Weather_analysis.ipynb

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        "#ALFIDO TECH WEATHER ANALYSIS"
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        "##ABOUT THE DATASET"
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        "## Understanding and Utilizing Weather Data\n",
        "\n",
        "##Introduction:\n",
        "\n",
        "Weather data plays a crucial role in our daily lives and various industries, from agriculture to transportation and emergency preparedness. Understanding and effectively utilizing weather data can help individuals and organizations make informed decisions, improve safety, and optimize operations.\n",
        "\n",
        "##Types of Weather Data:\n",
        "Weather data encompasses a wide range of information collected from various sources, including meteorological stations, satellites, weather balloons, and weather radars. The key types of weather data include:\n",
        "\n",
        "a. Temperature: Information about the current and forecasted temperature, which impacts clothing choices, heating and cooling needs, and agricultural practices.\n",
        "\n",
        "b. Precipitation: Data on rainfall, snowfall, and other forms of precipitation, critical for water resource management, flood forecasting, and agricultural planning.\n",
        "\n",
        "c. Humidity: Measures the amount of moisture in the air, influencing human comfort, crop health, and weather patterns.\n",
        "\n",
        "d. Wind Speed and Direction: Wind data is vital for aviation, renewable energy generation, and understanding weather patterns.\n",
        "\n",
        "e. Atmospheric Pressure: Information about the pressure exerted by the atmosphere, useful for weather predictions and altimeter settings for aviation.\n",
        "\n",
        "f. Cloud Cover: Indicates the fraction of the sky covered by clouds and helps determine potential rainfall and solar radiation.\n",
        "\n",
        "g. UV Index: Measures the strength of ultraviolet radiation from the sun, important for skin protection and outdoor activities.\n",
        "\n",
        "Weather Data Sources:\n",
        "Weather data comes from a variety of sources, including:\n",
        "\n",
        "a. National Meteorological Agencies: Government agencies responsible for collecting and disseminating weather information for specific regions or countries.\n",
        "\n",
        "b. Weather Stations: Ground-based installations that monitor local weather conditions, including temperature, humidity, and precipitation.\n",
        "\n",
        "c. Satellites: Orbiting satellites capture images and data from space, providing a broader perspective on weather patterns and storms.\n",
        "\n",
        "d. Weather Radars: Used to detect precipitation, measure wind speed, and identify severe weather events such as tornadoes and thunderstorms.\n",
        "\n",
        "e. Weather Balloons: Instruments attached to weather balloons collect atmospheric data at different altitudes.\n",
        "\n",
        "f. Weather Apps and Websites: Online platforms that provide real-time weather updates and forecasts based on data from various sources.\n",
        "\n",
        "Applications of Weather Data:\n",
        "Weather data has numerous applications across various industries and activities, including:\n",
        "\n",
        "a. Agriculture: Farmers use weather data to schedule irrigation, plan planting and harvesting, and mitigate the impact of extreme weather on crops.\n",
        "\n",
        "b. Transportation: Airlines, shipping companies, and road networks rely on weather data to optimize routes, avoid hazardous conditions, and ensure passenger safety.\n",
        "\n",
        "c. Renewable Energy: Wind and solar energy generation depend on weather data to predict energy production and manage power grids efficiently.\n",
        "\n",
        "d. Disaster Preparedness: Weather data is vital for early warning systems and emergency response planning during hurricanes, floods, and other severe weather events.\n",
        "\n",
        "e. Tourism: Tour operators and travelers use weather forecasts to plan outdoor activities and make the most of their trips.\n",
        "\n",
        "Challenges in Weather Data Analysis:\n",
        "While weather data is invaluable, analyzing and interpreting it can be complex due to:\n",
        "\n",
        "a. Data Volume: Weather data is vast and constantly updating, requiring powerful computing systems for processing and analysis.\n",
        "\n",
        "b. Data Quality: Ensuring the accuracy and reliability of weather data is crucial, as errors can lead to significant consequences.\n",
        "\n",
        "c. Forecasting Accuracy: Weather forecasting involves uncertainties, and improving prediction accuracy is an ongoing challenge for meteorologists.\n",
        "\n",
        "Conclusion:\n",
        "\n",
        "Weather data is a valuable resource that influences our daily lives and various industries. By understanding the types of weather data, its sources, and its applications, individuals and organizations can harness its power to make informed decisions, enhance safety, and optimize operations in a changing climate."
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      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns"
      ]
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      "source": [
        "df= pd.read_csv(\"weather.csv\")"
      ],
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              "       Date/Time  Temp_C  Dew Point Temp_C  Rel Hum_%  Wind Speed_km/h  \\\n",
              "0  1/1/2012 0:00    -1.8              -3.9         86                4   \n",
              "1  1/1/2012 1:00    -1.8              -3.7         87                4   \n",
              "2  1/1/2012 2:00    -1.8              -3.4         89                7   \n",
              "3  1/1/2012 3:00    -1.5              -3.2         88                6   \n",
              "4  1/1/2012 4:00    -1.5              -3.3         88                7   \n",
              "\n",
              "   Visibility_km  Press_kPa               Weather  \n",
              "0            8.0     101.24                   Fog  \n",
              "1            8.0     101.24                   Fog  \n",
              "2            4.0     101.26  Freezing Drizzle,Fog  \n",
              "3            4.0     101.27  Freezing Drizzle,Fog  \n",
              "4            4.8     101.23                   Fog  "
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            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 8784 entries, 0 to 8783\n",
            "Data columns (total 8 columns):\n",
            " #   Column            Non-Null Count  Dtype  \n",
            "---  ------            --------------  -----  \n",
            " 0   Date/Time         8784 non-null   object \n",
            " 1   Temp_C            8784 non-null   float64\n",
            " 2   Dew Point Temp_C  8784 non-null   float64\n",
            " 3   Rel Hum_%         8784 non-null   int64  \n",
            " 4   Wind Speed_km/h   8784 non-null   int64  \n",
            " 5   Visibility_km     8784 non-null   float64\n",
            " 6   Press_kPa         8784 non-null   float64\n",
            " 7   Weather           8784 non-null   object \n",
            "dtypes: float64(4), int64(2), object(2)\n",
            "memory usage: 549.1+ KB\n"
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              "            Temp_C  Dew Point Temp_C    Rel Hum_%  Wind Speed_km/h  \\\n",
              "count  8784.000000       8784.000000  8784.000000      8784.000000   \n",
              "mean      8.798144          2.555294    67.431694        14.945469   \n",
              "std      11.687883         10.883072    16.918881         8.688696   \n",
              "min     -23.300000        -28.500000    18.000000         0.000000   \n",
              "25%       0.100000         -5.900000    56.000000         9.000000   \n",
              "50%       9.300000          3.300000    68.000000        13.000000   \n",
              "75%      18.800000         11.800000    81.000000        20.000000   \n",
              "max      33.000000         24.400000   100.000000        83.000000   \n",
              "\n",
              "       Visibility_km    Press_kPa  \n",
              "count    8784.000000  8784.000000  \n",
              "mean       27.664447   101.051623  \n",
              "std        12.622688     0.844005  \n",
              "min         0.200000    97.520000  \n",
              "25%        24.100000   100.560000  \n",
              "50%        25.000000   101.070000  \n",
              "75%        25.000000   101.590000  \n",
              "max        48.300000   103.650000  "
            ],
            "text/html": [
              "\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Temp_C</th>\n",
              "      <th>Dew Point Temp_C</th>\n",
              "      <th>Rel Hum_%</th>\n",
              "      <th>Wind Speed_km/h</th>\n",
              "      <th>Visibility_km</th>\n",
              "      <th>Press_kPa</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>8784.000000</td>\n",
              "      <td>8784.000000</td>\n",
              "      <td>8784.000000</td>\n",
              "      <td>8784.000000</td>\n",
              "      <td>8784.000000</td>\n",
              "      <td>8784.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>8.798144</td>\n",
              "      <td>2.555294</td>\n",
              "      <td>67.431694</td>\n",
              "      <td>14.945469</td>\n",
              "      <td>27.664447</td>\n",
              "      <td>101.051623</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>11.687883</td>\n",
              "      <td>10.883072</td>\n",
              "      <td>16.918881</td>\n",
              "      <td>8.688696</td>\n",
              "      <td>12.622688</td>\n",
              "      <td>0.844005</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>-23.300000</td>\n",
              "      <td>-28.500000</td>\n",
              "      <td>18.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.200000</td>\n",
              "      <td>97.520000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>0.100000</td>\n",
              "      <td>-5.900000</td>\n",
              "      <td>56.000000</td>\n",
              "      <td>9.000000</td>\n",
              "      <td>24.100000</td>\n",
              "      <td>100.560000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>9.300000</td>\n",
              "      <td>3.300000</td>\n",
              "      <td>68.000000</td>\n",
              "      <td>13.000000</td>\n",
              "      <td>25.000000</td>\n",
              "      <td>101.070000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>18.800000</td>\n",
              "      <td>11.800000</td>\n",
              "      <td>81.000000</td>\n",
              "      <td>20.000000</td>\n",
              "      <td>25.000000</td>\n",
              "      <td>101.590000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>33.000000</td>\n",
              "      <td>24.400000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>83.000000</td>\n",
              "      <td>48.300000</td>\n",
              "      <td>103.650000</td>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ELl1pvIrw3Hc",
        "outputId": "bad920e9-2b08-43c2-8e61-853f4336625a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(8784, 8)"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Check for duplicate rows based on all columns\n",
        "duplicates = df[df.duplicated()]\n",
        "\n",
        "#\n",
        "if not duplicates.empty:\n",
        "    print(\"Duplicate Rows except first occurrence:\")\n",
        "    print(duplicates)\n",
        "else:\n",
        "    print(\"No duplicate rows found.\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "V9zI3Boow8TT",
        "outputId": "d633c6d2-d93a-46c1-83a5-c987f70ff3c0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "No duplicate rows found.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Jf7C_gs1xCNi",
        "outputId": "ae044e1e-55fa-4424-8fbf-b57226c105ef"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Date/Time           0\n",
              "Temp_C              0\n",
              "Dew Point Temp_C    0\n",
              "Rel Hum_%           0\n",
              "Wind Speed_km/h     0\n",
              "Visibility_km       0\n",
              "Press_kPa           0\n",
              "Weather             0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Temperature Analysis"
      ],
      "metadata": {
        "id": "Sv2vMsN71toq"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "# Assuming 'Date/Time' column is in datetime format\n",
        "df['Date/Time'] = pd.to_datetime(df['Date/Time'])\n",
        "\n",
        "# Set the 'Date/Time' column as the index\n",
        "df.set_index('Date/Time', inplace=True)\n",
        "\n",
        "# Plotting\n",
        "plt.figure(figsize=(12, 6))\n",
        "sns.lineplot(data=df['Temp_C'], color='blue')\n",
        "plt.title('Temperature Distribution Over Time')\n",
        "plt.xlabel('Date/Time')\n",
        "plt.ylabel('Temperature (°C)')\n",
        "plt.grid(True)\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 564
        },
        "id": "Ky74ZA1G1yM6",
        "outputId": "067aafb4-6dec-46ac-8e22-a1dde5e8f608"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Assuming 'Date/Time' column is in datetime format\n",
        "df['Date/Time'] = pd.to_datetime(df['Date/Time'])\n",
        "\n",
        "# Set the 'Date/Time' column as the index\n",
        "df.set_index('Date/Time', inplace=True)\n",
        "\n",
        "# Resample the data into quarters and calculate the mean temperature for each quarter\n",
        "average_temperatures = df['Temp_C'].resample('Q').mean()\n",
        "\n",
        "# Print the average temperatures for each quarter\n",
        "print(\"Average Temperatures for Each Quarter:\")\n",
        "print(average_temperatures)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zvDe_tH_46SV",
        "outputId": "6e2d0121-4b1d-4a1c-9f24-155656e06059"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Average Temperatures for Each Quarter:\n",
            "Date/Time\n",
            "2012-03-31    -2.794322\n",
            "2012-06-30    14.479899\n",
            "2012-09-30    20.561775\n",
            "2012-12-31     2.880978\n",
            "Freq: Q-DEC, Name: Temp_C, dtype: float64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "# Assuming 'Date/Time' column is in datetime format\n",
        "df['Date/Time'] = pd.to_datetime(df['Date/Time'])\n",
        "\n",
        "# Set the 'Date/Time' column as the index\n",
        "df.set_index('Date/Time', inplace=True)\n",
        "\n",
        "# Resample the data into quarters and calculate the mean temperature for each quarter\n",
        "df_quarters = df['Temp_C'].resample('Q').mean()\n",
        "\n",
        "# Plotting\n",
        "plt.figure(figsize=(12, 6))\n",
        "sns.barplot(x=df_quarters.index, y=df_quarters, color='orange')\n",
        "plt.title('Average Temperature by Quarter')\n",
        "plt.xlabel('Quarter')\n",
        "plt.ylabel('Average Temperature (°C)')\n",
        "plt.xticks(rotation=45)\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 663
        },
        "id": "p9p46Dvh3vF3",
        "outputId": "63fdb44f-d32b-48fc-8a76-eecee716f80a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "It appears that the initial three months of 2012 experienced notably cold temperatures, followed by a gradual and consistent rise in temperature from March to September. Notably, September stands out as a month with the highest increase in temperature. As the year progresses into the last three months, a return to colder temperatures is observed."
      ],
      "metadata": {
        "id": "UmixqjwrC5U4"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "\n",
        "\n",
        "df['Date/Time'] = pd.to_datetime(df['Date/Time'])\n",
        "\n",
        "# Set the 'Date/Time' column as the index\n",
        "df.set_index('Date/Time', inplace=True)\n",
        "\n",
        "# Calculate descriptive statistics for temperature\n",
        "temperature_stats = df['Temp_C'].describe()\n",
        "\n",
        "# Identify outliers using IQR method\n",
        "Q1 = temperature_stats['25%']\n",
        "Q3 = temperature_stats['75%']\n",
        "IQR = Q3 - Q1\n",
        "lower_bound = Q1 - 1.5 * IQR\n",
        "upper_bound = Q3 + 1.5 * IQR\n",
        "\n",
        "outliers = df[(df['Temp_C'] < lower_bound) | (df['Temp_C'] > upper_bound)]\n",
        "\n",
        "# Plotting box plot to visualize temperature distribution and outliers\n",
        "plt.figure(figsize=(10, 6))\n",
        "sns.boxplot(x=df.index.year, y=df['Temp_C'])\n",
        "plt.title('Temperature Distribution and Outliers Over Years')\n",
        "plt.xlabel('Year')\n",
        "plt.ylabel('Temperature (°C)')\n",
        "\n",
        "# Highlight outliers on the plot\n",
        "sns.scatterplot(x=outliers.index.year, y=outliers['Temp_C'], color='red', label='Outliers')\n",
        "\n",
        "plt.legend()\n",
        "plt.show()\n",
        "\n",
        "# Display descriptive statistics\n",
        "print(\"Descriptive Statistics for Temperature:\")\n",
        "print(temperature_stats)\n",
        "\n",
        "# Display identified outliers\n",
        "print(\"\\nIdentified Outliers:\")\n",
        "print(outliers)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 877
        },
        "id": "SuHYKqRZBYxQ",
        "outputId": "255b358d-dbd5-45e4-ca17-161b035ae149"
      },
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:matplotlib.legend:No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Descriptive Statistics for Temperature:\n",
            "count    8784.000000\n",
            "mean        8.798144\n",
            "std        11.687883\n",
            "min       -23.300000\n",
            "25%         0.100000\n",
            "50%         9.300000\n",
            "75%        18.800000\n",
            "max        33.000000\n",
            "Name: Temp_C, dtype: float64\n",
            "\n",
            "Identified Outliers:\n",
            "Empty DataFrame\n",
            "Columns: [Temp_C, Dew Point Temp_C, Rel Hum_%, Wind Speed_km/h, Visibility_km, Press_kPa, Weather]\n",
            "Index: []\n"
          ]
        }
      ]
    },
    {
      "source": [
        "sfrom matplotlib import pyplot as plt\n",
        "import seaborn as sns\n",
        "def _plot_series(series, series_name, series_index=0):\n",
        "  from matplotlib import pyplot as plt\n",
        "  import seaborn as sns\n",
        "  palette = list(sns.palettes.mpl_palette('Dark2'))\n",
        "  xs = series['Date/Time']\n",
        "  ys = series['Dew Point Temp_C']\n",
        "\n",
        "  plt.plot(xs, ys, label=series_name, color=palette[series_index % len(palette)])\n",
        "\n",
        "fig, ax = plt.subplots(figsize=(10, 5.2), layout='constrained')\n",
        "df_sorted = _df_11.sort_values('Date/Time', ascending=True)\n",
        "for i, (series_name, series) in enumerate(df_sorted.groupby('Weather')):\n",
        "  _plot_series(series, series_name, i)\n",
        "  fig.legend(title='Weather', bbox_to_anchor=(1, 1), loc='upper left')\n",
        "sns.despine(fig=fig, ax=ax)\n",
        "plt.xlabel('Date/Time')\n",
        "_ = plt.ylabel('Dew Point Temp_C')"
      ],
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 548
        },
        "id": "mI28mRjawLsP",
        "outputId": "fcc270be-7a4d-4ced-bcc5-c582f82231b2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x520 with 1 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "source": [
        "from matplotlib import pyplot as plt\n",
        "import seaborn as sns\n",
        "def _plot_series(series, series_name, series_index=0):\n",
        "  from matplotlib import pyplot as plt\n",
        "  import seaborn as sns\n",
        "  palette = list(sns.palettes.mpl_palette('Dark2'))\n",
        "  xs = series['Date/Time']\n",
        "  ys = series['Rel Hum_%']\n",
        "\n",
        "  plt.plot(xs, ys, label=series_name, color=palette[series_index % len(palette)])\n",
        "\n",
        "fig, ax = plt.subplots(figsize=(10, 5.2), layout='constrained')\n",
        "df_sorted = _df_13.sort_values('Date/Time', ascending=True)\n",
        "for i, (series_name, series) in enumerate(df_sorted.groupby('Weather')):\n",
        "  _plot_series(series, series_name, i)\n",
        "  fig.legend(title='Weather', bbox_to_anchor=(1, 1), loc='upper left')\n",
        "sns.despine(fig=fig, ax=ax)\n",
        "plt.xlabel('Date/Time')\n",
        "_ = plt.ylabel('Rel Hum_%')"
      ],
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 548
        },
        "id": "pQlsgChewKaP",
        "outputId": "fbbd7352-99a7-4f99-9ffa-f03a86f1c09c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x520 with 1 Axes>"
            ],
            "image/png": 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6Otu26OjobLde/Tur1Sqr1ZpPRwUAAADknclkknfLQXKv1VHRH49QUsRaXV4xRYm71yhg+EdyCaxldEQAAIoMQye8kpOTr5vUslgsOd6u1MfHR35+fjp27JjCw8PVq1evG+63VatWWr9+fbZtP//8s1q1apU/wQEAAIAC4uRbXoGjV8t/2GKZ3byVevJ3Rb7cVNd+WCiH3WZ0PAAAigRDC68ePXpo9uzZWrt2rU6fPq1Vq1ZpwYIF6tOnT9aa5cuXa+PGjTp58qRWr16t+++/X71799YDDzyQtebxxx/XpEmTsp4///zz+uGHHzR//nwdPnxY06dPV3h4uEaOHHlXjw8AAAC4HSaTST7tnlDwK/vkXu9+OTJSdenL8Tr32r1KjzlhdDwAAAo9Qwuvt99+W/3799ezzz6r2rVra/z48RoxYoRmzZqVtebixYt67LHHVKtWLY0aNUqPPfaYvvjii2z7OXPmTLaL2Ldu3Vqff/653n//fTVs2FArVqzQN998o3r16t21YwMAAADulHOZIFUYt07lhvxHJquHUo6GKfKlRor95T9y5HBWBAAA+JPJ4XA4jA5R2MTHx8vHx0dxcXHy9vY2Og4AAACgjEunFLV4uFIOb5QkudW+VwHDPpRz2WBjgwEwTFxcnCIjI1WtWjW5u7sbHadQs9vtSktLk9Vqzdeb4OHuSk1N1alTpxQSEiJXV9ebruW7DAAAABQBzn4hqvjCz/Ib/KZMLm5KOfSrIl9qqLhNH4q/wwYAIDsKLwAAAKCIMJnNKnX/SAXP3CPXaq1lT01Q9McjdH5hd2VcO290PAAACg0KLwAAAKCIcQmorqDJG1X24bkyOVmVvO8HRU5poPgt/2XaC0CR0L9/f5lMpuseBw4cMDoaigkKLwAAAKAIMpktKt1trCrN3CVryD2yJ8cq6oMndOGtvsqMjTI6HgDcUrt27XTmzJlsj5o1axodC8UEhRcAAABQhFkDa6vSS2Eq0+8VyeKspD1rdPqlBkr4/SujowHATVmtVgUFBWV7ODk5ad26dWrQoIFcXFzk5+en5557ThkZGVnvi42NVa9eveTm5iY/Pz/NnDlTzZs317Bhwww8GhQ2TkYHAAAAAHBnTBYnlekxSZ6NHlLUB0OVdmavLr77DyWEfy3/x/8ti1dZoyMCuAvsdruSMtIN+WwPZ5d8ufvhqVOn1LdvXw0YMECffvqp9u/fr3/9619ydXXV/PnzJUnPPPOMwsPD9dVXXykwMFCTJ0/WwYMHVb9+/Tv+fBQfFF4AAABAMWENaqBK07bpyrev6uq3rypx5wqlHPlN/kPelWfT3kbHA1DAkjLSVfvz6YZ89qF/TJeX1TVP79mwYYPc3d2znnfo0EHVq1dXQECAPvnkE5nNZjVq1Ejnz5/XzJkz9frrryshIUErV67UBx98oJ49e0qSvvjiC1WsWDFfjwdFH4UXAAAAUIyYnFxUts90eTbuoagPhir9/AFdeLufvFoNVrlH35TFo5TREQFAktSiRQu9//77Wc89PT311FNPqWnTptmmxTp06KDk5GSdPHlSV65cUWZmptq0aZP1epkyZRQSEnJXs6Pwo/ACAAAAiiHXyk1VafpOXVk1XdfWzVPCts+UfGiDAp58Xx4NuhkdD0AB8HB20aF/TDfss/PK3d1ddevWLYA0AIUXAAAAUGyZna3yGxgqzya9FPXhUGVEHdX5Bd3l3f5J+T0yTxZ3H6MjAshHZrM5z6cVFja1atXSt99+K7vdnjXltWnTJnl4eKhKlSry8/OTk5OTtm7dqurVq0uSrly5otOnT6tVq1ZGRkchw10aAQAAgGLOrVpLBc/YJd8uoyWTSfG/faTIlxoq6cAvRkcDgGzGjBmjqKgoDR06VHv37tXnn3+u1157TSNGjJDFYpGvr6/69eunKVOm6LvvvtOuXbs0ePBgmc1mmUwmo+OjEKHwAgAAAEoAs9Vd5QbNV8WJv8rZr4oyr57V+bldFP3pc7KnJhodDwAkSSEhIfr666+1Z88eNW/eXM8//7z+8Y9/6LXXXstas2jRIjVt2lQDBgxQ165d1bp1a1WpUkWurkV7ug35y+RwOBxGhyhs4uPj5ePjo7i4OHl7exsdBwAAAMhX9tREXVo2UXG/vitJcvarIv/hi+Ves73ByQDkRVxcnCIjI1WtWrVsdzssaeLj41WhQgXNmjVLo0ePznGN3W5XWlqarFZrtgvio2hJTU3VqVOnFBIScsuCk+8yAAAAUMKYXT3l//g7qjDhRzmVqaSMSyd17rV7FfP5WNnTko2OBwA3tXXrVr3//vs6ePCgtmzZon79+kmSHn74YYOToTCh8AIAAABKKI+6nRX8SoS82z8pORyK/elNRb7cVCnHtxkdDQBu6s0331SzZs304IMPKjk5WevXr1f58uWNjoVChFMac8ApjQAAAChpEiO+V/THI2SLvSCZzCrVbZzK9J4uswvXxAEKK05pzD1OaSweOKURAAAAQJ54NnxQlWfvk1erwZLDrmvfz9WZ6fco9fQuo6MBAJBnFF4AAAAAJEkWj1IqP+JTBf5rpSze5ZR+4aDOzGyly1+/LEdmutHxAADINQovAAAAANl4Nu2tyrP/kGfzAZLdpqtrXtGZma2Udnaf0dEA/I2Tk5OkP0/Xw8399TUymUwGJ8Hd4mR0AAAAAACFj8WrrAKf/VIJzfoq+tORSjuzV5HTm6tMr2kq/dALMln4VQIwmsVikdlsVmZmpjIzM7k21Q3Y7XZlZGTIYrFQeJUg/CkFAAAA4Ia8mg+UW80Oiv7kGSXtWaMrX09V4p41CnjqY1kDaxsdDyjx/iq9MjIyjI5SqFksFjk7OxsdA3cRhRcAAACAm3Ly8VfgqK+VsO0zxSx9XmmndurMtKYq02+WSnUZLZPZYnREoERzcXGR1WqVw+EwOkqhZDKZmOwqgZh3BAAAAHBLJpNJ3q0fVfDsfXJv0FWOzDRd/uoFnX21o9KjjhkdDyjxTCaTzGYzjxweuSm7KleurDfeeKPgv1F3aPr06WrUqFG+7KuoHPPtovACAAAAkGvOpSqowpjv5D/0fZldvZR6fKsipzXWtZ/floMLZwPIhSeeeCJr6urvj+PHjxuWaefOnXr66acL/HMqV66cdbxubm6qXLmyBg4cqF9//TVX7x8/frzWr19fwClzL6fvY9u2bY2OJYnCCwAAAEAemUwm+XQYpuBXIuRe5z450lN06bPROvf6/cq4dMroeACKgK5du+rixYvZHiEhIdetS09Pvyt5/Pz85O7uflc+a+bMmbp48aKOHDmiTz/9VL6+vurcubNmz559w/c4HA5lZmbK09NTZcqUuSs5c+vjjz/O9n1cs2aN0ZEkUXgBAAAAuE3OZYNVYfwPKvfYOzK5uCvl8EadntpIsRve41pCAG7KarUqICAg28Nisahjx44aOXKkRo8erbJly6pLly6SpP3796tbt27y9PSUv7+/HnvsMV2+fDlrf3a7XaGhoQoJCZGbm5saNmyoFStWZL1+o6myjRs3Srr+9D6TyaQPP/xQffr0kbu7u6pXr35dkbNmzRpVr15drq6u6tSpk5YsWSKTyaTY2NibHruXl5cCAgJUqVIltW/fXu+//76mTp2qadOm6ciRI5KkjRs3ymQyad26dWratKmsVqvCwsKuO6Uxp2OqXLlyro75f8XGxmr48OHy8/OTt7e37r33XkVERNz0WCTJ19c32/exdOnSWd+TmTNnqmLFirJarWrUqJF++OGHbO/dunWrGjVqJFdXVzVr1kzffPONTCaT9u7de8vPvRUKLwAAAAC3zWQ2y/e+fyr4lb1yq9FOjtRExSx5VufndVXGlbNGxwNKFIfDIXtakiGP/Cy5lyxZIhcXF23ZskWLFi1SbGys7r33XjVu3Fjh4eH64YcfFB0drYEDB2a9JzQ0VJ9++qkWLVqkAwcOaMyYMXr00Ue1adMmSdKbb76ZbQrp+eefV7ly5VSrVq0b5pgxY4YGDhyoffv26cEHH9TgwYN19epVSdKpU6fUv39/9e7dWxERERoxYoSmTJly28f8/PPPy+FwaPXq1dm2T5w4Ua+99poOHTqkBg0aXPe+vx/T8ePHVa1aNbVv3/62jnnAgAGKiYnRunXrtGvXLjVp0kT33Xdf1jHn1Ztvvqn58+dr3rx52rdvn7p06aKePXvq2LE/r/sYHx+vHj16qH79+tq9e7dmzZqlF1988bY+KyfcpREAAADAHXMpV1UVJ/6q2J/f0uUVU5R84BdFvtRAfv9YIO+2T3CHNOAucKQn6/gIb0M+u9p78TJZPXK9/rvvvpOnp2fW827dumn58uWSpOrVq+v111/Peu2VV15R48aN9eqrr2Zt++ijjxQUFKSjR48qODhYr776qn755Re1atVKklSlShWFhYXpvffeU4cOHeTj4yMfHx9J0tdff6333ntPv/zyiwICAm6Y8YknntCgQYMkSa+++qreeust7dixQ127dtV7772nmjVrau7cuZKkmjVrav/+/Tc9LfFmSpcurXLlyun06dPZts+cOVP333//Dd/3V36Hw6F+/frJx8dH7733niTl6ZjDwsK0Y8cOxcTEyGq1SpLmzZunb775RitWrLjp9c0GDRoki+X/7ta7dOlS9e7dW/PmzdOLL76oRx55RJI0Z84cbdiwQW+88Yb+/e9/6/PPP5fJZNIHH3wgV1dX1alTR+fPn9dTTz2Vi6/YrVF4AQAAAMgXJrNZpbqMlkeDbor6YKhST/6u6MXDlRi+Sv5D35OTb3mjIwIoJDp16qR3330367mHx/+VZU2bNs22NiIiQhs2bMhWkP3lxIkTysjIUHJy8nXFUHp6uho3bpxt2549e/TYY4/pnXfeUZs2bW6a8e8TVR4eHvL29lZMTIwk6ciRI7rnnnuyrW/evPlN93crDofjur8caNasWa7eO3nyZG3btk3h4eFyc3PL9lpujjkiIkKJiYnXXR8sJSVFJ06cuOlnL1y4UJ07d856Xr58ecXHx+vChQvXfV6bNm2yTpM8cuSIGjRoIFdX16zX7/Rr+HcUXgAAAADylUv5mgqa8puurZuvK99MV1LEWp2eUl/lHn1LXi0HMe0FFBCTi7uqvRdv2GfnhYeHh6pVq3bD1/4uMTFRPXr00Jw5c65bW758ee3fv1+StHbtWlWoUCHb639NK0lSVFSUevbsqeHDh2vYsGG3zOjs7Jztuclkkr2A7kZ75coVXbp06boL9//v1yInS5cu1cKFC7Vx48brjj+3x5yYmKjy5cvneH0vX1/fm35+QEDAdd/L+Hhjfg7/jsILAAAAQL4zWZxUuvuL8mj0kKI+GKq0yN2Keu8xJYZ/rXJD/iMn73JGRwSKHZPJlKfTCouKJk2aaOXKlapcubKcnK6vMerUqSOr1aozZ86oQ4cOOe4jNTVVvXr1Uq1atbRgwYI7zlSzZk19//332bbt3Lnztvf35ptvymw2q3fv3nl637Zt2zR8+HC99957atmyZbbX8nLMTZo0UVRUlJycnLIuen8nvL29FRgYqC1btmT7nmzZsiVriqtmzZpaunSp0tLSsorJO/ka/i8uWg8AAACgwFgr1lOlqVtVps90yeKkxF2rFDmlvhJ2rjQ6GoAi4rnnntPVq1c1aNAg7dy5UydOnNCPP/6ooUOHymazycvLS+PHj9eYMWO0ZMkSnThxQrt379bbb7+tJUuWSJJGjBihs2fP6q233tKlS5cUFRWlqKgopaen31amESNG6PDhw3rxxRd19OhRLVu2TJ988okk3XKKNSEhQVFRUTp79qx+++03Pf3003rllVc0e/bsG0695SQqKkp9+vTRI488oi5dumQd06VLl/J8zJ07d1arVq3Uu3dv/fTTTzp9+rS2bt2qKVOmKDw8PPdfmL+ZMGGC5syZo6+++kpHjhzRxIkTtXfvXj3//POSpH/84x+y2+16+umndejQIf3444+aN2+epFt/DXODwgsAAABAgTI5OatMr6mqNG27XCrWly3hsi7+e6AuLhosW+IVo+MBKOT+mhSy2Wx64IEHVL9+fY0ePVq+vr4ym/+sNWbNmqWpU6cqNDRUtWvXVteuXbV27dqsUwQ3bdqkixcvqk6dOipfvnzWY+vWrbeVKSQkRCtWrNDXX3+tBg0a6N133826S+PfT6PMybRp01S+fHlVq1ZNjz32mOLi4rR+/fo836Hw8OHDio6O1pIlS7Id01/XFsvLMZtMJn3//fdq3769hg4dqho1auiRRx5RZGSk/P39JUmnT5+WyWTK8bTHnIwaNUpjx47VuHHjVL9+ff3www9as2aNqlevLunPKbBvv/1We/fuVaNGjTRlyhRNmzZNkrJd1+t2mRz5ee/QYiI+Pl4+Pj6Ki4uTt7cxd7gAAAAAiiN7Rpqurp6lq2vnSA67LD4B8n9ikTwb9zA6GlDkpKam6tSpUwoJCcmXggB3Zvbs2Vq0aJHOnj1rdJQCsWHDBvXt21cnT55UqVKlCuQzPvvsMw0dOlRxcXHXXXxfytvPPNfwAgAAAHDXmJ2tKtv/FXk06anoD4Yq/eJhXXizt7zbPC6/fyyUxcPX6IgAkCv/+c9/dM8996hMmTLasmWL5s6dq5EjRxodq8B8//33mjx5cr6WXZ9++qmqVKmiChUqKCIiQi+++KIGDhyYY9mVVxReAAAAAO46tyrNVWnGLl35epqu/bhA8Vs+VfKhX+U/9H151O9idDwAuKVjx47plVde0dWrV1WpUiWNGzdOkyZNMjpWgZk7d26+7zMqKkrTpk1TVFSUypcvrwEDBmj27Nn5sm9OacwBpzQCAAAAd0/KsS2K+vBJZUQflyT5dHxKfg/PldnNy+BkQOHGKY0oafLyM89F6wEAAAAYyq16GwXP3C3fzn+eChS38QOdntpIyYc2GJwMAFBUUXgBAAAAMJzZ6qFyj76pii/+IqeylZV5+bTOzemsmKXPy56WZHQ8oFDjxC2UFHn5WafwAgAAAFBouNfupMqz9sqn41OSpNhf3lHktCZKObbF4GRA4ePs7CxJSk5ONjgJcHf89bP+18/+zXANrxxwDS8AAADAeEl//Kjoj55S5rXzksmkUl3GqkzfmTK7cK0i4C8XL15UbGysypUrJ3d3d5lMJqMjAfnO4XAoOTlZMTEx8vX1Vfny5W/5HgqvHFB4AQAAAIWDLSlWl74Yq/iwJZIkl/K15P/Ux3Kr0tzgZEDh4HA4FBUVpdjYWKOjAAXO19dXAQEBuSp2KbxyQOEFAAAAFC6Je75V9CfPyBYXJZktKv3gCyrda6rMzlajowGFgs1mU0ZGhtExgALj7Owsi8WS6/UUXjmg8AIAAAAKH1viFcUsHaWE7V9Kklwq1lfAUx/LNbixwckAAIUNF60HAAAAUCRYPMuo/DOfqfxzy2TxKqv0c3/ozMyWuvLNTDkymWwBAPwfJrxywIQXAAAAULhlxscoZsmzSty1SpJkDW6igKc+lrViPYOTAQAKAya8AAAAABQ5Tt7lVH7kcgWM+K/MHqWUFrlbZ6bfo6vfzZHDlml0PACAwZjwygETXgAAAEDRkXntgqI/GaGkiO8lSa5VWijgqY/lUr6mwckAAEZhwgsAAABAkeZUKlCBo9fIf9iHMrt5K/Xk74qc1kTXfnxDDrvd6HgAAAMw4ZUDJrwAAACAoinjyllFfzRcyQd+kSS51Wgn/+GL5VKuqsHJAAB3ExNeAAAAAIoN5zJBqjD+B5Ub8h+ZrB5KObpZkS81Uuz6d5n2AoAShAmvHDDhBQAAABR9GZdOKWrxcKUc3ihJcq9zn/yf/EDOZYONDQYAKHBMeAEAAAAolpz9QlTxhZ/lN/hNmVzclHxwvSJfaqi4TR+Kv/cHgOKNCa8cMOEFAAAAFC/pUccU9eGTSj2+VZLk3qCr/Ie+L+dSFQxOBgAoCEx4AQAAACj2XAKqK2jyRpV9+HWZnKxK3veDIqc0UPyW/zLtBQDFEBNeOWDCCwAAACi+0s4fVNSHTyrt1E5JkkfjnvJ/YpGcfPwNTgYAyC9MeAEAAAAoUawV6qjSS2Eq03eWZHFW0p41Oj2lvhJ2LDM6GgAgnzDhlQMmvAAAAICSIe1MhKI+GKq0sxGSJM/mA+T/2DuyeJU1OBkA4E4w4QUAAACgxLJWaqhKL29X6Z4vSWaLEncs1+kp9ZW4e7XR0QAAd4AJrxww4QUAAACUPKmnwhX1wVClXzgoSfJq/ajKDX5DFo9SBicDAOSVoRNeNptNU6dOVUhIiNzc3FS1alXNmjUr211SEhMTNXLkSFWsWFFubm6qU6eOFi1adNP9fvLJJzKZTNkerq6uBX04AAAAAIow15BmqjR9p0o9+IJkMith61KdntJASfvWGR0NAJBHTkZ++Jw5c/Tuu+9qyZIlqlu3rsLDwzV06FD5+Pho1KhRkqSxY8fq119/1dKlS1W5cmX99NNPevbZZxUYGKiePXvecN/e3t46cuRI1nOTyVTgxwMAAACgaDO7uMpvYKg8m/RU1IdPKiPqqM4v6C7v9k/Kb9B8Wdw4AwQAigJDJ7y2bt2qXr166aGHHlLlypXVv39/PfDAA9qxY0e2NUOGDFHHjh1VuXJlPf3002rYsGG2NTkxmUwKCAjIevj7c4thAAAAALnjVq2Vgmfsku8Dz0smk+J/+0iRLzVU8sH1RkcDAOSCoYVX69attX79eh09elSSFBERobCwMHXr1i3bmjVr1uj8+fNyOBzasGGDjh49qgceeOCm+05MTFRwcLCCgoLUq1cvHThw4IZr09LSFB8fn+0BAAAAoGQzW91V7h8LVHHir3L2C1HmlTM69/oDiv70OdlTE42OBwC4CUMLr4kTJ+qRRx5RrVq15OzsrMaNG2v06NEaPHhw1pq3335bderUUcWKFeXi4qKuXbvq3//+t9q3b3/D/dasWVMfffSRVq9eraVLl8put6t169Y6d+5cjutDQ0Pl4+OT9QgKCsr3YwUAAABQNLnXbK/gWXvlc+8zkqS4XxcpcmpjJR/5zeBkAIAbMfQujV9++aUmTJiguXPnqm7dutq7d69Gjx6tBQsWaMiQIZKkefPm6YMPPtC8efMUHBys3377TZMmTdKqVavUuXPnXH1ORkaGateurUGDBmnWrFnXvZ6Wlqa0tLSs5/Hx8QoKCuIujQAAAACySTrwi6IXD1fm1bOSySTf+0epbP/ZMru4GR0NAPA3hhZeQUFBmjhxop577rmsba+88oqWLl2qw4cPKyUlRT4+Plq1apUeeuihrDXDhw/XuXPn9MMPP+T6swYMGCAnJyd98cUXt1wbHx8vHx8fCi8AAAAA17Elx+nSF+MUv/ljSZJzQA0FDP9YbtVaGpwMAPAXQ09pTE5OltmcPYLFYpHdbpf052RWRkbGTdfkhs1m0x9//KHy5cvfeWgAAAAAJZrF3UcBwz5U4Og1sviWV0bUUZ2d3U6Xlk2SPSPt1jsAABQ4QwuvHj16aPbs2Vq7dq1Onz6tVatWacGCBerTp48kydvbWx06dNCECRO0ceNGnTp1Sp988ok+/fTTrDWS9Pjjj2vSpElZz2fOnKmffvpJJ0+e1O7du/Xoo48qMjJSw4cPv+vHCAAAAKB48mz0kCrP/kNerQZLDruuff+6zky/R6mndxkdDQBKPENPaUxISNDUqVO1atUqxcTEKDAwUIMGDdK0adPk4uIiSYqKitKkSZP0008/6erVqwoODtbTTz+tMWPGyGQySZI6duyoypUr65NPPpEkjRkzRl9//bWioqJUqlQpNW3aVK+88ooaN26cq1yc0ggAAAAgLxJ3faPoJf+ULT5GMltUusdklekxWSYnF6OjAUCJZGjhVVhReAEAAADIK1vCZUV/+pwSd66QJFkrNVLAUx/LGtTA4GQAUPIYekojAAAAABQXFq+yCnzuK5V/9guZPcso7cxeRU5vritrXpXDlml0PAAoUZjwygETXgAAAADuRGZslKKX/FNJe9ZIkqwh9/w57RVY2+BkAFAyMOEFAAAAAPnMyTdAgaO+VsBTn8js5qO0Uzt1ZlpTXV03Xw67zeh4AFDsMeGVAya8AAAAAOSXjGvnFf3RU0r+40dJkmv1NgoYtlguAdUNTgYAxRcTXgAAAABQgJxLVVCFsWvlP/Q9mV29lHpsiyKnNda1n9+Rw243Oh4AFEtMeOWACS8AAAAABSHjcqSiFg9XyqFfJUlutToqYNiHcvYLMTgZABQvTHgBAAAAwF3iXDZYFSf8qHKPvi2Ti7tSDm/U6amNFLvhPTGLAAD5hwmvHDDhBQAAAKCgpUcfV/TiYUo5GiZJcq93v/yHfiDnMkEGJwOAoo8JLwAAAAAwgIt/NVWc+Kv8Bs2XydlVyft/VuRLDRS3+ROmvQDgDjHhlQMmvAAAAADcTekXDivqwyeVevJ3SZJHw4fkP/Q9OfmWNzgZABRNTHgBAAAAgMFcAmspaMpvKtv/VZmcXJQUsVanp9RX/PYvmPYCgNvAhFcOmPACAAAAYJS0c/sV9cETSovcI0nybNZX5R7/t5y8yxmcDACKDia8AAAAAKAQsVasp0pTt6lM75cli5MSw79W5JQGSti50uhoAFBkMOGVAya8AAAAABQGqad3K+rDJ5V+7g9JklfLR1Tu0bdl8SxtcDIAKNyY8AIAAACAQsq1chNVevl3le4+STKZlbD9S52eUl+Je78zOhoAFGpMeOWACS8AAAAAhU3KyR2K/mCo0i8eliR5tx0iv38slMXdx+BkAFD4MOEFAAAAAEWAW5XmqjQjXKW6jpVMJsWHLVHkSw2UtP8no6MBQKHDhFcOmPACAAAAUJilHA1T1IdPKiPmhCTJp+PT8nv4dZndvAxOBgCFAxNeAAAAAFDEuNVoq+BZe+R733OSpLiN7+v01EZKPrTR2GAAUEgw4ZUDJrwAAAAAFBXJhzYo6sNhyrwSKUny7TxSZQeEymx1NzgZABiHwisHFF4AAAAAihJ7SoIufTVBcRs/kCQ5+1dTwPCP5Va9tcHJAMAYFF45oPACAAAAUBQl/fGjoj96SpnXzksmk0p1GasyfWfK7OJqdDQAuKsovHJA4QUAAACgqLIlxerS52MUv+VTSZJLYG0FDP9YrlXuMTgZANw9FF45oPACAAAAUNQl7lmj6I+fkS0+WjJbVPrBF1S611SZna1GRwOAAkfhlQMKLwAAAADFgS3ximL++y8l/P6VJMmlYn0FPPWJXIMbGRsMAAqY2egAAAAAAICCYfEso/L//Fzln/tKFq+ySj/3h87MbKErq2fJkZlhdDwAKDBMeOWACS8AAAAAxU1mfIxilvxTibu+kSRZKzdVwFMfy1qhrrHBAKAAMOEFAAAAACWAk3c5lR+5QgEj/iuzRymlnd6lMy8309W1r8thtxkdDwDyFRNeOWDCCwAAAEBxlnntgqI/GaGkiO8lSa5VWypg+EdyKV/T4GQAkD+Y8AIAAACAEsapVKACR6+R/7APZXbzVuqJ7Yqc1kTXfnxTDrvd6HgAcMeY8MoBE14AAAAASoqMK2cU/dFTSj7wiyTJrUY7+Q9fLJdyVQ1OBgC3jwkvAAAAACjBnMtUUoXxP6jckP/IZPVQytHNipzaWLHr32XaC0CRxYRXDpjwAgAAAFASZVw6pagPhynlyCZJknud++Q/7EM5l6lkcDIAyBsmvAAAAAAAkiRnvxBVfPEX+Q1+QyYXNyUfXK/IKQ0Ut2mxmJUAUJQw4ZUDJrwAAAAAlHTpUUcV9eGTSj2+TZLk0aCb/Ie+L6dSgQYnA4BbY8ILAAAAAHAdl4AaCpq8SWUHzpHJyaqkfet0ekp9xW9dyrQXgEKPCa8cMOEFAAAAAP8n7fxBRX04VGmnwiVJHk16yX/Iu3Ly8Tc4GQDkjAkvAAAAAMBNWSvUUaWXtqhM35mSxVlJu1fr9JT6Stix3OhoAJAjJrxywIQXAAAAAOQs7UyEoj4YqrSzEZIkr+YDVe6xt2XxKmtwMgD4P0x4AQAAAAByzVqpoSq9vF2le74kmS1K2LFMp6c0UOLu1UZHA4AsTHjlgAkvAAAAALi11FPhivpgqNIvHJQkebV+VOUGvyGLRymDkwEo6ZjwAgAAAADcFteQZqo0fadKPThBMpmVsHWpTk9poKR964yOBqCEY8IrB0x4AQAAAEDepBzfpqgPhioj+pgkybv9k/IbNF8WN36nAnD3MeEFAAAAALhjbtVaKXjmbvneP0qSFP/bR4p8qaGSD643OBmAkogJrxww4QUAAAAAty/58CZFLx6mjEunJEk+9/5TfgNfk9nV0+BkAEoKCq8cUHgBAAAAwJ2xpybq0lcvKG7De5IkZ78q8h/+kdxrtjM4GYCSgMIrBxReAAAAAJA/kvb/rOiPnlLm1bOSySTfB55X2X6vyOziZnQ0AMUYhVcOKLwAAAAAIP/YkuN06Ytxit/8sSTJOaCmAp76WG5VWxicDEBxReGVAwovAAAAAMh/iXvXKvqTEbLFXpRMZpV6cILK9H5ZZmer0dEAFDMUXjmg8AIAAACAgmFLvKqYz0YrYdtnkiSXCnUV8NTHcq3c1OBkAIoTCq8cUHgBAAAAQMFK2LVKMUuelS0+RjJbVLrHZJXpMVkmJxejowEoBii8ckDhBQAAAAAFLzP+kmL+O1KJO1dIkqyVGingqU9kDapvcDIARZ3Z6AAAAAAAgJLJydtPgc99pfL//Fxmj9JKO7NXkdPv0ZVvQ+WwZRodD0ARxoRXDpjwAgAAAIC7KzM2StFLnlHSnm8lSa5Vmst/+EeyBtY2OBmAoogJLwAAAACA4Zx8AxQ4apUCnvpYZjcfpZ7coTPTmurqugVy2G1GxwNQxDDhlQMmvAAAAADAOBlXzyn6o6eUvP8nSZJr9TYKGP6RXPyrGZwMQFHBhBcAAAAAoFBxLl1RFcZ9r3JPLJLJ1VOpx7YocmojXfv5HTnsdqPjASgCmPDKARNeAAAAAFA4ZFw6raiPhivl0AZJklvtTgp48kM5+1U2NhiAQo0JLwAAAABAoeXsV1kVJ/ykco++LZOLu1IObdDpqQ0Vu/F9Mb8B4EaY8MoBE14AAAAAUPikRx9X9OJhSjkaJklyr/eA/J/8QM6lKxqcDEBhY+iEl81m09SpUxUSEiI3NzdVrVpVs2bNytbSJyYmauTIkapYsaLc3NxUp04dLVq06Jb7Xr58uWrVqiVXV1fVr19f33//fUEeCgAAAACggLn4V1PFib/K75F5MjlZlbz/J0VOaaC4zZ8w7QUgG0MLrzlz5ujdd9/VO++8o0OHDmnOnDl6/fXX9fbbb2etGTt2rH744QctXbpUhw4d0ujRozVy5EitWbPmhvvdunWrBg0apGHDhmnPnj3q3bu3evfurf3799+NwwIAAAAAFBCT2aJSXccoeOZuuVZpLntKnKIXD9OFN3srM/ai0fEAFBKGntLYvXt3+fv7a/HixVnb+vXrJzc3Ny1dulSSVK9ePT388MOaOnVq1pqmTZuqW7dueuWVV3Lc78MPP6ykpCR99913WdtatmypRo0a5Wo6jFMaAQDIvcSMNL2y83s9XL2ZGvsFGR0HAFCCOGyZurZuni6vmi7ZMmT2KK1yj70lrxaPyGQyGR0PgIEMnfBq3bq11q9fr6NHj0qSIiIiFBYWpm7dumVbs2bNGp0/f14Oh0MbNmzQ0aNH9cADD9xwv9u2bVPnzp2zbevSpYu2bduW4/q0tDTFx8dnewAAgFvbcvGEOn+zUEuP/K5xYctl41bxAIC7yGRxUunuExU8faeswY1lT7qqqEWPKi1yj9HRABjMycgPnzhxouLj41WrVi1ZLBbZbDbNnj1bgwcPzlrz9ttv6+mnn1bFihXl5OQks9msDz74QO3bt7/hfqOiouTv759tm7+/v6KionJcHxoaqhkzZuTPQQEAUAIkZ6Tr1V3r9MmhP/8yKcizlF5p2UsWMzeABgDcfdag+qo0dZuufheqzPgYuVZuYnQkAAYztPBatmyZPvvsM33++eeqW7eu9u7dq9GjRyswMFBDhgyR9GfhtX37dq1Zs0bBwcH67bff9NxzzykwMPC6Ka7bNWnSJI0dOzbreXx8vIKCOCUDAICc7Iw+rTGbl+t0whVJ0qM1W+ilex6Up7PV4GQAgJLM5OSsMr2ncfF6AJIMLrwmTJigiRMn6pFHHpEk1a9fX5GRkQoNDdWQIUOUkpKiyZMna9WqVXrooYckSQ0aNNDevXs1b968GxZeAQEBio6OzrYtOjpaAQEBOa63Wq2yWvmfdAAAbiYlM0Pzdv+k9w+EySGHyrv7aF7bfupQoYbR0QAAyMK1uwBIBl/DKzk5Web/OfXBYrHI/v+v/5GRkaGMjIybrslJq1attH79+mzbfv75Z7Vq1SqfkgMAULLsuXRW3da8pfcObJZDDg2s1lS/9B5N2QUAAIBCydAJrx49emj27NmqVKmS6tatqz179mjBggV68sknJUne3t7q0KGDJkyYIDc3NwUHB2vTpk369NNPtWDBgqz9PP7446pQoYJCQ0MlSc8//7w6dOig+fPn66GHHtKXX36p8PBwvf/++4YcJwAARVWaLVNv7F2vf/+xUXaHQ+XcvPR6m77qHFTb6GgAAADADZkcBp7gnJCQoKlTp2rVqlWKiYlRYGCgBg0apGnTpsnFxUXSnxegnzRpkn766SddvXpVwcHBevrppzVmzJisUdWOHTuqcuXK+uSTT7L2vXz5cr300ks6ffq0qlevrtdff10PPvhgrnLFx8fLx8dHcXFx8vb2zvfjBgCgKNh/5bxGb16uw9f+vOlL7yqNNKtlT5WyuhucDAAAALg5QwuvworCCwBQkmXYbXo7YoPeivhVmQ67yrh6KLRVHz1YuZ7R0QAAAIBcMfSURgAAULgcvhalMZuX648r5yVJDwbXU2jr3irj6mlwMgAAACD3KLwAAIAy7TYt2r9ZC/b8rHS7Tb5Wd81u2Us9QxpwtysAAAAUORReAACUcCfiLmn05mXac+msJOn+oNp6rXUf+btzWj8AAACKJgovAABKKLvDrsUHt+i1XT8qzZYpbxdXzWjeQ/2rNWGqCwAAAEUahRcAACXQ6fgrGhe2XL9Hn5YkdQisrrlt+yvQw8fYYAAAAEA+oPACAKAEsTvs+u/h3/VK+PdKycyQh5OLpjZ/SINrNGeqCwAAAMUGhRcAACXEucRrGh+2UmEXj0uSWgVU0YK2/RXkVdrgZAAAAED+ovACAKCYczgc+uLYTs3csVaJGWlytThrcrOueqJ2K5lNZqPjAQAAAPmOwgsAgGLsYlKcXtjytTacPyJJalYuWAvaDlAVn7IGJwMAAAAKDoUXAADFkMPh0MoTe/Ty72sUl54qq8VJLzR5QMPrtJXFzFQXAAAAijcKLwAAipmY5ARN2rZKP545KElqWLai3mg3UNV9yxmcDAAAALg7KLwAAChG1pyM0JTtq3UtLVnOZovGNuqsf9ZvLyezxehoAAAAwF1D4QUAQDFwNTVJk7d9o+9O/yFJqlu6vBa2G6g6pcsbnAwAAAC4+yi8AAAo4n6IPKCJW1fpcmqiLCaz/tWwk0Y16CQXC3/MAwAAoGTi/4QBACiiYtOSNe33b/X1iT2SpJq+/lrYboAalK1ocDIAAADAWBReAAAUQb+eO6IJW1YqOjleZpNJ/6zXQWMbd5aVqS4AAACAwgsAgKIkIT1VM3Z8py+PhUuSqvr4aUHbAWparpLByQAAAIDCg8ILAIAiIuzCcY0LW6HzSbEyyaThddvohSZd5ObkbHQ0AAAAoFCh8AIAoJBLykjT7PB1+vTwdklSsFdpLWg7QC0CQgxOBgAAABROFF4AABRi26NOalzYCkUmXJUkDanVUpObdZOHs9XgZAAAAEDhReEFAEAhlJKZoTm7ftDig1vlkEMVPHw1v21/tQ2sZnQ0AAAAoNCj8AIAoJDZFXNGYzYv08n4y5KkQTXu0bR7HpKXi6vByQAAAICigcILAIBCIs2Wqfl7ftai/b/J7nDI391bc9v0070VaxodDQAAAChSKLwAACgE9l0+pzGbl+tIbLQkqV/VxprRood8re4GJwMAAACKHgovAAAMlG7L1Fv7NujtiA2yOewq6+qpOa37qEtwXaOjAQAAAEUWhRcAAAY5ePWixmxepgNXL0qSelRuoNmteqm0q4fByQAAAICi7bYLr8zMTL333nvauHGjbDab2rRpo+eee06urlxQFwCAm8m02/SfPzZp4d71yrDbVMrqrldb9VaPkAZGRwMAAACKhdsuvEaNGqWjR4+qb9++ysjI0Keffqrw8HB98cUX+ZkPAIBi5VhsjEZvXqaIy+ckSV0q1dFrrfvIz83L4GQAAABA8ZHrwmvVqlXq06dP1vOffvpJR44ckcVikSR16dJFLVu2zP+EAAAUAza7XR8cCNPcPT8pzZYpHxdXzWzZS32rNJLJZDI6HgAAAFCsmBwOhyM3C3v06CGLxaL//Oc/CgwM1MCBA+Xj46N+/fopIyNDH3zwgVJSUvTzzz8XdOYCFx8fLx8fH8XFxcnb29voOACAIu5k3GWNDVuu8JhISVKnCjX1epu+Ku/hY3AyAAAAoHjKdeElSV999ZWmTp2qf/3rX3rsscc0a9asbNfwmj59uvz8/Aoy711B4QUAyA92h10fH9qm0PAflGrLkKezVS83765HqjdjqgsAAAAoQHkqvCQpNjZWL7zwgiIiIrRo0SI1bty4oLIZhsILAHCnziRc1biwFdoWdVKS1LZ8Nc1r208VPUsZnAwAAAAo/vJceP3lt99+03PPPaeuXbtq1qxZxerujBReAIDb5XA49NmRHZq1c62SMtPl5uSsl5o9qMdqtZDZZDY6HgAAAFAi5Pr/vM+cOaOBAweqfv36Gjx4sKpXr65du3bJ3d1dDRs21Lp16woyJwAAhd6FxFg9+tNHmrhtlZIy09XCv7J+7jVaQ2q3ouwCAAAA7qJcT3h17NhRAQEBeuKJJ/Tjjz/qxIkTWrNmjSTp0KFDGjFihAICArRs2bICDXw3MOEFAMgLh8Oh5cd36eXfv1VCRpqsFidNatpVT9ZpTdEFAAAAGCDXhZenp6ciIiJUtWpVORwOhYSE6PTp09nWvP/++3r66acLIuddReEFAMit6OR4vbj1a/1y9rAkqYlfJS1sN0BVfYr+TVwAAACAoirXhVeHDh1UsWJFDRkyRL/88osOHTqkb7/9tqDzGYLCCwBwKw6HQ6tPRWjKttWKS0+Ri9micY3v1zP12stiZqoLAAAAMFKuC6/IyEiNGzdOhw4dUqNGjTR37lwFBgYWdD5DUHgBAG7mckqiJm/7Rt9H7pck1S9TQQvbDVCtUgEGJwMAAAAg3cFdGm/ltdde0zPPPCNfX9+C2H2BovACANzI2tN/aPK2b3QlNUlOJrOeb3SvRjboJGezxehoAAAAAP6/Aiu8vL29tXfvXlWpUqUgdl+gKLwAAP/rWlqyXtq+WqtPRkiSapUK0BvtBqhemQoGJwMAAADwv5wKascF1KMBAHDX/XL2kF7Y8rViUhJkMZn1XP0OGt3oPrlYCuyPUQAAAAB3gP9TBwDgBuLTUzX992+17PguSVJ1n3Ja2G6AGvkFGZwMAAAAwM1QeAEAkINN549qfNhKXUyOk0kmPV2vnSY0vl+uTs5GRwMAAABwCxReAAD8TWJGmmbtWKvPju6QJFX2KqOF7QboHv/KxgYDAAAAkGsUXgAA/H9bLp7Q+LAVOpt4TZI0tHZrTWraVe7OLgYnAwAAAJAXBVZ4tWvXTm5ubgW1ewAA8k1yRrpCd/2gjw9tlSQFeZbSvLb91aZ8VYOTAQAAALgdJsdt3k4xJiZGMTExstvt2bY3aNAgX4IZKT4+Xj4+PoqLi5O3t7fRcQAABWhn9GmN2bxcpxOuSJIG12iuqc0fkqez1eBkAAAAAG5Xnie8du3apSFDhujQoUP6qyszmUxyOBwymUyy2Wz5HhIAgPyWmpmhuXt+1vv7N8shhwLcvTWvbX91rFDD6GgAAAAA7lCeC68nn3xSNWrU0OLFi+Xv7y+TyVQQuQAAKDB7Lp3VmM3LdDzukiRpYLWmerl5d/lYORUfAAAAKA7yXHidPHlSK1euVLVq1QoiDwAABSbNlqk39q7Xf/7YJJvDrnJuXprTuo/ur1TH6GgAAAAA8lGeC6/77rtPERERFF4AgCLlwJULen7zMh2+FiVJ6l2lkWa16KFSrh4GJwMAAACQ3/J80frLly9ryJAhat68uerVqydnZ+dsr/fs2TNfAxqBi9YDQPGRYbfpnX0b9ObeX5XpsKuMq4debdVbD1Wub3Q0AAAAAAUkzxNe27Zt05YtW7Ru3brrXuOi9QCAwuTItWiN2bxM+66clyQ9GFxPr7bqrbJungYnAwAAAFCQ8jzhVblyZXXv3l1Tp06Vv79/QeUyFBNeAFC02ex2Ldr/m+bv+Vnpdpt8XNw0u1Uv9QppyM1WAAAAgBIgzxNeV65c0ZgxY4pt2QUAKNpOxF3SmM3LtfvSGUlS56BamtO6r/zd+QsMAAAAoKTIc+HVt29fbdiwQVWrVi2IPAAA3Ba7w66PDm5V6K4flGbLlJezVTNa9NCAak2Z6gIAAABKmDwXXjVq1NCkSZMUFham+vXrX3fR+lGjRuVbOAAAcuN0/BWNC1uu36NPS5I6BFbX3Db9FOjpa2guAAAAAMbI8zW8QkJCbrwzk0knT56841BG4xpeAFA02B12/ffw75odvk7Jmelyd3LRtHse0uCazZnqAgAAAEqwPE94nTp1qiByAACQJ+cTYzUubIXCLh6XJLUKqKL5bfurkldpg5MBAAAAMFqeCy8AAIzkcDj05bFwzdjxnRIz0uRqcdbkZl31RO1WMpvMRscDAAAAUAjkufB68sknb/r6Rx99lOt92Ww2TZ8+XUuXLlVUVJQCAwP1xBNP6KWXXso6FeVGp6S8/vrrmjBhQo6vTZ8+XTNmzMi2rWbNmjp8+HCuswEACp+LSXF6cevX+vXcEUlSs3LBWtB2gKr4lDU4GQAAAIDCJM+F17Vr17I9z8jI0P79+xUbG6t77703T/uaM2eO3n33XS1ZskR169ZVeHi4hg4dKh8fn6yL31+8eDHbe9atW6dhw4apX79+N9133bp19csvv2Q9d3JimA0AiiqHw6GVJ/bo5d/XKC49VVaLkyY0fkBP1W0ri5mpLgAAAADZ5bkFWrVq1XXb7Ha7/vnPf6pq1ap52tfWrVvVq1cvPfTQQ5KkypUr64svvtCOHTuy1gQEBGR7z+rVq9WpUydVqVLlpvt2cnK67r0AgKLnUkqCJm5dpR/PHJQkNSxbUQvbDVANX3+DkwEAAAAorPLlr8XNZrPGjh2rhQsX5ul9rVu31vr163X06FFJUkREhMLCwtStW7cc10dHR2vt2rUaNmzYLfd97NgxBQYGqkqVKho8eLDOnDlzw7VpaWmKj4/P9gAAGO/bU/t076qF+vHMQTmbLXqhyQNa/dA/KbsAAAAA3FS+ned34sQJZWZm5uk9EydOVHx8vGrVqiWLxSKbzabZs2dr8ODBOa5fsmSJvLy81Ldv35vut0WLFvrkk09Us2ZNXbx4UTNmzFC7du20f/9+eXl5Xbc+NDT0umt+AQCMczU1SVO2rda3p/dJkuqULq832g1QndKBBicDAAAAUBSYHA6HIy9vGDt2bLbnDodDFy9e1Nq1azVkyBC98847ud7Xl19+qQkTJmju3LmqW7eu9u7dq9GjR2vBggUaMmTIdetr1aql+++/X2+//XZeIis2NlbBwcFasGBBjtNhaWlpSktLy3oeHx+voKAgxcXFydvbO0+fBQC4Mz9GHtCLW1fpcmqiLCazRjboqOcb3isXC9diBAAAAJA7ef7tYc+ePdmem81m+fn5af78+be8g+P/mjBhgiZOnKhHHnlEklS/fn1FRkYqNDT0usJr8+bNOnLkiL766qu8Rpavr69q1Kih48eP5/i61WqV1WrN834BAPknNi1ZL//+rVae+PPPmRq+5bSw3UA1LFvR4GQAAAAAipo8F14bNmzItw9PTk6W+X/urmWxWGS3269bu3jxYjVt2lQNGzbM8+ckJibqxIkTeuyxx247KwCg4Px67ogmbFmp6OR4mU0mPVOvvcY26ixXJ2ejowEAAAAoggw9P6RHjx6aPXu2KlWqpLp162rPnj1asGDBdZNi8fHxWr58uebPn5/jfu677z716dNHI0eOlCSNHz9ePXr0UHBwsC5cuKCXX35ZFotFgwYNKvBjAgDkXkJ6qmbs+E5fHguXJFXxLquF7Qaoablgg5MBAAAAKMpyXXg1btxYJpPplut2796d6w9/++23NXXqVD377LOKiYlRYGCgRowYoWnTpmVb9+WXX8rhcNywsDpx4oQuX76c9fzcuXMaNGiQrly5Ij8/P7Vt21bbt2+Xn59frrMBAApW2IXjGhe2QueTYmWSScPrttELTR6Qm5OL0dEAAAAAFHG5vmj93+9i6HA4FBoaqmeeeUalS5fOtu7ll1/O34QGiI+Pl4+PDxetB4ACkJSRplfD12nJ4e2SpGCv0prftr9aBlQxOBkAAACA4iLPd2n8i5eXlyIiIlSlSvH7BYXCCwAKxu9RpzQ2bLkiE65KkobUaqnJzbrJw5kbhwAAAADIP9zjHQBQ4FIyM/T67h/14YEtcsihCh6+mte2n9oFVjc6GgAAAIBiiMILAFCgdl86ozGbl+tE3CVJ0iPVm+nl5t3l5eJqcDIAAAAAxRWFFwCgQKTZMrVgzy96d/8m2R0O+bt76/XWfXVfUC2jowEAAAAo5nJdeL311lvZnmdmZuqTTz5R2bJls20fNWpU/iQDABRZ+y6f05jNy3UkNlqS1LdqY81s0UO+VneDkwEAAAAoCXJ90fqQkJBb78xk0smTJ+84lNG4aD0A3J50W6be2rdBb0dskM1hV1lXT73Wuo+6Btc1OhoAAACAEiTXE16nTp0qyBwAgCLu4NWLGrN5mQ5cvShJ6l65vl5t1VulXT0MTgYAAACgpOEaXgCAO5Jpt+k/f2zSwr3rlWG3qZTVXa+26q0eIQ2MjgYAAACghKLwAgDctmOxMRq9eZkiLp+TJHWpVEehrfqonLuXwckAAAAAlGQUXgCAPLPZ7frgQJjm7vlJabZMebu4amaLnupXtbFMJpPR8QAAAACUcBReAIA8ORl3WePClmtnTKQkqWOFGprbpp/Ke/gYnAwAAAAA/kThBQDIFbvDrk8ObdOr4T8o1ZYhT2erpjV/SIOq38NUFwAAAIBCJVeFV3x8fK536O3tfdthAACF09mEqxoXtkJbo05KktqUr6r5bfuromcpg5MBAAAAwPVyVXj5+vre8m/vHQ6HTCaTbDZbvgQDABjP4XDos6M7NGvHWiVlpsvNyVlTmj2ox2u1kNlkNjoeAAAAAOQoV4XXhg0bCjoHAKCQuZAUpwlbVmrT+aOSpOb+lTW/bX+FeJc1OBkAAAAA3JzJ4XA4jA5R2MTHx8vHx0dxcXGcogmgxHE4HFp+fJem7/hO8empslqcNLFpFz1Zu40sZqa6AAAAABR+t/Wby+bNm/Xoo4+qdevWOn/+vCTpv//9r8LCwvI1HADg7opOjteT6z/V2LAVik9PVWO/IP3U63k9VbcdZRcAAACAIiPPv72sXLlSXbp0kZubm3bv3q20tDRJUlxcnF599dV8DwgAKHgOh0PfnNyr+755Qz+fPSQXs0UTm3bVqgefUVUfP6PjAQAAAECe5LnweuWVV7Ro0SJ98MEHcnZ2ztrepk0b7d69O1/DAQAK3pXURI3Y8JlGbvpSsWnJql+mgr7v+S+NbNBRTmaL0fEAAAAAIM9yddH6vzty5Ijat29/3XYfHx/FxsbmRyYAwF3y/en9mrRtla6kJsnJZNbzje7VyAad5EzRBQAAAKAIy3PhFRAQoOPHj6ty5crZtoeFhalKlSr5lQsAUICupSVr6vY1+ubkXklSrVIBeqPdANUrU8HYYAAAAACQD/JceD311FN6/vnn9dFHH8lkMunChQvatm2bxo8fr6lTpxZERgBAPlp/9rBe2LJS0SkJMptMeq5+R41udJ+sljz/kQAAAAAAhVKef7uZOHGi7Ha77rvvPiUnJ6t9+/ayWq0aP368/vWvfxVERgBAPohPT9WMHd/qq2O7JEnVfPy0sN1ANfYLMjgZAAAAAOQvk8PhcNzOG9PT03X8+HElJiaqTp068vT0VEpKitzc3PI7410XHx8vHx8fxcXFydvb2+g4AHDHNp0/qvFhK3UxOU4mmfR03bYa3+QBuTk53/rNAAAAAFDE3Pb5Ky4uLqpTp44kKS0tTQsWLNDrr7+uqKiofAsHALgziRlpemXn91p65HdJUrBXGS1sN0DN/SsbGwwAAAAAClCuC6+0tDRNnz5dP//8s1xcXPTCCy+od+/e+vjjjzVlyhRZLBaNGTOmILMCAPJg68UTGhe2QmcTr0mSnqjdSpObdpO7s4vByQAAAACgYOX6lMYXX3xR7733njp37qytW7fq0qVLGjp0qLZv367JkydrwIABsliKx23sOaURQFGWkpmuV8N/0MeHtkqSKnr6an7bAWpTvqrByQAAAADg7sj1hNfy5cv16aefqmfPntq/f78aNGigzMxMRUREyGQyFWRGAEAuhUdHavTmZTqdcEWSNLhGc01t/pA8na0GJwMAAACAuyfXE14uLi46deqUKlSoIElyc3PTjh07VL9+/QINaAQmvAAUNamZGZq752e9v3+zHHIowN1b89r2V8cKNYyOBgAAAAB3Xa4nvGw2m1xc/u+6L05OTvL09CyQUACA3Nt76azGbF6uY3ExkqQB1ZpoevMe8rEW/bvmAgAAAMDtyHXh5XA49MQTT8hq/fO0mNTUVD3zzDPy8PDItu7rr7/O34QAgByl2zL1xt71+vcfm2Rz2OXn5qk5rfvqgUp1jI4GAAAAAIbKdeE1ZMiQbM8fffTRfA8DAMidA1cuaPTmZTp0LUqS1CukoV5p2VOlXD1u8U4AAAAAKP5yfQ2vkoRreAEorDLsNv1730a9sXe9Mh12lbZ66NXWvdW9cvG7niIAAAAA3K5cT3gBAIx15Fq0xmxepn1XzkuSugXXVWirPirrxvUUAQAAAODvKLwAoJCz2e1678Bmzdv9k9LtNvm4uOmVlr3Uu0pDmUwmo+MBAAAAQKFD4QUAhdjJuEsavXm5dl86I0m6r2ItzWnTVwHunG4NAAAAADdC4QUAhZDdYddHB7cqdNcPSrNlysvZquktemhgtaZMdQEAAADALVB4AUAhE5lwRWM3r9Dv0ackSe0Dq2tem34K9PQ1NhgAAAAAFBEUXgBQSDgcDv33yO96Zef3Ss5Ml7uTi6bd85AG12zOVBcAAAAA5AGFFwAUAucTYzV+ywptvnBcktQyIEQL2g5QJa/SBicDAAAAgKKHwgsADORwOPTVsXDN2PGdEjLS5Gpx1qRmXTW0diuZTWaj4wEAAABAkUThBQAGiUqO1wtbVurXc0ckSU39KmlhuwGq4uNncDIAAAAAKNoovADgLnM4HPr65F5N275acempslqcNL7x/Xq6bjtZzEx1AQAAAMCdovACgLvoUkqCJm5dpR/PHJQkNSxbUQvbDVANX3+DkwEAAABA8UHhBQB3yXen9mnStm90LS1ZzmaLRje8V8816Cgns8XoaAAAAABQrFB4AUABu5qapJe2r9aaU/skSXVKl9cb7QaoTulAg5MBAAAAQPFE4QUABejHyAOauG2VLqUkymIya2SDjnq+4b1ysfCfXwAAAAAoKPzGBQAFIDYtWS///q1WntgjSarhW04L2w1Uw7IVDU4GAAAAAMUfhRcA5LMN545o/JaVik6Ol9lk0oi67TWucWe5OjkbHQ0AAAAASgQKLwDIJwnpqZq5c62+OLpTkhTiXVZvtBugpuWCDU4GAAAAACULhRcA5IMtF45rbNgKnU+KlUkmDavTWi827SI3JxejowEAAABAiUPhBQB3IDkjXbPD12nJ4W2SpEqepbWgXX+1DKhicDIAAAAAKLkovADgNu2IPq0xm5crMuGKJOnxWi01pVk3eThbDU4GAAAAACUbhRcA5FFKZobm7v5RHxzYIoccCvTw0fy2/dUusLrR0QAAAAAAovACgDzZfemMxmxerhNxlyRJD1dvppebd5e3i6vByQAAAAAAf6HwAoBcSLNlasGeX/Tu/k2yOxzyd/PS62366b6gWkZHAwAAAAD8DwovALiFPy6f1+jNy3QkNlqS1LdqY81o0UOlrO4GJwMAAAAA5ITCCwBuIMNu01sRv+rtiA3KdNhV1tVToa17q1twPaOjAQAAAABugsILAHJw6GqUxmxepv1XL0iSuleur9mteqmMq6fByQAAAAAAt0LhBQB/k2m3adH+3zR/zy/KsNvka3XXqy17qWeVhkZHAwAAAADkktnID7fZbJo6dapCQkLk5uamqlWratasWXI4HFlrTCZTjo+5c+fedN///ve/VblyZbm6uqpFixbasWNHQR8OgCLuWGyMeq9dpNd2/agMu00PBNXWr73HUHYBAAAAQBFj6ITXnDlz9O6772rJkiWqW7euwsPDNXToUPn4+GjUqFGSpIsXL2Z7z7p16zRs2DD169fvhvv96quvNHbsWC1atEgtWrTQG2+8oS5duujIkSMqV65cgR4TgKLHZrfrw4Nhen33T0qzZcrbxVUzW/RQv6pNZDKZjI4HAAAAAMgjk+Pv41R3Wffu3eXv76/FixdnbevXr5/c3Ny0dOnSHN/Tu3dvJSQkaP369Tfcb4sWLXTPPffonXfekSTZ7XYFBQXpX//6lyZOnHjd+rS0NKWlpWU9j4+PV1BQkOLi4uTt7X27hwegCDgVf1ljNy/XzphISVKHCjU0t00/BXr4GJwMAAAAAHC7DD2lsXXr1lq/fr2OHj0qSYqIiFBYWJi6deuW4/ro6GitXbtWw4YNu+E+09PTtWvXLnXu3Dlrm9lsVufOnbVt27Yc3xMaGiofH5+sR1BQ0B0cFYCiwO6w6+ODW/XA6je1MyZSHk4umtO6r5beP5SyCwAAAACKOENPaZw4caLi4+NVq1YtWSwW2Ww2zZ49W4MHD85x/ZIlS+Tl5aW+ffvecJ+XL1+WzWaTv79/tu3+/v46fPhwju+ZNGmSxo4dm/X8rwkvAMXT2YSrGhe2QlujTkqSWgdU0fy2/RXkVdrgZAAAAACA/GBo4bVs2TJ99tln+vzzz1W3bl3t3btXo0ePVmBgoIYMGXLd+o8++kiDBw+Wq6trvuawWq2yWq35uk8AhY/D4dBnR3do1o61SspMl5uTs6Y0e1CP12ohs8nQgVcAAAAAQD4ytPCaMGGCJk6cqEceeUSSVL9+fUVGRio0NPS6wmvz5s06cuSIvvrqq5vus2zZsrJYLIqOjs62PTo6WgEBAfl7AACKjAtJcZqwZaU2nf/zFOrm/pU1v21/hXiXNTgZAAAAACC/GTrSkJycLLM5ewSLxSK73X7d2sWLF6tp06Zq2LDhTffp4uKipk2bZruovd1u1/r169WqVav8CQ6gyHA4HFp+bJc6f7NQm84fldXipGn3PKTlXZ+m7AIAAACAYsrQCa8ePXpo9uzZqlSpkurWras9e/ZowYIFevLJJ7Oti4+P1/LlyzV//vwc93PfffepT58+GjlypCRp7NixGjJkiJo1a6bmzZvrjTfeUFJSkoYOHVrgxwSg8IhJTtCLW7/Wz2cPSZIalQ3SG+0GqJpvOYOTAQAAAAAKkqGF19tvv62pU6fq2WefVUxMjAIDAzVixAhNmzYt27ovv/xSDodDgwYNynE/J06c0OXLl7OeP/zww7p06ZKmTZumqKgoNWrUSD/88MN1F7IHUDw5HA6tObVPU7avVmxaslzMFo1tfL+eqddOTmaL0fEAAAAAAAXM5HA4HEaHKGzi4+Pl4+OjuLg4eXt7Gx0HQB5cSU3U5G2rtfb0H5KkeqUD9Ub7gapVimv4AQAAAEBJYeiEFwDkp3WR+zVx6ypdSU2Sk8msUQ3v1b8adpIzU10AAAAAUKJQeAEo8q6lJWva9jVadXKvJKmmr7/eaDdQ9ctWMDYYAAAAAMAQFF4AirT1Zw/rhS0rFZ2SILPJpGfrd9CYRp1ltfCfNwAAAAAoqfiNEECRFJ+eqhk7vtVXx3ZJkqr6+GlhuwFq4lfJ4GQAAAAAAKNReAEocn47f0zjt6zQhaQ4mWTS03XbanyTB+Tm5Gx0NAAAAABAIUDhBaDISMpI0ys7v9d/j/wuSQr2KqOF7QaouX9lY4MBAAAAAAoVCi8ARcK2qJMat3mFziRelSQ9UbuVJjftJndnF4OTAQAAAAAKGwovAIVaSma6QsN/0EeHtkqSKnr6an6b/moTWM3gZAAAAACAworCC0ChFR4dqTFhy3Uq/rIk6R81mmvqPQ/Ky8XV4GQAAAAAgMKMwgtAoZOamaF5e37W+wc2y+5wKMDdW3Pb9FOnijWNjgYAAAAAKAIovAAUKhGXz2nM5mU6GhsjSepftYlmtOghH6ubwckAAAAAAEUFhReAQiHdlqk3I37VO/s2yuawy8/NU3Na99UDleoYHQ0AAAAAUMRQeAEw3MGrFzR683IdvHpRktQrpKFeadlTpVw9DE4GAAAAACiKKLwAGCbDbtO/923UG3vXK9NhV2mrh15t1UvdQxoYHQ0AAAAAUIRReAEwxJFr0RqzeZn2XTkvSepaqa5CW/eWn5uXwckAAAAAAEUdhReAu8pmt+u9A5s1b/dPSrfb5OPiqlkte6lPlUYymUxGxwMAAAAAFAMUXgDumpNxlzRm83LtunRGknRvxZp6vU0/Bbh7G5wMAAAAAFCcUHgBKHB2h10fHdyq13b9qFRbhrycrZreoocGVmvKVBcAAAAAIN9ReAEoUJEJVzQubIW2R52SJLUPrK65bfqpgqevscEAAAAAAMUWhReAAuFwOLT0yO+atfN7JWemy93JRVPveVCP1mzBVBcAAAAAoEBReAHIdxcSYzV+y0r9duGYJKllQIjmt+2vYK8yBicDAAAAAJQEFF4A8o3D4dBXx8I1Y8d3SshIk6vFWRObdtGTdVrLbDIbHQ8AAAAAUEJQeAHIF1HJ8Xpxy9daf+6wJKmpXyUtbDdAVXz8DE4GAAAAAChpKLwA3BGHw6FVJ/dq6vY1iktPkYvZoglNHtDTddvJYmaqCwAAAABw91F4Abhtl1ISNGnrN/rhzAFJUsOyFbWw3QDV8PU3OBkAAAAAoCSj8AJwW747tU+Tt63W1bQkOZstGt3wXj3boKOczRajowEAAAAASjgKLwB5ci01SVO2r9aaU/skSbVLBejN9gNVp3SgwckAAAAAAPgThReAXPvpzEG9uPVrXUpJlMVk1sgGHfV8w3vlYuE/JQAAAACAwoPfUgHcUlxail7+/VutOLFbklTdp5wWthugRn5BBicDAAAAAOB6FF4AbmrDuSOasGWlopLjZZJJI+q10/jG98vVydnoaAAAAAAA5IjCC0COEjPSNHPHWn1+dIckKcS7rBa2HaBm/sEGJwMAAAAA4OYovABcZ8uF4xq3ZYXOJcZKkp6s3VqTmnWVm5OLscEAAAAAAMgFCi8AWZIz0jU7fJ2WHN4mSarkWVrz2/VXq4AqBicDAAAAACD3KLwASJJ2RJ/WmM3LFZlwRZL0WM0WeumeB+XhbDU4GQAAAAAAeUPhBZRwKZkZmrv7R31wYIsccqi8u4/mt+2v9hWqGx0NAAAAAIDbQuEFlGC7L53R2M3LdTzukiTp4epN9XLzHvJ2cTU4GQAAAAAAt4/CCyiB0myZWrj3F/3nj02yOxwq5+al19v0Veeg2kZHAwAAAADgjlF4ASXM/ivnNXrzch2+FiVJ6lOlkWa27KlSVneDkwEAAAAAkD8ovIASIsNu09sRG/RWxK/KdNhVxtVDr7Xuo27B9YyOBgAAAABAvqLwAkqAw9eiNGbzcv1x5bwk6aHK9fVqq14q4+ppcDIAAAAAAPIfhRdQjGXabVq0/zct2POL0u02+VrdNbtlL/UMaSCTyWR0PAAAAAAACgSFF1BMHY+N0Ziw5dpz6awk6f6g2prTuq/KuXsZnAwAAAAAgIJF4QUUMza7XYsPbtGc3T8qzZYpbxdXzWjeQ/2rNWGqCwAAAABQIlB4AcXIqfjLGhe2QjuiT0uSOlSooblt+inQw8fYYAAAAAAA3EUUXkAxYHfYteTQdr26a51SMjPk4eSiac276x817mGqCwAAAABQ4lB4AUXc2YSrGr9lpbZcPCFJah1QRfPb9leQV2mDkwEAAAAAYAwKL6CIcjgc+vzoTs3c8Z2SMtPl5uSsyU27aUjtljKbzEbHAwAAAADAMBReQBF0ISlOL2xZqY3nj0qS7ikXrAXtBijEu6zByQAAAAAAMB6FF1CEOBwOrTyxW9N+/1bx6amyWpz0QpMHNLxOW1nMTHUBAAAAACBReAFFRkxygiZu/Vo/nT0kSWpYtqLeaDdQ1X3LGZwMAAAAAIDChcILKALWnIzQ5O2rFZuWLGezRWMbddY/67eXk9lidDQAAAAAAAodCi+gELuSmqgp21bru9N/SJLqlQ7UwnYDVbt0gMHJAAAAAAAovCi8gEJqXeR+Tdr6jS6nJsrJZNa/GnbSqIb3ypmpLgAAAAAAborCCyhkYtOSNXX7Gq06uVeSVNPXX2+0G6j6ZSsYGwwAAAAAgCKCwgsoRNafPawXtqxUdEqCzCaT/lmvg8Y27iyrhX9VAQAAAADILX6LBgqB+PRUzdjxnb46Fi5JqurjpwVtB6hpuUoGJwMAAAAAoOih8AIMtvnCMY0LW6ELSXEyyaThddvohSZd5ObkbHQ0AAAAAACKJAovwCBJGWmaHb5Onx7eLkkK9iqjBW37q0VAiMHJAAAAAAAo2ii8AANsjzqpcWErFJlwVZI0pFYrTWnWTe7OLgYnAwAAAACg6KPwAu6ilMx0vbbrR310cKsccqiCh6/mt+2vtoHVjI4GAAAAAECxYTbyw202m6ZOnaqQkBC5ubmpatWqmjVrlhwOR7Z1hw4dUs+ePeXj4yMPDw/dc889OnPmzA33+8knn8hkMmV7uLq6FvThADe1KyZSD6x+S4sPbpFDDg2qcY9+6T2asgsAAAAAgHxm6ITXnDlz9O6772rJkiWqW7euwsPDNXToUPn4+GjUqFGSpBMnTqht27YaNmyYZsyYIW9vbx04cOCWBZa3t7eOHDmS9dxkMhXosQA3kpqZofl7ftF7B36T3eGQv7u35rbpp3sr1jQ6GgAAAAAAxZKhhdfWrVvVq1cvPfTQQ5KkypUr64svvtCOHTuy1kyZMkUPPvigXn/99axtVatWveW+TSaTAgICcpUjLS1NaWlpWc/j4+NzewjATUVcPqcxm5fpaGyMJKl/1Saa3qK7fK3uBicDAAAAAKD4MvSUxtatW2v9+vU6evSoJCkiIkJhYWHq1q2bJMlut2vt2rWqUaOGunTponLlyqlFixb65ptvbrnvxMREBQcHKygoSL169dKBAwduuDY0NFQ+Pj5Zj6CgoHw5PpRc6bZMzd39k3p+9x8djY2Rn5unFt/7mN5oP5CyCwAAAACAAmZy/O8Fs+4iu92uyZMn6/XXX5fFYpHNZtPs2bM1adIkSVJUVJTKly8vd3d3vfLKK+rUqZN++OEHTZ48WRs2bFCHDh1y3O+2bdt07NgxNWjQQHFxcZo3b55+++03HThwQBUrVrxufU4TXkFBQYqLi5O3t3fBHDyKrYNXL2j05uU6ePWiJKlnSAO90rKXSrt6GJwMAAAAAICSwdDC68svv9SECRM0d+5c1a1bV3v37tXo0aO1YMECDRkyRBcuXFCFChU0aNAgff7551nv69mzpzw8PPTFF1/k6nMyMjJUu3ZtDRo0SLNmzbrl+vj4ePn4+FB4IU8y7Tb9e99GvRHxqzLsNpWyuiu0VW91D2lgdDQAAAAAAEoUQ6/hNWHCBE2cOFGPPPKIJKl+/fqKjIxUaGiohgwZorJly8rJyUl16tTJ9r7atWsrLCws15/j7Oysxo0b6/jx4/maH/jL0dhojdm8XBGXz0mSulSqo9da95Gfm5fByQAAAAAAKHkMLbySk5NlNme/jJjFYpHdbpckubi46J577sl2t0VJOnr0qIKDg3P9OTabTX/88YcefPDBOw8N/I3Nbtf7BzZr3p6flWbLlI+Lq2a27KW+VRpxZ1AAAAAAAAxiaOHVo0cPzZ49W5UqVVLdunW1Z88eLViwQE8++WTWmgkTJujhhx9W+/bts67h9e2332rjxo1Zax5//HFVqFBBoaGhkqSZM2eqZcuWqlatmmJjYzV37lxFRkZq+PDhd/sQUYydjLussWHLFR4TKUnqVKGmXm/TV+U9fAxOBgAAAABAyWZo4fX2229r6tSpevbZZxUTE6PAwECNGDFC06ZNy1rTp08fLVq0SKGhoRo1apRq1qyplStXqm3btllrzpw5k21S7Nq1a3rqqacUFRWlUqVKqWnTptq6det1p0YCt8PusOvjQ9sUGv6DUm0Z8nS26uXm3fVI9WZMdQEAAAAAUAgYetH6woqL1uNGziRc1diw5doedUqS1C6wmua16a8Knr7GBgMAAAAAAFkMnfACigqHw6GlR37XrJ3fKzkzXe5OLnrpngf1WM0WTHUBAAAAAFDIUHgBt3AhMVbjt6zUbxeOSZJa+IdoQbv+CvYqY3AyAAAAAACQEwov4AYcDoeWHd+l6b9/q4SMNFktTprUtKuerNNaZpP51jsAAAAAAACGoPACchCdHK8Xt36tX84eliQ18aukhe0GqKqPn8HJAAAAAADArVB4AX/jcDj0zckIvbR9teLSU+Ritmhc4/v1TL32spiZ6gIAAAAAoCig8AL+v8spiZq0bZXWRR6QJNUvU0EL2w1QrVIBBicDAAAAAAB5QeEFSPru9B+avPUbXU1LkpPJrNGN7tNzDTrK2WwxOhoAAAAAAMgjCi+UaNdSk/TS9jVafSpCklS7VIDeaDdQdcsEGpwMAAAAAADcLgovlFg/nzmoF7euUkxKgiwms56r30GjG90nFwv/WgAAAAAAUJTxmz1KnLi0FE3f8a2WH98tSaruU04L2w1QI78gg5MBAAAAAID8QOGFEmXj+aMaH7ZCUcnxMsmkEfXaaXzj++Xq5Gx0NAAAAAAAkE8ovFAiJGakaeaOtfr86A5JUmWvMnqj3UA18w82OBkAAAAAAMhvFF4o9rZcPKFxYct1LjFWkvRk7daa1Kyr3JxcjA0GAAAAAAAKBIUXiq3kjHS9umudPjm0TZIU5FlK89v2V+vyVQ1OBgAAAAAAChKFF4qlndGnNWbzcp1OuCJJerRmC710z4PydLYanAwAAAAAABQ0Ci8UKymZGZq3+ye9fyBMDjlU3t1H89r2U4cKNYyOBgAAAAAA7hIKLxQbey6d1ZjNy3Q87pIkaWC1pnq5eXf5WN0MTgYAAAAAAO4mCi8UeWm2TL2xd73+/cdG2R0OlXPz0utt+qpzUG2jowEAAAAAAANQeKFI23/lvEZvXq7D16IkSb2rNNKsFj1UytXD4GQAAAAAAMAoFF4okjLsNr0dsUFvRfyqTIddZVw99Gqr3nqocn2jowEAAAAAAINReKHIOXwtSmM2L9cfV85Lkh4MrqdXW/VWWTdPg5MBAAAAAIDCgMILRUam3aZF+zdrwZ6flW63ycfFTbNb9VKvkIYymUxGxwMAAAAAAIUEhReKhBNxlzR68zLtuXRWktQ5qJbmtO4rf3dvg5MBAAAAAIDChsILhZrNbtdHh7botV0/Ks2WKS9nq2a06KEB1Zoy1QUAAAAAAHJE4YVC63T8FY0NW64d0aclSR0Cq2tum34K9PQ1NBcAAAAAACjcKLxQ6Ngddn16+HfNDv9eKZkZcndy0bR7HtLgms2Z6gIAAAAAALdE4YVC5VziNY0LW6EtF09IkloFVNH8tv1Vyau0wckAAAAAAEBRQeGFQsHhcOiLYzs1c8daJWakydXirMnNuuqJ2q1kNpmNjgcAAAAAAIoQCi8Y7mJSnF7Y8rU2nD8iSWpWLlgL2g5QFZ+yBicDAAAAAABFEYUXDONwOLTyxB69/PsaxaWnympx0gtNHtDwOm1lMTPVBQAAAAAAbg+FFwwRk5ygSdtW6cczByVJDctW1BvtBqq6bzmDkwEAAAAAgKKOwgt33ZqTEZqyfbWupSXL2WzR2Ead9c/67eVkthgdDQAAAAAAFAMUXrhrrqYmafK2b/Td6T8kSXVLl9fCdgNVp3R5g5MBAAAAAIDihMILd8UPkQc0cesqXU5NlMVk1r8adtKoBp3kYuFHEAAAAAAA5C/aBhSo2LRkTfv9W319Yo8kqaavvxa2G6AGZSsanAwAAAAAABRXFF4oML+eO6IJW1YqOjleZpNJz9Rrr3GN75eVqS4AAAAAAFCAaB6Q7xLSUzVjx3f68li4JKmKd1ktbDdQTctVMjgZAAAAAAAoCSi8kK/CLhzXuLAVOp8UK5NMGl63jV5o8oDcnFyMjgYAAAAAAEoICi/ki6SMNM0OX6dPD2+XJAV7ldb8tv3VMqCKwckAAAAAAEBJQ+GFO7Y96qTGha1QZMJVSdKQWi01uVk3eThbDU4GAAAAAABKIgov3LaUzHTN2fWjFh/cKoccquDhq3lt+6ldYHWjowEAAAAAgBKMwgu3ZVdMpMZsXq6T8ZclSY9Ub6aXm3eXl4urwckAAAAAAEBJR+GFPEnNzND8Pb/ovQO/ye5wyN/dW6+37qv7gmoZHQ0AAAAAAEAShRfyYN/lcxq9eZmOxsZIkvpWbayZLXrI1+pucDIAAAAAAID/Q+GFW0q3ZerNiF/1zr6NsjnsKuvqqdda91HX4LpGRwMAAAAAALgOhRdu6uDVixqzeZkOXL0oSepeub5ebdVbpV09DE4GAAAAAACQMwov5CjTbtN//tikhXvXK8NuUymru15t1Vs9QhoYHQ0AAAAAAOCmKLxwnWOxMRq9eZkiLp+TJHWpVEevte4jPzcvg5MBAAAAAADcGoUXstjsdn1wIExz9/ykNFumfFxcNbNlL/Wt0kgmk8noeAAAAAAAALlC4QVJ0sm4yxobtlzhMZGSpE4Vaur1Nn1V3sPH4GQAAAAAAAB5Q+FVwtkddn18aJtCw39Qqi1Dns5Wvdy8ux6p3oypLgAAAAAAUCRReJVgZxKualzYCm2LOilJalu+mua17aeKnqUMTgYAAAAAAHD7KLxKIIfDoc+O7NCsnWuVlJkuNydnvdTsQT1Wq4XMJrPR8QAAAAAAAO4IhVcJcyExVhO2rNSmC8ckSS38K2t+2wGq7F3G4GQAAAAAAAD5g8KrhHA4HFp+fJde/v1bJWSkyWpx0sSmXTSsThumugAAAAAAQLFC4VUCRCfH68WtX+uXs4clSY39gvRGu4Gq6uNncDIAAAAAAID8R+FVjDkcDq0+FaEp21YrLj1FLmaLxja+X8/Uaycns8XoeAAAAAAAAAWCwquYupySqMnbvtH3kfslSfXLVNDCdgNUq1SAwckAAAAAAAAKFoVXMbT29B+avO0bXUlNkpPJrOcb3auRDTrJmakuAAAAAABQAlB4FSPXUpP00u9rtPpkhCSpVqkAvdFugOqVqWBwMgAAAAAAgLvH0Nvz2Ww2TZ06VSEhIXJzc1PVqlU1a9YsORyObOsOHTqknj17ysfHRx4eHrrnnnt05syZm+57+fLlqlWrllxdXVW/fn19//33BXkohvv5zEHd980bWn0yQmaTSf9q0Elre4yk7AIAAAAAACWOoRNec+bM0bvvvqslS5aobt26Cg8P19ChQ+Xj46NRo0ZJkk6cOKG2bdtq2LBhmjFjhry9vXXgwAG5urrecL9bt27VoEGDFBoaqu7du+vzzz9X7969tXv3btWrV+9uHd5dEZeWouk7vtXy47slSdV8/LSw3UA19gsyOBkAAAAAAIAxTI7/Hae6i7p37y5/f38tXrw4a1u/fv3k5uampUuXSpIeeeQROTs767///W+u9/vwww8rKSlJ3333Xda2li1bqlGjRlq0aNF169PS0pSWlpb1PD4+XkFBQYqLi5O3t/ftHNpdsfH8UU0IW6mLyXEyyaSn67bV+CYPyM3J2ehoAAAAAAAAhjH0lMbWrVtr/fr1Onr0qCQpIiJCYWFh6tatmyTJbrdr7dq1qlGjhrp06aJy5cqpRYsW+uabb266323btqlz587ZtnXp0kXbtm3LcX1oaKh8fHyyHkFBhX86KsNu07Tta3QxOU7BXmW08sERmtr8IcouAAAAAABQ4hlaeE2cOFGPPPKIatWqJWdnZzVu3FijR4/W4MGDJUkxMTFKTEzUa6+9pq5du+qnn35Snz591LdvX23atOmG+42KipK/v3+2bf7+/oqKispx/f9r796DojrvMI4/y1URAW+wohCcRNF4QWMSB5KUoFYwiNhmEocxwRCnVoU0mmg7tETaTg3VjKaam206imltjY5Y1FQ7hltqJIiKN0jUSSUmEWTUKqIRFd7+4bDJlosgGtjl+5nZmew573vO793Mw8EfZ3dTU1N18eJF2+PLL7+8c4u8S9xdXLXi0aeUNCxCu+Jf1MMBIR1dEgAAAAAAQKfQoZ/htXHjRq1fv15/+9vfNHz4cB08eFDz589XYGCgZs6cqfr6eklSfHy8FixYIEkaPXq09uzZo9WrVysyMvKO1OHp6SlPT887cqzv04MB9+jBgHs6ugwAAAAAAIBOpUMbXosWLbLd5SVJI0eO1BdffKGMjAzNnDlTffv2lZubm+6//367ecOGDdPu3bubPa7VatWZM2fstp05c0ZWq/XOLwIAAAAAAACdSoe+pfHKlStycbEvwdXV1XZnl4eHhx566CEdO3bMbszx48d1zz3N39kUHh6unJwcu227du1SeHj4HaocAAAAAAAAnVWH3uEVFxenJUuWKDg4WMOHD1dJSYlWrFi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          },
          "metadata": {}
        }
      ]
    },
    {
      "source": [
        "from matplotlib import pyplot as plt\n",
        "_df_14['Temp_C'].plot(kind='line', figsize=(8, 4), title='Temp_C')\n",
        "plt.gca().spines[['top', 'right']].set_visible(False)"
      ],
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 390
        },
        "id": "4PKweDcgvqhd",
        "outputId": "2879beaa-afcb-4a7c-8c71-e0c1706aa094"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x400 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "source": [
        "from matplotlib import pyplot as plt\n",
        "_df_7.plot(kind='scatter', x='Dew Point Temp_C', y='Rel Hum_%', s=32, alpha=.8)\n",
        "plt.gca().spines[['top', 'right',]].set_visible(False)"
      ],
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 450
        },
        "id": "bWH1iU9BvnJn",
        "outputId": "25596bd3-85f1-4576-a16c-1c88fc5e475e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "source": [
        "from matplotlib import pyplot as plt\n",
        "_df_8.plot(kind='scatter', x='Rel Hum_%', y='Wind Speed_km/h', s=32, alpha=.8)\n",
        "plt.gca().spines[['top', 'right',]].set_visible(False)"
      ],
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 450
        },
        "id": "cVyk70EJvmRT",
        "outputId": "f3ffe491-7eb5-4237-9420-16d3507111bd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "source": [
        "from matplotlib import pyplot as plt\n",
        "import seaborn as sns\n",
        "def _plot_series(series, series_name, series_index=0):\n",
        "  from matplotlib import pyplot as plt\n",
        "  import seaborn as sns\n",
        "  palette = list(sns.palettes.mpl_palette('Dark2'))\n",
        "  xs = series['Date/Time']\n",
        "  ys = series['Rel Hum_%']\n",
        "\n",
        "  plt.plot(xs, ys, label=series_name, color=palette[series_index % len(palette)])\n",
        "\n",
        "fig, ax = plt.subplots(figsize=(10, 5.2), layout='constrained')\n",
        "df_sorted = _df_13.sort_values('Date/Time', ascending=True)\n",
        "for i, (series_name, series) in enumerate(df_sorted.groupby('Weather')):\n",
        "  _plot_series(series, series_name, i)\n",
        "  fig.legend(title='Weather', bbox_to_anchor=(1, 1), loc='upper left')\n",
        "sns.despine(fig=fig, ax=ax)\n",
        "plt.xlabel('Date/Time')\n",
        "_ = plt.ylabel('Rel Hum_%')"
      ],
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 548
        },
        "id": "mzPlKsK9viu7",
        "outputId": "f664bc90-fd89-4c79-c2c8-0004e0eb625f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x520 with 1 Axes>"
            ],
            "image/png": 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6Otu26OjobLde/Tur1Sqr1ZpPRwUAAADknclkknfLQXKv1VHRH49QUsRaXV4xRYm71yhg+EdyCaxldEQAAIoMQye8kpOTr5vUslgsOd6u1MfHR35+fjp27JjCw8PVq1evG+63VatWWr9+fbZtP//8s1q1apU/wQEAAIAC4uRbXoGjV8t/2GKZ3byVevJ3Rb7cVNd+WCiH3WZ0PAAAigRDC68ePXpo9uzZWrt2rU6fPq1Vq1ZpwYIF6tOnT9aa5cuXa+PGjTp58qRWr16t+++/X71799YDDzyQtebxxx/XpEmTsp4///zz+uGHHzR//nwdPnxY06dPV3h4uEaOHHlXjw8AAAC4HSaTST7tnlDwK/vkXu9+OTJSdenL8Tr32r1KjzlhdDwAAAo9Qwuvt99+W/3799ezzz6r2rVra/z48RoxYoRmzZqVtebixYt67LHHVKtWLY0aNUqPPfaYvvjii2z7OXPmTLaL2Ldu3Vqff/653n//fTVs2FArVqzQN998o3r16t21YwMAAADulHOZIFUYt07lhvxHJquHUo6GKfKlRor95T9y5HBWBAAA+JPJ4XA4jA5R2MTHx8vHx0dxcXHy9vY2Og4AAACgjEunFLV4uFIOb5QkudW+VwHDPpRz2WBjgwEwTFxcnCIjI1WtWjW5u7sbHadQs9vtSktLk9Vqzdeb4OHuSk1N1alTpxQSEiJXV9ebruW7DAAAABQBzn4hqvjCz/Ib/KZMLm5KOfSrIl9qqLhNH4q/wwYAIDsKLwAAAKCIMJnNKnX/SAXP3CPXaq1lT01Q9McjdH5hd2VcO290PAAACg0KLwAAAKCIcQmorqDJG1X24bkyOVmVvO8HRU5poPgt/2XaC0CR0L9/f5lMpuseBw4cMDoaigkKLwAAAKAIMpktKt1trCrN3CVryD2yJ8cq6oMndOGtvsqMjTI6HgDcUrt27XTmzJlsj5o1axodC8UEhRcAAABQhFkDa6vSS2Eq0+8VyeKspD1rdPqlBkr4/SujowHATVmtVgUFBWV7ODk5ad26dWrQoIFcXFzk5+en5557ThkZGVnvi42NVa9eveTm5iY/Pz/NnDlTzZs317Bhwww8GhQ2TkYHAAAAAHBnTBYnlekxSZ6NHlLUB0OVdmavLr77DyWEfy3/x/8ti1dZoyMCuAvsdruSMtIN+WwPZ5d8ufvhqVOn1LdvXw0YMECffvqp9u/fr3/9619ydXXV/PnzJUnPPPOMwsPD9dVXXykwMFCTJ0/WwYMHVb9+/Tv+fBQfFF4AAABAMWENaqBK07bpyrev6uq3rypx5wqlHPlN/kPelWfT3kbHA1DAkjLSVfvz6YZ89qF/TJeX1TVP79mwYYPc3d2znnfo0EHVq1dXQECAPvnkE5nNZjVq1Ejnz5/XzJkz9frrryshIUErV67UBx98oJ49e0qSvvjiC1WsWDFfjwdFH4UXAAAAUIyYnFxUts90eTbuoagPhir9/AFdeLufvFoNVrlH35TFo5TREQFAktSiRQu9//77Wc89PT311FNPqWnTptmmxTp06KDk5GSdPHlSV65cUWZmptq0aZP1epkyZRQSEnJXs6Pwo/ACAAAAiiHXyk1VafpOXVk1XdfWzVPCts+UfGiDAp58Xx4NuhkdD0AB8HB20aF/TDfss/PK3d1ddevWLYA0AIUXAAAAUGyZna3yGxgqzya9FPXhUGVEHdX5Bd3l3f5J+T0yTxZ3H6MjAshHZrM5z6cVFja1atXSt99+K7vdnjXltWnTJnl4eKhKlSry8/OTk5OTtm7dqurVq0uSrly5otOnT6tVq1ZGRkchw10aAQAAgGLOrVpLBc/YJd8uoyWTSfG/faTIlxoq6cAvRkcDgGzGjBmjqKgoDR06VHv37tXnn3+u1157TSNGjJDFYpGvr6/69eunKVOm6LvvvtOuXbs0ePBgmc1mmUwmo+OjEKHwAgAAAEoAs9Vd5QbNV8WJv8rZr4oyr57V+bldFP3pc7KnJhodDwAkSSEhIfr666+1Z88eNW/eXM8//7z+8Y9/6LXXXstas2jRIjVt2lQDBgxQ165d1bp1a1WpUkWurkV7ug35y+RwOBxGhyhs4uPj5ePjo7i4OHl7exsdBwAAAMhX9tREXVo2UXG/vitJcvarIv/hi+Ves73ByQDkRVxcnCIjI1WtWrVsdzssaeLj41WhQgXNmjVLo0ePznGN3W5XWlqarFZrtgvio2hJTU3VqVOnFBIScsuCk+8yAAAAUMKYXT3l//g7qjDhRzmVqaSMSyd17rV7FfP5WNnTko2OBwA3tXXrVr3//vs6ePCgtmzZon79+kmSHn74YYOToTCh8AIAAABKKI+6nRX8SoS82z8pORyK/elNRb7cVCnHtxkdDQBu6s0331SzZs304IMPKjk5WevXr1f58uWNjoVChFMac8ApjQAAAChpEiO+V/THI2SLvSCZzCrVbZzK9J4uswvXxAEKK05pzD1OaSweOKURAAAAQJ54NnxQlWfvk1erwZLDrmvfz9WZ6fco9fQuo6MBAJBnFF4AAAAAJEkWj1IqP+JTBf5rpSze5ZR+4aDOzGyly1+/LEdmutHxAADINQovAAAAANl4Nu2tyrP/kGfzAZLdpqtrXtGZma2Udnaf0dEA/I2Tk5OkP0/Xw8399TUymUwGJ8Hd4mR0AAAAAACFj8WrrAKf/VIJzfoq+tORSjuzV5HTm6tMr2kq/dALMln4VQIwmsVikdlsVmZmpjIzM7k21Q3Y7XZlZGTIYrFQeJUg/CkFAAAA4Ia8mg+UW80Oiv7kGSXtWaMrX09V4p41CnjqY1kDaxsdDyjx/iq9MjIyjI5SqFksFjk7OxsdA3cRhRcAAACAm3Ly8VfgqK+VsO0zxSx9XmmndurMtKYq02+WSnUZLZPZYnREoERzcXGR1WqVw+EwOkqhZDKZmOwqgZh3BAAAAHBLJpNJ3q0fVfDsfXJv0FWOzDRd/uoFnX21o9KjjhkdDyjxTCaTzGYzjxweuSm7KleurDfeeKPgv1F3aPr06WrUqFG+7KuoHPPtovACAAAAkGvOpSqowpjv5D/0fZldvZR6fKsipzXWtZ/floMLZwPIhSeeeCJr6urvj+PHjxuWaefOnXr66acL/HMqV66cdbxubm6qXLmyBg4cqF9//TVX7x8/frzWr19fwClzL6fvY9u2bY2OJYnCCwAAAEAemUwm+XQYpuBXIuRe5z450lN06bPROvf6/cq4dMroeACKgK5du+rixYvZHiEhIdetS09Pvyt5/Pz85O7uflc+a+bMmbp48aKOHDmiTz/9VL6+vurcubNmz559w/c4HA5lZmbK09NTZcqUuSs5c+vjjz/O9n1cs2aN0ZEkUXgBAAAAuE3OZYNVYfwPKvfYOzK5uCvl8EadntpIsRve41pCAG7KarUqICAg28Nisahjx44aOXKkRo8erbJly6pLly6SpP3796tbt27y9PSUv7+/HnvsMV2+fDlrf3a7XaGhoQoJCZGbm5saNmyoFStWZL1+o6myjRs3Srr+9D6TyaQPP/xQffr0kbu7u6pXr35dkbNmzRpVr15drq6u6tSpk5YsWSKTyaTY2NibHruXl5cCAgJUqVIltW/fXu+//76mTp2qadOm6ciRI5KkjRs3ymQyad26dWratKmsVqvCwsKuO6Uxp2OqXLlyro75f8XGxmr48OHy8/OTt7e37r33XkVERNz0WCTJ19c32/exdOnSWd+TmTNnqmLFirJarWrUqJF++OGHbO/dunWrGjVqJFdXVzVr1kzffPONTCaT9u7de8vPvRUKLwAAAAC3zWQ2y/e+fyr4lb1yq9FOjtRExSx5VufndVXGlbNGxwNKFIfDIXtakiGP/Cy5lyxZIhcXF23ZskWLFi1SbGys7r33XjVu3Fjh4eH64YcfFB0drYEDB2a9JzQ0VJ9++qkWLVqkAwcOaMyYMXr00Ue1adMmSdKbb76ZbQrp+eefV7ly5VSrVq0b5pgxY4YGDhyoffv26cEHH9TgwYN19epVSdKpU6fUv39/9e7dWxERERoxYoSmTJly28f8/PPPy+FwaPXq1dm2T5w4Ua+99poOHTqkBg0aXPe+vx/T8ePHVa1aNbVv3/62jnnAgAGKiYnRunXrtGvXLjVp0kT33Xdf1jHn1Ztvvqn58+dr3rx52rdvn7p06aKePXvq2LE/r/sYHx+vHj16qH79+tq9e7dmzZqlF1988bY+KyfcpREAAADAHXMpV1UVJ/6q2J/f0uUVU5R84BdFvtRAfv9YIO+2T3CHNOAucKQn6/gIb0M+u9p78TJZPXK9/rvvvpOnp2fW827dumn58uWSpOrVq+v111/Peu2VV15R48aN9eqrr2Zt++ijjxQUFKSjR48qODhYr776qn755Re1atVKklSlShWFhYXpvffeU4cOHeTj4yMfHx9J0tdff6333ntPv/zyiwICAm6Y8YknntCgQYMkSa+++qreeust7dixQ127dtV7772nmjVrau7cuZKkmjVrav/+/Tc9LfFmSpcurXLlyun06dPZts+cOVP333//Dd/3V36Hw6F+/frJx8dH7733niTl6ZjDwsK0Y8cOxcTEyGq1SpLmzZunb775RitWrLjp9c0GDRoki+X/7ta7dOlS9e7dW/PmzdOLL76oRx55RJI0Z84cbdiwQW+88Yb+/e9/6/PPP5fJZNIHH3wgV1dX1alTR+fPn9dTTz2Vi6/YrVF4AQAAAMgXJrNZpbqMlkeDbor6YKhST/6u6MXDlRi+Sv5D35OTb3mjIwIoJDp16qR3330367mHx/+VZU2bNs22NiIiQhs2bMhWkP3lxIkTysjIUHJy8nXFUHp6uho3bpxt2549e/TYY4/pnXfeUZs2bW6a8e8TVR4eHvL29lZMTIwk6ciRI7rnnnuyrW/evPlN93crDofjur8caNasWa7eO3nyZG3btk3h4eFyc3PL9lpujjkiIkKJiYnXXR8sJSVFJ06cuOlnL1y4UJ07d856Xr58ecXHx+vChQvXfV6bNm2yTpM8cuSIGjRoIFdX16zX7/Rr+HcUXgAAAADylUv5mgqa8puurZuvK99MV1LEWp2eUl/lHn1LXi0HMe0FFBCTi7uqvRdv2GfnhYeHh6pVq3bD1/4uMTFRPXr00Jw5c65bW758ee3fv1+StHbtWlWoUCHb639NK0lSVFSUevbsqeHDh2vYsGG3zOjs7Jztuclkkr2A7kZ75coVXbp06boL9//v1yInS5cu1cKFC7Vx48brjj+3x5yYmKjy5cvneH0vX1/fm35+QEDAdd/L+Hhjfg7/jsILAAAAQL4zWZxUuvuL8mj0kKI+GKq0yN2Keu8xJYZ/rXJD/iMn73JGRwSKHZPJlKfTCouKJk2aaOXKlapcubKcnK6vMerUqSOr1aozZ86oQ4cOOe4jNTVVvXr1Uq1atbRgwYI7zlSzZk19//332bbt3Lnztvf35ptvymw2q3fv3nl637Zt2zR8+HC99957atmyZbbX8nLMTZo0UVRUlJycnLIuen8nvL29FRgYqC1btmT7nmzZsiVriqtmzZpaunSp0tLSsorJO/ka/i8uWg8AAACgwFgr1lOlqVtVps90yeKkxF2rFDmlvhJ2rjQ6GoAi4rnnntPVq1c1aNAg7dy5UydOnNCPP/6ooUOHymazycvLS+PHj9eYMWO0ZMkSnThxQrt379bbb7+tJUuWSJJGjBihs2fP6q233tKlS5cUFRWlqKgopaen31amESNG6PDhw3rxxRd19OhRLVu2TJ988okk3XKKNSEhQVFRUTp79qx+++03Pf3003rllVc0e/bsG0695SQqKkp9+vTRI488oi5dumQd06VLl/J8zJ07d1arVq3Uu3dv/fTTTzp9+rS2bt2qKVOmKDw8PPdfmL+ZMGGC5syZo6+++kpHjhzRxIkTtXfvXj3//POSpH/84x+y2+16+umndejQIf3444+aN2+epFt/DXODwgsAAABAgTI5OatMr6mqNG27XCrWly3hsi7+e6AuLhosW+IVo+MBKOT+mhSy2Wx64IEHVL9+fY0ePVq+vr4ym/+sNWbNmqWpU6cqNDRUtWvXVteuXbV27dqsUwQ3bdqkixcvqk6dOipfvnzWY+vWrbeVKSQkRCtWrNDXX3+tBg0a6N133826S+PfT6PMybRp01S+fHlVq1ZNjz32mOLi4rR+/fo836Hw8OHDio6O1pIlS7Id01/XFsvLMZtMJn3//fdq3769hg4dqho1auiRRx5RZGSk/P39JUmnT5+WyWTK8bTHnIwaNUpjx47VuHHjVL9+ff3www9as2aNqlevLunPKbBvv/1We/fuVaNGjTRlyhRNmzZNkrJd1+t2mRz5ee/QYiI+Pl4+Pj6Ki4uTt7cxd7gAAAAAiiN7Rpqurp6lq2vnSA67LD4B8n9ikTwb9zA6GlDkpKam6tSpUwoJCcmXggB3Zvbs2Vq0aJHOnj1rdJQCsWHDBvXt21cnT55UqVKlCuQzPvvsMw0dOlRxcXHXXXxfytvPPNfwAgAAAHDXmJ2tKtv/FXk06anoD4Yq/eJhXXizt7zbPC6/fyyUxcPX6IgAkCv/+c9/dM8996hMmTLasmWL5s6dq5EjRxodq8B8//33mjx5cr6WXZ9++qmqVKmiChUqKCIiQi+++KIGDhyYY9mVVxReAAAAAO46tyrNVWnGLl35epqu/bhA8Vs+VfKhX+U/9H151O9idDwAuKVjx47plVde0dWrV1WpUiWNGzdOkyZNMjpWgZk7d26+7zMqKkrTpk1TVFSUypcvrwEDBmj27Nn5sm9OacwBpzQCAAAAd0/KsS2K+vBJZUQflyT5dHxKfg/PldnNy+BkQOHGKY0oafLyM89F6wEAAAAYyq16GwXP3C3fzn+eChS38QOdntpIyYc2GJwMAFBUUXgBAAAAMJzZ6qFyj76pii/+IqeylZV5+bTOzemsmKXPy56WZHQ8oFDjxC2UFHn5WafwAgAAAFBouNfupMqz9sqn41OSpNhf3lHktCZKObbF4GRA4ePs7CxJSk5ONjgJcHf89bP+18/+zXANrxxwDS8AAADAeEl//Kjoj55S5rXzksmkUl3GqkzfmTK7cK0i4C8XL15UbGysypUrJ3d3d5lMJqMjAfnO4XAoOTlZMTEx8vX1Vfny5W/5HgqvHFB4AQAAAIWDLSlWl74Yq/iwJZIkl/K15P/Ux3Kr0tzgZEDh4HA4FBUVpdjYWKOjAAXO19dXAQEBuSp2KbxyQOEFAAAAFC6Je75V9CfPyBYXJZktKv3gCyrda6rMzlajowGFgs1mU0ZGhtExgALj7Owsi8WS6/UUXjmg8AIAAAAKH1viFcUsHaWE7V9Kklwq1lfAUx/LNbixwckAAIUNF60HAAAAUCRYPMuo/DOfqfxzy2TxKqv0c3/ozMyWuvLNTDkymWwBAPwfJrxywIQXAAAAULhlxscoZsmzSty1SpJkDW6igKc+lrViPYOTAQAKAya8AAAAABQ5Tt7lVH7kcgWM+K/MHqWUFrlbZ6bfo6vfzZHDlml0PACAwZjwygETXgAAAEDRkXntgqI/GaGkiO8lSa5VWijgqY/lUr6mwckAAEZhwgsAAABAkeZUKlCBo9fIf9iHMrt5K/Xk74qc1kTXfnxDDrvd6HgAAAMw4ZUDJrwAAACAoinjyllFfzRcyQd+kSS51Wgn/+GL5VKuqsHJAAB3ExNeAAAAAIoN5zJBqjD+B5Ub8h+ZrB5KObpZkS81Uuz6d5n2AoAShAmvHDDhBQAAABR9GZdOKWrxcKUc3ihJcq9zn/yf/EDOZYONDQYAKHBMeAEAAAAolpz9QlTxhZ/lN/hNmVzclHxwvSJfaqi4TR+Kv/cHgOKNCa8cMOEFAAAAFC/pUccU9eGTSj2+VZLk3qCr/Ie+L+dSFQxOBgAoCEx4AQAAACj2XAKqK2jyRpV9+HWZnKxK3veDIqc0UPyW/zLtBQDFEBNeOWDCCwAAACi+0s4fVNSHTyrt1E5JkkfjnvJ/YpGcfPwNTgYAyC9MeAEAAAAoUawV6qjSS2Eq03eWZHFW0p41Oj2lvhJ2LDM6GgAgnzDhlQMmvAAAAICSIe1MhKI+GKq0sxGSJM/mA+T/2DuyeJU1OBkA4E4w4QUAAACgxLJWaqhKL29X6Z4vSWaLEncs1+kp9ZW4e7XR0QAAd4AJrxww4QUAAACUPKmnwhX1wVClXzgoSfJq/ajKDX5DFo9SBicDAOSVoRNeNptNU6dOVUhIiNzc3FS1alXNmjUr211SEhMTNXLkSFWsWFFubm6qU6eOFi1adNP9fvLJJzKZTNkerq6uBX04AAAAAIow15BmqjR9p0o9+IJkMith61KdntJASfvWGR0NAJBHTkZ++Jw5c/Tuu+9qyZIlqlu3rsLDwzV06FD5+Pho1KhRkqSxY8fq119/1dKlS1W5cmX99NNPevbZZxUYGKiePXvecN/e3t46cuRI1nOTyVTgxwMAAACgaDO7uMpvYKg8m/RU1IdPKiPqqM4v6C7v9k/Kb9B8Wdw4AwQAigJDJ7y2bt2qXr166aGHHlLlypXVv39/PfDAA9qxY0e2NUOGDFHHjh1VuXJlPf3002rYsGG2NTkxmUwKCAjIevj7c4thAAAAALnjVq2Vgmfsku8Dz0smk+J/+0iRLzVU8sH1RkcDAOSCoYVX69attX79eh09elSSFBERobCwMHXr1i3bmjVr1uj8+fNyOBzasGGDjh49qgceeOCm+05MTFRwcLCCgoLUq1cvHThw4IZr09LSFB8fn+0BAAAAoGQzW91V7h8LVHHir3L2C1HmlTM69/oDiv70OdlTE42OBwC4CUMLr4kTJ+qRRx5RrVq15OzsrMaNG2v06NEaPHhw1pq3335bderUUcWKFeXi4qKuXbvq3//+t9q3b3/D/dasWVMfffSRVq9eraVLl8put6t169Y6d+5cjutDQ0Pl4+OT9QgKCsr3YwUAAABQNLnXbK/gWXvlc+8zkqS4XxcpcmpjJR/5zeBkAIAbMfQujV9++aUmTJiguXPnqm7dutq7d69Gjx6tBQsWaMiQIZKkefPm6YMPPtC8efMUHBys3377TZMmTdKqVavUuXPnXH1ORkaGateurUGDBmnWrFnXvZ6Wlqa0tLSs5/Hx8QoKCuIujQAAAACySTrwi6IXD1fm1bOSySTf+0epbP/ZMru4GR0NAPA3hhZeQUFBmjhxop577rmsba+88oqWLl2qw4cPKyUlRT4+Plq1apUeeuihrDXDhw/XuXPn9MMPP+T6swYMGCAnJyd98cUXt1wbHx8vHx8fCi8AAAAA17Elx+nSF+MUv/ljSZJzQA0FDP9YbtVaGpwMAPAXQ09pTE5OltmcPYLFYpHdbpf052RWRkbGTdfkhs1m0x9//KHy5cvfeWgAAAAAJZrF3UcBwz5U4Og1sviWV0bUUZ2d3U6Xlk2SPSPt1jsAABQ4QwuvHj16aPbs2Vq7dq1Onz6tVatWacGCBerTp48kydvbWx06dNCECRO0ceNGnTp1Sp988ok+/fTTrDWS9Pjjj2vSpElZz2fOnKmffvpJJ0+e1O7du/Xoo48qMjJSw4cPv+vHCAAAAKB48mz0kCrP/kNerQZLDruuff+6zky/R6mndxkdDQBKPENPaUxISNDUqVO1atUqxcTEKDAwUIMGDdK0adPk4uIiSYqKitKkSZP0008/6erVqwoODtbTTz+tMWPGyGQySZI6duyoypUr65NPPpEkjRkzRl9//bWioqJUqlQpNW3aVK+88ooaN26cq1yc0ggAAAAgLxJ3faPoJf+ULT5GMltUusdklekxWSYnF6OjAUCJZGjhVVhReAEAAADIK1vCZUV/+pwSd66QJFkrNVLAUx/LGtTA4GQAUPIYekojAAAAABQXFq+yCnzuK5V/9guZPcso7cxeRU5vritrXpXDlml0PAAoUZjwygETXgAAAADuRGZslKKX/FNJe9ZIkqwh9/w57RVY2+BkAFAyMOEFAAAAAPnMyTdAgaO+VsBTn8js5qO0Uzt1ZlpTXV03Xw67zeh4AFDsMeGVAya8AAAAAOSXjGvnFf3RU0r+40dJkmv1NgoYtlguAdUNTgYAxRcTXgAAAABQgJxLVVCFsWvlP/Q9mV29lHpsiyKnNda1n9+Rw243Oh4AFEtMeOWACS8AAAAABSHjcqSiFg9XyqFfJUlutToqYNiHcvYLMTgZABQvTHgBAAAAwF3iXDZYFSf8qHKPvi2Ti7tSDm/U6amNFLvhPTGLAAD5hwmvHDDhBQAAAKCgpUcfV/TiYUo5GiZJcq93v/yHfiDnMkEGJwOAoo8JLwAAAAAwgIt/NVWc+Kv8Bs2XydlVyft/VuRLDRS3+ROmvQDgDjHhlQMmvAAAAADcTekXDivqwyeVevJ3SZJHw4fkP/Q9OfmWNzgZABRNTHgBAAAAgMFcAmspaMpvKtv/VZmcXJQUsVanp9RX/PYvmPYCgNvAhFcOmPACAAAAYJS0c/sV9cETSovcI0nybNZX5R7/t5y8yxmcDACKDia8AAAAAKAQsVasp0pTt6lM75cli5MSw79W5JQGSti50uhoAFBkMOGVAya8AAAAABQGqad3K+rDJ5V+7g9JklfLR1Tu0bdl8SxtcDIAKNyY8AIAAACAQsq1chNVevl3le4+STKZlbD9S52eUl+Je78zOhoAFGpMeOWACS8AAAAAhU3KyR2K/mCo0i8eliR5tx0iv38slMXdx+BkAFD4MOEFAAAAAEWAW5XmqjQjXKW6jpVMJsWHLVHkSw2UtP8no6MBQKHDhFcOmPACAAAAUJilHA1T1IdPKiPmhCTJp+PT8nv4dZndvAxOBgCFAxNeAAAAAFDEuNVoq+BZe+R733OSpLiN7+v01EZKPrTR2GAAUEgw4ZUDJrwAAAAAFBXJhzYo6sNhyrwSKUny7TxSZQeEymx1NzgZABiHwisHFF4AAAAAihJ7SoIufTVBcRs/kCQ5+1dTwPCP5Va9tcHJAMAYFF45oPACAAAAUBQl/fGjoj96SpnXzksmk0p1GasyfWfK7OJqdDQAuKsovHJA4QUAAACgqLIlxerS52MUv+VTSZJLYG0FDP9YrlXuMTgZANw9FF45oPACAAAAUNQl7lmj6I+fkS0+WjJbVPrBF1S611SZna1GRwOAAkfhlQMKLwAAAADFgS3ximL++y8l/P6VJMmlYn0FPPWJXIMbGRsMAAqY2egAAAAAAICCYfEso/L//Fzln/tKFq+ySj/3h87MbKErq2fJkZlhdDwAKDBMeOWACS8AAAAAxU1mfIxilvxTibu+kSRZKzdVwFMfy1qhrrHBAKAAMOEFAAAAACWAk3c5lR+5QgEj/iuzRymlnd6lMy8309W1r8thtxkdDwDyFRNeOWDCCwAAAEBxlnntgqI/GaGkiO8lSa5VWypg+EdyKV/T4GQAkD+Y8AIAAACAEsapVKACR6+R/7APZXbzVuqJ7Yqc1kTXfnxTDrvd6HgAcMeY8MoBE14AAAAASoqMK2cU/dFTSj7wiyTJrUY7+Q9fLJdyVQ1OBgC3jwkvAAAAACjBnMtUUoXxP6jckP/IZPVQytHNipzaWLHr32XaC0CRxYRXDpjwAgAAAFASZVw6pagPhynlyCZJknud++Q/7EM5l6lkcDIAyBsmvAAAAAAAkiRnvxBVfPEX+Q1+QyYXNyUfXK/IKQ0Ut2mxmJUAUJQw4ZUDJrwAAAAAlHTpUUcV9eGTSj2+TZLk0aCb/Ie+L6dSgQYnA4BbY8ILAAAAAHAdl4AaCpq8SWUHzpHJyaqkfet0ekp9xW9dyrQXgEKPCa8cMOEFAAAAAP8n7fxBRX04VGmnwiVJHk16yX/Iu3Ly8Tc4GQDkjAkvAAAAAMBNWSvUUaWXtqhM35mSxVlJu1fr9JT6Stix3OhoAJAjJrxywIQXAAAAAOQs7UyEoj4YqrSzEZIkr+YDVe6xt2XxKmtwMgD4P0x4AQAAAAByzVqpoSq9vF2le74kmS1K2LFMp6c0UOLu1UZHA4AsTHjlgAkvAAAAALi11FPhivpgqNIvHJQkebV+VOUGvyGLRymDkwEo6ZjwAgAAAADcFteQZqo0fadKPThBMpmVsHWpTk9poKR964yOBqCEY8IrB0x4AQAAAEDepBzfpqgPhioj+pgkybv9k/IbNF8WN36nAnD3MeEFAAAAALhjbtVaKXjmbvneP0qSFP/bR4p8qaGSD643OBmAkogJrxww4QUAAAAAty/58CZFLx6mjEunJEk+9/5TfgNfk9nV0+BkAEoKCq8cUHgBAAAAwJ2xpybq0lcvKG7De5IkZ78q8h/+kdxrtjM4GYCSgMIrBxReAAAAAJA/kvb/rOiPnlLm1bOSySTfB55X2X6vyOziZnQ0AMUYhVcOKLwAAAAAIP/YkuN06Ytxit/8sSTJOaCmAp76WG5VWxicDEBxReGVAwovAAAAAMh/iXvXKvqTEbLFXpRMZpV6cILK9H5ZZmer0dEAFDMUXjmg8AIAAACAgmFLvKqYz0YrYdtnkiSXCnUV8NTHcq3c1OBkAIoTCq8cUHgBAAAAQMFK2LVKMUuelS0+RjJbVLrHZJXpMVkmJxejowEoBii8ckDhBQAAAAAFLzP+kmL+O1KJO1dIkqyVGingqU9kDapvcDIARZ3Z6AAAAAAAgJLJydtPgc99pfL//Fxmj9JKO7NXkdPv0ZVvQ+WwZRodD0ARxoRXDpjwAgAAAIC7KzM2StFLnlHSnm8lSa5Vmst/+EeyBtY2OBmAoogJLwAAAACA4Zx8AxQ4apUCnvpYZjcfpZ7coTPTmurqugVy2G1GxwNQxDDhlQMmvAAAAADAOBlXzyn6o6eUvP8nSZJr9TYKGP6RXPyrGZwMQFHBhBcAAAAAoFBxLl1RFcZ9r3JPLJLJ1VOpx7YocmojXfv5HTnsdqPjASgCmPDKARNeAAAAAFA4ZFw6raiPhivl0AZJklvtTgp48kM5+1U2NhiAQo0JLwAAAABAoeXsV1kVJ/ykco++LZOLu1IObdDpqQ0Vu/F9Mb8B4EaY8MoBE14AAAAAUPikRx9X9OJhSjkaJklyr/eA/J/8QM6lKxqcDEBhY+iEl81m09SpUxUSEiI3NzdVrVpVs2bNytbSJyYmauTIkapYsaLc3NxUp04dLVq06Jb7Xr58uWrVqiVXV1fVr19f33//fUEeCgAAAACggLn4V1PFib/K75F5MjlZlbz/J0VOaaC4zZ8w7QUgG0MLrzlz5ujdd9/VO++8o0OHDmnOnDl6/fXX9fbbb2etGTt2rH744QctXbpUhw4d0ujRozVy5EitWbPmhvvdunWrBg0apGHDhmnPnj3q3bu3evfurf3799+NwwIAAAAAFBCT2aJSXccoeOZuuVZpLntKnKIXD9OFN3srM/ai0fEAFBKGntLYvXt3+fv7a/HixVnb+vXrJzc3Ny1dulSSVK9ePT388MOaOnVq1pqmTZuqW7dueuWVV3Lc78MPP6ykpCR99913WdtatmypRo0a5Wo6jFMaAQDIvcSMNL2y83s9XL2ZGvsFGR0HAFCCOGyZurZuni6vmi7ZMmT2KK1yj70lrxaPyGQyGR0PgIEMnfBq3bq11q9fr6NHj0qSIiIiFBYWpm7dumVbs2bNGp0/f14Oh0MbNmzQ0aNH9cADD9xwv9u2bVPnzp2zbevSpYu2bduW4/q0tDTFx8dnewAAgFvbcvGEOn+zUEuP/K5xYctl41bxAIC7yGRxUunuExU8faeswY1lT7qqqEWPKi1yj9HRABjMycgPnzhxouLj41WrVi1ZLBbZbDbNnj1bgwcPzlrz9ttv6+mnn1bFihXl5OQks9msDz74QO3bt7/hfqOiouTv759tm7+/v6KionJcHxoaqhkzZuTPQQEAUAIkZ6Tr1V3r9MmhP/8yKcizlF5p2UsWMzeABgDcfdag+qo0dZuufheqzPgYuVZuYnQkAAYztPBatmyZPvvsM33++eeqW7eu9u7dq9GjRyswMFBDhgyR9GfhtX37dq1Zs0bBwcH67bff9NxzzykwMPC6Ka7bNWnSJI0dOzbreXx8vIKCOCUDAICc7Iw+rTGbl+t0whVJ0qM1W+ilex6Up7PV4GQAgJLM5OSsMr2ncfF6AJIMLrwmTJigiRMn6pFHHpEk1a9fX5GRkQoNDdWQIUOUkpKiyZMna9WqVXrooYckSQ0aNNDevXs1b968GxZeAQEBio6OzrYtOjpaAQEBOa63Wq2yWvmfdAAAbiYlM0Pzdv+k9w+EySGHyrv7aF7bfupQoYbR0QAAyMK1uwBIBl/DKzk5Web/OfXBYrHI/v+v/5GRkaGMjIybrslJq1attH79+mzbfv75Z7Vq1SqfkgMAULLsuXRW3da8pfcObJZDDg2s1lS/9B5N2QUAAIBCydAJrx49emj27NmqVKmS6tatqz179mjBggV68sknJUne3t7q0KGDJkyYIDc3NwUHB2vTpk369NNPtWDBgqz9PP7446pQoYJCQ0MlSc8//7w6dOig+fPn66GHHtKXX36p8PBwvf/++4YcJwAARVWaLVNv7F2vf/+xUXaHQ+XcvPR6m77qHFTb6GgAAADADZkcBp7gnJCQoKlTp2rVqlWKiYlRYGCgBg0apGnTpsnFxUXSnxegnzRpkn766SddvXpVwcHBevrppzVmzJisUdWOHTuqcuXK+uSTT7L2vXz5cr300ks6ffq0qlevrtdff10PPvhgrnLFx8fLx8dHcXFx8vb2zvfjBgCgKNh/5bxGb16uw9f+vOlL7yqNNKtlT5WyuhucDAAAALg5QwuvworCCwBQkmXYbXo7YoPeivhVmQ67yrh6KLRVHz1YuZ7R0QAAAIBcMfSURgAAULgcvhalMZuX648r5yVJDwbXU2jr3irj6mlwMgAAACD3KLwAAIAy7TYt2r9ZC/b8rHS7Tb5Wd81u2Us9QxpwtysAAAAUORReAACUcCfiLmn05mXac+msJOn+oNp6rXUf+btzWj8AAACKJgovAABKKLvDrsUHt+i1XT8qzZYpbxdXzWjeQ/2rNWGqCwAAAEUahRcAACXQ6fgrGhe2XL9Hn5YkdQisrrlt+yvQw8fYYAAAAEA+oPACAKAEsTvs+u/h3/VK+PdKycyQh5OLpjZ/SINrNGeqCwAAAMUGhRcAACXEucRrGh+2UmEXj0uSWgVU0YK2/RXkVdrgZAAAAED+ovACAKCYczgc+uLYTs3csVaJGWlytThrcrOueqJ2K5lNZqPjAQAAAPmOwgsAgGLsYlKcXtjytTacPyJJalYuWAvaDlAVn7IGJwMAAAAKDoUXAADFkMPh0MoTe/Ty72sUl54qq8VJLzR5QMPrtJXFzFQXAAAAijcKLwAAipmY5ARN2rZKP545KElqWLai3mg3UNV9yxmcDAAAALg7KLwAAChG1pyM0JTtq3UtLVnOZovGNuqsf9ZvLyezxehoAAAAwF1D4QUAQDFwNTVJk7d9o+9O/yFJqlu6vBa2G6g6pcsbnAwAAAC4+yi8AAAo4n6IPKCJW1fpcmqiLCaz/tWwk0Y16CQXC3/MAwAAoGTi/4QBACiiYtOSNe33b/X1iT2SpJq+/lrYboAalK1ocDIAAADAWBReAAAUQb+eO6IJW1YqOjleZpNJ/6zXQWMbd5aVqS4AAACAwgsAgKIkIT1VM3Z8py+PhUuSqvr4aUHbAWparpLByQAAAIDCg8ILAIAiIuzCcY0LW6HzSbEyyaThddvohSZd5ObkbHQ0AAAAoFCh8AIAoJBLykjT7PB1+vTwdklSsFdpLWg7QC0CQgxOBgAAABROFF4AABRi26NOalzYCkUmXJUkDanVUpObdZOHs9XgZAAAAEDhReEFAEAhlJKZoTm7ftDig1vlkEMVPHw1v21/tQ2sZnQ0AAAAoNCj8AIAoJDZFXNGYzYv08n4y5KkQTXu0bR7HpKXi6vByQAAAICigcILAIBCIs2Wqfl7ftai/b/J7nDI391bc9v0070VaxodDQAAAChSKLwAACgE9l0+pzGbl+tIbLQkqV/VxprRood8re4GJwMAAACKHgovAAAMlG7L1Fv7NujtiA2yOewq6+qpOa37qEtwXaOjAQAAAEUWhRcAAAY5ePWixmxepgNXL0qSelRuoNmteqm0q4fByQAAAICi7bYLr8zMTL333nvauHGjbDab2rRpo+eee06urlxQFwCAm8m02/SfPzZp4d71yrDbVMrqrldb9VaPkAZGRwMAAACKhdsuvEaNGqWjR4+qb9++ysjI0Keffqrw8HB98cUX+ZkPAIBi5VhsjEZvXqaIy+ckSV0q1dFrrfvIz83L4GQAAABA8ZHrwmvVqlXq06dP1vOffvpJR44ckcVikSR16dJFLVu2zP+EAAAUAza7XR8cCNPcPT8pzZYpHxdXzWzZS32rNJLJZDI6HgAAAFCsmBwOhyM3C3v06CGLxaL//Oc/CgwM1MCBA+Xj46N+/fopIyNDH3zwgVJSUvTzzz8XdOYCFx8fLx8fH8XFxcnb29voOACAIu5k3GWNDVuu8JhISVKnCjX1epu+Ku/hY3AyAAAAoHjKdeElSV999ZWmTp2qf/3rX3rsscc0a9asbNfwmj59uvz8/Aoy711B4QUAyA92h10fH9qm0PAflGrLkKezVS83765HqjdjqgsAAAAoQHkqvCQpNjZWL7zwgiIiIrRo0SI1bty4oLIZhsILAHCnziRc1biwFdoWdVKS1LZ8Nc1r208VPUsZnAwAAAAo/vJceP3lt99+03PPPaeuXbtq1qxZxerujBReAIDb5XA49NmRHZq1c62SMtPl5uSsl5o9qMdqtZDZZDY6HgAAAFAi5Pr/vM+cOaOBAweqfv36Gjx4sKpXr65du3bJ3d1dDRs21Lp16woyJwAAhd6FxFg9+tNHmrhtlZIy09XCv7J+7jVaQ2q3ouwCAAAA7qJcT3h17NhRAQEBeuKJJ/Tjjz/qxIkTWrNmjSTp0KFDGjFihAICArRs2bICDXw3MOEFAMgLh8Oh5cd36eXfv1VCRpqsFidNatpVT9ZpTdEFAAAAGCDXhZenp6ciIiJUtWpVORwOhYSE6PTp09nWvP/++3r66acLIuddReEFAMit6OR4vbj1a/1y9rAkqYlfJS1sN0BVfYr+TVwAAACAoirXhVeHDh1UsWJFDRkyRL/88osOHTqkb7/9tqDzGYLCCwBwKw6HQ6tPRWjKttWKS0+Ri9micY3v1zP12stiZqoLAAAAMFKuC6/IyEiNGzdOhw4dUqNGjTR37lwFBgYWdD5DUHgBAG7mckqiJm/7Rt9H7pck1S9TQQvbDVCtUgEGJwMAAAAg3cFdGm/ltdde0zPPPCNfX9+C2H2BovACANzI2tN/aPK2b3QlNUlOJrOeb3SvRjboJGezxehoAAAAAP6/Aiu8vL29tXfvXlWpUqUgdl+gKLwAAP/rWlqyXtq+WqtPRkiSapUK0BvtBqhemQoGJwMAAADwv5wKascF1KMBAHDX/XL2kF7Y8rViUhJkMZn1XP0OGt3oPrlYCuyPUQAAAAB3gP9TBwDgBuLTUzX992+17PguSVJ1n3Ja2G6AGvkFGZwMAAAAwM1QeAEAkINN549qfNhKXUyOk0kmPV2vnSY0vl+uTs5GRwMAAABwCxReAAD8TWJGmmbtWKvPju6QJFX2KqOF7QboHv/KxgYDAAAAkGsUXgAA/H9bLp7Q+LAVOpt4TZI0tHZrTWraVe7OLgYnAwAAAJAXBVZ4tWvXTm5ubgW1ewAA8k1yRrpCd/2gjw9tlSQFeZbSvLb91aZ8VYOTAQAAALgdJsdt3k4xJiZGMTExstvt2bY3aNAgX4IZKT4+Xj4+PoqLi5O3t7fRcQAABWhn9GmN2bxcpxOuSJIG12iuqc0fkqez1eBkAAAAAG5Xnie8du3apSFDhujQoUP6qyszmUxyOBwymUyy2Wz5HhIAgPyWmpmhuXt+1vv7N8shhwLcvTWvbX91rFDD6GgAAAAA7lCeC68nn3xSNWrU0OLFi+Xv7y+TyVQQuQAAKDB7Lp3VmM3LdDzukiRpYLWmerl5d/lYORUfAAAAKA7yXHidPHlSK1euVLVq1QoiDwAABSbNlqk39q7Xf/7YJJvDrnJuXprTuo/ur1TH6GgAAAAA8lGeC6/77rtPERERFF4AgCLlwJULen7zMh2+FiVJ6l2lkWa16KFSrh4GJwMAAACQ3/J80frLly9ryJAhat68uerVqydnZ+dsr/fs2TNfAxqBi9YDQPGRYbfpnX0b9ObeX5XpsKuMq4debdVbD1Wub3Q0AAAAAAUkzxNe27Zt05YtW7Ru3brrXuOi9QCAwuTItWiN2bxM+66clyQ9GFxPr7bqrbJungYnAwAAAFCQ8jzhVblyZXXv3l1Tp06Vv79/QeUyFBNeAFC02ex2Ldr/m+bv+Vnpdpt8XNw0u1Uv9QppyM1WAAAAgBIgzxNeV65c0ZgxY4pt2QUAKNpOxF3SmM3LtfvSGUlS56BamtO6r/zd+QsMAAAAoKTIc+HVt29fbdiwQVWrVi2IPAAA3Ba7w66PDm5V6K4flGbLlJezVTNa9NCAak2Z6gIAAABKmDwXXjVq1NCkSZMUFham+vXrX3fR+lGjRuVbOAAAcuN0/BWNC1uu36NPS5I6BFbX3Db9FOjpa2guAAAAAMbI8zW8QkJCbrwzk0knT56841BG4xpeAFA02B12/ffw75odvk7Jmelyd3LRtHse0uCazZnqAgAAAEqwPE94nTp1qiByAACQJ+cTYzUubIXCLh6XJLUKqKL5bfurkldpg5MBAAAAMFqeCy8AAIzkcDj05bFwzdjxnRIz0uRqcdbkZl31RO1WMpvMRscDAAAAUAjkufB68sknb/r6Rx99lOt92Ww2TZ8+XUuXLlVUVJQCAwP1xBNP6KWXXso6FeVGp6S8/vrrmjBhQo6vTZ8+XTNmzMi2rWbNmjp8+HCuswEACp+LSXF6cevX+vXcEUlSs3LBWtB2gKr4lDU4GQAAAIDCJM+F17Vr17I9z8jI0P79+xUbG6t77703T/uaM2eO3n33XS1ZskR169ZVeHi4hg4dKh8fn6yL31+8eDHbe9atW6dhw4apX79+N9133bp19csvv2Q9d3JimA0AiiqHw6GVJ/bo5d/XKC49VVaLkyY0fkBP1W0ri5mpLgAAAADZ5bkFWrVq1XXb7Ha7/vnPf6pq1ap52tfWrVvVq1cvPfTQQ5KkypUr64svvtCOHTuy1gQEBGR7z+rVq9WpUydVqVLlpvt2cnK67r0AgKLnUkqCJm5dpR/PHJQkNSxbUQvbDVANX3+DkwEAAAAorPLlr8XNZrPGjh2rhQsX5ul9rVu31vr163X06FFJUkREhMLCwtStW7cc10dHR2vt2rUaNmzYLfd97NgxBQYGqkqVKho8eLDOnDlzw7VpaWmKj4/P9gAAGO/bU/t076qF+vHMQTmbLXqhyQNa/dA/KbsAAAAA3FS+ned34sQJZWZm5uk9EydOVHx8vGrVqiWLxSKbzabZs2dr8ODBOa5fsmSJvLy81Ldv35vut0WLFvrkk09Us2ZNXbx4UTNmzFC7du20f/9+eXl5Xbc+NDT0umt+AQCMczU1SVO2rda3p/dJkuqULq832g1QndKBBicDAAAAUBSYHA6HIy9vGDt2bLbnDodDFy9e1Nq1azVkyBC98847ud7Xl19+qQkTJmju3LmqW7eu9u7dq9GjR2vBggUaMmTIdetr1aql+++/X2+//XZeIis2NlbBwcFasGBBjtNhaWlpSktLy3oeHx+voKAgxcXFydvbO0+fBQC4Mz9GHtCLW1fpcmqiLCazRjboqOcb3isXC9diBAAAAJA7ef7tYc+ePdmem81m+fn5af78+be8g+P/mjBhgiZOnKhHHnlEklS/fn1FRkYqNDT0usJr8+bNOnLkiL766qu8Rpavr69q1Kih48eP5/i61WqV1WrN834BAPknNi1ZL//+rVae+PPPmRq+5bSw3UA1LFvR4GQAAAAAipo8F14bNmzItw9PTk6W+X/urmWxWGS3269bu3jxYjVt2lQNGzbM8+ckJibqxIkTeuyxx247KwCg4Px67ogmbFmp6OR4mU0mPVOvvcY26ixXJ2ejowEAAAAoggw9P6RHjx6aPXu2KlWqpLp162rPnj1asGDBdZNi8fHxWr58uebPn5/jfu677z716dNHI0eOlCSNHz9ePXr0UHBwsC5cuKCXX35ZFotFgwYNKvBjAgDkXkJ6qmbs+E5fHguXJFXxLquF7Qaoablgg5MBAAAAKMpyXXg1btxYJpPplut2796d6w9/++23NXXqVD377LOKiYlRYGCgRowYoWnTpmVb9+WXX8rhcNywsDpx4oQuX76c9fzcuXMaNGiQrly5Ij8/P7Vt21bbt2+Xn59frrMBAApW2IXjGhe2QueTYmWSScPrttELTR6Qm5OL0dEAAAAAFHG5vmj93+9i6HA4FBoaqmeeeUalS5fOtu7ll1/O34QGiI+Pl4+PDxetB4ACkJSRplfD12nJ4e2SpGCv0prftr9aBlQxOBkAAACA4iLPd2n8i5eXlyIiIlSlSvH7BYXCCwAKxu9RpzQ2bLkiE65KkobUaqnJzbrJw5kbhwAAAADIP9zjHQBQ4FIyM/T67h/14YEtcsihCh6+mte2n9oFVjc6GgAAAIBiiMILAFCgdl86ozGbl+tE3CVJ0iPVm+nl5t3l5eJqcDIAAAAAxRWFFwCgQKTZMrVgzy96d/8m2R0O+bt76/XWfXVfUC2jowEAAAAo5nJdeL311lvZnmdmZuqTTz5R2bJls20fNWpU/iQDABRZ+y6f05jNy3UkNlqS1LdqY81s0UO+VneDkwEAAAAoCXJ90fqQkJBb78xk0smTJ+84lNG4aD0A3J50W6be2rdBb0dskM1hV1lXT73Wuo+6Btc1OhoAAACAEiTXE16nTp0qyBwAgCLu4NWLGrN5mQ5cvShJ6l65vl5t1VulXT0MTgYAAACgpOEaXgCAO5Jpt+k/f2zSwr3rlWG3qZTVXa+26q0eIQ2MjgYAAACghKLwAgDctmOxMRq9eZkiLp+TJHWpVEehrfqonLuXwckAAAAAlGQUXgCAPLPZ7frgQJjm7vlJabZMebu4amaLnupXtbFMJpPR8QAAAACUcBReAIA8ORl3WePClmtnTKQkqWOFGprbpp/Ke/gYnAwAAAAA/kThBQDIFbvDrk8ObdOr4T8o1ZYhT2erpjV/SIOq38NUFwAAAIBCJVeFV3x8fK536O3tfdthAACF09mEqxoXtkJbo05KktqUr6r5bfuromcpg5MBAAAAwPVyVXj5+vre8m/vHQ6HTCaTbDZbvgQDABjP4XDos6M7NGvHWiVlpsvNyVlTmj2ox2u1kNlkNjoeAAAAAOQoV4XXhg0bCjoHAKCQuZAUpwlbVmrT+aOSpOb+lTW/bX+FeJc1OBkAAAAA3JzJ4XA4jA5R2MTHx8vHx0dxcXGcogmgxHE4HFp+fJem7/hO8empslqcNLFpFz1Zu40sZqa6AAAAABR+t/Wby+bNm/Xoo4+qdevWOn/+vCTpv//9r8LCwvI1HADg7opOjteT6z/V2LAVik9PVWO/IP3U63k9VbcdZRcAAACAIiPPv72sXLlSXbp0kZubm3bv3q20tDRJUlxcnF599dV8DwgAKHgOh0PfnNyr+755Qz+fPSQXs0UTm3bVqgefUVUfP6PjAQAAAECe5LnweuWVV7Ro0SJ98MEHcnZ2ztrepk0b7d69O1/DAQAK3pXURI3Y8JlGbvpSsWnJql+mgr7v+S+NbNBRTmaL0fEAAAAAIM9yddH6vzty5Ijat29/3XYfHx/FxsbmRyYAwF3y/en9mrRtla6kJsnJZNbzje7VyAad5EzRBQAAAKAIy3PhFRAQoOPHj6ty5crZtoeFhalKlSr5lQsAUICupSVr6vY1+ubkXklSrVIBeqPdANUrU8HYYAAAAACQD/JceD311FN6/vnn9dFHH8lkMunChQvatm2bxo8fr6lTpxZERgBAPlp/9rBe2LJS0SkJMptMeq5+R41udJ+sljz/kQAAAAAAhVKef7uZOHGi7Ha77rvvPiUnJ6t9+/ayWq0aP368/vWvfxVERgBAPohPT9WMHd/qq2O7JEnVfPy0sN1ANfYLMjgZAAAAAOQvk8PhcNzOG9PT03X8+HElJiaqTp068vT0VEpKitzc3PI7410XHx8vHx8fxcXFydvb2+g4AHDHNp0/qvFhK3UxOU4mmfR03bYa3+QBuTk53/rNAAAAAFDE3Pb5Ky4uLqpTp44kKS0tTQsWLNDrr7+uqKiofAsHALgziRlpemXn91p65HdJUrBXGS1sN0DN/SsbGwwAAAAAClCuC6+0tDRNnz5dP//8s1xcXPTCCy+od+/e+vjjjzVlyhRZLBaNGTOmILMCAPJg68UTGhe2QmcTr0mSnqjdSpObdpO7s4vByQAAAACgYOX6lMYXX3xR7733njp37qytW7fq0qVLGjp0qLZv367JkydrwIABsliKx23sOaURQFGWkpmuV8N/0MeHtkqSKnr6an7bAWpTvqrByQAAAADg7sj1hNfy5cv16aefqmfPntq/f78aNGigzMxMRUREyGQyFWRGAEAuhUdHavTmZTqdcEWSNLhGc01t/pA8na0GJwMAAACAuyfXE14uLi46deqUKlSoIElyc3PTjh07VL9+/QINaAQmvAAUNamZGZq752e9v3+zHHIowN1b89r2V8cKNYyOBgAAAAB3Xa4nvGw2m1xc/u+6L05OTvL09CyQUACA3Nt76azGbF6uY3ExkqQB1ZpoevMe8rEW/bvmAgAAAMDtyHXh5XA49MQTT8hq/fO0mNTUVD3zzDPy8PDItu7rr7/O34QAgByl2zL1xt71+vcfm2Rz2OXn5qk5rfvqgUp1jI4GAAAAAIbKdeE1ZMiQbM8fffTRfA8DAMidA1cuaPTmZTp0LUqS1CukoV5p2VOlXD1u8U4AAAAAKP5yfQ2vkoRreAEorDLsNv1730a9sXe9Mh12lbZ66NXWvdW9cvG7niIAAAAA3K5cT3gBAIx15Fq0xmxepn1XzkuSugXXVWirPirrxvUUAQAAAODvKLwAoJCz2e1678Bmzdv9k9LtNvm4uOmVlr3Uu0pDmUwmo+MBAAAAQKFD4QUAhdjJuEsavXm5dl86I0m6r2ItzWnTVwHunG4NAAAAADdC4QUAhZDdYddHB7cqdNcPSrNlysvZquktemhgtaZMdQEAAADALVB4AUAhE5lwRWM3r9Dv0ackSe0Dq2tem34K9PQ1NhgAAAAAFBEUXgBQSDgcDv33yO96Zef3Ss5Ml7uTi6bd85AG12zOVBcAAAAA5AGFFwAUAucTYzV+ywptvnBcktQyIEQL2g5QJa/SBicDAAAAgKKHwgsADORwOPTVsXDN2PGdEjLS5Gpx1qRmXTW0diuZTWaj4wEAAABAkUThBQAGiUqO1wtbVurXc0ckSU39KmlhuwGq4uNncDIAAAAAKNoovADgLnM4HPr65F5N275acempslqcNL7x/Xq6bjtZzEx1AQAAAMCdovACgLvoUkqCJm5dpR/PHJQkNSxbUQvbDVANX3+DkwEAAABA8UHhBQB3yXen9mnStm90LS1ZzmaLRje8V8816Cgns8XoaAAAAABQrFB4AUABu5qapJe2r9aaU/skSXVKl9cb7QaoTulAg5MBAAAAQPFE4QUABejHyAOauG2VLqUkymIya2SDjnq+4b1ysfCfXwAAAAAoKPzGBQAFIDYtWS///q1WntgjSarhW04L2w1Uw7IVDU4GAAAAAMUfhRcA5LMN545o/JaVik6Ol9lk0oi67TWucWe5OjkbHQ0AAAAASgQKLwDIJwnpqZq5c62+OLpTkhTiXVZvtBugpuWCDU4GAAAAACULhRcA5IMtF45rbNgKnU+KlUkmDavTWi827SI3JxejowEAAABAiUPhBQB3IDkjXbPD12nJ4W2SpEqepbWgXX+1DKhicDIAAAAAKLkovADgNu2IPq0xm5crMuGKJOnxWi01pVk3eThbDU4GAAAAACUbhRcA5FFKZobm7v5RHxzYIoccCvTw0fy2/dUusLrR0QAAAAAAovACgDzZfemMxmxerhNxlyRJD1dvppebd5e3i6vByQAAAAAAf6HwAoBcSLNlasGeX/Tu/k2yOxzyd/PS62366b6gWkZHAwAAAAD8DwovALiFPy6f1+jNy3QkNlqS1LdqY81o0UOlrO4GJwMAAAAA5ITCCwBuIMNu01sRv+rtiA3KdNhV1tVToa17q1twPaOjAQAAAABugsILAHJw6GqUxmxepv1XL0iSuleur9mteqmMq6fByQAAAAAAt0LhBQB/k2m3adH+3zR/zy/KsNvka3XXqy17qWeVhkZHAwAAAADkktnID7fZbJo6dapCQkLk5uamqlWratasWXI4HFlrTCZTjo+5c+fedN///ve/VblyZbm6uqpFixbasWNHQR8OgCLuWGyMeq9dpNd2/agMu00PBNXWr73HUHYBAAAAQBFj6ITXnDlz9O6772rJkiWqW7euwsPDNXToUPn4+GjUqFGSpIsXL2Z7z7p16zRs2DD169fvhvv96quvNHbsWC1atEgtWrTQG2+8oS5duujIkSMqV65cgR4TgKLHZrfrw4Nhen33T0qzZcrbxVUzW/RQv6pNZDKZjI4HAAAAAMgjk+Pv41R3Wffu3eXv76/FixdnbevXr5/c3Ny0dOnSHN/Tu3dvJSQkaP369Tfcb4sWLXTPPffonXfekSTZ7XYFBQXpX//6lyZOnHjd+rS0NKWlpWU9j4+PV1BQkOLi4uTt7X27hwegCDgVf1ljNy/XzphISVKHCjU0t00/BXr4GJwMAAAAAHC7DD2lsXXr1lq/fr2OHj0qSYqIiFBYWJi6deuW4/ro6GitXbtWw4YNu+E+09PTtWvXLnXu3Dlrm9lsVufOnbVt27Yc3xMaGiofH5+sR1BQ0B0cFYCiwO6w6+ODW/XA6je1MyZSHk4umtO6r5beP5SyCwAAAACKOENPaZw4caLi4+NVq1YtWSwW2Ww2zZ49W4MHD85x/ZIlS+Tl5aW+ffvecJ+XL1+WzWaTv79/tu3+/v46fPhwju+ZNGmSxo4dm/X8rwkvAMXT2YSrGhe2QlujTkqSWgdU0fy2/RXkVdrgZAAAAACA/GBo4bVs2TJ99tln+vzzz1W3bl3t3btXo0ePVmBgoIYMGXLd+o8++kiDBw+Wq6trvuawWq2yWq35uk8AhY/D4dBnR3do1o61SspMl5uTs6Y0e1CP12ohs8nQgVcAAAAAQD4ytPCaMGGCJk6cqEceeUSSVL9+fUVGRio0NPS6wmvz5s06cuSIvvrqq5vus2zZsrJYLIqOjs62PTo6WgEBAfl7AACKjAtJcZqwZaU2nf/zFOrm/pU1v21/hXiXNTgZAAAAACC/GTrSkJycLLM5ewSLxSK73X7d2sWLF6tp06Zq2LDhTffp4uKipk2bZruovd1u1/r169WqVav8CQ6gyHA4HFp+bJc6f7NQm84fldXipGn3PKTlXZ+m7AIAAACAYsrQCa8ePXpo9uzZqlSpkurWras9e/ZowYIFevLJJ7Oti4+P1/LlyzV//vwc93PfffepT58+GjlypCRp7NixGjJkiJo1a6bmzZvrjTfeUFJSkoYOHVrgxwSg8IhJTtCLW7/Wz2cPSZIalQ3SG+0GqJpvOYOTAQAAAAAKkqGF19tvv62pU6fq2WefVUxMjAIDAzVixAhNmzYt27ovv/xSDodDgwYNynE/J06c0OXLl7OeP/zww7p06ZKmTZumqKgoNWrUSD/88MN1F7IHUDw5HA6tObVPU7avVmxaslzMFo1tfL+eqddOTmaL0fEAAAAAAAXM5HA4HEaHKGzi4+Pl4+OjuLg4eXt7Gx0HQB5cSU3U5G2rtfb0H5KkeqUD9Ub7gapVimv4AQAAAEBJYeiEFwDkp3WR+zVx6ypdSU2Sk8msUQ3v1b8adpIzU10AAAAAUKJQeAEo8q6lJWva9jVadXKvJKmmr7/eaDdQ9ctWMDYYAAAAAMAQFF4AirT1Zw/rhS0rFZ2SILPJpGfrd9CYRp1ltfCfNwAAAAAoqfiNEECRFJ+eqhk7vtVXx3ZJkqr6+GlhuwFq4lfJ4GQAAAAAAKNReAEocn47f0zjt6zQhaQ4mWTS03XbanyTB+Tm5Gx0NAAAAABAIUDhBaDISMpI0ys7v9d/j/wuSQr2KqOF7QaouX9lY4MBAAAAAAoVCi8ARcK2qJMat3mFziRelSQ9UbuVJjftJndnF4OTAQAAAAAKGwovAIVaSma6QsN/0EeHtkqSKnr6an6b/moTWM3gZAAAAACAworCC0ChFR4dqTFhy3Uq/rIk6R81mmvqPQ/Ky8XV4GQAAAAAgMKMwgtAoZOamaF5e37W+wc2y+5wKMDdW3Pb9FOnijWNjgYAAAAAKAIovAAUKhGXz2nM5mU6GhsjSepftYlmtOghH6ubwckAAAAAAEUFhReAQiHdlqk3I37VO/s2yuawy8/NU3Na99UDleoYHQ0AAAAAUMRQeAEw3MGrFzR683IdvHpRktQrpKFeadlTpVw9DE4GAAAAACiKKLwAGCbDbtO/923UG3vXK9NhV2mrh15t1UvdQxoYHQ0AAAAAUIRReAEwxJFr0RqzeZn2XTkvSepaqa5CW/eWn5uXwckAAAAAAEUdhReAu8pmt+u9A5s1b/dPSrfb5OPiqlkte6lPlUYymUxGxwMAAAAAFAMUXgDumpNxlzRm83LtunRGknRvxZp6vU0/Bbh7G5wMAAAAAFCcUHgBKHB2h10fHdyq13b9qFRbhrycrZreoocGVmvKVBcAAAAAIN9ReAEoUJEJVzQubIW2R52SJLUPrK65bfqpgqevscEAAAAAAMUWhReAAuFwOLT0yO+atfN7JWemy93JRVPveVCP1mzBVBcAAAAAoEBReAHIdxcSYzV+y0r9duGYJKllQIjmt+2vYK8yBicDAAAAAJQEFF4A8o3D4dBXx8I1Y8d3SshIk6vFWRObdtGTdVrLbDIbHQ8AAAAAUEJQeAHIF1HJ8Xpxy9daf+6wJKmpXyUtbDdAVXz8DE4GAAAAAChpKLwA3BGHw6FVJ/dq6vY1iktPkYvZoglNHtDTddvJYmaqCwAAAABw91F4Abhtl1ISNGnrN/rhzAFJUsOyFbWw3QDV8PU3OBkAAAAAoCSj8AJwW747tU+Tt63W1bQkOZstGt3wXj3boKOczRajowEAAAAASjgKLwB5ci01SVO2r9aaU/skSbVLBejN9gNVp3SgwckAAAAAAPgThReAXPvpzEG9uPVrXUpJlMVk1sgGHfV8w3vlYuE/JQAAAACAwoPfUgHcUlxail7+/VutOLFbklTdp5wWthugRn5BBicDAAAAAOB6FF4AbmrDuSOasGWlopLjZZJJI+q10/jG98vVydnoaAAAAAAA5IjCC0COEjPSNHPHWn1+dIckKcS7rBa2HaBm/sEGJwMAAAAA4OYovABcZ8uF4xq3ZYXOJcZKkp6s3VqTmnWVm5OLscEAAAAAAMgFCi8AWZIz0jU7fJ2WHN4mSarkWVrz2/VXq4AqBicDAAAAACD3KLwASJJ2RJ/WmM3LFZlwRZL0WM0WeumeB+XhbDU4GQAAAAAAeUPhBZRwKZkZmrv7R31wYIsccqi8u4/mt+2v9hWqGx0NAAAAAIDbQuEFlGC7L53R2M3LdTzukiTp4epN9XLzHvJ2cTU4GQAAAAAAt4/CCyiB0myZWrj3F/3nj02yOxwq5+al19v0Veeg2kZHAwAAAADgjlF4ASXM/ivnNXrzch2+FiVJ6lOlkWa27KlSVneDkwEAAAAAkD8ovIASIsNu09sRG/RWxK/KdNhVxtVDr7Xuo27B9YyOBgAAAABAvqLwAkqAw9eiNGbzcv1x5bwk6aHK9fVqq14q4+ppcDIAAAAAAPIfhRdQjGXabVq0/zct2POL0u02+VrdNbtlL/UMaSCTyWR0PAAAAAAACgSFF1BMHY+N0Ziw5dpz6awk6f6g2prTuq/KuXsZnAwAAAAAgIJF4QUUMza7XYsPbtGc3T8qzZYpbxdXzWjeQ/2rNWGqCwAAAABQIlB4AcXIqfjLGhe2QjuiT0uSOlSooblt+inQw8fYYAAAAAAA3EUUXkAxYHfYteTQdr26a51SMjPk4eSiac276x817mGqCwAAAABQ4lB4AUXc2YSrGr9lpbZcPCFJah1QRfPb9leQV2mDkwEAAAAAYAwKL6CIcjgc+vzoTs3c8Z2SMtPl5uSsyU27aUjtljKbzEbHAwAAAADAMBReQBF0ISlOL2xZqY3nj0qS7ikXrAXtBijEu6zByQAAAAAAMB6FF1CEOBwOrTyxW9N+/1bx6amyWpz0QpMHNLxOW1nMTHUBAAAAACBReAFFRkxygiZu/Vo/nT0kSWpYtqLeaDdQ1X3LGZwMAAAAAIDChcILKALWnIzQ5O2rFZuWLGezRWMbddY/67eXk9lidDQAAAAAAAodCi+gELuSmqgp21bru9N/SJLqlQ7UwnYDVbt0gMHJAAAAAAAovCi8gEJqXeR+Tdr6jS6nJsrJZNa/GnbSqIb3ypmpLgAAAAAAborCCyhkYtOSNXX7Gq06uVeSVNPXX2+0G6j6ZSsYGwwAAAAAgCKCwgsoRNafPawXtqxUdEqCzCaT/lmvg8Y27iyrhX9VAQAAAADILX6LBgqB+PRUzdjxnb46Fi5JqurjpwVtB6hpuUoGJwMAAAAAoOih8AIMtvnCMY0LW6ELSXEyyaThddvohSZd5ObkbHQ0AAAAAACKJAovwCBJGWmaHb5Onx7eLkkK9iqjBW37q0VAiMHJAAAAAAAo2ii8AANsjzqpcWErFJlwVZI0pFYrTWnWTe7OLgYnAwAAAACg6KPwAu6ilMx0vbbrR310cKsccqiCh6/mt+2vtoHVjI4GAAAAAECxYTbyw202m6ZOnaqQkBC5ubmpatWqmjVrlhwOR7Z1hw4dUs+ePeXj4yMPDw/dc889OnPmzA33+8knn8hkMmV7uLq6FvThADe1KyZSD6x+S4sPbpFDDg2qcY9+6T2asgsAAAAAgHxm6ITXnDlz9O6772rJkiWqW7euwsPDNXToUPn4+GjUqFGSpBMnTqht27YaNmyYZsyYIW9vbx04cOCWBZa3t7eOHDmS9dxkMhXosQA3kpqZofl7ftF7B36T3eGQv7u35rbpp3sr1jQ6GgAAAAAAxZKhhdfWrVvVq1cvPfTQQ5KkypUr64svvtCOHTuy1kyZMkUPPvigXn/99axtVatWveW+TSaTAgICcpUjLS1NaWlpWc/j4+NzewjATUVcPqcxm5fpaGyMJKl/1Saa3qK7fK3uBicDAAAAAKD4MvSUxtatW2v9+vU6evSoJCkiIkJhYWHq1q2bJMlut2vt2rWqUaOGunTponLlyqlFixb65ptvbrnvxMREBQcHKygoSL169dKBAwduuDY0NFQ+Pj5Zj6CgoHw5PpRc6bZMzd39k3p+9x8djY2Rn5unFt/7mN5oP5CyCwAAAACAAmZy/O8Fs+4iu92uyZMn6/XXX5fFYpHNZtPs2bM1adIkSVJUVJTKly8vd3d3vfLKK+rUqZN++OEHTZ48WRs2bFCHDh1y3O+2bdt07NgxNWjQQHFxcZo3b55+++03HThwQBUrVrxufU4TXkFBQYqLi5O3t3fBHDyKrYNXL2j05uU6ePWiJKlnSAO90rKXSrt6GJwMAAAAAICSwdDC68svv9SECRM0d+5c1a1bV3v37tXo0aO1YMECDRkyRBcuXFCFChU0aNAgff7551nv69mzpzw8PPTFF1/k6nMyMjJUu3ZtDRo0SLNmzbrl+vj4ePn4+FB4IU8y7Tb9e99GvRHxqzLsNpWyuiu0VW91D2lgdDQAAAAAAEoUQ6/hNWHCBE2cOFGPPPKIJKl+/fqKjIxUaGiohgwZorJly8rJyUl16tTJ9r7atWsrLCws15/j7Oysxo0b6/jx4/maH/jL0dhojdm8XBGXz0mSulSqo9da95Gfm5fByQAAAAAAKHkMLbySk5NlNme/jJjFYpHdbpckubi46J577sl2t0VJOnr0qIKDg3P9OTabTX/88YcefPDBOw8N/I3Nbtf7BzZr3p6flWbLlI+Lq2a27KW+VRpxZ1AAAAAAAAxiaOHVo0cPzZ49W5UqVVLdunW1Z88eLViwQE8++WTWmgkTJujhhx9W+/bts67h9e2332rjxo1Zax5//HFVqFBBoaGhkqSZM2eqZcuWqlatmmJjYzV37lxFRkZq+PDhd/sQUYydjLussWHLFR4TKUnqVKGmXm/TV+U9fAxOBgAAAABAyWZo4fX2229r6tSpevbZZxUTE6PAwECNGDFC06ZNy1rTp08fLVq0SKGhoRo1apRq1qyplStXqm3btllrzpw5k21S7Nq1a3rqqacUFRWlUqVKqWnTptq6det1p0YCt8PusOvjQ9sUGv6DUm0Z8nS26uXm3fVI9WZMdQEAAAAAUAgYetH6woqL1uNGziRc1diw5doedUqS1C6wmua16a8Knr7GBgMAAAAAAFkMnfACigqHw6GlR37XrJ3fKzkzXe5OLnrpngf1WM0WTHUBAAAAAFDIUHgBt3AhMVbjt6zUbxeOSZJa+IdoQbv+CvYqY3AyAAAAAACQEwov4AYcDoeWHd+l6b9/q4SMNFktTprUtKuerNNaZpP51jsAAAAAAACGoPACchCdHK8Xt36tX84eliQ18aukhe0GqKqPn8HJAAAAAADArVB4AX/jcDj0zckIvbR9teLSU+Ritmhc4/v1TL32spiZ6gIAAAAAoCig8AL+v8spiZq0bZXWRR6QJNUvU0EL2w1QrVIBBicDAAAAAAB5QeEFSPru9B+avPUbXU1LkpPJrNGN7tNzDTrK2WwxOhoAAAAAAMgjCi+UaNdSk/TS9jVafSpCklS7VIDeaDdQdcsEGpwMAAAAAADcLgovlFg/nzmoF7euUkxKgiwms56r30GjG90nFwv/WgAAAAAAUJTxmz1KnLi0FE3f8a2WH98tSaruU04L2w1QI78gg5MBAAAAAID8QOGFEmXj+aMaH7ZCUcnxMsmkEfXaaXzj++Xq5Gx0NAAAAAAAkE8ovFAiJGakaeaOtfr86A5JUmWvMnqj3UA18w82OBkAAAAAAMhvFF4o9rZcPKFxYct1LjFWkvRk7daa1Kyr3JxcjA0GAAAAAAAKBIUXiq3kjHS9umudPjm0TZIU5FlK89v2V+vyVQ1OBgAAAAAAChKFF4qlndGnNWbzcp1OuCJJerRmC710z4PydLYanAwAAAAAABQ0Ci8UKymZGZq3+ye9fyBMDjlU3t1H89r2U4cKNYyOBgAAAAAA7hIKLxQbey6d1ZjNy3Q87pIkaWC1pnq5eXf5WN0MTgYAAAAAAO4mCi8UeWm2TL2xd73+/cdG2R0OlXPz0utt+qpzUG2jowEAAAAAAANQeKFI23/lvEZvXq7D16IkSb2rNNKsFj1UytXD4GQAAAAAAMAoFF4okjLsNr0dsUFvRfyqTIddZVw99Gqr3nqocn2jowEAAAAAAINReKHIOXwtSmM2L9cfV85Lkh4MrqdXW/VWWTdPg5MBAAAAAIDCgMILRUam3aZF+zdrwZ6flW63ycfFTbNb9VKvkIYymUxGxwMAAAAAAIUEhReKhBNxlzR68zLtuXRWktQ5qJbmtO4rf3dvg5MBAAAAAIDChsILhZrNbtdHh7botV0/Ks2WKS9nq2a06KEB1Zoy1QUAAAAAAHJE4YVC63T8FY0NW64d0aclSR0Cq2tum34K9PQ1NBcAAAAAACjcKLxQ6Ngddn16+HfNDv9eKZkZcndy0bR7HtLgms2Z6gIAAAAAALdE4YVC5VziNY0LW6EtF09IkloFVNH8tv1Vyau0wckAAAAAAEBRQeGFQsHhcOiLYzs1c8daJWakydXirMnNuuqJ2q1kNpmNjgcAAAAAAIoQCi8Y7mJSnF7Y8rU2nD8iSWpWLlgL2g5QFZ+yBicDAAAAAABFEYUXDONwOLTyxB69/PsaxaWnympx0gtNHtDwOm1lMTPVBQAAAAAAbg+FFwwRk5ygSdtW6cczByVJDctW1BvtBqq6bzmDkwEAAAAAgKKOwgt33ZqTEZqyfbWupSXL2WzR2Ead9c/67eVkthgdDQAAAAAAFAMUXrhrrqYmafK2b/Td6T8kSXVLl9fCdgNVp3R5g5MBAAAAAIDihMILd8UPkQc0cesqXU5NlMVk1r8adtKoBp3kYuFHEAAAAAAA5C/aBhSo2LRkTfv9W319Yo8kqaavvxa2G6AGZSsanAwAAAAAABRXFF4oML+eO6IJW1YqOjleZpNJz9Rrr3GN75eVqS4AAAAAAFCAaB6Q7xLSUzVjx3f68li4JKmKd1ktbDdQTctVMjgZAAAAAAAoCSi8kK/CLhzXuLAVOp8UK5NMGl63jV5o8oDcnFyMjgYAAAAAAEoICi/ki6SMNM0OX6dPD2+XJAV7ldb8tv3VMqCKwckAAAAAAEBJQ+GFO7Y96qTGha1QZMJVSdKQWi01uVk3eThbDU4GAAAAAABKIgov3LaUzHTN2fWjFh/cKoccquDhq3lt+6ldYHWjowEAAAAAgBKMwgu3ZVdMpMZsXq6T8ZclSY9Ub6aXm3eXl4urwckAAAAAAEBJR+GFPEnNzND8Pb/ovQO/ye5wyN/dW6+37qv7gmoZHQ0AAAAAAEAShRfyYN/lcxq9eZmOxsZIkvpWbayZLXrI1+pucDIAAAAAAID/Q+GFW0q3ZerNiF/1zr6NsjnsKuvqqdda91HX4LpGRwMAAAAAALgOhRdu6uDVixqzeZkOXL0oSepeub5ebdVbpV09DE4GAAAAAACQMwov5CjTbtN//tikhXvXK8NuUymru15t1Vs9QhoYHQ0AAAAAAOCmKLxwnWOxMRq9eZkiLp+TJHWpVEevte4jPzcvg5MBAAAAAADcGoUXstjsdn1wIExz9/ykNFumfFxcNbNlL/Wt0kgmk8noeAAAAAAAALlC4QVJ0sm4yxobtlzhMZGSpE4Vaur1Nn1V3sPH4GQAAAAAAAB5Q+FVwtkddn18aJtCw39Qqi1Dns5Wvdy8ux6p3oypLgAAAAAAUCRReJVgZxKualzYCm2LOilJalu+mua17aeKnqUMTgYAAAAAAHD7KLxKIIfDoc+O7NCsnWuVlJkuNydnvdTsQT1Wq4XMJrPR8QAAAAAAAO4IhVcJcyExVhO2rNSmC8ckSS38K2t+2wGq7F3G4GQAAAAAAAD5g8KrhHA4HFp+fJde/v1bJWSkyWpx0sSmXTSsThumugAAAAAAQLFC4VUCRCfH68WtX+uXs4clSY39gvRGu4Gq6uNncDIAAAAAAID8R+FVjDkcDq0+FaEp21YrLj1FLmaLxja+X8/Uaycns8XoeAAAAAAAAAWCwquYupySqMnbvtH3kfslSfXLVNDCdgNUq1SAwckAAAAAAAAKFoVXMbT29B+avO0bXUlNkpPJrOcb3auRDTrJmakuAAAAAABQAlB4FSPXUpP00u9rtPpkhCSpVqkAvdFugOqVqWBwMgAAAAAAgLvH0Nvz2Ww2TZ06VSEhIXJzc1PVqlU1a9YsORyObOsOHTqknj17ysfHRx4eHrrnnnt05syZm+57+fLlqlWrllxdXVW/fn19//33BXkohvv5zEHd980bWn0yQmaTSf9q0Elre4yk7AIAAAAAACWOoRNec+bM0bvvvqslS5aobt26Cg8P19ChQ+Xj46NRo0ZJkk6cOKG2bdtq2LBhmjFjhry9vXXgwAG5urrecL9bt27VoEGDFBoaqu7du+vzzz9X7969tXv3btWrV+9uHd5dEZeWouk7vtXy47slSdV8/LSw3UA19gsyOBkAAAAAAIAxTI7/Hae6i7p37y5/f38tXrw4a1u/fv3k5uampUuXSpIeeeQROTs767///W+u9/vwww8rKSlJ3333Xda2li1bqlGjRlq0aNF169PS0pSWlpb1PD4+XkFBQYqLi5O3t/ftHNpdsfH8UU0IW6mLyXEyyaSn67bV+CYPyM3J2ehoAAAAAAAAhjH0lMbWrVtr/fr1Onr0qCQpIiJCYWFh6tatmyTJbrdr7dq1qlGjhrp06aJy5cqpRYsW+uabb266323btqlz587ZtnXp0kXbtm3LcX1oaKh8fHyyHkFBhX86KsNu07Tta3QxOU7BXmW08sERmtr8IcouAAAAAABQ4hlaeE2cOFGPPPKIatWqJWdnZzVu3FijR4/W4MGDJUkxMTFKTEzUa6+9pq5du+qnn35Snz591LdvX23atOmG+42KipK/v3+2bf7+/oqKispx/f9r796DojrvMI4/y1URAW+wohCcRNF4QWMSB5KUoFYwiNhmEocxwRCnVoU0mmg7tETaTg3VjKaam206imltjY5Y1FQ7hltqJIiKN0jUSSUmEWTUKqIRFd7+4bDJlosgGtjl+5nZmew573vO793Mw8EfZ3dTU1N18eJF2+PLL7+8c4u8S9xdXLXi0aeUNCxCu+Jf1MMBIR1dEgAAAAAAQKfQoZ/htXHjRq1fv15/+9vfNHz4cB08eFDz589XYGCgZs6cqfr6eklSfHy8FixYIEkaPXq09uzZo9WrVysyMvKO1OHp6SlPT887cqzv04MB9+jBgHs6ugwAAAAAAIBOpUMbXosWLbLd5SVJI0eO1BdffKGMjAzNnDlTffv2lZubm+6//367ecOGDdPu3bubPa7VatWZM2fstp05c0ZWq/XOLwIAAAAAAACdSoe+pfHKlStycbEvwdXV1XZnl4eHhx566CEdO3bMbszx48d1zz3N39kUHh6unJwcu227du1SeHj4HaocAAAAAAAAnVWH3uEVFxenJUuWKDg4WMOHD1dJSYlWrFi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          },
          "metadata": {}
        }
      ]
    },
    {
      "source": [
        "from matplotlib import pyplot as plt\n",
        "_df_17['Wind Speed_km/h'].plot(kind='line', figsize=(8, 4), title='Wind Speed_km/h')\n",
        "plt.gca().spines[['top', 'right']].set_visible(False)"
      ],
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 391
        },
        "id": "-yvP8uE7vhfV",
        "outputId": "8c2e36d6-576a-405f-ec96-e5faa66bae9c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x400 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "source": [
        "from matplotlib import pyplot as plt\n",
        "_df_16['Rel Hum_%'].plot(kind='line', figsize=(8, 4), title='Rel Hum_%')\n",
        "plt.gca().spines[['top', 'right']].set_visible(False)"
      ],
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 391
        },
        "id": "8Im3ma_lvgft",
        "outputId": "c6c0b5e2-116d-4877-dfe2-126408757c09"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x400 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "source": [
        "from matplotlib import pyplot as plt\n",
        "_df_15['Dew Point Temp_C'].plot(kind='line', figsize=(8, 4), title='Dew Point Temp_C')\n",
        "plt.gca().spines[['top', 'right']].set_visible(False)"
      ],
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 391
        },
        "id": "edoVsr1nvfeg",
        "outputId": "8daaca6f-d55a-4b85-d5bf-e5f1d44cb08f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x400 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "source": [
        "from matplotlib import pyplot as plt\n",
        "import seaborn as sns\n",
        "figsize = (12, 1.2 * len(_df_21['Date/Time'].unique()))\n",
        "plt.figure(figsize=figsize)\n",
        "sns.violinplot(_df_21, x='Dew Point Temp_C', y='Date/Time', inner='stick', palette='Dark2')\n",
        "sns.despine(top=True, right=True, bottom=True, left=True)"
      ],
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "id": "3NSOO2-ivVFj",
        "outputId": "ac90d7a9-1711-4799-a63f-3e4f831385a4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "source": [
        "from matplotlib import pyplot as plt\n",
        "import seaborn as sns\n",
        "figsize = (12, 1.2 * len(_df_19['Date/Time'].unique()))\n",
        "plt.figure(figsize=figsize)\n",
        "sns.violinplot(_df_19, x='Temp_C', y='Date/Time', inner='stick', palette='Dark2')\n",
        "sns.despine(top=True, right=True, bottom=True, left=True)"
      ],
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "id": "Qo9hLWsYvTyF",
        "outputId": "68ad57ee-7b59-4e18-a4be-5439615dd3ba"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "source": [
        "from matplotlib import pyplot as plt\n",
        "import seaborn as sns\n",
        "figsize = (12, 1.2 * len(_df_20['Weather'].unique()))\n",
        "plt.figure(figsize=figsize)\n",
        "sns.violinplot(_df_20, x='Temp_C', y='Weather', inner='stick', palette='Dark2')\n",
        "sns.despine(top=True, right=True, bottom=True, left=True)"
      ],
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "GFiTBnCQvPax",
        "outputId": "3158e358-4d1d-4113-923f-b3da040ee75d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x240 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "source": [
        "from matplotlib import pyplot as plt\n",
        "import seaborn as sns\n",
        "figsize = (15, 1.2 * len(_df_22['Weather'].unique()))\n",
        "plt.figure(figsize=figsize)\n",
        "sns.violinplot(_df_22, x='Dew Point Temp_C', y='Weather', inner='stick', palette='Dark2')\n",
        "sns.despine(top=True, right=True, bottom=True, left=True)"
      ],
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "zPfnxf1EvIJT",
        "outputId": "2f89b6e4-3a60-45e9-d2ae-4c3a97ff0010"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x240 with 1 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "HrkXj9Qxu76C"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}