├── EDA Process ├── Objective 1 ├── Objective 2 ├── Objective 3 ├── Objective 4 ├── Objective 5 ├── Screenshot 2025-04-12 180724.png ├── Screenshot 2025-04-12 180754.png ├── Screenshot 2025-04-12 180808.png ├── Screenshot 2025-04-12 180839.png ├── Screenshot 2025-04-12 180900.png ├── Screenshot 2025-04-12 180916.png └── ShrutiCA2.ipynb /EDA Process: -------------------------------------------------------------------------------- 1 | import pandas as pd 2 | df = pd.read_csv("C:/Users/asus/Downloads/INT375.csv") 3 | df.columns = df.columns.str.replace("_x0020_", "_") 4 | df['Arrival_Date'] = pd.to_datetime(df['Arrival_Date'], dayfirst=True) 5 | print(df.info()) 6 | print(df.describe()) 7 | -------------------------------------------------------------------------------- /Objective 1: -------------------------------------------------------------------------------- 1 | import pandas as pd 2 | import matplotlib.pyplot as plt 3 | import seaborn as sns 4 | 5 | # Objective 1 6 | daily_counts = df.groupby('Arrival_Date').size() 7 | plt.figure(figsize=(12, 6)) 8 | plt.plot(daily_counts, marker='o', linestyle='-', color='b') 9 | plt.xlabel('Date') 10 | plt.ylabel('Total Records') 11 | plt.title('Total Daily Recorded Prices Over Time') 12 | plt.grid() 13 | plt.show() 14 | -------------------------------------------------------------------------------- /Objective 2: -------------------------------------------------------------------------------- 1 | # Objective 2 2 | commodity_counts = df['Commodity'].value_counts(normalize=True) * 100 3 | plt.figure(figsize=(12, 6)) 4 | commodity_counts[:10].plot(kind='bar', color='skyblue') 5 | plt.xlabel('Commodity') 6 | plt.ylabel('Percentage of Total Trade') 7 | plt.title('Proportion of Different Commodities Traded') 8 | plt.xticks(rotation=90) 9 | plt.show() 10 | -------------------------------------------------------------------------------- /Objective 3: -------------------------------------------------------------------------------- 1 | df = pd.read_csv("C:/Users/asus/Downloads/INT375.csv") 2 | # Objective 3 3 | key_commodities = ['Onion', 'Potato', 'Rice'] 4 | plt.figure(figsize=(12, 6)) 5 | for commodity in key_commodities: 6 | subset = df[df['Commodity'] == commodity].groupby('Arrival_Date')['Modal_x0020_Price'].mean() 7 | plt.plot(subset, marker='o', linestyle='-', label=commodity) 8 | plt.xlabel('Date') 9 | plt.ylabel('Average Modal Price') 10 | plt.title('Price Trends for Key Commodities') 11 | plt.legend() 12 | plt.grid() 13 | plt.show() 14 | -------------------------------------------------------------------------------- /Objective 4: -------------------------------------------------------------------------------- 1 | # Objective 4 2 | import matplotlib.pyplot as plt 3 | import seaborn as sns 4 | import pandas as pd 5 | 6 | state_prices = df.groupby('State')['Modal_x0020_Price'].mean().reset_index().sort_values(by='Modal_x0020_Price') 7 | 8 | # Plot 9 | plt.figure(figsize=(12, 6)) 10 | sns.barplot(data=state_prices, x='State', y='Modal_x0020_Price', hue='State', palette='coolwarm', dodge=False, legend=False) 11 | plt.xticks(rotation=90) 12 | plt.xlabel('State') 13 | plt.ylabel('Average Modal Price') 14 | plt.title('State-Wise Commodity Price Distribution') 15 | plt.tight_layout() 16 | plt.show() 17 | -------------------------------------------------------------------------------- /Objective 5: -------------------------------------------------------------------------------- 1 | # Objective 5 2 | market_volatility = df.groupby('Market')['Modal_x0020_Price'].std().sort_values(ascending=False) 3 | plt.figure(figsize=(12, 6)) 4 | market_volatility[:10].plot(kind='bar', color='orange') 5 | plt.xlabel('Market') 6 | plt.ylabel('Price Volatility (Std Dev)') 7 | plt.title('Top 10 Markets with Highest Price Variations') 8 | plt.xticks(rotation=90) 9 | plt.show() 10 | -------------------------------------------------------------------------------- /Screenshot 2025-04-12 180724.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/shrutii2631/Python-Project/14a36dcdb3702ffbeb502526a7460cc6de35ca69/Screenshot 2025-04-12 180724.png -------------------------------------------------------------------------------- /Screenshot 2025-04-12 180754.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/shrutii2631/Python-Project/14a36dcdb3702ffbeb502526a7460cc6de35ca69/Screenshot 2025-04-12 180754.png -------------------------------------------------------------------------------- /Screenshot 2025-04-12 180808.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/shrutii2631/Python-Project/14a36dcdb3702ffbeb502526a7460cc6de35ca69/Screenshot 2025-04-12 180808.png -------------------------------------------------------------------------------- /Screenshot 2025-04-12 180839.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/shrutii2631/Python-Project/14a36dcdb3702ffbeb502526a7460cc6de35ca69/Screenshot 2025-04-12 180839.png -------------------------------------------------------------------------------- /Screenshot 2025-04-12 180900.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/shrutii2631/Python-Project/14a36dcdb3702ffbeb502526a7460cc6de35ca69/Screenshot 2025-04-12 180900.png -------------------------------------------------------------------------------- /Screenshot 2025-04-12 180916.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/shrutii2631/Python-Project/14a36dcdb3702ffbeb502526a7460cc6de35ca69/Screenshot 2025-04-12 180916.png -------------------------------------------------------------------------------- /ShrutiCA2.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 3, 6 | "id": "c3ecf441-3614-44dc-a004-bb70ddf2be1d", 7 | "metadata": {}, 8 | "outputs": [ 9 | { 10 | "name": "stdout", 11 | "output_type": "stream", 12 | "text": [ 13 | "\n", 14 | "RangeIndex: 1944 entries, 0 to 1943\n", 15 | "Data columns (total 10 columns):\n", 16 | " # Column Non-Null Count Dtype \n", 17 | "--- ------ -------------- ----- \n", 18 | " 0 State 1944 non-null object \n", 19 | " 1 District 1944 non-null object \n", 20 | " 2 Market 1944 non-null object \n", 21 | " 3 Commodity 1944 non-null object \n", 22 | " 4 Variety 1944 non-null object \n", 23 | " 5 Grade 1944 non-null object \n", 24 | " 6 Arrival_Date 1944 non-null datetime64[ns]\n", 25 | " 7 Min_Price 1944 non-null int64 \n", 26 | " 8 Max_Price 1944 non-null int64 \n", 27 | " 9 Modal_Price 1944 non-null int64 \n", 28 | "dtypes: datetime64[ns](1), int64(3), object(6)\n", 29 | "memory usage: 152.0+ KB\n", 30 | "None\n", 31 | " Arrival_Date Min_Price Max_Price Modal_Price\n", 32 | "count 1944 1944.000000 1944.000000 1944.000000\n", 33 | "mean 2025-04-02 00:00:00 3856.166667 4497.363169 4199.249486\n", 34 | "min 2025-04-02 00:00:00 0.000000 0.000000 3.000000\n", 35 | "25% 2025-04-02 00:00:00 1100.000000 1500.000000 1400.000000\n", 36 | "50% 2025-04-02 00:00:00 2300.000000 2669.000000 2500.000000\n", 37 | "75% 2025-04-02 00:00:00 4000.000000 5000.000000 4500.000000\n", 38 | "max 2025-04-02 00:00:00 162500.000000 162580.000000 162540.000000\n", 39 | "std NaN 7695.687973 7855.489397 7755.975398\n" 40 | ] 41 | } 42 | ], 43 | "source": [ 44 | "import pandas as pd\n", 45 | "df = pd.read_csv(\"C:/Users/asus/Downloads/INT375.csv\")\n", 46 | "df.columns = df.columns.str.replace(\"_x0020_\", \"_\")\n", 47 | "df['Arrival_Date'] = pd.to_datetime(df['Arrival_Date'], dayfirst=True)\n", 48 | "print(df.info())\n", 49 | "print(df.describe())" 50 | ] 51 | }, 52 | { 53 | "cell_type": "code", 54 | "execution_count": 5, 55 | "id": "acb10462-7263-42e1-b78d-5e71f78c066c", 56 | "metadata": {}, 57 | "outputs": [ 58 | { 59 | "data": { 60 | "image/png": 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", 61 | "text/plain": [ 62 | "
" 63 | ] 64 | }, 65 | "metadata": {}, 66 | "output_type": "display_data" 67 | } 68 | ], 69 | "source": [ 70 | "import pandas as pd\n", 71 | "import matplotlib.pyplot as plt\n", 72 | "import seaborn as sns\n", 73 | "\n", 74 | "# Objective 1\n", 75 | "daily_counts = df.groupby('Arrival_Date').size()\n", 76 | "plt.figure(figsize=(12, 6))\n", 77 | "plt.plot(daily_counts, marker='o', linestyle='-', color='b')\n", 78 | "plt.xlabel('Date')\n", 79 | "plt.ylabel('Total Records')\n", 80 | "plt.title('Total Daily Recorded Prices Over Time')\n", 81 | "plt.grid()\n", 82 | "plt.show()" 83 | ] 84 | }, 85 | { 86 | "cell_type": "code", 87 | "execution_count": 7, 88 | "id": "1615566d-1dd8-4aec-bc4a-be94a435cc67", 89 | "metadata": {}, 90 | "outputs": [ 91 | { 92 | "data": { 93 | "image/png": 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", 94 | "text/plain": [ 95 | "
" 96 | ] 97 | }, 98 | "metadata": {}, 99 | "output_type": "display_data" 100 | } 101 | ], 102 | "source": [ 103 | "# Objective 2\n", 104 | "commodity_counts = df['Commodity'].value_counts(normalize=True) * 100\n", 105 | "plt.figure(figsize=(12, 6))\n", 106 | "commodity_counts[:10].plot(kind='bar', color='skyblue')\n", 107 | "plt.xlabel('Commodity')\n", 108 | "plt.ylabel('Percentage of Total Trade')\n", 109 | "plt.title('Proportion of Different Commodities Traded')\n", 110 | "plt.xticks(rotation=90)\n", 111 | "plt.show()" 112 | ] 113 | }, 114 | { 115 | "cell_type": "code", 116 | "execution_count": 11, 117 | "id": "7a970ced-7080-4517-b54c-f527c72c0129", 118 | "metadata": {}, 119 | "outputs": [ 120 | { 121 | "data": { 122 | "image/png": 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", 123 | "text/plain": [ 124 | "
" 125 | ] 126 | }, 127 | "metadata": {}, 128 | "output_type": "display_data" 129 | } 130 | ], 131 | "source": [ 132 | "df = pd.read_csv(\"C:/Users/asus/Downloads/INT375.csv\")\n", 133 | "# Objective 3\n", 134 | "key_commodities = ['Onion', 'Potato', 'Rice']\n", 135 | "plt.figure(figsize=(12, 6))\n", 136 | "for commodity in key_commodities:\n", 137 | " subset = df[df['Commodity'] == commodity].groupby('Arrival_Date')['Modal_x0020_Price'].mean()\n", 138 | " plt.plot(subset, marker='o', linestyle='-', label=commodity)\n", 139 | "plt.xlabel('Date')\n", 140 | "plt.ylabel('Average Modal Price')\n", 141 | "plt.title('Price Trends for Key Commodities')\n", 142 | "plt.legend()\n", 143 | "plt.grid()\n", 144 | "plt.show()" 145 | ] 146 | }, 147 | { 148 | "cell_type": "code", 149 | "execution_count": 13, 150 | "id": "08ee9335-8ab7-48db-a6bf-4d5c2f23fe4f", 151 | "metadata": {}, 152 | "outputs": [ 153 | { 154 | "data": { 155 | "image/png": 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", 156 | "text/plain": [ 157 | "
" 158 | ] 159 | }, 160 | "metadata": {}, 161 | "output_type": "display_data" 162 | } 163 | ], 164 | "source": [ 165 | "# Objective 4\n", 166 | "import matplotlib.pyplot as plt\n", 167 | "import seaborn as sns\n", 168 | "import pandas as pd\n", 169 | "\n", 170 | "state_prices = df.groupby('State')['Modal_x0020_Price'].mean().reset_index().sort_values(by='Modal_x0020_Price')\n", 171 | "\n", 172 | "# Plot\n", 173 | "plt.figure(figsize=(12, 6))\n", 174 | "sns.barplot(data=state_prices, x='State', y='Modal_x0020_Price', hue='State', palette='coolwarm', dodge=False, legend=False)\n", 175 | "plt.xticks(rotation=90)\n", 176 | "plt.xlabel('State')\n", 177 | "plt.ylabel('Average Modal Price')\n", 178 | "plt.title('State-Wise Commodity Price Distribution')\n", 179 | "plt.tight_layout()\n", 180 | "plt.show()" 181 | ] 182 | }, 183 | { 184 | "cell_type": "code", 185 | "execution_count": 15, 186 | "id": "3db0b16b-ebe8-47e4-a77d-503f216f31cd", 187 | "metadata": {}, 188 | "outputs": [ 189 | { 190 | "data": { 191 | "image/png": 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vn2Eft9ru7PugihYtmum+Ll26JEny8fHJ8r68vLzUsWNHzZgxQ9OnT1fjxo3tgvjtlixZog4dOqhEiRKaN2+etmzZou3bt6tHjx6ZLuZ3r1XTV69erXPnzqlXr14qXLiw3bZz587JMAz5+fkpf/78dretW7dmKchHRERoxowZOnHihF544QX5+vqqZs2adusbZKZAgQKqW7euLfyvXbtWTZo0Uf369ZWenq6NGzfa9vGw4b9o0aJ2929No7527VqWHl+2bFk99dRTGW5ZmR5/8eJFuy+pbsmsTZI8PT1VoECBDPXe/ns/d+6cEhIS5ObmluH3FhcXZ/u9lStXTmvWrJGvr6/69++vcuXKqVy5cvrvf/+bpdd9L6+++qq2b9+unTt36tixY4qNjVWfPn0y9MvKiv631ikoWbLkXfucO3dOkjR06NAMr7lfv36SdN/3q6enpzp16qSoqCjFxcXpxo0bmjdvnurVq2dbQf/kyZN65plndObMGf33v//Vxo0btX37dn3yySeSMr5nsnrFgm3btik8PFyS9Pnnn+vnn3/W9u3b9eabb2a636yIj4+XYRiZ1hAYGCgp49/C+/1bcOR7BgByAuf8A4AJFC1aVL/88osMw7D7AuD8+fO6ceOGihUrZtc/Li4uwz5utd35AfdBhYWFaeHChbpx44bdef+3Fp+7c9Xw++nRo4f+97//ad++fZo/f/5d+82bN0/BwcH64osv7I7FnYu+3XKvGQivv/66jh07pq5du+rGjRt26wUUK1ZMFotFGzduzPS84nuda3y7yMhIRUZGKjk5WT/99JNGjhypli1b6rfffrvrFxzSn7M3RowYoW3btun06dNq0qSJvL299fTTT2v16tU6e/asKlasqFKlSmWpjkdR0aJFtW3btgztmb1/s+rWYm1RUVGZbvf29rb9/Mwzz+iZZ55Renq6duzYoY8//liDBg2Sn5+fOnXq9MA1lCxZUk899dR9+2VldsytL1HuNWPn1r//4cOHq127dpn2CQkJue9z9ezZU59//rnmzJmjihUr6vz58/rggw9s27/55hslJydryZIldu/dPXv2ZLq/rM7+WbRokfLnz6/vvvvO7sudb775JkuPz0yRIkWUL18+xcbGZth2axG/O/9uZoWj3jMAkBMY+QcAE2jUqJGuXLmS4cPwnDlzbNtvt3btWttooCSlp6friy++ULly5e45gpgdbdu21ZUrV/T111/btc+ePVuBgYGqWbNmtvZXu3Zt9ejRQ23btlXbtm3v2s9iscjNzc0uWMTFxWW62v/95MuXT9OmTdOrr76q7t2769NPP7Vta9mypQzD0JkzZzId2b59kT13d/f7jk56eXmpefPmevPNN5Wamqr9+/ffs3/jxo1148YNvfXWWypZsqQqVapka1+zZo1tmvT9ZKU2Z6lXr54uX76s77//3q49q1emyEzLli118eJFpaenZ/p7yywEu7i4qGbNmrYR7F27dknK/iwIR6hTp46sVqumTp1610UUQ0JCVKFCBe3duzfT1/zUU0/ZfelxNzVr1lSVKlU0c+ZMzZw5U1ar1e7UhFv/5m7/4sswjLtevjCrLBaLXF1d7U4/uXbtmubOnZuhb1bfz15eXqpZs6aWLFli1//mzZuaN2+eSpYsqYoVKz5wzXd7zwCAMzHyDwAm0LVrV33yySfq1q2bjh8/rrCwMG3atEljxozRc889lyEEFitWTA0bNtRbb71lW+3/0KFDWQpVBw4csK1GHxcXp6tXr2rx4sWS/rxO+61rdDdv3lxNmjTRyy+/rKSkJJUvX14LFy5UVFSU5s2bZ/dBPqumT59+3z4tW7bUkiVL1K9fP7Vv316nTp3SO++8o4CAAB05ciTbzylJH3zwgby9vdWvXz9duXJFr7/+uurWras+ffooMjJSO3bs0LPPPisvLy/FxsZq06ZNCgsL08svvyzpz1kQS5Ys0aeffqrq1asrX758euqpp9S7d295eHiobt26CggIUFxcnMaOHSur1Wpbsf9uqlevriJFimjVqlV251w3btxY77zzju3n+7lbbY+Cbt26adKkSerSpYv+85//qHz58vr+++/1ww8/SMr6ZSdv16lTJ82fP1/PPfecXn31VdWoUUP58+fX6dOntX79ej3//PNq27atpk6dqnXr1qlFixYqXbq0rl+/bjvf/dZx9fb2VlBQkJYtW6ZGjRrJx8dHxYoVs11eLjcULFhQH3zwgXr16qXGjRurd+/e8vPz09GjR7V3715NnjxZkjRt2jQ1b95cTZs2Vffu3VWiRAldunRJBw8e1K5du/TVV19l6fl69OihwYMH6/Dhw+rbt688PDxs25o0aSI3Nze9+OKLGjZsmK5fv65PP/1U8fHxD/UaW7RooYkTJ6pz587q06ePLl68qAkTJmQ6uyYsLEyLFi3SF198obJly6pAgQJ3vdrF2LFj1aRJEzVo0EBDhw6Vm5ubpkyZoujoaC1cuDBb65JIytJ7BgCcypmrDQIAHsydq/0bhmFcvHjR+Mc//mEEBAQYrq6uRlBQkDF8+HDj+vXrdv0kGf379zemTJlilCtXzsifP79RqVIlY/78+Vl67lur8Gd2u3PV88uXLxsDBw40/P39DTc3N6Nq1ar3XSX+zue5cOHCPftlttr/uHHjjDJlyhju7u5G5cqVjc8//9y2v9vdOhZ3un21/9u9//77hiRjxIgRtrYZM2YYNWvWNLy8vAwPDw+jXLlyRteuXY0dO3bY+ly6dMlo3769UbhwYcNisdjqmD17ttGgQQPDz8/PcHNzMwIDA40OHToY+/bty9Ixatu2rSHJ7neXmppqeHl5Gfny5TPi4+Pt+me22v/darvbMbh13O63wv2t1f6/+uqrTLf379//vqv9G4ZhnDx50mjXrp1RsGBBw9vb23jhhReMlStXGpKMZcuW2fpl9m/CMIxMf+9paWnGhAkTjMcff9woUKCAUbBgQaNSpUpG3759jSNHjhiG8efVHNq2bWsEBQUZ7u7uRtGiRY169eoZ3377rd2+1qxZY1SrVs1wd3c3JN3zyhP3Oqa3u/V72r59+1233f47NAzDWLlypVGvXj3Dy8vL8PT0NEJDQ4333nvPrs/evXuNDh06GL6+vkb+/PkNf39/o2HDhsbUqVPvWc/tLly4YLi5uRmSjG3btmXYvnz5cttxLVGihPH6668b33//vSHJWL9+va1fvXr1jMceeyzT58jsfTBjxgwjJCTEcHd3N8qWLWuMHTvWmD59eoZjcfz4cSM8PNzw9vY2JNmuZJHZav+GYRgbN240GjZsaPv3W6tWLWP58uV2fe72+7j1Hr/1urL6ngEAZ7EYRhYutAsAMA2LxaL+/fvbRgSBv5oxY8bo3//+t06ePJljp6kAAGB2TPsHAACPrFtfUlWqVElpaWlat26dPvroI3Xp0oXgDwBANhD+AQDAI8vT01OTJk3S8ePHlZKSotKlS+uNN97Qv//9b2eXBgDAXwrT/gEAAAAAMDmnXurv008/VdWqVVWoUCEVKlRItWvXtrucj2EYGjVqlAIDA+Xh4aH69etnuPRRSkqKBgwYoGLFisnLy0utW7fOcK3b+Ph4RUREyGq1ymq1KiIiQgkJCXZ9Tp48qVatWsnLy0vFihXTwIEDlZqa6rDXDgAAAABAbnFq+C9ZsqTGjRunHTt2aMeOHWrYsKGef/55W8AfP368Jk6cqMmTJ2v79u3y9/dXkyZNdPnyZds+Bg0apKVLl2rRokXatGmTrly5opYtWyo9Pd3Wp3PnztqzZ4+ioqIUFRWlPXv2KCIiwrY9PT1dLVq0UHJysjZt2qRFixbp66+/1pAhQ3LvYAAAAAAA4CCP3LR/Hx8fvf/+++rRo4cCAwM1aNAgvfHGG5L+HOX38/PTe++9p759+yoxMVHFixfX3Llz1bFjR0nS2bNnVapUKa1cuVJNmzbVwYMHFRoaqq1bt6pmzZqSpK1bt6p27do6dOiQQkJC9P3336tly5Y6deqUAgMDJUmLFi1S9+7ddf78eRUqVMg5BwMAAAAAgBzwyCz4l56erq+++krJycmqXbu2YmJiFBcXp/DwcFsfd3d31atXT5s3b1bfvn21c+dOpaWl2fUJDAxUlSpVtHnzZjVt2lRbtmyR1Wq1BX9JqlWrlqxWqzZv3qyQkBBt2bJFVapUsQV/SWratKlSUlK0c+dONWjQINOaU1JSlJKSYrt/8+ZNXbp0SUWLFpXFYsnJwwMAAAAAQAaGYejy5csKDAxUvnx3n9zv9PD/66+/qnbt2rp+/boKFiyopUuXKjQ0VJs3b5Yk+fn52fX38/PTiRMnJElxcXFyc3NTkSJFMvSJi4uz9fH19c3wvL6+vnZ97nyeIkWKyM3NzdYnM2PHjtXo0aOz+YoBAAAAAMhZp06duudlcJ0e/kNCQrRnzx4lJCTo66+/Vrdu3bRhwwbb9jtH0A3DuO+o+p19Muv/IH3uNHz4cA0ePNh2PzExUaVLl9apU6c4VQAAAAAA4HBJSUkqVaqUvL2979nP6eHfzc1N5cuXlyQ99dRT2r59u/773//azvOPi4tTQECArf/58+dto/T+/v5KTU1VfHy83ej/+fPnVadOHVufc+fOZXjeCxcu2O3nl19+sdseHx+vtLS0DDMCbufu7i53d/cM7beuXgAAAAAAQG643yC5U1f7z4xhGEpJSVFwcLD8/f21evVq27bU1FRt2LDBFuyrV6+u/Pnz2/WJjY1VdHS0rU/t2rWVmJiobdu22fr88ssvSkxMtOsTHR2t2NhYW59Vq1bJ3d1d1atXd+jrBQAAAADA0Zw68v+vf/1LzZs3V6lSpXT58mUtWrRIP/74o6KiomSxWDRo0CCNGTNGFSpUUIUKFTRmzBh5enqqc+fOkiSr1aqePXtqyJAhKlq0qHx8fDR06FCFhYWpcePGkqTKlSurWbNm6t27t6ZNmyZJ6tOnj1q2bKmQkBBJUnh4uEJDQxUREaH3339fly5d0tChQ9W7d29G8AEAAAAAf3lODf/nzp1TRESEYmNjZbVaVbVqVUVFRalJkyaSpGHDhunatWvq16+f4uPjVbNmTa1atcruXIZJkybJ1dVVHTp00LVr19SoUSPNmjVLLi4utj7z58/XwIEDbVcFaN26tSZPnmzb7uLiohUrVqhfv36qW7euPDw81LlzZ02YMCGXjgQAAAAAAI5jMQzDcHYRZpGUlCSr1arExERmDAAAAAAAHC6rOfSRO+cfAAAAAADkLMI/AAAAAAAmR/gHAAAAAMDkCP8AAAAAAJgc4R8AAAAAAJMj/AMAAAAAYHKEfwAAAAAATI7wDwAAAACAyRH+AQAAAAAwOcI/AAAAAAAmR/gHAAAAAMDkCP8AAAAAAJgc4R8AAAAAAJMj/AMAAAAAYHKEfwAAAAAATM7V2QUgGxZYnF3Bg+lsOLsCAAAAAMjTGPkHAAAAAMDkCP8AAAAAAJgc4R8AAAAAAJMj/AMAAAAAYHKEfwAAAAAATI7wDwAAAACAyRH+AQAAAAAwOcI/AAAAAAAmR/gHAAAAAMDkCP8AAAAAAJgc4R8AAAAAAJMj/AMAAAAAYHKEfwAAAAAATM7V2QUAj7QFFmdX8GA6G86uAAAAAMAjhJF/AAAAAABMjvAPAAAAAIDJEf4BAAAAADA5wj8AAAAAACZH+AcAAAAAwOQI/wAAAAAAmBzhHwAAAAAAkyP8AwAAAABgcoR/AAAAAABMjvAPAAAAAIDJEf4BAAAAADA5wj8AAAAAACZH+AcAAAAAwOQI/wAAAAAAmBzhHwAAAAAAkyP8AwAAAABgcoR/AAAAAABMjvAPAAAAAIDJEf4BAAAAADA5wj8AAAAAACZH+AcAAAAAwOQI/wAAAAAAmBzhHwAAAAAAkyP8AwAAAABgcoR/AAAAAABMjvAPAAAAAIDJEf4BAAAAADA5wj8AAAAAACZH+AcAAAAAwOQI/wAAAAAAmBzhHwAAAAAAkyP8AwAAAABgcoR/AAAAAABMjvAPAAAAAIDJEf4BAAAAADA5wj8AAAAAACbn1PA/duxYPf300/L29pavr6/atGmjw4cP2/Xp3r27LBaL3a1WrVp2fVJSUjRgwAAVK1ZMXl5eat26tU6fPm3XJz4+XhEREbJarbJarYqIiFBCQoJdn5MnT6pVq1by8vJSsWLFNHDgQKWmpjrktQMAAAAAkFucGv43bNig/v37a+vWrVq9erVu3Lih8PBwJScn2/Vr1qyZYmNjbbeVK1fabR80aJCWLl2qRYsWadOmTbpy5Ypatmyp9PR0W5/OnTtrz549ioqKUlRUlPbs2aOIiAjb9vT0dLVo0ULJycnatGmTFi1apK+//lpDhgxx7EEAAAAAAMDBLIZhGM4u4pYLFy7I19dXGzZs0LPPPivpz5H/hIQEffPNN5k+JjExUcWLF9fcuXPVsWNHSdLZs2dVqlQprVy5Uk2bNtXBgwcVGhqqrVu3qmbNmpKkrVu3qnbt2jp06JBCQkL0/fffq2XLljp16pQCAwMlSYsWLVL37t11/vx5FSpU6L71JyUlyWq1KjExMUv9s22BJef3mRs6PzJvsezjmAMAAAB4hGU1hz5S5/wnJiZKknx8fOzaf/zxR/n6+qpixYrq3bu3zp8/b9u2c+dOpaWlKTw83NYWGBioKlWqaPPmzZKkLVu2yGq12oK/JNWqVUtWq9WuT5UqVWzBX5KaNm2qlJQU7dy5M9N6U1JSlJSUZHcDAAAAAOBR88iEf8MwNHjwYP3tb39TlSpVbO3NmzfX/PnztW7dOn3wwQfavn27GjZsqJSUFElSXFyc3NzcVKRIEbv9+fn5KS4uztbH19c3w3P6+vra9fHz87PbXqRIEbm5udn63Gns2LG2NQSsVqtKlSr14AcAAAAAAAAHcXV2Abe88sor2rdvnzZt2mTXfmsqvyRVqVJFTz31lIKCgrRixQq1a9furvszDEMWy/9N2b7954fpc7vhw4dr8ODBtvtJSUl8AQAAAAAAeOQ8EiP/AwYM0Lfffqv169erZMmS9+wbEBCgoKAgHTlyRJLk7++v1NRUxcfH2/U7f/68bSTf399f586dy7CvCxcu2PW5c4Q/Pj5eaWlpGWYE3OLu7q5ChQrZ3QAAAAAAeNQ4NfwbhqFXXnlFS5Ys0bp16xQcHHzfx1y8eFGnTp1SQECAJKl69erKnz+/Vq9ebesTGxur6Oho1alTR5JUu3ZtJSYmatu2bbY+v/zyixITE+36REdHKzY21tZn1apVcnd3V/Xq1XPk9QIAAAAA4AxOnfbfv39/LViwQMuWLZO3t7dt5N1qtcrDw0NXrlzRqFGj9MILLyggIEDHjx/Xv/71LxUrVkxt27a19e3Zs6eGDBmiokWLysfHR0OHDlVYWJgaN24sSapcubKaNWum3r17a9q0aZKkPn36qGXLlgoJCZEkhYeHKzQ0VBEREXr//fd16dIlDR06VL1792ZEHwAAAADwl+bUkf9PP/1UiYmJql+/vgICAmy3L774QpLk4uKiX3/9Vc8//7wqVqyobt26qWLFitqyZYu8vb1t+5k0aZLatGmjDh06qG7duvL09NTy5cvl4uJi6zN//nyFhYUpPDxc4eHhqlq1qubOnWvb7uLiohUrVqhAgQKqW7euOnTooDZt2mjChAm5d0AAAAAAAHAAi2EYXBA8h2T1+ooPjGvO5z6OOQAAAIBHWFZz6COx4B8AAAAAAHAcwj8AAAAAACZH+AcAAAAAwOQI/wAAAAAAmBzhHwAAAAAAkyP8AwAAAABgcoR/AAAAAABMjvAPAAAAAIDJEf4BAAAAADA5wj8AAAAAACZH+AcAAAAAwOQI/wAAAAAAmBzhHwAAAAAAkyP8AwAAAABgcoR/AAAAAABMjvAPAAAAAIDJEf4BAAAAADA5wj8AAAAAACZH+AcAAAAAwOQI/wAAAAAAmBzhHwAAAAAAkyP8AwAAAABgcoR/AAAAAABMjvAPAAAAAIDJEf4BAAAAADA5wj8AAAAAACZH+AcAAAAAwOQI/wAAAAAAmBzhHwAAAAAAkyP8AwAAAABgcoR/AAAAAABMjvAPAAAAAIDJEf4BAAAAADA5wj8AAAAAACZH+AcAAAAAwOQI/wAAAAAAmJyrswsAADsLLM6u4MF0NpxdAQAAAHBXjPwDAAAAAGByhH8AAAAAAEyO8A8AAAAAgMkR/gEAAAAAMDnCPwAAAAAAJkf4BwAAAADA5Aj/AAAAAACYHOEfAAAAAACTI/wDAAAAAGByhH8AAAAAAEyO8A8AAAAAgMkR/gEAAAAAMDnCPwAAAAAAJkf4BwAAAADA5Aj/AAAAAACYHOEfAAAAAACTI/wDAAAAAGByhH8AAAAAAEyO8A8AAAAAgMkR/gEAAAAAMDnCPwAAAAAAJkf4BwAAAADA5Aj/AAAAAACYHOEfAAAAAACTI/wDAAAAAGByhH8AAAAAAEyO8A8AAAAAgMkR/gEAAAAAMDnX7HQ2DEMbNmzQxo0bdfz4cV29elXFixdXtWrV1LhxY5UqVcpRdQIAAAAAgAeUpZH/a9euacyYMSpVqpSaN2+uFStWKCEhQS4uLjp69KhGjhyp4OBgPffcc9q6dWuWn3zs2LF6+umn5e3tLV9fX7Vp00aHDx+262MYhkaNGqXAwEB5eHiofv362r9/v12flJQUDRgwQMWKFZOXl5dat26t06dP2/WJj49XRESErFarrFarIiIilJCQYNfn5MmTatWqlby8vFSsWDENHDhQqampWX49AAAAAAA8irIU/itWrKhdu3Zp6tSpSkpK0tatW/X1119r3rx5WrlypU6ePKljx47pmWeeUceOHfX5559n6ck3bNig/v37a+vWrVq9erVu3Lih8PBwJScn2/qMHz9eEydO1OTJk7V9+3b5+/urSZMmunz5sq3PoEGDtHTpUi1atEibNm3SlStX1LJlS6Wnp9v6dO7cWXv27FFUVJSioqK0Z88eRURE2Lanp6erRYsWSk5O1qZNm7Ro0SJ9/fXXGjJkSJZeCwAAAAAAjyqLYRjG/TpFR0erSpUqWdphamqqTpw4oQoVKmS7mAsXLsjX11cbNmzQs88+K8MwFBgYqEGDBumNN96Q9Ocov5+fn9577z317dtXiYmJKl68uObOnauOHTtKks6ePatSpUpp5cqVatq0qQ4ePKjQ0FBt3bpVNWvWlCRt3bpVtWvX1qFDhxQSEqLvv/9eLVu21KlTpxQYGChJWrRokbp3767z58+rUKFC960/KSlJVqtViYmJWeqfbQssOb/P3ND5vm+xRxfHPPdxzAEAAIAsy2oOzdLIf1aDvyS5ubk9UPCXpMTEREmSj4+PJCkmJkZxcXEKDw+39XF3d1e9evW0efNmSdLOnTuVlpZm1ycwMFBVqlSx9dmyZYusVqst+EtSrVq1ZLVa7fpUqVLFFvwlqWnTpkpJSdHOnTszrTclJUVJSUl2NwAAAAAAHjXZXu0/ODhYb731lg4dOpSjhRiGocGDB+tvf/ub7cuGuLg4SZKfn59dXz8/P9u2uLg4ubm5qUiRIvfs4+vrm+E5fX197frc+TxFihSRm5ubrc+dxo4da1tDwGq1suAhAAAAAOCRlO3wP2DAAEVFRSk0NFTVq1fXhx9+qNjY2Icu5JVXXtG+ffu0cOHCDNssFvtpwIZhZGi70519Muv/IH1uN3z4cCUmJtpup06dumdNAAAAAAA4Q7bD/+DBg7V9+3YdOnRILVu21KeffqrSpUsrPDxcc+bMeaAiBgwYoG+//Vbr169XyZIlbe3+/v6SlGHk/fz587ZRen9/f6Wmpio+Pv6efc6dO5fheS9cuGDX587niY+PV1paWoYZAbe4u7urUKFCdjcAAAAAAB412Q7/t1SsWFGjR4/W4cOHtXHjRl24cEGRkZHZ2odhGHrllVe0ZMkSrVu3TsHBwXbbg4OD5e/vr9WrV9vaUlNTtWHDBtWpU0eSVL16deXPn9+uT2xsrKKjo219ateurcTERG3bts3W55dfflFiYqJdn+joaLtZDKtWrZK7u7uqV6+erdcFAAAAAMCjxPVhHrxt2zYtWLBAX3zxhRITE9W+fftsPb5///5asGCBli1bJm9vb9vIu9VqlYeHhywWiwYNGqQxY8aoQoUKqlChgsaMGSNPT0917tzZ1rdnz54aMmSIihYtKh8fHw0dOlRhYWFq3LixJKly5cpq1qyZevfurWnTpkmS+vTpo5YtWyokJESSFB4ertDQUEVEROj999/XpUuXNHToUPXu3ZsRfQAAAADAX1q2w/9vv/2m+fPna8GCBTp+/LgaNGigcePGqV27dvL29s7Wvj799FNJUv369e3aZ86cqe7du0uShg0bpmvXrqlfv36Kj49XzZo1tWrVKrvnmjRpklxdXdWhQwddu3ZNjRo10qxZs+Ti4mLrM3/+fA0cONB2VYDWrVtr8uTJtu0uLi5asWKF+vXrp7p168rDw0OdO3fWhAkTsvWaAOAvh8srAgAAmJ7FMIxsfXrKly+fnnrqKXXu3FmdOnWynZePrF9f8YHxAT33ccxzH8c893HMAQAA/rKymkOzPfJ/6NAhVaxY8aGKAwAAAAAAuSfbC/5VrFhRCQkJ+t///qfhw4fr0qVLkqRdu3bpzJkzOV4gAAAAAAB4ONke+d+3b58aNWqkwoUL6/jx4+rdu7d8fHy0dOlSnThx4oEv9wcAAAAAABwj2yP/r732miIjI3XkyBEVKFDA1t68eXP99NNPOVocAAAAAAB4eNke+d+xY4c+++yzDO0lSpSwXaoPAAAAAAA8OrI98l+gQAElJSVlaD98+LCKFy+eI0UBAAAAAICck+3w//zzz+vtt99WWlqaJMlisejkyZP65z//qRdeeCHHCwQAAAAAAA8n2+F/woQJunDhgnx9fXXt2jXVq1dP5cuXl7e3t959911H1AgAAAAAAB5Cts/5L1SokDZt2qR169Zp165dunnzpp588kk1btzYEfUBAAAAAICHlO3wf0vDhg3VsGHDnKwFAAAAAAA4QLbC/82bNzVr1iwtWbJEx48fl8ViUXBwsNq3b6+IiAhZLBZH1QkAAAAAAB5Qls/5NwxDrVu3Vq9evXTmzBmFhYXpscce04kTJ9S9e3e1bdvWkXUCAAAAAIAHlOWR/1mzZumnn37S2rVr1aBBA7tt69atU5s2bTRnzhx17do1x4sEAAAAAAAPLssj/wsXLtS//vWvDMFf+vP8/3/+85+aP39+jhYHAAAAAAAeXpZH/vft26fx48ffdXvz5s310Ucf5UhRAACY2oK/6Bo5nQ1nVwAAAB5Qlkf+L126JD8/v7tu9/PzU3x8fI4UBQAAAAAAck6WR/7T09Pl6nr37i4uLrpx40aOFAUAAJCjmG0BAMjjshz+DcNQ9+7d5e7unun2lJSUHCsKAAAAAADknCyH/27dut23Dyv9AwAAAADw6Mly+J85c6Yj6wAAAAAAAA6S5QX/AAAAAADAXxPhHwAAAAAAkyP8AwAAAABgcoR/AAAAAABMjvAPAAAAAIDJZWm1/2+//TbLO2zduvUDFwMAAAAAAHJelsJ/mzZt7O5bLBYZhmF3/5b09PScqQwAAAAAAOSILE37v3nzpu22atUqPfHEE/r++++VkJCgxMRErVy5Uk8++aSioqIcXS8AAAAAAMimLI38327QoEGaOnWq/va3v9namjZtKk9PT/Xp00cHDx7M0QIBAAAAAMDDyfaCf8eOHZPVas3QbrVadfz48ZyoCQAAAAAA5KBsh/+nn35agwYNUmxsrK0tLi5OQ4YMUY0aNXK0OAAAAAAA8PCyHf5nzJih8+fPKygoSOXLl1f58uVVunRpxcbGavr06Y6oEQAAAAAAPIRsn/Nfvnx57du3T6tXr9ahQ4dkGIZCQ0PVuHFju1X/AQAAAADAoyHb4X/OnDnq2LGjwsPDFR4ebmtPTU3VokWL1LVr1xwtEAAAAAAAPJxsT/uPjIxUYmJihvbLly8rMjIyR4oCAAAAAAA5J9vh3zCMTKf3nz59OtOrAAAAAAAAAOfK8rT/atWqyWKxyGKxqFGjRnJ1/b+HpqenKyYmRs2aNXNIkQAAAAAA4MFlOfy3adNGkrRnzx41bdpUBQsWtG1zc3NTmTJl9MILL+R4gQAAAAAA4OFkOfyPHDlSklSmTBl17NhRBQoUcFhRAAAAAAAg52R7tf9u3brZfr5+/bq++OILJScnq0mTJqpQoUKOFgcAAAAAAB5elsP/66+/rtTUVP33v/+V9Oel/WrVqqUDBw7I09NTw4YN0+rVq1W7dm2HFQsAAAAAALIvy6v9f//992rUqJHt/vz583Xy5EkdOXJE8fHx+vvf/67//Oc/DikSAAAAAAA8uCyH/5MnTyo0NNR2f9WqVWrfvr2CgoJksVj06quvavfu3Q4pEgAAAAAAPLgsh/98+fLJMAzb/a1bt6pWrVq2+4ULF1Z8fHzOVgcAAAAAAB5alsN/pUqVtHz5cknS/v37dfLkSTVo0MC2/cSJE/Lz88v5CgEAAAAAwEPJ1oJ/L774olasWKH9+/frueeeU3BwsG37ypUrVaNGDYcUCQAAAAAAHlyWR/5feOEFrVy5UlWrVtVrr72mL774wm67p6en+vXrl+MFAgAAAACAh5PlkX9Jaty4sRo3bpzptpEjR+ZIQQAAAAAAIGdlaeT/5MmT2drpmTNnHqgYAAAAAACQ87IU/p9++mn17t1b27Ztu2ufxMREff7556pSpYqWLFmSYwUCAAAAAICHk6Vp/wcPHtSYMWPUrFkz5c+fX0899ZQCAwNVoEABxcfH68CBA9q/f7+eeuopvf/++2revLmj6wYAAAAAAFmUpZF/Hx8fTZgwQWfPntWnn36qihUr6o8//tCRI0ckSS+99JJ27typn3/+meAPAAAAAMAjJlsL/hUoUEDt2rVTu3btHFUPAAAAAADIYVm+1B8AAAAAAPhrIvwDAAAAAGByhH8AAAAAAEyO8A8AAAAAgMllO/wnJyc7og4AAAAAAOAg2Q7/fn5+6tGjhzZt2uSIegAAAAAAQA7LdvhfuHChEhMT1ahRI1WsWFHjxo3T2bNnHVEbAAAAAADIAdkO/61atdLXX3+ts2fP6uWXX9bChQsVFBSkli1basmSJbpx44Yj6gQAAAAAAA/ogRf8K1q0qF577TXt3btXEydO1Jo1a9S+fXsFBgZqxIgRunr1ak7WCQAAAAAAHpDrgz4wLi5Oc+bM0cyZM3Xy5Em1b99ePXv21NmzZzVu3Dht3bpVq1atyslaAQAAAADAA8h2+F+yZIlmzpypH374QaGhoerfv7+6dOmiwoUL2/o88cQTqlatWk7WCQAAAAAAHlC2w39kZKQ6deqkn3/+WU8//XSmfcqWLas333zzoYsDAAAAAAAPL9vhPzY2Vp6envfs4+HhoZEjRz5wUQAAAAAAIOdke8E/b29vnT9/PkP7xYsX5eLikq19/fTTT2rVqpUCAwNlsVj0zTff2G3v3r27LBaL3a1WrVp2fVJSUjRgwAAVK1ZMXl5eat26tU6fPm3XJz4+XhEREbJarbJarYqIiFBCQoJdn5MnT6pVq1by8vJSsWLFNHDgQKWmpmbr9QAAAAAA8CjKdvg3DCPT9pSUFLm5uWVrX8nJyXr88cc1efLku/Zp1qyZYmNjbbeVK1fabR80aJCWLl2qRYsWadOmTbpy5Ypatmyp9PR0W5/OnTtrz549ioqKUlRUlPbs2aOIiAjb9vT0dLVo0ULJycnatGmTFi1apK+//lpDhgzJ1usBAAAAAOBRlOVp/x999JEkyWKx6H//+58KFixo25aenq6ffvpJlSpVytaTN2/eXM2bN79nH3d3d/n7+2e6LTExUdOnT9fcuXPVuHFjSdK8efNUqlQprVmzRk2bNtXBgwcVFRWlrVu3qmbNmpKkzz//XLVr19bhw4cVEhKiVatW6cCBAzp16pQCAwMlSR988IG6d++ud999V4UKFcrW6wIAAAAA4FGS5fA/adIkSX+O/E+dOtVuir+bm5vKlCmjqVOn5niBP/74o3x9fVW4cGHVq1dP7777rnx9fSVJO3fuVFpamsLDw239AwMDVaVKFW3evFlNmzbVli1bZLVabcFfkmrVqiWr1arNmzcrJCREW7ZsUZUqVWzBX5KaNm2qlJQU7dy5Uw0aNMi0tpSUFKWkpNjuJyUl5fTLBwAAAADgoWU5/MfExEiSGjRooCVLlqhIkSIOK+qW5s2b6+9//7uCgoIUExOjt956Sw0bNtTOnTvl7u6uuLg4ubm5ZajFz89PcXFxkqS4uDjblwW38/X1tevj5+dnt71IkSJyc3Oz9cnM2LFjNXr06Id9mQAAAAAAOFS2V/tfv369I+rIVMeOHW0/V6lSRU899ZSCgoK0YsUKtWvX7q6PMwxDFovFdv/2nx+mz52GDx+uwYMH2+4nJSWpVKlSd39BAAAAAAA4QZbC/+DBg/XOO+/Iy8vLLuxmZuLEiTlSWGYCAgIUFBSkI0eOSJL8/f2Vmpqq+Ph4u9H/8+fPq06dOrY+586dy7CvCxcu2Eb7/f399csvv9htj4+PV1paWoYZAbdzd3eXu7v7Q78uAAAAAAAcKUvhf/fu3UpLS7P9fDf3GiXPCRcvXtSpU6cUEBAgSapevbry58+v1atXq0OHDpKk2NhYRUdHa/z48ZKk2rVrKzExUdu2bVONGjUkSb/88osSExNtXxDUrl1b7777rmJjY237XrVqldzd3VW9enWHviYAAAAAABwtS+H/9qn+OTnt/8qVKzp69KjtfkxMjPbs2SMfHx/5+Pho1KhReuGFFxQQEKDjx4/rX//6l4oVK6a2bdtKkqxWq3r27KkhQ4aoaNGi8vHx0dChQxUWFmZb/b9y5cpq1qyZevfurWnTpkmS+vTpo5YtWyokJESSFB4ertDQUEVEROj999/XpUuXNHToUPXu3ZuV/gEAAAAAf3nZPuc/J+3YscNuJf1bpxR069ZNn376qX799VfNmTNHCQkJCggIUIMGDfTFF1/I29vb9phJkybJ1dVVHTp00LVr19SoUSPNmjXL7moE8+fP18CBA21XBWjdurUmT55s2+7i4qIVK1aoX79+qlu3rjw8PNS5c2dNmDDB0YcAAAAAAACHsxiGYdyv070W17vTkiVLHqqgv7KkpCRZrVYlJiY6ZsbAAseeVuEwne/7Fnt0ccxzH8c893HMcx/HPPdxzAEAJpXVHJqlkX+r1ZpjhQEAAAAAgNyVpfA/c+ZMR9cBAAAAAAAcJJ+zCwAAAAAAAI6VpZH/J598UmvXrlWRIkVUrVq1e17Sb9euXTlWHAAAAAAAeHhZCv/PP/+83N3dbT/fK/wDAAAAAIBHS5bC/8iRI20/jxo1ylG1AAAAAAAAB8j2Of9ly5bVxYsXM7QnJCSobNmyOVIUAAAAAADIOdkO/8ePH1d6enqG9pSUFJ0+fTpHigIAAAAAADknS9P+Jenbb7+1/fzDDz/IarXa7qenp2vt2rUKDg7O2eoAAAAAAMBDy3L4b9OmjSTJYrGoW7dudtvy58+vMmXK6IMPPsjR4gAAAAAAwMPLcvi/efOmJCk4OFjbt29XsWLFHFYUAAAAAADIOVkO/7fExMQ4og4AAAAAAOAg2Q7/kpScnKwNGzbo5MmTSk1Ntds2cODAHCkMAAAAAADkjGyH/927d+u5557T1atXlZycLB8fH/3xxx/y9PSUr68v4R8AAAAAgEdMti/199prr6lVq1a6dOmSPDw8tHXrVp04cULVq1fXhAkTHFEjAAAAAAB4CNkO/3v27NGQIUPk4uIiFxcXpaSkqFSpUho/frz+9a9/OaJGAAAAAADwELId/vPnzy+LxSJJ8vPz08mTJyVJVqvV9jMAAAAAAHh0ZPuc/2rVqmnHjh2qWLGiGjRooBEjRuiPP/7Q3LlzFRYW5ogaAQAAAADAQ8j2yP+YMWMUEBAgSXrnnXdUtGhRvfzyyzp//rw+++yzHC8QAAAAAAA8nGyP/D/11FO2n4sXL66VK1fmaEEAAAAAACBnZXvkHwAAAAAA/LVkaeS/WrVqtkX+7mfXrl0PVRAAAAAAAMhZWQr/bdq0cXAZAAAAAADAUbIU/keOHOnoOgAAAAAAgINke8G/W3bu3KmDBw/KYrEoNDRU1apVy8m6AAAAAABADsl2+D9//rw6deqkH3/8UYULF5ZhGEpMTFSDBg20aNEiFS9e3BF1AgAAAACAB5Tt1f4HDBigpKQk7d+/X5cuXVJ8fLyio6OVlJSkgQMHOqJGAAAAAADwELI98h8VFaU1a9aocuXKtrbQ0FB98sknCg8Pz9HiAAAAAADAw8v2yP/NmzeVP3/+DO358+fXzZs3c6QoAAAAAACQc7Id/hs2bKhXX31VZ8+etbWdOXNGr732mho1apSjxQEAAAAAgIeX7fA/efJkXb58WWXKlFG5cuVUvnx5BQcH6/Lly/r4448dUSMAAAAAAHgIWT7nf9CgQerVq5eqVKmiXbt2afXq1Tp06JAMw1BoaKgaN27syDoBAAAAAMADynL4j4qK0scff6zq1aurV69e6tSpk5o0aeLI2gAAAAAAQA7I8rT/Q4cO6aefflJYWJiGDh2qwMBAdevWTT/99JMj6wMAAAAAAA8pW+f8161bV9OnT1dcXJw+/vhjxcTEqH79+qpQoYLGjRtntwggAAAAAAB4NGR7wT9J8vT0VGRkpH766ScdOXJEHTp00Pjx41WmTJkcLg8AAAAAADysBwr/tyQnJ2vDhg3asGGDEhISVK5cuZyqCwAAAAAA5JAHCv8//fSTIiMj5e/vr1dffVUVK1bUxo0bdfDgwZyuDwAAAAAAPKQsr/Z/+vRpzZ49W7NmzdKxY8dUs2ZNTZo0SZ06dVLBggUdWSMAAAAAAHgIWQ7/ZcqUUdGiRRUREaGePXuqcuXKjqwLAAAAAADkkCyH/y+//FKtW7eWq2uWHwIAAAAAAB4BWU7y7dq1c2QdAAAAAADAQR5qtX8AAAAAAPDoI/wDAAAAAGByhH8AAAAAAEzugcP/0aNH9cMPP+jatWuSJMMwcqwoAAAAAACQc7Id/i9evKjGjRurYsWKeu655xQbGytJ6tWrl4YMGZLjBQIAAAAAgIeT7fD/2muvydXVVSdPnpSnp6etvWPHjoqKisrR4gAAAAAAwMPL8qX+blm1apV++OEHlSxZ0q69QoUKOnHiRI4VBgAAAAAAcka2R/6Tk5PtRvxv+eOPP+Tu7p4jRQEAAAAAgJyT7fD/7LPPas6cObb7FotFN2/e1Pvvv68GDRrkaHEAAAAAAODhZXva//vvv6/69etrx44dSk1N1bBhw7R//35dunRJP//8syNqBAAAAAAADyHbI/+hoaHat2+fatSooSZNmig5OVnt2rXT7t27Va5cOUfUCAAAAAAAHkK2R/4lyd/fX6NHj87pWgAAAGAWCyzOruDBdDacXQEAOES2R/5nzpypr776KkP7V199pdmzZ+dIUQAAAAAAIOdkO/yPGzdOxYoVy9Du6+urMWPG5EhRAAAAAAAg52Q7/J84cULBwcEZ2oOCgnTy5MkcKQoAAAAAAOScbId/X19f7du3L0P73r17VbRo0RwpCgAAAAAA5Jxsh/9OnTpp4MCBWr9+vdLT05Wenq5169bp1VdfVadOnRxRIwAAAAAAeAjZXu3/P//5j06cOKFGjRrJ1fXPh9+8eVNdu3blnH8AAAAAAB5B2Q7/bm5u+uKLL/TOO+9o79698vDwUFhYmIKCghxRHwAAAAAAeEjZDv+3VKxYURUrVszJWgAAAAAAgANkKfwPHjxY77zzjry8vDR48OB79p04cWKOFAYAAAAAAHJGlsL/7t27lZaWJknatWuXLBZLpv3u1g4AAAAAAJwnS+F//fr1tp9//PFHR9UCAAAAAAAcIFuX+rtx44ZcXV0VHR3tqHoAAAAAAEAOy1b4d3V1VVBQkNLT03PkyX/66Se1atVKgYGBslgs+uabb+y2G4ahUaNGKTAwUB4eHqpfv772799v1yclJUUDBgxQsWLF5OXlpdatW+v06dN2feLj4xURESGr1Sqr1aqIiAglJCTY9Tl58qRatWolLy8vFStWTAMHDlRqamqOvE4AAAAAAJwpW+Ffkv79739r+PDhunTp0kM/eXJysh5//HFNnjw50+3jx4/XxIkTNXnyZG3fvl3+/v5q0qSJLl++bOszaNAgLV26VIsWLdKmTZt05coVtWzZ0u4Lis6dO2vPnj2KiopSVFSU9uzZo4iICNv29PR0tWjRQsnJydq0aZMWLVqkr7/+WkOGDHno1wgAAAAAgLNl+1J/H330kY4eParAwEAFBQXJy8vLbvuuXbuyvK/mzZurefPmmW4zDEMffvih3nzzTbVr106SNHv2bPn5+WnBggXq27evEhMTNX36dM2dO1eNGzeWJM2bN0+lSpXSmjVr1LRpUx08eFBRUVHaunWratasKUn6/PPPVbt2bR0+fFghISFatWqVDhw4oFOnTikwMFCS9MEHH6h79+569913VahQoeweJgAAAAAAHhnZDv/PP/98rqzqHxMTo7i4OIWHh9va3N3dVa9ePW3evFl9+/bVzp07lZaWZtcnMDBQVapU0ebNm9W0aVNt2bJFVqvVFvwlqVatWrJardq8ebNCQkK0ZcsWValSxRb8Jalp06ZKSUnRzp071aBBg0xrTElJUUpKiu1+UlJSTh4CAAAAAAByRLbD/6hRoxxQRkZxcXGSJD8/P7t2Pz8/nThxwtbHzc1NRYoUydDn1uPj4uLk6+ubYf++vr52fe58niJFisjNzc3WJzNjx47V6NGjs/nKAAAAAADIXVk+5//q1avq37+/SpQoIV9fX3Xu3Fl//PGHI2uTpAyzDAzDuO/Mgzv7ZNb/Qfrcafjw4UpMTLTdTp06dc+6AAAAAABwhiyH/5EjR2rWrFlq0aKFOnXqpNWrV+vll192WGH+/v6SlGHk/fz587ZRen9/f6Wmpio+Pv6efc6dO5dh/xcuXLDrc+fzxMfHKy0tLcOMgNu5u7urUKFCdjcAAAAAAB41WQ7/S5Ys0fTp0/XZZ5/po48+0ooVK/TNN9/k2GX/7hQcHCx/f3+tXr3a1paamqoNGzaoTp06kqTq1asrf/78dn1iY2MVHR1t61O7dm0lJiZq27Zttj6//PKLEhMT7fpER0crNjbW1mfVqlVyd3dX9erVHfL6AAAAAADILVk+5//UqVN65plnbPdr1KghV1dXnT17VqVKlXqgJ79y5YqOHj1qux8TE6M9e/bIx8dHpUuX1qBBgzRmzBhVqFBBFSpU0JgxY+Tp6anOnTtLkqxWq3r27KkhQ4aoaNGi8vHx0dChQxUWFmZb/b9y5cpq1qyZevfurWnTpkmS+vTpo5YtWyokJESSFB4ertDQUEVEROj999/XpUuXNHToUPXu3ZvRfAAAAADAX16Ww396errc3NzsH+zqqhs3bjzwk+/YscNuJf3BgwdLkrp166ZZs2Zp2LBhunbtmvr166f4+HjVrFlTq1atkre3t+0xkyZNkqurqzp06KBr166pUaNGmjVrllxcXGx95s+fr4EDB9quCtC6dWtNnjzZtt3FxUUrVqxQv379VLduXXl4eKhz586aMGHCA782AAAAAAAeFRbDMIysdMyXL5+aN28ud3d3W9vy5cvVsGFDeXl52dqWLFmS81X+RSQlJclqtSoxMdExMwYWOP4Siw7ROUtvsUcTxzz3ccxzH8c893HMcx/HPPdxzAEgV2Q1h2Z55L9bt24Z2rp06fJg1QEAAAAAgFyT5fA/c+ZMR9YBAAAAAAAcJMur/QMAAAAAgL8mwj8AAAAAACaX5Wn/AAAAAB5hLLII4B4Y+QcAAAAAwOQI/wAAAAAAmBzhHwAAAAAAkyP8AwAAAABgcoR/AAAAAABMjvAPAAAAAIDJEf4BAAAAADA5wj8AAAAAACZH+AcAAAAAwOQI/wAAAAAAmBzhHwAAAAAAkyP8AwAAAABgcoR/AAAAAABMjvAPAAAAAIDJEf4BAAAAADA5wj8AAAAAACZH+AcAAAAAwOQI/wAAAAAAmBzhHwAAAAAAk3N1dgEAAAAA8Je0wOLsCh5MZ8PZFcAJCP8AAAAAgL8GvnB5YEz7BwAAAADA5Aj/AAAAAACYHOEfAAAAAACTI/wDAAAAAGByhH8AAAAAAEyO8A8AAAAAgMkR/gEAAAAAMDnCPwAAAAAAJkf4BwAAAADA5Aj/AAAAAACYHOEfAAAAAACTI/wDAAAAAGByhH8AAAAAAEyO8A8AAAAAgMkR/gEAAAAAMDnCPwAAAAAAJkf4BwAAAADA5Aj/AAAAAACYHOEfAAAAAACTI/wDAAAAAGByhH8AAAAAAEyO8A8AAAAAgMkR/gEAAAAAMDnCPwAAAAAAJkf4BwAAAADA5Aj/AAAAAACYHOEfAAAAAACTI/wDAAAAAGByhH8AAAAAAEyO8A8AAAAAgMkR/gEAAAAAMDnCPwAAAAAAJkf4BwAAAADA5Aj/AAAAAACYHOEfAAAAAACTI/wDAAAAAGByhH8AAAAAAEyO8A8AAAAAgMkR/gEAAAAAMDnCPwAAAAAAJvdIh/9Ro0bJYrHY3fz9/W3bDcPQqFGjFBgYKA8PD9WvX1/79++320dKSooGDBigYsWKycvLS61bt9bp06ft+sTHxysiIkJWq1VWq1URERFKSEjIjZcIAAAAAIDDPdLhX5Iee+wxxcbG2m6//vqrbdv48eM1ceJETZ48Wdu3b5e/v7+aNGmiy5cv2/oMGjRIS5cu1aJFi7Rp0yZduXJFLVu2VHp6uq1P586dtWfPHkVFRSkqKkp79uxRRERErr5OAAAAAAAcxdXZBdyPq6ur3Wj/LYZh6MMPP9Sbb76pdu3aSZJmz54tPz8/LViwQH379lViYqKmT5+uuXPnqnHjxpKkefPmqVSpUlqzZo2aNm2qgwcPKioqSlu3blXNmjUlSZ9//rlq166tw4cPKyQkJPdeLAAAAAAADvDIj/wfOXJEgYGBCg4OVqdOnfT7779LkmJiYhQXF6fw8HBbX3d3d9WrV0+bN2+WJO3cuVNpaWl2fQIDA1WlShVbny1btshqtdqCvyTVqlVLVqvV1uduUlJSlJSUZHcDAAAAAOBR80iH/5o1a2rOnDn64Ycf9PnnnysuLk516tTRxYsXFRcXJ0ny8/Oze4yfn59tW1xcnNzc3FSkSJF79vH19c3w3L6+vrY+dzN27FjbOgFWq1WlSpV64NcKAAAAAICjPNLhv3nz5nrhhRcUFhamxo0ba8WKFZL+nN5/i8VisXuMYRgZ2u50Z5/M+mdlP8OHD1diYqLtdurUqfu+JgAAAAAActsjHf7v5OXlpbCwMB05csS2DsCdo/Pnz5+3zQbw9/dXamqq4uPj79nn3LlzGZ7rwoULGWYV3Mnd3V2FChWyuwEAAAAA8Kj5S4X/lJQUHTx4UAEBAQoODpa/v79Wr15t256amqoNGzaoTp06kqTq1asrf/78dn1iY2MVHR1t61O7dm0lJiZq27Zttj6//PKLEhMTbX0AAAAAAPgre6RX+x86dKhatWql0qVL6/z58/rPf/6jpKQkdevWTRaLRYMGDdKYMWNUoUIFVahQQWPGjJGnp6c6d+4sSbJarerZs6eGDBmiokWLysfHR0OHDrWdRiBJlStXVrNmzdS7d29NmzZNktSnTx+1bNmSlf4BAAAAAKbwSIf/06dP68UXX9Qff/yh4sWLq1atWtq6dauCgoIkScOGDdO1a9fUr18/xcfHq2bNmlq1apW8vb1t+5g0aZJcXV3VoUMHXbt2TY0aNdKsWbPk4uJi6zN//nwNHDjQdlWA1q1ba/Lkybn7YgEAAAAAcJBHOvwvWrTontstFotGjRqlUaNG3bVPgQIF9PHHH+vjjz++ax8fHx/NmzfvQcsEAAAAAOCR9pc65x8AAAAAAGQf4R8AAAAAAJMj/AMAAAAAYHKEfwAAAAAATI7wDwAAAACAyRH+AQAAAAAwOcI/AAAAAAAmR/gHAAAAAMDkCP8AAAAAAJgc4R8AAAAAAJMj/AMAAAAAYHKEfwAAAAAATI7wDwAAAACAyRH+AQAAAAAwOcI/AAAAAAAmR/gHAAAAAMDkCP8AAAAAAJgc4R8AAAAAAJMj/AMAAAAAYHKEfwAAAAAATI7wDwAAAACAyRH+AQAAAAAwOcI/AAAAAAAmR/gHAAAAAMDkCP8AAAAAAJgc4R8AAAAAAJMj/AMAAAAAYHKEfwAAAAAATI7wDwAAAACAyRH+AQAAAAAwOcI/AAAAAAAmR/gHAAAAAMDkCP8AAAAAAJgc4R8AAAAAAJMj/AMAAAAAYHKEfwAAAAAATI7wDwAAAACAyRH+AQAAAAAwOcI/AAAAAAAmR/gHAAAAAMDkCP8AAAAAAJgc4R8AAAAAAJMj/AMAAAAAYHKEfwAAAAAATI7wDwAAAACAyRH+AQAAAAAwOcI/AAAAAAAmR/gHAAAAAMDkCP8AAAAAAJgc4R8AAAAAAJMj/AMAAAAAYHKEfwAAAAAATI7wDwAAAACAyRH+AQAAAAAwOcI/AAAAAAAmR/gHAAAAAMDkCP8AAAAAAJgc4R8AAAAAAJMj/AMAAAAAYHKEfwAAAAAATI7wDwAAAACAyRH+AQAAAAAwOcI/AAAAAAAmR/gHAAAAAMDkCP8AAAAAAJgc4R8AAAAAAJMj/N9hypQpCg4OVoECBVS9enVt3LjR2SUBAAAAAPBQCP+3+eKLLzRo0CC9+eab2r17t5555hk1b95cJ0+edHZpAAAAAAA8MML/bSZOnKiePXuqV69eqly5sj788EOVKlVKn376qbNLAwAAAADggbk6u4BHRWpqqnbu3Kl//vOfdu3h4eHavHlzpo9JSUlRSkqK7X5iYqIkKSkpyTFFXnXMbh3OUccjN3DMcx/HPPdxzHMfxzz3ccxzH8c893HMcx/HPPdxzDPZ9Z/7Ngzjnv0sxv165BFnz55ViRIl9PPPP6tOnTq29jFjxmj27Nk6fPhwhseMGjVKo0ePzs0yAQAAAADI4NSpUypZsuRdtzPyfweLxWJ33zCMDG23DB8+XIMHD7bdv3nzpi5duqSiRYve9TGPoqSkJJUqVUqnTp1SoUKFnF1OnsAxz30c89zHMc99HPPcxzHPfRzz3Mcxz30c89z3Vz7mhmHo8uXLCgwMvGc/wv//V6xYMbm4uCguLs6u/fz58/Lz88v0Me7u7nJ3d7drK1y4sKNKdLhChQr95d7of3Uc89zHMc99HPPcxzHPfRzz3Mcxz30c89zHMc99f9VjbrVa79uHBf/+Pzc3N1WvXl2rV6+2a1+9erXdaQAAAAAAAPzVMPJ/m8GDBysiIkJPPfWUateurc8++0wnT57UP/7xD2eXBgAAAADAAyP836Zjx466ePGi3n77bcXGxqpKlSpauXKlgoKCnF2aQ7m7u2vkyJEZTmGA43DMcx/HPPdxzHMfxzz3ccxzH8c893HMcx/HPPflhWPOav8AAAAAAJgc5/wDAAAAAGByhH8AAAAAAEyO8A8AAAAAgMkR/gEAAAAAMDnCfx70448/OrsEAAAAAEAuYrX/PKhAgQIqUaKEIiMj1a1bN5UqVcrZJQEAAOARde3aNaWlpdm1FSpUyEnVAHhQjPznQWfPntWrr76qJUuWKDg4WE2bNtWXX36p1NRUZ5cG5KgbN25o9OjROnXqlLNLyVPq16+vOXPm6Nq1a84uJU9IS0tTZGSkfv/9d2eXkmddu3ZNSUlJdjfkrBs3bsjV1VXR0dHOLiXPuHr1ql555RX5+vqqYMGCKlKkiN0NOY+/53A0wn8e5OPjo4EDB2rXrl3asWOHQkJC1L9/fwUEBGjgwIHau3evs0s0tY0bN6pLly6qXbu2zpw5I0maO3euNm3a5OTKzMfV1VXvv/++0tPTnV1KnlK9enUNGzZM/v7+6t27t7Zu3erskkwtf/78Wrp0qbPLyHMIRrnL1dVVQUFB/D3PRa+//rrWrVunKVOmyN3dXf/73/80evRoBQYGas6cOc4uz5T4e+48ixcvVocOHVSrVi09+eSTdjczIfzncU888YT++c9/qn///kpOTtaMGTNUvXp1PfPMM9q/f7+zyzOdr7/+Wk2bNpWHh4d2796tlJQUSdLly5c1ZswYJ1dnTo0bN2adi1z2wQcf6MyZM5ozZ44uXLigZ599VqGhoZowYYLOnTvn7PJMqW3btvrmm2+cXUaeQjDKff/+9781fPhwXbp0ydml5AnLly/XlClT1L59e7m6uuqZZ57Rv//9b40ZM0bz5893dnmmxd/z3PfRRx8pMjJSvr6+2r17t2rUqKGiRYvq999/V/PmzZ1dXo7inP88Ki0tTcuWLdOMGTO0evVqPfXUU+rZs6defPFFXbp0SW+88Yb27NmjAwcOOLtUU6lWrZpee+01de3aVd7e3tq7d6/Kli2rPXv2qFmzZoqLi3N2iaYzbdo0jRo1Si+99JKqV68uLy8vu+2tW7d2UmV5x4ULFzRt2jS9++67Sk9P13PPPaeBAweqYcOGzi7NNN59911NmDBBjRo1yvR9PnDgQCdVZl6lS5fWnDlzVL9+fRUqVEi7du1S+fLlNXfuXC1cuFArV650dommU61aNR09elRpaWkKCgrK8D7ftWuXkyozp4IFC2r//v0KCgpSyZIltWTJEtWoUUMxMTEKCwvTlStXnF2iKfH3PPdVqlRJI0eO1Isvvmj3+XzEiBG6dOmSJk+e7OwScwzhPw8aMGCAFi5cKEnq0qWLevXqpSpVqtj1OXnypMqUKaObN286o0TT8vT01IEDB1SmTBm7Py6///67QkNDdf36dWeXaDr58t19gpPFYmEKqYNt27ZNM2fO1MKFC2W1WtW9e3fFxsZq/vz5evnllzVhwgRnl2gKwcHBd91msVg4f9QBCEa5b/To0ffcPnLkyFyqJG+oWrWqPv74Y9WrV0/h4eGqWrWqJkyYoI8++kjjx4/X6dOnnV2iKfH3PPd5enrq4MGDCgoKkq+vr1avXq3HH39cR44cUa1atXTx4kVnl5hjXJ1dAHLfgQMH9PHHH+uFF16Qm5tbpn0CAwO1fv36XK7M/AICAnT06FGVKVPGrn3Tpk0qW7asc4oyOb7Ayn3nz5/X3LlzNXPmTB05ckStWrXSokWL1LRpU1ksFklShw4d1KZNG8J/DomJiXF2CXlO2bJldfz4cQUFBSk0NFRffvmlatSooeXLl6tw4cLOLs+UCPe5KzIyUnv37lW9evU0fPhwtWjRQh9//LFu3LihiRMnOrs80+Lvee7z9/fXxYsXFRQUpKCgIG3dulWPP/64YmJiZLZxcsJ/HpOWlqbSpUurZs2adw3+0p8L69SrVy8XK8sb+vbtq1dffVUzZsyQxWLR2bNntWXLFg0dOlQjRoxwdnlAjihZsqTKlSunHj16qHv37ipevHiGPjVq1NDTTz/thOqAnEEwcp6dO3fq4MGDslgsCg0NVbVq1Zxdkim99tprtp8bNGigQ4cOaceOHSpXrpwef/xxJ1YG5KyGDRtq+fLlevLJJ9WzZ0+99tprWrx4sXbs2KF27do5u7wcxbT/PKhw4cLatWsXI81O8uabb2rSpEm2Kf7u7u4aOnSo3nnnHSdXZk5vv/32PbfzpUvO27hxo5555hlnl5Gn9OjR457bZ8yYkUuV5F0nT54kGDnY+fPn1alTJ/34448qXLiwDMNQYmKiGjRooEWLFmX6RSPwV3T69Gl9++23OnnyZIZLcfPlYs67efOmbt68KVfXP8fFv/zyS23atEnly5fXP/7xj3sOmP7VEP7zoMjISIWFhWnw4MHOLiXPunr1qg4cOKCbN28qNDRUBQsWdHZJpnXniFBaWppiYmLk6uqqcuXKsUAUTKFt27Z299PS0hQdHa2EhAQ1bNhQS5YscVJl5jVnzhx17NhR7u7udu2pqalatGiRunbt6qTKzKtjx446duyY5s6dq8qVK0v681TGbt26qXz58rb1jPDgPvrooyz3ZeE5x1i7dq1at26t4OBgHT58WFWqVNHx48dlGIaefPJJrVu3ztkl4i+M8J8HsYoo8rqkpCR1795dbdu2VUREhLPLMYVq1arZzue/H75wyR03b95Uv379VLZsWQ0bNszZ5ZiOi4uLYmNj5evra9d+8eJF+fr6spioA1itVq1ZsybDKUPbtm1TeHi4EhISnFOYidxrsbnbsfCc49SoUUPNmjXT22+/bVsc2tfXVy+99JKaNWuml19+2dklmsK+fftUpUoV5cuXT/v27btn36pVq+ZSVY5H+M+DWEU0d2XnXCFG53JPdHS0WrZsqePHjzu7FFO43yrct2PRrtxz+PBh1a9fX7Gxsc4uxXTy5cunc+fOZZhqvnfvXjVo0IBr0TuAt7e3Nm7cqCeeeMKufffu3apXr56SkpKcUxiQg7y9vbVnzx6VK1dORYoU0aZNm/TYY49p7969ev755/nckkPy5cunuLg4+fr6Kl++fLJYLJku7me2K0Ox4F8exCqiuctqtdp+NgxDS5culdVq1VNPPSXpz4WLEhISTLegyKMuISFBiYmJzi7DNAj0j6Zjx47pxo0bzi7DVG7NcrFYLGrUqJHtHFFJSk9PV0xMjJo1a+bECs2rYcOGevXVV7Vw4UIFBgZKks6cOaPXXntNjRo1cnJ15pKWlqaQkBB99913Cg0NdXY5eYqXl5dSUlIk/Xn1rWPHjumxxx6TJP3xxx/OLM1UYmJibF/e5qVsRPjPw1JTUxUTE6Ny5crZfXhBzpo5c6bt5zfeeEMdOnTQ1KlT5eLiIunPD4v9+vVToUKFnFWiqd15/qJhGIqNjdXcuXP5gA7TuHMNl1vv8xUrVqhbt25Oqsqc2rRpI0nas2ePmjZtardmi5ubm8qUKaMXXnjBSdWZ2+TJk/X888+rTJkyKlWqlCwWi06ePKmwsDDNmzfP2eWZSv78+ZWSkpLl07mQc2rVqqWff/5ZoaGhatGihYYMGaJff/1VS5YsUa1atZxdnmkEBQVl+rPZMe0/D7p69aoGDBig2bNnS5J+++03lS1bVgMHDlRgYKD++c9/OrlC8ypevLg2bdqkkJAQu/bDhw+rTp06unjxopMqM687T3PJly+fihcvroYNG2r48OHy9vZ2UmXmUqRIkSx/SGQ6dM5r0KCB3f3b3+c9evTgC14HmD17tjp16pRhwT843urVq3Xo0CEZhqHQ0FA1btzY2SWZ0rhx43To0CH973//429ILvr999915coVVa1aVVevXtXQoUNtK89PmjQpTwVVR/r222/VvHlz5c+fX99+++09+xYsWFCVKlWyzTj6KyP850Gvvvqqfv75Z3344Ydq1qyZ9u3bp7Jly+rbb7/VyJEjtXv3bmeXaFpFihTRzJkzbSNHt3zzzTeKjIxUfHy8cwoDHtKtLxOzgpFomEHZsmW1fft2FS1a1K49ISFBTz75JOvn4C+vbdu2Wrt2rQoWLKiwsLAMC0SzThH+yu485/9+XFxcNH78eL322mu5UJ3j8DVeHvTNN9/oiy++UK1atexG6kJDQ3Xs2DEnVmZ+kZGR6tGjh44ePWqburV161aNGzdOkZGRTq4OeHAEeuQ1x48fz3QRqJSUFJ05c8YJFeUNGzZs0IQJE3Tw4EFZLBZVrlxZr7/+up555hlnl2Y6hQsX5hQWJ0pNTdX58+d18+ZNu/bSpUs7qSJzuf243nmM75SamqoFCxZo+PDhhH/89Vy4cCHDpYkkKTk5mXO7HGzChAny9/fXpEmTbKtvBwQEaNiwYRoyZIiTqzOn5ORkjRs3TmvXrs30P1FG5xzr2rVrSktLs2tjfYucd+7cOQ0dOtT2Pr9zUp+ZVip2ttunh/7www92i7qmp6dr7dq1KlOmjBMqM7958+YpMjJS7dq108CBA2UYhjZv3qxGjRpp1qxZ6ty5s7NLNJXb1yxC7vntt9/Us2dPbd682a7dMAzTrTz/V+Hm5qYXXnjhvpcE/Ctg2n8eVK9ePbVv314DBgyQt7e39u3bp+DgYL3yyis6evSooqKinF1innDrkkQEIcd68cUXtWHDBkVERCggICDDF1yvvvqqkyozr+TkZL3xxhv68ssvM13Hgg8uOa958+Y6efKkXnnllUzf588//7yTKjOfW9NDM7ssVP78+VWmTBl98MEHatmypTPKM7XKlSurT58+GUbeJk6cqM8//1wHDx50UmVAzqlbt65cXV31z3/+M9O/548//riTKjO33377TT/++GOmA0UjRoxwUlU5j/CfB23evFnNmjXTSy+9pFmzZqlv377av3+/tmzZog0bNqh69erOLtH0Lly4oMOHD8tisSgkJETFihVzdkmmVbhwYa1YsUJ169Z1dil5Rv/+/bV+/Xq9/fbb6tq1qz755BOdOXNG06ZN07hx4/TSSy85u0TTudv1z+E4wcHB2r59O3+/c5G7u7v279+v8uXL27UfPXpUVapU0fXr151UmXktXrxYX375pU6ePKnU1FS7bbt27XJSVebm5eWlnTt3qlKlSs4uJc/4/PPP9fLLL6tYsWLy9/e3+8LFYrGY6r1+/9UNYDp16tTRzz//rKtXr6pcuXJatWqV/Pz8tGXLFoK/gyUnJ6tHjx4KCAjQs88+q2eeeUYBAQHq2bOnrl696uzyTKlIkSLy8fFxdhl5yvLlyzVlyhS1b99erq6ueuaZZ/Tvf/9bY8aM0fz5851dnimVKlUqwyg0HCsmJsYW/AmduaNUqVJau3Zthva1a9eqVKlSTqjI3D766CNFRkbK19dXu3fvVo0aNVS0aFH9/vvvat68ubPLM63Q0FD98ccfzi4jT/nPf/6jd999V3FxcdqzZ492795tu5kp+EuM/AO5qm/fvlqzZo0mT55sG4netGmTBg4cqCZNmujTTz91coXmM2/ePC1btkyzZ8+Wp6ens8vJEwoWLKj9+/crKChIJUuW1JIlS1SjRg3FxMQoLCxMV65ccXaJprNq1Sp98MEHmjZtGueb55KbN2/q3Xff1dSpU3Xu3DnbZXPfeustlSlTRj179nR2iabz6aefatCgQerRo4fq1Kkji8WiTZs2adasWfrvf/+rvn37OrtEU6lUqZJGjhypF198Ud7e3tq7d6/Kli2rESNG6NKlS5o8ebKzSzSldevW2b4wDwsLU/78+e22c7pozitUqJD27NmjsmXLOrsUhyP851E3b97U0aNHMz2v5dlnn3VSVeZXrFgxLV68WPXr17drX79+vTp06KALFy44pzATq1atmo4dOybDMFSmTJkM/4ma7RvdR0HVqlX18ccfq169egoPD1fVqlU1YcIEffTRRxo/frxOnz7t7BJNp0iRIrp69apu3LghT0/PDO/zS5cuOaky83r77bc1e/Zsvf322+rdu7eio6NVtmxZffnll5o0aZK2bNni7BJNaenSpfrggw9s5/ffWu2fdS1ynqenpw4ePKigoCD5+vpq9erVevzxx3XkyBHVqlUr0zVd8PBuX1fkdiz45zg9e/bU008/rX/84x/OLsXhWO0/D9q6das6d+6sEydOZJgmyh8Vx7p69ar8/PwytPv6+jLt30HatGnj7BLynMjISO3du1f16tXT8OHD1aJFC3388ce6ceOGJk6c6OzyTOnDDz90dgl5zpw5c/TZZ5+pUaNGdh8Yq1atqkOHDjmxMnNr27at2rZt6+wy8gR/f39dvHhRQUFBCgoK0tatW/X4448rJiaG04wcaP369c4uIc8pX7683nrrLW3dujXT2RYDBw50UmU5j5H/POiJJ55QxYoVNXr06ExXEb39skXIWY0aNVLRokU1Z84cFShQQNKfl0Lr1q2bLl26pDVr1ji5QiDnnThxQjt37lS5cuVYpRim4eHhoUOHDikoKMhuSvSBAwdUo0YNTm9xgMjISHXp0kUNGzbk0sS5oFevXipVqpRGjhypqVOnavDgwapbt6527Nihdu3aafr06c4uEcgRwcHBd91msVhMdVloRv7zoCNHjmjx4sUZVsuF4/33v/9Vs2bNVLJkST3++OOyWCzas2ePChQooB9++MHZ5Zlaampqpqe5lC5d2kkV5R23Ro3gWJzOlbsee+wxbdy4McN7+6uvvlK1atWcVJW5Xbx4US1atFDRokXVqVMndenShWPtQJ999pntb8k//vEP+fj4aNOmTWrVqlWemB7tTAkJCdq2bVumf8+7du3qpKrMKyYmxtkl5BpG/vOghg0batiwYWrWrJmzS8mTrl27pnnz5unQoUMyDEOhoaF66aWX5OHh4ezSTOm3335Tz549tXnzZrt2zp1zrLVr12rSpEk6ePCgLBaLKlWqpEGDBqlx48bOLs2UOJ0r9y1fvlwREREaPny43n77bY0ePVqHDx/WnDlz9N1336lJkybOLtGUEhIS9OWXX2rBggXauHGjQkJC1KVLF3Xu3JnFLmEKy5cv10svvaTk5GR5e3tnuOwca7jgYRD+84h9+/bZfj527Jj+/e9/6/XXX8/0vJaqVavmdnmAw9StW1eurq765z//melpLkxDz3mTJ0/Wa6+9pvbt26t27dqS/gynixcv1sSJE/XKK684uULz4XQu5/jhhx80ZswY7dy5Uzdv3tSTTz6pESNGKDw83Nml5QmnT5/WwoULNWPGDB05ckQ3btxwdkmmwwh07qtYsaKee+45jRkzhqsU5aLTp0/r22+/1cmTJ5Wammq3zUzrFRH+84h8+fLJYrHcdYGWW9sYIXKssWPHys/PTz169LBrnzFjhi5cuKA33njDSZWZl5eXl3bu3KlKlSo5u5Q8o0SJEho+fHiGkP/JJ5/o3Xff1dmzZ51UmXl5eXlp7969nM6FPCMtLU0rVqzQvHnztGLFCvn4+OjMmTPOLstUGIF2Di8vL/3666954rJzj4q1a9eqdevWCg4O1uHDh1WlShUdP35chmHoySef1Lp165xdYo7J5+wCkDtiYmL0+++/KyYmJtPbrW1mWtDiUTRt2rRMQ+hjjz2mqVOnOqEi8wsNDdUff/zh7DLylKSkpExPKwoPD1dSUpITKjK/mjVr6ujRo84uI0/asWOH5s6dq3nz5mnnzp3OLsf01q9fr969e8vPz0/dunWTt7e3li9frlOnTjm7NNMZMmSIevToocuXLyshIUHx8fG2G8HfcZo2baodO3Y4u4w8Zfjw4RoyZIiio6NVoEABff311zp16pTq1aunv//9784uL0ex4F8ecfuCRD/99JPq1KkjV1f7X/+NGze0efNmFuZyoLi4OAUEBGRoL168uGJjY51Qkfm99957GjZsmMaMGZPpaS6FChVyUmXm1bp1ay1dulSvv/66XfuyZcvUqlUrJ1VlbgMGDNCQIUMUFxfH6Vy55PTp03rxxRf1888/q3DhwpL+nCJdp04dLVy4UKVKlXJugSZUsmRJXbx4UU2bNtW0adPUqlUr25VzkPPOnDmjgQMHMvU8l7Vo0UKvv/66Dhw4kOnf89atWzupMvM6ePCgFi5cKElydXXVtWvXVLBgQb399tt6/vnn9fLLLzu5wpxD+M+DGjRooNjYWPn6+tq1JyYmqkGDBkz7d6BSpUrp559/znBJkZ9//lmBgYFOqsrcbi0w16hRI7t2TnNxnMqVK+vdd9/Vjz/+aHfO/88//6whQ4boo48+svU107VznemFF16QJLtTijidy7F69OihtLQ0HTx4UCEhIZKkw4cPq0ePHurZs6dWrVrl5ArNZ8SIEfr73/+uIkWKOLuUPOHWCDTTz3NX7969JUlvv/12hm38PXcMLy8vpaSkSJICAwN17NgxPfbYY5JkutmjhP886NaHwTtdvHhRXl5eTqgo7+jVq5cGDRqktLQ0NWzYUNKf5xkNGzZMQ4YMcXJ15rR+/Xpnl5DnTJ8+XUWKFNGBAwd04MABW3vhwoXtrgttsVgI/zkkL12m6FGxceNGbd682Rb8JSkkJEQff/yx6tat68TKzKtPnz7OLsH0vv32W9vPjEA7x50LK8LxatWqpZ9//lmhoaFq0aKFhgwZol9//VVLlixRrVq1nF1ejiL85yHt2rWT9OcH7u7du8vd3d22LT09Xfv27VOdOnWcVV6eMGzYMF26dEn9+vWzrSRaoEABvfHGGxo+fLiTqzOnevXqObuEPIcgmvs4XSv3lS5dWmlpaRnab9y4oRIlSjihorxh+/bt+uqrrzJdkXvJkiVOqso82rRpk6GNEWiY3cSJE3XlyhVJ0qhRo3TlyhV98cUXKl++vCZNmuTk6nIW4T8PuXWpJ8Mw5O3tbXddeTc3N9WqVcs21QiOYbFY9N577+mtt97SwYMH5eHhoQoVKth9EQPHuHr1aqYfFjkXGmZy4MCBTN/njNDlvPHjx2vAgAH65JNPVL16dVksFu3YsUOvvvqqJkyY4OzyTGnRokXq2rWrwsPDtXr1aoWHh+vIkSOKi4tT27ZtnV2eKTDq7HyZfdlyuxEjRuRSJXlDenq6Tp06Zfs86OnpqSlTpji5KsfhUn950OjRozV06FCm+CNPuHDhgiIjI/X9999nup2Ri5wxePDgLPc10/VyHxW///672rZtq19//dXusq63TvHifZ7zihQpoqtXr+rGjRu2BXRv/Xzn/6+sjJ4zqlatqr59+6p///7y9vbW3r17FRwcrL59+yogIECjR492dommsG7dOr3yyivaunVrhkVxExMTVadOHU2dOlXPPPOMkyo0t2rVqtndT0tLU0xMjFxdXVWuXDnt2rXLSZWZV4ECBXTw4MEMa3KZESP/edDIkSOdXUKelZycrHHjxmnt2rU6f/58hm/YudRizhs0aJDi4+O1detWNWjQQEuXLtW5c+f0n//8Rx988IGzyzON3bt3Z6lfZuuN4OG9+uqrCg4O1po1a1S2bFlt27ZNFy9e1JAhQxiFdpAPP/zQ2SXkOceOHVOLFi0kSe7u7kpOTpbFYtFrr72mhg0bEv5zyIcffqjevXtnejUcq9Wqvn37auLEiYR/B8ns/9OkpCR1796dGS4OEhYWpt9//53wD/NavHixvvzyy0ynh/KNouP06tVLGzZsUEREhAICAghCuWDdunVatmyZnn76aeXLl09BQUFq0qSJChUqpLFjx9o+SOLhsLCic23ZskXr1q1T8eLFlS9fPuXLl09/+9vfNHbsWA0cODDLX84g67p16+bsEvIcHx8fXb58WZJUokQJRUdHKywsTAkJCbp69aqTqzOPvXv36r333rvr9vDwcL5UzGWFChXS22+/rZYtWyoiIsLZ5ZjOu+++q6FDh+qdd95R9erVM8zeMtNloQn/edBHH32kN998U926ddOyZcsUGRmpY8eOafv27erfv7+zyzO177//XitWrGAl6FyUnJxsu6ylj4+PLly4oIoVKyosLIwvumAa6enpKliwoCSpWLFiOnv2rEJCQhQUFKTDhw87uTrzSEpKynJfM31YfFQ888wzWr16tcLCwtShQwe9+uqrWrdunVavXp3hcq54cOfOncuwsv/tXF1ddeHChVysCJKUkJCgxMREZ5dhSs2aNZP05/o4tw/MmfFyuYT/PGjKlCn67LPP9OKLL2r27NkaNmyYypYtqxEjRnBeooMVKVJEPj4+zi4jTwkJCdHhw4dVpkwZPfHEE5o2bZrKlCmjqVOnyt/f39nlmVKDBg3uOatl3bp1uVhN3lClShXt27dPZcuWVc2aNTV+/Hi5ubnps88+4xrdOahw4cL3nbFlxg+Lj4rJkyfr+vXrkqThw4crf/782rRpk9q1a6e33nrLydWZR4kSJfTrr7+qfPnymW7ft2+fAgICcrmqvOOjjz6yu28YhmJjYzV37lxbSEXOykuzF1nwLw/y9PTUwYMHFRQUJF9fX61evVqPP/64jhw5olq1aunixYvOLtG05s2bp2XLlmn27Nny9PR0djl5wvz585WWlqbu3btr9+7datq0qS5evKj8+fNr9uzZ6tixo7NLNJ3XXnvN7n5aWpr27Nmj6OhodevWTf/973+dVJl5/fDDD0pOTla7du30+++/q2XLljp06JCKFi2qL774Qg0bNnR2iaawYcOGLPflMqP4qxowYIB+/PFHbd++XQUKFLDbdu3aNdWoUUMNGjTIEFKRM+487zxfvnwqXry4GjZsqOHDh8vb29tJlcEMCP95UNmyZbV48WI9+eSTevrpp9WrVy/17dtXq1atUqdOnRj9d6Bq1arp2LFjMgxDZcqUyTCtjmnoOWfChAkaOnRohvarV6/q0KFDKlasmDp06KCtW7c6obq86da1czlXNHdcunRJRYoUYW0RmEp6erqWLl2qgwcPymKxqHLlynr++edtV1zAwzt37pyefPJJubi46JVXXlFISIgsFosOHjyoTz75ROnp6dq1a5f8/PycXSqQo/LCZaH5S5kHNWzYUMuXL9eTTz6pnj176rXXXtPixYu1Y8cOtWvXztnlmVqbNm2cXUKe8dZbb6lo0aKKjIy0a/f09FTFihUVHh6erfN38fC6dOmiGjVqEP4dYNasWerYsaM8PDxsbZxilDvywofFR0V0dLSef/55xcXFKSQkRJL022+/qXjx4vr2228VFhbm5ArNwc/PT5s3b9bLL7+s4cOH2106tGnTppoyZQrB3wF69OiRpX4zZsxwcCV5T166LDQj/3nQzZs3dfPmTdu35F9++aU2bdqk8uXL6x//+Ifc3NycXCHw8BYvXqyIiAgtXLjQ7kuXK1euKDw8XBcvXtSGDRs47z8XzZ07V2+88YbOnj3r7FJMJyAgQMnJyfr73/+unj17qk6dOs4uyfTy0ofFR0WtWrXk6+ur2bNnq0iRIpKk+Ph4de/eXefPn9eWLVucXKH5xMfH6+jRozIMQxUqVLAdd+S8W1ckqlatmu4Vz5YuXZqLVeUNL730ko4fP64PP/ww08tCm+nKUIR/IJclJCRo8eLFOnbsmF5//XX5+PjYps+VKFHC2eWZyv/+9z8NHDhQK1asUIMGDXTlyhU1a9ZM58+f14YNG1iwyEHatm2bYbXc2NhY7dixQ2+99ZZGjhzpxOrMKT09XStWrNCsWbO0YsUKBQcHKzIyUt26deMLLgfJSx8WHxUeHh7asWOHHnvsMbv26OhoPf3007p27ZqTKgMeXr9+/bRo0SKVLl1aPXr0UJcuXZjBlUsCAgK0bNky1ahRQ4UKFdKOHTtUsWJFffvttxo/frw2bdrk7BJzTD5nFwDniI+P14QJE9SzZ0/16tVLH3zwAef654J9+/apYsWKeu+99zRhwgQlJCRI+vNb3OHDhzu3OBPq1auXRo0apTZt2ujHH39U8+bNFRcXp/Xr1xP8Hahw4cIqXLiwrFarrFarfHx8VL9+fa1cuZLg7yAuLi5q3bq1lixZolOnTqlPnz6aP3++SpcurdatW2vZsmW6efOms8s0lXXr1mnSpEl6+umnbSN2Xbp00fjx4zV27Fhnl2dKISEhOnfuXIb28+fP33VleuCvYsqUKYqNjdUbb7yh5cuXq1SpUurQoYN++OGHe84EwMPL7LLQkkx5WWjCfx60YcMGBQcH66OPPlJ8fLwuXbqkjz76SMHBwdlayRjZN3jwYHXv3l1HjhyxW0G3efPm+umnn5xYmXkNGzZM/fr1U6NGjXT27Fn9+OOPzLBwkKtXr6p///764Ycf9N133+n69et6//33NX36dI0bN07h4eHOLjFP8PX1Vd26dVW7dm3ly5dPv/76q7p3765y5crpxx9/dHZ5ppGXPiw6U1JSku02ZswYDRw4UIsXL9bp06d1+vRpLV68WIMGDdJ7773n7FKBh+bu7q4XX3xRq1ev1oEDB/TYY4+pX79+CgoK0pUrV5xdnmnduiy0JNtloc+cOWPKy0Kz4F8e1L9/f3Xo0EGffvqpXFxcJP05ZbRfv37q37+/oqOjnVyheW3fvl3Tpk3L0F6iRAnFxcU5oSLzunPxyvz586tYsWIaOHCgXfuSJUtysyxTGzlypGbNmqWXXnpJHh4eWrBggV5++WV99dVXzi4tTzh37pzmzp2rmTNn6vfff1ebNm303XffqXHjxrp27Zr+/e9/q1u3bjpx4oSzSzWFWx8Wy5QpY/uwWKZMGVN+WHSmwoULZziNqEOHDra2WyOirVq1Yp0FmIrFYpHFYpFhGMzccrBBgwYpNjZW0p+fZZo2bar58+fbLgttJpzznwd5eHhoz549tpVybzl8+LCeeOIJzplzID8/P0VFRalatWry9vbW3r17VbZsWa1atUo9e/bUqVOnnF2iady5yv/dzJw508GV5B3lypXTu+++q06dOkmStm3bprp16+r69eu2LxrhGK1atdIPP/ygihUrqlevXuratWuGc0XPnj2rkiVL8iEyh8yfP19paWnq3r27du/eraZNm+rixYu2D4sdO3Z0dommkJ0ZifXq1XNgJYDjpaSkaMmSJZoxY4Y2bdqkli1bKjIyUs2aNVO+fEzYzml58bLQhP88qG7dunr99dczXHbum2++0XvvvcdquQ7Up08fXbhwQV9++aV8fHy0b98+ubi4qE2bNnr22Wf14YcfOrtE4IG5ubkpJibG7rQKDw8P/fbbbypVqpQTKzO/W+u31K5d+659DMPQyZMnFRQUlIuVmU9e/LAIwPFuX/AvMjJSXbp0UdGiRZ1dlql5eHhoypQpmQ4Y3bo6VEJCgg4cOOCE6hyD8J9H7Nu3z/bzwYMHNWzYMA0YMEC1atWSJG3dulWffPKJxo0bx2iFAyUlJem5557T/v37dfnyZQUGBiouLk61a9fWypUr5eXl5ewSgQfm4uKiuLg4FS9e3Nbm7e2tffv2KTg42ImVmV9MTAzHOJfkxQ+Lj5Lr169r3759On/+fIZZLK1bt3ZSVcDDy5cvn0qXLq1q1arZnepyJ05XzDl58bLQhP88Il++fLbzhu7FYrFwzlwuWLdunXbt2qWbN2/qySefVOPGjZ1dEvDQ8uXLp+bNm8vd3d3Wtnz5cjVs2NDuiy0+uOQ8FxcXPfvss+rZs6fat29vt6AoclZe/LD4qIiKilLXrl31xx9/ZNjG5xf81XXv3v2eof8WTlfMWXntstCE/zwiOws8MSUUwINgnQXniY6O1owZMzR//nylpKSoY8eO6tmzp2rUqOHs0kwpr31YfFSUL19eTZs21YgRI+Tn5+fscgCYxPjx4/Xuu+9q2bJleuuttxQbG6sNGzaY8upQhH8gl61du1Zr167NdMrijBkznFQVADO4ceOGli9frlmzZun7779XhQoV1LNnT0VERNidjoGHl5c+LD4qChUqpN27d6tcuXLOLgWAyQwfPlzjx49XmTJltGHDBpUsWdLZJTkE4R/IRaNHj9bbb7+tp556SgEBARmmdy1dutRJlQEwk5SUFE2ZMkXDhw9Xamqq8ufPr44dO+q9995jVDoH5ZUPi4+KHj16qG7duurZs6ezSwFgAndeFnrlypV6/PHHM3yJa6bTFQn/QC4KCAjQ/2vvzoOqqv8/jr/OBUEQcQVFQ1FLydxTJhW/iqk4WjbZNGmoIDpFjRmYCJa7lqZm2UyLmaiZykSS5pozqSiZKZpbEKaY2EDlviGy3d8f39/3Tjf89nUBDvfe52OGmXs+n3MPL5hheZ/zWebPn6+RI0eaHQWAE8rIyFBSUpKSk5NVq1YtRUZGasyYMcrLy9O0adN07do17d+/3+yYDs0V/1msLgoKCvTss8/Kz89P7du3V40aNez6x48fb1IyAI7IFacrUvwDVahBgwbav38/QxYBVKhFixZp+fLlys7O1qBBgzR27FgNGjTIbl/okydPKjg4WCUlJSYmdXyu+M9idfHpp58qJiZGXl5eatCggd3oOcMwlJOTY2I6AKj+KP6BKpSQkCAfHx9NnTrV7CgAnMhDDz2k6OhojR49+r+uMl9UVKS1a9cqMjKyitMBFaNx48YaP368EhMT7W5sAQDuDMW/CysqKrrtonPNmjUzKZFzmjBhgu11WVmZVq5cqQ4dOqhDhw7lhiwuWrSoquMBAOAQ6tevrwMHDjB6DgDuEcW/C/rll18UHR2tvXv32rVbrVb2ya0EYWFhd3zuzp07KzEJAGdXUFCg3NxcFRUV2bV36NDBpERAxYmLi5Ofn59ef/11s6MAgENyNzsAql5UVJTc3d21adOm2644j4pFQQ+gsp07d05RUVHatm3bbfu5qQtnUFpaqvnz5+ubb75h9BwA3AOKfxd0+PBhHTx4UMHBwWZHcTnR0dFavHixateubdd+48YNvfLKK0pKSjIpGQBHFhsbq8uXL2vfvn0KCwvTV199pT/++ENz5szRO++8Y3Y8oEIcO3ZMnTt3liQdP37cro8HGQDwvzHs3wV169ZN7777rkJDQ82O4nLc3NyUn58vf39/u/bz58+rcePGrMIN4J4EBARow4YNCgkJka+vrzIyMtS6dWt9/fXXmj9/vtLT082OCAAATMZSqS7o7bff1qRJk7Rr1y5duHBBV69etftAxbt69aquXLkiq9Wqa9eu2X2/L126pC1btpS7IQAAd+rGjRu23yH169fXuXPnJEnt27fXoUOHzIwGAACqCYb9u6B+/fpJkh5//HG7dhb8qzx169aVYRgyDEOtW7cu128YhmbOnGlCMgDOoE2bNsrOzlZQUJA6deqkJUuWKCgoSB9//LECAgLMjgdUiLCwsH8c3r9jx44qTAMAjofi3wWxAF3V27lzp6xWq/r27at169apfv36tj4PDw81b95cTZo0MTEhAEcWGxur/Px8SdL06dMVHh6u1atXy8PDQytWrDA3HFBBOnXqZHdcXFysw4cP6/jx44qMjDQnFAA4EOb8A1XozJkzCgwMlMXCjBsA96+goEDx8fFav369iouL1a9fP73//vvy9vbWzz//rGbNmqlhw4ZmxwQq1YwZM3T9+nUtXLjQ7CgAUK1R/Lsw9oM2x+XLl7Vs2TJlZWXJMAy1bdtW0dHRqlOnjtnRADiY+Ph4ffjhh4qIiJCXl5fWrFmjPn36KCUlxexoQJU5efKkQkJCdPHiRbOjAEC1RvHvgs6dO6fRo0dr69att+1nzn/lycjIUHh4uLy8vBQSEiKr1aqMjAzdvHlT27dvV5cuXcyOCMCBtGrVSm+++aaGDRsmSdq/f7969uypwsJCubm5mZwOqBqrVq1SQkKC8vLyzI4CANUac/5dUGxsrC5dusR+0CaIi4vTkCFDtHTpUrm7//vHr6SkRGPHjlVsbKx2795tckIAjuTs2bPq1auX7TgkJETu7u7Ky8tTYGCgicmAijd06FC7Y6vVqvz8fGVkZGjq1KkmpQIAx0Hx74J27NihDRs2qFu3brJYLGrevLn69+8vX19fzZ07V4MHDzY7otPKyMiwK/wlyd3dXZMmTVLXrl1NTAbAEZWWlsrDw8Ouzd3dXSUlJSYlAirP36fHWSwWtWnTRrNmzdKAAQNMSgUAjoPi3wXdbj/o1q1bsx90FfD19VVubq6Cg4Pt2s+ePavatWublAqAo7JarYqKipKnp6etrbCwUDExMapVq5atLTU11Yx4QIUpLS1VVFSU2rdvb7djDgDgzlH8uyD2gzbPc889pzFjxmjhwoXq0aOHDMNQenq64uPjNXz4cLPjAXAwt9vebMSIESYkASqXm5ubwsPDlZWVRfEPAPeI4t8FsR+0eRYuXCiLxaJRo0bZhuXWqFFDL730kubNm2dyOgCOZvny5WZHAKpM+/btlZOToxYtWpgdBQAcEqv9QwUFBewHXcn+vhd3WFiYxo0bpzp16ujBBx+Ut7e32REBAKjWtm/froSEBM2ePVuPPvqo3dQW6d9T6wAA/x3FvwuaNWuWJk6cWK7gvHnzphYsWKBp06aZlMx5sRc3AAD3x2Kx2F4bhmF7bbVaZRgGWxUDwP9A8e+C3NzclJ+fb1v07z8uXLggf39//nhWAvbiBgDg/qSlpf1jf+/evasoCQA4Jub8u6D/3CH/uyNHjrCITiVhL24AAO4PxT0A3B+KfxdSr149GYYhwzDUunVruxsApaWlun79umJiYkxM6LzYixsAgPu3Z88eLVmyRDk5OUpJSVHTpk21atUqtWjRQqGhoWbHA4BqjeLfhbz33nuyWq2Kjo7WzJkzVadOHVufh4eHgoKC1L17dxMTOi/24gYA4P6sW7dOI0eOVEREhA4dOqRbt25Jkq5du6a33npLW7ZsMTkhAFRvzPl3QWlpaerRo4dq1KhhdhSXMXr06Ds6j227AAC4vc6dOysuLk6jRo1S7dq1deTIEbVs2VKHDx/WwIED9fvvv5sdEQCqNYp/F3H16tU7PpetcgAAQHXj7e2tzMxMBQUF2RX/OTk5atu2rQoLC82OCADVGsP+XUTdunVvu8jfX7FVDgAAqK4CAgJ08uRJBQUF2bWnp6erZcuW5oQCAAdC8e8idu7caXYEAACAe/biiy/q1VdfVVJSkgzDUF5enr7//ntNnDhR06ZNMzseAFR7DPsHAACAQ5gyZYoWLVpkG+Lv6empiRMnavbs2SYnA4Dqj+LfBe3evfsf+//1r39VURIAAIB/VlBQoPj4eK1fv17FxcUKCwvTa6+9Jklq27atfHx8TE4IAI6BYf8uqE+fPuXa/roeAHP+AQBAdTF9+nStWLFCERER8vLy0po1a1RWVqaUlBSzowGAQ6H4d0GXLl2yOy4uLtaPP/6oqVOn6s033zQpFQAAQHmpqalatmyZhg0bJkmKiIhQz549VVpaKjc3N5PTAYDjYNg/bHbv3q24uDgdPHjQ7CgAAACSJA8PD50+fVpNmza1tXl5eenEiRMKDAw0MRkAOBaL2QFQffj5+Sk7O9vsGAAAADalpaXy8PCwa3N3d1dJSYlJiQDAMTHs3wUdPXrU7thqtSo/P1/z5s1Tx44dTUoFAABQntVqVVRUlDw9PW1thYWFiomJUa1atWxtqampZsQDAIdB8e+COnXqJMMw9PcZH4899piSkpJMSgUAAFBeZGRkubYRI0aYkAQAHBtz/l3QmTNn7I4tFov8/PxUs2ZNkxIBAAAAACoTxT8AAAAAAE6OBf9cyA8//KCtW7fatX322Wdq0aKF/P399cILL+jWrVsmpQMAAAAAVBaKfxcyY8YMu8X+jh07pjFjxqhfv35KTEzUxo0bNXfuXBMTAgAAAAAqA8P+XUhAQIA2btyorl27SpLeeOMNpaWlKT09XZKUkpKi6dOnKzMz08yYAAAAAIAKxpN/F3Lp0iU1atTIdpyWlqaBAwfajrt166azZ8+aEQ0AAAAAUIko/l1Io0aNdPr0aUlSUVGRDh06pO7du9v6r127pho1apgVDwAAAABQSSj+XcjAgQOVmJioPXv2aPLkyfL29lavXr1s/UePHlWrVq1MTAgAAAAAqAzuZgdA1ZkzZ46GDh2q3r17y8fHRytXrpSHh4etPykpSQMGDDAxIQAAAACgMrDgnwu6cuWKfHx85ObmZtd+8eJF+fj42N0QAAAAAAA4Pop/AAAAAACcHHP+AQAAAABwchT/AAAAAAA4OYp/AAAAAACcHMU/AACoVlasWKG6deuaHQMAAKdC8Q8AAO5YVFSUDMNQTExMub6XX35ZhmEoKiqq6oP9xa5du2QYhi5fvmxqDgAAqhOKfwAAcFcCAwOVnJysmzdv2toKCwu1du1aNWvW7L6uXVxcfL/xAADAbVD8AwCAu9KlSxc1a9ZMqamptrbU1FQFBgaqc+fOtrZt27YpNDRUdevWVYMGDfTEE0/o1KlTtv5ff/1VhmHoiy++UJ8+fVSzZk19/vnn5T7fhQsXFBISoiFDhqiwsFBWq1Xz589Xy5Yt5eXlpY4dO+rLL7+0XTMsLEySVK9evWoxEgEAgOqA4h8AANy10aNHa/ny5bbjpKQkRUdH251z48YNTZgwQQcOHNC3334ri8Wip59+WmVlZXbnJSQkaPz48crKylJ4eLhd32+//aZevXopODhYqampqlmzpqZMmaLly5fro48+0k8//aS4uDiNGDFCaWlpCgwM1Lp16yRJ2dnZys/P1+LFiyvpuwAAgONwNzsAAABwPCNHjtTkyZNtT++/++47JScna9euXbZznnnmGbv3LFu2TP7+/srMzFS7du1s7bGxsRo6dGi5z3HixAn1799fTz31lBYvXizDMHTjxg0tWrRIO3bsUPfu3SVJLVu2VHp6upYsWaLevXurfv36kiR/f38WDgQA4P9R/AMAgLvWsGFDDR48WCtXrpTVatXgwYPVsGFDu3NOnTqlqVOnat++fTp//rztiX9ubq5d8d+1a9dy179586ZCQ0M1fPhwuyf3mZmZKiwsVP/+/e3OLyoqsptyAAAA7FH8AwCAexIdHa1x48ZJkj744INy/U8++aQCAwO1dOlSNWnSRGVlZWrXrp2KiorszqtVq1a593p6eqpfv37avHmz4uPj9cADD0iS7QbC5s2b1bRp03LvAQAAt0fxDwAA7snAgQNthfzf5+pfuHBBWVlZWrJkiXr16iVJSk9Pv+NrWywWrVq1Ss8//7z69u2rXbt2qUmTJmrbtq08PT2Vm5ur3r173/a9Hh4ekqTS0tJ7+bIAAHBKFP8AAOCeuLm5KSsry/b6r+rVq6cGDRrok08+UUBAgHJzc5WYmHjX11+9erWGDx9uuwHQuHFjTZw4UXFxcSorK1NoaKiuXr2qvXv3ysfHR5GRkWrevLkMw9CmTZs0aNAgeXl5ycfHp8K+bgAAHBGr/QMAgHvm6+srX1/fcu0Wi0XJyck6ePCg2rVrp7i4OC1YsOCur+/u7q61a9fqkUceUd++ffXnn39q9uzZmjZtmubOnauHH35Y4eHh2rhxo1q0aCFJatq0qWbOnKnExEQ1atTINjUBAABXZlitVqvZIQAAAAAAQOXhyT8AAAAAAE6O4h8AAAAAACdH8Q8AAAAAgJOj+AcAAAAAwMlR/AMAAAAA4OQo/gEAAAAAcHIU/wAAAAAAODmKfwAAAAAAnBzFPwAAAAAATo7iHwAAAAAAJ0fxDwAAAACAk6P4BwAAAADAyf0fqQU/jcP9V58AAAAASUVORK5CYII=", 192 | "text/plain": [ 193 | "
" 194 | ] 195 | }, 196 | "metadata": {}, 197 | "output_type": "display_data" 198 | } 199 | ], 200 | "source": [ 201 | "# Objective 5\n", 202 | "market_volatility = df.groupby('Market')['Modal_x0020_Price'].std().sort_values(ascending=False)\n", 203 | "plt.figure(figsize=(12, 6))\n", 204 | "market_volatility[:10].plot(kind='bar', color='orange')\n", 205 | "plt.xlabel('Market')\n", 206 | "plt.ylabel('Price Volatility (Std Dev)')\n", 207 | "plt.title('Top 10 Markets with Highest Price Variations')\n", 208 | "plt.xticks(rotation=90)\n", 209 | "plt.show()" 210 | ] 211 | }, 212 | { 213 | "cell_type": "code", 214 | "execution_count": null, 215 | "id": "8b1c4d4e-7f6c-4cfb-ac44-572d35db84a1", 216 | "metadata": {}, 217 | "outputs": [], 218 | "source": [] 219 | } 220 | ], 221 | "metadata": { 222 | "kernelspec": { 223 | "display_name": "Python [conda env:base] *", 224 | "language": "python", 225 | "name": "conda-base-py" 226 | }, 227 | "language_info": { 228 | "codemirror_mode": { 229 | "name": "ipython", 230 | "version": 3 231 | }, 232 | "file_extension": ".py", 233 | "mimetype": "text/x-python", 234 | "name": "python", 235 | "nbconvert_exporter": "python", 236 | "pygments_lexer": "ipython3", 237 | "version": "3.12.7" 238 | } 239 | }, 240 | "nbformat": 4, 241 | "nbformat_minor": 5 242 | } 243 | --------------------------------------------------------------------------------