Netflix_ExploratoryDataAnalysis.ipynb

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    {
      "cell_type": "markdown",
      "source": [
        "# **Netflix-ExploratoryDataAnalysis**"
      ],
      "metadata": {
        "id": "YBbflOv12yrt"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Importing Libraries"
      ],
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        "id": "B0qm8StE2nrp"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns"
      ],
      "metadata": {
        "id": "gL3_WcvWje5k"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Assigning the Excel file to a dataframe"
      ],
      "metadata": {
        "id": "1uVRluc927Xf"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.read_excel(\"Netflix_Titles.xlsx\")"
      ],
      "metadata": {
        "id": "X-c1Odn-jz-w"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Checking first 5 rows of the dataframe"
      ],
      "metadata": {
        "id": "1nTEh6Yg2_A9"
      }
    },
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      "cell_type": "code",
      "source": [
        "df.head()"
      ],
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              "         id                                title   type  \\\n",
              "0  ts300399  Five Came Back: The Reference Films   SHOW   \n",
              "1   tm84618                          Taxi Driver  MOVIE   \n",
              "2  tm154986                          Deliverance  MOVIE   \n",
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              "4  tm120801                      The Dirty Dozen  MOVIE   \n",
              "\n",
              "                                         description  release_year  \\\n",
              "0  This collection includes 12 World War II-era p...          1945   \n",
              "1  A mentally unstable Vietnam War veteran works ...          1976   \n",
              "2  Intent on seeing the Cahulawassee River before...          1972   \n",
              "3  King Arthur, accompanied by his squire, recrui...          1975   \n",
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      "source": [
        "# Checking last 5 rows of the dataframe"
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              "             id                                      title   type  \\\n",
              "5845  tm1014599                                  Fine Wine  MOVIE   \n",
              "5846   tm898842                                C/O Kaadhal  MOVIE   \n",
              "5847  tm1059008                                    Lokillo  MOVIE   \n",
              "5848  tm1035612  Dad Stop Embarrassing Me - The Afterparty  MOVIE   \n",
              "5849   ts271048         Mighty Little Bheem: Kite Festival   SHOW   \n",
              "\n",
              "                                            description  release_year  \\\n",
              "5845  A beautiful love story that can happen between...          2021   \n",
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              "5847  A controversial TV host and comedian who has b...          2021   \n",
              "5848  Jamie Foxx, David Alan Grier and more from the...          2021   \n",
              "5849  With winter behind them, Bheem and his townspe...          2021   \n",
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              "     age_certification  runtime                             genres  \\\n",
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              "5846               NaN      134                          ['drama']   \n",
              "5847               NaN       90                         ['comedy']   \n",
              "5848             PG-13       37                                 []   \n",
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              "      <td>2021</td>\n",
              "      <td>NaN</td>\n",
              "      <td>90</td>\n",
              "      <td>['comedy']</td>\n",
              "      <td>['CO']</td>\n",
              "      <td>NaN</td>\n",
              "      <td>tt14585902</td>\n",
              "      <td>3.8</td>\n",
              "      <td>68.0</td>\n",
              "      <td>26.005</td>\n",
              "      <td>6.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5848</th>\n",
              "      <td>tm1035612</td>\n",
              "      <td>Dad Stop Embarrassing Me - The Afterparty</td>\n",
              "      <td>MOVIE</td>\n",
              "      <td>Jamie Foxx, David Alan Grier and more from the...</td>\n",
              "      <td>2021</td>\n",
              "      <td>PG-13</td>\n",
              "      <td>37</td>\n",
              "      <td>[]</td>\n",
              "      <td>['US']</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.296</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5849</th>\n",
              "      <td>ts271048</td>\n",
              "      <td>Mighty Little Bheem: Kite Festival</td>\n",
              "      <td>SHOW</td>\n",
              "      <td>With winter behind them, Bheem and his townspe...</td>\n",
              "      <td>2021</td>\n",
              "      <td>NaN</td>\n",
              "      <td>7</td>\n",
              "      <td>['family', 'animation', 'comedy']</td>\n",
              "      <td>[]</td>\n",
              "      <td>1.0</td>\n",
              "      <td>tt13711094</td>\n",
              "      <td>7.8</td>\n",
              "      <td>18.0</td>\n",
              "      <td>2.289</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "    .colab-df-convert:hover {\n",
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              "  </style>\n",
              "\n",
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              "        document.querySelector('#df-a70c4a6f-05e7-4cc7-ba6c-4e4c26dc2cca button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-a70c4a6f-05e7-4cc7-ba6c-4e4c26dc2cca');\n",
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              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        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",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
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              "\n",
              "\n",
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              "            title=\"Suggest charts.\"\n",
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              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "\n",
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              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Overhead View of the dataframe"
      ],
      "metadata": {
        "id": "mTQVcz3_3L1Y"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Getting the information about our dataset to know how many\n",
        "#null value are there and what are the datatypes of each column\n",
        "df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "178O7deCkDYo",
        "outputId": "8d0e6122-9f53-4ea9-8348-f7a56c595078"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 5850 entries, 0 to 5849\n",
            "Data columns (total 15 columns):\n",
            " #   Column                Non-Null Count  Dtype  \n",
            "---  ------                --------------  -----  \n",
            " 0   id                    5850 non-null   object \n",
            " 1   title                 5849 non-null   object \n",
            " 2   type                  5850 non-null   object \n",
            " 3   description           5832 non-null   object \n",
            " 4   release_year          5850 non-null   int64  \n",
            " 5   age_certification     3231 non-null   object \n",
            " 6   runtime               5850 non-null   int64  \n",
            " 7   genres                5850 non-null   object \n",
            " 8   production_countries  5850 non-null   object \n",
            " 9   seasons               2106 non-null   float64\n",
            " 10  imdb_id               5447 non-null   object \n",
            " 11  imdb_score            5368 non-null   float64\n",
            " 12  imdb_votes            5352 non-null   float64\n",
            " 13  tmdb_popularity       5759 non-null   float64\n",
            " 14  tmdb_score            5539 non-null   float64\n",
            "dtypes: float64(5), int64(2), object(8)\n",
            "memory usage: 685.7+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Dropping the unnecessary columns"
      ],
      "metadata": {
        "id": "_EGGXlC_3WAf"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#These column are of no use in our analysis, so dropping them\n",
        "df = df.drop(columns = [\"id\", \"description\", 'production_countries',\n",
        "                        'imdb_id', 'tmdb_popularity', 'tmdb_score', 'seasons'])\n",
        "df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_Vfkkx1tkGfQ",
        "outputId": "e6be8105-f761-46c0-aca9-4a489c29ed63"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 5850 entries, 0 to 5849\n",
            "Data columns (total 8 columns):\n",
            " #   Column             Non-Null Count  Dtype  \n",
            "---  ------             --------------  -----  \n",
            " 0   title              5849 non-null   object \n",
            " 1   type               5850 non-null   object \n",
            " 2   release_year       5850 non-null   int64  \n",
            " 3   age_certification  3231 non-null   object \n",
            " 4   runtime            5850 non-null   int64  \n",
            " 5   genres             5850 non-null   object \n",
            " 6   imdb_score         5368 non-null   float64\n",
            " 7   imdb_votes         5352 non-null   float64\n",
            "dtypes: float64(2), int64(2), object(4)\n",
            "memory usage: 365.8+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Renaming Column as per need"
      ],
      "metadata": {
        "id": "AHPqUW2G3aLV"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Renaming column as it's name was unnecessary big\n",
        "df = df.rename(columns = {'age_certification': 'rating'})\n",
        "df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6Fuis0TrlEBS",
        "outputId": "52c3f160-d348-43f5-dea6-5a9e8865e280"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 5850 entries, 0 to 5849\n",
            "Data columns (total 8 columns):\n",
            " #   Column        Non-Null Count  Dtype  \n",
            "---  ------        --------------  -----  \n",
            " 0   title         5849 non-null   object \n",
            " 1   type          5850 non-null   object \n",
            " 2   release_year  5850 non-null   int64  \n",
            " 3   rating        3231 non-null   object \n",
            " 4   runtime       5850 non-null   int64  \n",
            " 5   genres        5850 non-null   object \n",
            " 6   imdb_score    5368 non-null   float64\n",
            " 7   imdb_votes    5352 non-null   float64\n",
            "dtypes: float64(2), int64(2), object(4)\n",
            "memory usage: 365.8+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Returning description of the data"
      ],
      "metadata": {
        "id": "HI9qiqvT3nDT"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "sOMYXkiBlqCX",
        "outputId": "4c7e59aa-c2b3-4dbf-d42f-5b439cc7801f"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       release_year      runtime   imdb_score    imdb_votes\n",
              "count   5850.000000  5850.000000  5368.000000  5.352000e+03\n",
              "mean    2016.417094    76.888889     6.510861  2.343938e+04\n",
              "std        6.937726    39.002509     1.163826  9.582047e+04\n",
              "min     1945.000000     0.000000     1.500000  5.000000e+00\n",
              "25%     2016.000000    44.000000     5.800000  5.167500e+02\n",
              "50%     2018.000000    83.000000     6.600000  2.233500e+03\n",
              "75%     2020.000000   104.000000     7.300000  9.494000e+03\n",
              "max     2022.000000   240.000000     9.600000  2.294231e+06"
            ],
            "text/html": [
              "\n",
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              "      <th></th>\n",
              "      <th>release_year</th>\n",
              "      <th>runtime</th>\n",
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              "      <th>imdb_votes</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>5850.000000</td>\n",
              "      <td>5850.000000</td>\n",
              "      <td>5368.000000</td>\n",
              "      <td>5.352000e+03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>2016.417094</td>\n",
              "      <td>76.888889</td>\n",
              "      <td>6.510861</td>\n",
              "      <td>2.343938e+04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>6.937726</td>\n",
              "      <td>39.002509</td>\n",
              "      <td>1.163826</td>\n",
              "      <td>9.582047e+04</td>\n",
              "    </tr>\n",
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              "      <th>min</th>\n",
              "      <td>1945.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.500000</td>\n",
              "      <td>5.000000e+00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>2016.000000</td>\n",
              "      <td>44.000000</td>\n",
              "      <td>5.800000</td>\n",
              "      <td>5.167500e+02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>2018.000000</td>\n",
              "      <td>83.000000</td>\n",
              "      <td>6.600000</td>\n",
              "      <td>2.233500e+03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>2020.000000</td>\n",
              "      <td>104.000000</td>\n",
              "      <td>7.300000</td>\n",
              "      <td>9.494000e+03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>2022.000000</td>\n",
              "      <td>240.000000</td>\n",
              "      <td>9.600000</td>\n",
              "      <td>2.294231e+06</td>\n",
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              "        if (!dataTable) return;\n",
              "\n",
              "        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",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-0efee007-68f0-4a27-9256-d893e703e6ce\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-0efee007-68f0-4a27-9256-d893e703e6ce')\"\n",
              "            title=\"Suggest charts.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "    background-color: #E8F0FE;\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: #1967D2;\n",
              "    height: 32px;\n",
              "    padding: 0 0 0 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: #E2EBFA;\n",
              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: #174EA6;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "    background-color: #3B4455;\n",
              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
              "    background-color: #434B5C;\n",
              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "    fill: #FFFFFF;\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const charts = await google.colab.kernel.invokeFunction(\n",
              "          'suggestCharts', [key], {});\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-0efee007-68f0-4a27-9256-d893e703e6ce button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Checking the shape of dataframe"
      ],
      "metadata": {
        "id": "NlpJG5ML3vuA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "x_fPmBeil-oc",
        "outputId": "906826b3-6d66-4b93-f408-af518523b508"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(5850, 8)"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0g5v_ZPDmbR6",
        "outputId": "c177b16e-0e18-42ff-9619-75a5a5e67c4d"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 5850 entries, 0 to 5849\n",
            "Data columns (total 8 columns):\n",
            " #   Column        Non-Null Count  Dtype  \n",
            "---  ------        --------------  -----  \n",
            " 0   title         5849 non-null   object \n",
            " 1   type          5850 non-null   object \n",
            " 2   release_year  5850 non-null   int64  \n",
            " 3   rating        3231 non-null   object \n",
            " 4   runtime       5850 non-null   int64  \n",
            " 5   genres        5850 non-null   object \n",
            " 6   imdb_score    5368 non-null   float64\n",
            " 7   imdb_votes    5352 non-null   float64\n",
            "dtypes: float64(2), int64(2), object(4)\n",
            "memory usage: 365.8+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Checking the dataframe for unique values"
      ],
      "metadata": {
        "id": "IlYIBbRV399n"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#We get to know how much unique values are in our data so we can proceed further accordingly\n",
        "df.nunique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zKH5xvBpmCIk",
        "outputId": "8d90f88b-c94e-42b6-bb78-214e08f041b4"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "title           5798\n",
              "type               2\n",
              "release_year      63\n",
              "rating            11\n",
              "runtime          202\n",
              "genres          1726\n",
              "imdb_score        80\n",
              "imdb_votes      3880\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Checking how many null values are in our dataframe"
      ],
      "metadata": {
        "id": "BS15NynP4GZF"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Checking count of null values and we found out that one title row is null, removing it would be better\n",
        "df.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EbZWZSoCmEGs",
        "outputId": "4b446380-b401-4ccd-8440-efa76c187e51"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "title              1\n",
              "type               0\n",
              "release_year       0\n",
              "rating          2619\n",
              "runtime            0\n",
              "genres             0\n",
              "imdb_score       482\n",
              "imdb_votes       498\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Returning the specific row which contains the null title"
      ],
      "metadata": {
        "id": "8ht0Lw5w4IdH"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Returning the row which contained null value in our title column\n",
        "df[df['title'].isnull()]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 89
        },
        "id": "Nwpy1o0HmVfz",
        "outputId": "5070e3ba-0ab8-4f58-9187-f72ceff51283"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     title   type  release_year rating  runtime genres  imdb_score  imdb_votes\n",
              "1704   NaN  MOVIE          2015    NaN       11     []         NaN         NaN"
            ],
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              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-4ef8ae37-2a7f-4120-b51b-eb2bd575952e button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-4ef8ae37-2a7f-4120-b51b-eb2bd575952e');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        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",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "\n",
              "\n",
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              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "\n",
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              "    padding: 0 0 0 0;\n",
              "    width: 32px;\n",
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              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: #E2EBFA;\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "    background-color: #3B4455;\n",
              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
              "    background-color: #434B5C;\n",
              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "    fill: #FFFFFF;\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const charts = await google.colab.kernel.invokeFunction(\n",
              "          'suggestCharts', [key], {});\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-f9ab8731-4b63-4982-9a26-9ff28a127d9c button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Dropping the row with the null title"
      ],
      "metadata": {
        "id": "h-CK0vHW4PNr"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df = df.drop(1704)"
      ],
      "metadata": {
        "id": "_28gf7KPnB1a"
      },
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "p3DEzY3ynkLB",
        "outputId": "57636622-e190-4d14-a0ff-8f7269afb1d9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "title              0\n",
              "type               0\n",
              "release_year       0\n",
              "rating          2618\n",
              "runtime            0\n",
              "genres             0\n",
              "imdb_score       481\n",
              "imdb_votes       497\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 168
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Filling null values in Rating column with Not Rated\n"
      ],
      "metadata": {
        "id": "JT59dVNa4TeE"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df['rating'].fillna('Not Rated')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Bd35exwtnxrI",
        "outputId": "eb34b5d9-7c74-422e-f69c-2af30421cbeb"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0           TV-MA\n",
              "1               R\n",
              "2               R\n",
              "3              PG\n",
              "4       Not Rated\n",
              "          ...    \n",
              "5845    Not Rated\n",
              "5846    Not Rated\n",
              "5847    Not Rated\n",
              "5848        PG-13\n",
              "5849    Not Rated\n",
              "Name: rating, Length: 5849, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['rating'] = df['rating'].fillna('Not Rated')\n",
        "df.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SZ9Ym8DKoJYI",
        "outputId": "3ed88a7d-ed24-4d29-9667-063763342b3a"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "title             0\n",
              "type              0\n",
              "release_year      0\n",
              "rating            0\n",
              "runtime           0\n",
              "genres            0\n",
              "imdb_score      481\n",
              "imdb_votes      497\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Checking for outliers"
      ],
      "metadata": {
        "id": "pqwYogpf4eAr"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.boxplot()\n",
        "plt.rcParams['figure.figsize'] = (7,5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 445
        },
        "id": "eqyfKSdHoVDA",
        "outputId": "e971b861-a0d2-4941-e1d9-d0d931833dfd"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Overhead view of data after cleaning and transforming data"
      ],
      "metadata": {
        "id": "LuOHgzqd4imD"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Now our data is clean and have null values only in imdb_scores and imdb_votes which can be fixed while working\n",
        "df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Krqn565go_Uv",
        "outputId": "5b3fd40b-a60a-4e85-b7a6-c58e64520100"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 5849 entries, 0 to 5849\n",
            "Data columns (total 8 columns):\n",
            " #   Column        Non-Null Count  Dtype  \n",
            "---  ------        --------------  -----  \n",
            " 0   title         5849 non-null   object \n",
            " 1   type          5849 non-null   object \n",
            " 2   release_year  5849 non-null   int64  \n",
            " 3   rating        5849 non-null   object \n",
            " 4   runtime       5849 non-null   int64  \n",
            " 5   genres        5849 non-null   object \n",
            " 6   imdb_score    5368 non-null   float64\n",
            " 7   imdb_votes    5352 non-null   float64\n",
            "dtypes: float64(2), int64(2), object(4)\n",
            "memory usage: 411.3+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Visualization of Top 10 Netflix Titles by IMDB_score"
      ],
      "metadata": {
        "id": "QXOkUaZEvU9r"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Sorting the dataframe to get top ten titles of Netflix whether its movie or a show\n",
        "#What title is top or bottom is decided by their respective imdb_scores\n",
        "top_10_titles = df.sort_values(by = 'imdb_score', ascending = False).head(10)\n",
        "ax = sns.barplot(x = 'title', y = 'imdb_score', data = top_10_titles)\n",
        "\n",
        "ax.set_xticklabels(ax.get_xticklabels(), rotation=40, ha=\"right\")\n",
        "plt.title('Top 10 Netflix Titles')\n",
        "plt.rcParams['figure.figsize'] = (15,7)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 803
        },
        "id": "szMhVmdIpWgm",
        "outputId": "22eca558-8831-4491-c06f-5f66ea8a6253"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x700 with 1 Axes>"
            ],
            "image/png": 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0NFSbNm2q9erV01u3bhnLnz59qsWLF1eLxaJVqlSJqzLxGsLDw43/DwkJMf5/zpw5mjhxYl2wYIE+fvxYVVVnzpypCRIk0AULFlitC/v21VdfaZIkSXTgwIE6evRozZYtm/r6+hptWK9ePS1UqJCOHj1amzdvrhaLRf38/Kz+bcA2Itsg6j530KBBmi5dOl2zZo3euHFDP/74Y02bNq3u2LFDw8LCdOPGjZotWzZt166drcrGK/zwww+aIkUKrVSpkmbMmFEzZcqk169fN96/e/euuru76/Hjx1U1Yr98//59LVGihC5dutRWZeMVom6f27Zt0759++qxY8dUVXXo0KGaIUMGTZUqla5cudJYLyAgQDt16qQTJkzgeGqHIts0PDxc+/btq3nz5tVTp04Z769Zs0ZLliyp58+fV1XV9evXa4oUKdRisXDtYsci2/Xhw4e6adMmPXTokPr5+amq6qlTp7Ru3bpasWJFPXjwoKoq50F27vLly7pkyRLt1q2bBgYGqmpE7nD58mWtUqWKlitXTvPmzavZsmXTFStWqKrqixcvbFmy3SM0s5F58+bpwIEDjR2SasROKUuWLPrw4UNVVT1+/Lh+/PHH+vnnn+uBAweM5Xny5NEFCxbEfdF4pag7m59//lmXLl2qq1evNpbNmTNHS5QooV988YWx7MGDB9q8eXPduHGjnj17Nk7rxT/75Zdf9O+//1ZV1V27dumiRYtUVbVFixZasGBB/emnn4x1P//8c02ePLlu3br1peEp7MeNGze0ePHixjbq5+en2bNn1ypVquiDBw9UVTU4OFhbtmyp5cuX10qVKun9+/dtWTL+39KlS3XWrFlWywIDA7V06dK6Zs0aVY04fqZMmVK7du2qz549U1XV58+f6/z589VisejGjRvjvG683K5duzRz5sy6YsUKDQ0NVVXVtGnT6uLFi63WK1GihDZt2lSfPHmi/v7+2rt3b82WLZtxgQ77NGnSJE2WLJlVaPbo0SPNly+fFi9eXI8fP65hYWHq7++vLVq0UE9PT71w4YJti8ZL+fv769SpU7VRo0Z66NAhq/f69++v7u7uxuuZM2fqsGHDjHaH/dq7d6+mT59ec+XKpRkyZNBs2bIZ7btjxw6tVKmS1q9f3zgv5lzXPp04cULz5MmjmTJl0nnz5qmqdVs9e/ZMd+7cqQ0aNFCLxaJFihTR58+f26rcdwahmY0MHjxY06ZNq7NmzdLg4GBVVV27dq26ubnps2fPYryLrhpxJzZ79uy6d+/eOK8ZLxf1jkv79u01c+bMWrBgQc2cObN+9NFHRjsOHjxYCxQooD4+Pjps2DD19vbWMmXKGL0OSfnth5+fn5YqVUo9PT11ypQparFYjINPaGioli5dWitUqKC7du0yPlOjRg1Nnjy50RMC9mvXrl3q6uqqqqq//fabpk6dWtu3b28ELDdu3FBV1cePHxOW2ZGnT59qhQoVtEyZMvrzzz8by//66y8tXLiwhoSE6Ny5czVZsmQ6ZswY4/0DBw5oQECABgYG6v79+21ROl5h7ty56uvra9wcVI3Yn/7444+6ZcsW4075woUL1c3NTVOmTKkFChRQLy8vvXLliqrS88Febd++XbNkyaKbNm2K9t7p06c1V65cmitXLvXy8lIfHx/Nnz+/3rlzxwaV4nWNGTNGU6ZMqenTpzeenogMuw8cOKDOzs5au3ZtbdeunSZLlkzXr19vy3JhEhQUZJzrRDp79qxmzJhRx4wZozdv3tQTJ05ovXr1NG3atHrkyBFVVV28eLGWK1dOGzVqpI8ePbJF6YiB+dh3+fJl7dq1qyZJkkTnzJmjqv+7vjTnCtOmTdOiRYvqmTNn4qbYdxihWRwKDQ3Vbdu2Ga8//fRT9fT0NLpFLliwwOoRvbCwMA0LC9Pw8HBdv3699u7dW5MmTarffPNNnNeOfxYeHq6ffPKJenl56cWLF1U1okeExWLRTz/9VFUj0v09e/Zow4YNtW7dutq+fXurz8O+HD58WJ2dnTVJkiS6fft2VY24aFdVvXr1qubOnVs//vhjqzuoH330kd67d88W5SIG4eHhMW5bN27c0KpVq2rfvn3V2dlZx4wZY6x3+PBhbd26NRdudiayfS5evKgVK1bUevXqGTeQHj9+rOnTp9eiRYtq2rRpddmyZcbnjh8/ru3bt9ejR4/apG78sxEjRmiaNGn0xIkTGhISoh07dtSECRNquXLlNGnSpFq7dm3jZsSFCxd0wYIFumrVKuNCgBtO9uubb75RHx8fDQoKsrpwi9yer127phs2bNBZs2bp8uXLbVkqYvCy3kS9e/fWFClS6KRJk6yWP3nyRNesWaPVqlXTWrVq6W+//RYXZeI1hIeH68WLF2O8ubtlyxbNkyeP3r5922p5yZIltWTJksbr4cOHa9OmTa1ucMB2XnbsO3PmjDZo0EDd3NyMa5So60Zu1wEBAZoyZUqeYHsNhGZxJDJQ8fHx0Q0bNhjLq1evroULF9Y9e/boF198oQMGDIj22cDAQJ0xY4ZWqFBB9+zZE5dl41/466+/tEePHvrHH3+oasQd8Q8//FBbtGihjo6OOmrUKKv1o47VEXmHDvYh8mCybds2zZIli6ZJk0Z79+5tvB/Zdnv37lV3d3ft2rWrnjt3zia14uWihmWnT5/WP/74Q//66y9VjQjNypcvr4kTJ4520j9w4ECtXr261XhKsL2o+8mffvpJS5YsqW3atNE///xTVSOGPTC359OnT7VVq1ZapkwZq/EkYRsvuzn0/PlzzZs3r2bPnl29vb01c+bMevLkSX3+/LnRG2n8+PExfpbAzD68rG379u2rOXLkMF5Hba9Lly4ZT1vA/kTd596+fdsYukA1YuyrevXqaYUKFax6/UZ6/vw5j3zZqZjaa8mSJZo4cWKjzSNvEEcOdRB5/RkaGmo1rh1sJ7Idbt68qW3bttW2bdtqly5djHOdQ4cOabVq1bRs2bJ69+5dVY35eFm2bFmdOXNm3BX+jiI0i0PHjh3T8uXLa6NGjYzHQx48eKAFCxbURo0aad68edXV1VUHDRqkY8eO1QULFuiePXv0559/1ps3b8Y4cQDiTtSDw6+//qrz5s3TVatWWbXLb7/9pi9evNBFixZp1qxZjTGw2rZtq8mSJdMlS5ZE+17GBLAf5rZ4/vy53rlzRxcsWKAuLi46ffp0VY04aYg88CxevFidnJx0x44dcV4vXi5qW06dOlWTJk2q2bNnVxcXF+OE8ZdfftHMmTNry5Yt9ccff9Rdu3ZpixYt1NXVVQ8fPmyr0hGDqPvfzz//XD/55BPNmjWrJkqUSHv16qX379/Xhw8favv27dVisehnn32m/fv315IlS6qnpye9Bu3Irl27dNSoUTpy5Ejdt2+fcWH97NkzvX79urZu3VpHjhypqv87wa9Tp45WrVqV46Wditoud+/etdretm3bppkzZ9avv/7a6jP37t3TwYMHG49+wb5EbdMGDRpoyZIlNX369PrVV18ZYwieOXNGy5Urp/Xq1TMGiIf9ihqYBAUFadu2bY0eZ3/99Zd6eXlZ3SBWVd2/f79mzJjRarIHVa5d7MXvv/+uyZMn13r16mnLli3Vw8NDPTw89Ndff1XViIC0ZMmS2qRJkxg/P2LECE2WLJlevXo1Dqt+NxGaxZHIE/4tW7Zo4cKFtUOHDsbd8ePHj2v27Nk1Z86cWq1aNe3Vq5eWK1dOs2fPrrly5dJGjRrZsnSo9cFhwIABmjp1avX19VWLxaI9evSI1lOsWbNm2qdPH2N5p06dNH369Orm5sZdVTsU9YL8woULumbNGt2zZ48GBASoquqtW7d0yJAh6uzsbPWIdeTJ/smTJ+O2YLy28+fPa+HChXXjxo16+PBh7dKliyZJksSYxWvJkiVav359/eCDD7RkyZJatmzZaI8nwH506tRJ3dzcdO/evbpnzx795JNP1N3dXceOHWuEL5MnT9batWtrkyZNtG/fvjauGFFNmzZNkyZNqo0aNdKKFSuqo6OjfvHFF3rp0iVVjbghUaJECZ09e7bxmWfPnmn16tWtxqiD/Yh6/Pz66681X758miNHDh05cqTevHlTAwMDtUOHDlq4cGFdtGiRPn/+XP39/bVz586aPXt2vXz5sg2rx6vcuXPHGHt39+7dOnXqVPX29ta2bdsaE5n98ssvWrJkSW3WrBk97t8hjx49UovFovXr11c/Pz99/vy5jhgxQosVK2b06n3x4oXOmDFD8+TJw3ZqJyL3t+Hh4frixQv9+OOPtVWrVlbr+Pr6aqlSpfTmzZsaFham8+bN00yZMunAgQOjfd+tW7folPOaCM3iSNSTirlz52rBggW1f//+xt24jRs3Gv+gIwe8ffr0KV2b7Uzt2rU1Xbp0euDAAVVV/f7779VisVhdZAcFBWnGjBl18ODBqqp6//59rV27th49elSDgoJsUjdez4IFCzRDhgyaJ08ezZs3rxYrVszYBq9cuaIdOnRQFxcXXb9+vX7++efq7u5uzCIE+9OgQQOtW7euduvWzWp5w4YNNWPGjHr69Glj2cWLF3l8z86FhISoj49PtMdpO3XqpDlz5tT58+fbqDK8joMHD2quXLmMwFpVddy4cWqxWPSTTz4xHofu06ePJkmSRH/44QfdunWrNm7cWHPmzMmdcDsU9YbiqlWr1M3NTb/++msdPHiwurq66qeffqp3797Vq1evardu3TRRokSaNWtW9fT0VE9PTx6Bt2MvXrzQIUOGaN26dY1lX331lTo6OqqXl5d269bNuDE8e/ZszZcvnzE8CeyLuVdYZLudOnVKEyZMqF27dtXQ0FD19/fXL774Qj/88EPNlSuXli5dWpMmTarr1q2zRdl4hadPn2poaKgWLFhQJ0yYoKpqTO7g7++vLi4uOnbsWFWNeJR6/vz50W4I83jtv0No9ha9quvqsGHD1MfHRydMmGCMjzRp0iR1d3fXcePGGT1cYB9CQ0O1du3a6uzsbLX88uXLWrp0af3xxx91z549xkV35IVAzZo1NW3atFq9enXjM4y/Yp/mzp2rrq6uxkDE+/btU4vFojVq1DDWuXTpkrZs2VLd3Ny0YMGCevbsWVuVi9cwYcIEtVgs+vHHH1udHISFhamPj4+WLFnSGOMM9iXq3VTViDbz9/dXb29vY+yNyEA7NDRU3dzctGjRolYTAHBCaF9Wrlyp3t7eGhQUpI8fP1bViGEr0qVLpwULFtRx48ZpWFiY/vXXX9qiRQtNkiSJ5s+fX2vWrGmszyNB9umbb77RLl26WAXXixYtUg8PDx08eLDRw/6PP/7Q1atX66pVq2xVKl4ipv3l0aNHjd717dq106xZs+qOHTu0e/fu6urqqhMnTjTWJQC1T+YxBM3ByQ8//KAWi0W/+uorVY04rp48eVLHjRunX331lV64cEFVXz6pEt6+0NBQ7datmzGTe8eOHfWXX35RVdUyZcpYPZEWmSm0b99eq1WrFq3zDdegsUdo9pZE/Ue5Y8cOnT9/vq5Zs8aqJ0PHjh21RIkSOnfuXGNZ27Zt1dvb2+j2DPvg5+enXbp00ZQpU+qhQ4dUNaJrc6FChTRdunSaO3duTZs2rZYpU8bYqX377bfap08f/fLLL43v4YTffkR9pPb+/fvas2dPXbhwoapGhKE5cuTQ0qVLa4oUKbRNmzZWnz137hyTN9iRV21XvXv3VmdnZ2O7jTzp8/f310SJEmn9+vWtJuWA7UU9fppn6KpXr556e3sb219k21epUkVTp06trVq1Mnprw74sX75cnZycjAGmVSMmb2jUqJHWq1dP8+XLZ4RjqhGPykc+tqnKhDn26sqVK+rs7KwWiyXa7O4jR47U3Llz6/Tp0xmawk6Fh4e/dNuKXL527VotXLiw/v7776oaMa5vihQp1N3dXVeuXBlnteLfiXosbdeunXp6emr27Nm1cuXKev36deP4OXr0aP3ggw901apVVvvnmL4HcW/37t1arFgxrVy5subMmVO9vb2Ngf1XrVqlmTNnjjaQf8OGDbVHjx62KDfeIjR7y/r3768pUqTQChUqaNq0abVZs2a6a9cuVY2YBKBu3bpauXJl/fHHH43P+Pv726havMrly5e1adOm6ubmpr/++qvmypVLa9WqpX///bc+ffpUZ82apenTp39pSMZBx/4EBQUZIef+/fv11q1beuLECc2RI4d2795dnz59avQajLwLB/sSdbvatWuXbtmyRbdv324sCwsL0ypVqqiHh4fxeFdkcHb06FHjUWvYh6h3sr/44gstVqyYNmvWzAi0r127punSpdNmzZoZj7s/ePBAW7RooYsWLTK2Z9jGq3oi3LlzR0uVKqU5cuTQb7/9Vnv16qUWi0W3bdumz58/10SJEun69etj/CzHT/tgvkER2d67du3StGnTart27fTGjRtW63zyySeaK1cuY2Ik2Id58+bpxo0brZb17NlTu3btqv369dNbt24Z293o0aM1T548+ujRI1WNmB2+RYsWOnv2bHof2ZHI7TNqCPr06VOtWLGiFilSRLdt26aXLl3SDBkyaIMGDawG92/ZsqW6urrqrl27aFM7EbUdxo8frxaLRT08PKzWuX37tg4cOFBTpkypX331lW7evFlnzJihzs7Ounbt2rguOV4jNHuLhgwZorly5TJmyly6dKmmSJFCa9SooSdOnFBV1bNnz2rZsmW1TJkyVuPrwD4dO3ZMK1WqZEwAoPq/g1NAQICmS5dOBw0aFO1zHIDsT3h4uDZr1kx9fHyslo8ZM0br1atnTK0+bdo0dXV1VYvFYswYBdsLCwuz2q569Oih6dOn1/z582uSJEm0Z8+expiRDx48UE9PT61SpYrx6DvbpP2JekE+YsQIY7iCqlWrqqenp3777beqGnGBnixZMi1YsKDWqFFD3dzctFq1arYqG/8v6ja1fv36GCdIOX/+vNauXVtLliyp3t7exk3Eu3fvaqZMmaxuIMK+RA0ur127pteuXbN6f8aMGZopUyadPHmy1RAjISEh2rhxY+O8F7YXEhKiLVq0UEdHR7148aKqqubLl0/z5cunTZs21QwZMqiPj49+//33qhrx5ETRokV1yJAhunLlSk2XLl2Ms8HD9vbv36+dOnUyeukuXbpU69WrZ/RMWrx4sSZOnFgTJkyojRs3thqXt0SJEurt7c2jtnYg6v722bNnOnnyZK1fv77my5dPhw8fbrXuzZs39auvvtK0adOqp6en5syZk2PpW0Bo9h+Zx12J9Pz5c+3bt69xUNm4caOmTp1aq1WrpoUKFdJmzZoZPco2btxIL5Z3yPbt29Xb21sbNGhgtfyvv/5SHx8fXbx4sY0qw6vEdId83bp1Wq5cOau7rbVq1dKKFSsar7t166bfffcdA/7bicjp0aPq2rWr5syZU48dO6aqqvPnz1eLxaLDhg0zws9z586pi4uLNmzYkF4rdiwgIECHDx+uvXr10sOHD6tqxAV63759NWPGjLplyxZVjbjhNGHCBO3atauOGzfOliXDZNiwYWqxWLRAgQIvnVwjKCjIap98/PhxLVCgQIzbN2wvalsNHDhQc+fOrenSpdO6desa26RqRE+lHDly6JIlS6zG0mFoCvvj5+enNWvW1Jw5c+qBAwe0bdu2Rps9ffpUq1evrpUqVdLjx49rQECAduzYUfPmzatZs2a1eqIC9uOvv/7SdOnSafLkybV79+4aGBiof/75p7GNDhs2TNOlS6c7duzQvXv3qoODgzHLrWrEteuHH36ovXv3tuWv8d6Leo46c+ZMXbRokV67dk2fPHmiw4YNUw8PD2Nop6j71nv37unt27f13r17qso4dG8aodkbcOTIEd28ebOqqh46dEgnT56sqhGDYj558kS3b9+umTNnNmb86tq1q7q4uGjHjh0ZS8cOvWwHE7k8JCREV69erenSpTMOLFeuXNHcuXNrjRo1ODm0c7Nnz9Zff/1VVSNOGitWrKj9+/c33l+zZo06Ojpq7dq11dfXV7NmzapXrlyxUbWI6qefflJPT0+rcSCvXLmi3bp10z179qhqxPgOqVKl0sqVK6vFYtGZM2caY+n8/PPPOmDAAJvUjn8WHh6u3377raZLl04zZsxo1Vvl3Llz2qpVK82RIwcTcNixNWvWqI+Pj06fPl1z5syptWrVMh7pUo1+fH3w4IFeuHBBfXx8tFatWpwT2bk2bdpotmzZdN26dXru3DktXry4li9f3qpXQ+PGjdXb21t/+OEH2xWK13LhwgXNnz+/fvDBB1q3bl0NDQ01zmEvXryo2bNn1379+qmqamBgoAYEBHAD0Y4FBQWpl5eXuru7a506dXTEiBHGe8eOHdP8+fPrzz//rKqqf/75p3744YdqsVh04cKFxr63d+/e2qhRI/bFdqBBgwaaMWNGnTlzpjG8yJUrV7RLly6aJ08e3blzp6pGXMv88MMPxpAVqtyoeBsIzf6j58+fa5EiRbR8+fI6cuRItVgs2rdvX6t1Pv30U23VqpWRHI8aNUo9PDy0atWqxqwksA+RJ/TPnj0z2iumEC04OFi//vprTZUqlXbp0kVdXV21ZcuWxvvsrOxT5IyYKVOm1EWLFunDhw9106ZN6ujoaJwIBgQE6MqVK7V58+baqVMnq4MQbOv8+fParFkzLV++vHHnNCQkRHfu3KlhYWH6/fffa+bMmfXrr79WVdVGjRqpm5ubrl69mhNAOxRTj7+bN2/q0KFDNWHChMY4ZpEOHTqktWrV0uzZszOouJ3asGGDjhs3ToOCgvTkyZPq7Oys3bp1i7Gtnz17pjNnztT8+fNr/fr1jeXcGbe9mNpg586dWr58eWMokf3792uSJEk0S5YsWrNmTd23b5+qqj558kQ9PT2jTQoA2zNvh+Hh4XrgwAH19PTUMmXKGD1TItcbNmyYurm56bNnz9gu7Yz5OiOyl+DChQu1bNmy2qpVKy1ZsqQxQPyqVas0S5Ysxozhhw4d0lGjRumcOXOMG1S3bt1Sb29vq1lREbcit7PBgwdr/vz59caNG9G2vaNHj2rz5s01Y8aM+tVXX2nSpEm1e/fuNqj2/UJo9i/FdNC4f/++pkuXTi0WS7RB4MPCwrRp06Zap04d4+K7efPmOnv2bKP7JGwv6sHnxo0b+vHHH1vNRBJTu9+9e1f79OmjFotFx44dayzn0S/7EVN4Wa9ePU2RIoV26tRJmzdvrkeOHNG2bdtaTdmsykxt9iCm9osMTqpVq2Y8jhm5zX388cfas2dPY9/bqlUr/eCDD9TDw4MZFe1M1P3knj17dP/+/UZw7efnp+3bt9c8efLo7t27rT63bt06bdSoERPm2Klnz55ZBZpr167VBAkS6LRp02JcP+qjQ6rsd23pn0KRGzduGE9VfPfdd5oyZUqdP3++7t27VxMnTqytW7c2Hq9lf2t/ou5zb926ZbRRaGiorl27VhMmTKijR4+2+sygQYO0Ro0aBGZ2JvLcKDg42Oh8EdlGmzdv1gYNGujJkye1devWWrp0ad26dateuXJFHRwctGvXrvr1119r5syZrZ6yUI14LDdypnHYVu3atbVPnz6q+r/2jroNHz9+XLt27apFixblcek4Qmj2L5ifG45M9Q8dOqS5cuVSV1dXHTBggNGFMtLkyZO1QIECWqhQIc2dO7cWKlQoxil9YRtR23XXrl06depUTZUqlZYuXVp/+eWXV3728uXL+ueff8b4XbAPly9f1rFjxxoBy+7du41QdMyYMZoiRQpt0qSJ+vr6GnfKYXtRTw5+/vlnXbZsmTGQ9M6dO7Vs2bL68ccf6+3bt1U1YgahrFmz6oQJE1Q14uSvZcuWeuHCBWMd2IeoF2ANGjTQbNmyae7cuTVLlixWvZQaNmyoRYoU0cuXLxvrmyeAgP376quv1NHRUdetW6eqEcHa/v37rca8UuWGky1F3aY2bNigI0eO1EqVKmnHjh116dKlVutdv35dixUrpvPmzTOW58mTR11dXbVfv370SrJjgYGBWrJkSS1YsKB6enoa5zzh4eE6efJktVgsOnz4cP3xxx918+bNmipVqhgnt4LtnTlzRjNlyqSZM2fWVatWqZ+fn/Geh4eHTp482Ri3rkqVKnrmzBlds2aN5sqVS/PkyaMDBw60+j62WduI6e89NDRU3d3djQH/o15bPn/+3CpnePjwofH/HEPfLkKz1xT5D/bGjRtavXp19fX11RIlSujvv/9urLNs2TLNmDGjjh8/3mra+/DwcF2+fLn269cv2owXsB8jR47UxIkT69ChQ7VNmzaaLFkyrVmzph48ePC1Ps8Bxz5t2bJFM2XKpLVr19b169frkydPtHXr1jp//nxVVf366681V65carFYdOTIkbSjHYg88D9//lzLly+vWbNm1eTJk6uzs7Mx6PvixYu1RIkS2qVLF+PRy65du2rChAm1WbNmmj17di1ZsiQnEXYqNDRUW7RoocWKFTNm+WrYsKGmSZNG9+7dq6qqW7du1SpVqmiFChWsxsXCu+eTTz7R1KlT67Zt27RGjRparlw5q/Mk2E7UfWSXLl3U09NTGzVqpHXr1tWCBQuqxWLRPn36GDcfjh49qlmyZNFNmzapquqlS5e0TZs2OnbsWL1x44ZNfgfELOpkZaGhodq4cWNt3Lixrl69Wj/66CNNkSKFbt26VVUjwuzevXurxWJRLy8v7dKli44aNcqW5eMVVq5cqWnTptVMmTJpnjx5tE2bNjp79mxVVV2+fLk2adJEX7x4oTt27NCyZctqs2bN1M/PT8PDw616anOOZDuv+rvv0aOH5s2bV0+dOqWq/8shDh06pOPHj4/2tBrXLm8fodm/sH37dk2WLJm2bNlSFy9erN7e3urj42P1D3XgwIHq7u6uCxcuNHqTHT161FYl4zVduHDBGPso0pYtW7RAgQLapk0bYyB4dkr27WUHoP3792uPHj00adKkumrVKh02bJgWLFjQeP+XX37Rjh07Ggcn2N7ly5c1U6ZMWrduXb148aLeunVLGzdurGnSpNEDBw6oquro0aO1WLFiOnToUONzAwcO1M6dO0e7iwr78uTJE/X19TUm5Zg+fbo6OzvrjBkzrNZbsmSJ5s2bV7dv326DKvEy5n3t6/Sy9vX1VYvFoh4eHla9ImA7kec0YWFh6uvrqx4eHnrkyBFjjCM/Pz+dOHGiWiwWHTVqlIaGhurJkyc1d+7c2rZtW509e7YWLFhQ27RpQ097OxO1PR4+fKihoaE6bNgwY0wrVdXq1auru7u7MVPxnTt3tHbt2po1a1Z9/PhxXJeMfyE8PFzHjh2rdevW1fbt2+vixYvV2dlZ+/Xrp59++qmWLVvWCLGXL1+uOXLk0H79+lntu7mmsZ2oPa3HjBmjffr00V69ehmPTW/fvl0rVKig1atXV39/fw0ODtZr165pkSJFtHHjxgxlYAOEZq9p3rx5miBBAmOAaVXVkydPas6cOfX27dtW//ibNWumBQoU0HHjxunw4cPVYrHo0aNHOaGwY+fOndOMGTMad9wizZ49W52cnLRPnz5WU/jC/kQ9EViwYIF+8803unLlSmNZ5OQN6dKl0379+mmiRIl0zJgxxvtsn/Yh8i5oqlSp1MfHx+rE/f79++ro6KhTpkxR1YiZonr27KnFihUz7rCqcufU3pj3mWFhYXru3DnNnj27Pnv2THv27Kmurq66YcMGVY14tHbdunX66NEjDQkJiTbkAexDWFiYrlix4rXW3bFjh6ZIkUKbNWtmLOOk3z4EBARoxowZtVixYvrkyRNV/d/xMHLb7dWrlyZJksQIV2bPnq0VKlTQ3Llza7t27WxTOF4q6j531KhRWqxYMc2dO7d6e3sbPXsj5c6dW319fY3H4K9fv86M4e+I58+f66effqqlS5fW3bt36/nz57Vv375auHBhtVgsOn36dGPdpUuXWj3KB9uImhc8e/ZMfX191cvLS1u1aqWFChXS/PnzG0ORrF27Vn19fTVJkiTq7e2tmTJl0nr16tmq9PceodlruHz5snp4eGiBAgWslo8aNUqzZMmiZcqU0WbNmhkzfb148UJbtGihpUuX1rx587724314+yJnBjK7dOmSpkyZUr/77jtVtd6p5ciRQ/PmzauTJk3iJN9ORbZpaGioli1bVr28vIyDT8OGDa3WXbVqlbZo0UItFovmzp2bC3I71bVrV82bN68uXbrUeDTvzp07milTJl24cKFxUXf16lVt166d5s2b1whdYHuRwWXUWUvN+89ixYppsmTJ1MvLS8+dO2csP3TokFavXp0Bie3cvHnzNGPGjHrt2rVXrufn56dVq1bVjh07Gss4ltqPoKAgzZ8/v/r6+loN4B/1XOnGjRvq5uamTZs2NZY9efJEb926Fae14tWiznypqjp//nx1c3PT8ePHa5MmTdTR0VEnTZpkNVnHnTt3NEWKFFqlShVClXdQYGCgNmjQQMuXL288LXHixAkdOnRojDcQualoO7/++qu2atVKb9y4oY8fP9YWLVpotWrVjDZZsGCBWiwWrVixojEx0tOnT3XBggW6ZMkSXbt2rfFdtGPcIzR7DU+fPtXly5drhgwZjMeABg4cqEmSJNFRo0bp+PHjtWzZspoxY0bdsWOH8Rl/f3/jrh3sy+7du3XatGm6detWY1yVgQMHavLkyY2EXzXijlu9evW0bt26WrRoUe6+2bHAwECtVauWVq1a1eidNGjQILVYLNqjRw+rdS9duqRffPEF43XYoagnAvXr19dChQrpvn379MWLF1q2bFn19vY2LrgjL+oOHjyonTt31uvXr9ukZljbsGGDzpo1y+oCvH///tqyZUsdNGiQ7ty5U1UjAuxs2bJpr169VDXiruvff/+tRYsW1caNG1sFbrCtmG427dixQ7NkyRJtzBWzFy9eGBcAka9hX65evaoZMmTQxo0bW523Rm33ypUra+PGjeltb4fmzZtnzKKoGnHjd8aMGdq8eXNds2aNsbxjx46aN29eXb16tdX2unfvXu3QoUOc1ow35++//9bKlStrvXr1os2myVMU9mHOnDlqsVh07NixqhoRVn/55Zd6+vRpVVXt3bu3pkmTRmfPnq0ffvihtmjR4qU3pDiG2gahmUlMj5GoRtyJmzZtmiZPnlzz5s2ruXLl0t27dxvr7d+/X1OkSKETJ06M8XsQ96K2QdQdzIQJEzRZsmSaO3duzZYtmzZq1Mi4CK9Zs6amSZNGp0+frhs2bNBGjRpp8+bN9fbt22qxWHTx4sVx/nvg9Zw5c0Y7deqkN2/eVFXVwYMHa6pUqbRLly7q4OBg9Wg17Fvk9vrkyRMtVqyY+vr6atasWbV69epGIBqbMZUQN5o3b65ubm66Zs0affLkidaqVUtz5sypnTt31rx586qHh4fOmjVLVSN6bCdKlEiLFy+utWrVUjc3N23QoIGNfwOoqhGemGe5jMrX11ebN2/+2t/Jdmq/9u3bp4kSJdIvvvgi2jnsixcvtGDBgtFuQMH29uzZo3Xq1LEaq2z79u2aKVMmTZw4sf70009W61epUkVLlSpl3LxA/HDgwAEtXbq0duzYUYOCglSVa1F70a1bN02SJIn+8MMPVsuvXr2qoaGhOmXKFM2XL5+RK/Tv318dHR21R48exviSsD1Csxj4+fkZg9RGPcHz9/fXwYMHa8KECY2xkiIH+7937556enoaM/LB9p49e6aq1m145MgR/fTTT3Xv3r36+PFjXbRokRYsWNBqnJV27dqpt7e3urm5qa+vr969e1cfPXqkOXLk0M2bN8f57wFr5scPooqczXbo0KHGdOrPnz/XihUrqoODg/74449xWCn+i8g2vnjxonp6emr27Nn12LFjqsqJoL2K2i41atTQ0qVL69y5c7VBgwbGMfXGjRs6ZMgQTZcundEze9++fdq7d28dO3asLlu2zCa1w9q5c+c0S5YsevLkSWPZ4MGDdfHixcbFeXh4uH7zzTdavnx5Zk2MJ5YsWaIWi0Xnzp1rtXz37t1avHhx3bVrl40qQ1QxhZqqqufPnzfeW7p0qbq5uWn79u2tZtq7d++eFi5cWMuXL89EZfHM6tWrNWfOnDpixAhbl4L/N2LECLVYLFa9rVVV586da1yfNmnSRHv06GF04Ojbt69WrlxZixcvblzLwvYIzUx2796tzs7OWr58ed2yZUu0u6IXLlzQ5s2ba8aMGa3GQho1apRmy5ZNjx8/HtclIwZff/21+vr6qur/Ti5Gjx6tadKk0TJlyhh3YUJCQnTBggWaLVs27devn/H5Bw8eWHWLHTt2rLq7u+vZs2fj8LdAVJcuXbIah0M14pGCU6dOWT1OEhwcrBUrVtTZs2dreHi4hoWFaZMmTdTDw0NLlixJt2Y7E7l93rlzJ1r7RrbVr7/+qpkyZdI+ffpwcW7HwsLCjGNmQECAFi5cWNOnT6+VKlWyWu/y5cvapEkTbdCgQbQ2h304ffq0litXTr28vIw2atOmjebPn18LFSqkGzZs0PDwcL106ZImTZpU9+zZo6r0JLNHUdvkdXroDh8+XBMlSqS//PKLqkbcbMyWLZt+/vnnb7dQvJaobbZo0SL9448/VDViLMgCBQrosGHDjPeHDRumPj4+OnHiRKtxBP/44w8tVqwYQxrEM+Hh4bpw4UK9c+eOrUuBRlxjfvfdd+rq6mo18VjTpk01efLkeu7cOX3+/Ll6eXlp27Zt1d/fX0+cOKE+Pj568eJFG1aOmBCamcyfP199fHz066+/1owZM2rPnj1148aNVuscOXJEy5cvr4ULF9bw8HDt0qWLOjs76969e21UNcx27dpldYdcVXXFihVapkwZdXNzs1r+8OFD/fLLL9XNzc3qEb6QkBDdu3ev1qlTR1OlSsUdVhsJCwvTQ4cOad68eXX8+PHG8nLlyqm7u7smTJhQP/vsM2NWL39/f02SJIlOmzZNVVWPHTumFStWJNC2M1FP/NetW6deXl564MCBaHfQI1/PmTNH3dzcdPjw4QxWbIeittvgwYN10aJF+tdff6m7u7vmzJnTaqxI1Ygp1nPkyGEVmtGD0L4cPHhQCxcurOXKlbNa1rdvX2MmzD179mjHjh21cePGBGZ27NSpU8bsiJcuXfrH4Qpatmypbm5uOnnyZE2cOLEx7iBsK2ro+fHHH6vFYjFmjr5796527NhRS5cubUxMpqravn17LVGihC5atMjqu1712DXefeyP7UNgYKBOnjxZnZ2d9dtvv9WyZctqkSJFrGax3bRpk1osFvX09NTEiRNrt27djPdoR/tBaGbi7++vadKk0TNnzujRo0d1wIABmjx5ch0zZozVLJh79uxRLy8vtVgs6ubmRu8HO7V7927jrlt4eLguXrxYs2XLpp07d7Za78aNG/rJJ59o5syZjTs0z58/1wMHDmj37t25G2djN2/e1Dp16mj58uV16dKlOmnSJK1Zs6ZevHhR58yZo8WLF9emTZvqmTNnVFX1iy++UIvFolWqVNHEiRNrz549bfwb4GXu3buntWrV0smTJ8f4ftQg5bPPPtNSpUoRmtmRqL3LVCMC0CxZshiDT2/YsEHTpUun/fv3t9qPLlq0SH18fPTu3btxXjNeLeoA0hs3btSsWbNq69atrdb5+eeftUePHurg4KBZs2bVokWLsl3aqWfPnqm3t7cWLlxYly1bph988IFVb6SYPH36VIsWLRrjo5qwjcjA7M6dO5otWzbNnz+/enh4GLO+q0YMZ9C0aVMtW7asbtmyRVUjjrH169fXcuXKRRtTCcDb5+fnp3369FFHR0fjKahIUSe0WrVqlW7dutV4j8DMvry3oVlM/xAjD0i9e/fWPn36GM8R79mzRxMnTqxZsmTRCRMmGCeGy5cv1+7du8dVyXgN5kcPJkyYoBaLxbjrFhQUpJMmTdLcuXPruHHjrNa9cOFCtGfO6flgezt37lQfHx/97bfftGbNmtqoUSOtVauWbtq0yVhn+fLlWrJkSe3cubM+ePBAVSNmk/riiy/0+++/t1Xp+AcjR45UT09PrVatmt6+fful60XdX0dOBADbmjFjhtUQBWFhYTp27Fht3Lixzpgxw2rdyZMna7p06bR58+a6du1a/fnnn9XV1VU//fTTuC4brxDTo+vBwcG6cOFCTZkypdXjJZE2btyoDRs2VAcHB121alVclIlYePTokSZLlkwTJUqkU6dOfa3P3L59W8+dO/eWK8O/cfDgQU2ePLkxDm+JEiWsbgyrRowRWbNmTa1Ro4bRw/7kyZPq4+PD+RBgI+fPn9dWrVpp5syZ1d/fX1XV6pFpMwIz+/Pehmaqqn/++aeR6EYNR6ZNm6Y+Pj7G6wYNGmiOHDl07Nixmi5dOi1atKh++eWXcV4vXi3qDmb27Nl6+/ZtvX37tvbv319dXFyMWUlu3LihAwcO1Dx58ujy5cujfQ9BmX1ZsGCBli5dWlUjHo0uVaqUOjo6Wk2jrqo6adIkLVq0qA4ZMkRDQkJUlWmZ7Y25Pf744w9Nnz69pkuXziqAiQnbpf04evSofvTRR1YX1Lt27VIfHx9NliyZsV+N+vhP37591WKxaM6cObVx48Y6cuTIOK8bLxd129y5c6ceOnTIOLF//PixjhkzRpMlS6arV6+Otr6fn5926NBB27ZtqyEhIWyrdiJqGx0/flwtFos6OjrqmDFjaKN30Lx589RisRj7zhcvXmjevHl1woQJxutIa9eu1fLly2vLli2NGcVfdWMKwNt39OhRLV26tBYpUsRY9qrgDPblvQ7Npk6dqokSJTJeR87MFhYWpnny5NExY8Zo/vz5tXDhwnr+/HlVjbho79mzZ7SxAWAbixcv1qFDh1otW7NmjWbLls0I0S5fvqxNmzbVjBkzGo8HnT17Vtu1a6eurq564cKFOK8bMYvpzkqvXr20Xr16xuudO3eql5eXNm3a1BijJVL//v01e/bsunjx4rdeK2Ln+vXrumjRIqNH4IYNG9TBwSFaz0/Yt8iZo//8809j2cqVKzVXrlxapUoVDQwMVFU1AmxV1erVq6uvr+8/BqSIW1H3u3Xq1NGUKVNqhgwZNGXKlDpjxgwNCAjQwMBA/eyzzzRFihTGjHtR23bYsGFaqlSpOK8dMYsMUMLDw40B/VVVV61apQkSJLAa8ypqgEbvBvu0f/9+9fT0NGYXjmyzypUr6/Dhw1U1os2jtuWcOXM0Z86cOmDAAKvPAHizzPvNV21rO3bs0Lx581pd1+Dd8F6GZt9++60GBASoqmqzZs10yJAhWqNGDe3YsaMGBQXpixcvtHv37mqxWLRVq1bRZiGJeqII2wkODtbu3burm5ubVY+xmTNnapUqVVT1fzuuY8eOadmyZbVQoULGert376aruh16/vy5/vzzz8bratWqadeuXa3WmTNnjhYsWFAHDBhgNY5OQECATp8+nRN/OzZmzBi1WCy6YsUKI3iZOHGiOjo66rp162xcHf5J1JPBM2fOaM6cObVPnz7GssmTJ2uRIkV04MCBxrLIY2ZwcLAx7iDsS2hoqP7000/q6+urZ8+e1b///lv79++vnp6eOmHCBH3+/LleuXJFGzZsqBkyZIg2Ft2AAQPUx8dHAwICuDi3sci//6tXr6qXl5c2aNBAt2/fbgRpgwYN0sSJExu971UjZkul3exXaGio0WMsqhIlSmjv3r2N1+Y2XLBggd67d++t1we8ryKvN54+fapBQUFW70XdHiP///nz57pixQr94IMPdPPmzXFXKP6z9zI0K1mypDZp0kRVVadMmaLJkyfXatWqGT0fVFWXLVumSZMmNQ5SnEzYp4sXL+qnn36qefLkMU4Ahw0bZkyNHvXxoJ07d2r+/Pm1QoUK0b6HkMV+DB8+XD08PHTt2rWqGnFSOH/+fFVVY5xB1YgTfx8fH50yZQqPYdqpl7VLq1atNHv27Lp161Zj2+vcubOmSpVKjxw5Epcl4h/E1IaRx8M7d+7owIED1cvLyxgs/OnTp9q/f38tVqyYTp8+3fgMjyDYLz8/P82WLZtWq1Yt2qyKPXv2VC8vL2N24n379qm3t7exf1aN6IHv6+urf/zxR5zWjZc7ceKEpk+fXjt06KC3bt2yOnaqqjZq1EjTpUun69at0/Hjx2uqVKn00KFDNqoWrxLT9UfkfrlUqVI6aNAgq2Xnz5/XJk2a6OnTp+OuSOA9E3W73Ldvn5YoUUKLFi2qlStX1h07dhjntjFtv0FBQXr27Nk4qxVvRgJ5j6iqiIiMHj1anJycZNKkSTJ+/HgJDg6WTp06SYoUKWT58uUiItKsWTPx9PSUb775RkRELBaLzerGy+XIkUPatWsnefLkkd69e8vNmzfl1q1bkiZNGhER+eCDD4x1S5YsKX379pVbt27J1atXJTw83HgvQYL3alOwaz169JACBQrIjBkzZNOmTZIgQQJxd3cXEREnJydjvdGjR0vZsmVl4cKFsmDBAluVi1dwcHAQEZEjR45ISEiIsXzRokWSNm1aGTZsmBw5ckRERGbNmiU+Pj5SqVIl8ff3t0m9iM7BwUGCgoJk2rRpsm/fPhH53/EwTZo00rFjRylTpoxMmjRJtm/fLokSJZLPP/9cvL29ZdmyZbJ48WIREXF0dLTZ7wBrkedCkRwcHKRIkSKydetWY9nz589FRGTy5MkSHBws69evFxGR4sWLy44dO6RevXrGuoUKFZLt27dL4cKF46B6vI61a9eKt7e3fPfdd5I+fXoJDg6Wffv2ybZt20REZNWqVeLl5SUDBgyQmTNnyooVK6Ro0aI2rhoxien6I3JZsmTJJDAwUEQituNt27ZJgQIFJFGiROLl5RWndQLvk8htcNWqVVK9enUpWbKkjB07VhInTiyDBg2SlStXGuuZj7nOzs6SO3duERGra1HYN4uaWzIeCwsLEwcHBwkNDZXatWvLnj17ZNGiRfLo0SOZPn26ZM2aVY4ePSp79uyRTJkySbt27eTatWuyZs0aSZUqla3Lx/8LDw+XBAkSGP8VEdm6dat8+eWXYrFY5P79+5ItWzYpVqyYuLq6Ss6cOSV16tTy+PFjKVSokDx58kSSJEli498Cr3L16lX57LPPJDg4WH777TcpUaKEpEyZUlxdXSVz5sySJk0ayZ49u1y5ckWWLVsms2bNkvz589u67PeaqhonEVG3zfnz50uHDh1k48aNUrVqVWP5gwcPJH/+/FKoUCGZOHGieHh4yL1792TMmDEyZcoUm/0esBYaGiodOnSQrVu3StKkSaVDhw5Sv3598fDwMNY5fPiwTJw4US5fvizLli0TDw8POXbsmHzxxRfSqFEjadeunQ1/A0T14sWLGAPMGzduSLNmzeT+/fvyxx9/SJIkSYxtunr16uLh4SFTp061+kzk6SM3FW0r6r438jz3iy++kP3798uoUaNk8+bNcvHiRdm0aZO4uLjIRx99JLNmzRIRkbNnz0rGjBnFxcXFlr8Coojanv+kTJkyUrBgQZk2bZrMmDFDunfvLl9++aX07t37LVcJvJ8i97EiIpcvX5ZOnTpJ/fr1pUuXLiIi4uvrK6dOnZJChQrJwIEDpUqVKrYsF2/QexWaRerWrZssXrxYnjx5Is+fP5dbt25J/vz5xc3NTVavXm30atm4caPcvHlTOnXqZOOKESnqzurZs2eSMGFC4yJ86dKl8u2338rvv/8u9evXlwcPHsj169fl6dOn8vjxY6lVq5bMnz9fRP7dSQls4+DBg9KtWze5ceOGVK9eXRwdHeXq1aty9+5duX//vjx58kTc3d3l+++/Fzc3N1uX+16L3J4ePnwoIhGBWPbs2Y33q1evLpcuXZIVK1ZI4cKFjVDt559/lkaNGknnzp2lV69ekjVrVlv9CniF/v37y/Xr1+WLL76Q7t27i4hIpUqVpGfPnpIoUSIREfnll19k4sSJ4ujoKCtXrhQXFxe5ffu2pE+f3palI4qox8+RI0fK/fv3JUmSJFK7dm35v/buO77G+///+OOcRGIHMWLvmBWjRkNRMzSh9qbUaIs0imhVtYqgqNWKvWsr2khtsXeNqFWxRQSJEImQnOv3h1/ON1Fa/bSchOf9H3KNc3u9b+eWK9f1ul7v19vd3Z3ff/+dRo0aUa5cOWbMmEGWLFm4efMm1atXZ9CgQfTt29fGI5AnJf1Ok1q1ahXTp09n586d1K5dG09PT6pXr8769ev58ccf2bx5M7ly5bJBxPJXkn6fSV8+Peu4Nm3aULJkSe7evcvUqVNZvXo1jRs3fpkhi7wWLBYLMTExZMyYEYDo6GgyZszIsmXLaNiwIZGRkXh4eFC2bFkGDBhAy5YtqVixIkOHDqVy5co2jl7+E7aYE2pL+/fvN1xdXY0zZ84YH3zwgdGqVSsjf/78Rs6cOY2uXbsahvG4L4B6XKU8id9JWFiY0b59e6NOnTpGr169rE3j79+/b0ycONGoXLmyMWLECOt5sbGxxrlz52wSs/w7y5YtM2rWrPmnFVIfPHhgxMXFJetZJy9f0l4NK1euNNzd3Y0SJUoY9vb2Ro0aNYxx48ZZ95cqVcqoXr16stVqFy9ebBQvXtxInz69ERwc/FJjl7+X+P1evHjRyJcvn3Hq1CkjLCzMWLFihVGmTBmjadOm1n6DhmEYa9asMQoVKmT07Nkz2fmScsTExBiVK1c2ypUrZ3z++eeGp6enUbJkSWPu3LmGYRjGpk2bjKxZsxo5cuQw2rdvb5QuXdpo2bKlbYOWp0q8JwoPDzc++ugj46OPPjIGDhxo3R8aGmpd6TSx39WwYcOM5s2bq8dgCpS0f+TYsWON77//3rh3795fntO2bVvDZDIZ+fPnN/74448XHaLIa8disRhRUVFG2bJljVWrVhmhoaFG4cKFjUGDBhmG8XiBI4vFYnTq1Mno2rWrdaHB1q1bG9myZTNat279pwUFJXV67Ro5ValShaNHj+Lq6kquXLlYs2YNXbp0Ye/evaxZs4bVq1djZ2enHlcpkNls5tChQ7zxxhsYhkGDBg0wm818+OGH7Nixg/Tp09OmTRsaN27M4sWLmTx5MgBp06a1Vg8mJCTYcgjyD7Vu3RpPT0/Wr1+fbGqQnZ0dDg4OyXrWycuXWK05ZswYOnbsSOvWrRk9ejTLly/Hzs6OgQMHMnjwYAC2bt3KiRMnGDZsGPv27cMwDPbs2cO4ceM4e/YsZcuWteVQ5CkSe3FkzZqVd955h6CgIHLlykXLli1p1qwZAQEB9O3bl3bt2rFlyxaaNm3Kd999xzfffGM9X2zHSDKRwGKxYBgG48aNI1u2bBw6dAg/Pz+qVq3KpUuXrFM2a9euzeTJk7l//z758uUjMDCQFStWAPr7mdKYzWYOHjzIG2+8wdWrV7FYLNZp8Ldv3yZ37txUqFABwzC4ffs2EyZMYPz48bz33nvqMZgCJVaYNW3alKlTpxIfH8/9+/f/8pxcuXLRvHlzzp8/T7FixV5GmCKvFZPJRObMmXF3d6dnz564urpSrVo1Ro8eDTzuKxgbG8vp06cpVqwYTk5OWCwW6zNp+/btrX22JZWzZcbOlr755hsjY8aMRvbs2Y0FCxYYhmEYgwcPNj7++GMbRybPcuXKFaNhw4bJqo5at25t2NnZGblz57a+ZTt79qzRuXNno3LlytaMv6Rejx49Mvr162e4ubkZixYtsnU48oSgoCCjZMmSxoYNG5JtDwkJMfr27WuYTCZj4cKFhmEYxp49e4wiRYoYBQoUMIoVK2YUKFDAuHr1qi3Cln/I19fXqFq1qmEYhvH5558bjo6OxuLFi43ffvvNqF+/vpE2bVprtZLYzt9V93Xo0MEYPny4YRiG8fHHHxvOzs7G6tWrDcMwjLi4OOPevXtGQkKC8dVXXxn29vbGrl27rPskZTl37pxRvXp14/PPP7duS6w86tChg3H//n3DMAxj4cKFRosWLYyCBQsaAQEBtgpX/kZCQoLRvXt3o2LFikZERMRfHpv4e/53lWgi8u8kVoBu3brVMJlMRs6cOY1Tp04lOyY8PNyoXr260aVLF2PlypWGr6+vUbZsWSM0NNQWIcsL8lr2NAPo3bs3PXr0IDg4GB8fH86fP4+jo6O1P4vYnvFE37H4+HhGjBhBt27dyJ49O02bNuXmzZt89dVXjBgxAjs7O3bt2oWDgwPBwcHkzp2b7Nmz23AE8l+5d+8eH374Id7e3lStWtXW4UgSEydOZOHChQQFBZE+ffpk/XXOnj3LJ598wunTp9m7dy8uLi4EBwcTEhLCtWvX+PDDD5/aj0dSjsTr8M2bN2nYsCF37twhOjqaxYsXU69ePQBu3LjB2bNnefvtt20c7estaQ+k6dOnc+bMGZydnfH09MTNzY2YmBg6d+5M1apV2bdvH8HBwSxbtowKFSoQFxfHggULyJ49O82aNSMqKgofHx9Wr17NkSNHrNXaknKcOnWKlStX4uvri2EYNGrUiLt37+Lj40OPHj0YPHgwQ4cOJSIigoCAAOrVq0eePHlsHbY8RUJCAmazmQYNGtCmTRu6d+/Ob7/9xpkzZ1ixYgV169alUaNGFClSxNahirwWnuwXefz4cUJCQhg4cCCFChVixowZyX4f16xZw8iRI4mIiMDBwYFly5ZpgbJXzGubNEt8EIiNjaVdu3b069ePWrVq2Tos+f+e1dz2/v37ZMiQgf79+3P8+HF+/PFHcubMSadOnfjxxx+pXLky+/fvtx7/V41UJXV51qpvYlvdu3fn0KFDHD169Kn7/f39GTBgAHv27MHNze3lBifP9ORLiaTXyqf9rkVGRtKhQweuXbvGunXryJcv30uNV/5a0u/Pw8OD8+fPU7x4cYKDg3F2duann36icOHCzJs3j27dulGhQgW2bNlClixZgMerKPbs2ZNu3bpZVzu9du0anp6edO3aFW9vb1sN7bX1PPcvly5domDBgnTo0IHIyEjmzZtHzpw5qVmzJrt27WLChAnWxTskZdq2bRshISF0796dN998Ezs7O0qUKMHVq1cxmUzY2dlx5coVunbtysCBAwFNfRd5kZLeA12+fBlHR0frwikhISGUK1eONm3aMGbMmGRTLx8+fMiFCxcoVKgQjo6Oz3yWldTptc0mJP7BcXR0ZPr06UqYpSAWiwU7OzsiIyMZNmwY/fv3Z8GCBVy+fJkMGTIQGRlJUFAQDRs2JGfOnABkz54dX19fmjdvnuyzlDB7dShhljJlyZKFW7duERwcnGy7xWIBoFmzZsTGxnLr1i1bhCfPkPg38MiRI9y7dw+z2cy6deuAp/+uZc2aFU9PT65cuYKTkxOQvGeW2JbZbObWrVu4urqSkJDAjh07WLduHUOGDOH48eMEBAQA0L59e7p168alS5c4ePAgu3fvZsOGDXh4eFCkSBFrwgwgb968BAUFKWFmI2azmevXr7Nz507g/66pSRUsWJCbN29y+vRpunTpQs6cOXn48CEFCxbkvffe4+LFiy85avmnvvvuOxYsWABAQEAAhQsX5s6dO/Tr14+pU6eyceNGChcuzI0bNzCZTEqYibxACQkJ2NvbEx0dTZ06dWjRogVubm54e3tz6NAhihYtyurVq5k3bx4zZswgIiKC4OBg6tWrR0xMDCVKlFDC7BX12mcUzGazlt1OYcxmM8eOHaNkyZIcPnyY8+fPs2rVKho0aMCdO3fImjUr+fLlY926dZw7d44ffviBjRs30qJFCwYNGgToYU7kZWnZsiWhoaEsX76cu3fvWrcn3tjv2bOHkiVLqsosBfrll1+oX78+GzZsoH///nh5eSWr1H1S06ZNKVq0KAsXLgRU7ZCSPHjwAB8fH0JDQxkzZgwuLi4AlCtXDsMwrA3FHRwcmDJlCrVr16Znz560adOG/v3706FDB+uDe9LkTGKCVF6+mJgYvvrqKzp06MCJEycwm81PXYzBbDZz6tQpLl26RFRUFIsWLeLkyZP4+/szYcIEG0Quz5L0dys+Ph6AoUOHcurUKbZu3YqLiwsLFy7k559/xsvLixIlSnD58mVu3LhBoUKFbBS1yKsvPDwceLwgR3h4OFWqVCFjxoyMHz8eb29vzpw5w/vvv8+lS5do0KABU6ZMYcSIEbRq1YqqVatSsWJFa+V24ufIq+W1nZ4pKUvSqUL37t2jXbt2lCxZknHjxgHg5eXFvn372Lx5M25ubqxevZqhQ4cSGRlJXFwc06dPt1aZPTntSERerIEDBzJlyhTGjRtHq1atrC8iYmJiaNu2LenSpWPevHmkTZtWv5spTLt27diwYQN2dnb8+uuvvPnmm8+8hsbGxlKuXDnatm3L8OHDbRCt/JW1a9fi7++Pk5MTS5cu5dy5c9SqVYuoqCiaNGlC4cKFKVWqFJ06dQLgypUr3LlzB0dHR1xdXYFnt0YQ29iyZQuTJk3i3r17rFq1imzZsiX7jhL/P3nyZHx8fHB1deXy5cssXLiQFi1a2Dh6eZonp79fvXqVbt26Ub9+fQYOHGjdv3PnTk6fPs0333xDjRo1WLJkiQ2jFnl1LVu2jEmTJhEQEEC2bNlYt24dgwcPZvPmzdbpl3v37mXo0KE4ODjwyy+/YDab+emnn7h8+TIlS5bEw8MD0DPoq0xJM7G5pDeA0dHRPHr0iIoVKxIQEECpUqVo0KABYWFhLFu2jDJlyvDgwQPSpk1LREQEx48fp3jx4uTNm9daXaaLlcjLFRUVhbe3N4sWLaJatWp4eXkBsHz5cuzt7dmxY4cWWUlBkvZKateuHevWraN8+fJMmjSJChUq/OU5ISEhFC1a9GWGK//AnDlzmDt3Lo6Ojuzfvx9fX18aNWqExWJhxowZrF+/nmLFilGmTBm+//77ZH8vdbOfciT9LlavXs24cePIly8fy5YtA56e3AwODubs2bNUrFhRCzekUOHh4XTr1o0yZcowfPhwHBwcAOjbty/btm3jxIkTAMTFxbFixQp++OEHWrZsSf/+/W0ZtsgrzdfXl4iICGbNmgU8vnft3bs3v/32G/nz5wceX5Nnz56Nv78/y5cvf+p9kP6Gvtpe++mZYluGYVhv/Dp06IC/vz83b97E1dWVP/74gzJlymBvb8/WrVspU6YMN2/eZOzYsRw/fpxs2bJRu3Zt8ubNi8ViUa8HERtxcnJi/vz5+Pn54eTkhL+/P3v37sXDw4MDBw4oYZZCGIaBYRiYzWauXbvG7du3mThxIkeOHOHWrVt8++23/P777089NzHJptXbUrZu3brh5eVFSEgItWrV4ssvv+TNN9+kSpUqzJo1i/3791OmTBkuXLiQbDo16IVTSmIymawvAps0aUK3bt04c+aMNXliZ2dn3X/06FE6dOhAlixZaNGihRJmKVhMTAx16tRh5syZtG7dmqlTpwKPq7UfPnxonSLt6OhIu3btWLFihRJmIi9I4jX02LFj1h7ZAM7OzmTLlo39+/fz8OFD4PE1uXz58hw7doyIiIinfp7+hr7alDQTm0nMyBuGwZw5c/j9999p164drq6uxMXF0bx5c2rUqEFgYKD1YrZt2za2bdtmvYglUsN/EdsbNGgQgYGBnDp1ihUrVuDn52frkOT/S7zemkwmVq5cSZ06dRg1ahRms5miRYvi7+/Prl27mDlzJlevXrWeFxMTk+xzdFOY8vXp04cWLVpw+/Ztpk2bZt3+6NEj8ubNy3fffUdgYCBOTk7q/5mCJd4f2dnZ0apVK9q2bUtgYCCTJk2y7g8ICKBmzZo8evTIWhEhKVehQoX49NNP2b17N/ny5WPkyJG0a9eOEydO4Obmxvnz54H/qyTUKsUi/727d++yb98+TCYTDx8+tK5CnKhu3bq4uroyatQo9u7da90eGhpKuXLlcHZ2tkXYYmOanik2YxgGN27coGXLlhQsWBAPDw9rr5XEC1Pjxo356KOPyJUrF5s2bcLX15evv/6afv362Th6EfkrKlNPmSZOnMjgwYOZMGECHh4eyW4UZ8+ezTfffEOnTp1o164dgwcPJjo6mi1bttgwYvlfXL16laFDh/LHH3/g6+trnTKdVNJpumJ7z7pmJm6/du0aEydO5JdffmHUqFFER0fTtWtXfH199YIiFUn8vXvw4AGnT5+mZ8+euLi48Ouvv5IlSxYuX75MunTpbB2myCspNjaWjz76iJMnTzJz5kzc3NwoUqQIixcvplq1atYWQHFxcbi7u2NnZ4ezszMVKlRg8uTJ9O/fn2HDhtl6GGIDf15XXuQ/lvRG8P79+9jZ2Vkbgjs5OWGxWFiyZAnvvPMO8PiGIk+ePKxatYpevXqxfv168uTJw507d/D396d9+/Z/+lwRSVn0u5nyXL16leXLlzN//nxatWrFgwcPiI2N5ejRo1SqVIkPPviA8PBwFi9ezIIFC8iTJw+//vqrrcOW/0G+fPnw9vZm5MiR+Pn5kStXLqpUqZLsGCXMbC9p4tJisSTrU5a4L/FamjdvXrp160ZkZCRt2rQhPj6eefPm0blzZ5vELk+X9Dt92n1q4j5HR0fKly/PmjVr2LFjBydPnsTV1VUJM5EXKF26dDRt2pTQ0FD8/Pzo1asXGTNmJFu2bADWdiKOjo4EBgYSEBBAQEAAFy5cYMaMGXoGfY2p0kxeqKQ3D8OHD2fXrl3cvn0bHx8fOnbsCDyuKqtTpw758+dn5cqV1ikjJpOJsLAwrl+/jsViwcXFRQ3/RUT+R+Hh4VSuXBlfX18aN27MtGnT2L17N8eOHaN48eJs376dTJkyERwcTEREBLVq1bJ1yPIvBQQEMHfuXPz8/ChRooStw5Ekkt4fzZs3jwMHDpAuXTrKly9vrbp/mqCgIBYsWIC3tzfly5d/SdHK30l6b3r37l3s7e1JSEggU6ZMz6zqfPKlcoYMGV5qzCKvqzlz5rB48WJiY2PZu3cvXl5eODs7kyNHDvLmzUvu3LnJmzcvd+7coX79+gCkSZMGUJX260pJM3lhkl5U6tevz6VLl+jSpQvnzp1j/vz5/Pbbb9YbvsOHD1OrVi169erF2LFjn3kx0oVKROSvPevFQkREBCNHjmTp0qXcuXOH1q1bU65cOZo2bUq5cuUYMmQIn332mS1ClhcoNjaWdOnS6c14CtW9e3d++eUXOnXqxP3791myZAn9+vXjq6++SnZc0u8vPj4ee3tNFkkpkn43GzZs4KuvvrLer06dOpWKFSv+o88QkRdvzJgxzJ07l4iICFq0aMHly5e5desWUVFR3L59m4cPH1pfKCqhLfqLKy+M2Wzm1q1buLu7U6BAAfbt20e2bNm4f/8+R48e5ebNm9abikqVKjFnzhzatWtHsWLF+Oijj575mSIi8nRJXyzs2LGDHTt28ODBA7p160aRIkUYPnw4zZs3J3369JQsWdKaTHnrrbeeuoS6pH5KmKVcmzZt4rfffmPLli2ULVuW7du3M2vWLMLCwv70kjDp96eEWcqS+N3MnDmTTz/9lMGDB/PGG2+wevVqPD09Wbt2LZUrV36uzxCRl6Nv376Eh4dz4MABqlevjr+/v3XfvXv3iI2NTbaqprzelIGQF+bBgwf4+PgQGhrKt99+a50vHhkZSWhoKHPnzqVOnTosXryYyMhIWrduzahRo+jduzdr1661cfQiIqlP4kP2hAkTaNKkCfv27WPjxo3Url2b5cuXYzKZqF69OhUqVMAwDMLCwujatSsXLlz424c6Sb30QJ4yHT58GCcnJ8qWLcvs2bPx9PRk2LBh+Pv7YzabuXfvHoBWOU0FTp48yZo1a5g2bRqff/451apVIzg4mFu3btG+fXtCQkJsHaKIJJE+fXp8fHwoXrw406ZNY82aNdZ9GTJkIEeOHMDj1WxFlDSTFyZt2rS0atWKGjVqMGbMGAzD4MyZM1SuXJly5cpRqVIl7Ozs6NWrF0uWLMEwDHx9ffnggw9sHbqISKo1b948pkyZwooVKwgICGDPnj3cuHGDsWPHsnHjRgDu3LnDrFmzaNasGcHBwezdu5dChQrZNnCRV5TFYnnq9oIFC1K8eHE+/fRTBgwYwLRp0xg8eDAAa9euZdKkSSQkJCjpmQI9mch0dnbGy8uLtm3bEhwcTNWqVSlWrBinTp3CYrEwYMAAbt68aaNoReRp8ufPj7e3N7lz52bMmDEcOHAAINkiLEkXaJHXl3qayQs3Z84c5s6di6OjI/v372fAgAEMHjzY2lDxjTfeIE+ePAQGBurCJCLyL8THx7Ny5Uqio6Pp3r07u3fvpm3bttSsWZOzZ8+SkJDA1KlTqVatGoGBgVy6dOmZ0+FF5H8XHh5Ozpw5SUhIsN7bHDt2jMyZM5M9e3YyZcrEr7/+SocOHbCzs2Pp0qXUrVsXgLt37/Lhhx+SO3duhg8fTvr06W05FEnCMAwMw8BsNvPo0SPrvSw8/t4yZ85MixYtyJo1K/7+/tjZ2dG4cWM2btxIy5YtWbJkie51RVIYLZojf0dNEeSF69atG7du3cLf359atWpZm9vGxMSQPn16KlasSExMjKYfiIj8S/b29ri7u+Pk5MTJkyfp1asXnTt3ZuTIkRw5coS33nqLcePG8dVXX9G4cWNbhyvySgoPD6dYsWL069ePYcOGAfDxxx+zbNkysmbNSrZs2di8eTONGjXCx8eHb7/9luDgYNKlS4ednR2DBg0iKiqKyZMnK2GWwphMJkwmEzt37mTq1Klky5YNDw8PvLy8yJw5M5cvX+bo0aOMHj2aNGnSYBgGRYsWZdasWdbvV0RSFk9PT+rWraseoPJMmp4pL0WfPn1o0aIFt2/fZtq0acDjueTHjx9n586d1KhRQ41tRUSe0++///7MfQUKFMDJyYmDBw+SIUMGevfuDcDFixdxdXVl//79xMXFvaxQRV4bidMwM2XKxIgRIxgzZgyrV69m586d7Nu3j19++QU/Pz8sFgs1atQgJiaGoUOH0rVrV5YsWUK9evXo06cPWbNm5ciRI2TPnt3GI5JESafYbt26lfr165MhQwa2b9+On58fo0ePBh5ff9OmTcvs2bPZuHEj3bt3Z8uWLXh5edGuXTtbhS8if0MJM/krylLIS5HYbDEiIoJFixbh6uqKg4MDHh4efPDBB3zyySe2DlFEJFU4efIkb7zxBpMnT6ZPnz7PvMn7448/iIuLIzIykpw5c7J+/Xp8fHxo0qSJHsZF/mOJU/aOHDnCnDlz6NOnDxcuXKBjx4506dKFXr164e7uDkClSpVo2LAhrVq1Yt26dUyZMoVbt24RGhpK2rRpcXV1tfFo5EmJi6ysW7eOffv2MWXKFHr06EF4eDhjx45l+fLlODs706NHD+bNm0fLli3p168fdnZ2bNy40dpUXERSLiXM5FnU00xeqqNHj+Ln58fevXu5du0a3333HT4+PgDJ+n6IiMjTxcXFMWrUKMaMGcO6deuoU6cOFovF+lCXmES7cuUKlSpVIkuWLMTHx2Mymdi9ezcuLi42HoHIqyNp0nrx4sV07NiRYcOG8eWXX3Lr1i369evHjz/+yJw5c3j//fetx+/duxcPDw+6d+/O+PHjbTwKeR4BAQEMGDCAqKgolixZQu3atQE4d+4co0eP5tixY4waNYp69eoRERFBZGQkRYsWtW3QIiLyrylpJi9dYGAgP/zwA4MGDaJmzZoAyR74RETkr927dw8fHx9++uknDh8+TJEiRZJdRxNfQpw5c4Y9e/Zw584d+vXrZ+OoRV4tSX/nJkyYgK+vL0uXLqVFixbWY0JCQujUqRPx8fHWldkSrVixgjZt2jBz5kytHJ6CJCY2n6ziffDgASNGjMDf35++ffvy9ddfW/cdPHiQ8ePHc+HCBaZNm0aFChVsELmIiLwISpqJTTx48IC0adNisVisTVVFROT5hYWF0bFjR65du8aRI0dImzZtsoe82bNnkz17dpo2bWrjSEVePUmr4zt27MjixYupUqUK+/btA0i2suLhw4fx8vKiTp06LFq0KNnnzJkzhwYNGpAvX76XOwD5k6TXz/j4eOzt7bl27Rr29vbY2dmRPXt2wsLCGDp0KMHBwfTv35+WLVtaz//555+ZMGECgwcPpn79+rYahoiI/MdU2iM2kfhwZzablTATEfkfuLi48P3332OxWHjvvfeAx/044uLiGD58OD169OD8+fO2DVLkFWVnZ0dsbCxVqlThyJEjTJs2jevXr1srOtOkSWNtHl+pUiVmzZrFqlWrGD58eLLP6datmxJmKUBcXBweHh7WZv329vbMmjWLqlWrUqtWLdq0aUNwcDAuLi58/PHH5MuXD39/f3bv3m39jCZNmrB06VIlzEREXjFKmonNKFkmIvJsz1MIXrJkSWbPns2BAwfo27cvhmHQo0cP/Pz8CAwM1JRMkRfEMAzKli1L5syZ+f333+nevTuDBg1i7ty5TJ069U/HN2zYkEmTJvHVV18xb968lx+w/CWLxYKXlxdbtmxhwoQJ3L59Gz8/P8aMGcMnn3xC+vTpadCgAZGRkZQvX56ePXuSNm1axo0bx+nTp62fkytXLhuOQkREXgStnikiIpLCPGthlKf1f6xevTrTp0+nc+fOzJs3j6xZsxIcHEyxYsVeVrgirx2TycTRo0fJlCkT8Hh1xdatW3P9+nU+++wzihcvTv369a3T/Ozs7OjUqRNnzpzh0aNHNo5enpQuXTo6dOhAZGQkX3/9NRcuXKBTp0506NABgDp16tC5c2dq1arF8ePHqV+/PuHh4dYXFCVLlrTxCERE5EVRTzMREZEUJGnCbPz48VgsFuzs7Pj000+fec7Dhw+ZOHEiu3fvZuXKldZeSiLy4iXthXX58mW+/vprAgMD2bVrF8WKFbMmzoBk/5eUIenLiGvXrjF69GimTZvGwIED8fPzAx5/x/v376d169ZUqVKFlStXAhAUFGRdRVNERF5NSpqJiIikMHfu3KFWrVo4ODhQoEABTp06RdasWZk1axalSpV66jmxsbGkS5fuJUcqIk86ceIEAwYMIDQ0lIMHD+Lo6KhkWQqU+AhkMpm4fPkyCQkJFC5cmNOnT+Pr68vhw4c5ffq0tZowISGB9evX4+XlRd++fZk0aZItwxcRkZdEPc1ERERSkISEBD755BMKFCjAwYMHWbVqFe3atWPv3r1ERkY+8zwlzERShrJlyzJ06FDMZjPVq1cHUMIsBUhaJ5BYHWgymVi+fDk1atRg2bJl3Lhxg5IlS/LFF1/g4uJCkyZNrOfY2dlRt25dZsyYQaNGjWwxBBERsQFVmomIiKQgsbGx1KlTh3HjxlG9enXef/99Nm7cyKxZs2jcuLF1+ubT+puJiG0lJmPi4+NZvXo1x48f/9OKmWIbERERZMuWLdl02okTJzJ06FDGjh1Lo0aNKFCgAPB4yubGjRvp1asX9erVY/bs2dbPSXq+iIi8+nS3LSIiYiMJCQl/2pYuXToMw+DEiRM0adKEQ4cOsXHjRho3bkxUVBSDBg0iNDRUCTORFCgxmWJvb0/z5s2VMEshdu7cSYkSJbh165Z1W2RkJKtXr2bMmDH06tWLnDlzEhsby969e7l58yYeHh6MHDmS1atX89lnn1nPU8JMROT1olpxERGRlygyMpKsWbMCWBv+X7lyhQwZMpAtWzYePXpEtWrV+OyzzyhRogTHjh2zHnfhwgV27tzJ22+/TdOmTW02BhH5e09bAVdsI0eOHKxevZrs2bNbt4WHh3Pp0iUyZMjArl27WLt2LQcPHmT//v289dZbDB8+nDZt2nD27Fnu3Llju+BFRMSm9JpaRETkJfnhhx945513OHv2LAD379+nevXqeHp64ubmxpo1a0iTJg0dO3akWLFiuLi4cOrUKUJDQ9m8eTONGzemcuXKSpiJiPwDJUuWpEaNGly9epX27dsDUKJECapVq8awYcOoU6cOd+7coX379gQGBhIeHs6hQ4dIkyYNAwcOZPLkyTYegYiI2Ip6momIiLxASfvf3LhxgxIlSvDuu+/i5+dHv379MJvNdOnShZUrV7J69Wr8/f3p0KEDK1euZObMmWzZsoWyZcsSERFB165dGTZsmI1HJCKSOiS9/l65coVjx47RqVMn3nvvPebOnQvA9u3bcXZ2pmTJktYFG2rWrEmXLl344IMPbBa7iIikDEqaiYiIvCBJH9imTZtGsWLFcHZ25s033+Szzz4jPDycESNGkCtXLgDef/99tm3bxuzZs6lXrx7x8fFs27aNLFmy4ODggJubmy2HIyKSaiQumgIwYsQI9uzZw5gxYzh27BiffPIJPj4+fPnll9bj7969S3x8PH369OHgwYNs2rSJQoUK2Sh6ERFJKZQ0ExEReQGSrm754YcfsnDhQtauXUu9evWYP38+Xbt2JU+ePOzfv5+8efNaz3vnnXeIjo7m+++/p2rVqrYKX0QkVXnWisLnzp2jY8eODBkyBE9PT6KiovD398fPz485c+bQsmVL7t27x1dffcWOHTswmUysX78eZ2dnG4xCRERSGvU0ExER+Y8lJCRYH94aN27Mhg0bOHjwIPXq1cNisdClSxdGjBhBaGgoe/fu5dGjR9Zz165dS1RUFJ9++imXLl2y1RBERFIVs9nMzZs3+f7773n48CEAzZs3p2PHjhQvXpxGjRoB4OTkROfOnenSpQs9e/bkyJEjZMqUiWbNmtG5c2cOHjyohJmIiFip0kxEROQ/lDgl6Pr16zRq1Ijjx4+za9cu3N3dk+2Hxw90hw8fZvny5cmqyo4dO8bs2bPVfFpE5DlYLBZMJhOtW7cmffr0zJ8/H4CFCxfStWtX3n77bdatW0f69Omt55w9e5Yvv/ySoKAggoODyZkzp63CFxGRFEyVZiIiIv8hOzs7du7ciaurK2+88QZ16tShd+/eXL161bo/Pj4egJ9++omsWbPi7e1tXVHTMAzc3NyUMBMReU5msxmTycTly5cpVaoU8Pha2qlTJ0aNGsWuXbvYunVrsnNcXV3p168fRYoUITg42BZhi4hIKqBKMxERkf/Qpk2b8PLy4ssvv+SLL77g5s2bVKtWjdKlS7NkyRIyZswIwKNHj0iTJg2RkZGUKVOGcuXKMWfOHPLkyWPjEYiIpB7x8fHWVS+LFy/OxIkTeffdd5Md06VLFzZu3MjmzZspU6aMdbthGERHR5MpU6aXGrOIiKQeqjQTERH5DxUuXJgNGzbwxRdfAJAjRw5WrVrFjh07+OKLL0hISAAgTZo0xMfHkzVrVtasWcOJEyfQeywRkb+XeK3s1asXCxYsICYmhhs3bhAZGUnBggX/dPyMGTMoXrw4Xbp0ISwszLrdZDIpYSYiIn9JlWYiIiL/EcMwMJlMT923du1amjdvznfffccnn3xi3Z5YJfHw4UMcHBxeVqgiIqley5YtCQoK4qeffsLJyYkGDRpw+PBh8uXL96djw8LCqFy5MgULFmTLli04OjraIGIREUltVGkmIiLyH3lWwgygadOmfPvttwwYMIBffvnFuj1xWpESZiIiz8disQCwcuVK3Nzc8PHxYceOHWTKlInz589z9uxZbt68yd27d62rE7u4uLB27VoaNmyohJmIiDw3VZqJiIi8RH379mXmzJns2LGDKlWq2DocEZFUKXElYovFgqurK+fPnyddunSYzY9rArJkyYJhGKRNmxYXFxeyZMnC/PnzcXZ2tnHkIiKSmtjbOgAREZHUzGKxWB/SnseECRM4ffp0sr46IiLyzySuRGxvb8/27dspW7Ys1apV44svvsDR0ZHY2FiuX7/OlStXuH//PjVr1lTCTERE/jFVmomIiPxDib3LEv+1WCxYLBbrVMu/k1ghISIi/07i9XTLli3Ur18fPz8/+vXrpymYIiLyn1BPMxERkX8gISHB2rssLCwMwzCoUKECM2fOfO7VL5UwExF5tsSeZc8jcYpm3bp1mTJlCl999RVLliwhNjb2BUYoIiKvCyXNREREnpNhGNaEV7NmzZg2bRqPHj3Czc2NPXv2EB8fb+MIRURSN8MwMJvNnDt3jlGjRnHo0CHgrxNpiS8yevfuTbdu3ejWrRtXrlx5KfGKiMirTUkzERGR55A4FTM+Pp7JkycTERHBRx99hIODA/Pnz2fBggWkSZPG1mGKiKRqJpOJdevWUalSJS5fvkx8fLy1d2RoaChjxowhLi4uWWVv4jR5AH9/fwICAnB1dbXVEERE5BWinmYiIiLPwTAMLl26RMuWLcmTJw+tWrWiU6dOT10IICoqCicnJxtFKiKSep08eZL33nuPDz/8kH79+lmryAACAgJo0qQJJ06coHTp0taXGYnUL1JERP5rqjQTERF5DiaTiUKFCmE2mwkICCAqKgogWcLMYrHQvXt3OnXqxJ07d2wUqYhI6hUVFUV4eDj169dPlhAD8PT0pH379kycOBFIXmEG6hcpIiL/vedb5ktEROQ186yKhZ07d1KyZEmWL1/Ou+++S+HCha37zGYzXl5eDBky5GWGKiLyysiUKRMlSpSga9eudOjQgSxZspA+fXrSpk1L+vTpyZgxI5kyZSI6OpqMGTPaOlwREXnFaXqmiIjIE5ImzNasWYO9vT3ly5cnX758AJw6dYoKFSrQvXt3vvnmG7Jlywb8X9+zp03ZFBGRv2cYBmFhYfj6+nLkyBHKlSvHxYsXiYmJwTAMLl68yL1796hUqRIxMTHMnz+fN99809Zhi4jIK0qVZiIiIkkkrpB5584dGjRoQGRkJBaLhejoaCZNmkTDhg0pVaoUy5Yto1mzZhQqVIiPPvqIDBkyWKcSKWEmIvLPJb54yJ07N/b29nh6ejJ69Gjri4yHDx/i4+PD/v37GThwILdv31bCTEREXijd1YuIiCRhMpm4evUqdevWpVixYhw6dIiQkBAKFSrEiBEjWLduHXFxcTRt2pSxY8fi6+vLTz/9hAq3RUT+naQ9zIoVK0ZgYCBhYWHY2dlhGAaGYfDgwQO6du1K69at+eijj2wYrYiIvA6UNBMRkddS0iRXQkJCsn1nz56lWrVqTJ8+HScnJz755BMuXryIo6MjI0eOJCgoCID+/fvTo0cP8uTJ86eG1SIi8r+rVKkSTk5OfPzxx+zdu5etW7fSuXNntm7dyrvvvmvr8ERE5DWh6ZkiIvJaSkxyBQYG0rhxYwCmTZtGrVq1cHNzI3v27GTKlIlevXqxb98+9uzZQ6FChXB2dmbatGnY2dlRr149pk+fbsthiIikKk9bZCVxWmZSHh4eXLp0iZkzZ/L2229TunRp8uXLx/Hjx8mcOfPLDFlERF5jWghAREReW9u3b+edd95h1qxZBAQEsHfvXrZv346rqysA586do2XLlowePRoPDw+uXbtG3bp1CQkJYeTIkQwcOFAVZiIizylxkZS4uDiWL19OsWLFKFKkCLly5UqWTEs8zjAMEhISOHfuHA4ODhQpUsTGIxARkdeNKs1EROS1VatWLYYMGULv3r3JmzcvR48eJVeuXNaqh5CQEG7fvk3GjBkBOH/+PJ6enrRq1YqqVavaOHoRkdTFbDZz4cIF3nnnHesU+eLFi7Ns2TKcnZ2Jj4/H3t4+2WIq9vb2lCxZ0lYhi4jIa049zURE5LUWHByMvb099+7d4969e8D/Td2sUaMGDg4OeHt707x5czw8PMiePbsSZiIiz8lisST7ef369bRu3ZpTp04xbtw44uPj8fLyAh4nyJL2mFQlr4iI2JqSZiIi8tp48uENYNmyZURFRVG6dGlatmzJ9evXAXj06BEZMmQgMDCQ2rVrkyFDBhYsWMBnn332ssMWEUmVEqdZAuzevZsTJ06wc+dOqlatSvr06WnZsiVffPEFt27dom3btgDY2dk99VotIiJiC+ppJiIir4Wk/XJ27dpFmjRpSJ8+PW+88QYA169fx93dnXLlyrF06VLSpUsHwB9//EHx4sWf2rxaRESeLmnCrEePHixatIjChQtz7do1li5dSqNGjQB4+PAhP/30E59++ildu3Zl5MiRtgxbREQkGVWaiYjIK88wDGvCq0ePHrRr147333+fqlWrMmfOHKKjo8mdOzerVq0iKCiIDz/8kO3bt/P222/j6+urhJmIyD+UmDDbsWMHZ86cYf/+/YwcOZLKlSvTp08foqOjAXBwcODdd99l4MCBjBo1ih07dtgybBERkWRUaSYiIq8FwzDo0KEDwcHBLFmyhLJly+Lt7c2PP/7Id999R5s2bUibNi1btmyhffv2ODs7U7RoUX755Rdbhy4ikurExsby1ltvkS1bNmrXrs3QoUMBOHPmDM2bNyd37txs3rzZenxYWBgnTpygXr16tgpZRETkT1RpJiIiryTDMEj6Xig4OJi0adNaE2bz5s1j0aJFFCxYEG9vb4KCgoiLi6Nu3bocOnSIVatWKWEmIvKcEq+3if+mS5cOLy8vgoKCrIusAJQoUYJZs2Zx7NgxPv74Y+t2FxcXJcxERCTFUaWZiIi80s6cOYOTkxPp0qXj4MGD1KtXD39/f0aOHMmYMWPo0KED5cqVw8nJiVGjRlG9enWt2CYi8g8kncL+6NEj0qRJY933/vvv8+uvv7J161bKlCkDPO53tnbtWlq0aMGUKVPo3bu3TeIWERH5O0qaiYjIK8lisXDjxg2KFy/Ojz/+SNOmTUlISCA+Pp7GjRvTqFEjBgwYQExMDJ6engQFBeHp6cmKFStwdHS0dfgiIqlC0ob/o0aN4ty5cwC88847dOzYEcMwcHd35+HDh6xbtw4XFxfg8QIAK1eupE6dOtZtIiIiKY2mZ4qIyCvJbDaTO3duGjVqxPTp062LAZw/f56jR49SrFgxAGJiYnB1deX3339nzpw5SpiJiPwDiQmzxo0bM2vWLFxdXXFwcGDw4MH4+vpiMplYtWoVt2/fpm/fvty/fx94vABA+/btlTATEZEUTUkzERF5JVgslmQ/x8fHA+Dp6Ul0dDRnzpwBoFSpUri5ueHt7U3v3r2pXLkyoaGhlCpViuzZs7/0uEVEUrulS5dy9+5d9u3bx6BBg3B3dyc8PJzMmTMDkCdPHlatWsWqVavo378/mugiIiKphZJmIiLySjCbzURERDBu3DjCw8Oxt7cHoH79+vz+++/s3LnTemxgYCC1atXi1q1bdOjQgZ9//tlWYYuIpHq///47uXLlIkeOHHz99df06dOHqVOnMmTIEAzDICwsjEqVKrF48WKqVq2qvpEiIpJqqKeZiIikWtHR0WTMmNHaU2fy5MnMmDGD6OhopkyZQqVKlciTJw+DBw9my5YtrFu3zlpNZhgG8fHxyRpWi4jIsyVt+J/IMAy+/fZbLl26RExMDJs2bWLhwoXUqVMHwzBYuXIlV69e5eOPP9b0dxERSXVUaSYiIqnS6NGj8fDwYNu2bTx8+BCAPn36sHv3burVq8fXX39Nx44dOXv2LG+++Sbp06fn0qVLwOOpnCaTSQkzEZHnlDRhtn37dg4ePMjZs2cxmUzUrFmTadOmsWHDBjZv3kydOnUACAsLY9asWdy9e/dPyTYREZHUQEkzERFJdeLi4ti0aRP37t2jT58+9OvXj3Xr1mE2m3FycmLWrFn4+fmRJUsW6tevz4EDB9i+fbt1GmZi42oREXk+iUmv5s2b88EHH9CtWzeqVavGd999R9WqVZk4cSK3b99m69atrFu3ji1btlC3bl0AhgwZYp0yLyIikpror5eIiKQ6dnZ2lC1blhIlSlCzZk1WrFhB69at8fX1pUaNGtStW5eGDRvSsGFDxowZQ3BwMADnzp2zceQiIqlTfHw8nTp1IjQ0lG3btpE/f37atWvHiBEjqFGjBt7e3oSGhjJnzhwuXrxI0aJFefvtt5k+fbqtQxcREfmfqaeZiIikShs2bKB9+/YcO3aMfPnysW/fPqZPn05AQABff/01devWpWTJkgBERkaya9cuvLy8bBy1iEjqdP/+fd59911GjRrFW2+9xbhx4xg+fDh+fn707t3belx4eDj379/HbDZTsGBBG0YsIiLy7ylpJiIiqY5hGDx8+JD27dtTq1YtvL29efToESVLlsTBwYGEhATy58+Pu7s7Q4cOVe8yEZF/wDCMZCtcGobB2bNnqV27NsHBwfj5+bF48WLmzp1Lo0aNiImJ4ddff6VJkya63oqIyCtFTV1ERCTVMZlMODo6ki1bNkJCQjh37hx58+alZMmSnDx5klWrVlG7dm2mTJnChQsXbB2uiEiK9+jRI+u/iQmz2NhY4PE1t0SJElSsWJHixYvz66+/snv3bho1agTAyZMn+eGHHzh27JhtghcREXlBVGkmIiKpTmIVRHBwMG5ubgD4+PgwYsQI0qdPbz3u3r17ZMqUyVZhioikCmvXruX48eP07NmTXLlyAY+vqdeuXaNgwYJ4e3tToEABZs+ezdixY3n33XcZP348Dx8+JDQ0lNatW1O0aFEWLFigSjMREXmlaCEAERFJdRKrIPLnz4+Hhwf58+dn/PjxPPkeSAkzEZG/d+DAAWbOnImLiwutW7emR48eBAcH07hxY2bOnMnp06cZNmwY7du359y5c8ybN48tW7ZQoEABjh49iru7O0uWLLH1MERERP5zqjQTEZFU7ZNPPmHHjh0cOXIE+HMvHhERebqk18uePXty4MABvL292bVrF2PGjCFHjhycOXOGNm3aULp0afz8/MiXLx9Hjhxh4cKF5M2bl/z589O+fXsbj0REROTFUNJMRERStStXrlC6dGm+//57unTpYutwRERStL96sVC3bl2OHTtGmTJl2L59u3V7YGAgn376KR4eHvTr10+rYoqIyGtDCwGIiEiqliNHDtzd3SldurStQxERSdEsFos1YbZy5Upmz57Nnj17rA3/ly1bRtGiRbl58yYHDhywnte4cWP69evHpk2bmDp1Knfv3rVJ/CIiIi+bKs1ERCTVe/jwIQ4ODrYOQ0QkxUpISMDOzg4AT09Pfv/9dzJkyMDp06eZP38+HTp0AODIkSM0a9aMRo0aMXDgQIoUKWL9jN69e3P//n1mzpyphv8iIvJaUNJMREREROQ1cP36dWrUqEHevHn58ccfyZ8/P507d+bYsWMcO3bMetyyZcv49NNP6d69O3369CFHjhw2jFpERMR2tHqmiIiIiMgr7urVq1SoUIGqVasSEBBAfHw8AO+88w4Wi4Wff/6ZfPny4ebmRps2bTh//jyzZ88ma9asdO/enYwZM9p4BCIiIi+fKs1ERERERF5xR48excfHh3v37rF3714cHBw4fPgwNWvWpFSpUoSEhJAlSxbq1q3LrFmzAOjUqROHDh1i06ZN5MuXz8YjEBERefm0EICIiIiIyCuufPny+Pn5kZCQQNu2bVm9ejX16tWjT58+bN68mZMnT+Ll5cX69evZuHEjAAsXLiQgIEAJMxEReW2p0kxERERE5BVmGAYmk4mEhATWrVtH//79CQkJYeXKlTRv3pxHjx6RJk0atm3bRv369QkMDKRBgwa2DltERMTmVGkmIiIiIvIKM5lMANjZ2VG3bl0GDRpE1qxZCQ0NTbb//v37lC1blpw5c9osVhERkZRECwGIiIiIiLwmMmTIQLNmzQgNDWXw4MEULFgQLy8vfv75Zzp37oy3tzfly5e3dZgiIiIpgpJmIiIiIiKvgMRpmH/H2dmZbt26ERoayocffsi2bdv4/vvvGTduHN7e3i8hUhERkdRBPc1ERERERFK5hIQE7OzsAIiNjcVkMpE2bdq/POf06dP06dOH3bt38/PPP1O/fv2XEaqIiEiqoaSZiIiIiEgqljRh9uWXX3LkyBEuX77MoEGDqF27Nnnz5n1mFdrRo0cpUKAA2bJle9lhi4iIpHhKmomIiIiIvAJatGjB0aNH6d+/P6GhoaxYsYL33nuPfv364eLikixx9rxTOUVERF5nWj1TRERERCQVslgsGIaBYRiMHz+esLAw9u3bx8cff0zDhg35448/WLNmDTNnzrRO2bRYLABKmImIiDwHJc1ERERERFKR6OhoAMxmM7du3cJkMlGlShUGDRpEjhw5GDt2LE2aNGHGjBnUrl2bqVOn8uOPP1rPERERkeejv5oiIiIiIqnEnDlz6NKlCwCzZ8+mbNmyXL9+nfLly+Pp6cnOnTtZuHAhs2fPpnv37vj4+BATE8OUKVNYuXKljaMXERFJXextHYCIiIiIiDyfihUr0r17d9566y2OHj3KokWLyJ07t3X/mTNnsFgsuLu7A49XyKxbty45c+akVq1atgpbREQkVVKlmYiIiIhIKvDo0SPKly+Pm5sbBw4cwMfHhxYtWgCPG/sD3L9/H3t7e9atW8ehQ4cYPnw49erVw9/fnxw5ctgyfBERkVRHq2eKiIiIiKRgT6506efnx82bN5k+fTqLFy/G09MTe/vHE0gePHhAixYtOHPmDFFRUXh4eLBw4UJbhS4iIpKqKWkmIiIiIpICJd6mm0wm7t69y4MHD8iZM6d1f/PmzTlw4ADLli3D3d3dmlh78OABYWFh3Lhxg6pVq9okdhERkVeBkmYiIiIiIinY8uXLGT9+PFFRUVSsWJF33nmHHj16AFChQgUcHR2ZMWMG5cqVY9iwYRQsWJD333/ftkGLiIi8ApQ0ExERERFJoWbMmIGPjw/Dhw8nXbp07Ny5k/3799O7d2/69+9PVFQUZcuWxcXFBZPJREhICNu3b6ds2bK2Dl1ERCTVU9JMRERERCQFiomJoV27dlSrVo3PP/8cgLCwMGbOnMmsWbOYPXs29erVIyQkhOXLl3Pv3j0GDx5MxowZbRy5iIjIq8He1gGIiIiIiMif2dnZce7cOcqUKWPd5uLiQuvWrdmxYwcHDhygTp06FC1alM8++yzZYgEiIiLy75ltHYCIiIiIyOssPj6ep03+ePjwIaVKleL69evcuHHDur1EiRIYhsHRo0cxmx/fzithJiIi8t9T0kxERERE5CW7d+8efn5+ANjb22Mymdi0aRP9+/dnzJgxXL58mUyZMtGyZUt++uknVqxYwd27dwGwWCxkypSJN954w5ZDEBEReeWpp5mIiIiIyEu2adMmGjZsyMiRI/n888/x9/dnwIABVKtWjUuXLhEbG8vevXspUKAAX375JXPnzuXNN9+kSpUqHD58mF27drFjxw5KlChh66GIiIi8spQ0ExERERF5yeLj45k5cyZ9+vRh+fLlnD59mooVK9KoUSMuXbpEly5dCA8P58CBA2TMmJH58+ezefNmrl+/TrZs2fD398fZ2dnWwxAREXmlKWkmIiIiImIDsbGxDB06lAkTJlCoUCFWr15tnXJ58eJFGjRoQOHChdmwYYP1nPv375MhQwZbhSwiIvJaUU8zEREREZGX4Ml31enSpWPAgAF069aNK1eu4ODgADzuWVaoUCEWLVrEb7/9Rs+ePa3nKGEmIiLy8qjSTERERETkBUlISMBisZAmTRrrttu3b2MYBtmzZwfg0qVLtGrVCoADBw4kO3/p0qW0b9+eM2fOULx48ZcXuIiIiKjSTERERETkv2YYBrdv36ZChQr88ssv1u2TJk2iZs2a1KpViy+++ILIyEgKFizIzJkzuXbtGm3btk32OW3btuX69etKmImIiNiAva0DEBERERF51ZhMJpydncmaNSu+vr4UKFCAs2fPMmHCBHx8fIiOjuabb74hKiqKIUOG4Obmxpw5c2jZsiVffvklw4cPt35Wrly5bDgSERGR15emZ4qIiIiI/EcsFgtms5mEhATs7OwAKFOmDHnz5sXd3Z2iRYvSqVMnAFavXs3777/PoEGD6NOnD5kzZ2b69Ol89NFHbN++nbffftuWQxEREXntqdJMREREROQ/YBgGZrOZK1euEBISQmxsLI0aNWL79u2ULVuWzZs3M2PGDOvxzZo1448//mD06NHkzZuXtm3b0qNHD4oUKaKEmYiISAqgnmYiIiIiIv8Bk8nEqlWraNy4MZMnT2b8+PHcuXOH7Nmzs2nTJsxmMwcOHCAiIsJ6jq+vL23btsXb25uNGzdiNpupX7++DUchIiIiiVRpJiIiIiLyH/juu+8YMmQIU6ZMoUmTJjg7O1unar7xxhssWLCAjh07Ur58ebp160batGkBmDp1KqGhoeTLl8/GIxAREZGklDQTEREREfmXDhw4wLx585g7dy5t2rSxbjcMw9rbrH379pw+fZr+/fuTL18+3n33Xeu+NWvW2CJsERER+QuanikiIiIi8i8dPHiQ+/fvU6tWLZKus2UymQBISEgA4JtvvuG9996jV69e7Ny50yaxioiIyPNR0kxERERE5F86ceIEGTJkwMXFBZPJlCxxllhtFh8fD8CSJUtIly4dR44csVW4IiIi8hyUNBMRERER+ZcyZsxIREQEwcHBwP9VmCX9f9euXZk9ezYAZ8+epV+/fi8/UBEREXluSpqJiIiIiPxLLVq0IDQ0lGXLlnH37t0/7b9x4wZxcXEUKVIEwNrLTERERFIuJc1ERERERP6latWqMWDAAMaNG8eCBQu4ceMGAPHx8dy+fZs+ffpw+/ZtypUrBySvRBMREZGUyWQkbbggIiIiIiL/k7t379K3b18WLVpE1apVadCgAVFRUWzdupV06dIRFBRE2rRpbR2miIiIPCclzURERERE/kPffvstu3bt4sSJE7z55puUK1eOIUOG2DosERER+YeUNBMREREReQHi4uJwcHDQVEwREZFUSkkzEREREZEXxDAMJc1ERERSKS0EICIiIiLygihhJiIiknopaSYiIiIiIiIiIvIEJc1ERERERERERESeoKSZiIiIiIiIiIjIE5Q0ExEREREREREReYKSZiIiIiIiIiIiIk9Q0kxEREREREREROQJSpqJiIiIiIiIiIg8QUkzERERkVdEUFAQJpOJO3fu/OVxhQoVYuLEiS8lJhEREZHUSkkzERERkVSqdu3a+Pj4WH92d3fn+vXrODk5ATBv3jyyZMlim+BEREREUjl7WwcgIiIiIv8NBwcHXFxcbB2GiIiIyCtBlWYiIiIiqdD777/P9u3bmTRpEiaTCZPJxLx586zTM4OCgujatStRUVHW/V9//fVTP+vOnTt0796dHDlykDlzZurUqcOxY8de7oBEREREUhglzURERERSoUmTJvHWW2/Ro0cPrl+/zvXr18mfP791v7u7OxMnTiRz5szW/QMGDHjqZ7Vq1Yrw8HB+/fVXDh8+TMWKFalbty4REREvazgiIiIiKY6mZ4qIiIikQk5OTjg4OJA+fXrrlMzTp09b9zs4OODk5ITJZPrLKZu7du3iwIEDhIeH4+joCMC4ceNYs2YNK1eupGfPni92ICIiIiIplJJmIiIiIq+xY8eOER0djbOzc7LtsbGxhISE2CgqEREREdtT0kxERETkNRYdHU3u3LkJCgr60z6tvCkiIiKvMyXNRERERFIpBwcHEhIS/uf9ABUrViQsLAx7e3sKFSr0H0coIiIiknppIQARERGRVKpQoULs37+fixcvcuvWLSwWy5/2R0dHs2XLFm7dukVMTMyfPqNevXq89dZbvPfee2zcuJGLFy+yZ88evvjiCw4dOvSyhiIiIiKS4ihpJiIiIpJKDRgwADs7O0qXLk2OHDm4fPlysv3u7u58+OGHtGnThhw5cvDtt9/+6TNMJhOBgYHUrFmTrl274urqStu2bbl06RK5cuV6WUMRERERSXFMhmEYtg5CREREREREREQkJVGlmYiIiIiIiIiIyBOUNBMREREREREREXmCkmYiIiIiIiIiIiJPUNJMRERERERERETkCUqaiYiIiIiIiIiIPEFJMxERERERERERkScoaSYiIiIiIiIiIvIEJc1ERERERERERESeoKSZiIiIiIiIiIjIE5Q0ExEREREREREReYKSZiIiIiIiIiIiIk/4fygaSJ/SEs1DAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Visualization of Bottom 10 Netflix Titles by IMDB_score"
      ],
      "metadata": {
        "id": "SMop1ajwve4u"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "##Sorting the dataframe to get bottom ten titles of Netflix\n",
        "bottom_10_titles = df.sort_values(by = 'imdb_score', ascending = True).head(10)\n",
        "ax = sns.barplot(x = 'title', y = 'imdb_score', data = bottom_10_titles)\n",
        "ax.set_xticklabels(ax.get_xticklabels(), rotation=40, ha=\"right\")\n",
        "plt.title('Bottom 10 Netflix Titles')\n",
        "plt.rcParams['figure.figsize'] = (15,7)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 791
        },
        "id": "PeUfkc3DqJZc",
        "outputId": "191fa97d-8715-4035-e05e-56e147a0517d"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x700 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Visualization of the count of Netflix shows and Movies"
      ],
      "metadata": {
        "id": "pvYB5I9HvjoB"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "sns.countplot(x=\"type\",data=df)\n",
        "plt.rcParams['figure.figsize'] = (7,5)\n",
        "plt.title('Count of Shows And Movies')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 504
        },
        "id": "DGWLNrxXyS_1",
        "outputId": "6097fef6-15e0-4f66-96e6-2495769ba3f4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Count of Shows And Movies')"
            ]
          },
          "metadata": {},
          "execution_count": 192
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Visualization of count of different age ratings shows"
      ],
      "metadata": {
        "id": "0p3MQaLRvu7l"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sns.countplot(x=\"rating\",data=df)\n",
        "plt.xticks(rotation=45)\n",
        "plt.title('Count of Different Age Ratings')\n",
        "plt.rcParams['figure.figsize'] = (7,5)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 532
        },
        "id": "WMuqsavyzKWa",
        "outputId": "8e985052-3cdb-44e6-a7da-d96c4ad6c33d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# IMDB Score difference between Shows and Movies"
      ],
      "metadata": {
        "id": "k2kPRcI_v9KA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sns.barplot(x=\"type\",y=\"imdb_score\",data=df)\n",
        "plt.title('IMDB Score Difference of Shows and Movies')\n",
        "plt.rcParams['figure.figsize'] = (7,5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "id": "8hArStiizm0T",
        "outputId": "c224e6b7-2e26-4706-e37f-12b5db54af5d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Replacing the Genre which was empty brackets with Not Given\n",
        "df['genres'] = df['genres'].replace('[]', 'Not Given')"
      ],
      "metadata": {
        "id": "skJWQhSG05Ox"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Visualizing Top 10 Netflix Genres"
      ],
      "metadata": {
        "id": "b4hqPD4RwKr4"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "top_10_genres = df.sort_values(by = 'imdb_score', ascending = False).head(10)\n",
        "ax = sns.barplot(x = 'genres', y = 'imdb_score', data = top_10_genres)\n",
        "ax.set_xticklabels(ax.get_xticklabels(), rotation=40, ha=\"right\")\n",
        "plt.title('Top 10 Netflix Genres')\n",
        "plt.rcParams['figure.figsize'] = (15,7)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 844
        },
        "id": "_e1XTHnOztd6",
        "outputId": "c16388e5-1d01-4b38-93bb-e258baa6ee23"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x700 with 1 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **Conclusion - After performing data analysis on our dataset, it is evident that 'ABTalks' show is the top rated Netflix show while 'Aerials' being the least rated. Netflix has a large collection of movies(around 3800) whereas shows are about 2200 but the IMDB ratings of shows are higher than movies. Apart from the genre that is missing, Netflix users prefer 'Drama, Crime and Thriller' genres the most.**"
      ],
      "metadata": {
        "id": "_2aRaoV1wPTw"
      }
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "xy5M35GB1mHW"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}