxL4eLnslZl5fSl/PfAVoBdYB3wgR2i6OXjwIMcffzz9/f0cPHiwid9WjUydOpWenh4ee+yxcV1n37597N69m0OHDo3rOhFBT0/PyBUltcU16zcz0v/L/6+3vmZCYlF3aud/Wr8xM5+s+7wauC0zr46I1eXzR4HzgCVlOwO4FjijJEhXAEuBBH4WEbdk5tOlzqXAHdQSnuXA94cLZv/+/Tz66KPN/H7qQkceeaSJj9SBhnpH1gDH7mgkndT+dwFwfdm/HlhRV35D1twOzImI44BzgQ2Zub0kORuA5eXY7My8vbTq3FB3LWlYmcmhQ4easklqjrWb+kas49gdjaRdLTwJ/ENEJPBfM/M6YH5mDvRv/BaYX/YXAI/Unbu1lA1XvrVB+YtExCpgFcCMGTOYOXPmeL6TulhEMGVKJ+X/L1T/rL7so99rczTS8Oqf10WLFo3rWgMvBh1Or2N3NArtSnj+IDP7IuKlwIaI+FX9wczMkgy1VEm0rgOYOXNm2pWhTlX/rC5efatTCdXR6p/XpUuXjut5vWb95mHfgg7wGcfuaBTakhZnZl/5uQ34DnA68HjpjqL83Faq9wEn1J2+sJQNV76wQbkkqUus3dTHmVf/YMSxO73Tpjh2R6My4QlPRMyKiKMG9oFzgF8AtwArS7WVwHfL/i3AxVGzDNhRur7WA+dExDERcUy5zvpybGdELCszvC6uu5YkqcMNdGONlOyArTsavXZ0ac0HvlPLRZgKfCMz/z4i7gRujohLgIeBC0v9ddSmpG+hNi39PQCZuT0iPg3cWep9KjO3l/338fy09O8zwgwteH6lZUlSe42mGwtgTu80W3c0ahOe8GTmA8BrG5Q/BbypQXkClw1xrTXAmgblG4FXH05cJ554ogvFSVIHeHQULTsAn/jjV7U4ElVJNZe4HYMHH3yQd77zne0OQxViAi2NzZyZ03h694ER633wprv44E13EcCDV7+l9YGpq5nwFLt27WLjxo3tDkOSJrW1m/p4bu/hrXafwImrbzXp0bBMeIopU6a4Do8ktdk16zdz4NDhz2R3rQaNxISnOPnkk23hkaQ2G+34HelwuTylJKkjrN3UZ0uNWsaER5LUdqN5hcRwoomxqJpMeCRJbffJv7t3VGvvDMUByxqJCY8kqa3Wbuob1TT0Ro7oCR4y2dEomPBIktrqmvWbx3Te7Bk9/Oqq85scjarKhEeS1FZjnZl19yeXNzkSVZkJjySpbcY6M+vdyxY1PRZVm+vwFA8//DDvfe97x3Tucccdx9lnn82cOXOaHJW62Wte41ucpeGs3dTHR/7mXw77vCUvncWVK05pQUSqMhOe4rnnnuOf//mfx3Tu3r17+epXv9rkiNTtfv3rX7c7BKmjffLv7j3sVZXPfPlcvn7pG1oUkarMhKeYOXMmp5wytv9i6O/v57nnnuPQoUNNjkqSqmksM7OWvHSWyY7GzISnOPHEE327tSRNkLHMzNrwobOaH4gmDRMeSdKE6xvDzKw3f/ZH3L9t1+8+L3npLJMgjZqztCRJE64nDv9lEPXJzsDnN3/2R02KSFVnwiNJmnD92ZzXhA5OgqShmPBIkqTKM+GRJE2oj68d+1vRpbEy4ZEkTaiv3f6bdoegSciER5I0YdZu6mvq9Za8dFZTr6fqMuGRJE2Yj32ned1Z84+a7rR0jZrr8EiSJsyu/f3jvsaUgM9eeCorTlvQhIg0WZjwSJK6xl/9qYmOxsaER5LU8R66+i3tDkFdzjE8kqSOdvhrMksvZsIjSepox8/pbXcIqgATHklSR/vIuSe1OwRVgAmPJGlCjHWFZQcpqxkqm/BExPKI2BwRWyJidbvjkaTJbiwrLL972aIWRKLJqJKztCKiB/gi8GZgK3BnRNySmfeN57qZyY4dO9m1exd79uxl77597Nq1i+ee28WOnTvY9sRTPPX0M+zYuZNnn9vN7j172Lf/AM/t3s2Op59h7949ZCbTp03l6NmzOWHhAmYfdSQRUzhw4AB79u3jmWd3sW/fAQ7219aqmD5tKkfOmsm/OnYuixYez+8tfhkLFy7gJXOPoaenh7379rF9+9Ps2LmTHTt3snv3Xvbu209/fz+HMslDhzh06BCQ9B86RH9/PwcPHKT/UD/9B/s52H+I/kP9tToJkEyZMoVp06YyY/p0ent7mTVzJkcdeSRHH300s2cfyewjj6K39wim9ExhSgRTenqYOqWHiOBQHmL37j1s7evjwYd+Q99jj7Jt25Nse/Ipntu1i337D3Do0CF6enqYPn06s2bO5MgjZzH7qFnMPOIIpk6dSibs3buXZ3Y+y9M7dvDcrt3lOx1iWs8UZvb2cuxL5vB7i1/GiS9bxKITFnL00Udz6NAhntr+NI/99nG2Pfkkjz72ONt37GTPnj0cONjPtJ4p9B4xg2Nmz+boo2czZ85s5s6Zw5w5c3jJ3GOYd+yxzJo1k54pPfRM7aFnyhSm9NR+9vRMZerUHqZMqex/I0gd6Vs/62Ppy+bayqNxq2TCA5wObMnMBwAi4kbgAmBMCc++/fu5+JL3ct8vf8XuPXsAyKkzIKYAAVOmwrRemNID03trZVE3ryAT+oH+qXDoIDz3HL99+jk2P/zoC2/UM612nUYyIQ/V9qcdUbvXjFnktFkwYxZMnwXTZ8L0WeT03lpMUIuFKXBwL7FvF+zZAXt3wO4dxL6dsH9PuW7W6k6dDlNnwPSZ5IyjYOoRtbJpR0BP3eOSwMF90L8f9u2Bg7uJ/btg327YvwsO7IFD/UQEMaWHQ5m186bPhJha+z1NnQJT95JTA3r218U7cAOgv4c4OBUO9sPBQ7D/OTi0A/6/B/jBP/+s9nuYOqP2/WfMInuPgZlz4IjZ5BHzYNrLYAa17cAeYtdueGon7HsM9j9Qi5ms/X4P7q991/owAA4eqH3XQwfhwF6m9O/lyBnTeMXLFvDWFX/MOy9827DPj6Sx23Ogn2vWbzbh0bhFDvxDVCER8TZgeWb+L+XznwFnZOb7B9VbBawqH08CNg9z2WOBJ1sQ7kTo1ti7NW6oxf6rzFzejIsNelZfDfyiGddtsk7938u4RufJFj2vv/vbOv1fveL1A3X6d++gZ+bRo77m/t9u+VkzYutgnfY8tNNIv4sxPauTOuE5zGtuzMylzYpxInVr7N0aN7Q29k79vRjX4enUuCbKZP/+g/n7eF6rfhdVHZDQB5xQ93lhKZMkSZNQVROeO4ElEXFiREwH3gHc0uaYJElSm1Ry0HJmHoyI9wPrgR5gTWbeO87LXjf+yNqmW2Pv1rihtbF36u/FuA5Pp8Y1USb79x/M38fzWvK7qOQYHkmSpHpV7dKSJEn6HRMeSZJUeROe8ETECRHxw4i4LyLujYgPlPK5EbEhIu4vP48p5RERny+viLg7Il5Xd62Vpf79EbGyrvz1EXFPOefzEfWrAEqSpMmmHS08B4EPZ+bJwDLgsog4GVgN3JaZS4DbymeA84AlZVsFXAu1BAm4AjiD2srKVwwkSaXOpXXnNWUxLUmS1J0mPOHJzMcy8+dl/1ngl8ACaq9+uL5Uux5YUfYvAG7ImtuBORFxHHAusCEzt2fm08AGYHk5Njszb8/aiOwb6q41pOXLlye19xm4uTVrawmfVbdmbZs3b87f//3fzy984QtJi/i8urVgG5O2juGJiMXAacAdwPzMfKwc+i0wv+wvAB6pO21rKRuufGuD8mE9+aQreqs7+KyqWZYsWcIf/uEfsm7dupbdw+dVnaJt6/BExJHAt4APZubO+mE2mZkRMeYs7jBi+N37XhYtWtTq20lj5rOqVpgyZQqf+cxn2L17d1Ov6/OqTtSWFp6ImEYt2fl6Zn67FD9euqMoP7eV8qFeEzFc+cIG5S+Smddl5tLMXDpv3rzxfSmphXxW1SpTp05l9uzZTb2mz6s6UTtmaQXwZeCXmfnZukO3ACvL/krgu3XlF5fZWsuAHaXraz1wTkQcUwYrnwOsL8d2RsSycq+L664lSZImoXZ0aZ0J/BlwT0TcVcr+A3A1cHNEXAI8DFxYjq0Dzge2ALuB9wBk5vaI+DS192YBfCozt5f99wFfAXqB75dNkiRNUhOe8GTmPwFDrYvzpgb1E7hsiGutAdY0KN8IvHocYUqSpApxpWVJklR5lXxbuiSpsy1efeuYznvo6rc0ORJNFrbwSJKkyjPhkSRJlWfCI0mSKs+ER5IkVZ4JjyRJqjwTHkmSVHkmPJIkqfJMeCRJUuWZ8EiSpMoz4ZEkSZVnwiNJkirPhEeSJFWeCY8kSao8Ex5JklR5JjySJKnyTHgkSVLlmfBIkqTKM+GRJEmVZ8IjSZIqz4RHkiRVngmPJEmqPBMeSZJUeSY8kiSp8kx4JElS5ZnwSJKkyjPhkSRJlWfCI0mSKs+ER5IkVZ4JjyRJqry2JDwRsSYitkXEL+rKPhERfRFxV9nOrzt2eURsiYjNEXFuXfnyUrYlIlbXlZ8YEXeU8psiYvrEfTtJktRp2tXC8xVgeYPyz2XmqWVbBxARJwPvAF5VzvnriOiJiB7gi8B5wMnARaUuwF+Ua70CeBq4pKXfRpIkdbS2JDyZ+WNg+yirXwDcmJn7MvNBYAtwetm2ZOYDmbkfuBG4ICICOBv423L+9cCKpn4BSZLUVTptDM/7I+Lu0uV1TClbADxSV2drKRuq/CXAM5l5cFC5JEmapDop4bkWeDlwKvAY8JetvmFErIqIjRGx8Yknnmj17aQx81lVN/F5VSfqmIQnMx/PzP7MPAR8iVqXFUAfcEJd1YWlbKjyp4A5ETF1UHmje16XmUszc+m8efOa92WkJvNZVTfxeVUn6piEJyKOq/v4J8DADK5bgHdExIyIOBFYAvwUuBNYUmZkTac2sPmWzEzgh8Dbyvkrge9OxHeQJEmdaerIVZovIr4JnAUcGxFbgSuAsyLiVCCBh4D3AmTmvRFxM3AfcBC4LDP7y3XeD6wHeoA1mXlvucVHgRsj4kpgE/DlCfpqkiSpA7Ul4cnMixoUD5mUZOZVwFUNytcB6xqUP8DzXWKSJGmS65guLUmSpFYx4ZEkSZVnwiNJkirPhEeSJFWeCY8kSao8Ex5JklR5JjySJKnyTHgkSVLlmfBIkqTKM+GRJEmVZ8IjSZIqz4RHkiRVngmPJEmqPBMeSZJUeSY8kiSp8kx4JElS5ZnwSJKkyjPhkSRJlWfCI0mSKm9cCU9EnBkRs8r+uyPisxHxsuaEJkmS1BzjbeG5FtgdEa8FPgz8Grhh3FFJkiQ10XgTnoOZmcAFwH/JzC8CR40/LEmSpOaZOs7zn42Iy4F3A/9jREwBpo0/LEmSpOYZbwvPnwL7gEsy87fAQuCacUclSZLURONq4SlJzmfrPv8Gx/BIkqQOM95ZWm+NiPsjYkdE7IyIZyNiZ7OCkyRJaobxjuH5j8AfZeYvmxGMJElSK4x3DM/jJjuSJKnTjamFJyLeWnY3RsRNwFpqg5cByMxvNyE2SZKkphhrl9Yf1e3vBs6p+5yACY8kSeoYY0p4MvM9UHu1RGb+pP5YRJzZjMAkSZKaZbxjeL4wyrIXiIg1EbEtIn5RVzY3IjaUWV8bIuKYUh4R8fmI2BIRd0fE6+rOWVnq3x8RK+vKXx8R95RzPh8RMc7vKUmSutiYEp6IeENEfBiYFxEfqts+AfSM4hJfAZYPKlsN3JaZS4DbymeA84AlZVtF7f1dRMRc4ArgDOB04IqBJKnUubTuvMH3kiRJk8hYW3imA0dS6xI7qm7bCbxtpJMz88fA9kHFFwDXl/3rgRV15Tdkze3AnIg4DjgX2JCZ2zPzaWADsLwcm52Zt5f3fN1Qdy1JkjQJjXUMzz8C/xgRX8nMh5sUy/zMfKzs/xaYX/YXAI/U1dtayoYr39qgXJIkTVLjXXhwd0RcA7wKOGKgMDPPHs9FMzMjIscZ24giYhW1bjIWLVrU6ttJY+azqm7i86pONN5By18HfgWcCHwSeAi4c4zXerx0R1F+bivlfcAJdfUWlrLhyhc2KH+RzLwuM5dm5tJ58+aNMWyp9XxW1U18XtWJxpvwvCQzvwwcyMx/zMz/GRhr684twMBMq5XAd+vKLy6ztZYBO0rX13rgnIg4pgxWPgdYX47tjIhlZXbWxXXXkiRJk9B4u7QOlJ+PRcRbgEeBuSOdFBHfBM4Cjo2IrdRmW10N3BwRlwAPAxeW6uuA84Et1BY5fA9AZm6PiE/zfIvSpzJzYCD0+6jNBOsFvl82SZI0SY034bkyIo4GPkxt/Z3ZwL8b6aTMvGiIQ29qUDeBy4a4zhpgTYPyjcCrR4pDkiRNDuNKeDLze2V3B/DG8YcjSZLUfOMawxMR/11E3DawYnJEvCYiPt6c0CRJkppjvIOWvwRcThnLk5l3A+8Yb1CSJEnNNN6EZ2Zm/nRQ2cFxXlOSJKmpxpvwPBkRLwcSICLeBjw2/CmSJEkTa7yztC4DrgNeGRF9wIPAu8YdlSRJUhONKeGJiA/VfVwH/JBaa9Eu4N8Anx1/aJIkSc0x1haeo8rPk4D/ntpKxgH8GTB4TI8kSVJbjfVt6Z8EiIgfA6/LzGfL508AtzYtOkmSpCYY76Dl+cD+us/7S5kkSVLHGO+g5RuAn0bEd8rnFdTeYSVJktQxxvtqiasi4vvA/1CK3pOZm8YfliRJUvOMt4WHzPw58PMmxCJJktQS4x3DI0mS1PFMeCRJUuWZ8EiSpMoz4ZEkSZVnwiNJkirPhEeSJFWeCY8kSao8Ex5JklR5JjySJKnyTHgkSVLlmfBIkqTKM+GRJEmVZ8IjSZIqz4RHkiRVngmPJEmqPBMeSZJUeSY8kiSp8kx4JElS5XVcwhMRD0XEPRFxV0RsLGVzI2JDRNxffh5TyiMiPh8RWyLi7oh4Xd11Vpb690fEynZ9H0mS1H4dl/AUb8zMUzNzafm8GrgtM5cAt5XPAOcBS8q2CrgWagkScAVwBnA6cMVAkiRJkiafTk14BrsAuL7sXw+sqCu/IWtuB+ZExHHAucCGzNyemU8DG4DlEx20JEnqDJ2Y8CTwDxHxs4hYVcrmZ+ZjZf+3wPyyvwB4pO7craVsqHJJkjQJTW13AA38QWb2RcRLgQ0R8av6g5mZEZHNuFFJqFYBLFq0qBmXlFrCZ1XdxOdVnajjWngys6/83AZ8h9oYnMdLVxXl57ZSvQ84oe70haVsqPLB97ouM5dm5tJ58+Y1+6tITeOzqm7i86pO1FEJT0TMioijBvaBc4BfALcAAzOtVgLfLfu3ABeX2VrLgB2l62s9cE5EHFMGK59TyiRJ0iTUaV1a84HvRATUYvtGZv59RNwJ3BwRlwAPAxeW+uuA84EtwG7gPQCZuT0iPg3cWep9KjO3T9zXkCRJnaSjEp7MfAB4bYPyp4A3NShP4LIhrrUGWNPsGCVJUvfpqC4tSZKkVjDhkSRJlWfCI0mSKs+ER5IkVZ4JjyRJqjwTHkmSVHkmPJIkqfJMeCRJUuWZ8EiSpMoz4ZEkSZVnwiNJkirPhEeSJFVeR708tJ0efPBB3vnOd7Y7DFXIN77xjXaHIEkqbOGRJEmVZwtPsWvXLjZu3NjuMCRJUguY8BSZSX9/f7vDkCRJLWCXliRJqjwTHkmSVHkmPJIkqfIcwzNBIqLdIVReZrY7BElShzLhGYOIYPr06e0OQxMkM9m/f3+7w5AkjYMJzxhMmTLFhGeSmT59ui1IktTFTHjGoL+/n2effXZUdcfTleU/sJIkNYcJTzF16lSOPfbYF5Q9+eST477ueJKWadOm0dPTM+4YJEma7Ex4it///d/njjvueFF5ZrJz584JX5Swt7eX3t7eCb2nJElVZcIzgojg6KOPbncYkiRpHFyHR5IkVZ4Jj9RlDh06xKFDh15Q9tRTT/Gl/7+9Ow+SozzvOP79zbkHskAiqBTJBRKnIU6wTBmjGIKpxBYy4PxhcySRKWEKMJDEBBlEyZVSqlAMdkwJAkGYaxOCuG2ZKCIQO6qAsUscthCIWAeCCiI2BGKhY3fuJ3+870qzyy7LLrPTs6PnU9W1PW/3dD/vO29Pv9v9Tr+3384tt9zC5s2bh3zfjh07eOSRRyiXy80I0znnWoo3eJybYF555RWWLVu2t0P8u+++y4IFC7juuuu44YYbOOecc9i0adOA9+zevZuFCxdy1VVXsXjx4vc0mJxzrt15Hx7nJpju7m56enqoVqusW7eOd955h507d3L33Xdz6KGHcvbZZ7Nw4ULWrl1LPp8HYMmSJWzYsIH58+ezatUqjjrqKC6++OKEc+Kcc83jV3icm2BKpRKSWLlyJWbG3LlzWbFiBVOnTmXjxo3s2rWLadOmkcns+39m5syZAKxZswaAGTNmJBK7c84lpW2v8EiaB9wIpIE7zOy6hENyriHMjGw2y6xZs7jvvvuYPHkya9eu5ayzzgJg9uzZ3HnnnQOe4XTllVeyfft2Vq9ezdVXX80ZZ5yRVPjOOZeItrzCIykN3AKcDhwLnCfp2GSjcq4x+voKTJs2jZ6enr2PTJg7dy5Tp04FYNGiRUyZMmXAe1KpFMuXL2fr1q1cdNFFTY/ZOeeS1q5XeD4FbDWzbQCS7ge+CLw8lo1Vq1UKhSLlcplqrYrVDDOjZjWq1SrlSpVSqUSpVKZUKlIsl6lV+zuFimwuQy6TJZfLks/n6MjnyWVzpNIpRH3PyAAADGVJREFUUgptzkqlQrFUorevl97eAn2FIuVKBQgdU9OpVFg/lYIaVKxKsVCmUCzSWyjS21ekUqlSqpSp1KpUK3VPeBZk02nyuSz5XIaPdHXQ3d1Nd1cnXZ2dZLMZUqkUtVqNcrlMX6FIX6FIoViir1CgXK5QrlSpxU6yKYlsJk06lSaXz5DP5ujsyNPZ1UFnPk9HLk82nyObSWNmVKs1SuVQPr29fRTKJYqFEoVikWq1RqW6b9sxXCSRUopMOkU2l41llqGzo4NcNpSlJKxmFMsl+gpFdu/uZWfvHt7duYc9vQV6i+VYHrVYhqIjm43lkKUzF7aTTadIZzKklUKp8HlIkE6nkUQ6JXK5PB25HF2debq7u+js7KS7q4tcLvehhg8Zi2omT+rgWRxyyCF70/L5PAsWLGD58uW8/vrrQ76v2XE651wradcGzwyg/lt/O3DiWDZ0z8r7Wbos3A2zVBYyoRMo9ScPCXIHhL/ZDkgNKtZaFcp9YAbl3vDaDMp9yMITnC3XDUpBthPSWcgfMHJwuS4sk4dsF3RMgkwuxJfrem8MpV6oFKG4Gwq7UGkXFHaH9FrdU6RT6fD+XCeW7YRMZ9h2/zIzsNiYqxShUoLiLlQpQqUQtlmrhPzWS2ch0xHiy+Qg3wVKh/jT+aHzV9qFzEJ8pV6wKpT69pYdtUrIeyoN+W7Id2Mdk6HzQOicjOUPgPykus+hgsp7oLAzbKdaDuWxd1nv0HHs3X8NinvCvislVN7DyXNPouf2W0f+rBop18WrO40dO3Zw7bXX8sQTTwCwZ88ezjzzTC644ILmxuOccxOA2nGASklfAuaZ2YXx9QLgRDO7fNB6FwH91/ePBgb+lnegg4EPP7hWMiZq7BM1bgix/9LM5jViY4Pq6u8ALzViuw3Wqp+Xx/XBvD1O9XW479ZWy3/SvDz2GaksxlRX27XBcxKw1Mw+H19fA2Bm3/oQ23zOzE5oUIhNNVFjn6hxw/jG3qrl4nGNTqvG1Sz7e/4H8/LYZ7zKoi07LQPPAkdKmiUpB5wLPJpwTM4555xLSFv24TGziqTLgccJP0u/y8w2JhyWc8455xLSlg0eADNbA6xp4Ca/18BtNdtEjX2ixg3jG3urlovHNTqtGlez7O/5H8zLY59xKYu27MPjnHPOOVevXfvwOOecc87t5Q2eD0DSPEmbJG2VtDihGD4qaa2klyVtlPSXMX2KpH+XtCX+PSimS9JNMeYNkubUbev8uP4WSefXpX9S0ovxPTepgU+qk5SW9AtJq+PrWZLWxX09EDuXIykfX2+Nyw+r28Y1MX2TpM/XpY/b5yPpQEkPS/qlpP+SdFKSZd6MuijptRjTeknPxbSm51nSXZLekvRSXdq4xzHcPkaIa6mkN2KZrZc0v27ZqOrtWI6NiaYZ9TgJSdXZVqRWPGeZmU/vMxE6Pb8CzAZywAvAsQnEMR2YE+cnAZsJw2Z8G1gc0xcD18f5+cBjhAcXfxpYF9OnANvi34Pi/EFx2TNxXcX3nt7A+P8KWAmsjq8fBM6N8yuAr8X5S4EVcf5c4IE4f2ws+zwwK34m6fH+fIB/BC6M8zngwKTKvFl1EXgNOHhQWtPzDJwCzAFeamYcw+1jhLiWAouGyMOo6y2jPDYm2tSsepxQ3hKps6040YLnrMQLpdUn4CTg8brX1wDXtEBcPwT+iPBAr+l1FWxTnL8NOK9u/U1x+XnAbXXpt8W06YQH5fWnD1jvQ8Y6E/gxcBqwOlbOt4HM4DIm/LLupDifietpcLn3rzeenw8wGXiV2NdtcFk2u8ybVRcZusGTVJ4PY+DJY9zjGG4fI8S1lKEbPKOqt4zh2Gj05z/eU7PqcYL5a3qdnQgTLXDO8ltaIxtqmIoZCcUCQLyU/QlgHTDNzH4VF/0amBbnh4v7/dK3D5HeCMuBq4D+AcamAjvMrDLEvvbGF5e/G9cfbX4aYRbwv8DdCrfj7pDUTXJl3qy6aMATkp5XeGIutE49a0Ycw+1jJJfHS/F31d0GG21cYzk2JpqW+04dZ61y7CSmVc5Z3uCZYCQdADwCfN3MdtYvs9DMbamf3Uk6A3jLzJ5POpYxyBAuT99qZp8A9hAuwe7VimXeAJ8xsznA6cBlkk6pX9gqeW5GHKPYx63A4cDxwK+A745nXG5iapVjp5la6ZzlDZ6RvQF8tO71zJjWdJKyhIpzr5l9Pya/KWl6XD4deCumDxf3+6XPHCL9w/p94CxJrwH3E25r3QgcKKn/OVD1+9obX1w+GXhnDPlphO3AdjNbF18/TGgAJVXmTamLZvZG/PsW8APgU7ROPWtGHMPtY1hm9qaZVc2sBtxOKLOxxPUOoz82JpqW+U5tklY5dpqu5c5ZSd/Xa/WJ8F/+NsLtjf4OdsclEIeAfwKWD0r/DgM7gH07zn+BgR3AnonpUwj9Ug6K06vAlLhscAew+Q3Ow6ns67T8EAM7Zl4a5y9jYMfMB+P8cQzs/LmN0PlxXD8f4Cng6Di/NJZ3ImXejLoIdAOT6uZ/CsxLMM+HMbA/xLjHMdw+Rohret38FcD9Y623jPLYmGhTM+pxwvlrep1txYkWPGclXigTYSL0Ht9M+GXBkoRi+Azh0t8GYH2c5hPu4f8Y2AL8qK4iCLglxvwicELdti4AtsZpYV36CYRRuF8BbqbBHSIZ2OCZHSvr1vgFn4/pHfH11rh8dt37l8TYNlHXG388Px/CLYrnYrmvigdcYmU+3nUxfi4vxGlj/z6SyDNwH+H2UJlwte2rzYhjuH2MENc9cb8bCOP21TeARlVvGcOxMdGm8a7HCeYrkTrbihMteM7yJy0755xzru15Hx7nnHPOtT1v8DjnnHOu7XmDxznnnHNtzxs8zjnnnGt73uBxzjnnXNvzBo97D0l/oTAy+G/aaSRj55xrFklLJS0aw/tOlTS37nWPpC81Nrr9U2bkVdx+6FLgD81s+4hrOueca6RTgd2Eh366BvIrPG4ASSsIDz57TNIVkm6O6T2SVkh6TtLmOEYWko6T9Iyk9XHgxCOTjN+1L0lfiXXsBUn3SDpT0ro4sOuPJE2L6/1BrI/r47JJMf0bkp6N2/ibmNYt6V/jNl+SdE6SeXQTm6Ql8fvxJ8DRMe1wSf8WB+N9StIxMf099TcOsnkJcEWsvyfHTZ8i6aeStvVf7ZE0XdKTcb2X6tZ1w/ArPG4AM7tE0jzgs8AZgxYfRhgj6HBgraQjCAfnjWZ2r6Qc4bH5zjWUpOOAbwJzzextSVMIT3H9tJmZpAuBq4ArgUXAZWb2dBy4sCDpc8CRhPor4NE4KOpvAf9jZl+I+5nc9My5tiDpk4QhP44nnFt/DjwPfA+4xMy2SDoR+AfCmII/YVD9NbMr4z+du83s7+J2vwpMJzy5+BjCk7wfBv4EeNzMlklKA11NzO6E5A0eNxoPWhgccYukbYSD72fAEkkzge+b2ZZEI3Tt6jTgITN7G8DM/k/Sx4EH4gCEOcIYOwBPAzdIupdQJ7fHBs/ngF/EdQ4gNICeAr4r6XrCsCdPNS9Lrs2cDPzAzHoBJD1KGA5kLvCQpP718vHvTIauv0NZFb97X+6/kgk8C9wVB+hcZWbrG5qbNuS3tNxoDB6HxMxsJXAW0AeskXRa88Ny+6m/B242s48DFxNOLpjZdcCFQCfwdLyFIOBbZnZ8nI4wszvNbDMwhzB2z7WS/jqRnLh2lQJ21NW7483sY3HZkPV3GMW6eQGY2ZPAKYQRwnskfaXx4bcXb/C40fiypJSkwwn9fDZJmg1sM7ObgB8Cv5tohK5d/Qeh/k0FiLe0JhO+7AHO719R0uFm9qKZXU/4L/gY4HHggniLC0kzJB0i6beBXjP7Z8IoznOaliPXbp4E/lhSZ+w3dibQC7wq6csACn4vrj9k/QV2AZNG2pmkQ4E3zex24A687o7Ib2m50fhvwijNHyHcky5IOhtYIKkM/Br42yQDdO3JzDZKWgb8p6Qq4dbUUsKtgt8QGkSz4upfl/RZoEYY8f0xMytK+hjws3hrYTfwZ8ARwHck1QgjXH+tidlybcTMfi7pAeAF4C1CYxvgT4FbJX0TyAL3x3WWMnT9/RfgYUlfBP78fXZ5KvCN+N27G/ArPCPw0dLdByKph9DH4eGkY3HOOedGy29pOeecc67t+RUe55xzzrU9v8LjnHPOubbnDR7nnHPOtT1v8DjnnHOu7XmDxznnnHNtzxs8zjnnnGt73uBxzjnnXNv7fyerpPmjYl5IAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 540x540 with 12 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "N7nTgzFQ_bU9",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}