Forecasting airlines.ipynb

{
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  {
   "cell_type": "markdown",
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   "source": [
    "# Forecast the Airlines Passengers data set. Prepare a document for each model explaining how many dummy variables you have created and RMSE value for each model. Finally which model you will use for Forecasting. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "18bf85f9",
   "metadata": {},
   "source": [
    "## Time series forecasting\n",
    "    occurs when you make scientific predictions based on historical time stamped data. It involves building models through historical analysis and using them to make observations and drive future strategic decision-making\n",
    "Time series can be decomposed into four components, each expressing a particular aspect of the movement of the values of the time series.\n",
    "\n",
    "These four components are:\n",
    "\n",
    "Secular trend, which describe the movement along the term;\n",
    "\n",
    "Seasonal variations, which represent seasonal changes;\n",
    "\n",
    "Cyclical fluctuations, which correspond to periodical but not seasonal variations;\n",
    "\n",
    "Irregular variations, which are other nonrandom sources of variations of series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
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   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns \n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\") "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f2ce2e09",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Month</th>\n",
       "      <th>Passengers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1995-01-01</td>\n",
       "      <td>112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1995-02-01</td>\n",
       "      <td>118</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1995-03-01</td>\n",
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       "      <td>1995-04-01</td>\n",
       "      <td>129</td>\n",
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       "      <th>4</th>\n",
       "      <td>1995-05-01</td>\n",
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       "      <th>92</th>\n",
       "      <td>2002-09-01</td>\n",
       "      <td>355</td>\n",
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       "      <td>2002-12-01</td>\n",
       "      <td>306</td>\n",
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       "  </tbody>\n",
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       "<p>96 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Month  Passengers\n",
       "0  1995-01-01         112\n",
       "1  1995-02-01         118\n",
       "2  1995-03-01         132\n",
       "3  1995-04-01         129\n",
       "4  1995-05-01         121\n",
       "..        ...         ...\n",
       "91 2002-08-01         405\n",
       "92 2002-09-01         355\n",
       "93 2002-10-01         306\n",
       "94 2002-11-01         271\n",
       "95 2002-12-01         306\n",
       "\n",
       "[96 rows x 2 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "air = pd.read_excel('Airlines+Data.xlsx')\n",
    "air "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "97804d4c",
   "metadata": {},
   "source": [
    "# Descriptive Statistics "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c0994247",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:44.769917Z",
     "start_time": "2022-11-15T06:34:44.754003Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Month         0\n",
       "Passengers    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "air.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6b1a9a12",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:44.793919Z",
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       "0"
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     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "air.duplicated().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "52ec17a0",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:44.809967Z",
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(96, 2)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "air.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "21e6806b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:44.826069Z",
     "start_time": "2022-11-15T06:34:44.809967Z"
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 96 entries, 0 to 95\n",
      "Data columns (total 2 columns):\n",
      " #   Column      Non-Null Count  Dtype         \n",
      "---  ------      --------------  -----         \n",
      " 0   Month       96 non-null     datetime64[ns]\n",
      " 1   Passengers  96 non-null     int64         \n",
      "dtypes: datetime64[ns](1), int64(1)\n",
      "memory usage: 1.6 KB\n"
     ]
    }
   ],
   "source": [
    "air.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c56e20c0",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:44.842059Z",
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       "      <td>96.000000</td>\n",
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       "      <td>213.708333</td>\n",
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       "      <td>71.918216</td>\n",
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       "    <tr>\n",
       "      <th>min</th>\n",
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       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>156.000000</td>\n",
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      "text/plain": [
       "       Passengers\n",
       "count   96.000000\n",
       "mean   213.708333\n",
       "std     71.918216\n",
       "min    104.000000\n",
       "25%    156.000000\n",
       "50%    200.000000\n",
       "75%    264.750000\n",
       "max    413.000000"
      ]
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   ],
   "source": [
    "air.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ef38b45",
   "metadata": {},
   "source": [
    "# Feature Engineering "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "39b9cdea",
   "metadata": {
    "ExecuteTime": {
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     "start_time": "2022-11-15T06:34:44.842059Z"
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   },
   "outputs": [],
   "source": [
    "air['month'] = air.Month.dt.strftime('%b')\n",
    "air['year'] = air.Month.dt.strftime('%Y')\n",
    "\n",
    "air['t'] = np.arange(1,len(air)+1)\n",
    "air['t_squared'] = np.square(air.t)\n",
    "\n",
    "air['log_passengers'] = np.log(air.Passengers) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "35f02d22",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:44.873973Z",
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       "      <td>May</td>\n",
       "      <td>1995</td>\n",
       "      <td>5</td>\n",
       "      <td>25</td>\n",
       "      <td>4.795791</td>\n",
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      ],
      "text/plain": [
       "       Month  Passengers month  year  t  t_squared  log_passengers\n",
       "0 1995-01-01         112   Jan  1995  1          1        4.718499\n",
       "1 1995-02-01         118   Feb  1995  2          4        4.770685\n",
       "2 1995-03-01         132   Mar  1995  3          9        4.882802\n",
       "3 1995-04-01         129   Apr  1995  4         16        4.859812\n",
       "4 1995-05-01         121   May  1995  5         25        4.795791"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "air.head()"
   ]
  },
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   "id": "e1196e54",
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      "text/plain": [
       "   t  t_squared month  Passengers  log_passengers\n",
       "0  1          1   Jan         112        4.718499\n",
       "1  2          4   Feb         118        4.770685\n",
       "2  3          9   Mar         132        4.882802\n",
       "3  4         16   Apr         129        4.859812\n",
       "4  5         25   May         121        4.795791"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "air1 = air[['t' , 't_squared', 'month' , 'Passengers', 'log_passengers']]\n",
    "air1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "94eda08e",
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       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>118</td>\n",
       "      <td>4.770685</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "      <td>132</td>\n",
       "      <td>4.882802</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>16</td>\n",
       "      <td>129</td>\n",
       "      <td>4.859812</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>25</td>\n",
       "      <td>121</td>\n",
       "      <td>4.795791</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   t  t_squared  Passengers  log_passengers  month_Apr  month_Aug  month_Dec  \\\n",
       "0  1          1         112        4.718499          0          0          0   \n",
       "1  2          4         118        4.770685          0          0          0   \n",
       "2  3          9         132        4.882802          0          0          0   \n",
       "3  4         16         129        4.859812          1          0          0   \n",
       "4  5         25         121        4.795791          0          0          0   \n",
       "\n",
       "   month_Feb  month_Jan  month_Jul  month_Jun  month_Mar  month_May  \\\n",
       "0          0          1          0          0          0          0   \n",
       "1          1          0          0          0          0          0   \n",
       "2          0          0          0          0          1          0   \n",
       "3          0          0          0          0          0          0   \n",
       "4          0          0          0          0          0          1   \n",
       "\n",
       "   month_Nov  month_Oct  month_Sep  \n",
       "0          0          0          0  \n",
       "1          0          0          0  \n",
       "2          0          0          0  \n",
       "3          0          0          0  \n",
       "4          0          0          0  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "air1 = pd.get_dummies(air1)\n",
    "air1.head() "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "24a4a594",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T05:35:33.829092Z",
     "start_time": "2022-11-15T05:35:33.814443Z"
    }
   },
   "source": [
    "# Data Visualisation "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "3348ac00",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:45.074936Z",
     "start_time": "2022-11-15T06:34:44.905989Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "air['Passengers'].plot(figsize=(20, 8),color='blue',marker='o')  "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0f42694",
   "metadata": {},
   "source": [
    "We can observe increasing trend in passengers "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "34a12ec7",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:45.421978Z",
     "start_time": "2022-11-15T06:34:45.074936Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='year', ylabel='Passengers'>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x864 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(18,12))\n",
    "\n",
    "plt.subplot(2,1,1)\n",
    "sns.boxplot(air.month, air.Passengers)\n",
    "plt.subplot(2,1,2)\n",
    "sns.boxplot(air.year, air.Passengers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "3f2ad3b2",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:46.342671Z",
     "start_time": "2022-11-15T06:34:45.421978Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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4PwT+ISK+lnsOrZDqPfTzXqymkfxFyrSNw/PERW8cq5n/yR/9jPufOtjRQFHruyrr5HdmBtnVRz8BPgx8OBl8tgg4DPxzRLzamexZUdV76Hdzls7ZAava6Mgwm9+1PDX/d3z/+crgmE69qdf7TopW1WX9rZFxCu8DDkXEgxGxxwHBoP7UzHkuVlNv7EHam/f46Ah7rvujzKA1u3DRiTUI6n0nntnUOqmRcQq/DUxK2i7p4mT8gQ24eg/9erN0tjqorJEVxRoppfxWygps9Y5rNI/NXFut76rMM5tap9UNChHxEUoDyW6l1Lj8jKT/JukNOefNCqzeQ3/tynFuuPwCxkdHEKW39Bsuv4C1K8fntFRkIyuK1QtYO3ZP8YtfN96hrpk39Vaurfq7AhhK3ruqvzOzTmloltSICEk/AX5CaWDZQuBLku6JiA/nmUErpkamZk6bpXMujdCNlAI2rDnvpDaF6oC1eedeaoxpY3genDI0lHpcI1q9Ns9oakVRNyhIej9wJfBT4HPAhoiYljQPeIZSY7QNoFYfZHNphG5kRbF6ASttUNv0cbjxigvm1E3Vy2Bar2ukpHA6cHlE/Kg6MSKOS7o0n2xZP5vLUpH1SgFlrQasub6xexlM63WNtCl8dHZAqNr2ZPuzZP1uLktFZrVVNGrhgtqNzGnpzfAymNbrmlmO06wt5rpU5Fzf5q9753I2fOkRpo+daFgYHhLXvXN5y+eszht4GUzrXYq0YZ89YGJiIiYnJ7udjYFQlCkh2qXfrsesGZJ2RcRErW0uKVhdRZjHqN3c28esto6s0Wy9rZGxAWbWHxwUrC53szQbHK4+srr6uZul2xbMZnJJwerq126Wc5luw6xfufeRNaQf36hXbb2vZgloSOJ4RN9cp9ls7n1kc9aPvXXS2kS88pkNMlcf2cBqpE3Evaxs0DgoWEe1uo5CHrLWMajmXlY2SFx9ZB3TjUFwWW0hs6ekmCdVqo6q9UMvK7NG5VZSkHS2pPslPSlpr6QPJOmnSbpH0jPJvwurjtkkaZ+kpyWtyStv1ph2v9V3ehBcI72L1q4c54GNq3l26zv45J/+Xl/2sjJrRp4lhaPAhyLiB5JeD+ySdA+l1dvujYitkjYCG4G/lnQ+sA5YDpwFfFvSuRFx8mK7lqsdu6fYvHPvjHUH5vpWv2P3VM2ePpBf9UyzC954MjuzHINCRBwADiSffynpSWAcuAx4a7Lb7cB3gL9O0u+MiCPAs5L2ARcCD+aVRzvZ7Cqeao2ujpZ2zjR5Vc+0MhK7H3tZmTWjI20KkpYCK4GHgDOTgEFEHJB0RrLbOPD9qsP2J2nWQbXerqs18lZfrsefOnSYoZR6+rI8q2f6eSS2WV5yDwqSXgd8GbgmIn6hZFHyWrvWSDvpaSJpPbAeYMmSJe3K5sCa3RCbVsVTVu+BOrukkRUQgFwXpm90lTYzOyHXLqmShikFhDsi4itJ8ouSFiXbFwEvJen7gbOrDl8MvDD7nBFxS0RMRMTE2NhYfpkfALUaYlNDNqWFaOo9UOuVNKqNj47kWlXTjlXazAZNbiUFlYoEtwJPRsRNVZt2AlcCW5N/v1aV/gVJN1FqaD4HeDiv/FntB3hQKrLVfL9vYEaURhuN097Y2z2dhtsIzJqTZ0lhFfDnwGpJe5KfSygFgz+U9Azwh8nvRMReYDvwBPAt4Gr3PMpX2gM8KM3/M9v08ajbfbSR+vq0N3ZPUGfWfXn2PvoetdsJAN6WcswWYEteebKZ0toQxkdHWl5DoVY9ftnI8NCMYDC7VPCrI0eb6kJqZu3naS4GWNaU2Glv/PVKAtX1+HCixDG7dFCrVFA9LqKap5kw6xxPczHA6g3WarXnTiP1+M00SLsLqVnnOCgMuLQHeDmtemTzqcOtFyyb7fpa5i6kZp3loGCZjhw9Xvn88qvTLU11UWsivLQeTgsXDLPgNad4mgmzLnFQGGD1un82O3dQ2jkb7fo6MjzEde9cztqV45XzXLttDzfe/bSDg1mHOCgMqEamsW62B1LaOdPaDoITPZ2qg1I3ptg2sxIHhR7R7kFdaaWA67++t3LeZucOSjtn2vxH46MjPLBxdcPncddUs/y5S2oPyGNQV9rb/suvTlfOm9VltZlzHotoy3ncNdUsfw4KPSCPxWmyunmWz9vs3EFp5ywfN9fzuGuqWf5cfdQDWn1zzqpy2rDmPK7ZtqfueRudO2jH7ile/c3Rk9LLJYJm5iDy7KZm3eOSQg9o5c25VpXTtdv2sDRZWhNgdGS46fNm/a2XX505Inl0ZLilWUk9u6lZ97ik0AMueuMYd3z/+ZO6b2a9Oad1A4VSgNjwpUc4Zd7JU1O18kaeNjr5tfNPaflB7tlNzbrDQaHgduye4su7pmYEBAF/8pbsh2a9qqXpY8H0sZk9ghYuGK6ME2iGG4bN+oeDQkFVL2k5WwD3P3Uw8/hmppIoW/Ca1t7sveylWf9wm0IBVbcHpGlkCuvZ3UDrafXNvtmuq2ZWXC4pFFAjM4g2MoV1+VxZcw3VOmezA+XqzbZqZr1DUWdh9SKbmJiIycnJbmej7ZZtvCvzAT57sZpGVD/oRxcM88qvjzJ9/MRfKZ8Tak+ZXd7mB79Z75O0KyImam1zSaGAstoDxlt8GM/uzZNWGli19b6aA+U279zLkaPHPR+RWZ9zm0IBpdXR3/yeFTywcXWuD+G0doVDh6fbPqrazIrHJYUCyruOPmsW0mZ7LbnbqVl/cVAoqDwHb2XNpZQ2xcSpw/NOGrEM7nZq1m8cFAZQ1mCztFIKtL5ms5n1DgeFAVRvsFlWKcW9j8z6W25BQdJtwKXASxHxpiRtM/BXQHk47t9ExDeTbZuAq4BjwPsj4u688lZ07V5QZ7ZWZyH1fERm/S/PksI/Av8A/K9Z6Z+KiE9UJ0g6H1gHLAfOAr4t6dyIyB7BVRDtfIh3YilKDzYzszS5BYWI+K6kpQ3ufhlwZ0QcAZ6VtA+4EHgwr/y1SzMP8UaCR1oj8DVtXsDeb/1mVks3xim8T9Kjkm6TtDBJGwd+XLXP/iTtJJLWS5qUNHnwYPakcJ3Q6KpojS6pmdXFs5llOHfsnmLV1vtYlqyfMJelO81scHQ6KHwGeAOwAjgAfDJJP3li/5SpeiLiloiYiIiJsbGxXDLZjEanjU4LHpt37p3x8B5dUHvhm+pj6g0Yy2NNZzMbDB0NChHxYkQci4jjwGcpVRFBqWRwdtWui4EXOpm3VjW6KlrWSOHqh/crvz7K8FCtGFn/XGV5rOlsZoOho0FB0qKqX98NPJ583gmskzRf0jLgHODhTuatVbWmpBCl1dKqNTrIa/p48NrXnMJ4xv71zuVFb8ysVbkFBUlfpNRQfJ6k/ZKuAj4u6TFJjwIXAdcCRMReYDvwBPAt4Opu9zxqtE5+7cpx/uQt4zPqvwL48q6pGcc0s77Bzw9P88DG1dz8nhUtrVPQyprOZmaQb++j99ZIvjVj/y3Alrzy04xmu4Xe/9TBkxpAytU15f1rdQN99TdHM6eOaLXraKvjEMzMPKK5hqw6+VoP5Eara2pNX53Hw9vjEMysVQ4KNdR7yM8ebzC6YLilyeLKD+nrv763cvz8U07U6M1lIJvHIZhZKxwUasiaG6jWg3p4nhgeEtPHZq5k1ugb/6+nj1c+Hzo8XXnwN1NiyXtqDDMbDF5kp4ZajcLDQ+JXR45yzbY9Jz2oq3sMidLqaI0ul5n14G+0WsrjEsysXVxSqGF2nXx5TeNDh0+uIir7+eFp9lz3R03/rawHf73ZTMuabQMxM0vjkkKKtSvHeWDjap7d+g4WvOaUGYvc15LWflCva2tW99G0ZTlnV0t5XIKZtYuDQgPqPVzT2g8aqdbJevCvXTnODZdfULdayuMSzKxdXH2Uodx4m1VGGM9o1G1mxtO0RuJGehF5XIKZtYuDQopaYwiqjQwP1W1MbmTGU5h791GPSzCzdnFQSFHrLb8sq3RQLa2huKydjcEel2Bm7eCgkCLtLV/AAxtXZx5brnaaOnQYkTIHeJ2/Y2bWDW5oTtFq42114zKUAkLWRNj11k8wM+ukgSwpZI3+zXrLb6Txtla1UwCjI8P86jdHZ4x6Bnjl10fZsXvKVT9mVggDFxSy5hMCZmwrv+UHjbcjpFUH/fzwNL81MnzSALjp4+FBZmZWGAMXFOqtSlbrLb8cEG68+2mu3bYns3dP1ihkDzIzs6IbuDaFrAdz2rZyaaKRuYVqzps0T7z6m6OpDc4eZGZmRTFwQSGrATlt25DU8JrHs0chj44Mg6g5tTZ4kJmZFcvABYWsaSXSth2L2u/4aSWL6nmTXjv/lJMal8uamU3VzKwTBq5NoZHRv7O3lXsjzdZItc9cxjuYmXXawAUFyB79m7at1bmFGp3+2sysCAau+qgVjc5WWkuj01+bmRXBQJYUWjG72qncyNzIWsnVx3myOjMrMgeFBmUNemskMDgImFkvyK36SNJtkl6S9HhV2mmS7pH0TPLvwqptmyTtk/S0pDV55atV9Qa9mZn1gzzbFP4RuHhW2kbg3og4B7g3+R1J5wPrgOXJMZ+WNESBeDSymQ2C3IJCRHwX+Nms5MuA25PPtwNrq9LvjIgjEfEssA+4MK+8tcJLXprZIOh076MzI+IAQPLvGUn6OPDjqv32J2knkbRe0qSkyYMHD+aa2WruRWRmg6AoXVJrLTlQcxhwRNwSERMRMTE2NpZztk6YS7dUM7Ne0eneRy9KWhQRByQtAl5K0vcDZ1fttxh4ocN5q8u9iMys33W6pLATuDL5fCXwtar0dZLmS1oGnAM83OG8mZkNvNxKCpK+CLwVOF3SfuA6YCuwXdJVwPPAFQARsVfSduAJ4ChwdUQcq3liMzPLTW5BISLem7LpbSn7bwG25JUfMzOrrygNzWZmVgAOCmZmVqFIWUCmF0g6CPyoiUNOB36aU3Y6xddQDP1wDdAf1+FraN7vRETNPv09HRSaJWkyIia6nY+58DUUQz9cA/THdfga2svVR2ZmVuGgYGZmFYMWFG7pdgbawNdQDP1wDdAf1+FraKOBalMwM7Nsg1ZSMDOzDA4KZmZW0TdBoR+W/0y5hs2SpiTtSX4uqdpWxGs4W9L9kp6UtFfSB5L0XrsXadfRM/dD0qmSHpb0SHIN1yfpPXMvMq6hZ+5DmaQhSbslfSP5vZj3ISL64gf4D8Cbgcer0j4ObEw+bwT+Lvl8PvAIMB9YBvwQGCroNWwG/kuNfYt6DYuANyefXw/8c5LXXrsXadfRM/eD0jolr0s+DwMPAb/fS/ci4xp65j5U5e2DwBeAbyS/F/I+9E1JIfpg+c+Ua0hT1Gs4EBE/SD7/EniS0ip6vXYv0q4jTeGuI0peSX4dTn6CHroXGdeQpnDXACBpMfAO4HNVyYW8D30TFFLMefnPgnifpEeT6qVyEbPw1yBpKbCS0ttdz96LWdcBPXQ/kiqLPZQWtLonInruXqRcA/TQfQBuBj4MHK9KK+R96PegkKbh5T8L4DPAG4AVwAHgk0l6oa9B0uuALwPXRMQvsnatkVbk6+ip+xERxyJiBaXVDC+U9KaM3XvpGnrmPki6FHgpInY1ekiNtI5dQ78HhRdVWvYT9eDynwAR8WLyP8Vx4LOcKEYW9hokDVN6kN4REV9JknvuXtS6jl68HwARcQj4DnAxPXgvYOY19Nh9WAW8S9JzwJ3Aakmfp6D3od+DQs8v/1n+jybxbqDcM6mQ1yBJwK3AkxFxU9WmnroXadfRS/dD0pik0eTzCPB24Cl66F6kXUMv3YeI2BQRiyNiKbAOuC8i/oyi3odutsa38wf4IqVi5DSlSHsV8K+Be4Fnkn9Pq9r/v1Jq1X8a+ONu5z/jGv438BjwKKX/WBYV/Br+PaWi7qPAnuTnkh68F2nX0TP3A/h3wO4kr48DH03Se+ZeZFxDz9yHWdfzVk70PirkffA0F2ZmVtHv1UdmZtYEBwUzM6twUDAzswoHBTMzq3BQMDOzCgcFszaStKhqFswVs2bvvLQ8y6dZUTkomLXXBymNsIXSFAyXVG27i9LI1gWdzpRZozxOwawFkj4G/DQi/j75fQvwInAN8G8pDXzbB4wAU8ANEbFN0qeAByNie1cyblaHSwpmrbmVZIoCSfMoTV/wAPBylKY8/g3wUWBbRKyIiG3JcZPAH3Qjw2aNOKXbGTDrRRHxnKR/kbQSOJPSVAzzgYN1Dn0JOCvv/Jm1ykHBrHWfA/4S+G3gNuAwcGqdY05N9jMrJAcFs9Z9FfhbSquB/UdKD/ylVdt/SWkpz2rncmJGT7PCcZuCWYuSdoP7ge1Rmtv/V8APJf2bZJf7gfOTheXfk6RdRKkXklkhufeRWYuSBuYfAFdExDNJ2ruBt0TER2rsfybwhYh4W2dzatY4lxTMWiDpfEpdTu8tBwSAiPgq8FzKYUuAD+WfO7PWuaRgZmYVLimYmVmFg4KZmVU4KJiZWYWDgpmZVTgomJlZxf8HkVumAC9mxiIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYUAAAEGCAYAAACKB4k+AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAAsTAAALEwEAmpwYAAAd5klEQVR4nO3df5DcdZ3n8eeLYQ7Gdb3AETFMkk0WY0pY1kTmKKs4r1y0LsiqRCi8eLsrW3LL3hWU68pFE3dL0S2OKIuu9wO34kqJtyLEI4YsoDkK8PakBG5CgBAwEg/UTLIhClnxHHNh8r4/+jtNZ9Ld093Tn29/v92vR1XXdH++32/nPd/55vv+fn58P19FBGZmZgAn9DoAMzMrDicFMzOrclIwM7MqJwUzM6tyUjAzs6oTex3AXJx22mmxZMmSXodhZlYq27dv/2lEzK+3rNRJYcmSJYyPj/c6DDOzUpH0o0bL3HxkZmZVTgpmZlblpGBmZlVOCmZmVuWkYGZmVaUefWSWypYdE9ywbTf7Dk1yxrwR1q5azuqVo70Oyyw5JwWzGbbsmGD95p1MHpkCYOLQJOs37wRwYrC+5+Yjsxlu2La7mhCmTR6Z4oZtu3sUkVl+nBTMZth3aLKtcrN+4qRgNsMZ80baKjfrJ04KZjOsXbWckeGhY8pGhodYu2p5jyIyy487ms1mmO5MLuLoI4+KstScFMzqWL1ytHAnW4+Ksjy4+cisJDwqyvLgpGBWEh4VZXlInhQkDUnaIemu7POpku6V9Ez285SadddL2iNpt6RVqWMzKxOPirI85FFT+BPg6ZrP64D7ImIZcF/2GUlnAWuAs4ELgZskDWFmgEdFWT6SJgVJC4HfBf6mpvhi4Jbs/S3A6pry2yLicEQ8C+wBzksZn1mZrF45yvWXnMPovBEEjM4b4fpLznEns3VV6tFHfwV8FPj1mrLTI2I/QETsl/TarHwUeKhmvb1Z2TEkXQlcCbB48eIEIZsVVxFHRVl/SVZTkPQu4PmI2N7qJnXK4riCiI0RMRYRY/Pn133utJmZdShlTeF84D2SLgJOBl4j6W+BA5IWZLWEBcDz2fp7gUU12y8E9iWMz8zMZkhWU4iI9RGxMCKWUOlAvj8ifh/YClyerXY5cGf2fiuwRtJJkpYCy4BHUsVnZmbH68UdzRuATZKuAH4MXAYQEbskbQKeAl4GroqIqcZfY2Zm3aaI45rtS2NsbCzGx8d7HYaZWalI2h4RY/WW+Y5mMzOrclIwM7MqJwUzM6tyUjAzsyonBTMzq3JSMDOzKicFMzOrclIwM7MqJwUzM6tyUjAzs6pezH1kZj22ZccEN2zbzb5Dk5wxb4S1q5b7OQ0GOCmYDZwtOyZYv3knk0cq801OHJpk/eadAE4M5uYjs0Fzw7bd1YQwbfLIFDds292jiKxInBTMBsy+Q5NtldtgcVIwGzBnzBtpq9wGi5OC2YBZu2o5I8NDx5SNDA+xdtXyHkVkReKOZrMBM92Z7NFHVo+TgtkAWr1y1EnA6nJSsL7m8fhm7XFSsL7l8fhm7XNHs/Utj8c3a5+TgvUtj8c3a5+TgvUtj8c3a5+TgvUtj8c3a587mq1vDdJ4fI+ysm5xUrC+Ngjj8T3KyrrJzUdmJedRVtZNTgpmJedRVtZNyZKCpJMlPSLpcUm7JH0qK79W0oSkx7LXRTXbrJe0R9JuSatSxWbWTzzKyropZU3hMHBBRLwJWAFcKOkt2bLPR8SK7HUPgKSzgDXA2cCFwE2Shup8r5nV8Cgr66ZkHc0REcAvso/D2SuabHIxcFtEHAaelbQHOA/4XqoYzXqtG6OGBmmUlaWXdPRRdqW/HXg98F8j4mFJ7wSulvQBYBy4JiJeBEaBh2o235uVzfzOK4ErARYvXpwyfLOkujlqaBBGWVk+knY0R8RURKwAFgLnSfot4IvAmVSalPYDN2arq95X1PnOjRExFhFj8+fPTxK3WR48asiKKJfRRxFxCPgOcGFEHMiSxVHgS1SaiKBSM1hUs9lCYF8e8Zn1gkcNWRGlHH00X9K87P0I8A7g+5IW1Kz2XuDJ7P1WYI2kkyQtBZYBj6SKz6zXPGrIiihlTWEB8ICkJ4D/DdwbEXcBn5W0Myv/HeBPASJiF7AJeAr4NnBVREzV/2qz8vOoISsiVQYJldPY2FiMj4/3OgyzjnnOIusFSdsjYqzeMs99ZNZDHjVkReNpLszMrMpJwczMqpwUzMysyknBzMyqnBTMzKzKScHMzKqcFMzMrMpJwczMqpwUzMysyknBzMyqnBTMzKzKScHMzKqcFMzMrMpJwczMqjx1tpmVSj88g6LIv4OTgpmVxpYdE6zfvJPJI5WHMk4cmmT95p0AhTmpzqbov4Obj8xysGXHBOdvuJ+l6+7m/A33s2XHRK9DKqUbtu2unkynTR6Z4oZtu3sUUfuK/ju4pmCWWNGvDMtk36HJtsqLaK6/Q+qmJ9cUzBJr9crQtYnZnTFvpK3yIprL7zB9gTFxaJLglQuMbh4rTgpmibVyZZjHf/Z+sHbVckaGh44pGxkeYu2q5T2KqH1z+R3yaHpyUjBLrJUrw6K3MxfF6pWjXH/JOYzOG0HA6LwRrr/knFI1w83ld8ij+cx9CmaJrV21/Jg+BTj+yrAf2srzsnrlaKmSQD2d/g5nzBthos4x0c3mM9cUzLpsZt8AMOuVYT+0lc/GfSZzl0fzmWsKZl3UaKTR9Zecw4PrLmi4XSu1iTLzCKzumN5XKUcftZwUJP0a8KuImJp1ZbMB1axvoNl/3Dz+s/dSp/vFjpe6+axhUpB0ArAG+D3gnwOHgZMkHQTuATZGxDPJIrPCKPIt+UUzl76Bfmgrb8R9JuXRrE/hAeBMYD3wuohYFBGvBd4KPARskPT7OcRoPeShku0ZhL6BTni/lEezpPCOiPiLiHgiIo5OF0bECxFxR0RcCtzeaGNJJ0t6RNLjknZJ+lRWfqqkeyU9k/08pWab9ZL2SNotaVU3fkGbGw+VbE8/jKNPwfulPBomhYg4MtvGs6xzGLggIt4ErAAulPQWYB1wX0QsA+7LPiPpLCrNVWcDFwI3SRqq98WWH1f729MP4+hT8H4pj2Z9Cr8NbARGgW8BH4uIF7Nlj0TEec2+OCIC+EX2cTh7BXAx8Las/BbgO8DHsvLbIuIw8KykPcB5wPc6+cWsO/IYF91v+rlvYC68X8qhWfPRTcC1wDnAD4DvSjozWzbcypdLGpL0GPA8cG9EPAycHhH7AbKfr81WHwV+UrP53qxs5ndeKWlc0vjBgwdbCcPmwNV+s8HSLCm8OiK+HRGHIuIvgauBb2dNQNHKl0fEVESsABYC50n6rSarq95X1PnOjRExFhFj8+fPbyUMmwNX+80GS7P7FCTpn0bEPwJExAOSLgXuAE5t5x+JiEOSvkOlr+CApAURsV/SAiq1CKjUDBbVbLYQ2NfOv2NpFK3a7yGyZuk0qyl8BnhjbUFEPAG8Hdg82xdLmi9pXvZ+BHgH8H1gK3B5ttrlwJ3Z+63AGkknSVoKLAMeafk3sYHgIbJmaTWsKUTErQ3Kfwz8UQvfvQC4JRtBdAKwKSLukvQ9YJOkK4AfA5dl37tL0ibgKeBl4CrfPW0z+c5Ys7SajT56FZV+hAD+M5XhopdQudr/dET8otG2UK1VrKxT/jMqtY1621wHXNdq8DZ4PETWLK1mzUdfAU4HlgJ3A2PAX1LpEP5i8sjM6vCdsWZpNetofkNEvE+SgP1U7nAOSf8LeDyf8MyO1e+ziZr12qyzpGaJ4J7sZrTpzy0NSTXrtn6fTdSs15olhXFJr46IX0TEB6cLsxvYXkofmll9RRsia53x0OJiajb66N82KP+hpLemC8nM+p0fulNcHT2Oc7opycysE559t7j8jGYzy52HFheXn9FsZrlrd/Zd9z/kp+WaQu3DcMzM5qKd2XfnMrXJlh0TnL/hfpauu5vzN9zv6VBa0E7z0X3JojCzgdLO7Lud9j94nqzOtNN8VG9qazPrkkFrIml1aHGn/Q+eJ6szTZOCpA9MvwVOqflMRHw1ZWBmg8RDNBvr9Ol/7szuzGzNR0uz1xLgpOzn9GcrMbe1FouHaDa2dtVyhk84tqFi+ATNOrWJ58nqTNOaQkR8avq9pIsj4tPpQ7LUfFVaPHlc1Za6eWpm43ULjdmeJ6sz7XQ0u0+hT/iqtHhSX9WWudP1hm27OTJ17P2yR6aipeP1pBNfOcWd8qphP0q2Be0khT9IFoXlym2txdPOEM1OFPlCYLamzE6O1+kkeGjySLXsV0eOdifgPtdyUoiIJ1MGYvlxW2vxtDNEsxNFvRBopQbTyfFa5CRYdL6jeQC5rbWYUs7+2ukIntRaGTbayfFa1CRYBk4Kc1DWjrsyPJOgrPu2qIp6IdDKybuT47WoSbAMZk0Kki6LiG/MVjZoyj6Cp8jPJCj7vi2iol4ItHrybvd4LWoSLAPNNgu2pEcj4s2zlfXC2NhYjI+P9+TfPn/D/XUP5tF5Izy47oIeRNQ/vG8Hx8wLAKicvLvRn+LaZmOStkfEWL1lDWsKkt4JXASMSvpPNYteA7zc3RDLx22W6XRj3/qEUA4pazBFrg0XWbPmo33AduA92c9pLwF/mjKoMnCbZTpz3bdufioXn7yLpeGQ1Ih4PCK+Arw+Im6peW2OiBfzC7GYUo8rH2Rz3bcejmjWuYZJQdLfSXp3g2W/KenTkj6YLrRiSz2ufJDNdd+6ac+sc82aj/4I+AjwV5JeAA4CJ1OZDO+HwH+JiDuTR1hgrvamM5d966Y9s841TAoR8Q/AR4GPSloCLAAmgR9ExC/zCc+sfR6OaNa5Vu5TuBr424h4Ln04ZnNX1DH5ZmXQyh3NrwPGJT0K3Axsi9lubgAkLQK+mm1/FNgYEV+QdC2VpqmD2aofj4h7sm3WA1cAU8CHImJbm7+PGeCmPbNOzTohXkT8ObAM+DLwh8Azkv6jpDNn2fRl4JqIeCPwFuAqSWdlyz4fESuy13RCOAtYA5wNXAjcJGmo3hebmVkaLc2SmtUM/iF7vQycAvx3SZ9tss3+iHg0e/8S8DTQ7NLtYuC2iDgcEc8Ce4DzWvotzMysK2ZNCpI+JGk78FngQeCciPj3wLnApa38I1lH9Urg4azoaklPSLpZ0ilZ2Sjwk5rN9lIniUi6UtK4pPGDBw/OXGxmZnPQSk3hNOCSiFgVEd+IiCMAEXEUeNdsG0t6NXAH8OGI+DnwReBMYAWwH7hxetU6mx/XdxERGyNiLCLG5s+f30L4ZmbWqlk7miPiE02WPd1sW0nDVBLC1yJic7bNgZrlXwLuyj7uBRbVbL6QylQbNgvP82Nm3ZLseQqSRKVz+umI+FxN+YKI2J99fC8w/US3rcCtkj4HnEGlc/uRVPGllteJ2vP85MsJ2PpdyofsnE/luc47JT2WlX0ceL+kFVSahp4D/hggInZJ2gQ8RaUz+6qImKKE8jxRt/LkKusOJ2AbBMmSQkR8l/r9BPc02eY64LpUMeUlzxO15/nJjxOwDYKWhqRae/I8UXfyUHPrjBOwDQI/ozmBPCdkSznPTxnbz1PG7In2eq+Mx2TZuKaQQJ7PWkg1hfd0+/nEoUmCV9rPt+yY6ErcKWzZMcHabzx+TMxrv/F412Lu1TM0tuyY4PwN97N03d2cv+H+Qv8NUirjMVlGrikkkPeEbCnm+Slj+/m1W3dx5Oixt7YcORpcu3VX1x7vCPCpv9vFi788AsBJJ6a9rnLn9ivKeEyWkZNCImWfkK2M7eeHJo+0Vd6pXx05esx3pzxJF+lE2OummzIek2Xk5iOryx3Y9eX9qM+inAiL0HTjYzIfA1lT6PUVTxmkflBNir/BKa8arjbrzCzvNL6JQ5MMSUxFMNqgoxnSnaSL0rldhBqLH56Uj4GrKRThiqcMUj6DOtXf4JPvPpvhoWNvjRkeEp9899kdxwcwlT0+ZOLQZN0bbyDdSbpXndszFaHG4uei52PgagpFuOIpi1T9Iqn+Bt3q4K8X37SgckdmbXd2ypP06pWjjP/oBb7+8E+YimBI4tJz8++vKkqNpex9dWUwcEmhCFc8gy7l36AbJ43Z4ggqV6l5ND9u2THBHdsnqrWVqQju2D7B2G+cmuvJ0U03g2PgkkJRrngGWdH/Bo3imzY6b4QH112QSyxFqdn6udeDY+D6FIrSRjvIiv43qBfftLzjLFLNdvXKUR5cdwHPbvhdHlx3gRNCnxq4moKveHqv6H+D2vhmjj7KO86i16qs/yjiuIeblcbY2FiMj4/3OgyzZGbe0QyV2opH3dhcSNoeEWP1lg1cTcGsTIpeq7L+46SQmG+Us7nyMEzLk5NCQp7MzMzKZuBGH+Up73lyzMzmykkhoSINJzQza4WTQkKe1dHMysZJIaGi36TVDX4qmFl/cUfzHDUbXdTvwwndkW7Wf5wU5qCVk2I/Dycsyrw8ZtY9bj6ag0EfXeSOdLP+46QwB4N+UnRHuln/cVKYg0E/KZahI90d4WbtcVKYgzKcFFMq+uMRi/zoVScrKyp3NM9Bv48uakXKjvS5zhtV1I5wj9qyIkuWFCQtAr4KvA44CmyMiC9IOhW4HVgCPAe8LyJezLZZD1wBTAEfiohtqeLrln4eXdRL3ThxFrXPp6jJygzSNh+9DFwTEW8E3gJcJeksYB1wX0QsA+7LPpMtWwOcDVwI3CSp/uOvrO91Y2RXUft8ipqszCBhUoiI/RHxaPb+JeBpYBS4GLglW+0WYHX2/mLgtog4HBHPAnuA81LFZ8XWjRNnUft8ipqszCCnPgVJS4CVwMPA6RGxHyqJQ9Jrs9VGgYdqNtublc38riuBKwEWL16cMOr8lenZC6lj7cZjKIva57N21fK6T1PrdbIygxySgqRXA3cAH46In0tquGqdsuOeFRoRG4GNUHkcZ7fi7LVudj6mPmHn0VHarRNnEft8ipqszCBxUpA0TCUhfC0iNmfFByQtyGoJC4Dns/K9wKKazRcC+1LGVyTd6nxMfcLesmOCazY9ztSMZ3t3u6O030+cRUxWZpB29JGALwNPR8TnahZtBS4HNmQ/76wpv1XS54AzgGXAI6niK5pudT6mHNkynXBmJoRp3e4o9YnTLH8pawrnA38A7JT0WFb2cSrJYJOkK4AfA5cBRMQuSZuAp6iMXLoqIqaO+9Y+1agNfd6rhtv6npQjW+olnFruKDUrv5Sjj74bEYqI346IFdnrnoj4WUS8PSKWZT9fqNnmuog4MyKWR8S3UsVWRGtXLWd46PhulV/86uW27nZNObKlWWJxR6lZf/A0FwWxeuUov/ZPjq+4HTkabY3NTzkMs1FiGZIKNb1Fpzz1hJmTQqH84+SRuuXtNP2knI+oUcK58X1v6ouEUNR5kszy5LmPCqQbY/MhXQdtP48I8tQTZhVOCm1IPf6/DDc19euIIE89YVbhpNCiPG7Y6vaVeJnukO61btXSzMrOSaFFeTUvdOtKPFUS69dEU4Zamlke3NHcojI1L0zfddzt50f3c2fs6pWjXHruKEPZNCxDEpee259NZWbNOCm0qCwzW6a867gb01kX1ZYdE9yxfaK636YiuGP7RF8kPLN2OCm0qKjTMM+U8q7jMtWW2tXPCc+sHU4KLSr684inpbzruCy1pU70c8Iza4c7mttQhuGYjUbRdOOu437ujPXoI7MK1xT6TMq7jstSW+pEWZoHzVJzTSFHeQznbPdeh3ZjKkNtqRP9fLe2WTsUDUaplMHY2FiMj4/3OoyWzLxvACpXor280i5iTGaWnqTtETFWb5mbj3JSxNEtRYzJzHrLSSEnRRzdUsSYzKy33KeQk7mObknRH+ERN2Y2k2sKOZnL6JZU00t4xI2ZzeSkkJO5DOdM1fbfz0NMzawzbj5KpFFzTycn3JRt//06xNTMOuOaQgLdbu7p5+klzKxYnBQS6HZzj9v+zSwvbj5KoNvNPb7b1szy4qSQQIqhnm77N7M8uPkoATf3mFlZuaaQgJt7zKysnBQScXOPmZWRm4/MzKwqWVKQdLOk5yU9WVN2raQJSY9lr4tqlq2XtEfSbkmrUsVlZmaNpawpfAW4sE755yNiRfa6B0DSWcAa4Oxsm5skDdXZ1szMEkqWFCLi74EXWlz9YuC2iDgcEc8Ce4DzUsVmZmb19aKj+WpJHwDGgWsi4kVgFHioZp29WdlxJF0JXAmwePHixKEWWx6P9zSzwZJ3R/MXgTOBFcB+4MasXHXWrfuc0IjYGBFjETE2f/78JEGWQarptM1ssOWaFCLiQERMRcRR4Eu80kS0F1hUs+pCYF+esZWNH6VpZinkmhQkLaj5+F5gemTSVmCNpJMkLQWWAY/kGVvZ+FGaZpZCsj4FSV8H3gacJmkv8EngbZJWUGkaeg74Y4CI2CVpE/AU8DJwVURM1flay/hRmmaWQrKkEBHvr1P85SbrXwdclyqefrN21XLWb955TBOS51cys7nyNBcl5fmVzCwFJ4US8/xKZtZtnvvIzMyqnBTMzKzKScHMzKqcFMzMrMpJwczMqhRRd4qhUpB0EPhRk1VOA36aUzjdVMa4HXM+yhgzlDPufo75NyKi7uRxpU4Ks5E0HhFjvY6jXWWM2zHno4wxQznjHtSY3XxkZmZVTgpmZlbV70lhY68D6FAZ43bM+ShjzFDOuAcy5r7uUzAzs/b0e03BzMza4KRgZmZVpU4Kkm6W9LykJ2vKTpV0r6Rnsp+n1CxbL2mPpN2SVhUo5hskfV/SE5K+KWleVr5E0qSkx7LXXxco5mslTdTEdlHNsp7v5yyOenHfXhPzc5Iey8qLsq8XSXpA0tOSdkn6k6y8sMd1k5gLe1w3ibnQx3WTuLt3XEdEaV/AvwTeDDxZU/ZZYF32fh3wmez9WcDjwEnAUuCHwFBBYv5XwInZ+8/UxLykdr2C7edrgf9QZ91C7OdGcc9YfiPwiYLt6wXAm7P3vw78INunhT2um8Rc2OO6ScyFPq4bxT1jnTkd16WuKUTE3wMvzCi+GLgle38LsLqm/LaIOBwRzwJ7gPPyiLNWvZgj4n9ExMvZx4eAhXnH1UyD/dxIIfYzNI9bkoD3AV/PNahZRMT+iHg0e/8S8DQwSoGP60YxF/m4brKfG+n5fobZ4+7GcV3qpNDA6RGxHyo7EHhtVj4K/KRmvb00Pwh65YPAt2o+L5W0Q9L/lPTWXgXVwNVZ08DNNc0ZZdnPbwUORMQzNWWF2teSlgArgYcpyXE9I+ZahT2u68RciuO6wb6e83Hdj0mhEdUpK9R4XEl/BrwMfC0r2g8sjoiVwEeAWyW9plfxzfBF4ExgBZU4b8zKC7+fM+/n2KupQu1rSa8G7gA+HBE/b7ZqnbKe7O9GMRf5uK4TcymO6ybHx5yP635MCgckLQDIfj6fle8FFtWstxDYl3NsDUm6HHgX8HuRNQZmVdWfZe+3U2nHfEPvonxFRByIiKmIOAp8iVeq0oXezwCSTgQuAW6fLivSvpY0TOU//NciYnNWXOjjukHMhT6u68VchuO6yb7uynHdj0lhK3B59v5y4M6a8jWSTpK0FFgGPNKD+I4j6ULgY8B7IuKXNeXzJQ1l73+TSsz/pzdRHmv6BJV5LzA9wqew+7nGO4DvR8Te6YKi7OusTfjLwNMR8bmaRYU9rhvFXOTjuknMhT6umxwf0K3jOu/e826+qFST9gNHqGTyK4B/BtwHPJP9PLVm/T+jkil3A+8sUMx7qLRXPpa9/jpb91JgF5VRD48C7y5QzP8N2Ak8QeU/zIIi7edGcWflXwH+3Yx1i7Kv/wWVZoknao6Hi4p8XDeJubDHdZOYC31cN4q7m8e1p7kwM7Oqfmw+MjOzDjkpmJlZlZOCmZlVOSmYmVmVk4KZmVU5KZh1kaQFku7K3q+YMcvmuyR9qnfRmc3OScGsuz5C5U5YqEyVcFHNsruB90h6Vd5BmbXK9ymYdUDSXwA/jYgvZJ+vAw4AHwbeSOUGoz3ACDABXB8Rt0v6PPC9iNjUk8DNZuGagllnvkw27YSkE4A1wIPAi1GZb+b/AZ8Abo+IFRExPR/NOJWZLM0K6cReB2BWRhHxnKSfSVoJnA7soPIAloOzbPo8cEbq+Mw65aRg1rm/Af4QeB1wMzAJnDzLNidn65kVkpOCWee+CXwaGAb+DZUT/pKa5S9ReWRirTfwysybZoXjPgWzDmX9Bg8Am6IyB///BX4o6fXZKg8AZ2UPTP/XWdnvUBmFZFZIHn1k1qGsg/lR4LLIHn8o6b3AuRHx53XWPx24NSLenm+kZq1zTcGsA5LOojLk9L6oeR5uRHwTeK7BZouBa9JHZ9Y51xTMzKzKNQUzM6tyUjAzsyonBTMzq3JSMDOzKicFMzOr+v+opb9Y+RVc5wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Lag plot\n",
    "from pandas.plotting import lag_plot\n",
    "\n",
    "for i in [1, 2, 4, 8, 12, 16, 20, 24, 28, 32]:\n",
    "    lag_plot(air.Passengers, lag=i)\n",
    "    plt.show() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "16f8765d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:47.710043Z",
     "start_time": "2022-11-15T06:34:46.342671Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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olIqIiIiISKf22cqdbMiv4NYT+uLnq4jU1vQTFxERERGRTqvR5eZf0zfRP64rpw3p4XQ5nZJCqYiIiIiIdFofLsslu6iK207si4+PcbqcTkmhVEREREREOqX6RjePT9/E0MQwThzY3elyOi2FUhERERER6ZTeWbyd3LIabp/YD2PUSuoUhVIREREREel0ahtcPPndZkalRnB0n2iny+nUFEpFRERERKTTeX3BNgoq6rhDraSOUygVEREREZFOpaqukadnbuGoPtGMSYtyupxOT6FUREREREQ6lVfmbaWkqp7bTuzrdCmCQqmIiIiIiHQi5TUNPDdrCycMiGV4coTT5QgKpSIiIiIi0om8OCeL3bWN3KpW0nZDoVRERERERDqF4so6Xp6bzWlDejAoPszpcsRDoVRERERERDqF52ZnUdPg4tYT+zhdijTj53QBIiIiIiJycFxuS3lNA6XV9ZRV11Na1UBJdT2Bfj6cPDiOQD9fp0tsd/J31zJ13lYmD0+gd2xXp8uRZhRKRURERETaMWst72bu4N3MHEqq6imtrqe8pgFr93x8XLcgbji2FxeMSiLIX+EUmn6Gd3+4CgvcfLxaSdsbhVIRERERkXZqV3ktd324kpkbChnYoxuD4rsRERJARIg/EV0CiAgJIDzEn0jP623F1TwxYxP3frKGp77fzPXH9OJXY5I7fTh9e/EOvltfwJ9OH0hKVBeny5GfMXZvf2JpQxkZGTYzM9PpMkRERERE2gVrLR8ty+W+T9bQ4LLcfWp/LhmTgo+POaBz52cV8/j0TSzMLiGmayDXHZ3GxWNSCA7ofOF0W3EVpzw+h+HJ4bx25ZgD+hlKyzPGLLHWZuxpn1pKRURERETakYKKWn7/0Wq+XZvPqNQIHjp3GKnRB966Z4xhfK9oxveKZoEnnN7/+TqenZXVFE7HJhMS0DliQKPLza3vLMfXx/DQucMUSNupzvE0ioiIiIh4gU9X7ORPH6+mqt7FH04bwBVH9MT3MILU2LQoxl4bxaLsEp6YsYm/fbGO52Zv4eYT+nLRqCT8fDv2YhzPzc5i6fYyHr8wnfjwYKfLkb1Q910REREREYeVVNXzx2mr+XxVHsOSwnnkvGH0jg1t8ftkbi3hn19vYFF2Cb1iunDPqQOY0D8WYzpeC+Lq3HImP/UDJw2O498XDe+Qn9Gb7Kv7rkKpiIiIiIiDlm4v5dpXMymvaeCWE/py3dFprdqCaa3l27X5PPDlerKKqhiXFsXvTxvA4ISwVrtnW6ttcHHGk3Mpr2ngm1uPJjwkwOmSOj2NKRURERERaYcaXG5+994KAv18+fSmMfSP69bq9zTGMHFQHMf1j+XNhdv51/SNnP7kXM4ensAdJ/XrEN1c//nVBjYVVDL1ytEKpF5gv3+CMcYEGWMWGWNWGGPWGGP+7NkeaYz51hizyfM9otk5dxtjNhtjNhhjTmrNDyAiIiIi4q2mztvKlsIq/jp5UJsE0ub8fX2YMj6VWXcex/XH9OKzVXkc9/BMHvp6PRW1DW1aS0v6YXMRL/+QzWXjUjimb4zT5cgBOJB+AXXABGvtMCAdONkYMxa4C5hhre0DzPC8xxgzELgQGAScDDxtjOl8c0+LiIiIiOxDYUUdj0/fxLH9YpjQv7tjdXQL8ueuU/rz3e3HcPLgOJ76fgvHPzKL7cXVjtV0qMprGrjjvRWkRXfh7lMGOF2OHKD9hlLbpNLz1t/zZYFJwFTP9qnAZM/rScDb1to6a202sBkY3ZJFi4iIiIh4u4e/3kBto4s/nj7Q6VIASIwI4fELh/PRr8dT1+jmqqmLva7F9N6PV1NQUcdjF6R3yjVZvdUBjaA2xvgaY5YDBcC31tqFQHdrbR6A53us5/AEYEez03M8235+zWuNMZnGmMzCwsLD+AgiIiIiIt5lxY4y3l2ygyuO6EmvmJafZfdwDE+O4JmLR5BdVMVv31qGy+38xKgH4rOVO5m2fCc3TejNsKRwp8uRg3BAodRa67LWpgOJwGhjzOB9HL6nuZZ/8SRba5+31mZYazNiYtTXW0REREQ6B7fbct+na4jqEshNE3o7Xc4eje8dzX1nDuL7DYX844t1TpezX7vKa/n9R6sZlhTOb45rnz9T2buDmmvaWlsGzKRprGi+MaYHgOd7geewHCCp2WmJwM7DLVREREREpCOYtjyXZdvLuOuU/nQN8ne6nL26ZGwKU8al8OLcbN5ZvN3pcvaqtsHFda9l0uhy89j5w/BvxeV0pHUcyOy7McaYcM/rYOAEYD3wCTDFc9gU4GPP60+AC40xgcaYnkAfYFEL1y0iIiIi4nUq6xr5x5frGZYUztnDfzHCrd354+kDOapPNH+YtpqFWcVOl/ML1lru+mAlK3LKeeyCdNLaWVdoOTAH8meEHsD3xpiVwGKaxpR+BjwAnGiM2QSc6HmPtXYN8C6wFvgK+I211tUaxYuIiIiIeJN/f7eZwoo6/nzmIHx89jTqrX3x8/Xh378aQVJkCNe/vqTdzcj77Kwspi3fyR0T+zJxUJzT5cghMtY6P3A5IyPDZmZmOl2GiIiIiEiryS6qYuJjs5iUnsDD5w1zupyDkl1UxeSnfiC2ayAf/np8u+h2PGNdPle/mslpQ3rw5EXDMab9h/zOzBizxFqbsad96nAtIiIiItIG7v9sLYF+vtx5cj+nSzloPaO78MzFI8hqJzPybsyv4Oa3lzM4PoyHzh2mQOrlFEpFRERERFrZ9xsKmLG+gN8e35vYrkFOl3NIms/I+8CXzs3IW1pVz9VTMwny9+X5y0ZqPdIOwM/pAkREREREOrL6Rjd//XQtadFduHx8T6fLOSyXjk1hU34FL8zJpk/3rpyfkbT/k1pQg8vNb95cyq7yWt6+biw9woLb9P7SOhRKRURERERa0SvzsskqquI/V4wiwM/7Oyr+6fSBZBVW8fuPVhHbNZBj+8W22b3v/2wt87YU8/B5wxiRHNFm95XW5f3/VYiIiIiItFMFFbU8MWMzx/eP5bg2DG+tyc/Xh6cuHkHf7l257rUlLGijpWLeXLidqfO3cc1RPTl3ZGKb3FPahkKpiIiIiEgrefSbjdQ1uvjD6QOdLqVFhQX78+qVo0mKDOGqVxazfEdZq95vYVYxf/p4Ncf0jeGuUwa06r2k7SmUioiIiIi0go35FbybuYPLxqXSM7qL0+W0uKjQQF6/agxRoYFc9tJC1u7c3Sr3WbGjjBveWEpyVAhPXDQcXy9Y31UOjkKpiIiIiEgrePDL9XQJ9OPG43o7XUqriQsL4o2rxxAS4MelLy1kS2Fli127sKKOO99fweSnf8DPx/DiZRmEBTu/Pqq0PIVSEREREZEWNn9LMTPWF/DrY3sT0SXA6XJaVVJkCG9cMwZj4OIXFrKjpPqwrtfgcvPinCwmPDyTj5blcs1Racy4/RjSYkJbqGJpbxRKRURERERakNtt+ceX6+gRFsQVR6Q6XU6b6BUTymtXjaGmwcXFLy4kf3ftIV1nzqZCTnl8Dvd/vo4RKRF8dcvR3HPqALoGqYW0I1MoFRERERFpQZ+vymNlTjm3T+xHkL+v0+W0mQE9ujH1ytEUV9Zx8YsLKa6sO+BztxdXc+2rmVz60iIaXG5empLBK1eMopdaRzsFrVMqIiIiItJC6hvdPPT1BvrHdeWs4QlOl9Pm0pPCeenyUUx5eRGXvrSIt64d+4txoLUNLkqr6ymtaqCsup4fthTxwpxs/HwMd57cj6uO7EmgX+cJ86JQKiIiIiLSYt5YuI3tJdVMvXJ0p50ldmxaFM9dOpJrXs3k7Kd/IC4s6KcAWlJdT22D+xfnTE6P565TBhAXFuRAxeI0hVIRERERkRawu7aBJ2Zs4ojeURzdJ9rpchx1bL9YnvrVCP41fRM19S56hAUxML4bESH+hIcEEBESQGSXptfxYcEkR4U4XbI4SKFURERERKQFPDtzC6XVDdx9ygCM6ZytpM1NHBTHxEFxTpchXkATHYmIiIiIHKa88hpempvN5PR4BieEOV2OiFdRKBUREREROUyPfrMRa+H2if2cLkXE6yiUioiIiIgchvW7dvPB0hwuG5dCUqTGRoocLIVSEREREZHD8OCX6wkN9OPGCb2dLkXEKymUioiIiIgconmbi/h+QyG/Oa434SEBTpcj4pUUSkVEREREDoHbbfnHl+tJCA9myvhUp8sR8VoKpSIiIiIih2Da8lxW5ZZz24l9CfL3dbocEa+lUCoiIiIicpCyCiv508drGJ4czuThCU6XI+LV/JwuQERERETalsttWZhdzKb8SuoaXdQ1uKl3ualrdFPX4Gp63eCmzuUmMSKYKeNSiQ8PdrrsdqO6vpEbXl+Kv6/hqV+NwNfHOF2SiFdTKBURERHpJNbl7Wbaslw+Xr6TXbtr/2efMRDo50Ogny+Bfj4EeL6+Wr2Ll+ZkMyk9geuPSaNP964OVd8+WGu5+8NVbCyo4NUrRyusi7QAhVIRERGRDiyvvIZPlu/ko2W5rN9VgZ+P4Zi+Mfz+tAGM6xVFkH9TCPXzMRjzyxa/nNJqXpyTzTuLd/DB0hxOGBDL9cf0IiM10oFP47zXF2zj4+U7uf3EvhzVJ8bpckQ6BGOtdboGMjIybGZmptNliIiIiHQI1fWNfL4yj2nLc5m3pRhrYXhyOGcNT+C0IT2ICg086GuWVNXz6vytvDJvK2XVDWSkRHD9Mb2Y0D8Wn07SfXXZ9lLOf24+R/WJ4cXLMjrN5xZpCcaYJdbajD3uUygVERER6Thcbsu5z85j2fYyUqJCmJyewOThCfSM7tIi16+ub+SdxTt4cU42uWU19O0eyg3H9uLMYQkdemxlcWUdpz85F18fw+c3HUVYiL/TJYl4lX2FUnXfFREREelAXp2/lWXby/jH2UO4cFTSHrvkHo6QAD+uOKInl4xN4bOVO3luVha3vrOCZ2Zu4faJ/Zg4sHuL39NpLrfl5reXU1xVz4c3jFcgFWlhWhJGREREpIPILavhoa83cGy/mFYJpM35+/pw1vBEvvjtUTz1qxE0uizXvbaEyU/P44fNRa12Xyf8a/pG5m4u4q+TBjE4IczpckQ6HIVSERERkQ7AWssfp63GWvjrpMFt1lrp42M4bWgPvrn1aP55zlAKd9dy8YsLufjFBSzbXtomNbSm79bn8+R3m7kgI4kLRiU7XY5Ih6RQKiIiItIBfLFqF9+tL+D2iX1Jigxp8/v7+fpw/qgkvrvjWP50+kDW51Vw1tPzuObVTDbsqmjzelrCjpJqbnl7OYPiu/HnSYOcLkekw9pvKDXGJBljvjfGrDPGrDHG3OzZfp8xJtcYs9zzdWqzc+42xmw2xmwwxpzUmh9AREREpLMrr27g3k/WMCQhjMvHpzpaS5C/L1ce2ZNZdx7H7Sf2ZcGWYk5+fDb3fLSK+ka3o7UdjNoGF9e/vgSAZy4eSZC/r8MViXRcBzLRUSNwu7V2qTGmK7DEGPOtZ99j1tqHmx9sjBkIXAgMAuKB6caYvtZaV0sWLiIiIiJNHvhqHaXV9bxyxSj8fNtHR7jQQD9uOr4Pl4xN4cnvNvPyD9nsKKnmmUtGEhrYvufabHS5ue3d5azZuZuXL88gOartW55FOpP9/l/LWptnrV3qeV0BrAMS9nHKJOBta22dtTYb2AyMboliRUREROR/Lcwq5q1FO7jqyJ7tchKeiC4B/OmMgTx07lDmbSnmoucXUFhR53RZe9XocnPzO8v5YtUu/nDaACb07+50SSId3kH9Kc0YkwoMBxZ6Nt1ojFlpjHnZGBPh2ZYA7Gh2Wg57CLHGmGuNMZnGmMzCwsKDr1xERESkk6ttcHH3R6tIigzmlhP6OF3OPp2XkcQLl41kU0EF5z47j23FVU6X9AuNLje3vruCz1fmcc+p/bn6qDSnSxLpFA44lBpjQoEPgFustbuBZ4BeQDqQBzzy46F7ON3+YoO1z1trM6y1GTExMQdbt4iIiLQz1v7in3tpZU/P3EJWYRV/mzyEkID23SUWYEL/7rx5zVjKaxo455l5rM4td7qknzR12V3Bpyt2cvcp/bn26F5OlyTSaRzQ/72MMf40BdI3rLUfAlhr85vtfwH4zPM2B0hqdnoisLNFqhUREZE2V1nXyM1vLWP9rgoa3W5cbkuj2+Jyeb67LS7b9H1gj26cNTyBM9Pj6d4tyOnSO7SN+RU8M3MzZw1P4Oi+3vMH/hHJEbx//XimvLyIC56bz7OXjuSoPs7W3+hyc/t7K/hkxU7uOqU/1x2jQCrSlsz+/qppmha5mgqUWGtvaba9h7U2z/P6VmCMtfZCY8wg4E2axpHGAzOAPvua6CgjI8NmZmYe7mcRERGRFtbocnPV1Ezmbi7ijKE9CPL3xcfH4Odj8P3puw9+PgaLZe7mYlbsKMMYOKJXNGcNT+CkwXHtfmIbb+N2W857bj5bCiuZcdsxRIUGOl3SQcvfXcuUlxexpbCSh88bxqT0fU1Z0npcbsvt7y5n2vKd3HlyP359bG9H6hDp6IwxS6y1GXvadyD/QhwBXAqsMsYs92y7B7jIGJNOU9fcrcB1ANbaNcaYd4G1NM3c+xvNvCsiIuJ9rLX8YdpqZm0s5O9nDeFXY5L3e87vToKswkqmLd/JtGW53P7eCn4/bRUTB8Zx1ogEjuod3W5mh/Vmby7azpJtpTx83jCvDKQA3bsF8c5147jm1Uxufns5hRV1bT6G0+W23PHeCqYt38nvTlIgFXHKfltK24JaSkVERNqff3+3iYe/2chvjuvF707qf9DnW2tZur2Uj5bl8tnKPMqqG4gODeC6o3tx1ZE98fHZ0zQUsj+7yms58dFZDE0K4/WrxtDUqc171Ta4uOXt5Xy1ZhfXHp3GXSf3b5Nnw+W2/O69FXy4LJc7Jvblxgnte6IoEW+3r5ZShVIRERH5hY+W5XDrOys4a3gCj54/7LCDT32jm1kbC3l9wTZmbSzkmL4xPHL+MKK9tJXPKdZarnttCbM2FvL1LUeTGt3F6ZJahMttufeT1by+YDtnDU/gwXOGEuDXei3qLrflzvdX8sHSHG4/sS83Ha9AKtLa9hVK1X9GRERE/se8zUXc+f5KxqVF8eA5Q1ukJS7Az4cTB3bnlStG8bezBrMgq5hTHp/DD5uLWqDizmPa8ly+WZvPbSf27TCBFMDXx/DXSYO5Y2JfPlqWy1VTF1NV19gq98ouquLy/yzig6U53HqCAqlIe6BQKiIiIj/ZsKuC615bQs/oLjx76cgWb60yxnDxmBQ+vvEIwoL9ueSlhTz89QYaXe4WvU9HlFdew58+XkNGSkSHXD/TGMONE/rw4DlD+GFzERe9sICiyroWu35NvYuHv97ASY/NZtn2Mv46aRA3t/O1XUU6C4VSERERAZrGKl7+n0UEB/jynytGExbs32r36h/XjU9uPILzRybx7+83c+HzC8gtq2m1+3k7ay3/98EqGl2Wh88bhm8HHo97wahknr80gw27Kjj3mXlsL64+rOtZa/l6zS5OeHQW//5+M6cN7cF3tx/DpeNSW6ZgETlsCqUiIiJCZV0jV7yymN01Dbx8+SgSwoNb/Z4hAX48eO5QHr8wnfW7Kjj18Tl8vWZXq9/XG721aAezNxZyz6n9O1S33b05YWB33rxmDGU1DZz9zDxW55Yf0nW2FlVxxSuLue61JYQG+vHOtWN57IJ0YrWGrki7olAqIiLSyTW43Nzw+hI25lfw9CUjGZwQ1qb3n5SewGc3HUlyZAjXvbaE+z5ZQ22DVpP70fbiau7/fC1H9o7m4jEpTpfTZkamRPL+9eMI8DVc+PyCgxp/XFPv4pFvNjDxsdlkbi3lD6cN4LPfHsmYtKhWrFhEDpVm3xUREenErG2ahfS9JTk8eM4QLhi1/7VIW0t9o5sHv1rPS3Oz6R0byj/OHsKo1EjH6mkP3G7LhS8sYN3O3Xx169Ft0oLd3uwqr2XKy4vIKqrkkfPTOXNY/P/sr21wsbOshtyymqbvpTV8sDSX3LIaJqfHc8+pA9QyKtIOaEkYERER+QVrLfd9soap87fx2+P7cNuJfZ0uCYBZGwu558NV5JbVcNHoZO46uT9hIa03vrU9e3FOFvd/vo6Hzh3KeRlJTpfjmPLqBq55NZNFW0s4Z0QiNQ2N5JbWkFtW+4vJkHwMDIzvxh9OG8hYtYyKtBsKpSIiIvI/rLXc//k6XpqbzTVH9eSeUwe0yNIvLaW6vpF/Td/ES3OziQgJ4N4zBnL60B7tqsbWtrmgglOfmMvRfaJ54bKMTvXZ96S2wcWd76/k27X59AgLIiEimPiwYBIigkkI/+/3uLAg/H01Qk2kvVEoFRERkZ9Ya3ngq/U8NyuLy8encu8ZA9tt4FmdW87dH65iVW45x/WL4a+TB5MYEeJ0Wa2u0eXmnGfmsa2kmm9uPZrYrup+KiLebV+hVH9GEhER6USstTzyzUaem5XFJWOT23UgBRicEMZHvx7PH08fyMLsEk58dDYvzsnq8OuaPjtrCytyyrl/8mAFUhHp8BRKRUREOpHHZ2xqWhd0VBJ/OXNwuw6kP/Lz9eGqI3vy7W3HML5XFPd/vo7JT//AurzdTpfWKtbsLOfxGZs4fWgPTh8av/8TRES8nEKpiIhIJ/HU95v51/RNnDsykb+fNQQfn/YfSJtLCA/mxSkZPH3xCPJ313HuM/OYu+nAlwnxBnWNLm5/dwVhwQH8ddJgp8sREWkTCqUiIiKdwPOzt/DQ1xs4a3gCD54z1OsC6Y+MMZw6pAef3XQkSZEhXPHKIj5enut0WS3CWstDX21g/a4KHjh7CBFdApwuSUSkTSiUioiIdHAvzc3m71+s5/ShPXjo3KH4emkgba57tyDeuW4cw5MjuPnt5bw4J8vpkg6LtZZ/fLmeF+dmc+nYFE4Y2N3pkkRE2oxCqYiISAc2dd5W/vrZWk4ZHMdjF6Tj14GWyggL9ufVK0dzyuA47v98Hf/4Yh1ut/OrChwsl9vy+2mreX52FlPGpfDnMwc5XZKISJvyc7oAERERaXnV9Y3c98ka3s3M4YQB3Xn8wuEdcu3GIH9f/v2rEdz3yRqem51FQUUd/zx3qNd81gaXmzveW8HHy3fy62N78buT+nnF5FMiIi1JoVRERKSDWZe3mxvfXEpWURU3TejNzcf36VAtpD/n62P4y6RBdO8WyMPfbKS4qp5nLh5Bl8D2/WtObYOLm95axrdr87nz5H78+tjeTpckIuKIjvsvlIiISCdjreX1BduY9NQP7K5t5PWrxnD7xH4dOpD+yBjDjRP68OA5Q5i7qZCLXlhAUWWd02XtVXV9I1dPzeTbtfn8ddIgBVIR6dQ6/r9SIiIinUB5TQO/fmMpf5i2mrFpUXx581Ec0Tva6bLa3AWjknn+0gw27Krg3Gfmsb242umSfqG8poFLX1rEvC1FPHLeMC4dl+p0SSIijlIoFRER8XJLt5dy6uNz+HZtPnef0p9XLh9FdGig02U55oSB3XnzmjGU1TQw5T+LKK9pcLqknxRX1nHR8wtYmVPGU78awTkjE50uSUTEcQqlIiIiXsrttjwzcwvnPTsfY+C968dx3TG9vHYN0pY0MiWSFy7LYEdJNbe9s7xdzMqbV17D+c/NJ6uokhenjOKUIT2cLklEpF1QKBUREfFC5TUNXP7KYh78aj0nD4rj898exfDkCKfLaldGpUbyx9MHMmN9AU98t8nRWlbllHP20/PI313Hq1eO4Zi+MY7WIyLSnrTvaelERETkF7YXV3PFK4vYXlLN/ZMHc/GYZC0jsheXjUthRU4Z/5q+iSEJYRw/oHub1zBtWS7/98FKokMDeee6sQyKD2vzGkRE2jOFUhER8Qrl1Q1sKaoku7CKrKJKsouqyCqsIqe0hthugfSJDaVPbFf6dG/6nhbThSB/X6fLbnFLtpVy7auZNLotr101hrFpUU6X1K4ZY/j7WUPYmF/BLe8s55Mbj6RndJc2ubfLbXnwq/U8PzuL0T0jeebiEUR14rG+IiJ7Y6x1foxFRkaGzczMdLoMERFpB6y1bC+pZmF2CUu3lbK5oJKsoipKqup/OsbXx5ASGULP6C4kRgSTv7uOTQUVbC2uxuUZO+hjIDkyhD7du9K3eyjH9YtlZEqEV7cofrpiJ7e/t4IeYUG8fPkoesWEOl2S18gpreaMJ+cSHRrItN8c0eprmJZXN3DT28uYvbGQy8al8MfTB+LfCZbmERHZG2PMEmttxh73KZSKiIiT3G7LxoIKFmWX/PRVUNG0vmR4iD/9uje1eqZFh9IzugtpMV1IigzZ4y/49Y1usouq2FRQwab8yp++ZxdV0ei2JEUGc1Z6ApOGJ3hVoLPW8vTMLTz09QZGpUbw3KUZRHYJcLosrzN3UxGXvbyQkwfH8dSvRrTaHyg25VdwzauZ5JbV8NdJg7lwdHKr3EdExJsolIqISLvS4HLzxoJtzN1cxOKtpT8t2dEjLIjRPSMZlRrJmJ6R9IoJbZGZZCvrGvl69S6mLc/lh81FuC0MSwxj8vAEzhgW366XT6lvdHPPR6t4f0kOk9Lj+ee5Qwn063jdktvKc7O28I8v13PXKf25/pheLX79b9fmc+s7ywny9+XZS0aQkRrZ4vcQEfFGCqUiItJu1Da4uPHNpUxfV0BadJefQujonpEkRgS3evfa/N21fLpiJx8uzWVt3m58fQxH94lm8vAETh4c164CX1l1Pde/voQFWSXcfHwfbjmhj1d3P24PrLXc+NYyvlyVx9QrR3NUn5aZBdfttvz7+808+u1GhiaG8dylI+kRFtwi1xYR6QgUSkVEpF2oqG3g6qmZLNpawl8mDebSsSmO1rNhVwXTlufy8bJcdpbXEh8WxI0T+nBeRqLj4/+2FVdxxX8Ws6O0mgfPGcrZIxIdracjqaprbFqepaKWT288kqTIkEO6TnV9I8u2l7Ewu4TZGwtZvqOMs4cn8Pezh3TISbZERA6HQqmIiDiuuLKOy/+zmHV5u3nk/GFMSk9wuqSfuN2W2ZsK+df0TSzfUUZSZDA3TejD2cMT8GvjcGqt5ePlO7n3kzUYA89dMpIxmmG3xWUXVXHmv+eSHBnCBzeMP6AQWVZdz+KtpSzeWsLC7BLW5JbT6Lb4GBgY340LMpK4ZGyKWrNFRPbgsEKpMSYJeBWIA9zA89bax40xkcA7QCqwFTjfWlvqOedu4CrABfzWWvv1vu6hUCoi0rHtLKvhkpcWkltawzOXjGBC/7ZfK/JAWGuZuaGQR7/dyKrccnpGd+Hm4/twxrB4fFtgbOv+FOyu5Z6PVjN9XT7Dk8N57Px0Utto+ZLOaMa6fK6amknXQD+6BPoR4OdDoJ8Pgf4+BPj6EOjn+9PrbcXVbMivACDA14f0pHBG9YxgVGokI1Mi6Brk7/CnERFp3w43lPYAelhrlxpjugJLgMnA5UCJtfYBY8xdQIS19v+MMQOBt4DRQDwwHehrrXXt7R4KpSIiHVdWYSWXvLiQitpGXrp8FKN7tv+JX6y1fLs2n0e/3cj6XRX0jg3llhP6cOrgHi0y8dKe7vfB0lz+8uka6hrd3DGxH1ce2bNNgnBn98WqPBZkFVPX4Kau0UVdo5v6Rjd1jf99X9fgpntYEKNTIxjdM4qhiWHqnisicpBatPuuMeZj4N+er2OttXme4DrTWtvP00qKtfYfnuO/Bu6z1s7f2zUVSkVEOqbVueVMeXkRAFOvHM3ghDCHKzo4brfly9W7eGz6RjYXVNI/rit/PnNQi3anzSuv4e4PVzFzQyGjUiN48JyhpHnRcjUiIiIHYl+h9KBWjjbGpALDgYVAd2ttHoAnmMZ6DksAFjQ7LcezTUREOpFF2SVc9cpiugX789pVo70yaPn4GE4b2oOTB8fx2cqdPPLNRi58YQFXH9mT2yf2O6zWMmst7yzewd8+X0ej23LvGQOZMi61VVpiRURE2rMDDqXGmFDgA+AWa+3ufQzi39OOXzTHGmOuBa4FSE7WotIiIh3J9+sLuP71JSRGBPPaVWOID/fupTF8fQyT0hM4cWB3/v7FOl6Yk83sjUU8esEwBsUffOtvTmk1d3+4ijmbihibFsmD5wwlJUpjR0VEpHM6oCkFjTH+NAXSN6y1H3o253u67f447rTAsz0HSGp2eiKw8+fXtNY+b63NsNZmxMS0zBphIiLivA+W5HDNq5n07d6Vd68b5/WBtLmQAD/unzyEV64YRWl1PZOf+oGnvt9Mo8u933OttSzZVspt7y7n+EdmsXRbKX+dPJg3rx6rQCoiIp3agUx0ZICpNE1qdEuz7Q8Bxc0mOoq01t5pjBkEvMl/JzqaAfTRREciIh2btZanZ27hoa83cETvKJ69ZGSHnpG0tKqeP3y8ms9X5jEiOZxH9zJTbkVtA9OW5fLGwu2s31VBlwBfzhqRwHVH9zrk9TFFRES8zeHOvnskMAdYRdOSMAD30DSu9F0gGdgOnGetLfGc83vgSqCRpu6+X+7rHgqlIiLerdHl5t5P1vDGwu1MTo/nn+cOI8Cvbdf3dIK1lk9W7OSP01bT4LL84fQB/Gp0MsYYVueW88bCbXy8fCfV9S4GxXfj4jEpnJkeT2jgQU3pICIi4vVadPbd1qBQKiLivWrqXdz01lKmryvghmN78buJ/TrdZD155TXc+f5K5mwq4sje0VTUNrAip5wgfx/OHBbPxWNSGJoYxj7mYxAREenQWmz2XRERkeaKK+u4amomK3LK+MukQVw2LtXpkhzRIyyYqVeM5rUF23jgy/UkRQZz3xkDOWtEImHBHbcLs4iISEtQKBURkUOyrbiKKS8vIq+8lmcvGclJg+KcLslRPj6GKeNTuXRsCsagVlEREZEDpFAqIiIHbcWOMq58ZTEua3nzmjGMTIl0uqR2o7N1XRYRETlcCqUiInJQvlufz2/eWEZUaABTrxxNr5hQp0sSERERL6ZQKiIiB8Ray4tzsnngq/UM6NGVly8fRWzXIKfLEhERES+nUCoiIvtVWdfIne+v4ItVuzh5UBwPnz9My5qIiIhIi9BvFCIisk+bCyq47rUlZBdVcfcp/bn26DRN4iMiIiItRqFURET26vOVedz5/gqC/H15/eoxjO8V7XRJIiIi0sEolIpIh1FWXU/+7jqKKpu+CivqKKyso6ii/qdt5TUN+BiDn4/B1/Pl52vwNZ7XPj6EBvlxyuA4Thvag5CAzvm/yUaXmwe/Ws8Lc7IZnhzO0xePoEdYsNNliYiISAdkrLVO10BGRobNzMx0ugwR8VI19S7+8tka3lq04xf7/H0N0aGBnq8AwkMCsNbS6La4raXRZXG5m943fXeTV17LtuJqQgP9ODM9ngtHJTEkIazTdFktrKjjxjeXsjC7hMvGpfCH0wYS4OfjdFkiIiLixYwxS6y1GXva1zmbAESkw9iwq4Ib31zKpoJKLh+fysiUCKJDA4npGkhMaCDdgv0OOkxaa1m8tZS3F2/nw6U5vLlwOwN6dOPCUUlMTk8gLMS/lT6N85ZsK+HXbyylvKaBR88fxtkjEp0uSURERDo4tZSKiFey1vL24h3c98kaugb58ej56RzdN6bF77O7toFPlu/kncU7WJVbToCfD6cOjuPckUmkJ4d3mBloS6vqeeK7Tbw2fxsJEcE8e8lIBvTo5nRZIiIi0kHsq6VUoVREvM7u2gbu/nAVn6/M48je0Tx6wbA2WS9zdW4572bu4KNluVTUNgKQHBlC/7iu9O/RjQGe7ymRIfj4eEdX39oGF6/O38qT322mqq6RC0Ylc9cp/QkL7ritwSIiItL2FEpFpMNYvqOMm95ays6yWm6f2Jfrj+7V5gGwtsHFD5uLWJe3m3W7KliXt5utRVW4Pf87Dfb3pV9cVwbFd+PsEYmMSA5vd+NRrbV8ujKPf361npzSGo7rF8Pdpw6gb/euTpcmIiIiHZBCqYh4Pbfb8uLcLP751Qa6dwviiYvSGZkS6XRZP6mpd7GpoIL1eRWs27Wb9XkVrMwpo6rexeCEblw2NpUz0+MJ8vd1ulQWZZfwty/WsWJHGQN6dOP3pw7gyD5a6kVERERaj0KpiHi1kqp6bnt3OTM3FHLSoO7885xhXjHZUGVdIx8ty+W1+VvZmF9JeIg/52ckccmYFJKjQtq8nqzCSh78aj1fr8mne7dA7pjYj7NHJOLrJV2NRURExHsplIqI11qzs5xrX11CYWUdfzxtAJeMTWl3XWH3x1rLgqwSXluwla/X5OO2lgn9Yrl0XApH94lpte7Hbrdlbd5uZm4oYOaGQpZuLyXI35cbjunF1UelERzgfKutiIiIdA4KpSLilT5fmccd760gLNif5y4dybCkcKdLOmx55TW8tXA7by7aTlFlPSlRIUwc2J1j+8UyKjXysNcDLa9uYPamQmZuKGTWxkKKKusAGJzQjeM8QbgtJoUSERERaU6hVES8ittteeTbDTz1/RZGpkTwzCUjOlyQqmt08dXqXbyXmcOi7BLqXW5CAnw5onc0x/aL4dh+sSSEB+/zGhW1DWwrrmZHSTUb8yuZvamQZdtLcVsIC/bn6L4xHNs3hqP6Rne4n5+IiIh4F4VSEfEau2sbuPXt5cxYX8CFo5L486RBBPp17G6mVXWNzN9SzPeebra5ZTUA9IkN5dh+MYzuGUVpdT3bi6vZXlLNtpJqthdXUVrd8D/XGZoYxrF9YzimXyzpSeEaKyoiIiLthkKpiHiFrMJKrn41k+3F1dx7xkCvHD96uKy1bCmsZOaGpi64P7aiAvj6GOLDg0iJ7EJSZAgpUSEkRzZ9pUSF0DWo/U/+JCIiIp3TvkKpX1sXIyKyJ99vKOC3by3D39eH168ew9i0KKdLcoQxht6xXekd25Wrj0qjqq6RdXm7iekaSHx4MP6+hzfmVERERKS9USgVEUdZa3l2Vhb//Ho9A+K68fxlI0mMaPvlUtqrLoF+ZKS2n/VYRURERFqaQqmIOGZ1bjl/+Wwti7JLOH1oDx46d5iWKRERERHpZBRKRaTNFVTU8vDXG3hvSQ4RIQH8/awhXDQ6qdONHxURERERhVIRaUO1DS5empvN099vpt7l5pqj0rhxQm+6aYIeERERkU5LoVREWp21li9W7eIfX64jp7SGiQO7c8+pA0iN7uJ0aSIiIiLiMIVSEWlVq3LK+ctna1i8tZT+cV158+oxjO8d7XRZIiIiItJOKJSKSKuw1vKv6Zt44rtNRIYE8I+zh3B+RhK+Pho3KiIiIiL/pVAqIi2uvtHNXR+u5MOluZwzIpF7zxyocaMiIiIiskcKpSLSosprGrjh9SXM21LM7Sf25cYJvTWrroiIiIjslUKpiLSYnNJqrnxlMdlFVTx6/jDOHpHodEkiIiIi0s757O8AY8zLxpgCY8zqZtvuM8bkGmOWe75ObbbvbmPMZmPMBmPMSa1VuIi0L6tzyznr6Xnkldcy9YrRCqQiIiIickAOpKX0FeDfwKs/2/6Ytfbh5huMMQOBC4FBQDww3RjT11rraoFaRdqV6vpGFm8tZXtxFQF+PgT6+RLo5/Pf1/4+BPj6EOjvQ1iwP3HdgjpsN9bv1udz45vLiAgJ4I2rx9C3e1enSxIRERERL7HfUGqtnW2MST3A600C3rbW1gHZxpjNwGhg/qGXKNI+1Da4WLq9lPlbipm/pZgVOWU0uOwBnx8a6Eev2FD6xobSp3sofWK70js2lITwYHy8eEba1xZs496PVzMwvhsvTxlFbLcgp0sSERERES9yOGNKbzTGXAZkArdba0uBBGBBs2NyPNt+wRhzLXAtQHJy8mGUIdI6Gl1ulu0oY/6WYuZtKWLp9jLqG934GBiaGM7VR6UxLi2K/nFdaXRb6hrd1DW6qGtwU+9yU9fged/opriqns35FWwqqGTmxkLeW5Lz031CAnzpHRtKr5hQkiNDSI4MISUqhOSoEGJCA9tt66rbbXnw6/U8NyuLCf1jefKi4XQJ1DB1ERERETk4h/ob5DPAXwHr+f4IcCWwp9+e99iUZK19HngeICMj48Cbm0TawOrccu54bwXrd1VgDAzs0Y0p41IY1yuKUamRdD3M5U3KquvZXFDJxvxKNhVUsLmgkoVZxUxbnott9l9DsL9vU1CNagqr/eO6ctLgOEeXV6lrdPHxsp28ODeLjfmVXDI2mfvOGISf736HqIuIiIiI/MIhhVJrbf6Pr40xLwCfed7mAEnNDk0Edh5ydSJtrK7RxZMzNvPMrC1EdQng0fOHMaF/LOEhAS16n/CQADJSI8lIjfzF/XNKa9heUs324mq2FVezvaSabcVVzNlUSG2Dmz9MW83Jg+M4d2Qi43tF49tGXX9Lq+p5Y+E2ps7fRmFFHQN6dOPxC9M5c1h8u23NFREREZH275BCqTGmh7U2z/P2LODHmXk/Ad40xjxK00RHfYBFh12lSBtYsaOM372/go35lZwzIpE/nT6QsJC2bZEM9POlV0xTV96fs9ayIqecD5bk8PHyXD5evpMeYUGcPSKBc0YkkraHc1rC1qIqXpqbzXtLdlDb4OaYvjFce0Ea43tFKYyKiIiIyGEz1u6756wx5i3gWCAayAfu9bxPp6lr7lbguh9DqjHm9zR15W0EbrHWfrm/IjIyMmxmZuYhfgSRw1Pb4OKx6Rt5YXYWsV2D+Mc5QziuX6zTZe1TbYOLGesKeH/JDmZtLMRtYWRKBOeOTOS0oT0Ou3uvtZal20t5fnYW36zNx9/Hh0np8Vx9VBr94jSzroiIiIgcHGPMEmttxh737S+UtgWFUnHKkm2l/O79FWQVVnHhqCTuOW2Ao+M1D0X+7lqmLcvlvSU5bC6oJMDXh7G9ojhhQCwT+seSGBFyQNdpcLlZnF3C9HUFfLc+n63F1YQF+3Pp2BQuG59CbFfNqisiIiIih0ahVORnaupdPPLNBl76IZv4sGAeOGcIR/WJcbqsw2KtZWVOOZ+u2MmM9QVkF1UB0D+uK8cPiOX4Ad1JTwz/n+VnyqrrmbmhkOnr8pm1sZCK2kYC/HwY3yuKiQPjmDw8npAAzagrIiIiIodHoVSkmZzSaq6emsn6XRVcPCaZu08dQGgHXMokq7CSGesKmL4un8xtpbjclujQAI7rF0tqdBdmbSgkc1sJbgvRoYEc3z+W4wfEcmSfaAVREREREWlR+wql+s1TOpXFW0u4/rUl1Lvc/OeKUe1+7OjhSIsJJS0mlGuOTqOsup5ZGwuZsa6Ar9fsYndtIwN6dOM3x/Xm+AHdGZoQ9j8tqCIiIiIibUWhVDqNdxZv5w/TVpMYEcKLUzL2OMNtRxUeEsCk9AQmpSfQ4HKzu6aBqNBAp8sSEREREVEodZq1lrpGN7trG6iobaSitpGQAF+SI0MI8vd1urwOodHl5u9frOflH7I5qk80/75oRJsv9dKe+Pv6KJCKiIiISLuhUNpGthdXM3X+Vtbv2k1FbSO7a/4bQutd7l8cbwwkRgTTMzqUtOgupMV0IS06lJ4xXejRLUhdLQ9QeU0DN721jNkbC7niiFR+f+oA/Hx9nC5LREREREQ8FEpb2ZJtpbw4J4uv1+zC18cwJCGMyC4BpEZ1oWuQH12D/OkW7Pke5EfXID8qahvJKqwiq6iK7KJKlmwtoare9dM1g/x9GNCjG+PSohjfK5qRKREEB6hV9eeyi6q4aupidpRU88DZQ7hwdLLTJYmIiIiIyM8olLYCl9vy7dpdPD87i6Xby+gW5Mf1x/RiyvhUunc7+LUerbUUVNR5gmolWYVVLNteyvOzs3h65hYCfH1ITwpnXK8oxvWKYnhyOIF+nTukztlUyG/eWIqfrw+vXzWGMWlRTpckIiIiIiJ7oCVhWlB1fSPvZebw8g/ZbCuuJikymKuO6Ml5GUl0aYUlRyrrGlm8tYT5W4qZv6WYNTvLcVsI9PNhZEoE4z0hdWhiOP6dpMtqcWUdL/+QzbOzsugTG8oLl2WQFBnidFkiIiIiIp2a1iltZRW1DbwwJ5up87ZSXtPA8ORwrjkqjZMGxeHbhmM/y2saWJTdFFLnbSli/a4KAEICfBmVGtnUkpoWxeCEsDatqy3sKKnmhTlZvJu5g9oGN5PS4/nbWUM65PqjIiIiIiLeRqG0ldQ3unlj4Tae/G4zJVX1TBzYneuOSWNkSqTTpQFQUlXPwqxi5m0pZn5WMZsLKgHoGuTHmJ6RjE2LYuLAOJKjvLclce3O3Tw3ewufrczDx8BZwxO49uhe9I7tPMu9iIiIiIi0dwqlLczttny6cicPf7OBHSU1jO8VxV2n9GdoYrjTpe1Twe5a5mcVsyCrqbvv1uJqfAxMTk/gNxN6e826ndZaFmSV8OysLczaWEiXAF9+NSaZq45MIy7s4MfsioiIiIhI61IobUFzNxXxwFfrWJ27mwE9unHXKf05uk80xnhfd9ic0mqmztvKawu2Ud/o5oxh8dw0oTe9Y7s6XdoelVXXM31dAa8t2MaKHWVEhwZwxRE9uWRMSqded1REREREpL1TKG0Bq3PLefCr9czZVERCeDB3nNSXScMSOsR6oUWVdbwwO4tX52+jttHF6UPj+e2E3vTp7nw43VlWwzdrdvHN2nwWZpfgcltSokK45qg0zh2ZSJB/555lWERERETEGyiUHoZGl5vb31vBx8t3Eh7iz43H9ebScSkdcsmV4so6XpybzavztlLd4OLUwT347fF96BfXtuF0c0EFX6/J5+s1u1iZUw5A79hQJg7szkmD4hiaGOaVLdMiIiIiIp2VQulhuu2d5cSFBXH9sb3oFtTxu4mWVNXz0twsps7bRmVdI8f2i+H0ofGcOLA7YcEt//mLK+tYvLWERdmlzNxYQFZhFQDpSeFMHNQURL1lvKuIiIiIiPySQulhstZ2ypa5sup6Xv5hKx8sySG3rAZ/X8MRvaM5dUgPJg7sTnhIwCFdN7eshkXZxSzKLmVRdjFbPCE00M+H0T0jmTiwOycOjNOkRSIiIiIiHYRCqRwWay0rcsr5clUen6/KI6e0Bj8fw/je0Zw6OI6Jg+KI7NIUUOsb3ZRV11NSXU9pVQNl1fWUVjdQWl3P5oJKFmWXkFtWAzQtTZOREsHonlGM7hnBkIRwAvx8nPyoIiIiIiLSChRKpcVYa1mVW84Xq3bxxao8tpdU4+tjiOsWRFl1PVX1rr2eGx0ayOieEYxOjWRUz0j6x3XDtwNMFCUiIiIiIvu2r1Dq19bFiHczxjA0MZyhieH838n9WLNzN1+symNXeS3hIQFEhPgT3qXpe2RIQNO2Lv5EhARoplwREREREfkFhVI5ZMYYBieEMTghzOlSRERERETES2kAn4iIiIiIiDhGoVREREREREQco1AqIiIiIiIijlEoFREREREREccolIqIiIiIiIhjFEpFRERERETEMQqlIiIiIiIi4hiFUhEREREREXGMsdY6XQPGmEJgm9N1iByiaKDI6SJEWpCeaelI9DxLR6LnWbxZirU2Zk872kUoFfFmxphMa22G03WItBQ909KR6HmWjkTPs3RU6r4rIiIiIiIijlEoFREREREREccolIocvuedLkCkhemZlo5Ez7N0JHqepUPSmFIRERERERFxjFpKRURERERExDEKpSIiIiIiIuIYhVKRg2CMSTLGfG+MWWeMWWOMudmzPdIY860xZpPne4TTtYocKGOMrzFmmTHmM897Pc/ilYwx4caY940x6z3/nx6n51m8mTHmVs/vG6uNMW8ZY4L0TEtHpFAqcnAagduttQOAscBvjDEDgbuAGdbaPsAMz3sRb3EzsK7Zez3P4q0eB76y1vYHhtH0XOt5Fq9kjEkAfgtkWGsHA77AheiZlg5IoVTkIFhr86y1Sz2vK2j6hScBmARM9Rw2FZjsSIEiB8kYkwicBrzYbLOeZ/E6xphuwNHASwDW2nprbRl6nsW7+QHBxhg/IATYiZ5p6YAUSkUOkTEmFRgOLAS6W2vzoCm4ArEOliZyMP4F3Am4m23T8yzeKA0oBP7j6Y7+ojGmC3qexUtZa3OBh4HtQB5Qbq39Bj3T0gEplIocAmNMKPABcIu1drfT9YgcCmPM6UCBtXaJ07WItAA/YATwjLV2OFCFujWKF/OMFZ0E9ATigS7GmEucrUqkdSiUihwkY4w/TYH0DWvth57N+caYHp79PYACp+oTOQhHAGcaY7YCbwMTjDGvo+dZvFMOkGOtXeh5/z5NIVXPs3irE4Bsa22htbYB+BAYj55p6YAUSkUOgjHG0DReaZ219tFmuz4BpnheTwE+buvaRA6WtfZua22itTaVpskzvrPWXoKeZ/FC1tpdwA5jTD/PpuOBteh5Fu+1HRhrjAnx/P5xPE1zWeiZlg7HWGudrkHEaxhjjgTmAKv47xi8e2gaV/oukEzTPyLnWWtLHClS5BAYY44F7rDWnm6MiULPs3ghY0w6TZN2BQBZwBU0/QFez7N4JWPMn4ELaJr9fxlwNRCKnmnpYBRKRURERERExDHqvisiIiIiIiKOUSgVERERERERxyiUioiIiIiIiGMUSkVERERERMQxCqUiIiIiIiLiGIVSERERERERcYxCqYiIiIiIiDjm/wFiLMBgO6CAdAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1152x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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zs78A/gK438yWAHcCS4FS4JdmtsDdgxfoO4iIiIiIyAzj7rza2MsPNh/hp7uaGRkPsXx2Dv/rg5dy66WlpCZpWZeZ4oyh1N0dGIi8TIw8HHgfcG2k/TvAi8D9kfYfufsoUG9mh4A1wMbzWbiIiIiIiMw8g6MBntrZzMNbjrC7qY+0pHh+d2U5d62t0LIuM9Sk7ik1s3hgGzAP+N/uvtnMZrl7C4C7t5hZUeTwMmDThLc3RtpOPed9wH0AFRUV7/wbiIiIiIjItObubDvSzePbG/nZrhYGRgMsKs7kr29fxu0rSslMSYx2iXIBTSqURoberjCzHOAnZrbsbQ63053iNOd8CHgIoKam5rf2i4iIiIjIzNbYPcRPtjfx+PZGGjqHSE2M5z2XFHPX2jmsqsjB7HTRQmaas5p91917zOxF4Cag1cxKIr2kJUBb5LBGYPaEt5UDzeejWBERERERmd4GRwM8s/s4j21rZGNdJwDrqvP43Lvm8Z5LSshI1gIhsWYys+8WAuORQJoKXA88CPwUuAf4u8jzU5G3/BR42My+Sniio/nAlgtQu4iIiIiITAPuzqa6Lh7b1sh/7W5haCxIRV4a//36Bbx/VRmz89KiXaJE0WR+DVECfCdyX2kc8Ki7P21mG4FHzexTwFHgQwDuvsfMHgX2AgHgc5p5V0REREQk9gyMBvjJ9ka+s/EIh9oGyEhO4LblpXxgdTk1c3I1PFcAsPDkutFVU1PjtbW10S5DRERERETOg8PtA3xv4xEe29bIwGiAS8uzuXt9Je+9pERLucQoM9vm7jWn26cB2yIiIiIics6CIeeF/W18Z2MDGw52kBhv3HJpKXevn8PKitxolydTmEKpiIiIiIi8Yz1DYzyy9Rjf23SExu5hirNS+NMbF/DhyyoozEyOdnkyDSiUioiIiIjIWQkEQ/z69XYe397IL/e2MRYMsbYqjwduXswNS2aRGB8X7RJlGlEoFRERERGRSdnX0sfj2xp5cmczHQOj5KUncde6Cu6omc3ikqxolyfTlEKpiIiIiIi8pc6BUZ7a2cxj2xrZ29JHYrxx3aIiPrh6NtcuLFSvqJwzhVIREREREXmTkfEgL+xv44kdTbywv41AyLm0PJsv37aUW5eXkpeeFO0SZQZRKBUREREREYIhZ1NdJ0/uaOKZ3cfpHw1QlJnMp66s4gOry1kwKzPaJcoMpVAqIiIiIhKj3J3dTX08ubOJn+1qpq1/lIzkBG5aVsztK8pYPzef+DiLdpkywymUioiIiIjEmKOdQzy5s4kndzZR1z5IYrxx7cIibl9RxrsXF5GSGB/tEiWGKJSKiIiIiMSAQDDE8/vb+P6mI2w42AHAmqo8Pn1lNTdfUkxOmu4TlehQKBURERERmcHa+kd4ZMsxHt5ylJbeEUqyU/jjGxbwgdXllOWkRrs8EYVSEREREZGZxt3ZUt/F9zYd4ZndxwmEnKvmF/BXty3l3YuKSNAyLjKFKJSKiIiIiMwQ/SPjPLmzme9vPMKB1n6yUhK45/JK7lpbQXVhRrTLEzkthVIRERERkWnK3TncPsiLB9p44UAbW+u7GQuGWFqaxYMfuITblpeRmqRJi2RqUygVEREREZlGhseCbKzr4IX97bxwoI3G7mEAFszK4BNXVPKeZcWsmJ2DmZZykenhjKHUzGYD3wWKgRDwkLt/zcweARZGDssBetx9hZlVAvuAA5F9m9z9s+e7cBERERGRWHG8d4T/2t3CCwfa2VTXyVggRGpiPFfMK+Cz18zl2oWFlOemRbtMkXdkMj2lAeBP3H27mWUC28zsOXf/8IkDzOwfgd4J7zns7ivOb6kiIiIiIrFjNBDkl3vbeLT2GBsOthNymFuYzsfXzeFdC4u4rCqX5AQNzZXp74yh1N1bgJbIdr+Z7QPKgL0AFh4XcAdw3QWsU0REREQkJuxu6uWxbY08ubOJnqFxSrNT+Ny75vH+VeVUFaRHuzyR8+6s7imNDM1dCWye0HwV0OruBye0VZnZDqAP+KK7bzjNue4D7gOoqKg4y7JFRERERGaOrsExntrZxKO1jexr6SMpIY7fWVrMh1aXc8W8AuLjdH+ozFyTDqVmlgE8DvyRu/dN2PUR4IcTXrcAFe7eaWargSfNbOkp78HdHwIeAqipqfF3+gVERERERKYjd6f2SDffeqWe5/a2Mh50LinL5q/ft5TblpeRnZYY7RJFLopJhVIzSyQcSH/g7k9MaE8A3g+sPtHm7qPAaGR7m5kdBhYAteexbhERERGRaSkQDPFfu4/zHy/Xs+tYDzlpiXx8XSUfqilncUlWtMsTuegmM/uuAd8A9rn7V0/ZfT2w390bJxxfCHS5e9DMqoH5QN15rFlEREREZNrpHxnnka3H+NYrDTT1DFOZn8Zfv28pH1hdTlqSVmqU2DWZ//uvAD4OvGZmOyNtD7j7z4E7efPQXYCrga+YWQAIAp91967zVK+IiIiIyLTS1DPMt1+p50dbjtE/GmBNZR5funUJ7148S/eKijC52XdfBk57tbj7J07T9jjhob4iIiIiIjHrtcZe/n1DHf/5WgsAN19SwqevrGL57JzoFiYyxWicgIiIiIjIeeLuvPh6Ow/9uo6NdZ1kJCdw7+WVfOKKSspz06JdnsiUpFAqIiIiInKOxgIhntrZxL9vqOP11gGKs1J44OZF3LmmgqwUzaIr8nYUSkVERERE3qG+kXEe3nyUb71ST2vfKIuKM/nHDy3n1uWlJCXERbs8kWlBoVRERERE5Cw19wzzrVfq+eGWYwyMBrhiXj4PfuBSrllQSHjxChGZLIVSEREREZFJau4Z5uu/OsiPaxtx4L2XlHDf1dUsK8uOdmki05ZCqYiIiIjIGXQOjPJ/XjzM9zYdwd356NoKPnNVNbPzNHmRyLlSKBUREREReQt9I+P8x4Z6vrGhjuHxIB9YVc4fXj9fM+mKnEcKpSIiIiIipxgeC/LdjQ38668P0zM0zs2XFPPHNyxkXlFGtEsTmXEUSkVEREREIsYCIR6pPcbXnz9IW/8o1ywo5E9vXMgl5bpnVORCUSgVERERkZjXPzLOj2sb+dZv6jnWNUzNnFy+/pGVrK3Oj3ZpIjOeQqmIiIiIxKy69gG+u/EIP649xuBYkFUVOXzltmVcu1BLu4hcLAqlIiIiIhJT3J2XDnbw7VfqeeFAO4nxxi2XlvKJyytZPjsn2uWJxByFUhERERGJCYOjAZ7Y3si3f9PA4fZBCjKS+aPr5/PRtRUUZaZEuzyRmKVQKiIiIiIz1lggxOb6Tp7d08qTO5voHwlwaXk2//Th5dx8SQnJCfHRLlEk5imUioiIiMiM0jM0xgsH2vjlvjZ+faCdgdEAKYlx3LCkmE9cXsmqihzdLyoyhSiUioiIiMi019AxyC/3tfLc3lZqj3QTDDmFmcncuryE6xfP4op5BaQkqldUZCo6Yyg1s9nAd4FiIAQ85O5fM7O/Aj4DtEcOfcDdfx55zxeATwFB4PPu/osLULuIiIiIxLC69gGe3NnMz19r4VDbAACLijP5b9fM5fols7i0LJu4OPWIikx1k+kpDQB/4u7bzSwT2GZmz0X2/ZO7/8PEg81sCXAnsBQoBX5pZgvcPXg+CxcRERGR2NPWP8LPdrXw1M4mXm3sxQzWVuVx19olXL94FrPz0qJdooicpTOGUndvAVoi2/1mtg8oe5u3vA/4kbuPAvVmdghYA2w8D/WKiIiISIzpHxnnF3taeWpnE68c6iDksLQ0i7+8eTG3Li+lOFsz54pMZ2d1T6mZVQIrgc3AFcAfmNndQC3h3tRuwoF104S3NXKaEGtm9wH3AVRUVLyT2kVERERkhhoYDfDKoQ5+uquZX+5tZTQQYnZeKr9/7TxuX1nKvKLMaJcoIufJpEOpmWUAjwN/5O59ZvavwF8DHnn+R+CTwOkG7vtvNbg/BDwEUFNT81v7RURERCR2BEPOq409bDjYwcsHO9h+tJtAyMlLT+KOmtncvrKUVRW5mjVXZAaaVCg1s0TCgfQH7v4EgLu3Ttj/78DTkZeNwOwJby8Hms9LtSIiIiIyYxztHOKlg+28fLCD3xzuoG8kAMCysiw+fVU1V80vYE1VHonxcVGuVEQupMnMvmvAN4B97v7VCe0lkftNAX4X2B3Z/inwsJl9lfBER/OBLee1ahERERGZlvY09/LYtkae39fG0a4hAEqzU7hpWTFXzi/kirn55GckR7lKEbmYJtNTegXwceA1M9sZaXsA+IiZrSA8NLcB+D0Ad99jZo8CewnP3Ps5zbwrIiIiEru6B8d4amcTP97WyJ7mPpLi47hqfgGfvKKSK+cXMrcwXcNyRWKYuUf/ds6amhqvra2NdhkiIiIicp4EQ86Gg+38eFsjz+1pZSwYYmlpFh9aXc77VpSRm54U7RJF5CIys23uXnO6fWc1+66IiIiIyNtp6Bjkx9uO8fi2Jo73jZCblshH11bwoZpylpZmR7s8EZmCFEpFRERE5JzUtQ/wzJ7j/GL3cXY19hJncO3CIr506xKuW1xEckJ8tEsUkSlMoVREREREzoq7s6+ln2f2HOeZ3S283joAwPLZOXzhPYu4fWUZs7JSolyliEwXCqUiIiIickahkLPjWA+/2HOcZ3Yf52jXEHEGa6ry+Ktbl3Dj0mJKc1KjXaaITEMKpSIiIiLyW4Ih58DxfrY2dLGloYst9V2094+SGG9cMa+A3792LtcvmUWBlm8RkXOkUCoiIiIijIwHebWxl60NXWxt6GLbkW76RwIAlGSnsL46n+sWFfGuRUVkpyZGuVoRmUkUSkVERERiTCjk1HcOsqe5jz1NvWw70s2rjb2MBUMAzC/K4JZLS1lTlctllXmU56ZFuWIRmckUSkVERERmsPFgiENtA+xp7mN3Uy97mnvZ29zH4FgQgKT4OBaXZnHP5XO4rDKPmso88rSGqIhcRAqlIiIiIjPAaCDIkc4h6toHONw+SF37IIfa+tl3vJ+xQLgHNC0pniUlWXxwdTlLy7JZVprNvKIMkhLioly9iMQyhVIRERGRaaRnaIx9Lf0cah+gvn2Quo4B6toHaeweIuRvHDcrK5m5hRl84vJKlpZmsbQ0m6qCdOLjLHrFi4ichkKpiIiIyBQUCjnHuofY29zHvpY+9rb0sbe5j+bekZPHpCbGU1WQzqXl2dy+soy5helUF2RQVZhORrJ+zBOR6UF/W4mIiIhE2eBogAOt/Rw43h8OoM197D/ez8BoePbbOIO5hRnUVOaxpDSLxSVZzC/KoDgrhTj1fIrINKdQKiIiInKRBENOQ+cg+1v6OXC8j33Hw0H0aNfQyWMykhNYXJLJ+1eVsaQkHEAXFmeSkhgfxcpFRC4chVIRERGRC8TdebWxl2f2HOflgx283trPaGTSoTiDqoJ0LinL5kOry1lYnMmi4izKc1PV+ykiMUWhVEREROQ8Coac2oYuntlznF/sPk5z7wjxcUbNnFw+vm4OC4szWVySxbyiDPV+iogwiVBqZrOB7wLFQAh4yN2/ZmZ/D9wKjAGHgXvdvcfMKoF9wIHIKTa5+2cvRPEiIiIiU8FYIMTGuk6e2X2c5/Yep2NgjKSEOK6eX8Af37iQ6xcXkZOmtT9FRE5nMj2lAeBP3H27mWUC28zsOeA54AvuHjCzB4EvAPdH3nPY3VdckIpFREREosjdaesfZf/xfva39LG7uY9fH2ijbyRAWlI871pUxHuWFXPtwiLNgCsiMgln/JvS3VuAlsh2v5ntA8rc/dkJh20CPnhhShQREZHpIBAM0T8SoH8kQN/IePgxPE7vhEfP0Jtf9w6PMzwWJDMlgezURHLSkshOTfytR05aIqmJ8cTFGXFmxBlY5DnOjPg4wyLbGckJZKclkpmcgNm53Zs5NBbg9dYB9reEZ8Pdf7yPA8f76R4aP3nMrKxkblxazE1Li7lyfoGG5IqInKWz+vVdZGjuSmDzKbs+CTwy4XWVme0A+oAvuvuG05zrPuA+gIqKirMpQ0RERC6QobEAPUOnhsex0wbKcAAdPxlEh8eDb3vu+Dh7U9DMTUuiMj+d1MR4+kfD52zrH+H11v6T5z8Xccabw+3JwJtAelICI+NBhsaCDI0HGR4LMjQWiDwHGY60dQ2N4R4+X1pSPAtmZXLTsmIWzspkUUkWi4ozNSxXROQcTTqUmlkG8DjwR+7eN6H9LwkP8f1BpKkFqHD3TjNbDTxpZksnvgfA3R8CHgKoqanxc/saIiIicjb6R8Z5vXWAg639HGjt52DrAK+39tPWP/qW75kYKrNSEshKTaQ0J4XM5EQyUxLITEkkKzX8HH6dMKGnM4n0pPiz6rkMhvxkT2vP8Dgj40FC7rhDyJ1Q5NndCYXC28GQMzAaeMve2WNdQ/QOjzM4GiAlMZ60pHhSk8LPaYkJ5KQlUZL9RntRZgqLSjJZVJzJ7Nw0zYorInIBTCqUmlki4UD6A3d/YkL7PcAtwLvdw79HdPdRYDSyvc3MDgMLgNrzXLuIiIicgbtzrGuY2iNd7I+siXmwtZ/m3pGTx6QmxjN/VgZXLyikujCdvBM9imlvHkKbcR6Gw56N+DgjNz2J3HT1RIqIzGSTmX3XgG8A+9z9qxPabyI8sdE17j40ob0Q6HL3oJlVA/OBuvNeuYiIiPyWYMjZf7yPrfVdbD3Szdb6rpO9n0kJccwrzGBtdT7zZ2WwoCiThcWZlOVoXUwREYmeyfSUXgF8HHjNzHZG2h4A/hlIBp6L/Nb0xNIvVwNfMbMAEAQ+6+5d57twERERgZHxILuO9bC1oYutDd1sP9JN/2j4XsyynFTWz83nsso8LqvMY15RBvEKnyIiMsVMZvbdl4HT/Qv287c4/nHCQ31FRETkPBsLhNh5rIeNhzvZWNfB9qM9jAVCACyYlcFtK0rDIbQqj7Kc1ChXKyIicmZaPEtERGQKGw+GeLWxl011nWw83EntkS5GxkOYwZKSLO5eN4e11fnUzMnVvZciIjItKZSKiIhMIe5OfccgLxxo56XX26lt6GJwLLzUyqLiTO68rIL1c/NZW5WnpUhERGRGUCgVERGJsuGxIJvqOnnxQBsvHGjnaFd4/sC5hel8YHU566vzWVudT556QkVEZAZSKBUREYmCI52DvLC/jRdfb2fj4U5GAyFSE+O5fG4+n7m6mmsXFDI7Ly3aZYqIiFxwCqUiIiIX2Mh4kL0tfew61sOuYz3sONbDkc5wb2h1QTofXVvBuxYWsaYqj5TE+ChXKyIicnEplIqIiJxHoZBT1zHAzmO94RDa2MO+lj7Ggw7ArKxklpfncO/llVy7sIjKgvQoVywiIhJdCqUiIiLnKBhyXnq9nUe2HuOVQx0n1wnNSE7g0vJsPn1VNcvLc1gxO4fi7JQoVysiIjK1KJSKiIi8Q8e6hni09hg/rm3keN8I+elJ3LqilFUVuayYnU11QQZxcadb6ltEREROUCgVERE5CyPjQZ7d28ojW4/yyqFOzOCaBYV86dYlvHvxLJIS4qJdooiIyLSiUCoiIjIJ+4/38cjWY/xkRxM9Q+OU5aTyxzcs4IOryynNSY12eSIiItOWQqmIiMhbcHdePNDO/33pMJvqukiKj+PGpbP48GWzuWJugYbmioiInAcKpSIiIqcYC4R4amcT/76hjtdbByjJTuGBmxfxwdWzyUtPinZ5IiIiM4pCqYiISETv8DgPbz7Kt39TT2vfKIuKM/nqHcu5dXkpifG6V1RERORCUCgVEZGY19QzzLderueHW44yOBbkynkF/K8PLufq+QWYaYiuiIjIhaRQKiIiMSkYcn5zuIMf1zby89dacOCWS0v4zFXVLCvLjnZ5IiIiMUOhVEREYsq+lj5+sqOJp3Y20do3SmZKAnevr+STV1ZSnpsW7fJERERizhlDqZnNBr4LFAMh4CF3/5qZ5QGPAJVAA3CHu3dH3vMF4FNAEPi8u//iglQvIiIyCa19Izy1s4kntjex/3g/CXHGtQsL+R+3lPPuxUWkJMZHu0QREZGYNZme0gDwJ+6+3cwygW1m9hzwCeB5d/87M/sL4C+A+81sCXAnsBQoBX5pZgvcPXhhvoKIiMibuTsdA2O8fKidJ7Y38cqhDkIOy2fn8OXblnLLpSXkZyRHu0wRERFhEqHU3VuAlsh2v5ntA8qA9wHXRg77DvAicH+k/UfuPgrUm9khYA2w8XwXLyIisWs8GKKpe5ijXUMc6RriaOdgeLtziGNdQwyOhX8XWp6byufeNY/bV5YxtzAjylWLiIjIqc7qnlIzqwRWApuBWZHAiru3mFlR5LAyYNOEtzVG2k49133AfQAVFRVnXbiIiMSOgdEArzX2squxh13HetjT3EdTzzDBkJ88Jikhjoq8NCry0lhXnc+c/DSWlWWzuiKXuDjNoCsiIjJVTTqUmlkG8DjwR+7e9zZT5J9uh/9Wg/tDwEMANTU1v7VfRERi03gwxIHj/exq7GHn0R52NfZwsG0Aj/xLUZGXxiVl2dy2vJSK/DTm5KVRkZ/GrMwUhU8REZFpaFKh1MwSCQfSH7j7E5HmVjMrifSSlgBtkfZGYPaEt5cDzeerYBERmVl6h8bZdrSLLfXd1DZ08VpTL6OBEAC5aYmsmJ3DzZeUsHx2DsvLc8hLT4pyxSIiInI+TWb2XQO+Aexz969O2PVT4B7g7yLPT01of9jMvkp4oqP5wJbzWbSIiExfLb3DbKnvYmtDF7UN3Rxo7ccdEuKMS8qz+di6OSyfncOK8hxm56XyNiNzREREZAaYTE/pFcDHgdfMbGek7QHCYfRRM/sUcBT4EIC77zGzR4G9hGfu/Zxm3hURiU2BYIgDrf3sONrDtiPdbKnvoqlnGID0pHhWzcnlvZeUUFOZx4rZOaQmaWkWERGRWGPu0b+ds6amxmtra6NdhoiInKP2/lF2HO1mx7Eedhzt5tXGXoYis+AWZCSzpiqXmjl5rKnKY1FxJgnxcVGuWERERC4GM9vm7jWn23dWs++KiIicEAw5+4/3sbW+i+1He9hxrJtjXeFe0IQ4Y2lpFnfUzGZlRQ6rKnIpz9VQXBEREfltCqUiIjIpgWCIPc19bK7vZHNd+J7QvpEAAMVZKayak8Pd6ypZWZHDsrJsUhI1FFdERETOTKFUREROaywQ4rWmHjbVdbGlvottR7oZGA2H0OqCdN57aQlrqvJYU5VPWU5qlKsVERGR6UqhVEREcHeOdg2x81gPu471squxh90TlmZZMCuD21eWsrYqn7VVeRRlpUS5YhEREZkpFEpFRGJQ58Aouxp72Hmsl13HetjV2EPP0DgAKYlxXFIWXprlsspcLqvMIz8jOcoVi4iIyEylUCoiEiPa+kZ4amczP9nRxN6WPgDiDBbMyuR3lhSzoiKH5eU5LJiVoVlxRURE5KJRKBURmcGGxgI8u6eVx7c38sqhDkIOy8uzuf+mRayKTEiUnqx/CkRERCR69JOIiMgMEww5Gw938sSORp7ZfZyhsSBlOan8/rXzuH1lGfOKMqJdooiIiMhJCqUiIjPAaCDIjqM9vLC/jad2NnO8b4TM5ARuvbSU311VxprKPOLitEaoiIiITD0KpSIi01Ao5Oxt6ePlQx28cqiDrQ1djIyHSIgzrllQyBdvWcz1i2dprVARERGZ8hRKRUSmAXenvmOQVw538ptDHWys6zw5W+78ogzuvKyCy+fms7Y6n+zUxChXKyIiIjJ5CqUiIlOUu/NaUy9Pv9rCz19robF7GIDS7BRuWDyLK+YVcPncfK0ZKiIiItOaQqmIyBTiHh6W+/SrLfznqy0c7RoiMd64cl4Bn71mLlfMK6AyPw0z3R8qIiIiM4NCqYhIlLk7B1r7+c9XW3j61RbqOwaJjzOumFfAH7xrHr+ztJjsNA3JFRERkZlJoVRE5AJzdwbHgrT3j558dAy8sb3taDeH2gaIM1g/N5/PXFXNTcuKyUtPinbpIiIiIhfcGUOpmX0TuAVoc/dlkbZHgIWRQ3KAHndfYWaVwD7gQGTfJnf/7PkuWkRkqhkZD9LQOUhd+yB17QPUtQ9ypGuItv4ROvrHGB4P/tZ74uOM/PQk5hZmcM/6Ody0rITCzOQoVC8iIiISPZPpKf028C/Ad080uPuHT2yb2T8CvROOP+zuK85TfSIiU8ZYIERL7zDHuoap7xjgcPsgdR3hENrUM4z7G8cWZ6VQWZDG6opcCjOTKcxMpiAj+eR2YUYyuWlJWjtUREREYt4ZQ6m7vxTpAf0tFp5p4w7guvNcl4jIRRcKOc29wzR2D3Osa4hj3cM0dg/R2BV+Pt43QmhC8ExLiqeqIJ2VFbl8YFU51YXpzC3MoKognfRk3R0hIiIiMhnn+lPTVUCrux+c0FZlZjuAPuCL7r7hHD9DROSCcHdebx1g4+Hwup+b67tOrv0JYAYlWSmU56axrjqf8rw0ynNTKc9NpaogneKsFM2CKyIiInKOzjWUfgT44YTXLUCFu3ea2WrgSTNb6u59p77RzO4D7gOoqKg4xzJERM7M3TncPsDGw51squtiU10nnYNjAJTnpnLD4lmsrMilIi+N2XmplGSnkpQQF+WqRURERGa2dxxKzSwBeD+w+kSbu48Co5HtbWZ2GFgA1J76fnd/CHgIoKamxk/dLyJyrsaDIfa19LHjaA+1R7rZVNdJe/8oACXZKVyzoJB1c/NZX53P7Ly0KFcrIiIiEpvOpaf0emC/uzeeaDCzQqDL3YNmVg3MB+rOsUYRkUk53jvCjqPd7DjWw46j3bza2MtoIATArKxk1lfnsz4SQufkp2norYiIiMgUMJklYX4IXAsUmFkj8CV3/wZwJ28eugtwNfAVMwsAQeCz7t51fksWEQkvwbKnuS8cQo+GQ2hz7wgASfFxLCvL4mPr5rCyIoeVFbmUZuv+TxEREZGpaDKz737kLdo/cZq2x4HHz70sEZE3uDuN3cPsONbD9iPhntC9zb2MB8Mj/8tyUlldmcenZ+ewsiKHJaVZJCfER7lqEREREZkMrVkgIlNOIBhiV2MvW+q72HG0m+1He+gYCN8LmpIYx6XlOXzqyupwL+jsHIqyUqJcsYiIiIi8UwqlIhJ17s6RziE2HOpgw+vtbKzrpH8kAEBVQTpXzy9g5ZxcVs7OYVFxJgnxmhFXREREZKZQKBWRqOgZGuM3hzvZcLCDDQfbaeweBsJDcd97SQlXzi9gfXU++RnJUa5URERERC4khVIRuSj6Rsapbehic30Xmw538mpTL+6QmZzAurn53Hd1NVfNL6RSs+KKiIiIxBSFUhG5IHqGxthSHw6hm+s72dvcR8ghMd5YXp7D56+bz1XzC1g+O4dEDccVERERiVkKpSJyXrT0DrP9SA9b6jvZXN/F/uP9ACQlxLGqIoc/uG4+66ryWFmRS2qSZsYVERERkTCFUhE5ayPjQXY39bL95BqhPRzvC68RmpoYT01lLu+9pIS11fksn52t5VlERERE5C0plIrIGTV2D1Hb0M2OoyfWCO0jEAqvETo7L5W11XmsnJ3DiopclpZmaTiuiIiIiEyaQqmIvMmJ5Vk213eyuS58T2hTT3hm3NTEeJbPzuYzV1ezqiKXFbNzKMzU7LgiIiIi8s4plIrEOHfncPsAm+q6IhMTddLaNwpAfnoSa6ry+PRVVVxWmac1QkVERETkvFMoFYkxoZBzoLX/ZADdUt9Fx8AYAEWZyaytzmdNVR7rqvKYV5Sh5VlERERE5IJSKBWZ4YIhZ29zX3g4bn0XWxu66BkaB6AsJ5Wr5heytiqPtdX5WiNURERERC46hVKRGWY8GOK1pl4213Wxpb6T2oZu+kcDAMzJT+PGJbNYWxXuDZ2dlxblakVEREQk1imUikxzo4Egu471nlwfdNuRbobGggDMLUzn1hWl4Z7QqnyKs1OiXK2IiIiIyJsplIpMM2OBELVHuiIz43ay42gPo4EQAIuKM/nQ6nLWRHpCNTOuiIiIiEx1CqUi00Rd+wA/2nqMx7Y10jU4hhksKcnirrVzWFudx5rKPHLTk6JdpoiIiIjIWTljKDWzbwK3AG3uvizS9lfAZ4D2yGEPuPvPI/u+AHwKCAKfd/dfXIC6RWLCyHiQX+w5zsObj7K5vouEOOP6xbN4/6oy1lbnk52aGO0SRURERETOyWR6Sr8N/Avw3VPa/8nd/2Fig5ktAe4ElgKlwC/NbIG7B89DrSIx42BrPz/ccowndjTSMzRORV4af37TQj64upyiTN0XKiIiIiIzxxlDqbu/ZGaVkzzf+4AfufsoUG9mh4A1wMZ3XqJIbGjrH+Gl1zt4ZOtRtjZ0kxhv3Li0mI+uqWB9dT5xcVqqRURERERmnnO5p/QPzOxuoBb4E3fvBsqATROOaYy0/RYzuw+4D6CiouIcyhCZftydhs4httZ3saWhi9qGLho6hwCoKkjngZsX8f5V5RRkaKIiEREREZnZ3mko/VfgrwGPPP8j8EngdF05froTuPtDwEMANTU1pz1GZKYIBEPsa+lna0NX5NFNx8AoADlpidTMyeOjaytYU5XP8vJszNQrKiIiIiKx4R2FUndvPbFtZv8OPB152QjMnnBoOdD8jqsTmcYGRwO89Ho7z+5t5fl9rfSNBAAoy0nlqvkFXFaZx2WVucwtzNDQXBERERGJWe8olJpZibu3RF7+LrA7sv1T4GEz+yrhiY7mA1vOuUqRaaJjYJTn97Xy7J5WNhzqYCwQIictkRuWFHP1gnAQLc1JjXaZIiIiIiJTxmSWhPkhcC1QYGaNwJeAa81sBeGhuQ3A7wG4+x4zexTYCwSAz2nmXZnpjnQO8tzeVn6x5zi1R7pxD/eG3rW2ghuXFHNZZS4J8XHRLlNEREREZEoy9+jfzllTU+O1tbXRLkPkjHqHxnmtqZdXm3p4rbGXVxt7aeoZBmBxSRY3LpnFjUtnsaQkS/eFioiIiIhEmNk2d6853b5zmX1XZEbrHxlnd1MfrzX18GpjL6819XIkMkMuwJz8NFZU5PDJK6u4YfEsKvLTolitiIiIiMj0pFAqEtE/Ms6W+i42Hu5kY10ne1v6ODGQoCwnlUvLs/nwZbO5tCyHZWVZ5KQlRbdgEREREZEZQKFUYtbgaICtDV1srOtk0+FOXmvqJeSQFB/HyoocPn/dfFZW5HBJWTb5Wi9UREREROSCUCiVmBAMOfUdg+xt6WNvcx9bG7rYdayHQMhJjDeWl+fwuXfNY311Pqvm5JKSGB/tkkVEREREYoJCqcw4A6MBDhwPh8+9LX3sbennwPE+RsZDACTGG0tLs/nM1dWsr86npjKXtCRdCiIiIiIi0aCfxGVacHcGx4J0DozSMTBG1+AYnQOjdA6O0TkwRufgKJ0DYzR2D9EwYTKinLREFhdncdfaOSwpyWJxSRbzijJIStASLSIiIiIiU4FCqUwJo4EgLT0jNPcM09gzTPPJxwhNke3RQOi0781ITiAvPYn8jCSWlGbxgVXlLCkNB9CS7BQtzSIiIiIiMoUplMpFNTwW5EBrP/si93bua+njSNcQ7f2jbzrODIoykynNSWVJaRbXLy6iMDOZvPRk8jOSKEhPJi8jifz0JN3/KSIiIiIyjSmUygXT1j9y8r7OfS397G3upb5jkFBkmZXM5AQWl2Tx7kVFlOakUpaTevJ5VnYyyQkKmyIiIiIiM51CqZyzQDD0ppltwyG0j46BsZPHlOemsrgki1suLWVJaRZLSrIoz03V0FoRERERkRinUCpnpX9knP3H+08Ovd3b0seB4/0n7/dMio9j/qwM3rWwiMUlWSfv7cxOTYxy5SIiIiIiMhUplMppuTvNvZHhtxMC6NGuN2a2zU1LZElpFnevn3MygM4tzCAxXjPbioiIiIjI5CiUxrjhseDJ2W2beoY52DrA3pZe9jb30TcSAMKTDlXmp3NJWTZ31JSzuCSLpaXZzMpK1vBbERERERE5JwqlM4C7MxYMMTIeYnQ8yGggxMh4MPw6EH7uGxk/GTybuodp7g0vt9I1OPamc6UkxrGoOItblpeGez9LslhUnEl6sv5XERERERGR809JI8rcnb6RAD1DY3QNjtEzNE7X4BjdQ2P0jwQYGA0wOPrG8+BoMLw99sbrkUAQ98l9XlpSPGU5qZTlpnJpeU54OzLrbWlOCiXZqcTHqfdTREREREQujjOGUjP7JnAL0ObuyyJtfw/cCowBh4F73b3HzCqBfcCByNs3uftnL0ThU0Uo5IyHQowFQowGQvQNj9N76mMo/Nwz4XXX0Bg9Q+EQGgi9daJMS4onPTmBjOQE0pPjSU9KoCQ7hfTkhPAjKZ7UpHhSEuNJTogjOTGelAnPJ9ozUxIpy0klKzVBQ25FRERERGTKmExP6beBfwG+O6HtOeAL7h4wsweBLwD3R/YddvcV57PIaLv3W1to6BxiLBBiLBhiPBgOoePBEOPByXVRpiXFk52aePIxvyiDnLQk8tITyU1LCj8mbqclkZmSQJx6LUVEREREZAY7Yyh195ciPaAT256d8HIT8MHzXNeUUlmQTmZKIonxcSQlxJEUbye332gLP2elJkwIn0knt5MSNCOtiIiIiIjIqc7HPaWfBB6Z8LrKzHYAfcAX3X3DefiMqPrSrUujXYKIiIiIiMiMdE6h1Mz+EggAP4g0tQAV7t5pZquBJ81sqbv3nea99wH3AVRUVJxLGSIiIiIiIjJNveMxpWZ2D+EJkO5yD8/96u6j7t4Z2d5GeBKkBad7v7s/5O417l5TWFj4TssQERERERGRaewdhVIzu4nwxEa3ufvQhPZCM4uPbFcD84G681GoiIiIiIiIzDyTWRLmh8C1QIGZNQJfIjzbbjLwXGR5kRNLv1wNfMXMAkAQ+Ky7d12g2kVERERERGSam8zsux85TfM33uLYx4HHz7UoERERERERiQ1ap0RERERERESiRqFUREREREREokahVERERERERKLGIqu5RLcIs3bgSLTrkKgpADqiXYRIFOkakFina0BE14HMfHPc/bRrgU6JUCqxzcxq3b0m2nWIRIuuAYl1ugZEdB1IbNPwXREREREREYkahVIRERERERGJGoVSmQoeinYBIlGma0Bina4BEV0HEsN0T6mIiIiIiIhEjXpKRUREREREJGoUSkVERERERCRqFErlojGz2Wb2gpntM7M9ZvaHkfY8M3vOzA5GnnOjXavIhWRm8Wa2w8yejrzWNSAxxcxyzOwxM9sf+Tdhva4DiSVm9t8jPwvtNrMfmlmKrgGJZQqlcjEFgD9x98XAOuBzZrYE+AvgeXefDzwfeS0yk/0hsG/Ca10DEmu+Bjzj7ouA5YSvB10HEhPMrAz4PFDj7suAeOBOdA1IDFMolYvG3VvcfXtku5/wDyFlwPuA70QO+w5we1QKFLkIzKwceC/wHxOadQ1IzDCzLOBq4BsA7j7m7j3oOpDYkgCkmlkCkAY0o2tAYphCqUSFmVUCK4HNwCx3b4FwcAWKoliayIX2/wF/DoQmtOkakFhSDbQD34oMY/8PM0tH14HECHdvAv4BOAq0AL3u/iy6BiSGKZTKRWdmGcDjwB+5e1+06xG5WMzsFqDN3bdFuxaRKEoAVgH/6u4rgUE0TFFiSORe0fcBVUApkG5mH4tuVSLRpVAqF5WZJRIOpD9w9yciza1mVhLZXwK0Ras+kQvsCuA2M2sAfgRcZ2bfR9eAxJZGoNHdN0deP0Y4pOo6kFhxPVDv7u3uPg48AVyOrgGJYQqlctGYmRG+h2ifu391wq6fAvdEtu8BnrrYtYlcDO7+BXcvd/dKwpNa/MrdP4auAYkh7n4cOGZmCyNN7wb2outAYsdRYJ2ZpUV+Nno34Xk2dA1IzDJ3j3YNEiPM7EpgA/Aab9xP9wDh+0ofBSoI/0X9IXfvikqRIheJmV0L/Km732Jm+egakBhiZisIT/aVBNQB9xL+RbmuA4kJZvZl4MOEVybYAXwayEDXgMQohVIRERERERGJGg3fFRERERERkahRKBUREREREZGoUSgVERERERGRqFEoFRERERERkahRKBUREREREZGoUSgVERERERGRqFEoFRERERERkaj5/wHbZNKxs3R4LwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1152x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Moving Average\n",
    "\n",
    "plt.figure(figsize=(16,4))\n",
    "air.Passengers.plot(label=\"org\")\n",
    "plt.title(\"Original Series\")\n",
    "for i in range(2,13):\n",
    "    plt.figure(figsize=(16,4))\n",
    "    air[\"Passengers\"].rolling(i).mean().plot(label=str(i))\n",
    "    plt.title(\"Moving Average \"+str(i))\n",
    "    plt.legend(loc='best')\n",
    "    plt.show() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "1802f3f6",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:47.993476Z",
     "start_time": "2022-11-15T06:34:47.710043Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Time series decomposition plot\n",
    "from statsmodels.tsa.seasonal import seasonal_decompose \n",
    "\n",
    "decompose_ts_add = seasonal_decompose(air.Passengers,period=12)\n",
    "decompose_ts_add.plot()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aaf492c9",
   "metadata": {},
   "source": [
    "## ACF plots and PACF plots:\n",
    "    The autocorrelation function (ACF) is a statistical technique that we can use to identify how correlated the values in a time series are with each other. The ACF plots the correlation coefficient against the lag, which is measured in terms of a number of periods or units.\n",
    "The correlation coefficient can range from -1 (a perfect negative relationship) to +1 (a perfect positive relationship). A coefficient of 0 means that there is no relationship between the variables.\n",
    "\n",
    "Partial autocorrelation is a statistical measure that captures the correlation between two variables after controlling for the effects of other variables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "9a08fc4f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:48.155854Z",
     "start_time": "2022-11-15T06:34:47.993476Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import statsmodels.graphics.tsaplots as tsa_plots\n",
    "plt.rc(\"figure\", figsize=(12,4)) \n",
    "tsa_plots.plot_acf(air.Passengers,lags=94)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1095e759",
   "metadata": {},
   "source": [
    "Notice that for a lag zero, ACF is always equal to one, which makes sense because the signal is always perfectly correlated with itself."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "85dea1e7",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:48.284990Z",
     "start_time": "2022-11-15T06:34:48.155854Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rc(\"figure\", figsize=(12,4))\n",
    "tsa_plots.plot_pacf(air.Passengers,lags=40)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0d4ffc97",
   "metadata": {},
   "source": [
    "# Forecasting: Model based methods "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "fc13d3ca",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:48.301041Z",
     "start_time": "2022-11-15T06:34:48.284990Z"
    }
   },
   "outputs": [],
   "source": [
    "Train = air1.head(72)\n",
    "Test = air1.tail(24) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "1734cf1f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:48.381094Z",
     "start_time": "2022-11-15T06:34:48.301041Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "51.667792995646266"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Linear Model\n",
    "import statsmodels.formula.api as smf \n",
    "\n",
    "linear_model = smf.ols('Passengers~t',data=Train).fit()\n",
    "pred_linear =  pd.Series(linear_model.predict(pd.DataFrame(Test['t'])))\n",
    "rmse_linear = np.sqrt(np.mean((np.array(Test['Passengers'])-np.array(pred_linear))**2))\n",
    "rmse_linear "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "995f0350",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:48.397100Z",
     "start_time": "2022-11-15T06:34:48.381094Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "42.552328946004586"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Exponential\n",
    "\n",
    "Exp = smf.ols('log_passengers~t',data=Train).fit()\n",
    "pred_Exp = pd.Series(Exp.predict(pd.DataFrame(Test['t'])))\n",
    "rmse_Exp = np.sqrt(np.mean((np.array(Test['Passengers'])-np.array(np.exp(pred_Exp)))**2))\n",
    "rmse_Exp "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "124ed5d1",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:48.429055Z",
     "start_time": "2022-11-15T06:34:48.397100Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "51.99073640155471"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Quadratic \n",
    "\n",
    "Quad = smf.ols('Passengers~t+t_squared',data=Train).fit()\n",
    "pred_Quad = pd.Series(Quad.predict(Test[[\"t\",\"t_squared\"]]))\n",
    "rmse_Quad = np.sqrt(np.mean((np.array(Test['Passengers'])-np.array(pred_Quad))**2))\n",
    "rmse_Quad"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "63e83704",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:48.462007Z",
     "start_time": "2022-11-15T06:34:48.429055Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "127.2645156532034"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Additive seasonality \n",
    "\n",
    "add_sea = smf.ols('Passengers ~ month_Apr + month_Aug+  month_Dec+ month_Feb+  month_Jan+  month_Jul+ month_Jun+  month_Mar+  month_May+  month_Nov+  month_Oct+ month_Sep',  data=Train).fit()\n",
    "\n",
    "pred_add_sea = pd.Series(add_sea.predict(Test[[ 'month_Apr',\n",
    "       'month_Aug', 'month_Dec', 'month_Feb', 'month_Jan', 'month_Jul',\n",
    "       'month_Jun', 'month_Mar', 'month_May', 'month_Nov', 'month_Oct',\n",
    "       'month_Sep']]))\n",
    "rmse_add_sea = np.sqrt(np.mean((np.array(Test['Passengers'])-np.array(pred_add_sea))**2))\n",
    "rmse_add_sea "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "79d24b8c",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:48.510425Z",
     "start_time": "2022-11-15T06:34:48.462007Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "35.24160848593291"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Additive Seasonality Quadratic \n",
    "\n",
    "add_sea_Quad = smf.ols('Passengers ~t +t_squared + month_Apr + month_Aug+  month_Dec+ month_Feb+  month_Jan+  month_Jul+ month_Jun+  month_Mar+  month_May+  month_Nov+  month_Oct+ month_Sep',data=Train).fit()\n",
    "pred_add_sea_quad = pd.Series(add_sea_Quad.predict(Test[['month_Apr',\n",
    "       'month_Aug', 'month_Dec', 'month_Feb', 'month_Jan', 'month_Jul',\n",
    "       'month_Jun', 'month_Mar', 'month_May', 'month_Nov', 'month_Oct',\n",
    "       'month_Sep','t','t_squared']]))\n",
    "rmse_add_sea_quad = np.sqrt(np.mean((np.array(Test['Passengers'])-np.array(pred_add_sea_quad))**2))\n",
    "rmse_add_sea_quad"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "31caf342",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:48.558562Z",
     "start_time": "2022-11-15T06:34:48.510425Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "132.18762800263448"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##Multiplicative Seasonality\n",
    "\n",
    "Mul_sea = smf.ols('log_passengers ~ month_Apr + month_Aug+  month_Dec+ month_Feb+  month_Jan+  month_Jul+ month_Jun+  month_Mar+  month_May+  month_Nov+  month_Oct+ month_Sep',data = Train).fit()\n",
    "pred_Mult_sea = pd.Series(Mul_sea.predict(Test))\n",
    "rmse_Mult_sea = np.sqrt(np.mean((np.array(Test['Passengers'])-np.array(np.exp(pred_Mult_sea)))**2))\n",
    "rmse_Mult_sea "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "e0ee2d9e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:48.607393Z",
     "start_time": "2022-11-15T06:34:48.558562Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "132.18762800263448"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Multiplicative Additive Seasonality \n",
    "\n",
    "\n",
    "Mul_Add_sea = smf.ols('log_passengers ~ t+ month_Apr + month_Aug+  month_Dec+ month_Feb+  month_Jan+  month_Jul+ month_Jun+  month_Mar+  month_May+  month_Nov+  month_Oct+ month_Sep',data = Train).fit()\n",
    "pred_Mult_add_sea = pd.Series(Mul_sea.predict(Test))\n",
    "rmse_Mult_add_sea = np.sqrt(np.mean((np.array(Test['Passengers'])-np.array(np.exp(pred_Mult_add_sea)))**2))\n",
    "rmse_Mult_add_sea "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "326dffed",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:48.623715Z",
     "start_time": "2022-11-15T06:34:48.607393Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MODEL</th>\n",
       "      <th>RMSE_Values</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>add_sea_quad</td>\n",
       "      <td>35.241608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Exp</td>\n",
       "      <td>42.552329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>linear</td>\n",
       "      <td>51.667793</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Quad</td>\n",
       "      <td>51.990736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>add_sea</td>\n",
       "      <td>127.264516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Mult_sea</td>\n",
       "      <td>132.187628</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Mult_add_sea</td>\n",
       "      <td>132.187628</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          MODEL  RMSE_Values\n",
       "4  add_sea_quad    35.241608\n",
       "1           Exp    42.552329\n",
       "0        linear    51.667793\n",
       "2          Quad    51.990736\n",
       "3       add_sea   127.264516\n",
       "5      Mult_sea   132.187628\n",
       "6  Mult_add_sea   132.187628"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Compare the results \n",
    "\n",
    "data = {\"MODEL\":pd.Series([\"linear\",\"Exp\",\"Quad\",\"add_sea\",\"add_sea_quad\",\"Mult_sea\",\"Mult_add_sea\"]),\"RMSE_Values\":pd.Series([rmse_linear,rmse_Exp,rmse_Quad,rmse_add_sea,rmse_add_sea_quad,rmse_Mult_sea,rmse_Mult_add_sea])}\n",
    "table_rmse=pd.DataFrame(data)\n",
    "table_rmse.sort_values(['RMSE_Values']) "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bfd39307",
   "metadata": {},
   "source": [
    "# Forecasting: Data Driven Models "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "7a87a70b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:48.688413Z",
     "start_time": "2022-11-15T06:34:48.623715Z"
    }
   },
   "outputs": [],
   "source": [
    "from statsmodels.tsa.seasonal import seasonal_decompose\n",
    "from statsmodels.tsa.holtwinters import SimpleExpSmoothing # SES\n",
    "from statsmodels.tsa.holtwinters import Holt # Holts Exponential Smoothing\n",
    "from statsmodels.tsa.holtwinters import ExponentialSmoothing  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "5b74c7ae",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:48.802361Z",
     "start_time": "2022-11-15T06:34:48.688413Z"
    }
   },
   "outputs": [],
   "source": [
    "import math  \n",
    "import sklearn.metrics  \n",
    "\n",
    "def rmse(actual, pred):\n",
    "    mse = sklearn.metrics.mean_squared_error(actual, pred)  \n",
    "    rmse = math.sqrt(mse)\n",
    "    return rmse "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "bc0bf689",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:48.818822Z",
     "start_time": "2022-11-15T06:34:48.802361Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "83.65334103034091"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Simple Exponential Method\n",
    "ses_model = SimpleExpSmoothing(Train[\"Passengers\"]).fit(smoothing_level=0.2)\n",
    "pred_ses = ses_model.predict(start = Test.index[0],end = Test.index[-1])\n",
    "rmse_ses = rmse(Test.Passengers, pred_ses) \n",
    "rmse_ses "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "16ed271e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:48.843220Z",
     "start_time": "2022-11-15T06:34:48.818822Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "148.1869009913489"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Holt method \n",
    "hw_model = Holt(Train[\"Passengers\"]).fit(smoothing_level=0.8, smoothing_slope=0.2)\n",
    "pred_hw = hw_model.predict(start = Test.index[0],end = Test.index[-1])\n",
    "rmse_hw = rmse(Test.Passengers, pred_hw) \n",
    "rmse_hw "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "27092cd4",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:48.964312Z",
     "start_time": "2022-11-15T06:34:48.843220Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "77.9631220021473"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Holts winter exponential smoothing with additive seasonality and additive trend\n",
    "hwe_model_add_add = ExponentialSmoothing(Train[\"Passengers\"],seasonal=\"add\",trend=\"add\",seasonal_periods=4).fit() #add the trend to the model\n",
    "pred_hwe_add_add = hwe_model_add_add.predict(start = Test.index[0],end = Test.index[-1])\n",
    "rmse_hwe_add_add = rmse(Test.Passengers, pred_hwe_add_add)  \n",
    "rmse_hwe_add_add"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "e5244554",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:49.118016Z",
     "start_time": "2022-11-15T06:34:48.964312Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "79.08022821080365"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Holts winter exponential smoothing with multiplicative seasonality and additive trend\n",
    "hwe_model_mul_add = ExponentialSmoothing(Train[\"Passengers\"],seasonal=\"mul\",trend=\"add\",seasonal_periods=4).fit() \n",
    "pred_hwe_mul_add = hwe_model_mul_add.predict(start = Test.index[0],end = Test.index[-1])\n",
    "rmse_mul_add =rmse(Test.Passengers, pred_hwe_mul_add) \n",
    "rmse_mul_add"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "227a824a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:49.133982Z",
     "start_time": "2022-11-15T06:34:49.118016Z"
    }
   },
   "outputs": [],
   "source": [
    "#Compare the results \n",
    "\n",
    "data = {\"MODEL\":pd.Series([\"linear\",\"Exp\",\"Quad\",\"add_sea\",\"add_sea_quad\",\"Mult_sea\",\"Mult_add_sea\",'ses_model', 'hw_model', 'hwe_model_add_add', 'hwe_model_mul_add']),\n",
    "        \"RMSE_Values\":pd.Series([rmse_linear,rmse_Exp,rmse_Quad,rmse_add_sea,rmse_add_sea_quad,rmse_Mult_sea,rmse_Mult_add_sea, rmse_ses, rmse_hw,rmse_hwe_add_add,rmse_mul_add  ])}\n",
    "table_rmse=pd.DataFrame(data) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "9b8d55cb",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:49.149981Z",
     "start_time": "2022-11-15T06:34:49.133982Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MODEL</th>\n",
       "      <th>RMSE_Values</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>add_sea_quad</td>\n",
       "      <td>35.241608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Exp</td>\n",
       "      <td>42.552329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>linear</td>\n",
       "      <td>51.667793</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Quad</td>\n",
       "      <td>51.990736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>hwe_model_add_add</td>\n",
       "      <td>77.963122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>hwe_model_mul_add</td>\n",
       "      <td>79.080228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>ses_model</td>\n",
       "      <td>83.653341</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>add_sea</td>\n",
       "      <td>127.264516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Mult_sea</td>\n",
       "      <td>132.187628</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Mult_add_sea</td>\n",
       "      <td>132.187628</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>hw_model</td>\n",
       "      <td>148.186901</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                MODEL  RMSE_Values\n",
       "4        add_sea_quad    35.241608\n",
       "1                 Exp    42.552329\n",
       "0              linear    51.667793\n",
       "2                Quad    51.990736\n",
       "9   hwe_model_add_add    77.963122\n",
       "10  hwe_model_mul_add    79.080228\n",
       "7           ses_model    83.653341\n",
       "3             add_sea   127.264516\n",
       "5            Mult_sea   132.187628\n",
       "6        Mult_add_sea   132.187628\n",
       "8            hw_model   148.186901"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "table_rmse = table_rmse.sort_values(by=['RMSE_Values']) \n",
    "table_rmse  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "3e91a78f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:49.357675Z",
     "start_time": "2022-11-15T06:34:49.149981Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(table_rmse.MODEL , table_rmse.RMSE_Values)\n",
    "plt.xticks(rotation = 90)\n",
    "plt.show() "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5706cf24",
   "metadata": {},
   "source": [
    "# Final Model by combining train and test "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "159626f7",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:49.405685Z",
     "start_time": "2022-11-15T06:34:49.357675Z"
    }
   },
   "outputs": [],
   "source": [
    "add_sea_Quad = smf.ols('Passengers ~t +t_squared + month_Apr + month_Aug+  month_Dec+ month_Feb+  month_Jan+  month_Jul+ month_Jun+  month_Mar+  month_May+  month_Nov+  month_Oct+ month_Sep',data=air1).fit()\n",
    "pred= add_sea_Quad.predict(air1.tail()) #predicting on historic data "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "3c79c406",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:49.421689Z",
     "start_time": "2022-11-15T06:34:49.405685Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>actual_passengers</th>\n",
       "      <th>Predicted_passengers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>405</td>\n",
       "      <td>371.0</td>\n",
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       "      <th>92</th>\n",
       "      <td>355</td>\n",
       "      <td>344.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>306</td>\n",
       "      <td>317.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>271</td>\n",
       "      <td>293.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>306</td>\n",
       "      <td>319.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    actual_passengers  Predicted_passengers\n",
       "91                405                 371.0\n",
       "92                355                 344.0\n",
       "93                306                 317.0\n",
       "94                271                 293.0\n",
       "95                306                 319.0"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "forecast_df = pd.DataFrame()\n",
    "\n",
    "forecast_df['actual_passengers'] = air1.Passengers.tail()\n",
    "forecast_df['Predicted_passengers'] = np.round(pred, 0)\n",
    "\n",
    "forecast_df  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "b84136dc",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:49.453690Z",
     "start_time": "2022-11-15T06:34:49.421689Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>t</th>\n",
       "      <th>t_squared</th>\n",
       "      <th>month_Apr</th>\n",
       "      <th>month_Aug</th>\n",
       "      <th>month_Dec</th>\n",
       "      <th>month_Feb</th>\n",
       "      <th>month_Jan</th>\n",
       "      <th>month_Jul</th>\n",
       "      <th>month_Jun</th>\n",
       "      <th>month_Mar</th>\n",
       "      <th>month_May</th>\n",
       "      <th>month_Nov</th>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>101</td>\n",
       "      <td>10201</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     t  t_squared  month_Apr  month_Aug  month_Dec  month_Feb  month_Jan  \\\n",
       "0   97       9409          0          0          0          0          1   \n",
       "1   98       9604          0          0          0          1          0   \n",
       "2   99       9801          0          0          0          0          0   \n",
       "3  100      10000          1          0          0          0          0   \n",
       "4  101      10201          0          0          0          0          0   \n",
       "\n",
       "   month_Jul  month_Jun  month_Mar  month_May  month_Nov  month_Oct  month_Sep  \n",
       "0          0          0          0          0          0          0          0  \n",
       "1          0          0          0          0          0          0          0  \n",
       "2          0          0          1          0          0          0          0  \n",
       "3          0          0          0          0          0          0          0  \n",
       "4          0          0          0          1          0          0          0  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#creating new inputs for forecasting\n",
    "new_df = pd.DataFrame() \n",
    "new_df['t'] = np.arange(97,109,1) \n",
    "new_df['t_squared'] = np.square(new_df.t)\n",
    "new_df['month'] = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec'] \n",
    "new_df = pd.get_dummies(new_df)\n",
    "new_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "cbe63f01",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:49.502185Z",
     "start_time": "2022-11-15T06:34:49.453690Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>t</th>\n",
       "      <th>t_squared</th>\n",
       "      <th>month_Apr</th>\n",
       "      <th>month_Aug</th>\n",
       "      <th>month_Dec</th>\n",
       "      <th>month_Feb</th>\n",
       "      <th>month_Jan</th>\n",
       "      <th>month_Jul</th>\n",
       "      <th>month_Jun</th>\n",
       "      <th>month_Mar</th>\n",
       "      <th>month_May</th>\n",
       "      <th>month_Nov</th>\n",
       "      <th>month_Oct</th>\n",
       "      <th>month_Sep</th>\n",
       "      <th>forcasted</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>97</td>\n",
       "      <td>9409</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>328.328687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>98</td>\n",
       "      <td>9604</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>329.438178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>99</td>\n",
       "      <td>9801</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>359.547668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>100</td>\n",
       "      <td>10000</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>354.907159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>101</td>\n",
       "      <td>10201</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>356.141650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>102</td>\n",
       "      <td>10404</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>385.376141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>103</td>\n",
       "      <td>10609</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>413.360631</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>104</td>\n",
       "      <td>10816</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>412.845122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>105</td>\n",
       "      <td>11025</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>385.829613</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>106</td>\n",
       "      <td>11236</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>358.939103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>107</td>\n",
       "      <td>11449</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>335.423594</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>108</td>\n",
       "      <td>11664</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>362.283085</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      t  t_squared  month_Apr  month_Aug  month_Dec  month_Feb  month_Jan  \\\n",
       "0    97       9409          0          0          0          0          1   \n",
       "1    98       9604          0          0          0          1          0   \n",
       "2    99       9801          0          0          0          0          0   \n",
       "3   100      10000          1          0          0          0          0   \n",
       "4   101      10201          0          0          0          0          0   \n",
       "5   102      10404          0          0          0          0          0   \n",
       "6   103      10609          0          0          0          0          0   \n",
       "7   104      10816          0          1          0          0          0   \n",
       "8   105      11025          0          0          0          0          0   \n",
       "9   106      11236          0          0          0          0          0   \n",
       "10  107      11449          0          0          0          0          0   \n",
       "11  108      11664          0          0          1          0          0   \n",
       "\n",
       "    month_Jul  month_Jun  month_Mar  month_May  month_Nov  month_Oct  \\\n",
       "0           0          0          0          0          0          0   \n",
       "1           0          0          0          0          0          0   \n",
       "2           0          0          1          0          0          0   \n",
       "3           0          0          0          0          0          0   \n",
       "4           0          0          0          1          0          0   \n",
       "5           0          1          0          0          0          0   \n",
       "6           1          0          0          0          0          0   \n",
       "7           0          0          0          0          0          0   \n",
       "8           0          0          0          0          0          0   \n",
       "9           0          0          0          0          0          1   \n",
       "10          0          0          0          0          1          0   \n",
       "11          0          0          0          0          0          0   \n",
       "\n",
       "    month_Sep   forcasted  \n",
       "0           0  328.328687  \n",
       "1           0  329.438178  \n",
       "2           0  359.547668  \n",
       "3           0  354.907159  \n",
       "4           0  356.141650  \n",
       "5           0  385.376141  \n",
       "6           0  413.360631  \n",
       "7           0  412.845122  \n",
       "8           1  385.829613  \n",
       "9           0  358.939103  \n",
       "10          0  335.423594  \n",
       "11          0  362.283085  "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "add_sea_Quad = smf.ols('Passengers ~t +t_squared + month_Apr + month_Aug+  month_Dec+ month_Feb+  month_Jan+  month_Jul+ month_Jun+  month_Mar+  month_May+  month_Nov+  month_Oct+ month_Sep',data=air1).fit()\n",
    "pred= add_sea_Quad.predict(new_df) \n",
    "\n",
    "new_df['forcasted'] = pred\n",
    "\n",
    "new_df "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "0733fad4",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-15T06:34:50.065008Z",
     "start_time": "2022-11-15T06:34:49.502185Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1f6e37d36a0>]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(18,6))\n",
    "plt.plot(air1.t , air1.Passengers)\n",
    "plt.plot(new_df.t , new_df.forcasted) "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "27334476",
   "metadata": {},
   "source": [
    "### We created dummy variables for Month feature and final model is based on Additive seasonality Quadratic. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4202bb1d",
   "metadata": {},
   "source": [
    "# Thank You "
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}