Grocery Exploratory Data Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "d185353a",
   "metadata": {},
   "source": [
    "# Exploratory Data Analysis of Grocery Sales "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "5fa597de",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "32cfbd28",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv(r\"C:\\Users\\chris\\Downloads\\archive (7)\\Supermart Grocery Sales - Retail Analytics Dataset.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6fd1e0d9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Order ID</th>\n",
       "      <th>Customer Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>Sub Category</th>\n",
       "      <th>City</th>\n",
       "      <th>Order Date</th>\n",
       "      <th>Region</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Discount</th>\n",
       "      <th>Profit</th>\n",
       "      <th>State</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>OD1</td>\n",
       "      <td>Harish</td>\n",
       "      <td>Oil &amp; Masala</td>\n",
       "      <td>Masalas</td>\n",
       "      <td>Vellore</td>\n",
       "      <td>11-08-2017</td>\n",
       "      <td>North</td>\n",
       "      <td>1254</td>\n",
       "      <td>0.12</td>\n",
       "      <td>401.28</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>OD2</td>\n",
       "      <td>Sudha</td>\n",
       "      <td>Beverages</td>\n",
       "      <td>Health Drinks</td>\n",
       "      <td>Krishnagiri</td>\n",
       "      <td>11-08-2017</td>\n",
       "      <td>South</td>\n",
       "      <td>749</td>\n",
       "      <td>0.18</td>\n",
       "      <td>149.80</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>OD3</td>\n",
       "      <td>Hussain</td>\n",
       "      <td>Food Grains</td>\n",
       "      <td>Atta &amp; Flour</td>\n",
       "      <td>Perambalur</td>\n",
       "      <td>06-12-2017</td>\n",
       "      <td>West</td>\n",
       "      <td>2360</td>\n",
       "      <td>0.21</td>\n",
       "      <td>165.20</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>OD4</td>\n",
       "      <td>Jackson</td>\n",
       "      <td>Fruits &amp; Veggies</td>\n",
       "      <td>Fresh Vegetables</td>\n",
       "      <td>Dharmapuri</td>\n",
       "      <td>10-11-2016</td>\n",
       "      <td>South</td>\n",
       "      <td>896</td>\n",
       "      <td>0.25</td>\n",
       "      <td>89.60</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>OD5</td>\n",
       "      <td>Ridhesh</td>\n",
       "      <td>Food Grains</td>\n",
       "      <td>Organic Staples</td>\n",
       "      <td>Ooty</td>\n",
       "      <td>10-11-2016</td>\n",
       "      <td>South</td>\n",
       "      <td>2355</td>\n",
       "      <td>0.26</td>\n",
       "      <td>918.45</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Order ID Customer Name          Category      Sub Category         City  \\\n",
       "0      OD1        Harish      Oil & Masala           Masalas      Vellore   \n",
       "1      OD2         Sudha         Beverages     Health Drinks  Krishnagiri   \n",
       "2      OD3       Hussain       Food Grains      Atta & Flour   Perambalur   \n",
       "3      OD4       Jackson  Fruits & Veggies  Fresh Vegetables   Dharmapuri   \n",
       "4      OD5       Ridhesh       Food Grains   Organic Staples         Ooty   \n",
       "\n",
       "   Order Date Region  Sales  Discount  Profit       State  \n",
       "0  11-08-2017  North   1254      0.12  401.28  Tamil Nadu  \n",
       "1  11-08-2017  South    749      0.18  149.80  Tamil Nadu  \n",
       "2  06-12-2017   West   2360      0.21  165.20  Tamil Nadu  \n",
       "3  10-11-2016  South    896      0.25   89.60  Tamil Nadu  \n",
       "4  10-11-2016  South   2355      0.26  918.45  Tamil Nadu  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "e6fe7e9e",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 9994 entries, 0 to 9993\n",
      "Data columns (total 11 columns):\n",
      " #   Column         Non-Null Count  Dtype  \n",
      "---  ------         --------------  -----  \n",
      " 0   Order ID       9994 non-null   object \n",
      " 1   Customer Name  9994 non-null   object \n",
      " 2   Category       9994 non-null   object \n",
      " 3   Sub Category   9994 non-null   object \n",
      " 4   City           9994 non-null   object \n",
      " 5   Order Date     9994 non-null   object \n",
      " 6   Region         9994 non-null   object \n",
      " 7   Sales          9994 non-null   int64  \n",
      " 8   Discount       9994 non-null   float64\n",
      " 9   Profit         9994 non-null   float64\n",
      " 10  State          9994 non-null   object \n",
      "dtypes: float64(2), int64(1), object(8)\n",
      "memory usage: 859.0+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "0e6d6d5e",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sales</th>\n",
       "      <th>Discount</th>\n",
       "      <th>Profit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>9994.000000</td>\n",
       "      <td>9994.000000</td>\n",
       "      <td>9994.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1496.596158</td>\n",
       "      <td>0.226817</td>\n",
       "      <td>374.937082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>577.559036</td>\n",
       "      <td>0.074636</td>\n",
       "      <td>239.932881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>500.000000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>25.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1000.000000</td>\n",
       "      <td>0.160000</td>\n",
       "      <td>180.022500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1498.000000</td>\n",
       "      <td>0.230000</td>\n",
       "      <td>320.780000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1994.750000</td>\n",
       "      <td>0.290000</td>\n",
       "      <td>525.627500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2500.000000</td>\n",
       "      <td>0.350000</td>\n",
       "      <td>1120.950000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Sales     Discount       Profit\n",
       "count  9994.000000  9994.000000  9994.000000\n",
       "mean   1496.596158     0.226817   374.937082\n",
       "std     577.559036     0.074636   239.932881\n",
       "min     500.000000     0.100000    25.250000\n",
       "25%    1000.000000     0.160000   180.022500\n",
       "50%    1498.000000     0.230000   320.780000\n",
       "75%    1994.750000     0.290000   525.627500\n",
       "max    2500.000000     0.350000  1120.950000"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce851a95",
   "metadata": {},
   "source": [
    "# Null Values & Duplicate Values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e9dcc0fe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Order ID         0\n",
       "Customer Name    0\n",
       "Category         0\n",
       "Sub Category     0\n",
       "City             0\n",
       "Order Date       0\n",
       "Region           0\n",
       "Sales            0\n",
       "Discount         0\n",
       "Profit           0\n",
       "State            0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "56639619",
   "metadata": {},
   "source": [
    "No null values present in the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "38af242d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.duplicated().any()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "63d219c4",
   "metadata": {},
   "source": [
    "No duplicate values present in the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 266,
   "id": "67ad5b11",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Order ID                 object\n",
       "Customer Name            object\n",
       "Category                 object\n",
       "Sub Category             object\n",
       "City                     object\n",
       "Order Date       datetime64[ns]\n",
       "Region                   object\n",
       "Sales                     int64\n",
       "Discount                float64\n",
       "Profit                  float64\n",
       "State                    object\n",
       "Order Year                int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 266,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "3ef4ecfc",
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Order Date'] = data['Order Date'].astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "4e1f5490",
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Order Date'] = pd.to_datetime(data['Order Date'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "735fcee3",
   "metadata": {},
   "source": [
    "# Total Sales by region"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "dcdd5af2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Region</th>\n",
       "      <th>Order ID</th>\n",
       "      <th>Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>West</td>\n",
       "      <td>3203</td>\n",
       "      <td>4798743</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>East</td>\n",
       "      <td>2848</td>\n",
       "      <td>4248368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Central</td>\n",
       "      <td>2323</td>\n",
       "      <td>3468156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>South</td>\n",
       "      <td>1619</td>\n",
       "      <td>2440461</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>North</td>\n",
       "      <td>1</td>\n",
       "      <td>1254</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Region  Order ID    Sales\n",
       "4     West      3203  4798743\n",
       "1     East      2848  4248368\n",
       "0  Central      2323  3468156\n",
       "3    South      1619  2440461\n",
       "2    North         1     1254"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "region = pd.pivot_table(data=data, index='Region', values=['Order ID', 'Sales'], \n",
    "               aggfunc = {'Order ID':'count', 'Sales':'sum'}).reset_index().sort_values(by='Sales', ascending=False)\n",
    "region"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 317,
   "id": "02c6060d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = plt.axes()\n",
    "sns.barplot(x='Sales',y='Region',data=region)\n",
    " \n",
    "for i in ax.containers:\n",
    "    ax.bar_label(i,label_type='edge',padding=5,fontsize=20,bbox=bbox_args,fmt=\"%d\")\n",
    "plt.title('Total Sales by Region')\n",
    "plt.ylabel(None)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ef67ddc",
   "metadata": {},
   "source": [
    "# Total Orders by Region"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 316,
   "id": "9d9adc27",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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b++vl5aW+fftmserMvfzyy+rcubP56NSpk5o3b67SpUvrkUceMX9WS5QoodmzZ6tBgwZp9pMXPzM7duzQ+fPnzddPP/10pn0+88wzmbaxVcrvV9WqVdWzZ88M2xcrVsyqxj///DPTe1E9PT3Vv3//DNtUr15dFStWNF8fOHAgw/YAChcCIIA8sXnzZvN569atbToD161bN1ksFvO1rUOcZ9X58+f1448/avTo0RowYIB69Ohh9Qdp586dzeHiDcOwGlwiL6UcAMbNzS1Hfd2+fvJAO+mpU6dOqoFz0pLymGQW/pJ16dIl0zYppzMICgqyqV9Jqlevnvl8x44dGbb18vKyap8eHx8fVa9eXdKt49+zZ0/9/fffNteUWzp16mRTu5Sf79atW9Ns07dvX/NM7ZEjRxQeHp5mu++//958PmDAABUvXtzWcm22detWLVu2zHwsX75cmzZtMqcrsVgsGjJkiPbt25fhgDV58TOT8vMrV66c6tatm2l/LVu2zLVBclL+3uzcubPV78P0pJwzMTY2Vvv378+wfaNGjWyqN+VAXPn1n2AA8gejgALIE0eOHDGfp5yXLiOenp7y9/fX8ePHU/WRG06fPq1Ro0Zp/vz55tlJW9hyaWFu8Pb2Ns965nQOrtvXT+8yzWTJgSczKY+JLWFKkk1/RKe8rHTRokXas2ePTX2nHKE0edTT9FSrVs2mP6gl6YUXXtDzzz8vSdq2bZvuuece3XPPPercubNatWql5s2bZ/qZ5lR2Pt/jx48rISEh1ciUxYoV06OPPqrPP/9c0q1RPm+f9/Ds2bNavHix+To/L/9MyTAMrVmzJtORa/PiZyblfIMZXbKekqurq2rUqJErZ8my83uzdu3acnFxMUcFPXLkSIbfuYwuKU2pRIkS5vPkM60AigYCIIA8kfJ/jJMvp7RF2bJlzQCYPBx5bti3b58CAwOzdVlpyjNzecnHx8es7/Zh8LPq9ks+Mzu7l9Ew+ymlPCZlypSxaR1b2qXc3wMHDmTrj+nMgrqt+yhJQ4cO1cGDB/XFF1+Y7+3atUu7du3Shx9+KCcnJzVu3Fj9+/fX448/Li8vryzXm5nsfr5RUVFpfueeeuopMwDOnz9fX375pdWlwjNmzDBDxL333quGDRtms/KMhYaGWoXP6OhonThxQrNnz9ZXX32lmJgY/fvvv2rbtq02b96satWqpdlPXvzMpHydlcuwc3rJdrLs/N50cXGRt7e3GWYz+72ZnasL0rtkGEDhxCWgAPJEdi9ndHd3T7OPnEhMTFS/fv3McOXu7q4nnnhCCxYs0IEDBxQdHa34+HgZt0ZGlmEYOR6EJTtSnoXbu3dvjv7o2r17t9Xr9P6ITubkZNs/BynnRbP1uKY8pum5evWqTX1lJLN7n2zdR+nWZYiff/651qxZo169eqXa16SkJG3ZskWjRo1StWrV9Msvv2Sr5oxk9/NN73tTt25d857CGzdu6Oeff7ZannJAlfw8++fl5aUGDRrogw8+0IYNG8wwdfHiRT3yyCPpnq3Pi5+Z7H7ncisgFaTfmwCKLgIggDyR8oxI8r09tkh56WJu/a/6n3/+aV4u5urqqtWrV2vq1KkKDg7WnXfeKU9Pz1T3xGSl5tzSsmVL83lMTEyOLilLeS9TrVq1VL58+RzVlizlhNC2fka2tEt5rKdPn24Vxm19ZDS6ZXa1atVKv//+uyIjI7V8+XK99dZbuv/++61G/IyMjNTAgQO1YMGCXN12dj/fjM5GphwMJuX9fuHh4Tp06JAkqXjx4ho4cGBWSs01devW1bfffmu+3rBhg1WdKeXFz0zKPrNy31tuXSZekH5vAii6CIAA8kS5cuXM58eOHbNpHcMwrNqm7CMnVqxYYT4fMGBApiMrXrt2zS6DHrRu3drq9ezZs7PVz7Fjx6wGa7m935xIGSSTL9W1pZ6s9JscRAqSEiVKqEOHDnr33Xe1du1anT9/Xh9++KHVfVIvvfRSrm4zO59viRIlVLJkyXTb9uvXzwwIO3fu1M6dOyVZh8EHH3wwTy5ptVW/fv2sBnV555130rwHLS9+ZlJOjWDrf8DcvHlTR48ezZXtZ+f3ZkREhFVYzK3fmwCKLgIggDyR8v6hlCPbZWTv3r3m6Ju395Es5WV8tl52lXJghyZNmmTafvPmzZleTpgXWrVqZTUP3w8//KDr169nuZ+vv/7a6rPJzcv57r33XvN5eiNO3s6Wds2aNTOfr1q1KuuF5bMyZcrolVde0VdffWW+d/To0VwduCg7n2/K45OW4sWL65FHHjFfT506VdHR0fr111/N9+w1+EtK77//vvn8zJkzVmcFk+XFz0zK3w8XL17Uvn37Ml1nw4YNVpdG50R2fm9u3LjRfG6xWDL9GQAAAiCAPNGqVSvz+b59+2waRj/lPUne3t5pjoKYcjoJW8PRzZs3zee2jAKZciLs/HT7XIj//fdfupNgp2ffvn2aPHmy+bpZs2ZWfyjnVMrjunz58kzPlCYlJWnu3LmZ9ptySolNmzZZTYZdkPXq1cvqdco55HJq0aJFmY6+mJCQYBXebJkLL+VloL/88ou+//5787tUq1atXD1jnF3Nmze3mt/w448/TjWVSV78zDRs2NBqMvm0guftbGljq5Tfr5UrV2Y6sq1k/XuzXr16XAIKIFMEQAB5okOHDvLz8zNfv/baaxm2P3XqlL788kvzdUhIiNV9VslSDmF+9OhRm84CppzQeP369Rm23bx5s3766adM+8wrTz75pNX/4H/00Uc2Xwp6/vx5BQcHm4HXxcXFHPUxtzz00EPmgBM3btzQe++9l2H777//3qbL4zp27Kg6deqYr5955hm7DWaRlQE9bh+IxJa5FG0VExOjCRMmZNjmm2++0X///We+Hjx4cKb91q9f3/xPgaioKL3xxhvmsieeeCKb1ea+t956y3x+9uxZTZ061Wp5XvzMuLi46LHHHjNff/PNN9q0aVO67ZcuXZrtS7XT0r9/f/Oy4vj4eL399tsZtt+2bZvmzZtnvi5Ixw9AwUUABJAnnJ2d9corr5ivlyxZopdeeinNSyvPnTun7t27m39Me3h4aOTIkWn2W79+fXOOs0uXLunHH3/MtJY2bdqYz+fOnZvu5WI7duxQz549szRHYG5zc3PTrFmzzD8Ck5KS9Oijj+q9996zOpN5u/Xr16tVq1Y6ePCg+d67775r0yWvWVG6dGmrSwQnTpyY7hnTsLAwqzOaGbFYLPr444/NM7SbN29Wt27dMj2jdv36df34449q166djXuQuTVr1qh79+4KCwvLMAwmJibq9ddfN1/7+vpaXcKbG95///10z6AuX77c6r7DXr16qXbt2jb1m/IsYPKZNRcXF4WEhGS/2FwWGBhodUZzwoQJVpda5tXPzCuvvGL+R9PNmzfVtWtX/fzzz1a/F+Lj4/Xtt9+qT58+knIv+Ht7e+u5554zX3/zzTfp/ifOwYMHFRwcbP5OrVSpklV4BYB0GQCQDceOHTMkmY9p06alapOUlGS0a9fOql3jxo2Nb775xli9erWxePFi44033jDKlClj1ebbb7/NcNu9e/e2ah8QEGB06dLF6NWrl/nYs2eP2f7atWuGr6+v2d7V1dV49tlnjT/++MNYs2aNMWfOHGPw4MGGi4uLIcno2LGj4efnZ7YPDQ1Ns45p06aZbdq0aZODTzO1NWvWGN7e3lb76efnZ7z44ovGnDlzjLCwMOPPP/80Jk+ebAQFBRkWi8Wq7csvv5zpNsaMGWO2Hzx4sM21RUVFWX0+kowePXoYP//8sxEeHm78+uuvRkhIiOHs7GxIMh566CGrthl56623rNqWKFHCeOyxx4wff/zRWLVqlREeHm78/vvvxoQJE4wHHnjA8PDwMCQZFSpUSLO/7Byj0NBQq8/8qaeeMv73v/8ZS5YsMdatW2csWbLE+Pjjj40GDRpY1Tpp0iSbP8P0+Pv7m/3169fPfP7AAw8Ys2bNMsLDw4158+YZjzzyiOHk5GQu9/b2Nk6ePGnzdq5evWp4eXlZ1d+7d+8c15+W239XpPd9SsvSpUsz/d2Q2z8zhmEYy5YtM9zc3Kz6LVu2rHH//fcbLVq0sPpujh492mjTpo35+pdffkmzz5Q/V/7+/ulu+/r160adOnWstt22bVvjhx9+MMLCwoyFCxcaI0eONEqUKGEud3JyMpYsWZJun9n5rqfcp7R+vwMovAiAALLFlgBoGIYRExNjBAYGWrXN6PHxxx/btO0qVapk2M/tf2SuWrUq1R90aT3q1KljXLhwweoPcXsEQMMwjD179hj33HOPzZ+dJMPT09P4+uuvbeo/uwHQMAxj3759Rrly5TKtp23btsbBgwdtDoCGYRgTJ040w6Otj7wKgLY+nn76aSMxMTErH2Gabv+5e+SRRzLdtoeHh7F+/fosb+u5556z6mfRokU5rj8tOQmAhmEYTZo0MdetWrWqcfPmzVRtcvNnJtmiRYuMsmXLZtjH8OHDjZs3bxpNmzY13/vrr7/S7M/WAGgYhnHmzBmjXr16Nu2Hq6urMWvWrAz7IwACSIlLQAHkqVKlSmnFihWaPHmy1b14t2vZsqXWr1+vF198MdM+q1atqr///lvjx49X69atVb58+UwnTW7btq3CwsJUv379NJeXKFFCzzzzjLZs2VJghlGvV6+etm/frmnTpqlp06YZTmReuXJljRw5UocPH9azzz6b57XVrl1bu3btUnBwcJp1lSxZUi+99JKWLVuWao7FzIwcOVJ79uxR//79VaxYsQzb3nXXXXrllVcUFhaWpW1kpH79+ho7dqwaN26c5n2oKd17771asGCBpkyZkqWJ5m01c+ZMffTRRypTpkyay4OCgrRjx45MpzZJS4MGDcznlStXVufOnbNdZ1568803zefHjx/XzJkzU7XJi5+Zbt26af/+/XrnnXd07733ytvbWyVKlFDNmjX16KOPau3atZo8ebJcXFx04cIFc72yZctmbQfTULFiRW3evFljxoyRj49Pmm2cnJzUtWtX7dy5U/3798/xNgE4DothZOFudwDIAcMwtHXrVu3Zs0cXL16Uu7u7fH191apVK1WpUiXfati2bZu2bdumyMhI+fj4yM/PT4GBgRnOn1YQXLhwQZs3b9a5c+cUEREhDw8PlS9fXnfddZfuueceu9V1+vRphYaG6vTp0/Lw8NAdd9yhtm3b5srneePGDa1fv15Hjx7VpUuXJN2aLLt69eqqX7++KlWqlONtZOTKlSvatWuXDh8+rIsXLyouLk4lS5ZU5cqV1bhxY1WrVi1Pt58sPj5eq1ev1rFjxxQdHS1fX1/df//9qlmzZrb7bN26tdauXSvpVsjKbECfwiK/f2YiIiLM/zRydnZWTEyM1fyQOZWQkKANGzbowIEDunTpkjw8PFSpUiUFBgbmStgE4HgIgAAAOJgDBw6YA8Y4OTnpyJEjqlq1qn2LKqQ+/vhjvfzyy5JunRHesWOHnSsCgIxxCSgAAA7mo48+Mp937tyZ8HcbW/9v/J9//rGaq7MgjaIKAOkhAAIA4EDmz59vNXVH8tkr/H8rVqxQly5d9Ouvv+rKlSupll+5ckVfffWVWrZsaS738/MjAAIoFFzsXQAAAMg7e/fu1ZtvvqmkpCQdO3ZMe/fuNZd17drVap5M3JKUlKSlS5dq6dKlcnJyUs2aNeXr6ytnZ2dFRERo//79SkhIMNsXK1ZMP/74ozw9Pe1YNQDYhgAIAEARFhERoT/++CPV+35+fvruu+/sUFHBl3JE16SkJB08eFAHDx5Ms2316tU1c+bMbI3ECgD2QAAEAMBBuLi4qEqVKurevbveeustlS9f3t4lFUgdO3bU1q1btXjxYm3cuFEHDx7U+fPndf36dZUqVUrlypVTkyZN1LVrV/Xv318uLvw5BaDwYBTQNCQlJenMmTMqVaqULBaLvcsBAAAAYCeGYSg2NlaVKlXKkzlf8xv/ZZWGM2fOyM/Pz95lAAAAACggTp06lW/zFuclAmAaSpUqJenWQeaGbgAAAMBxxcTEyM/Pz8wIhR0BMA3Jl316enoSAAEAAAAUmVvDCv9FrAAAAAAAmxAAAQAAAMBBEAABAAAAwEEQAAEAAADAQTAITAZavzlLzu7F7V0GAAAA4FC2fzzI3iUUWZwBBAAAAAAHQQAEAAAAAAdBAAQAAAAAB0EABAAAAAAHQQAEAAAAAAdBAAQAAAAAB0EABAAAAAAHwTyAAAAAAAqk6OhoLVy4UIsXL9b58+cVHR0twzDytYakpCS5urqqdevWcnIquOfP3N3d5ePjo/r166tv375q1KiRLBZLqnYWI78/wUIgJiZGXl5euvv5KUwEDwAAAOSzBcPa6Pnnn9eyZcsUHx+v++67T9WrV5eXl5ecnZ3tXV6BdP36dV2+fFnr169XRESEqlatquHDh2vkyJFWQZAzgAAAAAAKjLjoCAUGBsowDE2YMEF9+vSRn5+fvcsqNBISEhQeHq6ZM2dq1KhRunz5st59910zBBIAAQAAABQI8bGXdfTXCaroU1KhoaG644477F1SoePi4qJ27dqpXbt2qlu3rl5++WW5uLhozJgxkhgEBgAAAEABEbE7TE43rxP+cslLL72kV155RR988IFiYmIkEQABAAAAFACGYSj28DY9EBxM+MtFQ4cOVXx8vBYuXCiJAAgAAACgALgRcVpXL55Wv3597V1KkeLn56dmzZpp3rx5kgiAAAAAAAqAK2cOycnJSR06dLB3KUVOly5dtG7dOkkEQAAAAAAFQOKNK/L08pa7u7u9SylyKlSooKioKCUlJREAAQAAANhf0s04eXh42LuMIqlUqVJKSkrSjRs3CIAAAAAACoaUE5Yj9zARPAAAAIBCLSYmRosXL9bWrVu1bds2nT59WhcvXtT169fl7e2tOnXqqGvXrnriiSdUpkyZNPu4ceOGli1bppUrV2rLli06dOiQYmNjVapUKd15553q1KmTnn76aVWsWNGmmq5du6avvvpK8+bN0+HDhxUfHy8/Pz9169ZNw4cPz3B00wsXLmjJkiXaunWrduzYobNnzyoiIkLx8fEqXbq0GjRooN69e2vQoEE5OlNqMQzDyPbaRVRMTIy8vLx09/NT5Oxe3N7lAAAAAEXemXW/yuX03zp18oRN7VeuXGnTgDFly5bVTz/9pE6dOlm9v3v3bt1///2KjY3NcP1SpUpp6tSp6tevX4btjhw5om7duunff/9Nc7mXl5d++eUXde3aNc3lU6dO1ZAhQzLchiT5+/tr/vz5atSoUaZtk82aNUsDBgzQ1atXOQMIAAAAoHDy8/NTUFCQGjVqJD8/P1WsWFFJSUn677//9Ouvv2rBggWKiIhQz549tXXrVjVo0MBcNyYmxgx/LVu2VPfu3dW4cWOVKVNGFy9e1IIFCzR16lTFxsZqwIABKlWqlLp06ZJmHVeuXFH37t3N8DdkyBD1799fxYsXV2hoqMaPH6/o6Gj17dtXGzdutKojmcViUa1atRQYGKh7771XlStXVsWKFXXjxg2dOHFCP/30k5YtW6YTJ06oQ4cO+ueff2w+M2m1Hc4ApsYZQAAAACB/ZfUMYGJiopydnTNs8/vvvys4OFiS9MADD2j+/Pnmsg0bNmjy5MkaM2aM6tSpk+b6f/zxh4KDg2UYhmrUqKFDhw6leZ/i2LFj9c4770iSPvroI7300ktWyzdu3KjWrVsrISFBQUFBWr16dao+EhIS5OKS8fm5SZMm6YUXXpAkjRo1Sp9++mmG7ZOlPAPIIDAAAAAACp3Mwp8k9e7dW3fddZckac2aNVbLWrRooTlz5qQb/iSpV69eeuCBByTdusRz165dqdrcvHlTkydPliTVrl1bo0ePTtWmefPmeuKJJyRJoaGh2r59e6o2mYU/SRo2bJhKliyZ5v7YigAIAAAAoMhKHjDlxo0b2Vo/KCjIfH7kyJFUy8PCwhQVFSVJGjx4sJyc0o5YISEh5vMFCxZkqxYXFxdznsTs7g8BEAAAAECRtH//fvOsXfKZwKyKi4szn6cV7tauXWs+b9OmTbr9NG7c2Ayj69aty1YtK1as0KVLlyRlf38IgAAAAACKjGvXrunQoUP67LPPFBQUpMTEREnSiBEjstVfeHi4+Tyt0LV///4MlydzcXFRjRo1Uq2TmdjYWO3bt09jx45Vnz59zPeHDx9ucx8p5WsAnDJlikqVKqWEhATzvStXrsjV1VWtWrWyart27VpZLBYdPHgw29sLCwuTxWIxT8kCAAAAKHqmT58ui8Uii8UiDw8PBQQEaPTo0Tp//rwk6cUXX9TAgQOz3O/ff/+tv/76S5JUt27dNO8XPHXqlKRbl5p6e3tn2J+fn58k6eLFi1ZnFm83duxYc388PT1Vt25dvfPOO4qNjZWzs7MmTZqUKj/ZKl8DYFBQkK5cuaJt27aZ761du1a+vr7aunWrrl27Zr4fFhamSpUqKSAgID9LBAAAAFBE3HPPPdq0aZM+/vjjNEfvzEhcXJyefPJJ8wziBx98kGa75KkkkgdnyUjKCdyvXLmSpXokqV27dtq9e3e2z2ZK+RwA77zzTlWqVElhYWHme2FhYerVq5dq1KihDRs2WL0fFBSk+Ph4vfzyy6pcubI8PDzUtGlTq/VPnDihHj16yMfHRx4eHqpbt64WL16s48ePmzds+vj4yGKxWN14CQAAAKBo6N27t/bs2aM9e/Zoy5YtmjVrloKDg7Vr1y4NHDhQixYtynKfw4YNM09cDR48WD179kyzXfJgLG5ubpn2mTyAiyRdv3493XbPPfecuT+bNm3StGnTFBQUpFWrVunhhx/W5s2bs7IrVvL9HsDAwECFhoaar0NDQxUYGKg2bdqY78fHx2vjxo0KCgrSY489pvXr12v27NnavXu3+vbtq86dO+vQoUOSpKFDhyouLk5r1qzRnj17NGHCBJUsWVJ+fn7mPB///vuvzp49aw7Peru4uDjFxMRYPQAAAAAUDt7e3qpXr57q1aunJk2aqH///lqwYIF+/PFHHT16VL169dL06dNt7m/8+PGaOnWqJKlRo0b66quv0m1brFgxSbcyTGZSXvZZvHj6842XL1/e3J+mTZsqJCREq1ev1rhx47R7924FBgZq+fLltu6OFbsEwPXr1yshIUGxsbHauXOnWrdurTZt2phn9jZt2qTr168rMDBQs2bN0rx589SqVSvVqFFDL774ou6//35NmzZNknTy5Em1bNlS9evXV/Xq1dW9e3e1bt1azs7OKl26tKRbH6Cvr6+8vLzSrGn8+PHy8vIyH8nX5gIAAAAovB599FH17dtXSUlJGjZsmCIjIzNd59tvv9Xrr78u6dYVjEuWLLG6dPN2pUqVkmTbJZ1Xr141n9tyyejt3njjDTVt2lQ3btzQkCFDrMZWsVW+B8CgoCBdvXpVW7du1dq1axUQEKDy5curTZs22rp1q65evaqwsDDdcccd2rFjhwzDUEBAgEqWLGk+wsPDzTk4hg8frnHjxqlly5YaM2aMdu/eneWaXnvtNUVHR5uP5Bs5AQAAABRuvXr1knQrfC1ZsiTDtrNmzdJzzz0nSfL399fKlStVrly5DNepUqWK2X9mg08m54xy5cpZXQ6aFcmXop48eVJbtmzJ8vr5HgBr1qypKlWqKDQ0VKGhoeZcGb6+vqpWrZrWr1+v0NBQtW3bVklJSXJ2dtb27du1a9cu87F//37zcs4nn3xSR48e1aOPPqo9e/aocePG+uKLL7JUk7u7uzw9Pa0eAAAAAAq/lAHuxIkT6bZbuHChBg0apKSkJFWsWFGrVq0yw11GUo4MeuDAgXTbJSQkmCexateubUvpabJ1f9Jjl3kAg4KCFBYWprCwMAUGBprvt2nTRsuWLdOmTZsUFBSke++9V4mJibpw4YJq1qxp9fD19TXX8/Pz0zPPPKMFCxZo9OjR+u677yT9/xsxk0fuAQAAAOBYTp8+bT5P77LLVatWqV+/fkpISFCZMmW0YsUKc86+zNx///3m85RzBt5u27Zt5iWgLVu2tKnvtNiyPxmxWwBct26ddu3aZZ4BlG4FwO+++043btxQUFCQAgICNHDgQA0aNEgLFizQsWPHtHXrVk2YMEGLFy+WJI0cOVLLli3TsWPHtGPHDq1evdpM1P7+/rJYLFq0aJEuXryYraFWAQAAABRe8+bNM5/Xr18/1fINGzaoV69eiouLk6enp5YtW6a6deva3H9gYKA51siMGTNkGEaa7VIOQhMcHGxz/yklJSWZA11KUr169bLch90C4PXr11WzZk1VqFDBfL9NmzaKjY1VjRo1zIFYpk2bpkGDBmn06NG688471bNnT23evNlcnpiYqKFDh6p27drq3Lmz7rzzTn399deSpMqVK+udd97Rq6++qgoVKmjYsGH5v7MAAAAAct306dPNKRjSM3HiRPPEUdWqVa3O1knSrl271K1bN129elUeHh5avHixGjVqlKU63NzcNHz4cEnS/v379cknn6Rqs3HjRn3//feSbmWeJk2apGrz3XffZXjlYlJSkkaPHq29e/dKunXmsVq1almqVZIsRnoR1YHFxMTIy8tLdz8/Rc7u6Q/PCgAAACB3nFn3q1xO/61TJ227r61q1aqKjY1Vnz59dP/996tGjRoqWbKkYmNjtWfPHv38889av369pFsh7a+//lL79u3N9Y8cOaIWLVrowoULkm6FxZTL01K+fHmVL18+1fuxsbFq3LixDh48KEl66qmn1L9/fxUvXlyhoaH64IMPdOXKFRUvXlwbNmzQPffck6oPi8WiypUr68EHH1SzZs3k7++vEiVKKDIyUjt37tT06dPNAS89PT21bt26NM9opmXWrFkaMGCArl69SgBMCwEQAAAAyF/ZCYC2DIJSpUoV/fDDD+rQoYPV+9OnT9djjz2WpRrHjBmjsWPHprns8OHD6tq1qzlf+e08PT31888/q3v37mkut1gsNtVQu3Zt/fTTT2rYsKFN7SXrAOhi81oAAAAAUECsWrVKK1euVGhoqPbv36/z58/r0qVLKlasmCpUqKB77rlH3bt3V79+/VSiRIk8r6dmzZrauXOnvvrqK82bN0+HDx9WfHy8/Pz81LVrV40YMUL+/v7prr97926tXr1aYWFhOnTokM6fP6+oqCiVKFFClSpVUsOGDRUcHKxevXrJ1dU123VyBjANnAEEAAAA8ldWzwDCdinPANplEBgAAAAAQP4jAAIAAACAgyAAAgAAAICDIAACAAAAgIMgAAIAAACwP4uz4uPj7V1FkZT8ubq4uBAAAQAAANifS7ESiomJtncZRVJkZKRKlCghNzc3AiAAAAAA+3PzKqcb16/r4MGD9i6lyNm5c6eqVasmiUtAAQAAABQAnv715OJeTPPmzbN3KUVKXFyc/vjjD/Xp00cSARAAAABAAeDk6qZS1e7WL7NmyzAMe5dTZKxYsULR0dHq27evJAIgAAAAgAKidJ2W2vfPXr322muEwFxw9OhRDR06VPfee6/q1q0riQAIAAAAoIDwqn63qgQN0IQJE/TSSy/p2rVr9i6p0Nq9e7eCgoLk5uamP//8UxaLRZJkMYjWqcTExMjLy0t3Pz9Fzu7F7V0OAAAA4FAerXxZL7zwgkqUKKFu3brpgQceUPXq1eXl5SVnZ2d7l1fgGIah69evKzIyUmvWrNG8efO0Z88e1axZU2FhYapcubLZlgCYBgIgAAAAYD/bPx6kw4cPa968eZo3b5527txp75IKjZIlS6pHjx7q16+fOnXqpOLFrfMMATANBEAAAADAfrZ/PMjq9dmzZ3XhwgVFR0crKSkpX2u5evWqunfvrkWLFsnDwyNft50VxYoVk4+Pj/z9/VWsWLF027nkY00AAAAAkGUVK1ZUxYoV7bLtmJgYSVKrVq3k6elplxpyE4PAAAAAAICDIAACAAAAgIMgAAIAAACAgyAAAgAAAICDIAACAAAAgIMgAAIAAACAg2AaiAysGfdwkRjqFQAAAAAkzgACAAAAgMMgAAIAAACAgyAAAgAAAICDIAACAAAAgIMgAAIAAACAgyAAAgAAAICDIAACAAAAgIMgAAIAAACAgyAAAgAAAICDIAACAAAAgIMgAAIAAACAgyAAAgAAAICDIAACAAAAgIMgAAIAAACAg3CxdwEF2akPm6lUMWd7lwEAAIBC4o6399i7BCBDnAEEAAAAAAdBAAQAAAAAB0EABAAAAAAHQQAEAAAAAAdBAAQAAAAAB0EABAAAAAAHQQAEAAAAAAfBPIAAAABALouLi9OKFSv022+/6eTJk4qKilJiYqK9yyqQXF1d5e3trerVq+uBBx5QUFCQXFyIKXmFTxYAAADIJVevXtWIESM0b948xcTE6K677lL9+vVVrVo1ubq62ru8Aik+Pl6RkZFatmyZpkyZojJlymjgwIH6+OOP5ebmZu/yihwCIAAAAJALrsUn6dGuXbVjxw6NGjVK/fr1U926de1dVqFhGIZ27NihuXPnatKkSTp58qTmzJlDCMxlBEAAAAAgh+ISkhTy8yn9E3FSy5YtU4sWLexdUqFjsVjUqFEjNWrUSG3atFFwcLAeeughLViwQBaLxd7lFRkMAgMAAADkUPjhK9p8PFZ//vkn4S8XdO3aVTNnztTvv/+uLVu22LucIoUACAAAAOTQX//EqG6duxQYGGjvUoqMPn36qEKFCpo7d669SylSCIAAAABADty4maSVB6+q30MP27uUIsXZ2Vl9+vTRvHnzZBiGvcspMgiAAAAAQA78e+GGrty4qS5duti7lCKnS5cuOnXqlE6ePGnvUooMAiAAAACQA1HXb83vV6FCBTtXUvQkf6aRkZF2rqToIAACAAAAOXAtPkmSVLJkSTtXUvQkf6ZXrlyxcyVFBwEQAAAAyAVMVZD7+ExzHwEQAAAAyGc7duzQBx98oC5dusjPz0/u7u4qWbKkAgICFBISorVr19rc14kTJ/Tqq6+qUaNG8vb2lqurq0qXLq0WLVrovffe08WLF7NV45IlS2SxWMzH2LFjM13nypUrmjRpkoKCglSuXDm5ubnJ09NT9evX17Bhw/TPP/9kqxbkHiaCBwAAAPJRmzZttGbNmlTvx8fH69ChQzp06JBmzJihRx99VFOnTpWbm1u6ff3yyy8aMmSIrl27ZvV+ZGSkNm7cqI0bN2ry5MmaO3eu2rZta3ONV69e1bPPPmv7TknavXu3evbsqRMnTli9f/PmTe3du1d79+7Vt99+qw8//FCjR4/OUt/IPZwBBAAAAPLR6dOnJUmVKlXSiBEj9Ouvv2rLli3auHGjPvvsM1WuXFmSNHPmTIWEhKTbz8aNGzVo0CBdu3ZNTk5Oeuyxx8yJ03/99Vf16NFDknTp0iX17NlTx48ft7nGt956SydOnFD58uVtah8dHa3OnTub4a9169aaNWuWNm/erL/++ksjR46Uq6urEhIS9OKLLzK3nx0RAAEAAIB8dNddd2nOnDk6efKkJk2apD59+qhJkyZq1qyZXnjhBe3atUsBAQGSpFmzZqV7OegHH3ygxMRbI5B+8cUX+uGHH9SrVy81adJEffr00cKFCzVq1ChJt87offbZZzbVt2PHDn3++edyd3fXuHHjbFpn6tSpOnv2rCSpb9++Cg8PV//+/XXfffepa9eumjhxon799Vezva39IvcRAAEAAIB8tGjRIvXr10/Ozs5pLi9btqw+/fRT83XK4JTS+vXrJUllypTRc889l2abt99+23y+YcOGTGtLTEzUkCFDlJiYqNdff121atXKdJ2UtUi3zh6mpWfPnrr33nslSXv27FFsbKxNfSN3EQABAACAAiYwMNB8fuTIkTTbxMfHS5KqVauWbj9eXl4qW7asJCkuLi7T7U6cOFE7duxQQECAXnnlFZvrTa5FkqpXr55uuxo1aqS5DvIPARAAAAAoYFKGIyentP9kT75M9NixY+n2ExMTo4iICKv26Tl+/LjGjBkjSfr666/l7u5uc70p+z569Gi67ZLDbOnSpVWmTBmb+0fuIQACAAAABUx4eLj5/K677kqzzdNPPy3p1iAvU6ZMSbPNe++9l6p9ep599lldu3ZNAwcOVLt27bJU75NPPmle0vr++++n2eavv/7Szp07baoFecfuATAkJMRqfpHkR+fOnXPcd1hYmCwWi6KionJeKAAAAJAPkpKS9OGHH5qv+/Xrl2a7J598UgMHDpQkDR06VEOGDNGff/6pbdu2acGCBXrggQf0ySefSJJeeeUVdezYMd1t/vLLL1q6dKm8vb2t7j+0VZ06dTR58mQ5OTlpzpw5atu2rebMmaOtW7dqyZIlGj16tB544AFJUvv27fX6669neRvIHQViHsDOnTtr2rRpVu9l5ZQzAAAAUFRMnDhRW7ZskSQFBwercePGabZzdnbWTz/9pJ49e+rDDz/U1KlTNXXqVKs2QUFBevXVVzMMf5cvX9YLL7wgSRo/frwqVKiQrbqHDh2qxo0b66OPPtKCBQsUGhpqtbxGjRp69dVXFRISIheXAhFDHJLdzwBKt8Ker6+v1cPHx0eS9Nlnn6l+/fry8PCQn5+fnnvuOV25csVc98SJE+rRo4d8fHzk4eGhunXravHixTp+/LiCgoIkST4+PrJYLBnOowIAAADYW3h4uF599VVJUvny5fXNN99k2P7AgQP65ZdftGfPnjSXb9y4UT/++KM5RUNaXnzxRV24cEFNmzbVU089le3aY2Nj9eOPP2rlypVpLj969KhmzZqlrVu3ZnsbyLkCEQAz4uTkpM8//1x79+7VjBkztHr1ar388svm8qFDhyouLk5r1qzRnj17NGHCBJUsWVJ+fn6aP3++JOnff//V2bNnNXny5DS3ERcXp5iYGKsHAAAAkJ/++ecfBQcHKyEhQe7u7po7d26GZ+PWrl2r5s2b648//lDlypU1c+ZMnTt3TvHx8Tp16pS++uorFS9eXD///LPuu+8+7d+/P1UfYWFhmjZtmpydnTVlypR0B5zJzLlz59S8eXN9/fXXSkhI0Pjx43XkyBHFx8fr0qVL+u2331S3bl2tXr1aQUFB6U5tgbxXIALgokWLVLJkSatH8g2rI0eOVFBQkKpVq6a2bdvqvffe09y5c811T548qZYtW6p+/fqqXr26unfvrtatW8vZ2VmlS5eWdOt/T3x9feXl5ZXm9sePHy8vLy/z4efnl/c7DQAAAPyfY8eOqWPHjoqMjJSzs7NmzZqlNm3apNs+Li5ODz/8sKKiouTr66tNmzbpkUceUYUKFeTq6qoqVaroueee09q1a1WsWDH9999/GjRoUKo+kgdjGT58uO65555s1z9s2DD9888/slgsWrRokV599VVVr15drq6uKl26tHr37q2NGzeqdu3aiouLU0hIiM6fP5/t7SH7CsTFt0FBQalObyeHt9DQUH3wwQfat2+fYmJilJCQoBs3bujq1avy8PDQ8OHD9eyzz2r58uVq3769+vTpowYNGmRp+6+99ppGjRplvo6JiSEEAgAAIF+cOXNG7du315kzZ2SxWPTDDz8oODg4w3WWLl2q06dPS5Kef/55+fr6ptmubt26euSRRzR16lRt27ZNf//9t+6++25J0oIFC3Tw4EG5uLioTp06mj17dqr19+3bZz7fu3ev2aZp06bm/IORkZH67bffJN0a4CX5NqzblSxZUm+88YYeeeQRXb16VbNnz9aIESMy3E/kvgIRAD08PFSzZs1U7584cUJdu3bVM888o/fee0+lS5fWunXr9MQTT+jmzZuSbo1+1KlTJ/31119avny5xo8fr08//VTPP/+8zdt3d3dn0BkAAADku4iICHXo0MGcO++LL75IdaYuLSkv52zYsGGGbRs1amQODnPgwAEzACZPDJ+QkKAhQ4Zkus358+ebt1hNmzbNDID//vuvkpKSbK4l2YEDBzLdJnJfgbgEND3btm1TQkKCPv30UzVr1kwBAQE6c+ZMqnZ+fn565plntGDBAo0ePVrfffedJMnNzU2SlJiYmK91AwAAAJmJjo5Wp06dzLNsH374oYYOHWrTuilH0UxISMiwbfKJk9vXyy0FqRZkrkAEwLi4OJ07d87qERERoRo1aighIUFffPGFjh49qpkzZ6aa5HLkyJFatmyZjh07ph07dmj16tWqXbu2JMnf39+8DvnixYtWo4cCAAAA9nLt2jV169ZNO3bskCS98cYbeuWVV2xeP/nsm3RrMJiMpJxUPuV6ISEhMgwjw0fKqRzGjBljvp9ydP2qVavKYrHkqBbknwIRAJcuXaqKFStaPe6//37dc889+uyzzzRhwgTVq1dPP//8s8aPH2+1bmJiooYOHaratWurc+fOuvPOO/X1119LkipXrqx33nlHr776qipUqKBhw4bZY/cAAAAAU3x8vIKDg7V+/XpJ0ogRIzRu3Lgs9dGuXTuVKFFCkvTNN9+kOw3EkiVLzPvzKleunKOBXtJTtmxZNWvWTJK0ZcsWzZgxI812J06c0Pvvvy9Jslgs6tatW67XgsxZDMMw7F1EQRMTEyMvLy/tfa22ShVztnc5AAAAKMCW7IvWM3NO6fLly+Zc1hnp06ePFixYIElq27atJk2aZJ5BS4ubm5sCAgJSvf/ee+/p7bfflnRrgJXnn39eHTp0kI+Pj86fP68//vhD3333nXlZ5syZM/XII49kad/CwsLMQV3GjBmjsWPHptuuffv2SkxMlMVi0SOPPKJ+/fqpSpUqio2NVXh4uCZNmqRLly5Jkp544olUk9an5cCBA6pdu7bWrl2r+++/P0u155bkbBAdHS1PT0+71JCbuPAWAAAAyEfJ4U+SVq9enekI9v7+/jp+/Hiq9998801dvnxZkydP1pUrVzR+/PhUV8tJkqurqz744IMsh7+sCAwM1IwZM/T000/r6tWrmjlzpmbOnJlm2/79+5tX7CH/EQABAACAQshisWjixInmNA/r1q3TiRMndO3aNZUsWVI1a9ZUmzZt9PTTT6d5BjG3DRw4UG3atNH//vc/rVy5Uv/++69iYmLk7u6uKlWqqFmzZho8eHC600QgfxAAAQAAgHyU23dgNWrUyGp6hdwUGBiYpXqrVKmid999V++++26e1IOcKxCDwAAAAAAA8h4BEAAAAAAcBAEQAAAAABwEARAAAAAAHAQBEAAAAMgBF6dbc/jFx8fbuZKiJ/kzdXFh7MrcQgAEAAAAcsCzmLMkKSoqyr6FFEGRkZGSJB8fHztXUnQQAAEAAIAc8PNxlSTt3LnTzpUUPbt27ZKbm5sqVapk71KKDAIgAAAAkAOVvNx0t19JzZs7x96lFDnz5s1Tx44dVapUKXuXUmQQAAEAAIAc6nqXhxYvXqzY2Fh7l1Jk/Pfff1q/fr369etn71KKFAIgAAAAkEPd63nJSErUww8/rLi4OHuXU+jFxsaqf//+8vLyUs+ePe1dTpFCAAQAAAByqIq3m6b2r6KVK1eqT58+ioiIsHdJhdaZM2fUpUsX7dmzR8uXL5eXl5e9SypSGE8VAAAAyAWta5bSwoX/U8+ePeXr66u2bduqb9++qlu3rnx8fOTq6mrvEguk+Ph4RUZGaseOHZo3b57WrVunUqVKacWKFbrvvvvsXV6RQwAEAAAAcknHjh114sQJ/fbbb5o7d66eeeYZJSUl2busQsHFxUUdOnTQ999/r169eql06dL2LqlIIgACAAAAuahChQp65pln9Mwzz+jy5cs6c+aMoqKilJCQYO/SCiRXV1f5+PiocuXKXO6ZDwiAAAAAQB4pXbo0Z7JQoDAIDAAAAAA4CAIgAAAAADgIAiAAAAAAOAgCIAAAAAA4CAIgAAAAADgIAiAAAAAAOAimgciA36ub5Onpae8yAAAAACBXcAYQAAAAABwEARAAAAAAHAQBEAAAAAAcBAEQAAAAABwEARAAAAAAHAQBEAAAAAAcBAEQAAAAABwEARAAAAAAHAQBEAAAAAAcBAEQAAAAABwEARAAAAAAHAQBEAAAAAAcBAEQAAAAABwEARAAAAAAHISLvQsoyDpM6SCX4nxEAAAgd6x/fr29SwDg4DgDCAAAAAAOggAIAAAAAA6CAAgAAAAADoIACAAAAAAOggAIAAAAAA6CAAgAAAAADoIACAAAAAAOgknuAAAA8ll8fLxWrFih3377TSdOnFBUVJQSExPtXVaB5OLiIm9vb1WvXl0PPPCAgoKC5Orqau+ygEKLAAgAAJBPrl27phdeeEFz585VVFSU7rzzTtWvX1/VqlUj1KQjPj5eUVFRWrlypb799luVLl1aAwYM0CeffCJ3d3d7lwcUOgRAAACAfJAYn6gePXpo8+bNeuGFF9SvXz/Vq1dPFovF3qUVCoZhaNeuXZo7d64mTpyoY8eOaf78+YRAIIsIgAAAAHksKSFJ/373r27+d1OLFy9W69at7V1SoWOxWHTvvffq3nvvVVBQkHr27Kk+ffpo4cKFcnJiWAvAVnxbAAAA8lj0v9GK+jdKv/32G+EvF3Ts2FGzZs3SX3/9pfXr19u7HKBQIQACAADksYhdEapRq4bat29v71KKjF69eqly5cqaO3euvUsBChUCIAAAQB5KSkhS9N5oPfzQw9zvl4ucnJz04IMPav78+UpKSrJ3OUChQQAEAADIQ9fPXVf81Xh16dLF3qUUOV26dNHZs2d19OhRe5cCFBoEQAAAgDyUcC1BklShQgU7V1L0JH+mkZGRdq4EKDwIgAAAAHkoMe7WBO8lS5a0cyVFT/JneuXKFTtXAhQeBEAAAIB8wP1/uY/PFMg65gEEAAAoYHbs2KGlS5dq7dq12rt3ry5cuCBXV1dVqlRJLVq00BNPPKFWrVpl2Mf+/fu1atUqbd26VXv27NGFCxcUEREhZ2dnVahQQU2aNNGAAQPUs2fPDIPUyZMn9ddffyksLEy7du3Sf//9p8TERJUtW1aNGjVS//791bdvX7m4pP9n5YULF7RkyRJt3bpVO3bs0NmzZxUREaH4+HiVLl1aDRo0UO/evTVo0CB5eHhk+3MDkDmLYRiGvYsoaGJiYuTl5aX7Jtwnl+JkZAAAkH2X91zWge8O6Pz58ypfvnym7du0aaM1a9Zk2u7RRx/V1KlT5ebmlubyRx55RD///LNN21uwYIFKly6datnbb7+tcePGKbM/Fxs3bqz58+frjjvuSHP51KlTNWTIkExr8ff31/z589WoUaNM20rSkSNHVLNmTa1evVpBQUE2rQNkVXI2iI6Olqenp73LyTHSDQAAQAFy+vRpSVKlSpXUt29ftWrVSnfccYcSExO1ceNGffrppzp9+rRmzpyphIQE/fLLL2n24+LioqZNm6ply5aqX7++fH19Va5cOUVGRurAgQP69ttvtXfvXoWHh6tHjx5au3atnJys7w46c+aMDMOQh4eHgoOD1a5dO9WqVUvFihXT/v379fnnn2vr1q3atm2b2rdvrx07dqR5r6PFYlGtWrUUGBioe++9V5UrV1bFihV148YNnThxQj/99JOWLVumEydOqEOHDvrnn39UsWLF3P9wAXAGMC2cAQQAALklq2cAu3fvrkGDBqlPnz5ydnZOtTwiIkItW7bUwYMHJUlr1qxJ83LQhISEDC/LTExMVL9+/bRgwQJJ0sKFC9WjRw+rNq+88orKlCmjZ599VqVKlUqzjwEDBpiTsb/77rt66623slyLJE2aNEkvvPCCJGnUqFH69NNPM2wvcQYQ+aOonQFkEBgAAIACZNGiRerXr1+a4U+SypYtaxWOfv311zTbZRa4nJ2d9fLLL5uv07rsdMKECXr55ZfTDH/JfXz99dfmZajZrUWShg0bZp49tOUSWADZQwAEAAAoZAIDA83nR44cyXY/KQdcuXHjRrb6KFOmjBo0aJDjWlxcXOTu7p6jWgBkjgAIAABQyMTHx5vPb79vLytmzZplPr/rrruy3U9cXFyOa1mxYoUuXbqU41oAZMxhAmDVqlU1adIke5cBAACQY+Hh4ebzrIaliIgIbdy4UU888YTGjx8v6dZZvIEDB2arlgsXLmj//v3ZqiU2Nlb79u3T2LFj1adPH/P94cOHZ6sWAJnLVgA8d+6cnn/+eVWvXl3u7u7y8/NTjx49tGrVqlwrLDAwUCNHjsy1/gAAAIqCpKQkffjhh+brfv36ZbpOYGCgLBaLLBaLypUrpxYtWuiHH36QYRgqXbq0FixYIG9v72zV8/HHHyshIcHmWsaOHWvW4unpqbp16+qdd95RbGysnJ2dNWnSpEznOASQfVke4vL48eNq2bKlvL299dFHH6lBgwa6efOmli1bpqFDh+rAgQN5UWeaDMNQYmKiTTcWAwAAFAUTJ07Uli1bJEnBwcFq3Lhxtvt6/vnn9eabb9o0OmlaNm/ebF5hVaVKFT333HPZrqVdu3b6/PPPVadOnWz3ASBzWT4D+Nxzz8lisWjLli168MEHFRAQoLp162rUqFHatGmTJCk6OlpPPfWUypcvL09PT7Vt21Z///232cfYsWN1zz33aObMmapataq8vLzUv39/xcbGSpJCQkIUHh6uyZMnm/9DdPz4cYWFhclisWjZsmVq3Lix3N3dtXbtWh05ckS9evVShQoVVLJkSTVp0kQrV67MpY8IAACgYAgPD9err74qSSpfvry++eYbm9abNm2a9uzZo927d2vNmjX67LPPVKtWLX311Vd64okndP78+SzXcv78eT344INKSEiQxWLRjBkzVKJEiUzXe+6557Rnzx7t2bNHmzZt0rRp0xQUFKRVq1bp4Ycf1ubNm7NcCwDbZSkAXr58WUuXLtXQoUOtRo1K5u3tLcMw1K1bN507d06LFy/W9u3b1bBhQ7Vr106XL1822x45ckS///67Fi1apEWLFik8PNy8nGHy5Mlq3ry5hgwZorNnz+rs2bPy8/Mz13355Zc1fvx47d+/Xw0aNNCVK1fUtWtXrVy5Ujt37lSnTp3Uo0cPnTx50qb9iouLU0xMjNUDAACgIPnnn38UHByshIQEubu7a+7cuapQoYJN61arVk316tVT/fr11apVK73wwgvavXu3unbtqkWLFqlJkyb677//bK4lNjZW3bp1M9f54IMP1LZtW5vWLV++vOrVq6d69eqpadOmCgkJ0erVqzVu3Djt3r1bgYGBWr58uc21AMiaLAXAw4cPyzCMDG/wDQ0N1Z49ezRv3jw1btxYtWrV0ieffCJvb2+ruWGSkpI0ffp01atXT61atdKjjz5q3kPo5eUlNzc3lShRQr6+vvL19bWaC+fdd99Vhw4dVKNGDZUpU0Z33323nn76adWvX1+1atXSuHHjVL16dS1cuNCm/Ro/fry8vLzMR8qwCQAAYG/Hjh1Tx44dFRkZKWdnZ82aNUtt2rTJUZ/FihXTtGnTVKJECZ06dcpqTsCM3LhxQ7169dL27dsl3Zq0PfmsZE688cYbatq0qW7cuKEhQ4aY9xUCyF1ZCoCGYUiSLBZLum22b9+uK1euqEyZMipZsqT5OHbsmNXcMFWrVrWaVLRixYq6cOGCTXXcfq371atX9fLLL6tOnTry9vZWyZIldeDAAZvPAL722muKjo42H6dOnbJpPQAAgLx25swZtW/fXmfOnJHFYtEPP/yg4ODgXOm7bNmyatmypSTpjz/+yDR0JSQkqF+/fgoNDZUkPfnkk1aT0udUz549JUknT54073MEkLuyNHpKrVq1ZLFYtH//fvXu3TvNNklJSapYsaLCwsJSLUs5upSrq6vVMovFoqSkJJvquP3y05deeknLli3TJ598opo1a6p48eJ68MEHrebIyYi7u7s58SgAAEBBERERoQ4dOujo0aOSpC+++EKDBg3K1W2UK1dOknTt2jVdvHhRFStWTLNdUlKSHn30Uf3555+SpIceekjffvttntQiSSdOnFCLFi1ytX8AWQyApUuXVqdOnfTVV19p+PDhqYJYVFSUGjZsqHPnzsnFxUVVq1bNdmFubm5KTEy0qe3atWsVEhJi/m/YlStXdPz48WxvGwAAwN6io6PVqVMn7du3T5L04YcfaujQobm+ndOnT5vPS5YsmW67p59+WrNnz5Ykde/eXTNnzszRxO85qQVA9mX5W/v1118rMTFR9913n+bPn69Dhw5p//79+vzzz9W8eXO1b99ezZs3V+/evbVs2TIdP35cGzZs0Jtvvqlt27bZvJ2qVatq8+bNOn78uCIiIjI8O1izZk0tWLBAu3bt0t9//60BAwbYfDYRAACgoLl27Zq6deumHTt2SLp1f9wrr7yS69s5ffq0Nm7cKEny9/e3uj0npVGjRmnq1KmSbk3X8Ouvv6a6miunkpKSNH/+fPN1vXr1crV/ALdkOQBWq1ZNO3bsUFBQkEaPHq169eqpQ4cOWrVqlb755htZLBYtXrxYrVu31uOPP66AgAD1799fx48ft3mkKkl68cUX5ezsrDp16qhcuXIZ3s83ceJE+fj4qEWLFurRo4c6deqkhg0bZnXXAAAA7C4+Pl7BwcFav369JGnEiBEaN25clvo4ePCgVq9enWGb6OhoPfzww+YtM48++mia7caOHauJEydKklq0aKE//vgjy7fOfPfddxle2ZWUlKTRo0dr7969kqT7779f1apVy9I2ANjGYiSP7AJTTEyMvLy8dN+E++RSnEnmAQBA9l3ec1kHvjug8+fP2zThep8+fbRgwQJJUtu2bTVp0qQMB+Bzc3NTQECA1XthYWEKCgrS3Xffrd69e6tRo0by9fWVi4uLzp07p/Xr1+v777/XuXPnJN0627Zp06ZUt/d88cUXGj58uCSpcuXKmjNnjry8vDKs/84770xzrIfKlSvrwQcfVLNmzeTv768SJUooMjJSO3fu1PTp07V7925Jkqenp9atW6f69etn+lkdOXJENWvW1OrVqxUUFJRpeyA7krNBdHS0PD097V1OjpFuAAAACpDk8CdJq1evVoMGDTJs7+/vn+7YB3///bf+/vvvDNfv1q2bpk2bluYczykvyTx9+rTuv//+DPuSbk1ZkdY4EKdPn9bkyZM1efLkdNetXbu2fvrpJ5vCH4DsIQACAAAUMS1btlR4eLhWr16tdevW6eTJkzp//ryuXbsmT09PVatWTU2bNtWAAQPMaSDy0u7du7V69WqFhYXp0KFDOn/+vKKiolSiRAlVqlRJDRs2VHBwsHr16pXr9xYCsEYABAAAKEBy4+4cV1dXtW7dWq1bt85RP2lN65Ud9evXV/369TVixIhc6Q9A9uXu2L0AAAAAgAKLAAgAAAAADoIACAAAAAAOggAIAAAAAA6CAAgAAJCHLM635vBLnnAduSf5M3VxYVxDwFYEQAAAgDzkUvxWOImKirJvIUVQZGSkJMnHx8fOlQCFBwEQAAAgD7mXdpck7dy5086VFD27du2Ss7OzqlSpYu9SgEKDAAgAAJCH3Lzc5FXdS3PmzrF3KUXOvHnz1L59e3l7e9u7FKDQIAACAADkMZ+7fbR8+XIuA81F586dU3h4uPr27WvvUoBChQAIAACQx8rcU0aGDPXv3183btywdzmF3tWrV/XQQw/Jw8NDvXv3tnc5QKFCAAQAAMhj7j7uChgSoDVr1qh37966ePGivUsqtM6dO6euXbtqx44dWrZsmcqUKWPvkoBChTFzAQAA8oH3nd76888/1aNHD1WsWFGBgYHq27ev6tevLx8fH7m6utq7xAIpPj5ekZGR2rVrl+bNm6c1a9bIw8NDy5YtU4sWLexdHlDoEAABAADySbt27XT8+HH99ttvmjdvnp577jklJSXZu6xCwcXFRe3atdPUqVPVu3dvlS5d2t4lAYUSARAAACAflS9fXk8//bSefvppRUZG6vTp04qKilJCQoK9SyuQXFxc5OPjoypVqsjLy8ve5QCFHgEQAADATnx8fJjEHEC+YhAYAAAAAHAQBEAAAAAAcBAEQAAAAABwEARAAAAAAHAQBEAAAAAAcBAEQAAAAABwEEwDkYEVz6yQp6envcsAAAAAgFzBGUAAAAAAcBAEQAAAAABwEARAAAAAAHAQBEAAAAAAcBAEQAAAAABwEARAAAAAAHAQBEAAAAAAcBAEQAAAAABwEARAAAAAAHAQBEAAAAAAcBAEQAAAAABwEARAAAAAAHAQBEAAAAAAcBAEQAAAAABwEC72LqAgW9e5izxc+IgAoChosybc3iUAAGB3nAEEAAAAAAdBAAQAAAAAB0EABAAAAAAHQQAEAAAAAAdBAAQAAAAAB0EABAAAAAAHQQAEAAAAAAfBJHcAAIcSFRWlhQsXavHixbpw4YKio6NlGIa9yyqQ3N3d5ePjowYNGqhv375q2LChLBaLvcsCAOQAARAA4BCOHTum559/XsuXL9fNmzfVtGlTVatWTQEBAXJ2drZ3eQXS9evXdenSJU2dOlUTJkxQ9erVNWLECA0fPtzepQEAsokACAAo8s7euK5BgYFycnLSxx9/rD59+qhKlSr2LqvQSEhIUGhoqGbOnKkRI0bo8uXLGjt2rL3LAgBkAwEQAFCkXYiL0wv//KOSlSopNDSU4JcNLi4u6tChgzp06KDatWvr9ddfl6urq9544w17lwYAyCIGgQEAFGkLz57RdWdnwl8uee211zR69GiNGzdOV65csXc5AIAsIgACAIoswzAUHhmpPn37Ev5y0dChQ3Xjxg0tWrTI3qUAALKIAAgAKLKOXL2qU1euqG/fvvYupUipVq2aGjdurHnz5tm7FABAFhEAAQBF1p6YGLm6uKhdu3b2LqXI6dKli9atW2fvMgAAWUQABAAUWbEJN+Xj5SVXV1d7l1LkVKhQQZGRkcyhCACFDAEQAFBkXU9MkoeHh73LKJJKlSqlmzdv6ubNm/YuBQCQBQRAAECRZrFY7F1CkcTnCgCFEwEQAID/c+HCBS1atEhvv/22unTporJly8pischisSgkJCRbfW7ZskXPPfecateuLU9PT5UsWVI1atRQt27d9Nlnn+nixYtprnflyhWtWbNGn3zyifr166dq1aqZtVStWjVLNcTExGjChAlq2bKlSpcuLXd3d91xxx3q27evli5dmq39AgAUTkwEDwDA/6lQoUKu9RUXF6dhw4bp+++/T3Wf3NGjR3X06FEtXrxY1atXV+/evVOt36NHD4WFheW4jo0bN6pPnz46e/as1funTp3SqVOn9OuvvyokJERTp06Vs7NzjrcHACjYCIAAAKTBz89PtWvX1vLly7O8bnx8vIKDg7VkyRJJUqtWrTRo0CDVrl1bLi4uOnHihP7+++8Mp1FIGRp9fHzUuHFjbdy4MUuTr//777/q0qWLoqOj5eTkpCeffFIPPvigypQpo2PHjumbb77RqlWrNH36dJUqVUqff/55lvcVAFC4EAABAPg/b7/9tpo0aaImTZqoQoUKOn78uKpVq5blfsaNG2eGv08++USjR4+2Wt60aVP169dP77//frqDqAwYMEBPPfWU7rvvPtWsWVOSVLVq1SwFwNGjRys6OlqS9P3331tdxtqwYUM98MADevzxxzV9+nR9+eWXGjx4sBo1apSVXQUAFDIEQAAA/s8777yT4z6OHj2qDz/8UJIUEhKSKvzdLr0pKp566qkc1REREaHFixdLklq2bJnmPYwWi0UTJ07UvHnzdPXqVX344YdM7g4ARRyDwAAAkIv+97//6ebNm7JYLHr77bftVse2bdvMy0i7dOmSbjtvb281a9ZMkrR48WJdu3YtX+oDANgHARAAgFyUfAatcePG5uWjSUlJ+u+//3Ts2DFdv349X+q4fPmy+TyzwW2Sl1+7dk3btm3L07oAAPZV5AJgWFiYLBaLoqKi7F0KAMDBXLx4UUePHpUkNW/eXDExMRo5cqTKli0rPz8/Va9eXZ6enmrTpo3++uuvPK3Fw8PDfJ58H2B6Ui7ft29fntUEALC/PAuAFy5c0NNPP6077rhD7u7u8vX1VadOnbRx48Zc20ZgYKBGjhyZa/0BAJATKcNT8eLF1bBhQ02ePFmRkZHm+wkJCVqzZo26d++uUaNG5VkttWvXNp+Hh4en2y4+Pl6bN282X588eTLPagIA2F+eBcA+ffro77//1owZM3Tw4EEtXLhQgYGBVpekAABQlKT8N27SpEk6cuSIWrRoofDwcF27dk2XL1/Wzz//rIoVK0qSJk6cqClTpuRJLQEBAWYI/Ouvv7R+/fo023366aeKiIgwX8fGxuZJPQCAgiFPAmBUVJTWrVunCRMmKCgoSP7+/rrvvvv02muvqVu3bpJu/Q9jr169VLJkSXl6eqpfv346f/682UdISEiqiXFHjhypwMBAc3l4eLgmT54si8Uii8Wi48ePm223b9+uxo0bq0SJEmrRooX+/fffvNhVAABMV69eNZ/HxcWpUaNGWrVqlVq3bq3ixYvLx8dHAwYMUHh4uHmJ5ttvv51n9wW+//77km7dg9i1a1d99dVXOnfunG7evKlDhw7phRde0BtvvCE3Nzdznfy6RxEAYB95EgBLliypkiVL6vfff1dcXFyq5YZhqHfv3rp8+bLCw8O1YsUKHTlyRA899JDN25g8ebKaN2+uIUOG6OzZszp79qz8/PzM5W+88YY+/fRTbdu2TS4uLnr88cfT7SsuLk4xMTFWDwAAsqpYsWJWr99///1U70lSrVq19Oyzz0q6dd/gypUr86Se4OBgffDBB7JYLIqJidGwYcNUsWJFubm5KSAgQJMmTVKxYsU0fvx4c51SpUrlSS0AgIIhTwKgi4uLpk+frhkzZsjb21stW7bU66+/rt27d0uSVq5cqd27d+uXX35Ro0aN1LRpU82cOVPh4eHaunWrTdvw8vKSm5ubSpQoIV9fX/n6+srZ2dlc/v7776tNmzaqU6eOXn31VW3YsEE3btxIs6/x48fLy8vLfKQMkgAA2CpleHJzc1NQUFC6bTt16mQ+t/Xfvux47bXXFBYWpi5duliFUVdXVwUHB2vnzp0KCAgw3/fx8cmzWgAA9pen9wCeOXNGCxcuVKdOnRQWFqaGDRtq+vTp2r9/v/z8/KyCVp06deTt7a39+/fnyvYbNGhgPk++1+LChQtptn3ttdcUHR1tPk6dOpUrNQAAHEvKf9cqVKhgdWllRm3T+/cpt7Ru3VqLFy9WdHS0jh8/riNHjig2NlYLFizQnXfeaf4HrXTr32MAQNGVp9NAFCtWTB06dNDbb7+tDRs2KCQkRGPGjJFhGLJYLKnap3zfycnJnMA22c2bN23etqurq/k8uc+kpKQ027q7u8vT09PqAQBAVtWqVcv89ycxMTHDtimXu7i45Gldydzc3OTv76/q1avL3d3dfH/dunXm86ZNm+ZLLQAA+8jXeQDr1Kmjq1evqk6dOjp58qTVmbZ9+/YpOjraHLGsXLlyOnv2rNX6u3btsnrt5uaW6T+wAADkF1dXVzVv3lySdP78eatBYW535MgR83nlypXzvLb0pLwHsVmzZtwGAQBFXJ4EwEuXLqlt27b66aeftHv3bh07dkzz5s3TRx99pF69eql9+/Zq0KCBBg4cqB07dmjLli0aNGiQ2rRpo8aNG0uS2rZtq23btunHH3/UoUOHNGbMGO3du9dqO1WrVtXmzZt1/PhxRUREpHuGDwCA/NKnTx9Jt87w/fHHH+m2W7Bggfm8VatWeV5XesaOHWteYTN06FC71QEAyB95Ngpo06ZNNXHiRLVu3Vr16tXTW2+9pSFDhujLL7+UxWLR77//Lh8fH7Vu3Vrt27dX9erVNWfOHLOPTp066a233tLLL7+sJk2aKDY2VoMGDbLazosvvihnZ2fVqVNH5cqVY/JaAIDdPf744ypfvrwk6fXXX7ea4ihZWFiYZs6cKUmqV6+eWrZsmSe13Lx5U+fOnUt3+ZQpU/T1119LuhVCBw4cmCd1AAAKDotx+412UExMjLy8vPRX8xbyyKf7MgAAue/bY8e02dlJR1LME5uRdevW6fDhw+briIgIvfTSS5Kkli1b6sknn7RqHxISkmY/c+bM0cMPPyzDMOTn56dXX31V9913n27cuKElS5Zo4sSJun79ulxcXBQWFpZmADx8+LDVvXnSrf/4vHTpksqUKaNPPvnEalnnzp3l6+tr9V5ERIQqVqyoXr16qVevXrrzzjslSYcOHdLMmTO1bNkySZK/v7/Cw8Pl7+9vw6d0y8yZMzVo0CDFxcVlONgNABR2ydkgOjq6SIwVQgBMAwEQAIqGrAbAkJAQzZgxw+b+M/on9KuvvtKoUaMUHx+f5vKSJUvqp59+Uq9evdJcPn36dD322GM21xIaGqrAwECr9yIiIlSuXLkM12vevLl++eUXVa1a1eZtSQRAAI6jqAVA0g0AAHlg6NChCgwM1FdffaUVK1bo9OnTcnZ2VvXq1dW5c2eNHDnSnKYor3h7e2vq1KlatWqVduzYoXPnzunGjRuqUKGCGjdurP79++vBBx9Mc2RuAEDRxBnANHAGEACKhqyeAYTtOAMIwFEUtTOA+ToNBAAAAADAfgiAAAAAAOAgCIAAAAAA4CAIgAAAAADgIAiAAIAiy9midKdhQM4kf67Ozs52rgQAkBUEQABAkVXSxUXRMTH2LqNIioyMlKenJwEQAAoZAiAAoMiqVKy4Yq9e1ZEjR+xdSpGzc+dOVatWzd5lAACyiAAIACiymvj4qJiLi3799Vd7l1KkXL9+XQsXLlSfPn3sXQoAIIsIgACAIqu4s7Oa+fho9i+/yDAMe5dTZCxbtkxXrlxR37597V0KACCLCIAAgCKtY7ny2rV7t9566y1CYC44fPiwnn/+eTVp0kR33XWXvcsBAGQRARAAUKS1KFNGz1Srpvfff1+vvfaarl27Zu+SCq1du3YpKChIJUqU0B9//GHvcgAA2WAx+O/QVGJiYuTl5aW/mreQh4uLvcsBAOSCrT176KWXXpKHh4e6d++uBx54QFWrVpWXlxcjWabBMAxdv35dly9f1po1azRv3jzt3btXAQEBCgsLU8WKFe1dIgDki+RsEB0dLU9PT3uXk2MEwDQQAAGg6GmzJlyHDh3SvHnzNHfuXP3999/2LqnQKFWqlHr27Km+ffuqU6dOKlasmL1LAoB8QwB0AARAACh62qwJt3p95swZXbx4UdHR0UpKSrJTVQVbsWLF5OPjI39/f0IfAIdV1AIg6QYA4JAqVaqkSpUq2bsMAADyFYPAAAAAAICDIAACAAAAgIMgAAIAAACAgyAAAgAAAICDIAACAAAAgIMgAAIAAACAg2AaiAzcv3RJkZjrAwAAAAAkzgACAAAAgMMgAAIAAACAgyAAAgAAAICDIAACAAAAgIMgAAIAAACAgyAAAgAAAICDIAACAAAAgIMgAAIAAACAgyAAAgAAAICDIAACAAAAgIMgAAIAAACAgyAAAgAAAICDIAACAAAAgIMgAAIAAACAgyAAAgAAAICDIAACAAAAgIMgAAIAAACAgyAAAgAAAICDIAACAAAAgIMgAAIAAACAgyAAAgAAAICDIAACAAAAgINwsXcBhcH169e1dOlS/fHHH/rvv/8UHR2txMTEHPfr7Owsb29vVa1aVcHBwWrfvr3c3NxyoWIAAAAASI0AmIGoqCgNHTpUv//+u65cuaL69eurdu3aqlGjhlxccv7R3bx5U5GRkVqzZo2mTp0qb29v9evXTxMnTlSJEiVyYQ8AAAAA4P8jAGagd+/eOn78uF555RX17dtXd955Z55sxzAM7d27V3PnztXEiRN15MgRLVy4kBAIAAAAIFdZDMMw7F1EQXPmzBndcccd8vLy0sqVK3Xvvffm27bXrFmjrl27qlmzZlqyZIlcXV3zbdsAAAAArMXExMjLy0vR0dHy9PS0dzk5xiAwafjzzz+VmJio5cuX52v4k6TWrVvrt99+06pVq7Rq1ap83TYAAACAoo0AmIbff/9dTZs2VaNGjeyy/fbt2ysgIEBz5861y/YBAAAAFE0EwNtERUVp1apVevjhh+1Wg8ViUd++ffX7778rPj7ebnUAAAAAKFoIgLfZtm2bbt68qS5duti1ji5duigyMlL79u2zax0AAAAAig4C4G0uX74sSapQoYJd60jefmRkpF3rAAAAAFB0EABvc/XqVUlSyZIl7VpH8vavXLli1zoAAAAAFB0EwHRYLBaH3j4AAACAoocAmAsuXLigRYsW6e2331aXLl1UtmxZWSwWWSwWhYSE2Ls8AAAAAJAkudi7gKLA3vcLAgAAAIAtOAOYy/z8/NSxY0d7lwEAAAAAqXAGMBe8/fbbatKkiZo0aaIKFSro+PHjqlatmr3LAgAAAAArBMBc8M4779i7BAAAAADIFJeAAgAAAICDIAACAAAAgIMocgEwJCREvXv3tncZAAAAAFDg5GkADAkJkcVi0Ycffmj1/u+//57jic6PHz8ui8WiXbt25agfAAAAAHAUeX4GsFixYpowYYIiIyNzrc/4+Phc6wsAAAAAHEWeB8D27dvL19dX48ePT7fN/PnzVbduXbm7u6tq1ar69NNPrZZXrVpV48aNU0hIiLy8vDRkyBBzmoV7771XFotFgYGBVut88sknqlixosqUKaOhQ4fq5s2bub5vAAAAAFCY5HkAdHZ21gcffKAvvvhC//33X6rl27dvV79+/dS/f3/t2bNHY8eO1VtvvaXp06dbtfv4449Vr149bd++XW+99Za2bNkiSVq5cqXOnj2rBQsWmG1DQ0N15MgRhYaGasaMGZo+fXqq/lKKi4tTTEyMYmJidP369VzZbwAAAAAoaPJlHsDg4GDdc889GjNmjL7//nurZZ999pnatWunt956S5IUEBCgffv26eOPP1ZISIjZrm3btnrxxRfN18ePH5cklSlTRr6+vlZ9+vj46Msvv5Szs7PuuusudevWTatWrdKQIUPSrG/8+PHM5QcAAACgyMu3UUAnTJigGTNmaN++fVbv79+/Xy1btrR6r2XLljp06JASExPN9xo3bmzzturWrStnZ2fzdcWKFXXhwoV027/22muKjo5WdHS0vvrqK5u3AwAAAACFSb4FwNatW6tTp056/fXXrd43DCPViKCGYaRa38PDw+Ztubq6Wr22WCxKSkpKt727u7s8PT3l6emp4sWL27wdAAAAAChM8uUS0GTjx4/Xvffeq4CAAPO9OnXqaN26dVbtNmzYoICAAKuzeLdzc3OTJKuzhAAAAACA9OXrRPANGjTQwIED9cUXX5jvjR49WqtWrdJ7772ngwcPasaMGfryyy+t7vdLS/ny5VW8eHEtXbpU58+fV3R0dF6XDwAAAACFWr4GQEl67733rC7xbNiwoebOnavZs2erXr16evvtt/Xuu+9aDQCTFhcXF33++ef69ttvValSJfXq1SuPKwcAAACAws1ipHXDnQObNm2aHn/8cSUmJsrJybZ8vG7dOh0+fNh8HRERoZdeeknSrQFtnnzySav2mYVbSTp//rx8fX21cOFC9ejRw/YdAAAAAJBrYmJi5OXlpejoaHl6etq7nBzL13sAi6qpU6dqxowZaS5bv3691q9fb/WeLQEQAAAAAHJbvl8CCgAAAACwDwJgLpg+fboMw7D5AQAAAAD2QAAEAAAAAAdBAAQAAAAAB0EABAAAAAAHQQAEAAAAAAdBALyNi8utmTHi4+PtWkfy9pPrAQAAAICcIgDextvbW5IUFRVl1zoiIyMlST4+PnatAwAAAEDRQQC8TfXq1SVJO3futGsdu3btkiRVrVrVrnUAAAAAKDoIgLepU6eOatasqblz59q1jnnz5qlly5by9fW1ax0AAAAAig4C4G0sFot69+6t+fPn2+0+wKioKC1btkz9+vWzy/YBAAAAFE0EwDQ8+OCDunLligYNGqSEhIR83faNGzfUv39/ubi4qE+fPvm6bQAAAABFGwEwDbVr15ZhGJo/f74eeeQRc0CWvHbx4kX17t1ba9as0aJFi1S5cuV82S4AAAAAx8AcAxmYNm2aHnvsMS1YsEAdOnTQgw8+qLvuukve3t5ydXXNcf83b95UZGSk9uzZo3nz5ik0NFTu7u5atGiR2rZtmwt7AAAAAAD/n8UwDMPeRRQ0MTEx8vLyUnR0tK5cuaL58+dr7ty5Wr9+vfLi43JyclJQUJD69eun4OBglStXLte3AQAAACDrUmYDT09Pe5eTYwTANKR3kCMiInT27FlFRUUpMTExx9txcXGRt7e3KleuzHx/AAAAQAFU1AIgl4BmQdmyZVW2bFl7lwEAAAAA2cIgMAAAAADgIAiAAAAAAOAgCIAAAAAA4CAIgAAAAADgIAiAAAAAAOAgCIAAAAAA4CAIgAAAAADgIAiAAAAAAOAgCIAAAAAA4CAIgAAAAADgIAiAAAAAAOAgCIAAAAAA4CAIgAAAAADgIFzsXUBBZBiGJCkmJsbOlQAAAACwp+RMkJwRCjsCYBouXbokSfLz87NzJQAAAAAKgtjYWHl5edm7jBwjAKahdOnSkqSTJ08WiYPs6GJiYuTn56dTp07J09PT3uUgBziWRQfHsujgWBYtHM+ig2OZewzDUGxsrCpVqmTvUnIFATANTk63bo308vLiC1OEeHp6cjyLCI5l0cGxLDo4lkULx7Po4FjmjqJ0UohBYAAAAADAQRAAAQAAAMBBEADT4O7urjFjxsjd3d3epSAXcDyLDo5l0cGxLDo4lkULx7Po4FgiPRajqIxnCgAAAADIEGcAAQAAAMBBEAABAAAAwEEQAAEAAADAQRAAAQAAAMBBEADT8PXXX6tatWoqVqyYGjVqpLVr19q7JKQwduxYWSwWq4evr6+53DAMjR07VpUqVVLx4sUVGBiof/75x6qPuLg4Pf/88ypbtqw8PDzUs2dP/ffff/m9Kw5pzZo16tGjhypVqiSLxaLff//danluHb/IyEg9+uij8vLykpeXlx599FFFRUXl8d45lsyOZUhISKrvarNmzazacCwLhvHjx6tJkyYqVaqUypcvr969e+vff/+1asN3s3Cw5Vjy3SwcvvnmGzVo0MCcyL158+ZasmSJuZzvJLKLAHibOXPmaOTIkXrjjTe0c+dOtWrVSl26dNHJkyftXRpSqFu3rs6ePWs+9uzZYy776KOP9Nlnn+nLL7/U1q1b5evrqw4dOig2NtZsM3LkSP3222+aPXu21q1bpytXrqh79+5KTEy0x+44lKtXr+ruu+/Wl19+meby3Dp+AwYM0K5du7R06VItXbpUu3bt0qOPPprn++dIMjuWktS5c2er7+rixYutlnMsC4bw8HANHTpUmzZt0ooVK5SQkKCOHTvq6tWrZhu+m4WDLcdS4rtZGFSpUkUffvihtm3bpm3btqlt27bq1auXGfL4TiLbDFi57777jGeeecbqvbvuust49dVX7VQRbjdmzBjj7rvvTnNZUlKS4evra3z44Yfmezdu3DC8vLyMKVOmGIZhGFFRUYarq6sxe/Zss83p06cNJycnY+nSpXlaO6xJMn777TfzdW4dv3379hmSjE2bNpltNm7caEgyDhw4kMd75ZhuP5aGYRiDBw82evXqle46HMuC68KFC4YkIzw83DAMvpuF2e3H0jD4bhZmPj4+xtSpU/lOIkc4A5hCfHy8tm/fro4dO1q937FjR23YsMFOVSEthw4dUqVKlVStWjX1799fR48elSQdO3ZM586dszqG7u7uatOmjXkMt2/frps3b1q1qVSpkurVq8dxtrPcOn4bN26Ul5eXmjZtarZp1qyZvLy8OMb5LCwsTOXLl1dAQICGDBmiCxcumMs4lgVXdHS0JKl06dKS+G4WZrcfy2R8NwuXxMREzZ49W1evXlXz5s35TiJHCIApREREKDExURUqVLB6v0KFCjp37pydqsLtmjZtqh9//FHLli3Td999p3PnzqlFixa6dOmSeZwyOobnzp2Tm5ubfHx80m0D+8it43fu3DmVL18+Vf/ly5fnGOejLl266Oeff9bq1av16aefauvWrWrbtq3i4uIkcSwLKsMwNGrUKN1///2qV6+eJL6bhVVax1Liu1mY7NmzRyVLlpS7u7ueeeYZ/fbbb6pTpw7fSeSIi70LKIgsFovVa8MwUr0H++nSpYv5vH79+mrevLlq1KihGTNmmDexZ+cYcpwLjtw4fmm15xjnr4ceesh8Xq9ePTVu3Fj+/v7666+/9MADD6S7HsfSvoYNG6bdu3dr3bp1qZbx3Sxc0juWfDcLjzvvvFO7du1SVFSU5s+fr8GDBys8PNxczncS2cEZwBTKli0rZ2fnVP/jceHChVT/w4KCw8PDQ/Xr19ehQ4fM0UAzOoa+vr6Kj49XZGRkum1gH7l1/Hx9fXX+/PlU/V+8eJFjbEcVK1aUv7+/Dh06JIljWRA9//zzWrhwoUJDQ1WlShXzfb6bhU96xzItfDcLLjc3N9WsWVONGzfW+PHjdffdd2vy5Ml8J5EjBMAU3Nzc1KhRI61YscLq/RUrVqhFixZ2qgqZiYuL0/79+1WxYkVVq1ZNvr6+VscwPj5e4eHh5jFs1KiRXF1drdqcPXtWe/fu5TjbWW4dv+bNmys6Olpbtmwx22zevFnR0dEcYzu6dOmSTp06pYoVK0riWBYkhmFo2LBhWrBggVavXq1q1apZLee7WXhkdizTwnez8DAMQ3FxcXwnkTP5OuRMITB79mzD1dXV+P777419+/YZI0eONDw8PIzjx4/buzT8n9GjRxthYWHG0aNHjU2bNhndu3c3SpUqZR6jDz/80PDy8jIWLFhg7Nmzx3j44YeNihUrGjExMWYfzzzzjFGlShVj5cqVxo4dO4y2bdsad999t5GQkGCv3XIYsbGxxs6dO42dO3cakozPPvvM2Llzp3HixAnDMHLv+HXu3Nlo0KCBsXHjRmPjxo1G/fr1je7du+f7/hZlGR3L2NhYY/To0caGDRuMY8eOGaGhoUbz5s2NypUrcywLoGeffdbw8vIywsLCjLNnz5qPa9eumW34bhYOmR1LvpuFx2uvvWasWbPGOHbsmLF7927j9ddfN5ycnIzly5cbhsF3EtlHAEzDV199Zfj7+xtubm5Gw4YNrYZOhv099NBDRsWKFQ1XV1ejUqVKxgMPPGD8888/5vKkpCRjzJgxhq+vr+Hu7m60bt3a2LNnj1Uf169fN4YNG2aULl3aKF68uNG9e3fj5MmT+b0rDik0NNSQlOoxePBgwzBy7/hdunTJGDhwoFGqVCmjVKlSxsCBA43IyMh82kvHkNGxvHbtmtGxY0ejXLlyhqurq3HHHXcYgwcPTnWcOJYFQ1rHUZIxbdo0sw3fzcIhs2PJd7PwePzxx82/R8uVK2e0a9fODH+GwXcS2WcxDMPIv/ONAAAAAAB74R5AAAAAAHAQBEAAAAAAcBAEQAAAAABwEARAAAAAAHAQBEAAAAAAcBAEQAAAAABwEARAAAAAAHAQBEAAAAAAcBAEQACAw5s+fbq8vb3tXQYAAHmOAAgAKHROnTqlJ554QpUqVZKbm5v8/f01YsQIXbp0yd6lpRIYGKiRI0davbZYLLJYLHJ3d1flypXVo0cPLViwwH5FAgAcBgEQAFCoHD16VI0bN9bBgwc1a9YsHT58WFOmTNGqVavUvHlzXb58Od114+Pj86yumzdv2tx2yJAhOnv2rA4fPqz58+erTp066t+/v5566qk8qw8AAIkACAAoZIYOHSo3NzctX75cbdq00R133KEuXbpo5cqVOn36tN544w2zbdWqVTVu3DiFhITIy8tLQ4YMkXTrks877rhDJUqUUHBwcJpnDv/88081atRIxYoVU/Xq1fXOO+8oISHBXG6xWDRlyhT16tVLHh4eGjdunM37UKJECfn6+srPz0/NmjXThAkT9O233+q7777TypUrc/DpAACQMQIgAKDQuHz5spYtW6bnnntOxYsXt1rm6+urgQMHas6cOTIMw3z/448/Vr169bR9+3a99dZb2rx5sx5//HE999xz2rVrl4KCglKFt2XLlumRRx7R8OHDtW/fPn377beaPn263n//fat2Y8aMUa9evbRnzx49/vjjOdq3wYMHy8fHh0tBAQB5ysXeBQAAYKtDhw7JMAzVrl07zeW1a9dWZGSkLl68qPLly0uS2rZtqxdffNFs8/bbb6tTp0569dVXJUkBAQHasGGDli5darZ5//339eqrr2rw4MGSpOrVq+u9997Tyy+/rDFjxpjtBgwYkOPgl8zJyUkBAQE6fvx4rvQHAEBaOAMIACgyks/8WSwW873GjRtbtdm/f7+aN29u9d7tr7dv3653331XJUuWNB/J9+1du3Yt3b5zo/6UtQMAkNs4AwgAKDRq1qwpi8Wiffv2qXfv3qmWHzhwQD4+Pipbtqz5noeHh1WblJeHpicpKUnvvPOOHnjggVTLihUrlm7fOZGYmKhDhw6pSZMmudYnAAC3IwACAAqNMmXKqEOHDvr666/1wgsvWN0HeO7cOf38888aNGhQhmfR6tSpo02bNlm9d/vrhg0b6t9//1XNmjVzdwcyMGPGDEVGRqpPnz75tk0AgOMhAAIACpUvv/xSLVq0UKdOnTRu3DhVq1ZN//zzj1566SVVrlw51UAttxs+fLhatGihjz76SL1799by5cut7v+Tbt0n2L17d/n5+alv375ycnLS7t27tWfPniyN9pmea9eu6dy5c0pISNDp06e1YMECTZw4Uc8++6yCgoJy3D8AAOnhHkAAQKFSq1Ytbdu2TTVq1NBDDz2kGjVq6KmnnlJQUJA2btyo0qVLZ7h+s2bNNHXqVH3xxRe65557tHz5cr355ptWbTp16qRFixZpxYoVatKkiZo1a6bPPvtM/v7+ubIP3333nSpWrKgaNWooODhY+/bt05w5c/T111/nSv8AAKTHYthyMwQAAAAAoNDjDCAAAAAAOAgCIAAAAAA4CAIgAAAAADgIAiAAAAAAOAgCIAAAAAA4CAIgAAAAADgIAiAAAAAAOAgCIAAAAAA4CAIgAAAAADgIAiAAAAAAOAgCIAAAAAA4iP8H8xVuf/JigMkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = plt.axes()\n",
    "sns.barplot(y='Region', x='Order ID', data=region)\n",
    "\n",
    "for i in ax.containers:\n",
    "    ax.bar_label(i,label_type='edge',padding=5,fontsize=20,bbox=bbox_args)\n",
    "\n",
    "plt.title('Total Orders by Region',fontsize=25)\n",
    "plt.ylabel(None)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ea9419cf",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "id": "90b2d0e2",
   "metadata": {},
   "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>Order ID</th>\n",
       "      <th>Customer Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>Sub Category</th>\n",
       "      <th>City</th>\n",
       "      <th>Order Date</th>\n",
       "      <th>Region</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Discount</th>\n",
       "      <th>Profit</th>\n",
       "      <th>State</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>OD1</td>\n",
       "      <td>Harish</td>\n",
       "      <td>Oil &amp; Masala</td>\n",
       "      <td>Masalas</td>\n",
       "      <td>Vellore</td>\n",
       "      <td>1970-01-01 00:00:00.011082017</td>\n",
       "      <td>North</td>\n",
       "      <td>1254</td>\n",
       "      <td>0.12</td>\n",
       "      <td>401.28</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>OD2</td>\n",
       "      <td>Sudha</td>\n",
       "      <td>Beverages</td>\n",
       "      <td>Health Drinks</td>\n",
       "      <td>Krishnagiri</td>\n",
       "      <td>1970-01-01 00:00:00.011082017</td>\n",
       "      <td>South</td>\n",
       "      <td>749</td>\n",
       "      <td>0.18</td>\n",
       "      <td>149.80</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>OD3</td>\n",
       "      <td>Hussain</td>\n",
       "      <td>Food Grains</td>\n",
       "      <td>Atta &amp; Flour</td>\n",
       "      <td>Perambalur</td>\n",
       "      <td>1970-01-01 00:00:00.006122017</td>\n",
       "      <td>West</td>\n",
       "      <td>2360</td>\n",
       "      <td>0.21</td>\n",
       "      <td>165.20</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>OD4</td>\n",
       "      <td>Jackson</td>\n",
       "      <td>Fruits &amp; Veggies</td>\n",
       "      <td>Fresh Vegetables</td>\n",
       "      <td>Dharmapuri</td>\n",
       "      <td>1970-01-01 00:00:00.010112016</td>\n",
       "      <td>South</td>\n",
       "      <td>896</td>\n",
       "      <td>0.25</td>\n",
       "      <td>89.60</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>OD5</td>\n",
       "      <td>Ridhesh</td>\n",
       "      <td>Food Grains</td>\n",
       "      <td>Organic Staples</td>\n",
       "      <td>Ooty</td>\n",
       "      <td>1970-01-01 00:00:00.010112016</td>\n",
       "      <td>South</td>\n",
       "      <td>2355</td>\n",
       "      <td>0.26</td>\n",
       "      <td>918.45</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Order ID Customer Name          Category      Sub Category         City  \\\n",
       "0      OD1        Harish      Oil & Masala           Masalas      Vellore   \n",
       "1      OD2         Sudha         Beverages     Health Drinks  Krishnagiri   \n",
       "2      OD3       Hussain       Food Grains      Atta & Flour   Perambalur   \n",
       "3      OD4       Jackson  Fruits & Veggies  Fresh Vegetables   Dharmapuri   \n",
       "4      OD5       Ridhesh       Food Grains   Organic Staples         Ooty   \n",
       "\n",
       "                     Order Date Region  Sales  Discount  Profit       State  \n",
       "0 1970-01-01 00:00:00.011082017  North   1254      0.12  401.28  Tamil Nadu  \n",
       "1 1970-01-01 00:00:00.011082017  South    749      0.18  149.80  Tamil Nadu  \n",
       "2 1970-01-01 00:00:00.006122017   West   2360      0.21  165.20  Tamil Nadu  \n",
       "3 1970-01-01 00:00:00.010112016  South    896      0.25   89.60  Tamil Nadu  \n",
       "4 1970-01-01 00:00:00.010112016  South   2355      0.26  918.45  Tamil Nadu  "
      ]
     },
     "execution_count": 192,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f64d2ae",
   "metadata": {},
   "source": [
    "# Total Sales by Category and Sub Category"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "id": "64d43145",
   "metadata": {},
   "outputs": [],
   "source": [
    "category_sales = pd.pivot_table(data=data,index=['Category','Sub Category'],values='Sales',\n",
    "                                aggfunc='sum').reset_index().sort_values(['Category','Sales'],ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "id": "38f78b17",
   "metadata": {},
   "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>Category</th>\n",
       "      <th>Sub Category</th>\n",
       "      <th>Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Snacks</td>\n",
       "      <td>Cookies</td>\n",
       "      <td>768213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Snacks</td>\n",
       "      <td>Noodles</td>\n",
       "      <td>735435</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Snacks</td>\n",
       "      <td>Chocolates</td>\n",
       "      <td>733898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Oil &amp; Masala</td>\n",
       "      <td>Masalas</td>\n",
       "      <td>697480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Oil &amp; Masala</td>\n",
       "      <td>Spices</td>\n",
       "      <td>672876</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Oil &amp; Masala</td>\n",
       "      <td>Edible Oil &amp; Ghee</td>\n",
       "      <td>668086</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Fruits &amp; Veggies</td>\n",
       "      <td>Fresh Fruits</td>\n",
       "      <td>551212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Fruits &amp; Veggies</td>\n",
       "      <td>Fresh Vegetables</td>\n",
       "      <td>525842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Fruits &amp; Veggies</td>\n",
       "      <td>Organic Vegetables</td>\n",
       "      <td>520271</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Fruits &amp; Veggies</td>\n",
       "      <td>Organic Fruits</td>\n",
       "      <td>503402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Food Grains</td>\n",
       "      <td>Organic Staples</td>\n",
       "      <td>558929</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Food Grains</td>\n",
       "      <td>Atta &amp; Flour</td>\n",
       "      <td>534649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Food Grains</td>\n",
       "      <td>Dals &amp; Pulses</td>\n",
       "      <td>523371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Food Grains</td>\n",
       "      <td>Rice</td>\n",
       "      <td>498323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Eggs, Meat &amp; Fish</td>\n",
       "      <td>Mutton</td>\n",
       "      <td>611200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Eggs, Meat &amp; Fish</td>\n",
       "      <td>Eggs</td>\n",
       "      <td>575156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Eggs, Meat &amp; Fish</td>\n",
       "      <td>Fish</td>\n",
       "      <td>560548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Eggs, Meat &amp; Fish</td>\n",
       "      <td>Chicken</td>\n",
       "      <td>520497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Beverages</td>\n",
       "      <td>Health Drinks</td>\n",
       "      <td>1051439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Beverages</td>\n",
       "      <td>Soft Drinks</td>\n",
       "      <td>1033874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Bakery</td>\n",
       "      <td>Breads &amp; Buns</td>\n",
       "      <td>742586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Bakery</td>\n",
       "      <td>Cakes</td>\n",
       "      <td>685612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Bakery</td>\n",
       "      <td>Biscuits</td>\n",
       "      <td>684083</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Category        Sub Category    Sales\n",
       "21             Snacks             Cookies   768213\n",
       "22             Snacks             Noodles   735435\n",
       "20             Snacks          Chocolates   733898\n",
       "18       Oil & Masala             Masalas   697480\n",
       "19       Oil & Masala              Spices   672876\n",
       "17       Oil & Masala   Edible Oil & Ghee   668086\n",
       "13   Fruits & Veggies        Fresh Fruits   551212\n",
       "14   Fruits & Veggies    Fresh Vegetables   525842\n",
       "16   Fruits & Veggies  Organic Vegetables   520271\n",
       "15   Fruits & Veggies      Organic Fruits   503402\n",
       "11        Food Grains     Organic Staples   558929\n",
       "9         Food Grains        Atta & Flour   534649\n",
       "10        Food Grains       Dals & Pulses   523371\n",
       "12        Food Grains                Rice   498323\n",
       "8   Eggs, Meat & Fish              Mutton   611200\n",
       "6   Eggs, Meat & Fish                Eggs   575156\n",
       "7   Eggs, Meat & Fish                Fish   560548\n",
       "5   Eggs, Meat & Fish             Chicken   520497\n",
       "3           Beverages       Health Drinks  1051439\n",
       "4           Beverages         Soft Drinks  1033874\n",
       "1              Bakery       Breads & Buns   742586\n",
       "2              Bakery               Cakes   685612\n",
       "0              Bakery            Biscuits   684083"
      ]
     },
     "execution_count": 196,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "category_sales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 319,
   "id": "9d253635",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = plt.axes()\n",
    "sns.barplot(x='Sales',y='Sub Category',data=category_sales)\n",
    "for i in ax.containers:\n",
    "    ax.bar_label(i,label_type='edge',padding=5,fontsize = 10,bbox = bbox_args,fmt='%d')\n",
    "plt.title('Sales by Category & Sub Category',fontsize=20)\n",
    "plt.ylabel(None)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3b82cee1",
   "metadata": {},
   "source": [
    "# Profit margin by sub category"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "id": "65da18b7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Order ID', 'Customer Name', 'Category', 'Sub Category', 'City',\n",
       "       'Order Date', 'Region', 'Sales', 'Discount', 'Profit', 'State'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 211,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "id": "43aeedfe",
   "metadata": {},
   "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>Sub Category</th>\n",
       "      <th>Profit</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profit Margin</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Noodles</td>\n",
       "      <td>193685.81</td>\n",
       "      <td>735435</td>\n",
       "      <td>26.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Fish</td>\n",
       "      <td>147248.01</td>\n",
       "      <td>560548</td>\n",
       "      <td>26.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Organic Fruits</td>\n",
       "      <td>130862.33</td>\n",
       "      <td>503402</td>\n",
       "      <td>26.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Organic Staples</td>\n",
       "      <td>144136.89</td>\n",
       "      <td>558929</td>\n",
       "      <td>25.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Breads &amp; Buns</td>\n",
       "      <td>190764.98</td>\n",
       "      <td>742586</td>\n",
       "      <td>25.69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Organic Vegetables</td>\n",
       "      <td>133596.37</td>\n",
       "      <td>520271</td>\n",
       "      <td>25.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Rice</td>\n",
       "      <td>126932.36</td>\n",
       "      <td>498323</td>\n",
       "      <td>25.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Health Drinks</td>\n",
       "      <td>267469.79</td>\n",
       "      <td>1051439</td>\n",
       "      <td>25.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Edible Oil &amp; Ghee</td>\n",
       "      <td>168593.58</td>\n",
       "      <td>668086</td>\n",
       "      <td>25.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Eggs</td>\n",
       "      <td>144669.92</td>\n",
       "      <td>575156</td>\n",
       "      <td>25.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Chocolates</td>\n",
       "      <td>183849.34</td>\n",
       "      <td>733898</td>\n",
       "      <td>25.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Soft Drinks</td>\n",
       "      <td>258135.97</td>\n",
       "      <td>1033874</td>\n",
       "      <td>24.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Fresh Vegetables</td>\n",
       "      <td>131273.33</td>\n",
       "      <td>525842</td>\n",
       "      <td>24.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Dals &amp; Pulses</td>\n",
       "      <td>130232.29</td>\n",
       "      <td>523371</td>\n",
       "      <td>24.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Cookies</td>\n",
       "      <td>190643.70</td>\n",
       "      <td>768213</td>\n",
       "      <td>24.82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Mutton</td>\n",
       "      <td>151389.40</td>\n",
       "      <td>611200</td>\n",
       "      <td>24.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Biscuits</td>\n",
       "      <td>169357.62</td>\n",
       "      <td>684083</td>\n",
       "      <td>24.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Cakes</td>\n",
       "      <td>168398.46</td>\n",
       "      <td>685612</td>\n",
       "      <td>24.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Fresh Fruits</td>\n",
       "      <td>134668.35</td>\n",
       "      <td>551212</td>\n",
       "      <td>24.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Masalas</td>\n",
       "      <td>168999.11</td>\n",
       "      <td>697480</td>\n",
       "      <td>24.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Atta &amp; Flour</td>\n",
       "      <td>127861.10</td>\n",
       "      <td>534649</td>\n",
       "      <td>23.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Chicken</td>\n",
       "      <td>124049.89</td>\n",
       "      <td>520497</td>\n",
       "      <td>23.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Spices</td>\n",
       "      <td>160302.60</td>\n",
       "      <td>672876</td>\n",
       "      <td>23.82</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Sub Category     Profit    Sales  Profit Margin\n",
       "16             Noodles  193685.81   735435          26.34\n",
       "10                Fish  147248.01   560548          26.27\n",
       "17      Organic Fruits  130862.33   503402          26.00\n",
       "18     Organic Staples  144136.89   558929          25.79\n",
       "2        Breads & Buns  190764.98   742586          25.69\n",
       "19  Organic Vegetables  133596.37   520271          25.68\n",
       "20                Rice  126932.36   498323          25.47\n",
       "13       Health Drinks  267469.79  1051439          25.44\n",
       "8    Edible Oil & Ghee  168593.58   668086          25.24\n",
       "9                 Eggs  144669.92   575156          25.15\n",
       "5           Chocolates  183849.34   733898          25.05\n",
       "21         Soft Drinks  258135.97  1033874          24.97\n",
       "12    Fresh Vegetables  131273.33   525842          24.96\n",
       "7        Dals & Pulses  130232.29   523371          24.88\n",
       "6              Cookies  190643.70   768213          24.82\n",
       "15              Mutton  151389.40   611200          24.77\n",
       "1             Biscuits  169357.62   684083          24.76\n",
       "3                Cakes  168398.46   685612          24.56\n",
       "11        Fresh Fruits  134668.35   551212          24.43\n",
       "14             Masalas  168999.11   697480          24.23\n",
       "0         Atta & Flour  127861.10   534649          23.91\n",
       "4              Chicken  124049.89   520497          23.83\n",
       "22              Spices  160302.60   672876          23.82"
      ]
     },
     "execution_count": 225,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prof_margin = pd.pivot_table(data=data,index='Sub Category',values=['Sales','Profit'],aggfunc='sum').reset_index()\n",
    "prof_margin['Profit Margin'] = round(prof_margin['Profit']/prof_margin['Sales']*100,2)\n",
    "prof_margin.sort_values(by='Profit Margin',ascending=False,inplace=True)\n",
    "prof_margin"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 242,
   "id": "87078a77",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x2000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Adjusting size of figure\n",
    "plt.rcParams['figure.figsize'] = (10,20)\n",
    "ax = plt.axes()\n",
    "sns.barplot(x='Profit Margin',y='Sub Category',data=prof_margin)\n",
    "for i in ax.containers:\n",
    "    ax.bar_label(i,padding=6,fontsize=11,bbox=bbox_args)\n",
    "    \n",
    "plt.title('Profit Margin by Sub Category',fontsize=20)\n",
    "plt.ylabel(None)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "203a0265",
   "metadata": {},
   "source": [
    "# Total Sales & Orders by Year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 243,
   "id": "2a803f4e",
   "metadata": {},
   "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>Order ID</th>\n",
       "      <th>Customer Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>Sub Category</th>\n",
       "      <th>City</th>\n",
       "      <th>Order Date</th>\n",
       "      <th>Region</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Discount</th>\n",
       "      <th>Profit</th>\n",
       "      <th>State</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>OD1</td>\n",
       "      <td>Harish</td>\n",
       "      <td>Oil &amp; Masala</td>\n",
       "      <td>Masalas</td>\n",
       "      <td>Vellore</td>\n",
       "      <td>1970-01-01 00:00:00.011082017</td>\n",
       "      <td>North</td>\n",
       "      <td>1254</td>\n",
       "      <td>0.12</td>\n",
       "      <td>401.28</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>OD2</td>\n",
       "      <td>Sudha</td>\n",
       "      <td>Beverages</td>\n",
       "      <td>Health Drinks</td>\n",
       "      <td>Krishnagiri</td>\n",
       "      <td>1970-01-01 00:00:00.011082017</td>\n",
       "      <td>South</td>\n",
       "      <td>749</td>\n",
       "      <td>0.18</td>\n",
       "      <td>149.80</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>OD3</td>\n",
       "      <td>Hussain</td>\n",
       "      <td>Food Grains</td>\n",
       "      <td>Atta &amp; Flour</td>\n",
       "      <td>Perambalur</td>\n",
       "      <td>1970-01-01 00:00:00.006122017</td>\n",
       "      <td>West</td>\n",
       "      <td>2360</td>\n",
       "      <td>0.21</td>\n",
       "      <td>165.20</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>OD4</td>\n",
       "      <td>Jackson</td>\n",
       "      <td>Fruits &amp; Veggies</td>\n",
       "      <td>Fresh Vegetables</td>\n",
       "      <td>Dharmapuri</td>\n",
       "      <td>1970-01-01 00:00:00.010112016</td>\n",
       "      <td>South</td>\n",
       "      <td>896</td>\n",
       "      <td>0.25</td>\n",
       "      <td>89.60</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>OD5</td>\n",
       "      <td>Ridhesh</td>\n",
       "      <td>Food Grains</td>\n",
       "      <td>Organic Staples</td>\n",
       "      <td>Ooty</td>\n",
       "      <td>1970-01-01 00:00:00.010112016</td>\n",
       "      <td>South</td>\n",
       "      <td>2355</td>\n",
       "      <td>0.26</td>\n",
       "      <td>918.45</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Order ID Customer Name          Category      Sub Category         City  \\\n",
       "0      OD1        Harish      Oil & Masala           Masalas      Vellore   \n",
       "1      OD2         Sudha         Beverages     Health Drinks  Krishnagiri   \n",
       "2      OD3       Hussain       Food Grains      Atta & Flour   Perambalur   \n",
       "3      OD4       Jackson  Fruits & Veggies  Fresh Vegetables   Dharmapuri   \n",
       "4      OD5       Ridhesh       Food Grains   Organic Staples         Ooty   \n",
       "\n",
       "                     Order Date Region  Sales  Discount  Profit       State  \n",
       "0 1970-01-01 00:00:00.011082017  North   1254      0.12  401.28  Tamil Nadu  \n",
       "1 1970-01-01 00:00:00.011082017  South    749      0.18  149.80  Tamil Nadu  \n",
       "2 1970-01-01 00:00:00.006122017   West   2360      0.21  165.20  Tamil Nadu  \n",
       "3 1970-01-01 00:00:00.010112016  South    896      0.25   89.60  Tamil Nadu  \n",
       "4 1970-01-01 00:00:00.010112016  South   2355      0.26  918.45  Tamil Nadu  "
      ]
     },
     "execution_count": 243,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 252,
   "id": "9966c4df",
   "metadata": {},
   "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>Order Year</th>\n",
       "      <th>Order ID</th>\n",
       "      <th>Profit</th>\n",
       "      <th>Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1970</td>\n",
       "      <td>9994</td>\n",
       "      <td>3747121.2</td>\n",
       "      <td>14956982</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Order Year  Order ID     Profit     Sales\n",
       "0        1970      9994  3747121.2  14956982"
      ]
     },
     "execution_count": 252,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "year_performance = pd.pivot_table(data=data, index='Order ', values=['Order ID', 'Sales', 'Profit'], \n",
    "               aggfunc={'Order ID':'count', 'Sales':'sum', 'Profit':'sum'}).reset_index()\n",
    "year_performance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 267,
   "id": "986830c2",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv(r\"C:\\Users\\chris\\Downloads\\archive (7)\\Supermart Grocery Sales - Retail Analytics Dataset.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 269,
   "id": "5f93b587",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2018    3312\n",
       "2017    2587\n",
       "2016    2102\n",
       "2015    1993\n",
       "Name: Order Year, dtype: int64"
      ]
     },
     "execution_count": 269,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Order Year'] = data['Order Date'].str[-4:]\n",
    "data['Order Year'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 272,
   "id": "bb47fae0",
   "metadata": {},
   "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>Order Year</th>\n",
       "      <th>Order ID</th>\n",
       "      <th>Profit</th>\n",
       "      <th>Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015</td>\n",
       "      <td>1993</td>\n",
       "      <td>752529.11</td>\n",
       "      <td>2975599</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016</td>\n",
       "      <td>2102</td>\n",
       "      <td>797192.99</td>\n",
       "      <td>3131959</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017</td>\n",
       "      <td>2587</td>\n",
       "      <td>953216.22</td>\n",
       "      <td>3871912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018</td>\n",
       "      <td>3312</td>\n",
       "      <td>1244182.88</td>\n",
       "      <td>4977512</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Order Year  Order ID      Profit    Sales\n",
       "0       2015      1993   752529.11  2975599\n",
       "1       2016      2102   797192.99  3131959\n",
       "2       2017      2587   953216.22  3871912\n",
       "3       2018      3312  1244182.88  4977512"
      ]
     },
     "execution_count": 272,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "year_performance = pd.pivot_table(data=data, index='Order Year', values=['Order ID', 'Sales', 'Profit'], \n",
    "               aggfunc={'Order ID':'count', 'Sales':'sum', 'Profit':'sum'}).reset_index()\n",
    "year_performance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 315,
   "id": "8e5d693e",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Resizing the figure\n",
    "plt.rcParams['figure.figsize'] = (10,5)\n",
    "ax = sns.barplot(x='Order Year',y='Sales',data=year_performance,)\n",
    "for i in ax.containers:\n",
    "    ax.bar_label(i,padding=5,fontsize=10,bbox=bbox_args,fmt = '%d')\n",
    "plt.ylabel(None)\n",
    "plt.title('Year Wise Performance',fontsize=20)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 371,
   "id": "7e7ca57b",
   "metadata": {
    "scrolled": true
   },
   "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>Order ID</th>\n",
       "      <th>Customer Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>Sub Category</th>\n",
       "      <th>City</th>\n",
       "      <th>Order Date</th>\n",
       "      <th>Region</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Discount</th>\n",
       "      <th>Profit</th>\n",
       "      <th>State</th>\n",
       "      <th>Order Year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>OD1</td>\n",
       "      <td>Harish</td>\n",
       "      <td>Oil &amp; Masala</td>\n",
       "      <td>Masalas</td>\n",
       "      <td>Vellore</td>\n",
       "      <td>11-08-2017</td>\n",
       "      <td>North</td>\n",
       "      <td>1254</td>\n",
       "      <td>0.12</td>\n",
       "      <td>401.28</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "      <td>2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>OD2</td>\n",
       "      <td>Sudha</td>\n",
       "      <td>Beverages</td>\n",
       "      <td>Health Drinks</td>\n",
       "      <td>Krishnagiri</td>\n",
       "      <td>11-08-2017</td>\n",
       "      <td>South</td>\n",
       "      <td>749</td>\n",
       "      <td>0.18</td>\n",
       "      <td>149.80</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "      <td>2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>OD3</td>\n",
       "      <td>Hussain</td>\n",
       "      <td>Food Grains</td>\n",
       "      <td>Atta &amp; Flour</td>\n",
       "      <td>Perambalur</td>\n",
       "      <td>06-12-2017</td>\n",
       "      <td>West</td>\n",
       "      <td>2360</td>\n",
       "      <td>0.21</td>\n",
       "      <td>165.20</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "      <td>2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>OD4</td>\n",
       "      <td>Jackson</td>\n",
       "      <td>Fruits &amp; Veggies</td>\n",
       "      <td>Fresh Vegetables</td>\n",
       "      <td>Dharmapuri</td>\n",
       "      <td>10-11-2016</td>\n",
       "      <td>South</td>\n",
       "      <td>896</td>\n",
       "      <td>0.25</td>\n",
       "      <td>89.60</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>OD5</td>\n",
       "      <td>Ridhesh</td>\n",
       "      <td>Food Grains</td>\n",
       "      <td>Organic Staples</td>\n",
       "      <td>Ooty</td>\n",
       "      <td>10-11-2016</td>\n",
       "      <td>South</td>\n",
       "      <td>2355</td>\n",
       "      <td>0.26</td>\n",
       "      <td>918.45</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Order ID Customer Name          Category      Sub Category         City  \\\n",
       "0      OD1        Harish      Oil & Masala           Masalas      Vellore   \n",
       "1      OD2         Sudha         Beverages     Health Drinks  Krishnagiri   \n",
       "2      OD3       Hussain       Food Grains      Atta & Flour   Perambalur   \n",
       "3      OD4       Jackson  Fruits & Veggies  Fresh Vegetables   Dharmapuri   \n",
       "4      OD5       Ridhesh       Food Grains   Organic Staples         Ooty   \n",
       "\n",
       "   Order Date Region  Sales  Discount  Profit       State Order Year  \n",
       "0  11-08-2017  North   1254      0.12  401.28  Tamil Nadu       2017  \n",
       "1  11-08-2017  South    749      0.18  149.80  Tamil Nadu       2017  \n",
       "2  06-12-2017   West   2360      0.21  165.20  Tamil Nadu       2017  \n",
       "3  10-11-2016  South    896      0.25   89.60  Tamil Nadu       2016  \n",
       "4  10-11-2016  South   2355      0.26  918.45  Tamil Nadu       2016  "
      ]
     },
     "execution_count": 371,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "287c737a",
   "metadata": {},
   "source": [
    "# Total Sales by Cities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 396,
   "id": "0e0c37f7",
   "metadata": {
    "scrolled": false
   },
   "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>City</th>\n",
       "      <th>Order Year</th>\n",
       "      <th>Profit</th>\n",
       "      <th>Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Kanyakumari</td>\n",
       "      <td>2018</td>\n",
       "      <td>61504.79</td>\n",
       "      <td>263243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Coimbatore</td>\n",
       "      <td>2018</td>\n",
       "      <td>59836.89</td>\n",
       "      <td>232831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>Tenkasi</td>\n",
       "      <td>2018</td>\n",
       "      <td>57448.63</td>\n",
       "      <td>232412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Bodi</td>\n",
       "      <td>2018</td>\n",
       "      <td>58880.87</td>\n",
       "      <td>230626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>Ramanadhapuram</td>\n",
       "      <td>2018</td>\n",
       "      <td>52641.46</td>\n",
       "      <td>227804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>Namakkal</td>\n",
       "      <td>2016</td>\n",
       "      <td>24780.63</td>\n",
       "      <td>105114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>Trichy</td>\n",
       "      <td>2015</td>\n",
       "      <td>25489.56</td>\n",
       "      <td>103001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>Ramanadhapuram</td>\n",
       "      <td>2015</td>\n",
       "      <td>27478.04</td>\n",
       "      <td>102407</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Madurai</td>\n",
       "      <td>2015</td>\n",
       "      <td>25403.58</td>\n",
       "      <td>98886</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>Nagercoil</td>\n",
       "      <td>2016</td>\n",
       "      <td>21198.41</td>\n",
       "      <td>85900</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>96 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              City Order Year    Profit   Sales\n",
       "27     Kanyakumari       2018  61504.79  263243\n",
       "11      Coimbatore       2018  59836.89  232831\n",
       "71         Tenkasi       2018  57448.63  232412\n",
       "3             Bodi       2018  58880.87  230626\n",
       "63  Ramanadhapuram       2018  52641.46  227804\n",
       "..             ...        ...       ...     ...\n",
       "45        Namakkal       2016  24780.63  105114\n",
       "80          Trichy       2015  25489.56  103001\n",
       "60  Ramanadhapuram       2015  27478.04  102407\n",
       "36         Madurai       2015  25403.58   98886\n",
       "41       Nagercoil       2016  21198.41   85900\n",
       "\n",
       "[96 rows x 4 columns]"
      ]
     },
     "execution_count": 396,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "city_sales = pd.pivot_table(data=data, index=['City','Order Year'], values=['Sales', 'Profit'], \n",
    "               aggfunc={'Sales':'sum', 'Profit':'sum'}).reset_index()\n",
    "city_sales = city_sales.sort_values(by='Sales',ascending=False)\n",
    "city_sales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 397,
   "id": "268e1a8c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, '')"
      ]
     },
     "execution_count": 397,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x='Sales',y='City',data=city_sales)\n",
    "for i in ax.containers:\n",
    "    ax.bar_label(i,label_type='edge',padding=7,bbox=bbox_args)\n",
    "plt.title('Total Sales by Cities',fontsize=25)\n",
    "plt.ylabel(None)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f635bec1",
   "metadata": {},
   "source": [
    "# Obeservations / Insights"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "033ad45a",
   "metadata": {},
   "source": [
    "From the above visulaisations, here are some various insights:\n",
    "- The most sales & orders was from the West region\n",
    "- The highest sales by category & sub-category comes from Health Drinks\n",
    "- The lowest sales by category & sub-category comes from Dals & Pulses\n",
    "- The sub-category with the highest profit margin is Noodles with a profit margin of 26.34%\n",
    "- The sub-category with the lowest profit margin is Spices with a profit margin of 23.82%\n",
    "- The city 'Kanyakumari' has the most number of sales in overall years\n",
    "- The city 'Nagercoil' has the least number of sales in overall years\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 320,
   "id": "9708af82",
   "metadata": {},
   "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>Order ID</th>\n",
       "      <th>Customer Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>Sub Category</th>\n",
       "      <th>City</th>\n",
       "      <th>Order Date</th>\n",
       "      <th>Region</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Discount</th>\n",
       "      <th>Profit</th>\n",
       "      <th>State</th>\n",
       "      <th>Order Year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>OD1</td>\n",
       "      <td>Harish</td>\n",
       "      <td>Oil &amp; Masala</td>\n",
       "      <td>Masalas</td>\n",
       "      <td>Vellore</td>\n",
       "      <td>11-08-2017</td>\n",
       "      <td>North</td>\n",
       "      <td>1254</td>\n",
       "      <td>0.12</td>\n",
       "      <td>401.28</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "      <td>2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>OD2</td>\n",
       "      <td>Sudha</td>\n",
       "      <td>Beverages</td>\n",
       "      <td>Health Drinks</td>\n",
       "      <td>Krishnagiri</td>\n",
       "      <td>11-08-2017</td>\n",
       "      <td>South</td>\n",
       "      <td>749</td>\n",
       "      <td>0.18</td>\n",
       "      <td>149.80</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "      <td>2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>OD3</td>\n",
       "      <td>Hussain</td>\n",
       "      <td>Food Grains</td>\n",
       "      <td>Atta &amp; Flour</td>\n",
       "      <td>Perambalur</td>\n",
       "      <td>06-12-2017</td>\n",
       "      <td>West</td>\n",
       "      <td>2360</td>\n",
       "      <td>0.21</td>\n",
       "      <td>165.20</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "      <td>2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>OD4</td>\n",
       "      <td>Jackson</td>\n",
       "      <td>Fruits &amp; Veggies</td>\n",
       "      <td>Fresh Vegetables</td>\n",
       "      <td>Dharmapuri</td>\n",
       "      <td>10-11-2016</td>\n",
       "      <td>South</td>\n",
       "      <td>896</td>\n",
       "      <td>0.25</td>\n",
       "      <td>89.60</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>OD5</td>\n",
       "      <td>Ridhesh</td>\n",
       "      <td>Food Grains</td>\n",
       "      <td>Organic Staples</td>\n",
       "      <td>Ooty</td>\n",
       "      <td>10-11-2016</td>\n",
       "      <td>South</td>\n",
       "      <td>2355</td>\n",
       "      <td>0.26</td>\n",
       "      <td>918.45</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Order ID Customer Name          Category      Sub Category         City  \\\n",
       "0      OD1        Harish      Oil & Masala           Masalas      Vellore   \n",
       "1      OD2         Sudha         Beverages     Health Drinks  Krishnagiri   \n",
       "2      OD3       Hussain       Food Grains      Atta & Flour   Perambalur   \n",
       "3      OD4       Jackson  Fruits & Veggies  Fresh Vegetables   Dharmapuri   \n",
       "4      OD5       Ridhesh       Food Grains   Organic Staples         Ooty   \n",
       "\n",
       "   Order Date Region  Sales  Discount  Profit       State Order Year  \n",
       "0  11-08-2017  North   1254      0.12  401.28  Tamil Nadu       2017  \n",
       "1  11-08-2017  South    749      0.18  149.80  Tamil Nadu       2017  \n",
       "2  06-12-2017   West   2360      0.21  165.20  Tamil Nadu       2017  \n",
       "3  10-11-2016  South    896      0.25   89.60  Tamil Nadu       2016  \n",
       "4  10-11-2016  South   2355      0.26  918.45  Tamil Nadu       2016  "
      ]
     },
     "execution_count": 320,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9c9b866",
   "metadata": {},
   "source": [
    "#  Top 10 Customers with the most number of orders"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 403,
   "id": "c828e2ac",
   "metadata": {},
   "outputs": [],
   "source": [
    "customers = data['Customer Name'].value_counts().head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 401,
   "id": "add8a1b5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Amrish      227\n",
       "Krithika    224\n",
       "Verma       218\n",
       "Arutra      218\n",
       "Vidya       215\n",
       "Shah        215\n",
       "Suresh      212\n",
       "Surya       209\n",
       "Harish      208\n",
       "Hussain     208\n",
       "Name: Customer Name, dtype: int64"
      ]
     },
     "execution_count": 401,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "customers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 343,
   "id": "56febe3c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Order ID</th>\n",
       "      <th>Customer Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>Sub Category</th>\n",
       "      <th>City</th>\n",
       "      <th>Order Date</th>\n",
       "      <th>Region</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Discount</th>\n",
       "      <th>Profit</th>\n",
       "      <th>State</th>\n",
       "      <th>Order Year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>OD1</td>\n",
       "      <td>Harish</td>\n",
       "      <td>Oil &amp; Masala</td>\n",
       "      <td>Masalas</td>\n",
       "      <td>Vellore</td>\n",
       "      <td>11-08-2017</td>\n",
       "      <td>North</td>\n",
       "      <td>1254</td>\n",
       "      <td>0.12</td>\n",
       "      <td>401.28</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "      <td>2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>OD2</td>\n",
       "      <td>Sudha</td>\n",
       "      <td>Beverages</td>\n",
       "      <td>Health Drinks</td>\n",
       "      <td>Krishnagiri</td>\n",
       "      <td>11-08-2017</td>\n",
       "      <td>South</td>\n",
       "      <td>749</td>\n",
       "      <td>0.18</td>\n",
       "      <td>149.80</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "      <td>2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>OD3</td>\n",
       "      <td>Hussain</td>\n",
       "      <td>Food Grains</td>\n",
       "      <td>Atta &amp; Flour</td>\n",
       "      <td>Perambalur</td>\n",
       "      <td>06-12-2017</td>\n",
       "      <td>West</td>\n",
       "      <td>2360</td>\n",
       "      <td>0.21</td>\n",
       "      <td>165.20</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "      <td>2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>OD4</td>\n",
       "      <td>Jackson</td>\n",
       "      <td>Fruits &amp; Veggies</td>\n",
       "      <td>Fresh Vegetables</td>\n",
       "      <td>Dharmapuri</td>\n",
       "      <td>10-11-2016</td>\n",
       "      <td>South</td>\n",
       "      <td>896</td>\n",
       "      <td>0.25</td>\n",
       "      <td>89.60</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>OD5</td>\n",
       "      <td>Ridhesh</td>\n",
       "      <td>Food Grains</td>\n",
       "      <td>Organic Staples</td>\n",
       "      <td>Ooty</td>\n",
       "      <td>10-11-2016</td>\n",
       "      <td>South</td>\n",
       "      <td>2355</td>\n",
       "      <td>0.26</td>\n",
       "      <td>918.45</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Order ID Customer Name          Category      Sub Category         City  \\\n",
       "0      OD1        Harish      Oil & Masala           Masalas      Vellore   \n",
       "1      OD2         Sudha         Beverages     Health Drinks  Krishnagiri   \n",
       "2      OD3       Hussain       Food Grains      Atta & Flour   Perambalur   \n",
       "3      OD4       Jackson  Fruits & Veggies  Fresh Vegetables   Dharmapuri   \n",
       "4      OD5       Ridhesh       Food Grains   Organic Staples         Ooty   \n",
       "\n",
       "   Order Date Region  Sales  Discount  Profit       State Order Year  \n",
       "0  11-08-2017  North   1254      0.12  401.28  Tamil Nadu       2017  \n",
       "1  11-08-2017  South    749      0.18  149.80  Tamil Nadu       2017  \n",
       "2  06-12-2017   West   2360      0.21  165.20  Tamil Nadu       2017  \n",
       "3  10-11-2016  South    896      0.25   89.60  Tamil Nadu       2016  \n",
       "4  10-11-2016  South   2355      0.26  918.45  Tamil Nadu       2016  "
      ]
     },
     "execution_count": 343,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ccb6187e",
   "metadata": {},
   "source": [
    "# Category with Top 3 position in sales (overall years)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 368,
   "id": "64c8097e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\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>Order Year</th>\n",
       "      <th>Category</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "      <th>2015_Rank</th>\n",
       "      <th>2016_Rank</th>\n",
       "      <th>2017_Rank</th>\n",
       "      <th>2018_Rank</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Bakery</td>\n",
       "      <td>433979</td>\n",
       "      <td>487965</td>\n",
       "      <td>504263</td>\n",
       "      <td>686074</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Beverages</td>\n",
       "      <td>409091</td>\n",
       "      <td>425719</td>\n",
       "      <td>543575</td>\n",
       "      <td>706928</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Eggs, Meat &amp; Fish</td>\n",
       "      <td>482982</td>\n",
       "      <td>462055</td>\n",
       "      <td>565101</td>\n",
       "      <td>757263</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Food Grains</td>\n",
       "      <td>356704</td>\n",
       "      <td>438736</td>\n",
       "      <td>609338</td>\n",
       "      <td>710494</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Fruits &amp; Veggies</td>\n",
       "      <td>409212</td>\n",
       "      <td>468441</td>\n",
       "      <td>516400</td>\n",
       "      <td>706674</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Oil &amp; Masala</td>\n",
       "      <td>423918</td>\n",
       "      <td>412725</td>\n",
       "      <td>564196</td>\n",
       "      <td>637603</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Snacks</td>\n",
       "      <td>459713</td>\n",
       "      <td>436318</td>\n",
       "      <td>569039</td>\n",
       "      <td>772476</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Order Year           Category    2015    2016    2017    2018  2015_Rank  \\\n",
       "0                      Bakery  433979  487965  504263  686074        3.0   \n",
       "1                   Beverages  409091  425719  543575  706928        6.0   \n",
       "2           Eggs, Meat & Fish  482982  462055  565101  757263        1.0   \n",
       "3                 Food Grains  356704  438736  609338  710494        7.0   \n",
       "4            Fruits & Veggies  409212  468441  516400  706674        5.0   \n",
       "5                Oil & Masala  423918  412725  564196  637603        4.0   \n",
       "6                      Snacks  459713  436318  569039  772476        2.0   \n",
       "\n",
       "Order Year  2016_Rank  2017_Rank  2018_Rank  \n",
       "0                 1.0        7.0        6.0  \n",
       "1                 6.0        5.0        4.0  \n",
       "2                 3.0        3.0        2.0  \n",
       "3                 4.0        1.0        3.0  \n",
       "4                 2.0        6.0        5.0  \n",
       "5                 7.0        4.0        7.0  \n",
       "6                 5.0        2.0        1.0  "
      ]
     },
     "execution_count": 368,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top3_sales = pd.pivot_table(data=data, index='Category', columns = 'Order Year', values='Sales', aggfunc='sum').reset_index()\n",
    "top3_sales['2015_Rank']=top3_sales['2015'].rank(method='max',ascending=False)\n",
    "top3_sales['2016_Rank']=top3_sales['2016'].rank(method='max',ascending=False)\n",
    "top3_sales['2017_Rank']=top3_sales['2017'].rank(method='max',ascending=False)\n",
    "top3_sales['2018_Rank']=top3_sales['2018'].rank(method='max',ascending=False)\n",
    "top3_sales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 369,
   "id": "38ba8e34",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Order Year</th>\n",
       "      <th>Category</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "      <th>2015_Rank</th>\n",
       "      <th>2016_Rank</th>\n",
       "      <th>2017_Rank</th>\n",
       "      <th>2018_Rank</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Eggs, Meat &amp; Fish</td>\n",
       "      <td>482982</td>\n",
       "      <td>462055</td>\n",
       "      <td>565101</td>\n",
       "      <td>757263</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "Order Year           Category    2015    2016    2017    2018  2015_Rank  \\\n",
       "2           Eggs, Meat & Fish  482982  462055  565101  757263        1.0   \n",
       "\n",
       "Order Year  2016_Rank  2017_Rank  2018_Rank  \n",
       "2                 3.0        3.0        2.0  "
      ]
     },
     "execution_count": 369,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top3_sales[(top3_sales['2015_Rank'] <=3) & (top3_sales['2016_Rank'] <=3) & (top3_sales['2017_Rank'] <=3) & (top3_sales['2018_Rank'] <=3)]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "56031e85",
   "metadata": {},
   "source": [
    "Eggs, Meat & Fish Category is consistent in the sales across years."
   ]
  }
 ],
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