projekt_engeto_academy.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install sqlalchemy\n",
    "!pip install pymysql"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# python -m venv venv \n",
    "# .\\venv\\Scripts\\activate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import sqlalchemy\n",
    "\n",
    "student_conn_string = \"mysql+pymysql://student:p7%40vw7MCatmnKjy7@data.engeto.com/data\"\n",
    "alchemy_conn = sqlalchemy.create_engine(student_conn_string)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# edinburgh_bikes\n",
    "import pandas as pd\n",
    "from sqlalchemy import create_engine, text\n",
    "\n",
    "# Create an SQLAlchemy engine with your database connection details\n",
    "engine = create_engine('mysql+pymysql://student:p7%40vw7MCatmnKjy7@data.engeto.com/data')\n",
    "\n",
    "# Your SQL query as a text object\n",
    "query = text(\n",
    "\"\"\"\n",
    "SELECT\n",
    "*\n",
    "FROM edinburgh_bikes as ed;\n",
    "\"\"\"\n",
    ")\n",
    "\n",
    "# Execute the query and read the result into a DataFrame\n",
    "with engine.connect() as conn:\n",
    "    result = conn.execute(query)\n",
    "    edinburgh_bikes = pd.DataFrame(result.fetchall(), columns=result.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# edinburgh_weather\n",
    "import pandas as pd\n",
    "from sqlalchemy import create_engine, text\n",
    "\n",
    "# Create an SQLAlchemy engine with your database connection details\n",
    "engine = create_engine('mysql+pymysql://student:p7%40vw7MCatmnKjy7@data.engeto.com/data')\n",
    "\n",
    "# Your SQL query as a text object\n",
    "query = text(\n",
    "\"\"\"\n",
    "SELECT\n",
    "*\n",
    "FROM edinburgh_weather as ed;\n",
    "\"\"\"\n",
    ")\n",
    "\n",
    "# Execute the query and read the result into a DataFrame\n",
    "with engine.connect() as conn:\n",
    "    result = conn.execute(query)\n",
    "    edinburgh_weather = pd.DataFrame(result.fetchall(), columns=result.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Example DataFrames with different column names for the key\n",
    "df_left = pd.DataFrame({'left_key': [1, 2, 3], 'value': ['a', 'b', 'c']})\n",
    "df_right = pd.DataFrame({'right_key': [2, 3, 4], 'description': ['X', 'Y', 'Z']})\n",
    "\n",
    "# Merge using left_on and right_on since the key column names differ\n",
    "merged_df = df_left.merge(df_right, left_on='left_key', right_on='right_key', how='left')\n",
    "\n",
    "print(merged_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "edinburgh_bikes.head(10)\n",
    "edinburgh_weather.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "edinburgh_bikes = pd.DataFrame(edinburgh_bikes)\n",
    "edinburgh_weather = pd.DataFrame(edinburgh_weather)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "edinburgh_bikes['started_at'] = pd.to_datetime(edinburgh_bikes['started_at'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "edinburgh_weather['datetime'] = pd.to_datetime(edinburgh_weather['date'] + ' ' + edinburgh_weather['time'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def remove_minutes_seconds(dt_str):\n",
    "    dt = pd.to_datetime(dt_str)\n",
    "    dt = dt.replace(minute=0,second=0)\n",
    "    return dt\n",
    "\n",
    "edinburgh_bikes['datetime02'] = edinburgh_bikes['started_at'].apply(remove_minutes_seconds)\n",
    "edinburgh_weather['datetime'] = edinburgh_weather['datetime'].apply(remove_minutes_seconds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "pd.set_option('display.max_columns', None)  # Display all columns\n",
    "pd.set_option('display.max_rows', None)     # Display all rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "merged_data = edinburgh_bikes.merge(edinburgh_weather, left_on='datetime02', right_on='datetime', how='left')\n",
    "merged_data.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Odstraneni textu z cisel\n",
    "merged_data['temp'] = merged_data['temp'].str.replace(\" °c\", \"\", regex=False).astype(float)\n",
    "merged_data['feels'] = merged_data['feels'].str.replace(\" °c\", \"\", regex=False).astype(float)\n",
    "merged_data['gust'] = merged_data['gust'].str.replace(\" km/h\", \"\", regex=False).astype('float')\n",
    "merged_data['rain'] = merged_data['rain'].str.replace(\" mm\", \"\", regex=False).astype(float)\n",
    "merged_data['humidity'] = merged_data['humidity'].str.replace(\"%\", \"\", regex=False).astype('Int64')\n",
    "merged_data['cloud'] = merged_data['cloud'].str.replace(\"%\", \"\", regex=False).astype('Int64')\n",
    "merged_data['pressure'] = merged_data['pressure'].str.replace(\" mb\", \"\", regex=False).astype('Int64')\n",
    "\n",
    "# Use regex to remove any characters following the numeric part of the wind speed values\n",
    "merged_data['wind'] = merged_data['wind'].str.extract('(\\d+)').astype('float')\n",
    "\n",
    "# # Now, you can safely convert the column to 'Int64' if keeping NaN values is important\n",
    "# merged_data['wind'] = merged_data['wind'].astype('Int64')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "merged_dataa = pd.DataFrame(merged_data)\n",
    "tolerance = 1e-6  # Define a tolerance level\n",
    "temp = merged_dataa[(merged_dataa['temp'] >= 12.386976 - tolerance) & (merged_dataa['temp'] <= 12.386976 + tolerance)]\n",
    "temp.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>started_at</th>\n",
       "      <th>duration</th>\n",
       "      <th>start_station_id</th>\n",
       "      <th>start_station_latitude</th>\n",
       "      <th>start_station_longitude</th>\n",
       "      <th>end_station_id</th>\n",
       "      <th>end_station_latitude</th>\n",
       "      <th>end_station_longitude</th>\n",
       "      <th>datetime02</th>\n",
       "      <th>temp</th>\n",
       "      <th>feels</th>\n",
       "      <th>wind</th>\n",
       "      <th>gust</th>\n",
       "      <th>rain</th>\n",
       "      <th>humidity</th>\n",
       "      <th>cloud</th>\n",
       "      <th>pressure</th>\n",
       "      <th>datetime</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
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       "      <td>438259</td>\n",
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       "      <td>114777.0</td>\n",
       "      <td>114777.0</td>\n",
       "      <td>114777</td>\n",
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       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>9043.264173</td>\n",
       "      <td>2020-04-21 12:26:31.690651392</td>\n",
       "      <td>1948.838039</td>\n",
       "      <td>924.245437</td>\n",
       "      <td>55.950637</td>\n",
       "      <td>-3.196594</td>\n",
       "      <td>969.345296</td>\n",
       "      <td>55.952541</td>\n",
       "      <td>-3.195375</td>\n",
       "      <td>2020-04-21 11:56:35.299126272</td>\n",
       "      <td>12.386976</td>\n",
       "      <td>11.069753</td>\n",
       "      <td>15.811164</td>\n",
       "      <td>21.149342</td>\n",
       "      <td>0.314286</td>\n",
       "      <td>73.612658</td>\n",
       "      <td>59.892932</td>\n",
       "      <td>1012.838827</td>\n",
       "      <td>2020-02-05 18:23:59.096683008</td>\n",
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       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>2018-09-15 08:52:05</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>171.000000</td>\n",
       "      <td>55.908404</td>\n",
       "      <td>-3.407156</td>\n",
       "      <td>171.000000</td>\n",
       "      <td>53.395525</td>\n",
       "      <td>-3.407156</td>\n",
       "      <td>2018-09-15 08:00:00</td>\n",
       "      <td>-4.000000</td>\n",
       "      <td>-5.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>38.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>958.0</td>\n",
       "      <td>2018-09-15 09:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>3252.000000</td>\n",
       "      <td>2019-10-03 15:46:27</td>\n",
       "      <td>624.000000</td>\n",
       "      <td>260.000000</td>\n",
       "      <td>55.940238</td>\n",
       "      <td>-3.207964</td>\n",
       "      <td>262.000000</td>\n",
       "      <td>55.941791</td>\n",
       "      <td>-3.208070</td>\n",
       "      <td>2019-10-03 15:00:00</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>64.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1005.0</td>\n",
       "      <td>2019-08-25 06:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>7127.000000</td>\n",
       "      <td>2020-06-04 11:26:46</td>\n",
       "      <td>1163.000000</td>\n",
       "      <td>1019.000000</td>\n",
       "      <td>55.947600</td>\n",
       "      <td>-3.192444</td>\n",
       "      <td>1024.000000</td>\n",
       "      <td>55.951501</td>\n",
       "      <td>-3.191862</td>\n",
       "      <td>2020-06-04 11:00:00</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>74.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>1014.0</td>\n",
       "      <td>2020-04-21 18:00:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "               index                     started_at       duration  \\\n",
       "count  438259.000000                         438259  438259.000000   \n",
       "mean     9043.264173  2020-04-21 12:26:31.690651392    1948.838039   \n",
       "min         0.000000            2018-09-15 08:52:05      61.000000   \n",
       "25%      3252.000000            2019-10-03 15:46:27     624.000000   \n",
       "50%      7127.000000            2020-06-04 11:26:46    1163.000000   \n",
       "\n",
       "       start_station_id  start_station_latitude  start_station_longitude  \\\n",
       "count     438259.000000           438259.000000            438259.000000   \n",
       "mean         924.245437               55.950637                -3.196594   \n",
       "min          171.000000               55.908404                -3.407156   \n",
       "25%          260.000000               55.940238                -3.207964   \n",
       "50%         1019.000000               55.947600                -3.192444   \n",
       "\n",
       "       end_station_id  end_station_latitude  end_station_longitude  \\\n",
       "count   438259.000000         438259.000000          438259.000000   \n",
       "mean       969.345296             55.952541              -3.195375   \n",
       "min        171.000000             53.395525              -3.407156   \n",
       "25%        262.000000             55.941791              -3.208070   \n",
       "50%       1024.000000             55.951501              -3.191862   \n",
       "\n",
       "                          datetime02           temp          feels  \\\n",
       "count                         438259  114777.000000  114777.000000   \n",
       "mean   2020-04-21 11:56:35.299126272      12.386976      11.069753   \n",
       "min              2018-09-15 08:00:00      -4.000000      -5.000000   \n",
       "25%              2019-10-03 15:00:00       9.000000       6.000000   \n",
       "50%              2020-06-04 11:00:00      13.000000      12.000000   \n",
       "\n",
       "                wind           gust           rain   humidity      cloud  \\\n",
       "count  114777.000000  114777.000000  114777.000000   114777.0   114777.0   \n",
       "mean       15.811164      21.149342       0.314286  73.612658  59.892932   \n",
       "min         0.000000       0.000000       0.000000       38.0        0.0   \n",
       "25%         9.000000      13.000000       0.000000       64.0       30.0   \n",
       "50%        15.000000      20.000000       0.000000       74.0       69.0   \n",
       "\n",
       "          pressure                       datetime  \n",
       "count     114777.0                         114777  \n",
       "mean   1012.838827  2020-02-05 18:23:59.096683008  \n",
       "min          958.0            2018-09-15 09:00:00  \n",
       "25%         1005.0            2019-08-25 06:00:00  \n",
       "50%         1014.0            2020-04-21 18:00:00  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Data analysis\n",
    "summary = merged_data.describe()\n",
    "summary.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\ercak\\AppData\\Local\\Temp\\ipykernel_108540\\1199115197.py:22: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  data_2019['rental_count_2019'] = data_2019.groupby(data_2019['datetime02'].dt.month)['datetime02'].transform('count')\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>started_at</th>\n",
       "      <th>rental_count_2019</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>14147</th>\n",
       "      <td>2019-01-01 05:58:47</td>\n",
       "      <td>4864</td>\n",
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      ],
      "text/plain": [
       "               started_at  rental_count_2019\n",
       "14147 2019-01-01 05:58:47               4864"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# data_2019 = merged_data[merged_data['datetime02'].dt.year == 2019]\n",
    "# # pocet = data_2019.groupby['started_at'].count()\n",
    "# monthly_counts_2019 = data_2019.groupby(data_2019['datetime02'].dt.month).size().reset_index(name='pocet')\n",
    "# monthly_counts_2019.head(10)\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "# Ensure 'datetime02' is a datetime type\n",
    "merged_data['datetime02'] = pd.to_datetime(merged_data['datetime02'])\n",
    "\n",
    "# Create a new column 'rental_count_2019' initialized with NaN\n",
    "merged_data['rental_count_2019'] = np.nan\n",
    "\n",
    "# Create a mask for rows where 'datetime02' year is 2019\n",
    "mask = merged_data['datetime02'].dt.year == 2019\n",
    "\n",
    "# Use the mask to filter the data to only include 2019\n",
    "data_2019 = merged_data[mask]\n",
    "\n",
    "# Group by the month of 'datetime02', and for each group, count the non-NaN entries\n",
    "# Then use transform to broadcast the month's count to the original rows\n",
    "data_2019['rental_count_2019'] = data_2019.groupby(data_2019['datetime02'].dt.month)['datetime02'].transform('count')\n",
    "\n",
    "# Update the 'rental_count_2019' column in the original dataframe for the 2019 entries\n",
    "# merged_data.loc[mask, 'rental_count_2019'] = data_2019['rental_count_2019']\n",
    "\n",
    "# Now, merged_data has a 'rental_count_2019' column with the count of rentals per month for the year 2019\n",
    "# and NaN for other years\n",
    "selection = data_2019[['started_at', 'rental_count_2019']]\n",
    "selection.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "# Ensure 'started_at' is a datetime column\n",
    "merged_data['started_at'] = pd.to_datetime(merged_data['started_at'])\n",
    "merged_data['ended_at'] = pd.to_datetime(merged_data['ended_at'])\n",
    "# Create a 'year_month' column for aggregating by year and month\n",
    "merged_data['year_month'] = merged_data['started_at'].dt.to_period('M')\n",
    "\n",
    "# Group by 'year_month' to get the total rentals per month\n",
    "monthly_rentals = merged_data.groupby('year_month')['started_at'].count()\n",
    "\n",
    "# Convert the PeriodIndex to timestamps for plotting\n",
    "monthly_rentals.index = monthly_rentals.index.to_timestamp()\n",
    "\n",
    "# Plot the monthly rentals\n",
    "plt.figure(figsize=(12, 6))\n",
    "monthly_rentals.plot(kind='line', marker='o')\n",
    "\n",
    "plt.title('Bike Rentals Per Month')\n",
    "plt.xlabel('Month')\n",
    "plt.ylabel('Number of Rentals')\n",
    "plt.grid(True)\n",
    "plt.xticks(rotation=45)\n",
    "plt.tight_layout()  # Adjust layout to make room for x-axis labels\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = merged_data\n",
    "df['duration_mins'] = (df['ended_at'] - df['started_at']).dt.total_seconds() / 60\n",
    "\n",
    "\n",
    "minutes = df[['duration_mins', 'ended_at']]\n",
    "\n",
    "# Filter rows where 'ended_at' year is 2019\n",
    "minutes_2019 = minutes[minutes['ended_at'].dt.year == 2019]\n",
    "minutes_2019.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fill NaN values with the mean of the column\n",
    "df['temp'] = df['temp'].fillna(df['temp'].mean())\n",
    "df['feels'] = df['feels'].fillna(df['feels'].mean())\n",
    "df['wind'] = df['wind'].fillna(df['wind'].mean())\n",
    "df['gust'] = df['gust'].fillna(df['gust'].mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Two conditions and select only two columns\n",
    "data = df[(df['start_station_name']=='Charlotte Square') & (df['started_at'].dt.year == 2019)]\n",
    "data = data[['start_station_name', 'started_at']]\n",
    "data.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Zadání:\n",
    "\n",
    "V Edinburghu, stejně jako v dalších městech, funguje systém \"bike sharing\" - ve městě jsou stanice s koly, člověk si může nějaké půjčit a potom ho vrátit v nějaké další stanici. Problém je, že v některých stanicích se kola pravidelně hromadí a jinde naopak chybí. Provozovatel kol, firma Just Eat Cycles, zadala projekt, jehož cílem je systém zefektivnit.\n",
    "\n",
    "Coby datový analytik jste součástí týmu, který na projektu pracuje. Vaším úkolem je zpracovat relevantní data a zjistit z nich informace užitečné pro zbytek týmu. Máte k dispozici data o všech výpůjčkách (na ENGETO databázi v tabulce edinburgh_bikes). Proveďte standardní deskriptivní statistiku dat. Také zjistěte minimálně následující informace:\n",
    "\n",
    "- identifikujte aktivní a neaktivní stanice\n",
    "- identifikujte nejfrekventovanější stanice\n",
    "- identifikujte stanice, na kterých se kola hromadí a stanice, kde potenciálně chybí!\n",
    "- spočítejte vzdálenosti mezi jednotlivými stanicemi\n",
    "- jak dlouho trvá jedna výpůjčka? Najděte odlehlé hodnoty, zobrazte histogram\n",
    "\n",
    "Analýza poptávky:\n",
    "\n",
    "- zobrazte vývoj poptávky po půjčování kol v čase\n",
    "- identifikujte příčiny výkyvů poptávky\n",
    "- zjistěte vliv počasí na poptávku po kolech (údaje o počasí v Edinburghu jsou v tabulce edinburgh_weather)\n",
    "- půjčují si lidé kola více o víkendu než během pracovního týdne?\n",
    "Výstupem analýzy bude ideálně jupyter notebook nebo colab notebook uložený na Vašem githubu. Výstupy Vaší analýzy musí být zřejmé i bez spouštění kódu. V textových buňkách popište, jak jste postupovali a napište své závěry. Pokud v zadání chybí nějaká informace, doplňte ji podle vlastního uvážení, své rozhodnutí uveďte a vysvětlete v notebooku."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Proveďme standardní deskriptivní statistiku dat o výpůjčkách v rámci projektu \"bike sharing\" v Edinburghu. Data jsou k dispozici v tabulce edinburgh_bikes. Zjistíme následující informace:\n",
    "\n",
    "\n",
    "# Počet záznamů (výpůjček):\n",
    "# To nám dá představu o celkovém rozsahu dat.\n",
    "pocet = merged_data.index.nunique()\n",
    "print(f\"pocet: {pocet}\")\n",
    "\n",
    "# Průměrná doba výpůjčky (duration):Jak dlouho obvykle trvá jedna výpůjčka?\n",
    "prumerna_vypujcka = edinburgh_bikes['duration'].mean()\n",
    "print(f\"prumerna_vypujcka: {prumerna_vypujcka}\")\n",
    "\n",
    "# Minimální a maximální doba trvání výpůjčky: Zjistíte nejkratší a nejdelší výpůjčky, což může být užitečné pro zjištění extrémních hodnot.\n",
    "minimalni_doba = edinburgh_bikes['duration'].min()\n",
    "print(f\"minimalni_doba: {minimalni_doba}\")\n",
    "\n",
    "maximalni_doba = edinburgh_bikes['duration'].max()\n",
    "print(f\"maximalni_doba: {maximalni_doba}\")\n",
    "\n",
    "# Průměrná poloha začáteční stanice: Vypočítáte průměrnou zeměpisnou šířku a délku začátečních stanic. To může pomoci určit, kde se nejčastěji začínají výpůjčky.\n",
    "average_latitude_start_station = edinburgh_bikes['start_station_latitude'].mean()\n",
    "average_longitude_start_station = edinburgh_bikes['start_station_longitude'].mean()\n",
    "\n",
    "print(f\"average_latitude_start_station: {average_latitude_start_station}\")\n",
    "print(f\"average_longitude_start_station: {average_longitude_start_station}\")\n",
    "\n",
    "# Průměrná poloha koncové stanice: Stejně jako v předchozím bodě, ale pro koncové stanice.\n",
    "average_latitude_end_station = edinburgh_bikes['end_station_latitude'].mean()\n",
    "average_longitude_end_station = edinburgh_bikes['end_station_longitude'].mean()\n",
    "\n",
    "print(f\"average_latitude_end_station: {average_latitude_end_station}\")\n",
    "print(f\"average_longitude_end_station: {average_longitude_end_station}\")\n",
    "\n",
    "# Nejčastější začáteční stanice: Zjistíte, která stanice se nejčastěji používá jako začáteční bod výpůjček.\n",
    "nejcastejsi_zacatecni_stanice = edinburgh_bikes['start_station_name'].value_counts().idxmax()\n",
    "print(f\"nejcastejsi_zacatecni_stanice: {nejcastejsi_zacatecni_stanice}\")\n",
    "\n",
    "# Nejčastější koncová stanice: Analogicky k předchozímu bodu, ale pro koncové stanice.\n",
    "nejcastejsi_koncova_stanice = edinburgh_bikes['end_station_name'].value_counts().idxmax()\n",
    "print(f\"nejcastejsi_koncova_stanice: {nejcastejsi_koncova_stanice}\")\n",
    "\n",
    "# Směrodatná odchylka (standard deviation): Ukazuje, jak hodnoty odcházejí od průměru, což může indikovat variabilitu trvání výpůjček.\n",
    "std_duration = edinburgh_bikes['duration'].std()\n",
    "print(f\"Směrodatná odchylka doby trvání: {std_duration} sekund\")\n",
    "# V tomto kódu používáme Pandas k výpočtu směrodatné odchylky doby trvání výpůjček založené na sloupci 'duration' ve vašem DataFrame ('edinburgh_bikes'). Metoda .std() vrátí směrodatnou odchylku, což indikuje,\n",
    "# jak hodnoty odcházejí od průměru, a tím i variabilitu doby trvání výpůjček. Směrodatná odchylka vyjadřuje, jak moc jsou hodnoty rozptýleny okolo průměru.\n",
    "\n",
    "\n",
    "## Korelace mezi začátečními a koncovými stanicemi: Můžete analyzovat, zda existuje nějaká korelace mezi určitými začátečními a koncovými stanicemi.\n",
    "# Vytvoření křížové tabulky pro korelaci začátečních a koncových stanic\n",
    "cross_table = pd.crosstab(edinburgh_bikes['start_station_name'], edinburgh_bikes['end_station_name'])\n",
    "# Získání nejčastější kombinace začáteční a koncové stanice\n",
    "most_frequent_combination = cross_table.stack().idxmax()\n",
    "print(f\"Nejčastější kombinace začáteční a koncové stanice: {most_frequent_combination}\")\n",
    "# V tomto kódu vytváříme křížovou tabulku pro korelaci mezi začátečními a koncovými stanicemi v datech. Křížová tabulka obsahuje počty výskytů různých kombinací začátečních a koncových stanic.\n",
    "# Následně můžeme zjistit nejčastější kombinaci začáteční a koncové stanice pomocí metody .idxmax(). Tím získáte informaci o tom, jaké kombinace stanic jsou nejčastější v datech.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# **# Identifikujte aktivní a neaktivní stanice**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "aktivni_stanice_pocet: 875536\n",
      "neaktivni_stanice_pocet: 982\n"
     ]
    }
   ],
   "source": [
    "# identifikujte aktivní a neaktivní stanice\n",
    "\n",
    "# Concatenating 'start_station_name' and 'end_station_name' into a single Series\n",
    "combined_stations = pd.concat([edinburgh_bikes['start_station_name'], edinburgh_bikes['end_station_name']])\n",
    "\n",
    "# Vytvoření Series s počtem výpůjček pro každou stanici\n",
    "# Computing the value counts for each station\n",
    "station_counts = combined_stations.value_counts()\n",
    "\n",
    "# Definice prahu pro aktivní stanice (například 100 výpůjček)\n",
    "prah_pro_aktivni_stanici = 100\n",
    "\n",
    "# Identifikace aktivních a neaktivních stanic\n",
    "aktivni_stanice = station_counts[station_counts >= prah_pro_aktivni_stanici]\n",
    "aktivni_stanice_pocet = aktivni_stanice.sum()\n",
    "\n",
    "neaktivni_stanice = station_counts[station_counts < prah_pro_aktivni_stanici]\n",
    "neaktivni_stanice_pocet = neaktivni_stanice.sum()\n",
    "\n",
    "# print(\"Aktivní stanice:\")\n",
    "# print(aktivni_stanice)\n",
    "print(f\"aktivni_stanice_pocet: {aktivni_stanice_pocet}\")\n",
    "\n",
    "# print(\"Neaktivní stanice:\")\n",
    "# print(neaktivni_stanice)\n",
    "print(f\"neaktivni_stanice_pocet: {neaktivni_stanice_pocet}\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# **Identifikujte nejfrekventovanější stanice**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#  identifikujte nejfrekventovanější stanice\n",
    "# Kombinace začátečních a koncových stanic do jednoho sloupce\n",
    "all_stations = pd.concat([edinburgh_bikes['start_station_name'], edinburgh_bikes['end_station_name']])\n",
    "all_stations\n",
    "# Počet výskytů každé stanice\n",
    "station_counts = all_stations.value_counts()\n",
    "\n",
    "# Počet nejfrekventovanějších stanic, které chcete získat\n",
    "pocet_nejfrekventovanejsich_stanic = 10  # Můžete změnit podle požadavků\n",
    "\n",
    "# Získání nejfrekventovanějších stanic\n",
    "nejfrekventovanejsi_stanice = station_counts.head(pocet_nejfrekventovanejsich_stanic)\n",
    "\n",
    "print(\"Nejfrekventovanější stanice:\")\n",
    "print(nejfrekventovanejsi_stanice)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# **# Identifikujte stanice, na kterých se kola hromadí a stanice, kde potenciálně chybí!**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a Series with the counts of bikes borrowed and returned at each station\n",
    "borrow_counts = edinburgh_bikes['start_station_name'].value_counts()\n",
    "return_counts = edinburgh_bikes['end_station_name'].value_counts()\n",
    "\n",
    "# Calculate the difference between borrows and returns\n",
    "station_balance = borrow_counts.sub(return_counts, fill_value=0)\n",
    "\n",
    "# Stations with positive balance are where bikes are piling up\n",
    "# Stations with negative balance are where bikes might be missing\n",
    "bikes_piling_up = station_balance[station_balance > 0]\n",
    "bikes_missing = station_balance[station_balance < 0]\n",
    "\n",
    "# Print out the results\n",
    "print(\"Stanice, kde se kola hromadí:\")\n",
    "print(bikes_piling_up)\n",
    "\n",
    "print(\"\\nStanice, kde potenciálně chybí kola:\")\n",
    "print(bikes_missing)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "# Sort stations by the absolute value of their balance to get the ones with the largest discrepancies\n",
    "top_20_stations = station_balance.abs().sort_values(ascending=False).head(20)\n",
    "\n",
    "# Filter 'bikes_piling_up' and 'bikes_missing' to include only the top 20 stations\n",
    "bikes_piling_up_top_20 = bikes_piling_up[bikes_piling_up.index.isin(top_20_stations.index)]\n",
    "bikes_missing_top_20 = bikes_missing[bikes_missing.index.isin(top_20_stations.index)]\n",
    "\n",
    "# Visualization\n",
    "fig, ax = plt.subplots(2, 1, figsize=(10, 12))\n",
    "\n",
    "# Top 20 Stations with bikes piling up\n",
    "bikes_piling_up_top_20.sort_values().plot(kind='barh', ax=ax[0], color='green')\n",
    "ax[0].set_title('Top 20 Stanic, Kde Se Kola Hromadí')\n",
    "ax[0].set_xlabel('Přebytek Kol')\n",
    "ax[0].set_ylabel('Stanice')\n",
    "\n",
    "# Top 20 Stations where bikes might be missing\n",
    "bikes_missing_top_20.sort_values().plot(kind='barh', ax=ax[1], color='red')\n",
    "ax[1].set_title('Top 20 Stanic, Kde Potenciálně Chybí Kola')\n",
    "ax[1].set_xlabel('Nedostatek Kol')\n",
    "ax[1].set_ylabel('Stanice')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# **Spočítejte vzdálenosti mezi jednotlivými stanicemi**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# spočítejte vzdálenosti mezi jednotlivými stanicemi\n",
    "from geopy.distance import geodesic\n",
    "import pandas as pd\n",
    "\n",
    "# Předpokládejme, že máte DataFrame s daty pojmenovaným 'edinburgh_bikes'\n",
    "# DataFrame by měl obsahovat sloupce 'start_station_latitude', 'start_station_longitude', 'end_station_latitude' a 'end_station_longitude'\n",
    "\n",
    "# Vytvoření funkce pro výpočet vzdálenosti mezi stanicemi\n",
    "def vypocet_vzdalenosti(row):\n",
    "    start_coords = (row['start_station_latitude'], row['start_station_longitude'])\n",
    "    end_coords = (row['end_station_latitude'], row['end_station_longitude'])\n",
    "    return geodesic(start_coords, end_coords).kilometers\n",
    "\n",
    "# Aplikace funkce na DataFrame pro výpočet vzdáleností\n",
    "edinburgh_bikes['vzdalenost_km'] = edinburgh_bikes.apply(vypocet_vzdalenosti, axis=1)\n",
    "\n",
    "# Výpis výsledného DataFrame s vzdálenostmi\n",
    "print(edinburgh_bikes[['start_station_name', 'end_station_name', 'vzdalenost_km']])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# **Jak dlouho trvá jedna výpůjčka? Najděte odlehlé hodnoty, zobrazte histogram**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# jak dlouho trvá jedna výpůjčka? Najděte odlehlé hodnoty, zobrazte histogram\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Předpokládejme, že máte DataFrame s daty pojmenovaným 'edinburgh_bikes'\n",
    "# DataFrame by měl obsahovat sloupec 'duration' reprezentující dobu trvání výpůjček\n",
    "\n",
    "# Vytvoření histogramu doby trvání\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.hist(edinburgh_bikes['duration'], bins=50, edgecolor='k')\n",
    "plt.yscale('log')\n",
    "plt.xlabel('Doba trvání (minuty)')\n",
    "plt.ylabel('Počet výpůjček')\n",
    "plt.title('Histogram doby trvání výpůjček')\n",
    "plt.grid(True)\n",
    "plt.show()\n",
    "\n",
    "# Identifikace odlehlých hodnot (outliers)\n",
    "Q1 = edinburgh_bikes['duration'].quantile(0.25)\n",
    "Q3 = edinburgh_bikes['duration'].quantile(0.75)\n",
    "IQR = Q3 - Q1\n",
    "lower_bound = Q1 - 1.5 * IQR\n",
    "upper_bound = Q3 + 1.5 * IQR\n",
    "\n",
    "odlehle_hodnoty = edinburgh_bikes[(edinburgh_bikes['duration'] < lower_bound) | (edinburgh_bikes['duration'] > upper_bound)]\n",
    "print(\"Odlehlé hodnoty (outliers):\")\n",
    "print(odlehle_hodnoty)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# zobrazte vývoj poptávky po půjčování kol v čase\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Předpokládejme, že máte DataFrame s daty pojmenovaným 'edinburgh_bikes'\n",
    "# DataFrame by měl obsahovat sloupec 'started_at' s časem začátku výpůjčky\n",
    "\n",
    "# Převedení sloupce 'started_at' na typ datetime\n",
    "edinburgh_bikes['started_at'] = pd.to_datetime(edinburgh_bikes['started_at'])\n",
    "\n",
    "# Seskupení dat podle času a spočítání počtu výpůjček v daném čase\n",
    "poptavka_v_case = edinburgh_bikes.groupby(edinburgh_bikes['started_at'].dt.date)['started_at'].count()\n",
    "\n",
    "# Vytvoření časového řadového grafu\n",
    "plt.figure(figsize=(12, 6))\n",
    "plt.plot(poptavka_v_case.index, poptavka_v_case.values, marker='o', linestyle='-')\n",
    "plt.xlabel('Datum')\n",
    "plt.ylabel('Počet výpůjček')\n",
    "plt.title('Vývoj poptávky po půjčování kol v čase')\n",
    "plt.grid(True)\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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VpUoVSVLlypV19OhRHTp0SAcPHtTly5etQLZ//35JV7rYv5GzZ88qMTFRZ86c0fjx4zV+/Pjrtrv6/6tr1666dOmStm7delufCcC9iUAGIENzcXFRrVq1NGrUKO3fv/9fN3KaNm2qadOmaebMmXrllVecxiUnJ6tevXrq2bPndV/72GOP/Ws9mTNnVt26da3nVapUUbly5fT222/r008/td7H4XDoxx9/vG6vi1cHxRv1zGiuc73T1ZKSklSvXj2dOnVKvXr1UtGiRZU5c2YdOXJEL7/88k2PfHl7e2v16tVauXKlFi5cqMWLF2v27NmqXbu2li5d+p96jNy5c6ckqXDhwpKuzJOcOXNe9zokSdeE5Bu9963MqxYtWmjdunXq0aOHypQpIx8fHyUnJ6tBgwbXnR//Zf6nt4ceekhPPfWUFcjmzp2r+Pj4NF9DeT1XL5O0/O+4urrqhRde0IQJEzRmzBitXbtWR48eTZe6blfq68g8PDyUNWtWFS1aVNKVWzJkypRJa9as0cGDB53ap3yujz/++IZHsHx8fKxOYF588cUbhrdSpUo5PX/22Wf11Vdf6cMPP9T06dP/844NAPcGAhmADO/y5cuS/reH/2Y+/vhjubm56bXXXlOWLFn0wgsvWOMeffRRnT9/3ilQ/VelSpXSiy++qM8//1zdu3dX/vz59eijj8oYo0KFCt1SyLsVNzo6smPHDv3++++aNm2aU0cMqXvSuxkXFxfVqVNHderU0fDhw/XBBx/onXfe0cqVK297Pp0/f17ffvut8uXLp2LFikm6Mu+XLVumKlWqOJ0ml95Onz6t5cuXa8CAAerXr581POWoyO0oUKCAdUQ09ZGeffv2pWk6V9dgjNGBAweu2ahv06aNnn32Wf3yyy+aOXOmypYtmy5HW2bMmCFJCgkJkZT2/502bdpo2LBh+uGHH/Tjjz8qR44c1rRuJEeOHMqUKdN159XevXvl4uJy2/dFK1eunBW6PD09FRwcbK0nbm5ueuKJJ7R27VodPHhQOXPmtNbFlCOdvr6+N/0fT+lRMykp6ZbXhcaNG6t+/fp6+eWXlSVLFo0dO/a2PhuAewu7VgBkaImJiVq6dKk8PDysjfubcTgcGj9+vJo1a6a2bdvq+++/t8a1aNFC69ev15IlS6553ZkzZ6zgl1Y9e/ZUYmKidSPkJk2ayNXVVQMGDLjmKIsx5pru129F5syZrTpTSzm6k/p9jDEaNWrUv07z1KlT1wxLOWIQHx+f5hqlK73LvfTSSzp16pTeeecdawO5RYsWSkpK0qBBg655zeXLl6/5XLfrevND0k17xPs3DRs2lCTrCOjtTnP69OlO12/NnTtXx44ds6af+v2yZ8+ujz76SD/99FO6HIWaNWuWJk6cqODgYNWpU0dS2v93SpUqpVKlSmnixImaN2+eWrVq9a83Z3d1dVX9+vX13XffOZ2aGRMTo1mzZqlq1ary9fW9rc/k5uamihUrau3atVq7du01PRlWrlxZq1ev1oYNG6xTGSUpKChIjz76qD755JPr7uRJue2Aq6urmjZtqnnz5llHF6/X7mopPbiOGzdOvXr1uq3PBuDewhEyABnKjz/+qL1790q6cn3GrFmztH//fvXu3fuWN9xcXFz0xRdfqHHjxmrRooUWLVqk2rVrq0ePHvr+++/11FNP6eWXX1ZQUJDi4uK0Y8cOzZ07V4cOHXK6oe6tCgwM1JNPPqmJEyfq3Xff1aOPPqr3339fffr00aFDh9S4cWNlyZJFBw8e1LfffqvOnTure/fuaXqPRx99VP7+/ho3bpyyZMmizJkzq2LFiipatKgeffRRde/eXUeOHJGvr6/mzZt3zfVA1zNw4ECtXr1ajRo1UoECBXT8+HGNGTNGefPmdbpf040cOXJEX3zxhaQrR8V2796tOXPmKDo6Wm+99ZbTKaM1atTQK6+8oiFDhmjbtm2qX7++3N3dtX//fs2ZM0ejRo1Ss2bN0jRPrsfX11fVq1fX0KFDlZiYqIcfflhLly61Tlu7HWXKlNHzzz+vMWPG6OzZs6pcubKWL1+uAwcOpGk6WbNmVdWqVdWuXTvFxMRo5MiRKly4sDp16uTUzt3dXa1atdJnn30mV1dXPf/882l6n7lz58rHx0cJCQk6cuSIlixZorVr16p06dKaM2eO1e52/nfatGlj/e/ealB8//33rfvdvfbaa3Jzc9Pnn3+u+Ph4p/vt3Y6qVataHY2kDl3SlUA2ZMgQq10KFxcXTZw4UQ0bNlTx4sXVrl07Pfzwwzpy5IhWrlwpX19f/fDDD5KkDz/8UCtXrlTFihXVqVMnBQYG6tSpU9qyZYuWLVt23Z0akhQWFqbY2Fi988478vPz+0/39gNwD7jr/ToCgA2u1+29l5eXKVOmjBk7dqxT99TG3Lzb+xQXLlwwNWrUMD4+PmbDhg3GGGPOnTtn+vTpYwoXLmw8PDxM9uzZTeXKlc0nn3xiEhISblpjjRo1TPHixa87btWqVdfUNG/ePFO1alWTOXNmkzlzZlO0aFETGhpq9u3b96/TbNu2rSlQoIDTsO+++84EBgYaNzc3p+7Gd+/eberWrWt8fHxM9uzZTadOncz27duv6ZL86m7vly9fbp599lmTJ08e4+HhYfLkyWOef/75a24LcD0pXdNLMg6Hw/j6+prixYubTp06mY0bN97wdePHjzdBQUHG29vbZMmSxZQsWdL07NnTHD161Gna1+tSX5IJDQ11Gna9rtL//vtv89xzzxl/f3/j5+dnmjdvbo4ePXpL/zPG/O9/8eDBg9awixcvmjfeeMNky5bNZM6c2Tz99NPm8OHDaer2/ssvvzR9+vQxOXPmNN7e3qZRo0ZOXcuntmnTJiPJ1K9f/6bTTi3l86Ref/LmzWueeuopM3nyZHPp0qVrXnOr/zspjh07ZlxdXc1jjz12y3UZc6WL/JCQEOPj42MyZcpkatWq5XRbA2PS3u29Mf+7HYKbm5uJi4tzGvfPP/8Yh8NhJF33f3Lr1q2mSZMmJlu2bMbT09MUKFDAtGjRwixfvtypXUxMjAkNDTX58uUz7u7uJleuXKZOnTpm/PjxVpvU3d6n1rNnTyPJfPbZZ7f8mQDcexzG2HBVMQAAsM327dtVpkwZTZ8+3bqh873g5MmTyp07t/r166d3333X7nIA4K7gGjIAADKYCRMmyMfHR02aNLG7FCdTp05VUlLSPRUSAeBO4xoyAAAyiB9++EG7d+/W+PHjFRYWZnXmYrcVK1Zo9+7dGjx4sBo3bqyCBQvaXRIA3DWcsggAQAZRsGBBxcTEKCQkRDNmzLjpTZfvppo1a2rdunWqUqWKvvjiCz388MN2lwQAdw2BDAAAAABswjVkAAAAAGATAhkAAAAA2IROPdJJcnKyjh49qixZssjhcNhdDgAAAACbGGN07tw55cmTRy4uNz8GRiBLJ0ePHlW+fPnsLgMAAADAPeLw4cPKmzfvTdsQyNJJSk9Vhw8flq+vr83VAAAAALBLbGys8uXLd0u92RLI0knKaYq+vr4EMgAAAAC3dCkTnXoAAAAAgE0IZAAAAABgEwIZAAAAANiEQAYAAAAANiGQAQAAAIBNCGQAAAAAYBMCGQAAAADYhEAGAAAAADYhkAEAAACATQhkAAAAAGATAhkAAAAA2IRABgAAAAA2IZABAAAAgE0IZAAAAABgEwIZAAAAANiEQAYAAAAANiGQAQAAAIBNCGQAAAAAYBMCGQAAAADYxM3uAgAAAPBgKdh7od0l3FGHPmxkdwl4gNh6hKxgwYJyOBzXPEJDQyVJly5dUmhoqLJlyyYfHx81bdpUMTExTtOIiopSo0aNlClTJuXMmVM9evTQ5cuXndqsWrVK5cqVk6enpwoXLqypU6deU0tERIQKFiwoLy8vVaxYUZs2bbpjnxsAAAAAJJsD2S+//KJjx45Zj8jISElS8+bNJUnh4eH64YcfNGfOHP300086evSomjRpYr0+KSlJjRo1UkJCgtatW6dp06Zp6tSp6tevn9Xm4MGDatSokWrVqqVt27apa9eu6tixo5YsWWK1mT17trp166b+/ftry5YtKl26tEJCQnT8+PG7NCcAAAAAZEQOY4yxu4gUXbt21YIFC7R//37FxsYqR44cmjVrlpo1ayZJ2rt3r4oVK6b169erUqVK+vHHH/XUU0/p6NGjCggIkCSNGzdOvXr10okTJ+Th4aFevXpp4cKF2rlzp/U+rVq10pkzZ7R48WJJUsWKFfXEE0/os88+kyQlJycrX758ev3119W7d+9bqj02NlZ+fn46e/asfH1903O2AAAA3Fc4ZREZXVqywT3TqUdCQoK++OILtW/fXg6HQ5s3b1ZiYqLq1q1rtSlatKjy58+v9evXS5LWr1+vkiVLWmFMkkJCQhQbG6tdu3ZZbVJPI6VNyjQSEhK0efNmpzYuLi6qW7eu1eZ64uPjFRsb6/QAAAAAgLS4ZwLZ/PnzdebMGb388suSpOjoaHl4eMjf39+pXUBAgKKjo602qcNYyviUcTdrExsbq4sXL+rkyZNKSkq6bpuUaVzPkCFD5OfnZz3y5cuX5s8MAAAAIGO7ZwLZpEmT1LBhQ+XJk8fuUm5Jnz59dPbsWetx+PBhu0sCAAAAcJ+5J7q9/+uvv7Rs2TJ988031rBcuXIpISFBZ86ccTpKFhMTo1y5clltru4NMaUXxtRtru6ZMSYmRr6+vvL29parq6tcXV2v2yZlGtfj6ekpT0/PtH9YAAAAAPh/98QRsilTpihnzpxq1Oh/F0gGBQXJ3d1dy5cvt4bt27dPUVFRCg4OliQFBwdrx44dTr0hRkZGytfXV4GBgVab1NNIaZMyDQ8PDwUFBTm1SU5O1vLly602AAAAAHAn2H6ELDk5WVOmTFHbtm3l5va/cvz8/NShQwd169ZNWbNmla+vr15//XUFBwerUqVKkqT69esrMDBQL730koYOHaro6Gj17dtXoaGh1tGrV199VZ999pl69uyp9u3ba8WKFfr666+1cOH/ev/p1q2b2rZtq/Lly6tChQoaOXKk4uLi1K5du7s7MwAAAABkKLYHsmXLlikqKkrt27e/ZtyIESPk4uKipk2bKj4+XiEhIRozZow13tXVVQsWLFCXLl0UHByszJkzq23btho4cKDVplChQlq4cKHCw8M1atQo5c2bVxMnTlRISIjVpmXLljpx4oT69eun6OholSlTRosXL76mow8AAAAASE/31H3I7mfchwwAAOAK7kOGjO6+vA8ZAAAAAGQ0BDIAAAAAsAmBDAAAAABsQiADAAAAAJsQyAAAAADAJgQyAAAAALAJgQwAAAAAbEIgAwAAAACbEMgAAAAAwCYEMgAAAACwCYEMAAAAAGxCIAMAAAAAm7jZXQAAAACAe0PB3gvtLuGOOfRhI7tLuC6OkAEAAACATQhkAAAAAGATAhkAAAAA2IRABgAAAAA2IZABAAAAgE0IZAAAAABgEwIZAAAAANiEQAYAAAAANiGQAQAAAIBNCGQAAAAAYBMCGQAAAADYhEAGAAAAADYhkAEAAACATQhkAAAAAGATAhkAAAAA2IRABgAAAAA2IZABAAAAgE0IZAAAAABgEwIZAAAAANiEQAYAAAAANiGQAQAAAIBNCGQAAAAAYBM3uwsAAAC4kYK9F9pdwh1z6MNGdpcA4B7AETIAAAAAsAmBDAAAAABsQiADAAAAAJsQyAAAAADAJgQyAAAAALAJgQwAAAAAbEIgAwAAAACbEMgAAAAAwCYEMgAAAACwCYEMAAAAAGxCIAMAAAAAmxDIAAAAAMAmBDIAAAAAsAmBDAAAAABs4mZ3AQAA3GkFey+0u4Q75tCHjewuAQDwH9h+hOzIkSN68cUXlS1bNnl7e6tkyZL69ddfrfHGGPXr10+5c+eWt7e36tatq/379ztN49SpU2rdurV8fX3l7++vDh066Pz5805tfvvtN1WrVk1eXl7Kly+fhg4dek0tc+bMUdGiReXl5aWSJUtq0aJFd+ZDAwAAAIBsDmSnT59WlSpV5O7urh9//FG7d+/WsGHD9NBDD1lthg4dqk8//VTjxo3Txo0blTlzZoWEhOjSpUtWm9atW2vXrl2KjIzUggULtHr1anXu3NkaHxsbq/r166tAgQLavHmzPv74Y7333nsaP3681WbdunV6/vnn1aFDB23dulWNGzdW48aNtXPnzrszMwAAAABkOLaesvjRRx8pX758mjJlijWsUKFC1t/GGI0cOVJ9+/bVs88+K0maPn26AgICNH/+fLVq1Up79uzR4sWL9csvv6h8+fKSpNGjR+vJJ5/UJ598ojx58mjmzJlKSEjQ5MmT5eHhoeLFi2vbtm0aPny4FdxGjRqlBg0aqEePHpKkQYMGKTIyUp999pnGjRt3t2YJAAAAgAzE1iNk33//vcqXL6/mzZsrZ86cKlu2rCZMmGCNP3jwoKKjo1W3bl1rmJ+fnypWrKj169dLktavXy9/f38rjElS3bp15eLioo0bN1ptqlevLg8PD6tNSEiI9u3bp9OnT1ttUr9PSpuU97lafHy8YmNjnR4AAAAAkBa2BrI///xTY8eOVZEiRbRkyRJ16dJFb7zxhqZNmyZJio6OliQFBAQ4vS4gIMAaFx0drZw5czqNd3NzU9asWZ3aXG8aqd/jRm1Sxl9tyJAh8vPzsx758uVL8+cHAAAAkLHZGsiSk5NVrlw5ffDBBypbtqw6d+6sTp063RenCPbp00dnz561HocPH7a7JAAAAAD3GVsDWe7cuRUYGOg0rFixYoqKipIk5cqVS5IUExPj1CYmJsYalytXLh0/ftxp/OXLl3Xq1CmnNtebRur3uFGblPFX8/T0lK+vr9MDAAAAANLC1k49qlSpon379jkN+/3331WgQAFJVzr4yJUrl5YvX64yZcpIutJj4saNG9WlSxdJUnBwsM6cOaPNmzcrKChIkrRixQolJyerYsWKVpt33nlHiYmJcnd3lyRFRkbq8ccft3p0DA4O1vLly9W1a1erlsjISAUHB9+xzw/g/vIg38tK4n5WAADYwdYjZOHh4dqwYYM++OADHThwQLNmzdL48eMVGhoqSXI4HOratavef/99ff/999qxY4fatGmjPHnyqHHjxpKuHFFr0KCBOnXqpE2bNmnt2rUKCwtTq1atlCdPHknSCy+8IA8PD3Xo0EG7du3S7NmzNWrUKHXr1s2q5c0339TixYs1bNgw7d27V++9955+/fVXhYWF3fX5AgAAACBjsPUI2RNPPKFvv/1Wffr00cCBA1WoUCGNHDlSrVu3ttr07NlTcXFx6ty5s86cOaOqVatq8eLF8vLystrMnDlTYWFhqlOnjlxcXNS0aVN9+umn1ng/Pz8tXbpUoaGhCgoKUvbs2dWvXz+ne5VVrlxZs2bNUt++ffX222+rSJEimj9/vkqUKHF3ZgYAAACADMfWQCZJTz31lJ566qkbjnc4HBo4cKAGDhx4wzZZs2bVrFmzbvo+pUqV0s8//3zTNs2bN1fz5s1vXjAAAAAApBNbT1kEAAAAgIyMQAYAAAAANrH9lEUgI3qQe+ujpz4AAIBbxxEyAAAAALAJgQwAAAAAbEIgAwAAAACbcA3ZfYzrkAAAAID7G0fIAAAAAMAmBDIAAAAAsAmBDAAAAABsQiADAAAAAJsQyAAAAADAJgQyAAAAALAJgQwAAAAAbEIgAwAAAACbEMgAAAAAwCYEMgAAAACwCYEMAAAAAGxCIAMAAAAAmxDIAAAAAMAmBDIAAAAAsAmBDAAAAABsQiADAAAAAJsQyAAAAADAJgQyAAAAALAJgQwAAAAAbEIgAwAAAACbEMgAAAAAwCYEMgAAAACwCYEMAAAAAGxCIAMAAAAAmxDIAAAAAMAmBDIAAAAAsAmBDAAAAABsQiADAAAAAJsQyAAAAADAJgQyAAAAALAJgQwAAAAAbEIgAwAAAACbEMgAAAAAwCYEMgAAAACwCYEMAAAAAGxCIAMAAAAAmxDIAAAAAMAmBDIAAAAAsAmBDAAAAABsQiADAAAAAJsQyAAAAADAJgQyAAAAALAJgQwAAAAAbEIgAwAAAACb2BrI3nvvPTkcDqdH0aJFrfGXLl1SaGiosmXLJh8fHzVt2lQxMTFO04iKilKjRo2UKVMm5cyZUz169NDly5ed2qxatUrlypWTp6enChcurKlTp15TS0REhAoWLCgvLy9VrFhRmzZtuiOfGQAAAABS2H6ErHjx4jp27Jj1WLNmjTUuPDxcP/zwg+bMmaOffvpJR48eVZMmTazxSUlJatSokRISErRu3TpNmzZNU6dOVb9+/aw2Bw8eVKNGjVSrVi1t27ZNXbt2VceOHbVkyRKrzezZs9WtWzf1799fW7ZsUenSpRUSEqLjx4/fnZkAAAAAIEOyPZC5ubkpV65c1iN79uySpLNnz2rSpEkaPny4ateuraCgIE2ZMkXr1q3Thg0bJElLly7V7t279cUXX6hMmTJq2LChBg0apIiICCUkJEiSxo0bp0KFCmnYsGEqVqyYwsLC1KxZM40YMcKqYfjw4erUqZPatWunwMBAjRs3TpkyZdLkyZPv/gwBAAAAkGHYHsj279+vPHny6JFHHlHr1q0VFRUlSdq8ebMSExNVt25dq23RokWVP39+rV+/XpK0fv16lSxZUgEBAVabkJAQxcbGateuXVab1NNIaZMyjYSEBG3evNmpjYuLi+rWrWu1uZ74+HjFxsY6PQAAAAAgLWwNZBUrVtTUqVO1ePFijR07VgcPHlS1atV07tw5RUdHy8PDQ/7+/k6vCQgIUHR0tCQpOjraKYyljE8Zd7M2sbGxunjxok6ePKmkpKTrtkmZxvUMGTJEfn5+1iNfvny3NQ8AAAAAZFxudr55w4YNrb9LlSqlihUrqkCBAvr666/l7e1tY2X/rk+fPurWrZv1PDY2llAGAAAAIE1sP2UxNX9/fz322GM6cOCAcuXKpYSEBJ05c8apTUxMjHLlyiVJypUr1zW9LqY8/7c2vr6+8vb2Vvbs2eXq6nrdNinTuB5PT0/5+vo6PQAAAAAgLe6pQHb+/Hn98ccfyp07t4KCguTu7q7ly5db4/ft26eoqCgFBwdLkoKDg7Vjxw6n3hAjIyPl6+urwMBAq03qaaS0SZmGh4eHgoKCnNokJydr+fLlVhsAAAAAuBNsDWTdu3fXTz/9pEOHDmndunV67rnn5Orqqueff15+fn7q0KGDunXrppUrV2rz5s1q166dgoODValSJUlS/fr1FRgYqJdeeknbt2/XkiVL1LdvX4WGhsrT01OS9Oqrr+rPP/9Uz549tXfvXo0ZM0Zff/21wsPDrTq6deumCRMmaNq0adqzZ4+6dOmiuLg4tWvXzpb5AgAAACBjsPUasr///lvPP/+8/vnnH+XIkUNVq1bVhg0blCNHDknSiBEj5OLioqZNmyo+Pl4hISEaM2aM9XpXV1ctWLBAXbp0UXBwsDJnzqy2bdtq4MCBVptChQpp4cKFCg8P16hRo5Q3b15NnDhRISEhVpuWLVvqxIkT6tevn6Kjo1WmTBktXrz4mo4+AAAAACA92RrIvvrqq5uO9/LyUkREhCIiIm7YpkCBAlq0aNFNp1OzZk1t3br1pm3CwsIUFhZ20zYAAAAAkJ7uqWvIAAAAACAjIZABAAAAgE0IZAAAAABgEwIZAAAAANiEQAYAAAAANiGQAQAAAIBNCGQAAAAAYBMCGQAAAADYhEAGAAAAADYhkAEAAACATdIcyLZs2aIdO3ZYz7/77js1btxYb7/9thISEtK1OAAAAAB4kKU5kL3yyiv6/fffJUl//vmnWrVqpUyZMmnOnDnq2bNnuhcIAAAAAA+qNAey33//XWXKlJEkzZkzR9WrV9esWbM0depUzZs3L73rAwAAAIAHVpoDmTFGycnJkqRly5bpySeflCTly5dPJ0+eTN/qAAAAAOABluZAVr58eb3//vuaMWOGfvrpJzVq1EiSdPDgQQUEBKR7gQAAAADwoEpzIBs5cqS2bNmisLAwvfPOOypcuLAkae7cuapcuXK6FwgAAAAADyq3tL6gVKlSTr0spvj444/l6uqaLkUBAAAAQEaQ5kB2I15eXuk1KQAAAADIEG4pkD300ENyOBy3NMFTp079p4IAAAAAIKO4pUA2cuTIO1wGAAAAAGQ8txTI2rZte6frAAAAAIAM5z9dQ3bp0iUlJCQ4DfP19f1PBQEAAABARpHmbu/j4uIUFhamnDlzKnPmzHrooYecHgAAAACAW5PmQNazZ0+tWLFCY8eOlaenpyZOnKgBAwYoT548mj59+p2oEQAAAAAeSGk+ZfGHH37Q9OnTVbNmTbVr107VqlVT4cKFVaBAAc2cOVOtW7e+E3UCAAAAwAMnzUfITp06pUceeUTSlevFUrq5r1q1qlavXp2+1QEAAADAAyzNgeyRRx7RwYMHJUlFixbV119/LenKkTN/f/90LQ4AAAAAHmRpDmTt2rXT9u3bJUm9e/dWRESEvLy8FB4erh49eqR7gQAAAADwoErzNWTh4eHW33Xr1tXevXu1efNmFS5cWKVKlUrX4gAAAADgQZbmI2TTp09XfHy89bxAgQJq0qSJihYtSi+LAAAAAJAGt3XK4tmzZ68Zfu7cObVr1y5digIAAACAjCDNgcwYI4fDcc3wv//+W35+fulSFAAAAABkBLd8DVnZsmXlcDjkcDhUp04dubn976VJSUk6ePCgGjRocEeKBAAAAIAH0S0HssaNG0uStm3bppCQEPn4+FjjPDw8VLBgQTVt2jTdCwQAAACAB9UtB7L+/ftLkgoWLKiWLVvKy8vrjhUFAAAAABlBmru9b9u2rSQpISFBx48fV3JystP4/Pnzp09lAAAAAPCAS3Mg279/v9q3b69169Y5DU/p7CMpKSndigMAAACAB1maA9nLL78sNzc3LViwQLlz575uj4sAAAAAgH+X5kC2bds2bd68WUWLFr0T9QAAAABAhpHm+5AFBgbq5MmTd6IWAAAAAMhQ0hzIPvroI/Xs2VOrVq3SP//8o9jYWKcHAAAAAODWpPmUxbp160qS6tSp4zScTj0AAAAAIG3SHMhWrlx5J+oAAAAAgAwnzYGsRo0ad6IOAAAAAMhw0nwNmST9/PPPevHFF1W5cmUdOXJEkjRjxgytWbMmXYsDAAAAgAdZmgPZvHnzFBISIm9vb23ZskXx8fGSpLNnz+qDDz5I9wIBAAAA4EGV5kD2/vvva9y4cZowYYLc3d2t4VWqVNGWLVvStTgAAAAAeJClOZDt27dP1atXv2a4n5+fzpw5kx41AQAAAECGkOZAlitXLh04cOCa4WvWrNEjjzySLkUBAAAAQEaQ5kDWqVMnvfnmm9q4caMcDoeOHj2qmTNnqnv37urSpcudqBEAAAAAHkhp7va+d+/eSk5OVp06dXThwgVVr15dnp6e6t69u15//fU7USMAAAAAPJDSfITM4XDonXfe0alTp7Rz505t2LBBJ06c0KBBg3Tx4sXbLuTDDz+Uw+FQ165drWGXLl1SaGiosmXLJh8fHzVt2lQxMTFOr4uKilKjRo2UKVMm5cyZUz169NDly5ed2qxatUrlypWTp6enChcurKlTp17z/hERESpYsKC8vLxUsWJFbdq06bY/CwAAAADcitu6D5kkeXh4KDAwUBUqVJC7u7uGDx+uQoUK3da0fvnlF33++ecqVaqU0/Dw8HD98MMPmjNnjn766ScdPXpUTZo0scYnJSWpUaNGSkhI0Lp16zRt2jRNnTpV/fr1s9ocPHhQjRo1Uq1atbRt2zZ17dpVHTt21JIlS6w2s2fPVrdu3dS/f39t2bJFpUuXVkhIiI4fP35bnwcAAAAAbsUtB7L4+Hj16dNH5cuXV+XKlTV//nxJ0pQpU1SoUCGNGDFC4eHhaS7g/Pnzat26tSZMmKCHHnrIGn727FlNmjRJw4cPV+3atRUUFKQpU6Zo3bp12rBhgyRp6dKl2r17t7744guVKVNGDRs21KBBgxQREaGEhARJ0rhx41SoUCENGzZMxYoVU1hYmJo1a6YRI0ZY7zV8+HB16tRJ7dq1U2BgoMaNG6dMmTJp8uTJaf48AAAAAHCrbjmQ9evXT2PHjlXBggV16NAhNW/eXJ07d9aIESM0fPhwHTp0SL169UpzAaGhoWrUqJHq1q3rNHzz5s1KTEx0Gl60aFHlz59f69evlyStX79eJUuWVEBAgNUmJCREsbGx2rVrl9Xm6mmHhIRY00hISNDmzZud2ri4uKhu3bpWGwAAAAC4E265U485c+Zo+vTpeuaZZ7Rz506VKlVKly9f1vbt2+VwOG7rzb/66itt2bJFv/zyyzXjoqOj5eHhIX9/f6fhAQEBio6OttqkDmMp41PG3axNbGysLl68qNOnTyspKem6bfbu3XvD2uPj4xUfH289j42N/ZdPCwAAAADObvkI2d9//62goCBJUokSJeTp6anw8PDbDmOHDx/Wm2++qZkzZ8rLy+u2pmGnIUOGyM/Pz3rky5fP7pIAAAAA3GduOZAlJSXJw8PDeu7m5iYfH5/bfuPNmzfr+PHjKleunNzc3OTm5qaffvpJn376qdzc3BQQEKCEhASdOXPG6XUxMTHKlSuXpCs3qb6618WU5//WxtfXV97e3sqePbtcXV2v2yZlGtfTp08fnT171nocPnz4tuYDAAAAgIzrlk9ZNMbo5Zdflqenp6QrXdK/+uqrypw5s1O7b7755pamV6dOHe3YscNpWLt27VS0aFH16tVL+fLlk7u7u5YvX66mTZtKkvbt26eoqCgFBwdLkoKDgzV48GAdP35cOXPmlCRFRkbK19dXgYGBVptFixY5vU9kZKQ1DQ8PDwUFBWn58uVq3LixJCk5OVnLly9XWFjYDev39PS05gUAAAAA3I5bDmRt27Z1ev7iiy/+pzfOkiWLSpQo4TQsc+bMypYtmzW8Q4cO6tatm7JmzSpfX1+9/vrrCg4OVqVKlSRJ9evXV2BgoF566SUNHTpU0dHR6tu3r0JDQ62w9Oqrr+qzzz5Tz5491b59e61YsUJff/21Fi5caL1vt27d1LZtW5UvX14VKlTQyJEjFRcXp3bt2v2nzwgAAAAAN3PLgWzKlCl3so7rGjFihFxcXNS0aVPFx8crJCREY8aMsca7urpqwYIF6tKli4KDg5U5c2a1bdtWAwcOtNoUKlRICxcuVHh4uEaNGqW8efNq4sSJCgkJsdq0bNlSJ06cUL9+/RQdHa0yZcpo8eLF13T0AQAAAADp6ZYD2d2watUqp+deXl6KiIhQRETEDV9ToECBa05JvFrNmjW1devWm7YJCwu76SmKAAAAAJDebrlTDwAAAABA+iKQAQAAAIBNCGQAAAAAYJNbCmTlypXT6dOnJUkDBw7UhQsX7mhRAAAAAJAR3FIg27Nnj+Li4iRJAwYM0Pnz5+9oUQAAAACQEdxSL4tlypRRu3btVLVqVRlj9Mknn8jHx+e6bfv165euBQIAAADAg+qWAtnUqVPVv39/LViwQA6HQz/++KPc3K59qcPhIJABAAAAwC26pUD2+OOP66uvvpIkubi4aPny5cqZM+cdLQwAAAAAHnRpvjF0cnLynagDAAAAADKcNAcySfrjjz80cuRI7dmzR5IUGBioN998U48++mi6FgcAAAAAD7I034dsyZIlCgwM1KZNm1SqVCmVKlVKGzduVPHixRUZGXknagQAAACAB1Kaj5D17t1b4eHh+vDDD68Z3qtXL9WrVy/digMAAACAB1maj5Dt2bNHHTp0uGZ4+/bttXv37nQpCgAAAAAygjQHshw5cmjbtm3XDN+2bRs9LwIAAABAGqT5lMVOnTqpc+fO+vPPP1W5cmVJ0tq1a/XRRx+pW7du6V4gAAAAADyo0hzI3n33XWXJkkXDhg1Tnz59JEl58uTRe++9pzfeeCPdCwQAAACAB1WaA5nD4VB4eLjCw8N17tw5SVKWLFnSvTAAAAAAeNDd1n3IUhDEAAAAAOD2pblTDwAAAABA+iCQAQAAAIBNCGQAAAAAYJM0BbLExETVqVNH+/fvv1P1AAAAAECGkaZA5u7urt9+++1O1QIAAAAAGUqaT1l88cUXNWnSpDtRCwAAAABkKGnu9v7y5cuaPHmyli1bpqCgIGXOnNlp/PDhw9OtOAAAAAB4kKU5kO3cuVPlypWTJP3+++9O4xwOR/pUBQAAAAAZQJoD2cqVK+9EHQAAAACQ4dx2t/cHDhzQkiVLdPHiRUmSMSbdigIAAACAjCDNgeyff/5RnTp19Nhjj+nJJ5/UsWPHJEkdOnTQW2+9le4FAgAAAMCDKs2BLDw8XO7u7oqKilKmTJms4S1bttTixYvTtTgAAAAAeJCl+RqypUuXasmSJcqbN6/T8CJFiuivv/5Kt8IAAAAA4EGX5iNkcXFxTkfGUpw6dUqenp7pUhQAAAAAZARpDmTVqlXT9OnTrecOh0PJyckaOnSoatWqla7FAQAAAMCDLM2nLA4dOlR16tTRr7/+qoSEBPXs2VO7du3SqVOntHbt2jtRIwAAAAA8kNJ8hKxEiRL6/fffVbVqVT377LOKi4tTkyZNtHXrVj366KN3okYAAAAAeCCl+QiZJPn5+emdd95J71oAAAAAIEO5rUB2+vRpTZo0SXv27JEkBQYGql27dsqaNWu6FgcAAAAAD7I0n7K4evVqFSxYUJ9++qlOnz6t06dP69NPP1WhQoW0evXqO1EjAAAAADyQ0nyELDQ0VC1bttTYsWPl6uoqSUpKStJrr72m0NBQ7dixI92LBAAAAIAHUZqPkB04cEBvvfWWFcYkydXVVd26ddOBAwfStTgAAAAAeJClOZCVK1fOunYstT179qh06dLpUhQAAAAAZAS3dMrib7/9Zv39xhtv6M0339SBAwdUqVIlSdKGDRsUERGhDz/88M5UCQAAAAAPoFsKZGXKlJHD4ZAxxhrWs2fPa9q98MILatmyZfpVBwAAAAAPsFsKZAcPHrzTdQAAAABAhnNLgaxAgQJ3ug4AAAAAyHBu68bQR48e1Zo1a3T8+HElJyc7jXvjjTfSpTAAAAAAeNClOZBNnTpVr7zyijw8PJQtWzY5HA5rnMPhIJABAAAAwC1KcyB799131a9fP/Xp00cuLmnuNR8AAAAA8P/SnKguXLigVq1aEcYAAAAA4D9Kc6rq0KGD5syZcydqAQAAAIAMJc2nLA4ZMkRPPfWUFi9erJIlS8rd3d1p/PDhw9OtOAAAAAB4kN1WIFuyZIkef/xxSbqmUw8AAAAAwK1J8ymLw4YN0+TJk7Vnzx6tWrVKK1eutB4rVqxI07TGjh2rUqVKydfXV76+vgoODtaPP/5ojb906ZJCQ0OVLVs2+fj4qGnTpoqJiXGaRlRUlBo1aqRMmTIpZ86c6tGjhy5fvuzUZtWqVSpXrpw8PT1VuHBhTZ069ZpaIiIiVLBgQXl5ealixYratGlTmj4LAAAAAKRVmgOZp6enqlSpki5vnjdvXn344YfavHmzfv31V9WuXVvPPvusdu3aJUkKDw/XDz/8oDlz5uinn37S0aNH1aRJE+v1SUlJatSokRISErRu3TpNmzZNU6dOVb9+/aw2Bw8eVKNGjVSrVi1t27ZNXbt2VceOHbVkyRKrzezZs9WtWzf1799fW7ZsUenSpRUSEqLjx4+ny+cEAAAAgOtJcyB78803NXr06HR586efflpPPvmkihQposcee0yDBw+Wj4+PNmzYoLNnz2rSpEkaPny4ateuraCgIE2ZMkXr1q3Thg0bJElLly7V7t279cUXX6hMmTJq2LChBg0apIiICCUkJEiSxo0bp0KFCmnYsGEqVqyYwsLC1KxZM40YMcKqY/jw4erUqZPatWunwMBAjRs3TpkyZdLkyZPT5XMCAAAAwPWkOZBt2rRJ06ZN0yOPPKKnn35aTZo0cXrcrqSkJH311VeKi4tTcHCwNm/erMTERNWtW9dqU7RoUeXPn1/r16+XJK1fv14lS5ZUQECA1SYkJESxsbHWUbb169c7TSOlTco0EhIStHnzZqc2Li4uqlu3rtXmeuLj4xUbG+v0AAAAAIC0SHOnHv7+/v8peF1tx44dCg4O1qVLl+Tj46Nvv/1WgYGB2rZtmzw8POTv7+/UPiAgQNHR0ZKk6OhopzCWMj5l3M3axMbG6uLFizp9+rSSkpKu22bv3r03rHvIkCEaMGDAbX1mAAAAAJBuI5BNmTIlXQt4/PHHtW3bNp09e1Zz585V27Zt9dNPP6Xre9wJffr0Ubdu3aznsbGxypcvn40VAQAAALjfpDmQpTcPDw8VLlxYkhQUFKRffvlFo0aNUsuWLZWQkKAzZ844HSWLiYlRrly5JEm5cuW6pjfElF4YU7e5umfGmJgY+fr6ytvbW66urnJ1db1um5RpXI+np6c8PT1v70MDAAAAgG7jGrJChQrpkUceueHjv0pOTlZ8fLyCgoLk7u6u5cuXW+P27dunqKgoBQcHS5KCg4O1Y8cOp94QIyMj5evrq8DAQKtN6mmktEmZhoeHh4KCgpzaJCcna/ny5VYbAAAAALgT0nyErGvXrk7PExMTtXXrVi1evFg9evRI07T69Omjhg0bKn/+/Dp37pxmzZqlVatWacmSJfLz81OHDh3UrVs3Zc2aVb6+vnr99dcVHBysSpUqSZLq16+vwMBAvfTSSxo6dKiio6PVt29fhYaGWkevXn31VX322Wfq2bOn2rdvrxUrVujrr7/WwoULrTq6deumtm3bqnz58qpQoYJGjhypuLg4tWvXLq2zBwAAAABuWZoD2Ztvvnnd4REREfr111/TNK3jx4+rTZs2OnbsmPz8/FSqVCktWbJE9erVkySNGDFCLi4uatq0qeLj4xUSEqIxY8ZYr3d1ddWCBQvUpUsXBQcHK3PmzGrbtq0GDhxotSlUqJAWLlyo8PBwjRo1Snnz5tXEiRMVEhJitWnZsqVOnDihfv36KTo6WmXKlNHixYuv6egDAAAAANJTul1D1rBhQ/Xp0ydNnX5MmjTppuO9vLwUERGhiIiIG7YpUKCAFi1adNPp1KxZU1u3br1pm7CwMIWFhd20DQAAAACkpzRfQ3Yjc+fOVdasWdNrcgAAAADwwEvzEbKyZcvK4XBYz40xio6O1okTJ5xOJwQAAAAA3FyaA1njxo2dnru4uChHjhyqWbOmihYtml51AQAAAMADL82BrH///neiDgAAAADIcNLtGjIAAAAAQNrc8hEyFxcXp2vHrsfhcOjy5cv/uSgAAAAAyAhuOZB9++23Nxy3fv16ffrpp0pOTk6XogAAAAAgI7jlQPbss89eM2zfvn3q3bu3fvjhB7Vu3drphswAAAAAgJu7rWvIjh49qk6dOqlkyZK6fPmytm3bpmnTpqlAgQLpXR8AAAAAPLDSFMjOnj2rXr16qXDhwtq1a5eWL1+uH374QSVKlLhT9QEAAADAA+uWT1kcOnSoPvroI+XKlUtffvnldU9hBAAAAADculsOZL1795a3t7cKFy6sadOmadq0addt980336RbcQAAAADwILvlQNamTZt/7fYeAAAAAHDrbjmQTZ069Q6WAQAAAAAZz231sggAAAAA+O8IZAAAAABgEwIZAAAAANiEQAYAAAAANiGQAQAAAIBNCGQAAAAAYBMCGQAAAADYhEAGAAAAADYhkAEAAACATQhkAAAAAGATAhkAAAAA2IRABgAAAAA2IZABAAAAgE0IZAAAAABgEwIZAAAAANiEQAYAAAAANiGQAQAAAIBNCGQAAAAAYBMCGQAAAADYhEAGAAAAADYhkAEAAACATQhkAAAAAGATAhkAAAAA2IRABgAAAAA2IZABAAAAgE0IZAAAAABgEwIZAAAAANiEQAYAAAAANiGQAQAAAIBNCGQAAAAAYBMCGQAAAADYhEAGAAAAADYhkAEAAACATQhkAAAAAGATAhkAAAAA2IRABgAAAAA2IZABAAAAgE1sDWRDhgzRE088oSxZsihnzpxq3Lix9u3b59Tm0qVLCg0NVbZs2eTj46OmTZsqJibGqU1UVJQaNWqkTJkyKWfOnOrRo4cuX77s1GbVqlUqV66cPD09VbhwYU2dOvWaeiIiIlSwYEF5eXmpYsWK2rRpU7p/ZgAAAABIYWsg++mnnxQaGqoNGzYoMjJSiYmJql+/vuLi4qw24eHh+uGHHzRnzhz99NNPOnr0qJo0aWKNT0pKUqNGjZSQkKB169Zp2rRpmjp1qvr162e1OXjwoBo1aqRatWpp27Zt6tq1qzp27KglS5ZYbWbPnq1u3bqpf//+2rJli0qXLq2QkBAdP3787swMAAAAABmOm51vvnjxYqfnU6dOVc6cObV582ZVr15dZ8+e1aRJkzRr1izVrl1bkjRlyhQVK1ZMGzZsUKVKlbR06VLt3r1by5YtU0BAgMqUKaNBgwapV69eeu+99+Th4aFx48apUKFCGjZsmCSpWLFiWrNmjUaMGKGQkBBJ0vDhw9WpUye1a9dOkjRu3DgtXLhQkydPVu/eve/iXAEAAACQUdxT15CdPXtWkpQ1a1ZJ0ubNm5WYmKi6detabYoWLar8+fNr/fr1kqT169erZMmSCggIsNqEhIQoNjZWu3btstqknkZKm5RpJCQkaPPmzU5tXFxcVLduXavN1eLj4xUbG+v0AAAAAIC0uGcCWXJysrp27aoqVaqoRIkSkqTo6Gh5eHjI39/fqW1AQICio6OtNqnDWMr4lHE3axMbG6uLFy/q5MmTSkpKum6blGlcbciQIfLz87Me+fLlu70PDgAAACDDumcCWWhoqHbu3KmvvvrK7lJuSZ8+fXT27FnrcfjwYbtLAgAAAHCfsfUashRhYWFasGCBVq9erbx581rDc+XKpYSEBJ05c8bpKFlMTIxy5cpltbm6N8SUXhhTt7m6Z8aYmBj5+vrK29tbrq6ucnV1vW6blGlczdPTU56enrf3gQEAAABANh8hM8YoLCxM3377rVasWKFChQo5jQ8KCpK7u7uWL19uDdu3b5+ioqIUHBwsSQoODtaOHTucekOMjIyUr6+vAgMDrTapp5HSJmUaHh4eCgoKcmqTnJys5cuXW20AAAAAIL3ZeoQsNDRUs2bN0nfffacsWbJY12v5+fnJ29tbfn5+6tChg7p166asWbPK19dXr7/+uoKDg1WpUiVJUv369RUYGKiXXnpJQ4cOVXR0tPr27avQ0FDrCNarr76qzz77TD179lT79u21YsUKff3111q4cKFVS7du3dS2bVuVL19eFSpU0MiRIxUXF2f1uggAAAAA6c3WQDZ27FhJUs2aNZ2GT5kyRS+//LIkacSIEXJxcVHTpk0VHx+vkJAQjRkzxmrr6uqqBQsWqEuXLgoODlbmzJnVtm1bDRw40GpTqFAhLVy4UOHh4Ro1apTy5s2riRMnWl3eS1LLli114sQJ9evXT9HR0SpTpowWL158TUcfAAAAAJBebA1kxph/bePl5aWIiAhFRETcsE2BAgW0aNGim06nZs2a2rp1603bhIWFKSws7F9rAgAAAID0cM/0sggAAAAAGQ2BDAAAAABsQiADAAAAAJsQyAAAAADAJgQyAAAAALAJgQwAAAAAbEIgAwAAAACbEMgAAAAAwCYEMgAAAACwCYEMAAAAAGxCIAMAAAAAmxDIAAAAAMAmBDIAAAAAsAmBDAAAAABsQiADAAAAAJsQyAAAAADAJgQyAAAAALAJgQwAAAAAbEIgAwAAAACbEMgAAAAAwCYEMgAAAACwCYEMAAAAAGxCIAMAAAAAmxDIAAAAAMAmBDIAAAAAsAmBDAAAAABsQiADAAAAAJsQyAAAAADAJgQyAAAAALAJgQwAAAAAbEIgAwAAAACbEMgAAAAAwCYEMgAAAACwCYEMAAAAAGxCIAMAAAAAmxDIAAAAAMAmBDIAAAAAsAmBDAAAAABsQiADAAAAAJsQyAAAAADAJgQyAAAAALAJgQwAAAAAbEIgAwAAAACbEMgAAAAAwCYEMgAAAACwCYEMAAAAAGxCIAMAAAAAmxDIAAAAAMAmBDIAAAAAsAmBDAAAAABsQiADAAAAAJvYGshWr16tp59+Wnny5JHD4dD8+fOdxhtj1K9fP+XOnVve3t6qW7eu9u/f79Tm1KlTat26tXx9feXv768OHTro/PnzTm1+++03VatWTV5eXsqXL5+GDh16TS1z5sxR0aJF5eXlpZIlS2rRokXp/nkBAAAAIDVbA1lcXJxKly6tiIiI644fOnSoPv30U40bN04bN25U5syZFRISokuXLlltWrdurV27dikyMlILFizQ6tWr1blzZ2t8bGys6tevrwIFCmjz5s36+OOP9d5772n8+PFWm3Xr1un5559Xhw4dtHXrVjVu3FiNGzfWzp0779yHBwAAAJDhudn55g0bNlTDhg2vO84Yo5EjR6pv37569tlnJUnTp09XQECA5s+fr1atWmnPnj1avHixfvnlF5UvX16SNHr0aD355JP65JNPlCdPHs2cOVMJCQmaPHmyPDw8VLx4cW3btk3Dhw+3gtuoUaPUoEED9ejRQ5I0aNAgRUZG6rPPPtO4cePuwpwAAAAAkBHds9eQHTx4UNHR0apbt641zM/PTxUrVtT69eslSevXr5e/v78VxiSpbt26cnFx0caNG6021atXl4eHh9UmJCRE+/bt0+nTp602qd8npU3K+1xPfHy8YmNjnR4AAAAAkBb3bCCLjo6WJAUEBDgNDwgIsMZFR0crZ86cTuPd3NyUNWtWpzbXm0bq97hRm5Tx1zNkyBD5+flZj3z58qX1IwIAAADI4O7ZQHav69Onj86ePWs9Dh8+bHdJAAAAAO4z92wgy5UrlyQpJibGaXhMTIw1LleuXDp+/LjT+MuXL+vUqVNOba43jdTvcaM2KeOvx9PTU76+vk4PAAAAAEiLezaQFSpUSLly5dLy5cutYbGxsdq4caOCg4MlScHBwTpz5ow2b95stVmxYoWSk5NVsWJFq83q1auVmJhotYmMjNTjjz+uhx56yGqT+n1S2qS8DwAAAADcCbYGsvPnz2vbtm3atm2bpCsdeWzbtk1RUVFyOBzq2rWr3n//fX3//ffasWOH2rRpozx58qhx48aSpGLFiqlBgwbq1KmTNm3apLVr1yosLEytWrVSnjx5JEkvvPCCPDw81KFDB+3atUuzZ8/WqFGj1K1bN6uON998U4sXL9awYcO0d+9evffee/r1118VFhZ2t2cJAAAAgAzE1m7vf/31V9WqVct6nhKS2rZtq6lTp6pnz56Ki4tT586ddebMGVWtWlWLFy+Wl5eX9ZqZM2cqLCxMderUkYuLi5o2bapPP/3UGu/n56elS5cqNDRUQUFByp49u/r16+d0r7LKlStr1qxZ6tu3r95++20VKVJE8+fPV4kSJe7CXAAAAACQUdkayGrWrCljzA3HOxwODRw4UAMHDrxhm6xZs2rWrFk3fZ9SpUrp559/vmmb5s2bq3nz5jcvGAAAAADS0T17DRkAAAAAPOgIZAAAAABgEwIZAAAAANiEQAYAAAAANiGQAQAAAIBNCGQAAAAAYBMCGQAAAADYhEAGAAAAADYhkAEAAACATQhkAAAAAGATAhkAAAAA2IRABgAAAAA2IZABAAAAgE0IZAAAAABgEwIZAAAAANiEQAYAAAAANiGQAQAAAIBNCGQAAAAAYBMCGQAAAADYhEAGAAAAADYhkAEAAACATQhkAAAAAGATAhkAAAAA2IRABgAAAAA2IZABAAAAgE0IZAAAAABgEwIZAAAAANiEQAYAAAAANiGQAQAAAIBNCGQAAAAAYBMCGQAAAADYhEAGAAAAADYhkAEAAACATQhkAAAAAGATAhkAAAAA2IRABgAAAAA2IZABAAAAgE0IZAAAAABgEwIZAAAAANiEQAYAAAAANiGQAQAAAIBNCGQAAAAAYBMCGQAAAADYhEAGAAAAADYhkAEAAACATQhkAAAAAGATAhkAAAAA2IRABgAAAAA2IZABAAAAgE0IZAAAAABgEwIZAAAAANiEQHaViIgIFSxYUF5eXqpYsaI2bdpkd0kAAAAAHlAEslRmz56tbt26qX///tqyZYtKly6tkJAQHT9+3O7SAAAAADyACGSpDB8+XJ06dVK7du0UGBiocePGKVOmTJo8ebLdpQEAAAB4ALnZXcC9IiEhQZs3b1afPn2sYS4uLqpbt67Wr19/Tfv4+HjFx8dbz8+ePStJio2NvfPF/r/k+At37b3utrs5H+3Asrs/PcjLTWLZ3a8e5OUmsezuVw/ycpNYdveru7ncUt7LGPOvbQlk/+/kyZNKSkpSQECA0/CAgADt3bv3mvZDhgzRgAEDrhmeL1++O1ZjRuI30u4KcLtYdvcvlt39ieV2/2LZ3b9YdvcnO5bbuXPn5Ofnd9M2BLLb1KdPH3Xr1s16npycrFOnTilbtmxyOBw2VnZnxMbGKl++fDp8+LB8fX3tLge3iOV2/2LZ3b9Ydvcnltv9i2V3/3qQl50xRufOnVOePHn+tS2B7P9lz55drq6uiomJcRoeExOjXLlyXdPe09NTnp6eTsP8/f3vZIn3BF9f3wduhckIWG73L5bd/Ytld39iud2/WHb3rwd12f3bkbEUdOrx/zw8PBQUFKTly5dbw5KTk7V8+XIFBwfbWBkAAACABxVHyFLp1q2b2rZtq/Lly6tChQoaOXKk4uLi1K5dO7tLAwAAAPAAIpCl0rJlS504cUL9+vVTdHS0ypQpo8WLF1/T0UdG5Onpqf79+19zmibubSy3+xfL7v7Fsrs/sdzuXyy7+xfL7gqHuZW+GAEAAAAA6Y5ryAAAAADAJgQyAAAAALAJgQwAAAAAbEIgAwAAAACbEMgAXFfq/n7o+wcAAODOIJABuC6Hw+H0N6HswZGcnCyJoH0vu3rZpCwzAHdG6nWO9e3e9iD+dhHIcMfwhXb/i4iI0MsvvyzJOaDh/ubicuWr/88//7S5EtxIyvr2ySefaOfOnXJxcXkgN0LuR4TlB1PKOjdq1Cht2rRJEsv2XpWyrKKjo22uJP0QyHDHpGz0LV26VMePH2dj4j5z+fJlnT59WocOHVJsbKzd5SCd/fjjj6pataoOHTpkdym4gQsXLmj+/Pn69NNPlZSUxE6Re0TKcpg+fbqioqKs3zo8GGbMmKHBgwdLEsv2HjZ69Gj17t1b0oNxxIz/NNwxycnJ2rlzpxo0aKD9+/dz2tt9xs3NTc2aNdOvv/6qOXPm2F0O0lnmzJn10EMP6e+//5bEnuB7UaZMmfTkk09qy5YtiouLk/RgbHg8CA4cOKAPP/xQq1atkiQlJSXZWxD+s5TvwN69e+v48eP67bffJLHO3aty5sypWbNmadu2bQ/EzioCGe4YFxcXlShRQi1atNCHH36o8+fPPxArTUZStGhRvfXWW/riiy907Ngxu8vBbbpe2Kpevboef/xxde/eXRJ7gu12o0AcHh6u48ePa+jQoZI4dfheUbhwYRUrVkyTJ0+WJLm6utpcEdLq6qCV8h1YvXp1nTx50toRyTpnv6s7GUtOTla9evVUv359/fDDD5Lu/52K/AIj3Vy9MiQmJkqSnnrqKR05ckRHjx69bjvcOwYNGqTu3btryZIl1rCaNWvqzz//1MGDByWx/O5HKRsa58+fdxreu3dvXb58WYsXL5bEnmA7pSyjL774QsuWLdOFCxckSd7e3goNDdWGDRt04sQJO0vMsK7+zks5GjZ48GAdPnxYX375pR1l4T9KCVqzZ8/WmDFjrOE5c+ZU3759NXv2bOsoGeyVsqzOnTsnh8MhFxcXZc2aVaVLl9aECRN06dKl+/46WwIZ0k3KBsXKlSv1zz//yN3dXZL04osvKj4+nnOy7wPZs2fX2rVr1bVrVzVq1EgrV65UrVq11LBhQ/Xq1UtJSUksv/vUxIkT9cgjj6hfv37WRkaJEiXk7e2tuXPnSmJPsN3Onz+vQYMGqU+fPgoODlZkZKSio6PVtm1b/fLLL/rpp5/sLjFDSvnO+/7773X+/HkrkGXPnl0lS5bU6tWrJbFD43508uRJTZ48WR9//LHKli2rcePG6eDBg2rUqJH8/Pys70pOSbXf1KlTVb9+fS1YsMDaOTV48GBly5bN2r68n3/D2LJCulq5cqVCQ0NVokQJTZo0SRs3bpQkDRgwQPv379fWrVttrhAprnekq0uXLpo/f76mT5+uxMRE9e7dW2XKlJGnp6dOnz6tzZs33/C1uLc1b95c7du312+//aZKlSopPDxcv/32mz7++GMtXLhQa9assbvEDOfq9cjHx0fbtm3TmDFjVL58eb3xxht6+umntWDBAj3zzDMaPXq0/vnnH5uqzdj279+v559/XtWrV1doaKj27t2r7Nmzq1u3bpo6darWrFlzX28MZhRXr3PZs2fX119/rc2bN+uJJ57QN998oyeeeEJLliyRq6urhg0bposXL3JK6j3AxcVFpUuX1ksvvaSXX35ZAwYMUGxsrKpXr64///zzvg/NDsMuHfwHxhinH6HLly/r0KFDmj59uiIjI3X8+HE1b95cpUuXVt++fdW/f3+1adPGxoohXflRStnru2zZMh07dky+vr6qUaOG/P39rXZbtmzRvHnzNH36dB05ckShoaEaPXq0TVXjVqVevlc7d+6clixZopkzZ2r79u3y8/PT8ePH1bVrV/Xo0UNJSUlsfNwFqZfR7t275eHhIWOMihQpYrXZuHGjtm7dqoEDB8rhcOjUqVP66aefVKFChZsuY/x3V/+2SVd6vRw7dqxWr16t5cuXq127dipfvrx+/vlnZcuWTUOGDJHEWSD3qtTrzM6dO5WYmKiAgADlyZPHahMTE6OvvvpK3333nY4dO6Z9+/bpq6++UosWLa77P4E742bfbxs2bNDq1as1atQolS1bVg6HQwsXLtTs2bPVvHnzu1xp+iGQ4balXmEuXryouLg4Zc+e3Rq/f/9+7d27V2+//baKFy+ur7/+WoUKFdKKFStUoEABu8rO8FL/qPTu3Vtz586Vq6urAgIC5OLiorlz5zotR+nKsly4cKEiIiL01VdfKSgoyI7ScQtSr5fTpk3Txo0blTlzZgUFBalVq1ZWuzNnzuj48eN6//33tW7dOl24cEHbtm1Tzpw57So9w0i9Dr733nuaO3euLly4IE9PT/Xv399pOUnSsWPHtH79en344Yd66KGHnK7xRPpLvQ7FxMTI3d1dbm5u8vX1tZbdF198oXXr1mnevHk6ceKE8ufPr99++82pDe4dqZdJv379NHPmTEnSiRMnFBERoUaNGilr1qxW+8OHD+vYsWPq3Lmz8uTJo0WLFtlSd0aUev2bN2+eoqOjlZCQoDZt2uihhx6yxsXFxWn06NH6/fffNXXqVD377LOaOnWqfH1978/1zwC3ISkpyfp7yJAhpm7duiZ//vyme/fuZufOnU5tT5w4YVasWGFeeeUVkzVrVjNnzhxjjDGXL1++qzXD2SeffGJy585t1q9fb4wx5oMPPjAOh8OULFnSREdHG2OMiY+Pt9ofOHDAFC1a1Hz99de21It/l5ycbP3ds2dPkydPHtOmTRvTpk0bkzdvXjNixAhrfGJiovX3li1bTPXq1a3xqaeD9JV63vbv39/kzJnTLFmyxOzdu9c8//zzxuFwmIkTJ1ptUn9PLl682JQqVcrs27fvrtackaT+bRs0aJCpXr26yZs3r+nYsaOJjIx0ahsfH2/++OMP06NHD1OoUCHTq1evu10ubkHqdWjAgAEmd+7cZsmSJSY5Odm88MILxt/f3wwbNsycPXvWapeynu7atcsEBASYn3/++a7XndH16tXLBAQEmPr165uAgABTu3Zt8+OPPzqtoykmTpxoHnroIfPbb7/ZUGn6IJAhTa7eUHvnnXdMrly5zIgRI8z8+fONv7+/adWqlVmzZs11X//SSy+ZChUq3I1SkcrYsWPN33//bT2PiooyjRs3tsLxokWLjI+Pj+nRo4cpW7asKVOmjDlx4oQxxnnDvXLlyuadd94xxrDRfi+5eufGpEmTzCOPPGI2bNhgjDFmxowZxt3d3Xh6epoBAwZY7VICd3JysmnVqpV54YUX7l7RGcz69euddnD8+uuvpkaNGmb58uXGGGMWLFhg/P39TcOGDY3D4TCTJk2y2qasa9HR0SZXrlxm9erVd7f4DKhv374mW7Zs5quvvjJfffWVqVOnjilWrJhZsGCB1SYhIcEYY8zFixdN3759Tf369Z2+L2Gv+fPnOz3ftWuXqVu3rvnhhx+s8Q899JB5+umnjcPhMMOGDTOnTp2y2icnJ5tTp06ZwMBAs2LFirtae0aUOmiNHDnS5MuXz2zevNkYY8zcuXONw+EwVatWNYsWLbLapv7tq1WrlgkPD7+7RacjAhlu2ZkzZ4wx/1sBFi1aZB5//HGzdu1aY4wxmzZtMm5ubiZHjhymXr161sagMf/b8Fu5cqUJCgoyx44du8vVZ1zbtm0zDofDvPLKK07zfcGCBeavv/4yv/76q8mfP78ZO3asMebKHkSHw2Fy5sxp/vnnH6v9d999Z3LkyGF27dp11z8Dbqxt27Zm3rx51oZgQkKC6devnxk6dKgxxpjvv//e+Pn5mY8//tj07dvXuLi4OB0pS9nYDwsLM7Vr1zYXL14kbKezgQMHmnz58pl58+ZZG/F//fWX+fDDD01iYqJZvny5yZ07txk7dqw5d+6cqVOnjnE4HGbUqFFO05kxY4bx9vY2Bw8etOFTPLhSb4Qbc+VIZPHixa3fsGXLlhkvLy9TqVIlU7RoUbN48WKrbcp6t23bNpMjRw6zZ8+eu1c4bmj8+PHmkUceMR9//LE17K+//jKTJ082CQkJZvXq1SZPnjxm9OjRxhhjmjVrZrJmzWoGDhxozp8/b71m5syZxuFwmD///POuf4aMokePHmbjxo3GmCu/R6dPnzY9evQwEyZMMMZcCWP+/v7m448/NqVKlTKlSpUyCxYssLZFU36vatWqZXr06GHPh0gHBDLcknfeeceUK1fOOpUtMTHRrFmzxkRERBhjjPnxxx/NQw89ZGbOnGn27NljPDw8TIsWLcyyZcucpvP666+bXLlymdOnT9/tj5AhpXxRRUZGGnd3d9O5c2cTFRXl1Objjz82TZs2NRcuXDDGGDNlyhTTsmVL06tXL6e9T3/++ScbgvegatWqmZw5c5pFixZZOz5Onz5t9u/fb6KiokyxYsXMsGHDjDHG/PzzzyZTpkzG4XCYzz//3JrG9u3bzRNPPGG2bt1qx0d44F24cME0aNDAlC9f3syZM8dcunTJGGOsU6Refvll89prr1kb9506dTLlypUzVatWtdbh5ORk8+WXX5rdu3fb8yEeUK+99pp5/PHHzdGjR61h+/btM927dzfGXNnxmD17djNhwgTzyy+/mAIFCpgiRYpYZxek+PDDD83DDz9sYmJi7mr9uL5Dhw6Z0NBQU6lSJTNkyBBreMpOxk6dOpn27dubhIQEk5ycbF577TVTqlQpU6VKFad1btOmTYTsO+i3334zlStXdvr9SUhIMGvWrDHHjx83O3fuNEWKFDEjR440xlzZWeLu7m5Kly5tnYmVnJxstm/fbhwOh9m2bZtdH+U/I5DhlkydOtXUqFHDNGjQwDrKcurUKXPs2DFz9uxZU6NGDfP+++8bY66sTCVKlDAuLi6mT58+1jSSk5PN22+/be0JwZ2X+vSZRYsWGRcXF9OjRw9z+PBha3i3bt1Mvnz5zMWLF01CQoJ57rnnnE5r4xSce1Pq0zuee+45kz17drNw4UITFxdnDf/xxx9NiRIlrI3EzZs3mxdffNF8++2315zmmPpoKNLPxYsXjTFXlldISIipUqWK+frrr60jZbGxsaZ06dLWd+WFCxdMkyZNzKJFi6xpXO+aCaSP33//3RQpUsRUr17dHDlyxBoeGxtrEhISzJNPPmn69etnDa9fv74pWrSoeemll4wx/9vp1atXL3Zo3CNS1q1//vnHdO3a1VStWtXprIALFy6YmjVrmjfeeMMa9txzz5nt27c7hTHcHcuXLzdPP/20CQoKsk5RTFmGkydPNsHBwdbBgK+//tq8+OKL5tVXX73mN+z48eN3t/B0RiDDLZs7d65p2LChqVevntM/fkxMjClZsqSZOXOmMebKD9mrr75qVq5cSccdNrq684D333/fZMuWzTgcDtOlSxdr42P9+vWmXLlyJnfu3KZ06dKmWLFiVgjjR+nelXoj/cKFC6ZcuXKmRIkSZuHChdaP2erVq423t7eZMGGCiY6ONk8++aRp06aNtVwTExPZ2L+DUs/bhQsXmg8++MC4u7ubEiVKmG+++cZaTn379jXu7u4mNDTUVKhQwZQtW/aa03GQ/lK+5w4dOmQef/xxU7t2baedVSdOnDAFChSwTmv7559/TMuWLc2cOXOs5cL6c29Jvb7MmTPHvPLKKyZHjhwmd+7cTqcAv/POO8bDw8O8+OKLply5ciYwMJDfvbss5fvPmCvLqkGDBqZChQpWx3DJycnmww8/NMWKFTNbtmwxp06dMs8884x1Or4xD1bncHR7j5tK3f3ojz/+qCVLlmjs2LFq0KCBJk6cqBw5cuivv/5SrVq1VK1aNVWrVk3z5s3T6dOntX79ejkcDu5rZLOPPvpIH330kebMmSNjjA4cOKCwsDB16NBBgwcPVtasWbVp0yYtX75crq6u6t69u9zc3Fhu94nw8HD9/vvvunTpkrZu3SovLy9NnDhR9erV08WLF/Xee+9p7Nixyp07t/z8/LRp0ya5u7vTNfdd9M477+jzzz/XgAEDFBcXpxkzZigpKUnvv/++nn32WZ09e1ajR4/WunXrlDdvXo0bN07u7u6sg3dQ6t+2yMhI7dmzR127dtWTTz6pzz//XA8//LDOnz+vTp066ciRI3ruuee0aNEiXbhwQT///LNcXFy4F9w97J133tH48eM1cOBAubq6atq0abp48aJatmypXr16SZIGDBigPXv2yN/fX6NHj2adu4tS//4MHjxYv/76qw4dOqTt27erfPnyGj9+vMqUKaOoqChVqVLFWs8eeugh/fLLL3J3d7ez/DvD1jiI+0bXrl1NYGCgef31102dOnVMnjx5TEhIiHX64tKlS02RIkVM2bJlTe3ata09H+xpsldSUpJ58sknreshUnz33XfGxcXFhIWFXbeDlQdpr9ODbOrUqcbPz89s2bLFREdHm5iYGPPkk0+a7NmzW73BnT171mzevNksXLjQWq6chnr3HDx40BQsWNDpdhEXL140VatWNY8++qiZP3++tTxSruM0hmV0t/Ts2dPkzZvXDBgwwLzwwgsmICDAVKtWzbqmbPHixaZly5amRIkS5umnn7Z+2zgydm9Jva3x999/m2LFipkvv/zSGvbXX3+ZDh06mMcff9x8+umn1vCU6zmNYZ2zw+jRo42Pj49ZtmyZOXTokJk0aZKpXbu2KV++vPn111+NMVd6hZ48ebKZOnWqtYwexGVFIMO/WrNmjcmdO7dTV8uTJk0ywcHBJiQkxDq39+jRo+bEiRNOp0Ph7ro6AF+4cMFUqlTJdO3a1RhzJWilLJfQ0FDj6upq2rZty4Xo96khQ4aYmjVrmsTERKdlX69ePVOgQAGzcOFC6xqmFITtO+vqdfDIkSPmkUcesbrgTtkAjIuLM3nz5jWVK1c206ZNczp9hx1Zd0bq2w4Y87+eEX/88UenYYUKFTJVq1a1ftsuXbpkTp8+zW/bPSp1OP7777/N2bNnTZEiRaxTTVPfNqJQoULmkUceMe+++64tteJ/Ll++bF588UXTuXNnp+ELFiwwZcqUMRUrVjTbt2+/7useRBxrx786d+6cLl68qIcfftga9tJLL6lFixZavXq1XnnlFR09elS5c+dW9uzZ5XA4lJycLDc3NxurzniSk5OtUwB27dqlhIQEeXt7q0mTJpoyZYo2bdokV1dX69B/QECAateurT///FPZs2e3s3TcguTk5GuGXbhwQYcOHZKbm5scDocuXbokSeratauioqLUrFkzbdmyxek1nI5z56ReB8+cOSPpyik2np6e+uGHHyRJnp6eSkxMlKenp4oUKaLt27dr7dq1TqfgcCpp+qtVq5YiIyOdhl28eFGSVLRoUUlXTqMqXbq0ZsyYoc2bN+u1115TVFSUPD095e/vz2/bPSrlN+2tt95Sjx49FB0drYcfflhbt25VXFycpCvLNiAgQBUrVpSPj49iY2NluGLHVq6ursqSJYv279+v+Ph4a3ijRo3UsGFDbdq0Sc8884z27t17zeseRAQyOEn9BZXyd968eZU3b179+uuv1kahu7u72rVrp3z58mnt2rX66KOPnKbDefV3V+prGfr3769u3brphx9+kDFGTZo0UUhIiNq3b68NGzbIxcVFFy5c0KZNm/Tmm29q9erV1vUQuDelXr5LlizR5s2bJUkdO3aUMUadO3eWJHl5eUmSMmfOrLfeekthYWGqWLGiPUVnMKmX0bBhw9S9e3cdOHBA3t7e+uSTTzRr1iy9++67kq58fzocDuXPn19Lly7V2LFj7Sw9Q6hXr57q1q0rSUpKSpIkFStWTMYYff3115L+F4QfffRRFShQQN9++60++OADp+nw23Zv2rNnjyIjIxUWFqbHHntM77zzjqZOnaoPPvhAp06dksPhUHx8vJKSkvTWW29pxIgRcjgchLK75EbbF6VKldKRI0e0ZMkSa4eidGUnScOGDdW5c2cVKVLkbpVpL9uOzeGek/qwf0JCgnWq04ULF0zdunVNpUqVnG72HBUVZZo0aWJmz57N+fT3iN69e5vs2bObxYsXO52GuHXrVtOyZUvj5uZmgoKCTOHChelN8T6Retn06tXLBAYGmnHjxpnTp0+bCxcumM8//9w8/vjj5oUXXjB//fWX+e2330yDBg1MWFiY9boH9RSPe1H37t1NQECAmTFjhvnjjz+MMcacP3/eREREGE9PT1OvXj3TqVMnU7lyZVO0aFHru5NldGdc/ds0ePBgM2HCBHPu3DljzJXe9oKCgsykSZOsNrGxsaZt27Zm27ZtLJf7wAcffGDatm1r2rZt63Tq7+zZs42Hh4epV6+eee6550xwcLApXry4tUzZbrk7Us/nb7/91nz11Vfm+++/t4Y99dRTpnDhwmbGjBnm0KFD5vTp0+bZZ5817777rvX7lxHWQ3pZxDWGDBmin376SUlJSerUqZNatGihs2fPqlq1avLy8lK9evVUsmRJjR8/Xp6enlq4cCE9Tt0D1q1bp7Zt22rWrFl64oknFBcXp+PHj2vTpk2qW7eusmXLpm+//VYHDhyQp6enXnvtNXpTvI8MGjRIo0eP1rx581SpUiXrFLfLly9r3rx5evfddxUTEyM/Pz/lzJlT69evfzB7orqHzZ49W2+99Zbmz5+v8uXLS5ISEhJ0/Phx6yyDoUOHyuFwyMfHx+pNke/OOyf1vE1OTlZ4eLg+++wzTZ8+Xa1bt9aff/6pDz/8UKtWrVKNGjVUpkwZzZkzR+fPn9emTZvk4uLCd+Q95ur15YMPPlDfvn1VvHhxrVq1StmyZbN68du0aZO+/fZbHT58WNmyZdMnn3zCOncXmVS9Kfbo0UPjx49Xnjx59Mcff6hLly4aNWqUJKlly5bas2ePDh8+rNy5c8sYox07dsjNzS3j9AhsZxrEvSH13oshQ4aYHDlymLfeess0b97cOBwO8+GHHxpjrvTW9uqrr5pKlSqZ4sWLm5CQEHqcuods2rTJ5M+f32zbts3s3r3bdOvWzTz66KMmd+7cJmfOnNftuCMj7HV6EBw5csRUqFDBzJs3z3q+atUqExoaaj7//HOr3cqVK83GjRvpTfEuufp777PPPjPVqlUzxhizc+dO88knn5iiRYsaPz8/6+bCVx+NZhndOann9VtvvWXatWtnjDEmLCzMeHp6munTpxtjjDl8+LCZMGGCKV68uKlatap56qmn+G27D0RFRVnLZ+zYsdb2yr/d3Jl17u5L+Q3bvn27iYqKMnPnzjWZMmUy7du3t9ps3LjRfPnll+bLL7+0fsMy0jYKV6bC2kv0+++/y9PTU19++aXq1Kmjy5cvq1q1auratauMMerdu7c+++wzJSYm6syZMwoICJDD4dDly5e5yPkuu97ePX9/fz366KNq3bq1Dh8+rFatWum9995TzZo1VaVKFX333Xfq1KmT02vY63t/8Pf3lyStXbtW/v7+Gj9+vP744w/5+PhozJgxOnbsmPr376+aNWtar0lKSmK9vMNS1sE+ffooa9asevzxx7V//341adJEu3bt0hNPPKGOHTvK19dXr7zyilq0aKHixYtbrzfGsIzukKNHjypPnjySpJUrV2r58uX67LPPJEmjR49WcnKy9X3YunVrdezYUe3bt1dCQoJ1LSa/bfeuSZMm6aOPPtL48eNVvXp1vfrqq4qLi1PPnj3l7e2tN954wzqqkvr3knXu7hsyZIg2b96sEiVKqGjRovLw8FC+fPnk5eWlli1bysXFRRMmTFCFChVUoUIF63UZ7si0zYEQ94gVK1YYh8NhcuTIYZYtW+Y0bvTo0cbV1dXp7ugp2Ht496We5+vWrTPz5883a9asMZcuXTIHDx40kydPNkuWLDFxcXHGmCtHNsuXL291u4172/XWqcTERNO/f38TFBRk3NzczFtvvWWtp+3btzevvfba3S4zQ0u9jL777jvzyCOPmF9++cVER0ebyZMnm2eeecZMmjTJHDp0yBhjzO7du01wcLA5cOCAXSVnKKNGjTL58+c3SUlJ5ptvvjEvv/yyCQ0NNcYYp9tAvPbaa8bb29t88cUX1jVlKbiu9t52+vRpU6JECRMcHGx++ukna5385JNPjKurq9O9xnB3pf5+TE5ONiNGjDDe3t4mKCjomrYLFiwwvr6+pkWLFnezxHsSgQzGGGNOnTplBgwYYNzd3U1ERIQxxvkHKSIiwjgcDjNz5ky7SsRVevbsaR5//HFTpEgRU7NmTVO2bFnz999/W+Pj4+NNVFSUadSokXniiScy1KH/+1XqH7JZs2aZt99+2/Tr189ERkYaY67c62/Xrl1Or6latSr31LHJkiVLzCuvvGIGDRrkNDz16Tbnz583jRo1MrVq1WIH1l0wbtw44+npad0UuG7dusbb29vUqlXLapP6fmRhYWHG4XCYxYsX3/VacWtutN6cPXvWlClTxlSoUMEplA0bNsw4HA6nm7Hj7jt27Jgx5sp9/CZNmmTc3NxM//79r2k3d+5cU6dOnQz//Uggy4Bu9E9//vx507NnT+Pi4mK++uqra8bPmzePc6/vERERESZHjhxm/fr1xhhjBg0aZBwOh9VzUUJCgomIiDANGjQwlSpVsq6HIJTdH3r06GHy5Mlj2rZta1588UXj6+trPvjgA2v8+fPnzZYtW0xISIgpVaoU6+VdkrKTKikpyezfv98UK1bMeHt7mzfeeMNqk/L9GhcXZ7788ktrZwnXJN1548ePNx4eHubbb7+1hsXGxprnnnvOFCtWzHz22WfWMkwdyj755BPWofvAF198YXbu3Ok07MyZM6ZUqVKmTJkyZvXq1db6NWvWLJapjaZPn278/PzMpk2bjDFXtj3GjBljXF1dzcCBA2/4uoz8/Uggy2BS/7N/+eWXZujQoaZfv35m+/bt1g9U9+7dnUIZF6HfWy5fvmw6duxodbby3XffGR8fHzNhwgRjzJUNwcTERLNp0yYzYcIEOni4zyxYsMDkz5/fCtszZswwXl5eZvLkyVabL7/80jz33HOmfv36hG0bpHwnLlu2zFSoUMEUL17cLF261KlNdHS0iYiIML169bLWPdbBO2flypXG4XCYAQMGOA1/8803TVhYmGnSpImpWrWqU/f2ly5dcmrL8rl3JCcnO32nXbhwwXh4eJgaNWqYvXv3OrU9c+aMyZkzpwkJCTGLFy922mZhmdojISHBBAcHmyJFiphffvnFGPO/UObm5mbef/99myu89xDIMpCre5zKli2befLJJ03u3LlN8eLFTb9+/UxcXJxJTk42PXv2NO7u7k4bgbBHSohOvfxatWplxo4daxYsWGB8fHzM2LFjjTFXvvDGjx9vpk6d6jQNNtbvH6NHjzYNGzY0xlw5Kp0lSxarJ8XY2Fjz22+/mfj4ePPzzz9b/xtsdNw9kydPNi+88IIVhCMjI02lSpVM06ZNzapVq5zaXrhwwfqbdfDO+v333021atXMM888Y20ANmnSxBQpUsTExcWZEydOmKZNm5rq1avzu3Yf2L9/v/X3hAkTTFRUlDl8+LDJkyePqVOnjlMoS0xMNLVq1TIOh8N07tzZjnIztKt32qc8T0xMNNWqVTOFChVyCmUpPWJOmTLlbpd6TyOQZUDff/+9efjhh83mzZutYT179jRVqlQxQ4cONUlJSSY2NtZ06dLFVK1a1cZKkdrvv/9ujLnyZRceHm51pz1mzBirzfHjx01ISIj5+OOP7SoTtynlR2zatGmmY8eOZu7cucbHx8eMGzfOavPdd9+Zt956y5w5c8YalpFP8bjbUjpXKVu2rOnSpYsVyn788UcTHBxsmjVrZn766Sebq8y4fv/9d9OgQQPTqFEjU7VqVVOuXDlz8OBBa/yxY8dM8+bNTdGiRc2CBQvsKxQ3tX37duPm5mZmzJhhevXqZfz9/c2+ffuMMVduURAQEGBq165tXU+bnJxsQkNDzY4dO9jxcZelPso8efJkqyOj1KGsatWq5tFHH7VCWWJiovnmm2/YkXgVAlkGsGTJEusCZ2OuXPQcGBhozpw5Y600Fy5cMJ07dzZly5a1vtBSjpbBfosWLTLe3t5m7ty5xpgrR0pKlSpl8ufPb/bs2WNOnTpl/v77b9OwYUNTsWJFvujuAzcKUkuWLDGZM2c2DofDKWzHxcWZkJAQ8+qrr7Je3iXXW0bnz583H3/8sXniiSfMK6+84hTKqlatamrVqmW2bt16lytFit9//93UrVvX+Pn5OXXqkLKcjhw5Yt5++2023O9hx44dM4MGDTLe3t7Gz8/PHD161Bjzvx4yDx8+bPLly2cqVqxo2rRpY2rVqmVKlixpra8s27tjyZIlZujQoWbDhg0mNjbW5MyZ05QrV84cPnzYGPO/UHb69GlTsGBBU7lyZbN27VqnabCt8j/cpvwBt3btWjVo0EDDhg3T9OnTJUmZM2fWxYsXlZCQIIfDocTERHl7e+udd97R9u3btXr1aklSpkyZ5HA4ZIyx8yNkSBcuXHB6njdvXj3//PPq3r275s6dqyxZsujbb7+Vq6urnn32WRUvXlwtWrTQyZMn9fPPP8vNzU1JSUk2VY9/Y4yx7oszY8YMDRs2TGPHjlVycrLq16+vIUOGSJLi4uK0atUqbdiwQY0bN1Z0dLRGjx7NenmXpCyjNWvWWMMyZ86sLl26qHnz5tqyZYvefPNNJSYmqkGDBurevbsee+wxlSpVyq6SM7wiRYpo3LhxqlSpkqZMmWItO3d3dyUmJipPnjwaPHiwXF1d+Y68R+XKlUu5cuXSpUuXlJiYqMjISEmSl5eX4uPjlTdvXv3yyy8qWbKkzp07p4cfflibN2+Wi4uLkpOTM9a9q2wyZcoUtW/fXgcPHpSLi4uyZMmiX3/9VfHx8WratKkOHz5s3QfOw8NDjz/+uNavX68RI0Y4TYd7wqVicyDEHTZ//nzjcDhM9erVzbPPPmu+/vprc+7cOZMzZ07Ttm1bp7Y7duwwgYGBZvv27fYUC2OMMVOmTDEDBw68Zu/87t27TadOnUzevHnNvHnzjDFX9hjOmTPHTJgwwSxZsoQOPO4D17uWs2zZsqZQoUKmUqVK1jJ8//33TcGCBY2/v7+pUKGCadCgAR142CAyMtI89thj13TXHBsba/r06WNy5MhhunXr5tRrnzGcSmq3lNMXGzRoYNasWWN3OfgXKd+LKd9tf/31l9m0aZMZNGiQyZIli3XqdnJy8g3XLX737o4vv/zSZMqUycyePducPXvWadzhw4dNyZIlTVBQkImKirKWVYcOHcyBAwf4XrwJhzHsZn3QtWnTRlFRUcqWLZtOnDihnj17yt/fX88995yqV6+uTp06yd/fX4MGDdKpU6e0du1aa88w7q7x48fr1Vdf1dq1a/Xnn3/q4YcfVs2aNa3xu3fv1siRI7Vo0SKNGTNGzzzzzDXTyHB3t79PnTp1Sl26dFHfvn1VsGBBbd26Va+++qrc3d21ZcsWubq66sCBA4qPj1fmzJlVoEABORwOXb58mb2Kd5AxxtqzK0kxMTEaPHiwNm/erJCQEPXr188a99dff6lKlSpKSEhQeHi4+vTpc83rYZ/9+/crPDxcMTExmjRpEkcu71HJycnWNkdcXJy8vLys37C//vpLEyZM0Keffqrhw4erY8eOkqQPPvhA9erV0xNPPCHp2vUWd8aJEyfUokULNWvWTKGhodbw8+fPa9euXfL09FTWrFnVunVr/fXXX6pbt67279+vc+fOacuWLXJxcWEb5UZsjYO4o1Iutvziiy9Mp06dzIYNG0yTJk1MjRo1zMyZM8327dtN6dKlTd68ea2bC3OvHPtMnz7duLu7mwULFpjTp0+bOnXqmOLFi19zzvW2bdtM8eLFTZ48ebjx5X1ix44dxpj/7QUeO3asKVy4sGnYsKH5559/rHEbNmwwxYoVM6VKlbruUTDWyzvr6nme8h0aHR1tunbtaipUqOB0D519+/aZ1q1bm2nTprFs7lG7d+823bp1Y/nco1IvlxEjRpj69eubunXrmi5duljDo6KiTN++fY2np6d5/fXXTd26dc1jjz3GmQI2OH78uAkMDHS619+YMWNMs2bNjMPhMLlz5zYNGzY0CQkJ5vXXXzctWrQwL730EtuWt4BA9oBZsWKFmThxotOwo0ePmocffthMnjzZHDt2zDRp0sRUr17d/PjjjyYpKclERUWZnTt30oW2jaZMmWIcDoepV6+eNWzZsmWmRYsWpnTp0tecctOsWTNTtGhR06RJk7tdKtIoIiLCOBwOs2LFCmPMlc4FvvrqK2tnSGrJyclm48aNpmTJkiZ37tx03nGXXH1fo48//ti0aNHCNGnSxNohcvz4cRMeHm6eeOIJ06ZNG7Ns2TJTv35907p162tOt8K9iY3Be1fv3r1Nrly5zJAhQ8zYsWNN9uzZzbPPPmttj0RHR5sxY8aYypUrO912gmV6dx0/ftzkzZvXdOzY0Sxfvtw0bdrUlCxZ0nTp0sUsXbrUzJkzx+TLl8+MGjXqmteybXlzBLIHyIoVK4zD4TAOh8OEhISYsWPHWnvmv/zyS/P000+bc+fOmZ07d5qmTZuamjVrXhPe+HK7+8aPH29cXFxMx44dTZ48eUxoaKg1bsWKFaZp06ambNmyZsOGDcaYK728vfTSS+abb75hg/0+cPz4cdOxY0eTKVMms2zZMmPMlWX43XffmYcfftiEhIQ4tU9OTjY///yzad26NRv4d8GIESOMw+Gwdnr079/f5MiRw3Ts2NHUqlXLuLi4mFmzZhljjDl58qQZOXKkCQwMNIULFza1atWyNgxZF4Fbl7q79Pnz55vAwECzbt06Y8yV23tkzpzZZMqUyVStWtVax4wxJj4+3qlLddx9y5YtM35+fuaRRx4xpUuXNsuXLzcnT540xhhz6tQpU6ZMGdO3b1+n1/D9+O8IZA+Q/fv3m+rVq5vatWubmjVrmtdff91ky5bNjBw50gwfPtzUrl3b/Pzzz8YYY3bt2mVq1qxpwsLCWFFslLIxuGjRImPMlVsSZM+e3YSFhVltVqxYYVq0aGH8/PxMmzZtTIUKFUyFChWsjXVC9L0rZd06d+6cef311423t7e1Dl64cMHMnz/fPProo6ZRo0bXfZ0xHHW50/744w/z6quvGh8fH7N27VrTv39/p2XUq1cv4+bmZmbOnGmMubIReO7cObNv3z7OKgBuQ0p36Rs3bjTGGDNnzhwzePBgY4wxCxcuNFmzZjURERFmxYoVxt3d3Tz33HPXdJrDdou9jh8/bv78889rhp86dcpUq1bNfP755zZUdX8jkD1g9u3bZ5o0aWKefvppExkZaRYvXmyaNPm/9u4+rOb7/wP486NOqTO5aSx3cxeyuYlr6JKj5SalTFe4NpPc5MpYczcSunZjF1luUszdEMOFzV0XkYVOKTaN0XDC3A5RVipF6vT6/dHV+TnfspWxs/R8XFd/9D7nfD6v07nOp/fz835/3h8f8fDwEEVRxNvb29DBu3btmqFDwYObaWi1WqN7xD148EDWrFlTLpTpdDpZtGiReHl5yaRJkzhdoxp4+rNZu3atzJ8/XxRFERsbG8P0xYKCAtmzZ4+0bdtWBg8ebKpSa6wtW7bIF198ITdv3pSRI0eKpaWltGnTxtBRFCmdYjpr1ixRqVRG39Uy/A4SVd6GDRukadOmMnHiRKPv2Y0bNyQnJ0ecnJzkq6++EpHSyy3at28viqJIQECAqUqmSsrIyBBPT0/p2bMnTyQ+BwayV1BaWpq4u7uLm5ub6HQ6KS4ulvPnz4u/v7+cOXNGRIwDGDsUpvf055GTk1NhKBMRo7OEPCtfPQQHB0uTJk1k7dq18vnnn0vfvn2ldu3ahumLBQUFEh0dLa+99prMmDHDxNXWHGvWrBFFUSQ2NlZERO7duyeffPKJKIoie/fuFRExGgGbM2eOKIpi+NyIqGr+arl0kdLR6mbNmsnp06dFpPQG0aNGjZKUlBR28P/DMjMzJTQ0VDw9PaV79+68PctzYiB7RV26dEnc3NzEzc1NEhMTjR5jAPvvKwtlDRs2lKlTp5Z7nCOa1cPt27fFwcHBMN1NpPRM8KhRo8TKykoSEhJERCQ/P18SExP5D+xfUraiaUxMjFH73bt3ZfTo0WJtbW1YzKPsu/bkyRNZtWoVT4QQPYeMjAx59913ZcWKFUbteXl58vPPP8vJkyclKytLOnbsKN7e3pKQkCD9+/eXfv36GfosPD7+N/3666/i5eUlU6ZMMRwfeZysOgayV9jTN8YsuyaCqo+cnBxZu3atKIoiy5YtM3U59ByuXr0q1tbWsm/fPkNbSUmJpKWlSevWrcXW1tYwQlOGnY6Xq6IVTZ/uPGRkZIivr6+o1epyoayi5xPR36vMcukajUZ27dolHTp0kLZt24pGo+H0/GoiOzubq83+Q7z77yusbdu2iIyMhJmZGaZNm4bU1FRTl0RVYGNjg+HDh2PPnj0IDAw0dTn0N0SkXFurVq3Qp08fbN68GVlZWQAARVHQrl07dOrUCRYWFggNDTV6DW+Y+fJ8++238Pf3h7+/P86fP48pU6YAAMzNzVFcXAwAaNiwIcLDw+Hj4wMPDw9otdpyN5zljbmJqi43NxcxMTE4evQohg0bhlWrVqFhw4Y4dOgQIiMjkZGRAZ1Oh59++gnR0dHQarVQqVQoLi423Dia/pvq1asHRVEgIvwf9pwUqagXQa8UnU6HdevWYdGiRTyoVWPFxcXsCP5HlZSUGL5bN2/eRF5eHpo0aYL69etj06ZNWLFiBdzd3TF79mxYW1sjPz8fI0eOxOTJk+Hq6lquw08v3rJlyzB9+nTExMTAw8MDa9asQUhICD788ENEREQAMP6O3b9/H2PGjMHjx49x+PBhU5ZO9Eo4cuQIhg4dCltbW9SpUwdLly5Fly5dYGtri+zsbLi6uuK9997DvHnzDK95+thK9CpjIKtheHAjerFExBCoQkJCEBcXB51OBxcXFzg6OuKrr77Cl19+iZiYGBQVFUGj0eDEiRPQ6/VISUmBmZkZv5f/goSEBKSnp+ODDz4AAOTk5GDHjh2YO3fuM0NZTk4O6tSpw8+G6AXJzMzEw4cP0apVK6P27OxsDBkyBL6+vggICDA6rhLVBAxkRETPKSsrCw0aNAAALFiwAOHh4di2bRs6duyIyZMnIzY2FidPnoSDgwMOHjyIgwcP4saNG7Czs8OKFSugUqmg1+s5xeNf9HRHLzc3F9u3by8XyoqKiqBSqQyvYWAmenkyMzMxduxY3L9/H8nJyTweUo3E+U9ERM8hMTERPj4+0Ol0sLW1xeHDh7Fy5Ur0798fcXFxOHDgACIiIuDg4AAA8PDwgIeHh1Fnn9NQ/31Pn3W3sbExjJiFhISgVq1aCA8PNwpjABjGiF6C+/fvY926dUhKSkJGRoYhjPEkFdVE/C9DRPQc7Ozs0KBBA8ybNw+5ubkoLCyEg4MD9u3bBx8fHyxevBj+/v4oLCzEunXrcPz4cQAw6uwzjJleWSibP38+IiIiDKNkRPRy3bp1C8nJybC3t8fx48cNC3gwjFFNxN4AEdFzaN26NUaMGIG9e/ciMTERer0eISEhSEpKQlhYGD766CMApYt87Ny5EwEBASaumJ6lbEXTRo0awcvLy9TlENUIjo6O2Lx5M+rWrQtFUaDX63mSimosXkNGRFRJaWlphimIAPDgwQO88847GDhwIPz8/DBgwAD06dMH+/fvh4ggLy8PI0aMwKNHjxAXF8czv9UEp5IS/bu4iAfVdAxkRESVsG/fPgwZMgQeHh5YuXIl6tWrh7p16yI+Ph7u7u5YtGgRXn/9dfj6+mLAgAEAgMLCQmRnZ+OXX37hAh5ERERUIQYyIqJKSE1NhaenJ3JycqDRaODs7IxBgwbB0dEREydOhE6nw6pVq5CXl4dt27ZBRNC6dWtMmjTJcONhjroQERHR/2IgIyJ6hrLlzouLi6HX6xEREYHc3FzUrVsXN2/exJEjRxAWFgYLCwsEBARg0qRJCAoKKrdsOkfGiIiI6Fm4yiIR0TPcvn0bQOlqiJaWlnB0dERSUhK6d++O5cuXY+rUqRg/fjzOnj0LOzs7fP3110hLSyu3bDrDGBERET0LAxkRUQVSUlLQokULzJw5ExcvXgQAuLm5QaPRYMSIEUhPT0dAQACio6Nx69YtWFlZITs7G6tXrzZx5URERFSdcMoiEVEFHjx4gM2bN2PevHl46623MHDgQMyZMwcAMGbMGKjVaixcuBB16tRBVlYWrly5gu+++w7h4eG8VoyIiIgqjYGMiOgvXLp0CaGhoUhISICdnR2WL1+OM2fO4NixY/joo4/g5ORUbslmLuBBRERElcVARkT0N3JycnDmzBkEBwcjMzMTgwYNQmxsLPr374+VK1eaujwiIiKqxhjIiIiqYO7cuTh37hwSExORk5OD3bt3w9vb29RlERERUTXFQEZEVAllS+ADwMmTJ7F//37ExcXh2LFjnJ5IREREz42BjIiokv73WrEyvGaMiIiInhcDGRHRP/CskEZERERUGbwPGRHRP8AwRkRERP8EAxkREREREZGJMJARERERERGZCAMZERERERGRiTCQERERERERmQgDGRERERERkYkwkBEREREREZkIAxkREdELkpycjE6dOkGlUsHb29vU5Rhp2bIlli1bZuoyiIjofzCQERFRtTBmzBgoigJFUaBSqfDGG29gwIAB2LBhA0pKSkxdHgBg+vTpcHR0xLVr17Bx48ZyjwcHB8PBwcGoLS0tDYqiYMyYMUbtGzduhKWlJR49evQSKyYiIlNjICMiomrD3d0d6enpuH79Og4ePAhXV1dMmTIFXl5eKC4uNnV5uHLlCvr27YtmzZqhXr165R53dXXFxYsXcffuXUNbfHw8mjdvDq1Wa/Tc+Ph4ODk5wcrK6iVXTUREpsRARkRE1YalpSXs7OzQtGlTdOvWDXPmzEF0dDQOHjxoNCK1dOlSdOrUCWq1Gs2bN8ekSZPw8OFDAEB+fj5sbGywc+dOo23v3bsXarUaeXl5Fe67sLAQkydPRqNGjVC7dm307t0bKSkpAIDr169DURT8+eefGDduHBRFqXCErHfv3lCpVEbhS6vV4uOPP0ZWVhauX79u1O7q6mrY94wZM9C0aVOo1Wr07NmzXIBLSkqCRqOBlZUVmjdvjsmTJyM/P/+Zf8t169ahXr16OHLkyDOfQ0RELx8DGRERVWt9+/ZFly5dsHv3bkNbrVq1EBkZifPnz2PTpk04evQogoKCAABqtRoffPABoqKijLYTFRWFYcOGoU6dOhXuJygoCLt27cKmTZtw+vRp2NvbY+DAgcjKykLz5s2Rnp4OGxsbLFu2DOnp6Xj//ffLbUOtVqN79+6Ij483tGm1WvTr1w/Ozs6G9qtXr+LmzZuGQBYYGIgTJ05g+/btSE1NxfDhw+Hu7o7Lly8DKB2Zc3d3x9ChQ5GamoodO3YgKSkJgYGBFb6XsLAwBAcH48cff0S/fv0q+6cmIqKXQYiIiKqB0aNHy5AhQyp87P3335cOHTo887U//PCD2NraGn7/+eefxczMTO7cuSMiIvfu3RNzc3PRarUVvv7hw4eiUqlk69athrYnT55IkyZNJCwszNBWt25diYqK+sv3MXfuXGnXrp2IiJw/f15sbGykuLhYFixYIH5+fiIisn79eqldu7Y8fvxYbty4IWZmZnL79m2j7fTr109mz54tIiL+/v4SEBBg9PixY8ekVq1a8ujRIxERadGihYSHh0tQUJA0btxYzp0795d1EhHRv8Pc1IGQiIjonxIRKIpi+P3w4cMIDQ1FWloacnNzUVxcjMePH6OgoADW1tbo0aMH3n77bWzatAnBwcHYsmULWrRogT59+lS4/StXrqCoqAjOzs6GNpVKhR49ekCn01Wp1nfffRfz589Heno6tFotevfuDTMzM7i4uGD16tUASkfNevXqBUtLS/z222/Q6/Vo166d0XYKCwtha2sLADh79ixSU1OxdetWo79JSUkJrl27hg4dOgAAlixZgvz8fPzyyy9o3bp1leomIqKXg1MWiYio2tPpdGjVqhWA0uu5vLy80LlzZ+zatQunTp3CN998AwB48uSJ4TXjx483XOcVFRWFsWPHGoW6l8XZ2RkWFhaIj49HfHw8XFxcAADdu3fH/fv3cfXqVWi1WvTt2xcA8PDhQ5iZmeHUqVM4c+aM4Uen0yEiIsLwnAkTJhg9fvbsWVy+fBlt2rQx7Fuj0UCv1+P7779/6e+TiIgqhyNkRERUrR09ehS//fYbpk2bBgA4deoUSkpKsGTJEtSqVXresaIA4uvri6CgIERGRuLChQsYPXr0M/fRpk0bWFhYIDk5GS1atAAAFBUVISUlBVOnTq1SvVZWVoZFORISEjBz5kwApSNuTk5OWL9+Pf744w/D9WNdu3aFXq9HRkYGNBpNhdvs1q0bLly4AHt7+7/cd48ePRAYGAh3d3eYm5tjxowZVaqdiIhePAYyIiKqNgoLC3H37l3o9Xrcu3cPsbGxCA0NhZeXF/z8/AAA9vb2KCoqwvLlyzF48GAkJycbpgI+rX79+vDx8cHMmTPh5uaGZs2aPXO/arUaEydOxMyZM9GgQQO8+eabCAsLQ0FBAfz9/av8PlxdXREeHg6gNEyVcXFxweLFiw2LfwBAu3btMHLkSPj5+WHJkiXo2rUrMjMzceTIEXTu3Bmenp6YNWsWnJycEBgYiPHjx0OtVuPChQuIi4vDihUrjPbdq1cvHDhwAB4eHjA3N69yoCQioheLUxaJiKjaiI2NRePGjdGyZUu4u7sjPj4ekZGRiI6OhpmZGQCgS5cuWLp0Kb7++mt07NgRW7duRWhoaIXb8/f3x5MnTzBu3Li/3ffChQsxdOhQjBo1Ct26dcPvv/+OQ4cOoX79+lV+H66ursjLy4OzszPMzf//3KiLiwvy8vIMy+OXiYqKgp+fHz799FO0b98e3t7eSElJwZtvvgkA6Ny5MxISEnDp0iVoNBp07doVn332GZo0aVLh/nv37o2YmBiEhIRg+fLlVa6fiIheHEVExNRFEBERmcLmzZsxbdo03LlzBxYWFqYuh4iIaiBOWSQiohqnoKAA6enpWLhwISZMmMAwRkREJsMpi0REVOOEhYXBwcEBdnZ2mD17tqnLISKiGoxTFomIiIiIiEyEI2REREREREQmwkBGRERERERkIgxkREREREREJsJARkREREREZCIMZERERERERCbCQEZERERERGQiDGREREREREQmwkBGRERERERkIgxkREREREREJvJ/uug9FuUYmuIAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = merged_data\n",
    "# Assuming 'df' is your DataFrame containing the bike rentals data\n",
    "df['started_at'] = pd.to_datetime(df['started_at'])\n",
    "df['day_of_week'] = df['started_at'].dt.dayofweek  # Monday=0, Sunday=6\n",
    "df['hour'] = df['started_at'].dt.hour\n",
    "\n",
    "# Aggregate data by day of week to see weekly demand pattern\n",
    "weekly_demand = df.groupby('day_of_week').size()\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "weekly_demand.plot(kind='bar')\n",
    "plt.title('Bike Rentals Demand by Day of Week')\n",
    "plt.xlabel('Day of Week')\n",
    "plt.ylabel('Number of Rentals')\n",
    "plt.xticks(ticks=range(7), labels=['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday'], rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# **Identifikujte příčiny výkyvů poptávky**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# Assuming your DataFrame is named df\n",
    "df['started_at'] = pd.to_datetime(df['started_at'])\n",
    "df['date'] = df['started_at'].dt.date\n",
    "df['hour'] = df['started_at'].dt.hour\n",
    "df['day_of_week'] = df['started_at'].dt.dayofweek  # Monday=0, Sunday=6\n",
    "\n",
    "# Clean temperature data\n",
    "df['temp'] = pd.to_numeric(df['temp'], errors='coerce')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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s3r270PGqu379OipWrIiKFSvC29sbCxYsQJcuXVS6oP744w8oFAp88MEHys9WbGwsnJycUK1aNRw6dEhlmxYWFir98VKpFI0aNcLdu3cLFdPLn8fU1FTExsbC398fQog8MxBe9nysx59//qn1bJGXXzMxMRGxsbEICAjA3bt3kZiYqFLXx8cHzZs3Vz6vWLEiatSoobJ/u3btwttvv41GjRqp1OvXr1+h4vH394eBgYFyLMPx48dhbGyMhg0bwsLCAr6+vsrm/uf/Pm/a/+2332BtbY133nlH5f3y8/ODhYWFyvulr3M/MDBQZZzP8+Pz/Jjo8h2l/p1QkKSkpEJ/Dx84cABZWVkYO3asyjixYcOGwcrKKs/3cGE+y7t27YKzszN69uypLDMzM8Pw4cMLFVNhafsbUpjPqY2NDa5evYpbt27pNdY3jVYjU6ysrADknnCF8eDBAxgYGMDLy0ul3MnJCTY2Nnjw4IFK+csjqdWpL3v+xg8aNKjAdRITE2Fra5vvsqtXr+KLL77AwYMH8/xYq39xFsbzfalRo0aeZTVr1sTevXvzDICqUqWKSr3nsT579kx5rF+lY8eOsLS0xJYtW3DhwgU0bNgQXl5e+c6pVygUWLZsGVasWIF79+6p9PFWqFChUK8HAK6urloNjly4cCH+/PNPXLhwAZs3b4aDg8Mr13nw4AFcXFzyfEHWrFlTuVxX7u7uyhHgd+7cwZw5c/D06VOVAbC3bt2CEALVqlXLdxvqg8AqVaqUp6/W1tYWly5dKlRMERERmDZtGnbs2JGnj17T57F379747rvvMHToUEyZMgVt2rRB9+7d0bNnz1cOKD5+/DimT5+OEydO5Blrk5iYCGtra+Vz9c8qkLt/L8f64MEDNG7cOE+9/M6J/NjY2KBWrVoqCcJbb72l/LH39/dXWfb8Rw3Ifb8SExML/Gy9PJZFX+e+pvP3eUyAdt9Rmr4DX2ZlZaXV9zCQ932QSqXw8PDIcy4V5rP84MEDeHl55alX2Pe6sLT9DSnM53TmzJno2rUrqlevjtq1a6NDhw4YMGAAfH199Rp7ead18uDi4oIrV65o9SKFvehHfjMrClr2PGNfsGBBgdPeLCws8i1PSEhAQEAArKysMHPmTHh6esLExATnzp3D5MmTi3y+/3MFjeoX/w0ILAyZTIbu3btj/fr1uHv3rnLgUX7mzp2LL7/8Eh999BFmzZoFOzs7GBgYYOzYsVrts6b3KT/nz59XfnlfvnwZffr00Wp9fTM3N0fbtm2Vz5s2bYr69etj6tSp+PrrrwHkfr4kEgl2796d7/uk/tl6nfdSLpfjnXfeQXx8PCZPngxvb2+Ym5vj8ePHGDx48Ctb0I4cOYJDhw5h586d2LNnD7Zs2YLWrVtj3759BcZ1584dtGnTBt7e3li8eDEqV64MqVSKXbt2YcmSJXleUx+f1cJo1qwZVq1ahYSEBBw/fhz+/v7KZf7+/li3bh2ys7Nx7Ngx+Pn5KRM+hUIBBwcHbNq0Kd/tPh+kp89z/1XHRJfvqMKeW97e3rhw4QKysrL0PsupuN5rbRT2N6Qwsbdo0QJ37tzBn3/+iX379uG7777DkiVLsGrVKgwdOlQv8b4JtJ4T895772HNmjU4ceIEmjRporGum5sbFAoFbt26pfyLEci9sElCQgLc3Ny0j/g/np6eAHITmpd/CAojPDwccXFx+OOPP9CiRQtlufpFaIDCf2if78uNGzfyLLt+/Trs7e0LnHb1uvr27Yt169bBwMAAH374YYH1fv/9d7Rq1Qrff/+9SnlCQgLs7e2Vz/V5hbfU1FQEBgbCx8cH/v7+mD9/Pt5//33lzIOCuLm54cCBA0hOTlZpfXjerPw6nx11vr6+6N+/P1avXo0JEyagSpUq8PT0hBACVatWRfXq1fXyOgUd18uXL+PmzZtYv349Bg4cqCwv7OhvAwMDtGnTBm3atMHixYsxd+5cfP755zh06FCB58b//vc/ZGZmYseOHSp/ral3x2jDzc0t36bg/M6JgjRr1gwrV67EgQMHcP78eUycOFG5zN/fH+np6di5cyfu3r2LHj16KJd5enriwIEDaNq0qcYf4KI49wvyOt9Rr9K5c2ecOHECW7dufWUy/vJ3k4eHh7I8KysL9+7d0yk2Nzc3XLlyBUIIleNUmPdam+NaVL8hdnZ2CAwMRGBgIFJSUtCiRQvMmDGDyYMWtJ6qOWnSJJibm2Po0KGIjo7Os/zOnTtYtmwZgNwmdQB5rtK2ePFiAECnTp20fXklPz8/eHp6YuHChUhJScmz/OnTpwWu+zw7fTkbzcrKwooVK/LUNTc3L1RTprOzM+rVq4f169erTH+6cuUK9u3bpzwWRaFVq1aYNWsWli9fDicnpwLrGRoa5vnr4bfffsPjx49Vyp4nOfq4Qt3kyZMRERGB9evXY/HixXB3d8egQYPyndL1so4dO0Iul2P58uUq5UuWLIFEIsG777772rG9bNKkScjOzlZ+Nrt37w5DQ0OEhITkOWZCCMTFxWn9GgUd1/w+j0II5XmkSXx8fJ6y53/lajrG+b1mYmIifvjhh1e+ZkE6duyIf/75B6dOnVKWPX36tMDWgPw8H8OwePFiZGdnq7Q8uLu7w9nZWTlt8OWpjB988AHkcjlmzZqVZ5s5OTnKY14U535BXuc76lU++eQTODs7Y/z48bh582ae5TExMZg9ezYAoG3btpBKpfj6669V9vv7779HYmKiTt/DHTt2xJMnT1Qu0Z2WllaoiwOamZkBKNz3S1H8hqifuxYWFvDy8nrldxKp0rrlwdPTE5s3b0bv3r1Rs2ZNlStM/v333/jtt98wePBgAEDdunUxaNAgrFmzRtlceOrUKaxfvx7dunVDq1atdA7cwMAA3333Hd59913UqlULgYGBcHV1xePHj3Ho0CFYWVnhf//7X77r+vv7w9bWFoMGDcLo0aMhkUiwcePGfJvl/Pz8sGXLFgQFBSkHbnXu3Dnf7S5YsADvvvsumjRpgiFDhiA9PR3ffPMNrK2tNXYnvC4DA4M8c7rz895772HmzJkIDAyEv78/Ll++jE2bNqn8NQLkvsc2NjZYtWoVLC0tYW5ujsaNGxe6P/a5gwcPYsWKFZg+fTrq168PIPfaAi1btsSXX36Z79zx5zp37oxWrVrh888/x/3791G3bl3s27cPf/75J8aOHav8q05ffHx80LFjR3z33Xf48ssv4enpidmzZyM4OBj3799Ht27dYGlpiXv37mHbtm0YPnw4JkyYoNVrFHRcvb294enpiQkTJuDx48ewsrLC1q1b84x9yM/MmTNx5MgRdOrUCW5uboiJicGKFStQqVIljdcJaNeuHaRSKTp37oyPP/4YKSkpWLt2LRwcHBAZGanVfj03adIkbNy4ER06dMCYMWNgbm6ONWvWwM3NrdBjP6pUqYLKlSvjxIkTcHd3h4uLi8pyf39/bN26FRKJBE2bNlWWBwQE4OOPP0ZoaCguXLiAdu3awdjYGLdu3cJvv/2GZcuWoWfPnkV27ufndb6jXsXW1hbbtm1Dx44dUa9ePZUrTJ47dw4///yzsmW4YsWKCA4ORkhICDp06IAuXbrgxo0bWLFiBRo2bKgyOLKwhg0bhuXLl2PgwIE4e/YsnJ2dsXHjRmVioImpqSl8fHywZcsWVK9eHXZ2dqhdu7byeh0vK4rfEB8fH7Rs2RJ+fn6ws7PDmTNn8Pvvv2PkyJFab+uNpus0jZs3b4phw4YJd3d3IZVKhaWlpWjatKn45ptvVKY7ZWdni5CQEFG1alVhbGwsKleuLIKDg1XqCJE7zSa/6TPPp0X99ttv+cZx/vx50b17d1GhQgUhk8mEm5ub+OCDD0RYWJiyTn5TNY8fPy7efvttYWpqKlxcXMSkSZOU0wpfnmaUkpIi+vbtK2xsbAQA5ZSj/KZqCiHEgQMHRNOmTYWpqamwsrISnTt3Fv/++69KnefTkdSn1+UXZ35enqpZkIKmao4fP144OzsLU1NT0bRpU3HixIl8p1j++eefwsfHRxgZGansp6ZpkS9vJykpSbi5uYn69euL7OxslXrjxo0TBgYG4sSJExr3ITk5WYwbN064uLgIY2NjUa1aNbFgwQKVaW+viim/GAuqGx4enmcK2datW0WzZs2Eubm5MDc3F97e3mLEiBHixo0br9ym+hQ1IQo+rv/++69o27atsLCwEPb29mLYsGHi4sWLeT5j6lPZwsLCRNeuXYWLi4uQSqXCxcVF9OnTR9y8efOVx2LHjh3C19dXmJiYCHd3d/HVV1+JdevW5fkMFnRu5ve5uXTpkggICBAmJibC1dVVzJo1S3z//feF+lw/16dPHwFA9O3bN8+yxYsXK6dJ5mfNmjXCz89PmJqaCktLS1GnTh0xadIk8eTJE2Wd1z33C/pOKug7oTDfUQV9J7zKkydPxLhx45TXXDAzMxN+fn5izpw5IjExUaXu8uXLhbe3tzA2NhaOjo7i008/VbleiRDafZYfPHggunTpIszMzIS9vb0YM2aMcmqspqmaQgjx999/Cz8/PyGVSlXOufyu8/C6vyHqn9PZs2eLRo0aCRsbG2Fqaiq8vb3FnDlzVK53Qa8mEaIER8EQERFRmfNG3JKbiIiI9IfJAxEREWmFyQMRERFphckDERFRKXHkyBF07twZLi4ukEgk2L59+yvXCQ8PR/369SGTyeDl5ZXnbs9FgckDERFRKZGamoq6devi22+/LVT9e/fuoVOnTmjVqhUuXLiAsWPHYujQodi7d2+RxsnZFkRERKWQRCLBtm3b0K1btwLrTJ48GTt37lS5bcSHH36IhIQE7Nmzp8hiY8sDERFREcrMzERSUpLKQ19XtDxx4kSeS4y3b98eJ06c0Mv2C6L1FSaLyk5j/d6NjXTX8shXJR0C/af/plolHQL9Z1Ofwl0lk4qHWdMer670GvT5m3T68z4ICQlRKZs+fbperjwcFRUFR0dHlTJHR0ckJSUhPT1d6xsZFlapSR6IiIhKC4mx/m4QGBwcjKCgIJUymUymt+2XBCYPREREagyM9Jc8yGSyIksWnJyc8tykMjo6GlZWVkXW6gBwzAMREVGZ1aRJE4SFhamU7d+/X3ljtKLClgciIiI1EuOS+ds6JSUFt2/fVj6/d+8eLly4ADs7O1SpUgXBwcF4/PgxNmzYACD39uzLly/HpEmT8NFHH+HgwYP49ddfsXPnziKNk8kDERGRGn12W2jjzJkzKrcafz5WYtCgQfjxxx8RGRmJiIgI5fKqVati586dGDduHJYtW4ZKlSrhu+++Q/v27Ys0Tp2Sh5kzZ2LChAl57t2enp6OBQsWYNq0aXoJjoiI6E3SsmVLaLr8Un5Xj2zZsiXOnz9fhFHlpVO7TEhICFJSUvKUp6Wl5ZmOQkREVNZIjCV6e5RHOrU8CCEgkeQ9IBcvXoSdnd1rB0VERFSSSqrboqzQKnmwtbWFRCKBRCJB9erVVRIIuVyOlJQUfPLJJ3oPkoiIiEoPrZKHpUuXQgiBjz76CCEhIbC2tlYuk0qlcHd3L/LpIUREREWtvHY36ItWycOgQYMA5I7u9Pf3h7GxcZEERUREVJLYbaGZTmMeAgICoFAocPPmTcTExEChUKgsb9GihV6CIyIiotJHp+Thn3/+Qd++ffHgwYM8U0okEgnkcrlegiMiIioJEkO2PGiiU/LwySefoEGDBti5cyecnZ3znXlBRERUVhkwedBIp+Th1q1b+P333+Hl5aXveIiIiEqcxIDJgyY6XSSqcePGKtfeJiIiojeHTi0Po0aNwvjx4xEVFYU6derkmXXh6+url+CIiIhKgsSQN53WRKfkoUePHgCAjz76SFkmkUiUV57kgEkiIirLOOZBM52Sh3v37uk7DiIiIiojdEoe3Nzc9B0HERFRqcEBk5rplDxs2LBB4/KBAwfqFAwREVFpwG4LzXRKHsaMGaPyPDs7G2lpaZBKpTAzM2PyQEREVI7plDw8e/YsT9mtW7fw6aefYuLEia8dFBERUUniFSY10yl5yE+1atUwb9489O/fH9evX9fXZomIiIqdxIBTNTXR69ExMjLCkydP9LlJIiIiKmV0annYsWOHynMhBCIjI7F8+XI0bdpUL4ERERGVFM620Eyn5KFbt24qzyUSCSpWrIjWrVtj0aJF+oiLiIioxHC2hWY6JQ8KhULfcRAREZUabHnQ7LXHPAghIITQRyxERERUBuicPGzYsAF16tSBqakpTE1N4evri40bN+ozNiIiohIhMTDQ26M80qnbYvHixfjyyy8xcuRI5QDJY8eO4ZNPPkFsbCzGjRun1yCJiIiKE7stNNMpefjmm2+wcuVKlStJdunSBbVq1cKMGTOYPBAREZVjOiUPkZGR8Pf3z1Pu7++PyMjI1w6KiIioJHG2hWY6dcZ4eXnh119/zVO+ZcsWVKtW7bWDIiIiKkkSA4neHuWRTi0PISEh6N27N44cOaIc83D8+HGEhYXlm1QQERFR+aFT8tCjRw+cPHkSS5Yswfbt2wEANWvWxKlTp/DWW2/pMz4iIqJiV15nSeiLzjfG8vPzw08//aTPWIiIiEqF8trdoC86pVa7du3C3r1785Tv3bsXu3fvfu2giIiIqPTSKXmYMmUK5HJ5nnIhBKZMmfLaQREREZUkDpjUTKdui1u3bsHHxydPube3N27fvv3aQREREZWk8vqjry86JQ/W1ta4e/cu3N3dVcpv374Nc3NzfcRVptg1awCP8UNgXb82TFwccKbHZ4jeEVbSYZUrWw78jQ27jyAuMRnVqzhjUv+uqO1ROd+6O46ewYzvf1MpkxoZ4Z/v5iifh525gq2H/sG1+4+RmJqGn0PGoIabS5HuQ3nTp5Md2vpbw9zUANfvZmD1lhhEPs0usL6Ppwm6tbWFZxUT2FkbIXTNE5y6lKpSx9rSEAO72qNeTTOYmxrg6u10fPfbU43bfdNtCTuB9XuOIi4xBdUrO2Fyv84FnxvHzmL6uq0qZVIjI5xcMxMAkJ0jx4pt+3Hs0g08ehoPC1MTNPbxwuie7eFga1Xk+1KacMCkZjolD127dsXYsWOxbds2eHp6AshNHMaPH48uXbroNcCywNDcDEmXbuDhj1vR4PdvSzqccmfvyYtY/MtfmDrofdTxqIJN+45hxMLvsW3eBNhZWeS7joWpDH+ETlQ+l6j9EZGemYV61d3xTiNfzPphK0g777e1RacAG3y9MRrRcdno+14FTBvhitGzHyA7J/8b5ZnIDHD/cRbCTiRhyvD8E7Xg4c7IkQOhq58gLUOBLq1tMWNU7nYzs3gDPnV7T13Coi278PmAbqjtUQmb9/+Nzxb/gO1zgzSeG9vmBimfv3xqZGRl49qDJxjWuRWqV3ZGUlo6Fmz+C2O/3ojN00cU8d5QWaJTajV//nyYm5vD29sbVatWRdWqVVGzZk1UqFABCxcu1HeMpd7TvUdwc/pSRP95oKRDKZc27T2K9wMaoWvzhvBwdcTng96HidQYfx45rWEtCextLJWPCtaWKkvfa1ofw7u2RWMfr6INvpx6r5UNftsbj1OXU/HgSRaWbYiGnbUhGtctuOXx3L9p2PxXHE6qtTY85+JgjBpVTbH6lxjcjsjEk5hsrN4SA5mxBM39LPNd5033095j6N6iIbo294OnqyM+H9gVJlIpth89q2EtCeytLZWPl88NSzMTrJrwEdo18oW7c0X4elbBlP5dcO3BY0TGJRT5/pQmBoYSvT3KI527Lf7++2/s378fFy9eVN5Vs0WLFvqOj95w2Tk5uHb/MQI7tVKWGRgYoHEtL1y6E1HgeumZWeg4PhRCCHi7uWJkz/bwdHUqjpDLPccKRrCzNsLF62nKsrQMBW7dz0ANdxMcO5ui03aNjHK/ZF9uuRAi93lNT1McOJH0eoGXM9k5Obj24Ak+6tRSWWZgYIDGPp6vPDfenTgfQiHg7eaCUT3awdPVscD6yWkZkEgksDQz0Wf4pR7HPGim83UeJBIJ2rVrh3bt2hVYp06dOti1axcqV1btf8vMzERmZqZKWbZQwFjCPiZSlZCcBrlCATtr1SZYOytL3I98mu86bs4VMX1IT1Sr5IyU9Axs2H0EgbNX4Lc5QXC0symGqMs3G6vcr43EZNUZVwnJcuUyXTyOykJMfDb6d6mAlT/HIDNLgc6tbGFvawxb66zXirk8evb83FDrnqhgZVHwueFUEdMDu6N6ZSckp2dg455jGDx3FX6fNRaOdtZ56mdmZ+Pr3/egQ2NfWJi+WckDaab7mV4I9+/fR3Z23oFOoaGhCAkJUSnrI7FDP0P7ogyH3hB1vdxQ18tN+dzXyw09pi7C1kMn8VmP9iUYWdnUooElPunjoHw+Z+WTInkduQL4am0kRvZzxE8LPCGXC1y8kYazV1PBvwH1o65XFdT1qvLiuacbenyxBL+Hn8KI7u+o1M3OkWPSyp8hBDB1QNfiDrXEccCkZkWaPBQkODgYQUFBKmUH7fxKIhQq5WwszWBoYID4RNWm8Pik5DzjGApibGQI7youeBgTVxQhlnunLqfg5v0M5XPj/7oXrC0N8SzpReuDjaUh7j3KzLO+Nu4+zETQvAiYmRjAyEiCpBQ5vppQGXciMl698hvG9vm5kaR6bsQlpWh1btTI59zIzpFj8sqfERmbgDWThr6RrQ7sttCsRFIrmUwGKysrlQe7LCg/xkZGqOnuilP/vrh+iEKhwKl/b8PXs4qGNV+QKxS4/SgK9jYcdKeLjEyBqNhs5eNhVBbiE3PgW8NMWcfUxADV3E1w475+fuTTMhRISpHDuaIxPKvIChxk+SYzNjJCTTcXnLymdm5cu/Na58bzxCEiJharJnwEGwszDVugN1WJtDyUN4bmZjB/qSnQrGolWNX1RlZ8IjIeRpZgZOVDv/bNMX3tr/CpWgm1PCph875jSM/MRpfmDQAAX67ZAgdbK4zq9S4AYM2fB1DHswoqO1RAcloGNuw+jMi4Z3i/RSPlNhNT0hAVl4CnCbmD8O5H5fYRV7C2ZJJRCH8dSkCvDnaIfJqdO1WzUwXEJ8px8uKLH/mQUa7452IKdh9JBACYSCVwqmisXO5YwRjurlKkpCkQ+ywHAOD/lgUSU+SIjc+Gm4sMQ3pWxKlLqSqDM+mF/u2bYdp3v8PHvRJqV62EzfuPIz0zC12b1QcAfLH2NzjYWmF0z9zuutU7wuDr8d+5kZ6O9buPIjIuAe//dy5l58gxccVmXH/wBMvGDIRCCMQmJgMArM1NYWz05vxksOVBszfnk1CErP1qo0nYRuVzn4VTAQAPN/yBS0OCSyqscqN947p4lpyKldv2IS4xGTWquGD5+I+UTbNRcQkweOlCDkmp6Zj1w1bEJSbDyswUNd0r4YcvPoPHSyPKD5//V+VCUsErNwMAhndti0/eV+37pby2HXgGE5kEn/ZxgLmpAa7dycCsFY9VZko42RvDysJQ+dzTzQSzx1RSPv+oR0UAwMF/kvDNT9EAAFsrQwR2t4e1pRGeJeUg/GQSftsTX0x7Vfa0b+Sbe25sP5B7blR2xrfjAl+cG/EJMHjpRzA5NQMz12976dxwxY9TP1HOtniakITDF64BAD6c8Y3Ka62dNBQNvD2Kac9KHsc8aCYRQhTZlVcsLS1x8eJFeHi8+gO307hGUYVBWmp55KuSDoH+039TrZIOgf6zqc+lkg6BXmLWtEeRbj/ik+5621aVVX/obVulRZG2PKxevRqOjgXPHyYiIiqN2G2hWaGTh6+//rrQGx09ejQAoG/fvtpHREREVMLYbaFZoZOHJUuWFKqeRCJRJg9ERERlkvoNcYrZt99+iwULFiAqKgp169bFN998g0aNGhVYf+nSpVi5ciUiIiJgb2+Pnj17IjQ0FCYmRTPNttDJw71794okACIiInphy5YtCAoKwqpVq9C4cWMsXboU7du3x40bN+Dg4JCn/ubNmzFlyhSsW7cO/v7+uHnzJgYPHgyJRILFixcXSYxslyEiIlIjMZDo7ZGZmYmkpCSVh/otGl62ePFiDBs2DIGBgfDx8cGqVatgZmaGdevW5Vv/77//RtOmTdG3b1+4u7ujXbt26NOnD06dOlVUh0f3AZOPHj3Cjh07EBERgaws1evOF1WmQ0REVBz0OeYhv1syTJ8+HTNmzMhTNysrC2fPnkVw8Itp/gYGBmjbti1OnDiR7/b9/f3x008/4dSpU2jUqBHu3r2LXbt2YcCAAXrbB3U6JQ9hYWHo0qULPDw8cP36ddSuXRv379+HEAL169fXd4xERERlVn63ZJDJZPnWjY2NhVwuzzNT0dHREdevX893nb59+yI2NhbNmjWDEAI5OTn45JNPMHXqVP3sQD50Sq2Cg4MxYcIEXL58GSYmJti6dSsePnyIgIAA9OrVS98xEhERFSt9dlvkd0uGgpIHXYSHh2Pu3LlYsWIFzp07hz/++AM7d+7ErFmz9PYa6nRqebh27Rp+/vnn3A0YGSE9PR0WFhaYOXMmunbtik8//VSvQRIRERWnkpqqaW9vD0NDQ0RHR6uUR0dHw8nJKd91vvzySwwYMABDhw4FANSpUwepqakYPnw4Pv/8cxgUwb7otEVzc3PlOAdnZ2fcuXNHuSw2NlY/kREREb1hpFIp/Pz8EBYWpixTKBQICwtDkyZN8l0nLS0tT4JgaJh7afiiuoi0Ti0Pb7/9No4dO4aaNWuiY8eOGD9+PC5fvow//vgDb7/9tr5jJCIiKlYleYXJoKAgDBo0CA0aNECjRo2wdOlSpKamIjAwEAAwcOBAuLq6IjQ0FADQuXNnLF68GG+99RYaN26M27dv48svv0Tnzp2VSYS+6ZQ8LF68GCkpufeQDwkJQUpKCrZs2YJq1apxpgUREZV5JZk89O7dG0+fPsW0adMQFRWFevXqYc+ePcpBlBERESotDV988QUkEgm++OILPH78GBUrVkTnzp0xZ86cIouxSG+MpQ3eGKv04I2xSg/eGKv04I2xSpeivjFWTPBAvW3LIXSD3rZVWug05sHDwwNxcXF5yhMSEgp1B00iIqJSzcBAf49ySKdui/v370Mul+cpz8zMxOPHj187KCIiopIkKeF7W5R2WiUPO3bsUP5/7969sLa2Vj6Xy+UICwuDu7u73oIjIiIqCbyrpmZaJQ/dunUDkJuRDRo0SGWZsbEx3N3dsWjRIr0FR0RERKWPVsmDQqEAAFStWhWnT5+Gvb19kQRFRERUkkpytkVZoNOYB96em4iIyjV2W2ik8101w8LCEBYWhpiYGGWLxHMF3TaUiIiIyj6dkoeQkBDMnDkTDRo0gLOzM0elEhFRucJuC810Sh5WrVqFH3/8sUjvFU5ERFRSJBJ2W2ii09HJysqCv7+/vmMhIiKiMkCn5GHo0KHYvHmzvmMhIiIqHQwk+nuUQzp1W2RkZGDNmjU4cOAAfH19YWxsrLKcN8ciIqKyjBeJ0kyn5OHSpUuoV68eAODKlSsqyzh4koiIyjoOmNRMp+Th0KFD+o6DiIiIyojXape5ffs29u7di/T0dABAKbm7NxER0euRGOjvUQ7ptFdxcXFo06YNqlevjo4dOyIyMhIAMGTIEIwfP16vARIRERU3iYFEb4/ySKfkYdy4cTA2NkZERATMzMyU5b1798aePXv0FhwRERGVPjqNedi3bx/27t2LSpUqqZRXq1YNDx480EtgREREJYazLTTSKXlITU1VaXF4Lj4+HjKZ7LWDIiIiKkmcOaiZTqlV8+bNsWHDBuVziUQChUKB+fPno1WrVnoLjoiIiEofnVoeFixYgNatW+PMmTPIysrCpEmTcPXqVcTHx+P48eP6jpGIiKh4sdtCI62Th+zsbIwePRr/+9//sH//flhaWiIlJQXdu3fHiBEj4OzsXBRxEhERFZvyOktCX7ROHoyNjXHp0iXY2tri888/L4qYiIiIqBTTqV2mf//++P777/UdCxERUenAi0RppNOYh5ycHKxbtw4HDhyAn58fzM3NVZbzxlhERFSmsdtCI52ShytXrqB+/foAgJs3b6os4/QWIiIq6yTltMVAX3hjLCIiItKKTslDUWh55KuSDoH+E95ickmHQP+xnBJe0iHQf452mVbSIdBL2sf1KNoXYLeFRqUmeSAiIiotJLzOg0Y8OkRERKQVtjwQERGp4+B/jZg8EBERqWO3hUY8OkRERKQVtjwQERGpY7eFRkweiIiI1HC2hWY8OkRERKQVtjwQERGp4+WpNWLyQEREpI5XmNSIyQMREZEa3hhLMx4dIiIi0gpbHoiIiNSx20IjJg9ERETq2G2hEY8OERERaYUtD0REROp4hUmNmDwQERGp4xUmNeLRISIiIq2w5YGIiEgdB0xqxKNDRESkzkCiv4cOvv32W7i7u8PExASNGzfGqVOnNNZPSEjAiBEj4OzsDJlMhurVq2PXrl06vXZhsOWBiIioFNmyZQuCgoKwatUqNG7cGEuXLkX79u1x48YNODg45KmflZWFd955Bw4ODvj999/h6uqKBw8ewMbGpshiZPJARESkTo/dFpmZmcjMzFQpk8lkkMlk+dZfvHgxhg0bhsDAQADAqlWrsHPnTqxbtw5TpkzJU3/dunWIj4/H33//DWNjYwCAu7u73uLPD7stiIiI1EkkenuEhobC2tpa5REaGprvy2ZlZeHs2bNo27atsszAwABt27bFiRMn8l1nx44daNKkCUaMGAFHR0fUrl0bc+fOhVwuL5JDA7DlgYiIKC89TtUMDg5GUFCQSllBrQ6xsbGQy+VwdHRUKXd0dMT169fzXefu3bs4ePAg+vXrh127duH27dv47LPPkJ2djenTp+tnJ9QweSAiIipCmroo9EGhUMDBwQFr1qyBoaEh/Pz88PjxYyxYsIDJAxERUbEpoStM2tvbw9DQENHR0Srl0dHRcHJyyncdZ2dnGBsbw9DQUFlWs2ZNREVFISsrC1KpVO9xcswDERGROomB/h5akEql8PPzQ1hYmLJMoVAgLCwMTZo0yXedpk2b4vbt21AoFMqymzdvwtnZuUgSB4DJAxERUakSFBSEtWvXYv369bh27Ro+/fRTpKamKmdfDBw4EMHBwcr6n376KeLj4zFmzBjcvHkTO3fuxNy5czFixIgii5HdFkREROpK8N4WvXv3xtOnTzFt2jRERUWhXr162LNnj3IQZUREBAxeiq9y5crYu3cvxo0bB19fX7i6umLMmDGYPHlykcXI5IGIiEhdCd9Vc+TIkRg5cmS+y8LDw/OUNWnSBP/8808RR/WCzsmDXC7Htm3bcO3aNQC5gzO6desGIyPmI0REROWZTr/0V69eRZcuXRAVFYUaNWoAAL766itUrFgR//vf/1C7dm29BklERFSseGMsjXQ6OkOHDkWtWrXw6NEjnDt3DufOncPDhw/h6+uL4cOH6ztGIiKi4qXHK0yWRzq1PFy4cAFnzpyBra2tsszW1hZz5sxBw4YN9RYcERERlT46tTxUr149zwUsACAmJgZeXl6vHRQREVGJMjDQ36Mc0qnlITQ0FKNHj8aMGTPw9ttvAwD++ecfzJw5E1999RWSkpKUda2srPQTKRERUTER5bS7QV90Sh7ee+89AMAHH3wAyX8HWAgBAOjcubPyuUQiKdK7ehERERUJDpjUSKfk4dChQ/qOg4iIiMoInZKHgIAAfcdBRERUerDlQSOdr+iUkZGBS5cuISYmRuVmHADQpUuX1w6MiIiopHDMg2Y6JQ979uzBwIEDERsbm2dZeRrnsOXA39iw+wjiEpNRvYozJvXvitoelfOtu+PoGcz4/jeVMqmREf75bo7yediZK9h66B9cu/8Yialp+DlkDGq4uRTpPrxp7Jo1gMf4IbCuXxsmLg440+MzRO8Ie/WKpLXurS3QsoEZzEwMcCsiCz/uSER0fMHnfg03KTo2M4e7izFsrQyxdHM8zl3LLLD+4M5WaN3IHJt2JWLvibSi2IVyofKQPqg6MhBSB3skX72B61PmIvHc5XzrSoyM4DF2GFw+7AKZsyPSbt/HzZDFiD147EUlAwN4TR4B517vQeZgj8yoGDz++U/cXbSqmPaIygKd2mVGjRqFXr16ITIyEgqFQuVRXhKHvScvYvEvf2F4tzbYHDIa1So7Y8TC7xGflFLgOhamMuxb+oXysXPRFJXl6ZlZqFfdHaM/eLeow39jGZqbIenSDVwZHVLSoZRrnZqb4523zfHjjkSErI5FZpbAxEF2MNbw54hMKkFEVDY2/JX4yu371ZTBs7IU8Unl4/ukqDh16wDvWZNwe8EKnGjdC8lXbsDvt9WQ2tvlW7/a56NRaXAvXJsyF8f9u+Dhj1tQb8MyWNbxVtapOmYIKgf2xrXJc3CsSWfcDFmCqqM/QpXh/Yprt0qHErold1mh015FR0cjKChIeYev8mjT3qN4P6ARujZvCA9XR3w+6H2YSI3x55HTGtaSwN7GUvmoYG2psvS9pvUxvGtbNPbhtTCKytO9R3Bz+lJE/3mgpEMp19o3MceOwyk4dz0TD6NzsHprAmwsDVG/pkmB61y6lYmtYSk4q6G1AQBsLQ0woJM1Vv2eALlc6Dv0csXts0F4tPF3PNm8Hak37uDf8SGQp2fAtV/3fOs7f9AZd5esReyBo0h/8AgPf9iC2ANH4T5isLKOTcN6iNl9ELH7jyDj4RNE/28f4g79Dev6dYppr0oJXmFSI52Sh549e+Z7V6/yIjsnB9fuP0Zjn2rKMgMDAzSu5YVLdyIKXC89Mwsdx4fi3aC5GLdsPe48jiqOcImKVUVbQ9hYGuLqnRdJQHqmwN1HWfCqLH2tbUskwMc9bbDrWAoex+S8bqjlmsTYGFZ1fRB3+MSLQiEQd/gf2DSsm+86BlIpFBmqyZs8IwO2jesrnyecvoAKLd6GmacbAMCyVg3YNH4LsQeO6n8nqMzSaczD8uXL0atXLxw9ehR16tSBsbGxyvLRo0drXD8zMxOZmaof4JysbMikxgWsUbwSktMgVyhgZ22hUm5nZYn7kU/zXcfNuSKmD+mJapWckZKegQ27jyBw9gr8NicIjnY2xRA1UfGwtsj9myMxRXWgdGKqAjYWr9dE26m5OeQKYN8/HOPwKtIKNjAwMkJmTJxKeVZMHMyrVc13nbiDx+H+2SA8O3EGafceokLA23Ds1BYSQ0NlnXtLv4ORpQWa/fMXhFwOiaEhbs1Zhsjfdxbp/pQ65fTKkPqiU/Lw888/Y9++fTAxMUF4eLjyQlFA7oDJVyUPoaGhCAlR7ZMO/qg3Ph/6oS7hlAp1vdxQ18tN+dzXyw09pi7C1kMn8VmP9iUYGdHraeJrgsAu1srni356ViSv4+5ihHZvm2PayrwDsUk/rk0NRa2lIbmJgRBIv/8Qj3/eDte+7yvrOHXrAOeenXBp+CSkXL8Nyzre8J4zBZlRT/Hklz9LMPrixdkWmumUPHz++ecICQnBlClTYKBDdhYcHIygoCCVspzze3UJpUjYWJrB0MAA8YmqgyPjk5LzjGMoiLGRIbyruOCh2l8FRGXN+euZuPPoxQ+6sVHul6q1hYFK64O1uQEeROne1VDDTQorcwMsGe+gLDM0lKBPByu0a2KO8Yvzb/V7U2XFJUCRkwOZQwWVcqlDBWTF5J+AZcc9w4UBo2Egk8LYzgaZkTGoPj0I6Q8eKetUDxmPe8u+R9S23QCAlGu3YFrZBVXHDn2jkgfSTKfkISsrC71799YpcQAAmUwGmUymUpZaSrosAMDYyAg13V1x6t/baOVXCwCgUChw6t/b6N3Gv1DbkCsUuP0oCk3r1ijKUImKXEaWQIbaFMyEZDl8PGSI+C9ZMJFJ4FFJirDTunc3HL+Qjit3slTKJg6yw98X0nHkPLsx1InsbCRd/Bd2Ld5GzK6DuYUSCSq0aIyI737WuK4iMwuZkTGQGBnB8b13EPXnHuUyQ1NTQO3aPUIuh6Sczhoo0Ju2v1rSKXkYNGgQtmzZgqlTp+o7nlKjX/vmmL72V/hUrYRaHpWwed8xpGdmo0vzBgCAL9dsgYOtFUb1yp12uebPA6jjWQWVHSogOS0DG3YfRmTcM7zfopFym4kpaYiKS8DThNwbh92Pyv1LqoJ17uwMen2G5mYw96qifG5WtRKs6nojKz4RGQ8jSzCy8mXviVR0bWmB6PgcPH0mR482lkhIluPctQxlncmD7XD2WgYOnMz94ZdJJXC0e9G3XtHGCFWc5EhNVyAuUYGUdIGUdNWWC7lcIDFFjqhYTtnMz4MV61H727lIunAViecuw+3jATA0M8XjzdsAALVXzEVmZAxuzVoKALD2qwOZsyOSL1+HzNkBXpNHAAYS3Pt6nXKbT/eGwyNoONIfRSLl+m1Y+daE+6eDlNt8UwgmDxrplDzI5XLMnz8fe/fuha+vb54Bk4sXL9ZLcCWpfeO6eJacipXb9iEuMRk1qrhg+fiPlN0WUXEJMHipTywpNR2zftiKuMRkWJmZoqZ7JfzwxWfwcH0xnfXw+X9VLiQVvHIzAGB417b45P13imnPyjdrv9poErZR+dxnYW6C+3DDH7g0JLikwip3dh5NhcxYgsAu1sqLRC3cEI/sl377HewMYWn24gu4qosxpg550cTer2PuHXePnkvD2m2vvvYD5RW1fQ+k9nbwmjISMgd7JF25jrMffIysp7ndpaauzoDixXRXA5kM1aaOhqlbJchT0/D0wBFc/nQKcpKSlXWuTZmDasGj4bPgS0jt7ZAZFYOH63/DnQUri33/ShTHPGgkEc9vh6mFVq1aFbxBiQQHDx7UOpDUE9u1XoeKRniLySUdAv1ny5Twkg6B/tNvRduSDoFe0j7uapFuP+Xk//S2LYvGnfW2rdKCd9UkIiJSw24LzV7r6Ny+fRt79+5Feno6AECHRgwiIqLSh1eY1Ein5CEuLg5t2rRB9erV0bFjR0RG5g5EGzJkCMaPH6/XAImIiKh00Sl5GDduHIyNjREREQEzMzNlee/evbFnzx4NaxIREZUBvDGWRjqNedi3bx/27t2LSpUqqZRXq1YNDx480EtgREREJYVXmNRMp5QoNTVVpcXhufj4+DwXfyIiIqLyRafkoXnz5tiwYYPyuUQigUKhwPz58zVO4yQiIioT2G2hkU7dFvPnz0ebNm1w5swZZGVlYdKkSbh69Sri4+Nx/PhxfcdIRERUrATYbaGJTimRlZUVrl27hmbNmqFr165ITU1F9+7dcf78+TxXmyQiIqLyRaeWh6pVqyIyMhKff/65SnlcXBwqVaoEuZzXoSciorKLF4nSTKfkoaCLQaWkpMDExOS1AiIiIipxTB400ip5CAoKApA7QHLatGkqMy7kcjlOnjyJevXq6TVAIiKi4sapmppplTycP38eQG7Lw+XLlyGVSpXLpFIp6tatiwkTJug3QiIiIipVtEoent8QKzAwEMuWLYOVlVWRBEVERFSSOOZBM53GPPzwww/6joOIiKj0YLeFRkytiIiISCs6tTwQERGVZ+y20IzJAxERkRpeYVIzplZERESkFbY8EBERqWG3hWZMHoiIiNRxtoVGTK2IiIhIK2x5ICIiUiP4t7VGTB6IiIjU8N4WmjF5ICIiUsMBk5rx6BAREZUy3377Ldzd3WFiYoLGjRvj1KlThVrvl19+gUQiQbdu3Yo0PiYPREREagQkentoa8uWLQgKCsL06dNx7tw51K1bF+3bt0dMTIzG9e7fv48JEyagefPmuu52oTF5ICIiUiMkBnp7aGvx4sUYNmwYAgMD4ePjg1WrVsHMzAzr1q0rcB25XI5+/fohJCQEHh4er7PrhcLkgYiIqAhlZmYiKSlJ5ZGZmZlv3aysLJw9exZt27ZVlhkYGKBt27Y4ceJEga8xc+ZMODg4YMiQIXqPPz9MHoiIiNQIiURvj9DQUFhbW6s8QkND833d2NhYyOVyODo6qpQ7OjoiKioq33WOHTuG77//HmvXrtX7cSgIZ1sQERGp0eeNsYKDgxEUFKRSJpPJ9LLt5ORkDBgwAGvXroW9vb1etlkYTB6IiIiKkEwmK3SyYG9vD0NDQ0RHR6uUR0dHw8nJKU/9O3fu4P79++jcubOyTKFQAACMjIxw48YNeHp6vkb0+WO3BRERkZqSGjAplUrh5+eHsLAwZZlCoUBYWBiaNGmSp763tzcuX76MCxcuKB9dunRBq1atcOHCBVSuXPm1j0V+2PJARESkRp/dFtoKCgrCoEGD0KBBAzRq1AhLly5FamoqAgMDAQADBw6Eq6srQkNDYWJigtq1a6usb2NjAwB5yvWJyQMREVEp0rt3bzx9+hTTpk1DVFQU6tWrhz179igHUUZERMDAoGQ7Dpg8EBERqSnpy1OPHDkSI0eOzHdZeHi4xnV//PFH/QekhskDERGRmpLstigLmDwQERGpKemWh9KOR4eIiIi0wpYHIiIiNey20KzUJA/9N9Uq6RDoP5ZTwks6BPpP73ktSzoE+s+sDmtKOgR6Sfsi3r6QMHnQhN0WREREpJVS0/JARERUWgjBlgdNmDwQERGpEWyY14hHh4iIiLTClgciIiI1nG2hGZMHIiIiNUweNGO3BREREWmFLQ9ERERq2PKgGZMHIiIiNUweNGPyQEREpIbXedCMYx6IiIhIK2x5ICIiUsNuC82YPBAREalh8qAZuy2IiIhIK2x5ICIiUsOWB82YPBAREanhbAvN2G1BREREWmHLAxERkRoFuy00YvJARESkhmMeNGO3BREREWmFLQ9ERERqOGBSMyYPREREathtoRmTByIiIjVsedCMYx6IiIhIK2x5ICIiUsNuC82YPBAREalht4Vm7LYgIiIirbDlgYiISI2ipAMo5Zg8EBERqWG3hWbstiAiIiKtsOWBiIhIDWdbaMbkgYiISA27LTRjtwURERFppdAtD0FBQYXe6OLFi3UKhoiIqDRgt4VmhU4ezp8/r/L83LlzyMnJQY0aNQAAN2/ehKGhIfz8/PQbIRERUTFTiJKOoHQrdPJw6NAh5f8XL14MS0tLrF+/Hra2tgCAZ8+eITAwEM2bN9d/lERERMWILQ+a6TTmYdGiRQgNDVUmDgBga2uL2bNnY9GiRXoLjoiIiEofnWZbJCUl4enTp3nKnz59iuTk5NcOioiIqCRxtoVmOrU8vP/++wgMDMQff/yBR48e4dGjR9i6dSuGDBmC7t276ztGIiKiYiWE/h7lkU4tD6tWrcKECRPQt29fZGdn527IyAhDhgzBggUL9BogERERlS46JQ9mZmZYsWIFFixYgDt37gAAPD09YW5urtfgSoM+nezQ1t8a5qYGuH43A6u3xCDyaXaB9X08TdCtrS08q5jAztoIoWue4NSlVJU61paGGNjVHvVqmsHc1ABXb6fju9+eatwuAd1bW6BlAzOYmRjgVkQWftyRiOh4eYH1a7hJ0bGZOdxdjGFrZYilm+Nx7lpmgfUHd7ZC60bm2LQrEXtPpBXFLrxR7Jo1gMf4IbCuXxsmLg440+MzRO8IK+mwyqUh/dzRuZ0TLM2NcPlaEhauuIVHkekF1u/fszIC/O3h5mqGzCwFLl9Pwsof7+Lh4xfr2NkY47OPPNGwni3MTA0R8TgNG36NwOG/Y4tjl0qcggMmNXqti0SZm5vD19cXvr6+5TJxeL+tLToF2GD1LzGYvPAhMrMUmDbCFcZGBX+oTGQGuP84C2u2xBRYJ3i4MxztjRG6+gmC5kXgaXwOZoxyhUzKD2tBOjU3xztvm+PHHYkIWR2LzCyBiYPsYKwh/ZVJJYiIysaGvxJfuX2/mjJ4VpYiPqngZIS0Y2huhqRLN3BldEhJh1Ku9etRGT3fc8XCFbcwfMJ5pGfIsXhmHUiNC/4+eau2Df7Y+QQfTzyPcV9egpGhBEtm+sJE9uIn4Ysgb1RxNcWUWVcwaOQZHPk7FjMn+aCah0Vx7FaJE0Kit0d5pFPykJqaii+//BL+/v7w8vKCh4eHyqO8eK+VDX7bG49Tl1Px4EkWlm2Ihp21IRrXLThROvdvGjb/FYeTaq0Nz7k4GKNGVVOs/iUGtyMy8SQmG6u3xEBmLEFzP8ui2pUyr30Tc+w4nIJz1zPxMDoHq7cmwMbSEPVrmhS4zqVbmdgaloKzGlobAMDW0gADOllj1e8JkMvLaQdlCXi69whuTl+K6D8PlHQo5VqvLq7Y8OsDHDsZhzv3UzF7yXVUsJOh+dv2Ba4zfsZl7A6Lxr2INNy+n4q5S2/AycEENbxefAfV9rbG1r8e49qtZDyJzsD6XyOQkpqDGl5vRvJQ0r799lu4u7vDxMQEjRs3xqlTpwqsu3btWjRv3hy2trawtbVF27ZtNdbXB526LYYOHYrDhw9jwIABcHZ2hkRS/jIrxwpGsLM2wsXrL5qv0zIUuHU/AzXcTXDsbIpO2zX6r9UiO+fFj5QQuc9repriwImk1wu8HKpoawgbS0NcvfMiCUjPFLj7KAtelaU4eTlD521LJMDHPW2w61gKHsfk6CNcomLj4mgCezsZTl94pixLTZPj35tJqO1thbCjeWfF5cfc3BAAkJT8ouv0yvVEtG7ugL9PxyMlNQetm1WEVGqA85cT9LoPpVVJDnTcsmULgoKCsGrVKjRu3BhLly5F+/btcePGDTg4OOSpHx4ejj59+sDf3x8mJib46quv0K5dO1y9ehWurq5FEqNOycPu3buxc+dONG3aVN/xlBo2VrmHJjFZtRk7IVmuXKaLx1FZiInPRv8uFbDy5xhkZinQuZUt7G2NYWud9Voxl1fWFrkNZIkpCpXyxFQFbCxe7/YsnZqbQ64A9v3DMQ5U9tjZSgEAzxJUx0s9S8hSLnsViQQYPcwLl/5NxL2IF+fBtK/+RcgkH+z+uSlychTIyFRg6tyreBype7JelpTkRaIWL16MYcOGITAwEEDuJIWdO3di3bp1mDJlSp76mzZtUnn+3XffYevWrQgLC8PAgQOLJEadfgVtbW1hZ2en84tmZmYiM1O1KVkuz4KhYeE+7EWhRQNLfNLnRUY3Z+WTInkduQL4am0kRvZzxE8LPCGXC1y8kYazV1M5POc/TXxNENjFWvl80U/PNNTWnbuLEdq9bY5pK9+MAWBU9r0T4ICJI6orn0+aefm1txn0STV4VDHHZ5NVb0EwtF9VWJobYcznF5GYlI3mb9tj5iQfjJhyAXcf5N8tS/nL7zdPJpNBJpPlqZuVlYWzZ88iODhYWWZgYIC2bdvixIkThXq9tLQ0ZGdnv9bv9KvolDzMmjUL06ZNw/r162FmZqb1+qGhoQgJUR1EVaPhSNRsNFqXcPTi1OUU3Lz/IqN+PijS2tIQz14aRGdjaYh7jzT3ob/K3YeZCJoXATMTAxgZSZCUIsdXEyrjTsSbkdG/yvnrmbjz6MUPuvK9sDBQaX2wNjfAgyjduxpquElhZW6AJeNfJI2GhhL06WCFdk3MMX5x4Zp8iYrLsVNx+PfmGeVzqXFuy5utjTHinr1oubS1keL23Vd3rY772Av+De0wMvginsa9WN/FyQQ9O7tiwIjTytaI2/dTUbeWNbp3csHCFbf0tUullj7vbZHfb9706dMxY8aMPHVjY2Mhl8vh6OioUu7o6Ijr168X6vUmT54MFxcXtG3bVueYX0Wn5GHRokW4c+cOHB0d4e7uDmNjY5Xl586d07h+cHBwnrt09p/8UJdQ9CYjUyAqU7XpLz4xB741zHD/ce5JZWpigGruJthz7NWj9wsjLSP3h9C5ojE8q8iw+a84vWy3rMvIEsiIz9td5OMhQ8R/yYKJTAKPSlKEnda9u+H4hXRcuaPaVTRxkB3+vpCOI+fZjUGlT3q6HI/TVc+N2PhMNKhri9v3clsDzEwN4VPdCtt3aW49HfexF1o0sceo4IuIjFb9w8VEljsGQqHaUwi5QsDgDWki1ecsifx+8/JrddCHefPm4ZdffkF4eDhMTAoeUP66dEoeunXr9lovml9zTUl2WRTkr0MJ6NXBDpFPsxEdl42+nSogPlGOkxdfNNmFjHLFPxdTsPtIbkJhIpXAqeKLZMqxgjHcXaVISVMg9lnuD5//WxZITJEjNj4bbi4yDOlZEacupaoMziRVe0+komtLC0TH5+DpMzl6tLFEQrIc5669+NKbPNgOZ69l4MDJ3OMok0rgaGeoXF7RxghVnORITVcgLlGBlHSBlHTVlgu5XCAxRY6oWE7ZfF2G5mYw96qifG5WtRKs6nojKz4RGQ8jSzCy8uW3HY8xqHcVPHySjsjoDAzt7464+Ewc/edF693S2b44ciIWf+zMTSjGf+qFti0cETznCtLSc2Bnk/udlZImR1aWAg8epeHhkzRMHFEN3667i8TkbLR42x4N69li0swrJbKfxU2fAyYL6qLIj729PQwNDREdHa1SHh0dDScnJ43rLly4EPPmzcOBAwfg6+urc7yFoVPyMH36dH3HUSptO/AMJjIJPu3jAHNTA1y7k4FZKx6rzJRwsjeGlcWLHyhPNxPMHlNJ+fyjHhUBAAf/ScI3P+V+GGytDBHY3R7WlkZ4lpSD8JNJ+G1PfDHtVdm082gqZMYSBHaxVl4kauGGeGS/9NvvYGcIS7MXAyiruhhj6pAKyuf9OloBAI6eS8PabfppPaKCWfvVRpOwjcrnPgunAgAebvgDl4YEF7QaaWnT1ocwMTHEpJHVYWFuhMv/JmL89MvIyn7xPeXqZAobqxd/1LzfMXcE/vLQeirbmrP0OnaHRUMuF5g44wo+GVwVX31ZG6amhngcmY45S6/jn7P8ripKUqkUfn5+CAsLU/6hrlAoEBYWhpEjRxa43vz58zFnzhzs3bsXDRo0KPI4JUKUjitvvz+y/PehlRWWtpzHXVr0nteypEOg/4R2WFPSIdBLjv0voEi3/9c5/U3dfq++dn+nb9myBYMGDcLq1avRqFEjLF26FL/++iuuX78OR0dHDBw4EK6urggNDQUAfPXVV5g2bRo2b96sMgvSwsICFhZF831e6D2ys7PDzZs3YW9vD1tbW43XdoiPZ2ZKRERlV0n+Wd27d288ffoU06ZNQ1RUFOrVq4c9e/YoB1FGRETAwOBFK+vKlSuRlZWFnj17qmynoEGZ+lDo5GHJkiWwtMy9+tjSpUuLJBgiIiICRo4cWWA3RXh4uMrz+/fvF31AagqdPAwaNEj5/7CwMLRs2RIBAQHw9PQsksCIiIhKSnm9J4W+6HR5PplMhnnz5qF69eqoXLky+vfvj++++w63bnHcAhERlX0Kob9HeaRT8rB27VrcvHkTERERmD9/PiwsLLBo0SJ4e3ujUqVKr94AERERlVm636QBuZeprlChAmxtbWFjYwMjIyNUrFhRX7ERERGViNIxD7H00qnlYerUqfD390eFChUwZcoUZGRkYMqUKYiKisL58+dfvQEiIqJSTECit0d5pFPLw7x581CxYkVMnz4d3bt3R/Xq1V+9EhEREZULOiUP58+fx+HDhxEeHo5FixZBKpUiICAALVu2RMuWLZlMEBFRmVZeBzrqi07JQ926dVG3bl2MHp17F8yLFy9iyZIlGDFiBBQKBeRy3heAiIjKLo550Eyn5EEIgfPnzyM8PBzh4eE4duwYkpKS4Ovri4CAor1kKBERUVFj8qCZTsmDnZ0dUlJSULduXQQEBGDYsGFo3rw5bGxs9BweERERlTY6JQ8//fQTmjdvDisrK33HQ0REVOIUvMKkRjolD506ddJ3HERERKUGuy000+k6D0RERPTmeq0rTBIREZVHbHnQjMkDERGRGl7nQTN2WxAREZFW2PJARESkRnC2hUZMHoiIiNRwzINm7LYgIiIirbDlgYiISA0HTGrG5IGIiEgNuy00Y/JARESkhsmDZhzzQERERFphywMREZEajnnQjMkDERGRGnZbaMZuCyIiItIKWx6IiIjUKBQlHUHpxuSBiIhIDbstNGO3BREREWmFLQ9ERERq2PKgGZMHIiIiNZyqqRm7LYiIiEgrbHkgIiJSI/TabyHR47ZKByYPREREajjmQTMmD0RERGp4nQfNOOaBiIiItMKWByIiIjXsttCMyQMREZEaTtXUjN0WREREpJVS0/Kwqc+lkg6B/nO0y7SSDoH+M6vDmpIOgf4TvGd4SYdAKm4U6dbZbaFZqUkeiIiISguh136L8nedB3ZbEBERkVbY8kBERKSGAyY1Y/JARESkhmMeNGO3BREREWmFLQ9ERERqFOy30IjJAxERkRp2W2jGbgsiIiI1QujvoYtvv/0W7u7uMDExQePGjXHq1CmN9X/77Td4e3vDxMQEderUwa5du3R74UJi8kBERFSKbNmyBUFBQZg+fTrOnTuHunXron379oiJicm3/t9//40+ffpgyJAhOH/+PLp164Zu3brhypUrRRYjkwciIiI1CiH09tDW4sWLMWzYMAQGBsLHxwerVq2CmZkZ1q1bl2/9ZcuWoUOHDpg4cSJq1qyJWbNmoX79+li+fPnrHoYCMXkgIiJSIxT6e2RmZiIpKUnlkZmZme/rZmVl4ezZs2jbtq2yzMDAAG3btsWJEyfyXefEiRMq9QGgffv2BdbXByYPRERERSg0NBTW1tYqj9DQ0HzrxsbGQi6Xw9HRUaXc0dERUVFR+a4TFRWlVX194GwLIiIiNUKP0y2Cg4MRFBSkUiaTyfS2/ZLA5IGIiEiNQqG/bclkskInC/b29jA0NER0dLRKeXR0NJycnPJdx8nJSav6+sBuCyIiolJCKpXCz88PYWFhyjKFQoGwsDA0adIk33WaNGmiUh8A9u/fX2B9fWDLAxERkRp9dltoKygoCIMGDUKDBg3QqFEjLF26FKmpqQgMDAQADBw4EK6urspxE2PGjEFAQAAWLVqETp064ZdffsGZM2ewZs2aIouRyQMREZGakrw6de/evfH06VNMmzYNUVFRqFevHvbs2aMcFBkREQEDgxcdB/7+/ti8eTO++OILTJ06FdWqVcP27dtRu3btIouRyQMREVEpM3LkSIwcOTLfZeHh4XnKevXqhV69ehVxVC8weSAiIlIjeGMsjZg8EBERqeGNsTRj8kBERKSGt+TWjFM1iYiISCtseSAiIlJTklM1ywImD0RERGqEHq8wWR6x24KIiIi0wpYHIiIiNQp2W2jE5IGIiEgNxzxoxm4LIiIi0gpbHoiIiNTwOg+aMXkgIiJSw14LzZg8EBERqeG9LTTTy5iHpKQkbN++HdeuXdPH5oiIiKgU0yl5+OCDD7B8+XIAQHp6Oho0aIAPPvgAvr6+2Lp1q14DJCIiKm4KIfT2KI90Sh6OHDmC5s2bAwC2bdsGIQQSEhLw9ddfY/bs2XoNkIiIqLgJhdDbozzSKXlITEyEnZ0dAGDPnj3o0aMHzMzM0KlTJ9y6dUuvARIREVHpolPyULlyZZw4cQKpqanYs2cP2rVrBwB49uwZTExM9BogERFRcWPLg2Y6zbYYO3Ys+vXrBwsLC7i5uaFly5YAcrsz6tSpo8/4iIiIil05/c3XG52Sh88++wyNGjXCw4cP8c4778DAILcBw8PDg2MeiIiIyjmdr/PQoEEDNGjQQKWsU6dOrx0QERFRSSuv3Q36UujkISgoqNAbXbx4sU7BEBERlQa8MZZmhU4ezp8/X6h6EolE52BKmy1hJ7B+z1HEJaagemUnTO7XGbU9Kudbd8exs5i+TvUaF1IjI5xcMxMAkJ0jx4pt+3Hs0g08ehoPC1MTNPbxwuie7eFga1Xk+1LWVR7SB1VHBkLqYI/kqzdwfcpcJJ67nG9diZERPMYOg8uHXSBzdkTa7fu4GbIYsQePvahkYACvySPg3Os9yBzskRkVg8c//4m7i1YV0x6VfUP6uaNzOydYmhvh8rUkLFxxC48i0wus379nZQT428PN1QyZWQpcvp6ElT/excPHL9axszHGZx95omE9W5iZGiLicRo2/BqBw3/HFsculVt2zRrAY/wQWNevDRMXB5zp8Rmid4SVdFhUhhU6eTh06FBRxlHq7D11CYu27MLnA7qhtkclbN7/Nz5b/AO2zw2CnZVFvutYmMqwbe6LFpqX06iMrGxce/AEwzq3QvXKzkhKS8eCzX9h7NcbsXn6iCLem7LNqVsHeM+ahKsTQpB49jLcPh4Av99W41jj95AVG5+nfrXPR8O513u4OnY6Um/dg33rpqi3YRlOvtsPyZevAwCqjhmCyoG9cXnEVKRcvw3rerVRe/ls5CQnI2LNpuLexTKnX4/K6PmeK+YsvY7I6AwM7eeOxTProP9np5GVnf9fbG/VtsEfO5/g+q1kGBpIMHxgVSyZ6Yv+n51GRqYCAPBFkDcszI0wZdYVJCZl450AB8yc5IOhQedw625Kce5iuWJoboakSzfw8MetaPD7tyUdTpnAG2Np9lqXp759+zb27t2L9PTcvxzKUzPPT3uPoXuLhuja3A+ero74fGBXmEil2H70rIa1JLC3tlQ+KlhbKpdYmplg1YSP0K6RL9ydK8LXswqm9O+Caw8eIzIuocj3pyxz+2wQHm38HU82b0fqjTv4d3wI5OkZcO3XPd/6zh90xt0laxF74CjSHzzCwx+2IPbAUbiPGKysY9OwHmJ2H0Ts/iPIePgE0f/bh7hDf8O6PmcLFUavLq7Y8OsDHDsZhzv3UzF7yXVUsJOh+dv2Ba4zfsZl7A6Lxr2INNy+n4q5S2/AycEENbxenCe1va2x9a/HuHYrGU+iM7D+1wikpOaghlf+CTsVztO9R3Bz+lJE/3mgpEMpM4QQenuURzolD3FxcWjTpg2qV6+Ojh07IjIyEgAwZMgQjB8/Xq8BloTsnBxce/AEjX28lGUGBgZo7OOJS3ciClwvPTML706cjw7jv8LYrzfizuNoja+TnJYBiUQCSzNeG6MgEmNjWNX1QdzhEy8KhUDc4X9g07BuvusYSKVQZGSqlMkzMmDbuL7yecLpC6jQ4m2YeboBACxr1YBN47cQe+Co/neinHFxNIG9nQynLzxTlqWmyfHvzSTU9i58F5y5uSEAICk5W1l25XoiWjd3gKWFESQSoE3zipBKDXD+coLe4icqDF7nQTOdkodx48bB2NgYERERMDMzU5b37t0be/bseeX6mZmZSEpKUnlkZmW/cr3i8iw5DXKFIk/3RAUrC8QlJue7jptTRUwP7I6lo/pj9vBeEEJg8NxViI5PzLd+ZnY2vv59Dzo09oWFKZOHgkgr2MDAyAiZMXEq5VkxcZA65P9XbtzB43D/bBDMPKoAEgkqtGwCx05tIXOsqKxzb+l3iNy2G83++QvvRF1Ak/Df8WD1RkT+vrNI96c8sLOVAgCeJaies88SspTLXkUiAUYP88KlfxNxLyJNWT7tq39hZCjB7p+b4tAfzTFxRHVMnXsVjyMz9LcDRPTadEoe9u3bh6+++gqVKlVSKa9WrRoePHjwyvVDQ0NhbW2t8li48Q9dQik16npVQeem9VGjigsa1PDAwhH9YGtpjt/DT+Wpm50jx6SVP0MIYOqAriUQbfl2bWooUu8+UCYGNb/6HI9/3g6hUCjrOHXrAOeenXBp+CScaNULl0dMhfuIQLh8yPdD3TsBDtj3azPlw8jo9QdFB31SDR5VzDF9/r8q5UP7VYWluRHGfH4RQ8edw5btjzBzkg883Mxf+zWJtMGWB810us5DamqqSovDc/Hx8ZDJZK9cPzg4OM/UT/nZXbqEUiRsLc1gaGCA+CTVAVpxSSkq4xg0MTYyRI0qLnio9hdzdo4ck1f+jMjYBKyZNJStDq+QFZcARU4OZA4VVMqlDhWQFZP/CPzsuGe4MGA0DGRSGNvZIDMyBtWnByH9wSNlneoh43Fv2feI2rYbAJBy7RZMK7ug6tihePLLn0W3Q2XQsVNx+PfmGeVzqXHu3xy2NsaIe5alLLe1keJ2IQY1jvvYC/4N7TAy+CKexr1Y38XJBD07u2LAiNPK1ojb91NRt5Y1undywcIVvG8OFZ/yejdMfdGp5aF58+bYsGGD8rlEIoFCocD8+fPRqlWrV64vk8lgZWWl8pBJjXUJpUgYGxmhppsLTl67rSxTKBQ4de0OfD2rFGobcoUCtx9Fwd7mRbLxPHGIiInFqgkfwcYibwJGqkR2NpIu/gu7Fm+/KJRIUKFFYyScvqhxXUVmFjIjYyAxMoLje+8gZvdB5TJDU1PgpZYIABByOSSS1xpDXC6lp8vxODJD+bgXkYbY+Ew0qGurrGNmagif6la4cj1J47bGfeyFFk3sMebzS4iMVu2KMJHljoFQe1sgVwgYlJ8Z4ETlgk4tD/Pnz0ebNm1w5swZZGVlYdKkSbh69Sri4+Nx/PhxfcdYIvq3b4Zp3/0OH/dKqF21EjbvP470zCx0bZY76O6Ltb/BwdYKo3u2BwCs3hEGX48qqOxQAcnp6Vi/+ygi4xLwfvPcq3Bm58gxccVmXH/wBMvGDIRCCMT+N37C2twUxkY6X+yz3HuwYj1qfzsXSReuIvFc7lRNQzNTPN68DQBQe8VcZEbG4NaspQAAa786kDk7IvnydcicHeA1eQRgIMG9r9cpt/l0bzg8goYj/VEkUq7fhpVvTbh/Oki5TdLstx2PMah3FTx8kp47VbO/O+LiM3H0nxetQUtn++LIiVj8sfMJAGD8p15o28IRwXOuIC09B3Y2uX8wpKTJkZWlwINHaXj4JA0TR1TDt+vuIjE5Gy3etkfDeraYNPNKiexneWFobgZzrxd/+JhVrQSrut7Iik9ExsPIEoys9Cqv3Q36otMvVu3atXHz5k188803sLS0REpKCrp3744RI0bA2dlZ3zGWiPaNfPEsORUrtx9AXGIyalR2xrfjApXdFlHxCTB46c+h5NQMzFy/DXGJybAyM0VNd1f8OPUTeLo6AgCeJiTh8IVrAIAPZ3yj8lprJw1FA2+PYtqzsidq+x5I7e3gNWUkZA72SLpyHWc/+BhZT3O7hExdnVXuYmMgk6Ha1NEwdasEeWoanh44gsufTkFO0ovBrtemzEG14NHwWfAlpPZ2yIyKwcP1v+HOgpXFvn9l0aatD2FiYohJI6vDwtwIl/9NxPjpl1Wu8eDqZAobqxctiu93dAUALA+tp7KtOUuvY3dYNORygYkzruCTwVXx1Ze1YWpqiMeR6Ziz9Dr+OZv3eh5UeNZ+tdEkbKPyuc/CqQCAhxv+wKUhwSUVVqlWXqdY6otElJIjlHZ866srUbE42mVaSYdA/5nlv6KkQ6D/BO8ZXtIh0Es6Zd8o0u0P/FJ/LTIbZpWPP6pfpnMH79GjR9G/f3/4+/vj8ePHAICNGzfi2LFjr1iTiIiodFMohN4e5ZFOycPWrVvRvn17mJqa4ty5c8jMzL0gT2JiIubOnavXAImIiIobp2pqplPyMHv2bKxatQpr166FsfGLPs2mTZvi3LlzeguOiIiISh+dBkzeuHEDLVq0yFNubW2NhISE142JiIioRJWS4YCllk4tD05OTrh9+3ae8mPHjsHDg7MGiIiobBMKhd4e5ZFOLQ/Dhg3DmDFjsG7dOkgkEjx58gQnTpzAhAkT8OWXX+o7RiIiomJVXgc66kuhk4dLly6hdu3aMDAwQHBwMBQKBdq0aYO0tDS0aNECMpkMEyZMwKhRo4oyXiIiIiphhU4e3nrrLURGRsLBwQEeHh44ffo0Jk6ciNu3byMlJQU+Pj6wsLB49YaIiIhKOY550KzQyYONjQ3u3bsHBwcH3L9/HwqFAlKpFD4+PkUZHxERUbErr1Ms9aXQyUOPHj0QEBAAZ2dnSCQSNGjQAIaGhvnWvXv3rt4CJCIiotKl0MnDmjVr0L17d9y+fRujR4/GsGHDYGlZuNtTExERlSVsedBMq9kWHTp0AACcPXsWY8aMYfJARETlkkKUzymW+qLTVM0ffvhB33EQERFRGaFT8kBERFSesdtCM53vqklERFRelYUbY8XHx6Nfv36wsrKCjY0NhgwZgpSUFI31R40ahRo1asDU1BRVqlTB6NGjkZiYqPVrM3kgIiIqg/r164erV69i//79+Ouvv3DkyBEMHz68wPpPnjzBkydPsHDhQly5cgU//vgj9uzZgyFDhmj92uy2ICIiUlPaLxJ17do17NmzB6dPn0aDBg0AAN988w06duyIhQsXwsXFJc86tWvXxtatW5XPPT09MWfOHPTv3x85OTkwMip8SsCWByIiIjUKhUJvj8zMTCQlJak8MjMzXyu+EydOwMbGRpk4AEDbtm1hYGCAkydPFno7iYmJsLKy0ipxAJg8EBER5aHPMQ+hoaGwtrZWeYSGhr5WfFFRUXBwcFApMzIygp2dHaKiogq1jdjYWMyaNUtjV0dBmDwQEREVoeDgYCQmJqo8goOD8607ZcoUSCQSjY/r16+/dkxJSUno1KkTfHx8MGPGDK3X55gHIiIiNUKPF4mSyWSQyWSFqjt+/HgMHjxYYx0PDw84OTkhJiZGpTwnJwfx8fFwcnLSuH5ycjI6dOgAS0tLbNu2DcbGxoWK7WVMHoiIiNSU1HUeKlasiIoVK76yXpMmTZCQkICzZ8/Cz88PAHDw4EEoFAo0bty4wPWSkpLQvn17yGQy7NixAyYmJjrFyW4LIiKiMqZmzZro0KEDhg0bhlOnTuH48eMYOXIkPvzwQ+VMi8ePH8Pb2xunTp0CkJs4tGvXDqmpqfj++++RlJSEqKgoREVFQS6Xa/X6bHkgIiJSUxauMLlp0yaMHDkSbdq0gYGBAXr06IGvv/5auTw7Oxs3btxAWloaAODcuXPKmRheXl4q27p37x7c3d0L/dpMHoiIiNSUhRtj2dnZYfPmzQUud3d3V7leRcuWLfV2/Qp2WxAREZFW2PJARESkpix0W5QkJg9ERERqhKL0d1uUJHZbEBERkVbY8kBERKSG3RaaMXkgIiJSo88rTJZHTB6IiIjUKNjyoBHHPBAREZFW2PJARESkhrMtNGPyQEREpIYDJjVjtwURERFphS0PREREajjbQjMmD0RERGrYbaEZuy2IiIhIK2x5ICIiUsPZFppJhL5u7v2Gy8zMRGhoKIKDgyGTyUo6nDce34/Sg+9F6cH3gvSFyYOeJCUlwdraGomJibCysirpcN54fD9KD74XpQffC9IXjnkgIiIirTB5ICIiIq0weSAiIiKtMHnQE5lMhunTp3MQUinB96P04HtRevC9IH3hgEkiIiLSClseiIiISCtMHoiIiEgrTB6IiIhIK0weiIiISCtMHnTg7u6OpUuXlnQYRKXSjz/+CBsbm9feTsuWLTF27NjX3k55JITA8OHDYWdnB4lEggsXLrz2Nnm8SRtvdPIgkUiwffv2kg6jyOnry7w48Yus7Orduzdu3rxZ0mGUa3v27MGPP/6Iv/76C5GRkahdu3ZJh0RvmDJ5V82srCxIpdKSDoOI8mFqagpTU9OSDqNcu3PnDpydneHv71/SodAbqky0PLRs2RIjR47E2LFjYW9vj/bt2+PKlSt49913YWFhAUdHRwwYMACxsbEq64wePRqTJk2CnZ0dnJycMGPGDOVyd3d3AMD7778PiUSifH7nzh107doVjo6OsLCwQMOGDXHgwAGdY09ISMDHH38MR0dHmJiYoHbt2vjrr7+Uy7du3YpatWpBJpPB3d0dixYtUlk/v9YRGxsb/PjjjwCA+/fvQyKR4I8//kCrVq1gZmaGunXr4sSJEwCA8PBwBAYGIjExERKJBBKJROU4lEaDBw/G4cOHsWzZMmXM9+/fL9R7PmrUKIwdOxa2trZwdHTE2rVrkZqaisDAQFhaWsLLywu7d+9WrhMeHg6JRIKdO3fC19cXJiYmePvtt3HlypWS2PVS66+//oKNjQ3kcjkA4MKFC5BIJJgyZYqyztChQ9G/f/88LV0zZsxAvXr1sHHjRri7u8Pa2hoffvghkpOTlXVSU1MxcOBAWFhYwNnZOc95QC8MHjwYo0aNQkREhPK7S6FQIDQ0FFWrVoWpqSnq1q2L33//XWW9V50/6lasWIFq1arBxMQEjo6O6NmzZ1HvGpUhZSJ5AID169dDKpXi+PHjmDdvHlq3bo233noLZ86cwZ49exAdHY0PPvggzzrm5uY4efIk5s+fj5kzZ2L//v0AgNOnTwMAfvjhB0RGRiqfp6SkoGPHjggLC8P58+fRoUMHdO7cGREREVrHrFAo8O677+L48eP46aef8O+//2LevHkwNDQEAJw9exYffPABPvzwQ1y+fBkzZszAl19+qUwMtPH5559jwoQJuHDhAqpXr44+ffogJycH/v7+WLp0KaysrBAZGYnIyEhMmDBB6+0Xp2XLlqFJkyYYNmyYMmZLS8tCv+f29vY4deoURo0ahU8//RS9evWCv78/zp07h3bt2mHAgAFIS0tTWW/ixIlYtGgRTp8+jYoVK6Jz587Izs4uzt0u1Zo3b47k5GScP38eAHD48GHY29sjPDxcWefw4cNo2bJlvuvfuXMH27dvx19//YW//voLhw8fxrx585TLJ06ciMOHD+PPP//Evn37EB4ejnPnzhXlLpVZy5Ytw8yZM1GpUiXld1doaCg2bNiAVatW4erVqxg3bhz69++Pw4cPA8j9I6Yw589zZ86cwejRozFz5kzcuHEDe/bsQYsWLYpzN6m0E2VAQECAeOutt5TPZ82aJdq1a6dS5+HDhwKAuHHjhnKdZs2aqdRp2LChmDx5svI5ALFt27ZXvn6tWrXEN998o3zu5uYmlixZ8sr19u7dKwwMDJQxqevbt6945513VMomTpwofHx8NMZobW0tfvjhByGEEPfu3RMAxHfffadcfvXqVQFAXLt2TQghxA8//CCsra1fGW9pEhAQIMaMGaN8rst7npOTI8zNzcWAAQOUZZGRkQKAOHHihBBCiEOHDgkA4pdfflHWiYuLE6ampmLLli1FsWtlVv369cWCBQuEEEJ069ZNzJkzR0ilUpGcnCwePXokAIibN2/m+bxNnz5dmJmZiaSkJGXZxIkTRePGjYUQQiQnJwupVCp+/fVX5fLn78HLnwF6YcmSJcLNzU0IIURGRoYwMzMTf//9t0qdIUOGiD59+gghCn/+PD/eW7duFVZWVirvGdHLykzLg5+fn/L/Fy9exKFDh2BhYaF8eHt7A8j9C+c5X19flW04OzsjJiZG4+ukpKRgwoQJqFmzJmxsbGBhYYFr167p1PJw4cIFVKpUCdWrV893+bVr19C0aVOVsqZNm+LWrVvK5uHCenlfnZ2dAeCV+1qW6PKeGxoaokKFCqhTp46yzNHREUDeY9OkSRPl/+3s7FCjRg1cu3atSPalrAoICEB4eDiEEDh69Ci6d++OmjVr4tixYzh8+DBcXFxQrVq1fNd1d3eHpaWl8vnL5+KdO3eQlZWFxo0bK5c/fw/o1W7fvo20tDS88847KufHhg0blOdGYc+f59555x24ubnBw8MDAwYMwKZNm/K01tGbrcwMmDQ3N1f+PyUlBZ07d8ZXX32Vp97zH04AMDY2VlkmkUigUCg0vs6ECROwf/9+LFy4EF5eXjA1NUXPnj2RlZWldcz6GDQmkUgg1G4/kl9z+sv7KpFIAOCV+1qWvM57Xt6PTXFp2bIl1q1bh4sXL8LY2Bje3t5o2bIlwsPD8ezZMwQEBBS4ri7nIhVOSkoKAGDnzp1wdXVVWfb8BliFPX+es7S0xLlz5xAeHo59+/Zh2rRpmDFjBk6fPl3mZm5R0SgzycPL6tevj61bt8Ld3R1GRrrvgrGxcZ6/8I8fP47Bgwfj/fffB5B70t2/f1+n7fv6+uLRo0e4efNmvq0PNWvWxPHjx/O8fvXq1ZXjIipWrIjIyEjl8lu3bmn9F4BUKtW6JaOkqcesr/e8IP/88w+qVKkCAHj27Blu3ryJmjVr6v11yrLn4x6WLFmiTBRatmyJefPm4dmzZxg/frxO2/X09ISxsTFOnjyZ5z3QlJBQLh8fH8hkMkRERBR4vHQ5f4yMjNC2bVu0bdsW06dPh42NDQ4ePIju3bvrM3wqo8pMt8XLRowYgfj4ePTp0wenT5/GnTt3sHfvXgQGBmr1I+nu7o6wsDBERUXh2bNnAIBq1arhjz/+wIULF3Dx4kX07dtX57+QAgIC0KJFC/To0QP79+/HvXv3sHv3buzZswcAMH78eISFhWHWrFm4efMm1q9fj+XLl6sMaGzdujWWL1+O8+fP48yZM/jkk0/y/BVXmP1MSUlBWFgYYmNjy0Tzo7u7O06ePIn79+8jNjZWb+95QWbOnImwsDBcuXIFgwcPhr29Pbp16/b6O1KO2NrawtfXF5s2bVIOjGzRogXOnTv3Wj/0FhYWGDJkCCZOnIiDBw8q3wMDgzL59VTsLC0tMWHCBIwbNw7r16/HnTt3cO7cOXzzzTdYv349AO2/M//66y98/fXXuHDhAh48eIANGzZAoVCwK4mUyuTZ6eLiguPHj0Mul6Ndu3aoU6cOxo4dCxsbG62+cBYtWoT9+/ejcuXKeOuttwAAixcvhq2tLfz9/dG5c2e0b98e9evX1znWrVu3omHDhujTpw98fHwwadIk5clav359/Prrr/jll19Qu3ZtTJs2DTNnzsTgwYNVYqxcuTKaN2+Ovn37YsKECTAzM9MqBn9/f3zyySfo3bs3KlasiPnz5+u8P8VlwoQJMDQ0hI+PDypWrIisrCy9vOcFmTdvHsaMGQM/Pz9ERUXhf//7H68lko+AgADI5XJl8mBnZwcfHx84OTm91g/LggUL0Lx5c3Tu3Blt27ZFs2bNVMY5kWazZs3Cl19+idDQUNSsWRMdOnTAzp07UbVqVQDaf2fa2Njgjz/+QOvWrVGzZk2sWrUKP//8M2rVqlXcu0allESod6gTvUHCw8PRqlUrPHv2jH25RESFVCZbHoiIiKjkMHl4DZs2bVKZ+vTyg817RERUXrHb4jUkJycjOjo632XGxsZwc3Mr5oiIiIiKHpMHIiIi0gq7LYiIiEgrTB6IiIhIK0weiIiISCtMHoiIiEgrTB6IiIhIK0weiIiISCtMHoiIiEgr/wfbrszNPFo82gAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Aggregate bike rentals by day and weather conditions\n",
    "daily_rentals_weather = df.groupby('date').agg({\n",
    "    'started_at':'count',\n",
    "    'temp':'mean',\n",
    "    # Assuming 'wind' and 'feels' represent wind speed and \"feels like\" temperature respectively\n",
    "    'wind':'mean',\n",
    "    'feels':'mean'\n",
    "}).rename(columns={'started_at':'rental_count'})\n",
    "\n",
    "# Correlation matrix between rentals and weather conditions\n",
    "corr_matrix_weather = daily_rentals_weather.corr()\n",
    "sns.heatmap(corr_matrix_weather, annot=True, cmap='coolwarm')\n",
    "plt.title(\"Correlation Matrix of Rentals and Weather Conditions\")\n",
    "plt.show()\n",
    "\n",
    "# Scatter plot: Rentals vs. Temperature\n",
    "plt.scatter(daily_rentals_weather['temp'], daily_rentals_weather['rental_count'])\n",
    "plt.title('Bike Rentals vs. Temperature')\n",
    "plt.xlabel('Temperature')\n",
    "plt.ylabel('Number of Rentals')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# **Zjistěte vliv počasí na poptávku po kolech (údaje o počasí v Edinburghu jsou v tabulce edinburgh_weather)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "rentals_per_temperature = df.groupby('temp').size()\n",
    "\n",
    "# Display the number of rentals ('switches') at each temperature\n",
    "print(rentals_per_temperature)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Example: Analyzing the relationship between temperature and bike rentals\n",
    "plt.figure(figsize=(10, 6))\n",
    "rentals_per_temperature.plot(kind='bar')  # or 'line' if you prefer\n",
    "plt.title('Number of Bike Rentals According to Temperature')\n",
    "plt.xlabel('Temperature (°C)')\n",
    "plt.ylabel('Number of Rentals')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "rentals_per_wind = df.groupby('wind').size()\n",
    "\n",
    "# Display the number of rentals ('switches') at each temperature\n",
    "print(rentals_per_wind)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Example: Analyzing the relationship between wind and bike rentals\n",
    "plt.figure(figsize=(10, 6))\n",
    "rentals_per_wind.plot(kind='bar')  # or 'line' if you prefer\n",
    "plt.title('Number of Bike Rentals According to Wind')\n",
    "plt.xlabel('Wind km/h')\n",
    "plt.ylabel('Number of Rentals')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "rentals_per_rain = df.groupby('rain').size()\n",
    "\n",
    "# Display the number of rentals ('switches') at each temperature\n",
    "print(rentals_per_rain)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Example: Analyzing the relationship between wind and bike rentals\n",
    "plt.figure(figsize=(10, 6))\n",
    "rentals_per_rain.plot(kind='bar')  # or 'line' if you prefer\n",
    "plt.title('Number of Bike Rentals According to rain')\n",
    "plt.xlabel('rain mm')\n",
    "plt.ylabel('Number of Rentals')\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "venv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
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