Sales_analysis_python.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a4a9ff29",
   "metadata": {},
   "source": [
    "### import necessary libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c69dd96d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import os"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1062fa43",
   "metadata": {},
   "source": [
    "### merging 12 months of sales data in a single file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "608a6d61",
   "metadata": {},
   "outputs": [],
   "source": [
    "df= pd.read_csv(\"./Sales_Data/Sales_April_2019.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f3137172",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\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>Product</th>\n",
       "      <th>Quantity Ordered</th>\n",
       "      <th>Price Each</th>\n",
       "      <th>Order Date</th>\n",
       "      <th>Purchase Address</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>176558</td>\n",
       "      <td>USB-C Charging Cable</td>\n",
       "      <td>2</td>\n",
       "      <td>11.95</td>\n",
       "      <td>04/19/19 08:46</td>\n",
       "      <td>917 1st St, Dallas, TX 75001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>176559</td>\n",
       "      <td>Bose SoundSport Headphones</td>\n",
       "      <td>1</td>\n",
       "      <td>99.99</td>\n",
       "      <td>04/07/19 22:30</td>\n",
       "      <td>682 Chestnut St, Boston, MA 02215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>176560</td>\n",
       "      <td>Google Phone</td>\n",
       "      <td>1</td>\n",
       "      <td>600</td>\n",
       "      <td>04/12/19 14:38</td>\n",
       "      <td>669 Spruce St, Los Angeles, CA 90001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>176560</td>\n",
       "      <td>Wired Headphones</td>\n",
       "      <td>1</td>\n",
       "      <td>11.99</td>\n",
       "      <td>04/12/19 14:38</td>\n",
       "      <td>669 Spruce St, Los Angeles, CA 90001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18378</th>\n",
       "      <td>194090</td>\n",
       "      <td>Google Phone</td>\n",
       "      <td>1</td>\n",
       "      <td>600</td>\n",
       "      <td>04/08/19 17:11</td>\n",
       "      <td>177 Jackson St, Los Angeles, CA 90001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18379</th>\n",
       "      <td>194091</td>\n",
       "      <td>AA Batteries (4-pack)</td>\n",
       "      <td>1</td>\n",
       "      <td>3.84</td>\n",
       "      <td>04/15/19 16:02</td>\n",
       "      <td>311 Forest St, Austin, TX 73301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18380</th>\n",
       "      <td>194092</td>\n",
       "      <td>AAA Batteries (4-pack)</td>\n",
       "      <td>2</td>\n",
       "      <td>2.99</td>\n",
       "      <td>04/28/19 14:36</td>\n",
       "      <td>347 Sunset St, San Francisco, CA 94016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18381</th>\n",
       "      <td>194093</td>\n",
       "      <td>AA Batteries (4-pack)</td>\n",
       "      <td>1</td>\n",
       "      <td>3.84</td>\n",
       "      <td>04/14/19 15:09</td>\n",
       "      <td>835 Lake St, Portland, OR 97035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18382</th>\n",
       "      <td>194094</td>\n",
       "      <td>Lightning Charging Cable</td>\n",
       "      <td>1</td>\n",
       "      <td>14.95</td>\n",
       "      <td>04/18/19 11:08</td>\n",
       "      <td>354 North St, Boston, MA 02215</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>18383 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Order ID                     Product Quantity Ordered Price Each  \\\n",
       "0       176558        USB-C Charging Cable                2      11.95   \n",
       "1          NaN                         NaN              NaN        NaN   \n",
       "2       176559  Bose SoundSport Headphones                1      99.99   \n",
       "3       176560                Google Phone                1        600   \n",
       "4       176560            Wired Headphones                1      11.99   \n",
       "...        ...                         ...              ...        ...   \n",
       "18378   194090                Google Phone                1        600   \n",
       "18379   194091       AA Batteries (4-pack)                1       3.84   \n",
       "18380   194092      AAA Batteries (4-pack)                2       2.99   \n",
       "18381   194093       AA Batteries (4-pack)                1       3.84   \n",
       "18382   194094    Lightning Charging Cable                1      14.95   \n",
       "\n",
       "           Order Date                        Purchase Address  \n",
       "0      04/19/19 08:46            917 1st St, Dallas, TX 75001  \n",
       "1                 NaN                                     NaN  \n",
       "2      04/07/19 22:30       682 Chestnut St, Boston, MA 02215  \n",
       "3      04/12/19 14:38    669 Spruce St, Los Angeles, CA 90001  \n",
       "4      04/12/19 14:38    669 Spruce St, Los Angeles, CA 90001  \n",
       "...               ...                                     ...  \n",
       "18378  04/08/19 17:11   177 Jackson St, Los Angeles, CA 90001  \n",
       "18379  04/15/19 16:02         311 Forest St, Austin, TX 73301  \n",
       "18380  04/28/19 14:36  347 Sunset St, San Francisco, CA 94016  \n",
       "18381  04/14/19 15:09         835 Lake St, Portland, OR 97035  \n",
       "18382  04/18/19 11:08          354 North St, Boston, MA 02215  \n",
       "\n",
       "[18383 rows x 6 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "184ca46f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sales_April_2019.csv\n",
      "Sales_August_2019.csv\n",
      "Sales_December_2019.csv\n",
      "Sales_February_2019.csv\n",
      "Sales_January_2019.csv\n",
      "Sales_July_2019.csv\n",
      "Sales_June_2019.csv\n",
      "Sales_March_2019.csv\n",
      "Sales_May_2019.csv\n",
      "Sales_November_2019.csv\n",
      "Sales_October_2019.csv\n",
      "Sales_September_2019.csv\n"
     ]
    }
   ],
   "source": [
    "#printing all files name\n",
    "files=[file for file in os.listdir('./Sales_Data')]\n",
    "for file in files:\n",
    "    print(file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "62c3f0b0",
   "metadata": {},
   "outputs": [],
   "source": [
    " # creating an empty dataframe to get the merge files\n",
    "all_months_data = pd.DataFrame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "51ddb25c",
   "metadata": {},
   "outputs": [],
   "source": [
    "for file in files:\n",
    "    df=pd.read_csv(\"./Sales_Data/\"+file)\n",
    "    all_months_data=pd.concat([all_months_data,df])\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "33b9b4f1",
   "metadata": {},
   "outputs": [],
   "source": [
    "#writing the merged dataframe into a csv file\n",
    "all_months_data.to_csv(\"all_data.csv\",index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "ecee885d",
   "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>Order ID</th>\n",
       "      <th>Product</th>\n",
       "      <th>Quantity Ordered</th>\n",
       "      <th>Price Each</th>\n",
       "      <th>Order Date</th>\n",
       "      <th>Purchase Address</th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>176558</td>\n",
       "      <td>USB-C Charging Cable</td>\n",
       "      <td>2</td>\n",
       "      <td>11.95</td>\n",
       "      <td>04/19/19 08:46</td>\n",
       "      <td>917 1st St, Dallas, TX 75001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>176559</td>\n",
       "      <td>Bose SoundSport Headphones</td>\n",
       "      <td>1</td>\n",
       "      <td>99.99</td>\n",
       "      <td>04/07/19 22:30</td>\n",
       "      <td>682 Chestnut St, Boston, MA 02215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>176560</td>\n",
       "      <td>Google Phone</td>\n",
       "      <td>1</td>\n",
       "      <td>600</td>\n",
       "      <td>04/12/19 14:38</td>\n",
       "      <td>669 Spruce St, Los Angeles, CA 90001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>176560</td>\n",
       "      <td>Wired Headphones</td>\n",
       "      <td>1</td>\n",
       "      <td>11.99</td>\n",
       "      <td>04/12/19 14:38</td>\n",
       "      <td>669 Spruce St, Los Angeles, CA 90001</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Order ID                     Product Quantity Ordered Price Each  \\\n",
       "0   176558        USB-C Charging Cable                2      11.95   \n",
       "1      NaN                         NaN              NaN        NaN   \n",
       "2   176559  Bose SoundSport Headphones                1      99.99   \n",
       "3   176560                Google Phone                1        600   \n",
       "4   176560            Wired Headphones                1      11.99   \n",
       "\n",
       "       Order Date                      Purchase Address  \n",
       "0  04/19/19 08:46          917 1st St, Dallas, TX 75001  \n",
       "1             NaN                                   NaN  \n",
       "2  04/07/19 22:30     682 Chestnut St, Boston, MA 02215  \n",
       "3  04/12/19 14:38  669 Spruce St, Los Angeles, CA 90001  \n",
       "4  04/12/19 14:38  669 Spruce St, Los Angeles, CA 90001  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_data = pd.read_csv(\"all_data.csv\")\n",
    "all_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "87b26cac",
   "metadata": {},
   "outputs": [],
   "source": [
    "#adding a city column\n",
    "def get_city(address):\n",
    "    return address.split(',')[1]\n",
    "all_data['City']=all_data['Purchase Address'].apply(lambda x:get_city(x))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "06ecb902",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Adding a month column\n",
    "all_data['Month']=all_data['Order Date'].str[0:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "28e26a16",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Order ID</th>\n",
       "      <th>Product</th>\n",
       "      <th>Quantity Ordered</th>\n",
       "      <th>Price Each</th>\n",
       "      <th>Order Date</th>\n",
       "      <th>Purchase Address</th>\n",
       "      <th>Month</th>\n",
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       "  </thead>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>356</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>735</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1433</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1553</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Order ID Product Quantity Ordered Price Each Order Date Purchase Address  \\\n",
       "1         NaN     NaN              NaN        NaN        NaN              NaN   \n",
       "356       NaN     NaN              NaN        NaN        NaN              NaN   \n",
       "735       NaN     NaN              NaN        NaN        NaN              NaN   \n",
       "1433      NaN     NaN              NaN        NaN        NaN              NaN   \n",
       "1553      NaN     NaN              NaN        NaN        NaN              NaN   \n",
       "\n",
       "     Month  \n",
       "1      NaN  \n",
       "356    NaN  \n",
       "735    NaN  \n",
       "1433   NaN  \n",
       "1553   NaN  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Cleanup the data\n",
    "nan_df=all_data[all_data.isna().any(axis=1)]\n",
    "nan_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "095412f3",
   "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>Order ID</th>\n",
       "      <th>Product</th>\n",
       "      <th>Quantity Ordered</th>\n",
       "      <th>Price Each</th>\n",
       "      <th>Order Date</th>\n",
       "      <th>Purchase Address</th>\n",
       "      <th>Month</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>176558</td>\n",
       "      <td>USB-C Charging Cable</td>\n",
       "      <td>2</td>\n",
       "      <td>11.95</td>\n",
       "      <td>04/19/19 08:46</td>\n",
       "      <td>917 1st St, Dallas, TX 75001</td>\n",
       "      <td>04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>176559</td>\n",
       "      <td>Bose SoundSport Headphones</td>\n",
       "      <td>1</td>\n",
       "      <td>99.99</td>\n",
       "      <td>04/07/19 22:30</td>\n",
       "      <td>682 Chestnut St, Boston, MA 02215</td>\n",
       "      <td>04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>176560</td>\n",
       "      <td>Google Phone</td>\n",
       "      <td>1</td>\n",
       "      <td>600</td>\n",
       "      <td>04/12/19 14:38</td>\n",
       "      <td>669 Spruce St, Los Angeles, CA 90001</td>\n",
       "      <td>04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>176560</td>\n",
       "      <td>Wired Headphones</td>\n",
       "      <td>1</td>\n",
       "      <td>11.99</td>\n",
       "      <td>04/12/19 14:38</td>\n",
       "      <td>669 Spruce St, Los Angeles, CA 90001</td>\n",
       "      <td>04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>176561</td>\n",
       "      <td>Wired Headphones</td>\n",
       "      <td>1</td>\n",
       "      <td>11.99</td>\n",
       "      <td>04/30/19 09:27</td>\n",
       "      <td>333 8th St, Los Angeles, CA 90001</td>\n",
       "      <td>04</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Order ID                     Product Quantity Ordered Price Each  \\\n",
       "0   176558        USB-C Charging Cable                2      11.95   \n",
       "2   176559  Bose SoundSport Headphones                1      99.99   \n",
       "3   176560                Google Phone                1        600   \n",
       "4   176560            Wired Headphones                1      11.99   \n",
       "5   176561            Wired Headphones                1      11.99   \n",
       "\n",
       "       Order Date                      Purchase Address Month  \n",
       "0  04/19/19 08:46          917 1st St, Dallas, TX 75001    04  \n",
       "2  04/07/19 22:30     682 Chestnut St, Boston, MA 02215    04  \n",
       "3  04/12/19 14:38  669 Spruce St, Los Angeles, CA 90001    04  \n",
       "4  04/12/19 14:38  669 Spruce St, Los Angeles, CA 90001    04  \n",
       "5  04/30/19 09:27     333 8th St, Los Angeles, CA 90001    04  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_data=all_data.dropna(how='all')\n",
    "all_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "8c0e0587",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Order ID</th>\n",
       "      <th>Product</th>\n",
       "      <th>Quantity Ordered</th>\n",
       "      <th>Price Each</th>\n",
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       "  <tbody>\n",
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       "      <th>519</th>\n",
       "      <td>Order ID</td>\n",
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       "      <td>Price Each</td>\n",
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       "      <td>Or</td>\n",
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       "      <th>1149</th>\n",
       "      <td>Order ID</td>\n",
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       "    <tr>\n",
       "      <th>1155</th>\n",
       "      <td>Order ID</td>\n",
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       "      <td>Order Date</td>\n",
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       "      <td>Or</td>\n",
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       "    <tr>\n",
       "      <th>2878</th>\n",
       "      <td>Order ID</td>\n",
       "      <td>Product</td>\n",
       "      <td>Quantity Ordered</td>\n",
       "      <td>Price Each</td>\n",
       "      <td>Order Date</td>\n",
       "      <td>Purchase Address</td>\n",
       "      <td>Or</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2893</th>\n",
       "      <td>Order ID</td>\n",
       "      <td>Product</td>\n",
       "      <td>Quantity Ordered</td>\n",
       "      <td>Price Each</td>\n",
       "      <td>Order Date</td>\n",
       "      <td>Purchase Address</td>\n",
       "      <td>Or</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Order ID  Product  Quantity Ordered  Price Each  Order Date  \\\n",
       "519   Order ID  Product  Quantity Ordered  Price Each  Order Date   \n",
       "1149  Order ID  Product  Quantity Ordered  Price Each  Order Date   \n",
       "1155  Order ID  Product  Quantity Ordered  Price Each  Order Date   \n",
       "2878  Order ID  Product  Quantity Ordered  Price Each  Order Date   \n",
       "2893  Order ID  Product  Quantity Ordered  Price Each  Order Date   \n",
       "\n",
       "      Purchase Address Month  \n",
       "519   Purchase Address    Or  \n",
       "1149  Purchase Address    Or  \n",
       "1155  Purchase Address    Or  \n",
       "2878  Purchase Address    Or  \n",
       "2893  Purchase Address    Or  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp_df=all_data[all_data['Order Date'].str[0:2]=='Or']\n",
    "temp_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "3562bd70",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_data=all_data[all_data['Order Date'].str[0:2]!='Or']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "31393b7e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Order ID</th>\n",
       "      <th>Product</th>\n",
       "      <th>Quantity Ordered</th>\n",
       "      <th>Price Each</th>\n",
       "      <th>Order Date</th>\n",
       "      <th>Purchase Address</th>\n",
       "      <th>Month</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>176558</td>\n",
       "      <td>USB-C Charging Cable</td>\n",
       "      <td>2</td>\n",
       "      <td>11.95</td>\n",
       "      <td>04/19/19 08:46</td>\n",
       "      <td>917 1st St, Dallas, TX 75001</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>176559</td>\n",
       "      <td>Bose SoundSport Headphones</td>\n",
       "      <td>1</td>\n",
       "      <td>99.99</td>\n",
       "      <td>04/07/19 22:30</td>\n",
       "      <td>682 Chestnut St, Boston, MA 02215</td>\n",
       "      <td>4</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>176560</td>\n",
       "      <td>Google Phone</td>\n",
       "      <td>1</td>\n",
       "      <td>600</td>\n",
       "      <td>04/12/19 14:38</td>\n",
       "      <td>669 Spruce St, Los Angeles, CA 90001</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>176560</td>\n",
       "      <td>Wired Headphones</td>\n",
       "      <td>1</td>\n",
       "      <td>11.99</td>\n",
       "      <td>04/12/19 14:38</td>\n",
       "      <td>669 Spruce St, Los Angeles, CA 90001</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>176561</td>\n",
       "      <td>Wired Headphones</td>\n",
       "      <td>1</td>\n",
       "      <td>11.99</td>\n",
       "      <td>04/30/19 09:27</td>\n",
       "      <td>333 8th St, Los Angeles, CA 90001</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Order ID                     Product Quantity Ordered Price Each  \\\n",
       "0   176558        USB-C Charging Cable                2      11.95   \n",
       "2   176559  Bose SoundSport Headphones                1      99.99   \n",
       "3   176560                Google Phone                1        600   \n",
       "4   176560            Wired Headphones                1      11.99   \n",
       "5   176561            Wired Headphones                1      11.99   \n",
       "\n",
       "       Order Date                      Purchase Address  Month  \n",
       "0  04/19/19 08:46          917 1st St, Dallas, TX 75001      4  \n",
       "2  04/07/19 22:30     682 Chestnut St, Boston, MA 02215      4  \n",
       "3  04/12/19 14:38  669 Spruce St, Los Angeles, CA 90001      4  \n",
       "4  04/12/19 14:38  669 Spruce St, Los Angeles, CA 90001      4  \n",
       "5  04/30/19 09:27     333 8th St, Los Angeles, CA 90001      4  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_data['Month']=all_data['Month'].astype('int32')\n",
    "all_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "3d416553",
   "metadata": {},
   "outputs": [],
   "source": [
    "###Add a Sales column(Quantity * Price)\n",
    "# Converting column to integer for arithmatic operation\n",
    "all_data['Quantity Ordered']=pd.to_numeric(all_data['Quantity Ordered'])\n",
    "all_data['Price Each']=pd.to_numeric(all_data['Quantity Ordered'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "4a2cce22",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
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       "        text-align: right;\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>Product</th>\n",
       "      <th>Quantity Ordered</th>\n",
       "      <th>Price Each</th>\n",
       "      <th>Order Date</th>\n",
       "      <th>Purchase Address</th>\n",
       "      <th>Month</th>\n",
       "      <th>Sales</th>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>176558</td>\n",
       "      <td>USB-C Charging Cable</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>04/19/19 08:46</td>\n",
       "      <td>917 1st St, Dallas, TX 75001</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>176559</td>\n",
       "      <td>Bose SoundSport Headphones</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>04/07/19 22:30</td>\n",
       "      <td>682 Chestnut St, Boston, MA 02215</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>176560</td>\n",
       "      <td>Google Phone</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>04/12/19 14:38</td>\n",
       "      <td>669 Spruce St, Los Angeles, CA 90001</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>176560</td>\n",
       "      <td>Wired Headphones</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>04/12/19 14:38</td>\n",
       "      <td>669 Spruce St, Los Angeles, CA 90001</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>176561</td>\n",
       "      <td>Wired Headphones</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>04/30/19 09:27</td>\n",
       "      <td>333 8th St, Los Angeles, CA 90001</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Order ID                     Product  Quantity Ordered  Price Each  \\\n",
       "0   176558        USB-C Charging Cable                 2           2   \n",
       "2   176559  Bose SoundSport Headphones                 1           1   \n",
       "3   176560                Google Phone                 1           1   \n",
       "4   176560            Wired Headphones                 1           1   \n",
       "5   176561            Wired Headphones                 1           1   \n",
       "\n",
       "       Order Date                      Purchase Address  Month  Sales  \n",
       "0  04/19/19 08:46          917 1st St, Dallas, TX 75001      4      4  \n",
       "2  04/07/19 22:30     682 Chestnut St, Boston, MA 02215      4      1  \n",
       "3  04/12/19 14:38  669 Spruce St, Los Angeles, CA 90001      4      1  \n",
       "4  04/12/19 14:38  669 Spruce St, Los Angeles, CA 90001      4      1  \n",
       "5  04/30/19 09:27     333 8th St, Los Angeles, CA 90001      4      1  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_data['Sales']=all_data['Quantity Ordered']*all_data['Price Each']\n",
    "all_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f820235",
   "metadata": {},
   "source": [
    "### Question 1: What was the best month for sales? How much was earned that month?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "4c938215",
   "metadata": {},
   "outputs": [],
   "source": [
    "results=all_data.groupby('Month').sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "de16444e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "months = range(1,13)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "fc6dac79",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(months, results['Sales'])\n",
    "plt.xticks(months)\n",
    "plt.ylabel('Sales in USD($)')\n",
    "plt.xlabel('Months Number')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "01aad332",
   "metadata": {},
   "source": [
    "### Question 2:What city sold the most product?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "18a2b1c6",
   "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>Product</th>\n",
       "      <th>Quantity Ordered</th>\n",
       "      <th>Price Each</th>\n",
       "      <th>Order Date</th>\n",
       "      <th>Purchase Address</th>\n",
       "      <th>Month</th>\n",
       "      <th>Sales</th>\n",
       "      <th>City</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>176558</td>\n",
       "      <td>USB-C Charging Cable</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>04/19/19 08:46</td>\n",
       "      <td>917 1st St, Dallas, TX 75001</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>Dallas  (TX)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>176559</td>\n",
       "      <td>Bose SoundSport Headphones</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>04/07/19 22:30</td>\n",
       "      <td>682 Chestnut St, Boston, MA 02215</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>Boston  (MA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>176560</td>\n",
       "      <td>Google Phone</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>04/12/19 14:38</td>\n",
       "      <td>669 Spruce St, Los Angeles, CA 90001</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>Los Angeles  (CA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>176560</td>\n",
       "      <td>Wired Headphones</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>04/12/19 14:38</td>\n",
       "      <td>669 Spruce St, Los Angeles, CA 90001</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>Los Angeles  (CA)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>176561</td>\n",
       "      <td>Wired Headphones</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>04/30/19 09:27</td>\n",
       "      <td>333 8th St, Los Angeles, CA 90001</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>Los Angeles  (CA)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Order ID                     Product  Quantity Ordered  Price Each  \\\n",
       "0   176558        USB-C Charging Cable                 2           2   \n",
       "2   176559  Bose SoundSport Headphones                 1           1   \n",
       "3   176560                Google Phone                 1           1   \n",
       "4   176560            Wired Headphones                 1           1   \n",
       "5   176561            Wired Headphones                 1           1   \n",
       "\n",
       "       Order Date                      Purchase Address  Month  Sales  \\\n",
       "0  04/19/19 08:46          917 1st St, Dallas, TX 75001      4      4   \n",
       "2  04/07/19 22:30     682 Chestnut St, Boston, MA 02215      4      1   \n",
       "3  04/12/19 14:38  669 Spruce St, Los Angeles, CA 90001      4      1   \n",
       "4  04/12/19 14:38  669 Spruce St, Los Angeles, CA 90001      4      1   \n",
       "5  04/30/19 09:27     333 8th St, Los Angeles, CA 90001      4      1   \n",
       "\n",
       "                City  \n",
       "0       Dallas  (TX)  \n",
       "2       Boston  (MA)  \n",
       "3  Los Angeles  (CA)  \n",
       "4  Los Angeles  (CA)  \n",
       "5  Los Angeles  (CA)  "
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# adding a column for state \n",
    "\n",
    "def get_city(address):\n",
    "    return address.split(\",\")[1].strip(\" \")\n",
    "\n",
    "def get_state(address):\n",
    "    return address.split(\",\")[2].split(\" \")[1]\n",
    "\n",
    "all_data['City'] = all_data['Purchase Address'].apply(lambda x: f\"{get_city(x)}  ({get_state(x)})\")\n",
    "all_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a12e7787",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "e650da78",
   "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>Quantity Ordered</th>\n",
       "      <th>Price Each</th>\n",
       "      <th>Month</th>\n",
       "      <th>Sales</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>City</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Atlanta  (GA)</th>\n",
       "      <td>16602</td>\n",
       "      <td>16602</td>\n",
       "      <td>104794</td>\n",
       "      <td>21184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Austin  (TX)</th>\n",
       "      <td>11153</td>\n",
       "      <td>11153</td>\n",
       "      <td>69829</td>\n",
       "      <td>14469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Boston  (MA)</th>\n",
       "      <td>22528</td>\n",
       "      <td>22528</td>\n",
       "      <td>141112</td>\n",
       "      <td>29600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dallas  (TX)</th>\n",
       "      <td>16730</td>\n",
       "      <td>16730</td>\n",
       "      <td>104620</td>\n",
       "      <td>21964</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Los Angeles  (CA)</th>\n",
       "      <td>33289</td>\n",
       "      <td>33289</td>\n",
       "      <td>208325</td>\n",
       "      <td>43241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New York City  (NY)</th>\n",
       "      <td>27932</td>\n",
       "      <td>27932</td>\n",
       "      <td>175741</td>\n",
       "      <td>36106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Portland  (ME)</th>\n",
       "      <td>2750</td>\n",
       "      <td>2750</td>\n",
       "      <td>17144</td>\n",
       "      <td>3500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Portland  (OR)</th>\n",
       "      <td>11303</td>\n",
       "      <td>11303</td>\n",
       "      <td>70621</td>\n",
       "      <td>14849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>San Francisco  (CA)</th>\n",
       "      <td>50239</td>\n",
       "      <td>50239</td>\n",
       "      <td>315520</td>\n",
       "      <td>65223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Seattle  (WA)</th>\n",
       "      <td>16553</td>\n",
       "      <td>16553</td>\n",
       "      <td>104941</td>\n",
       "      <td>21407</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Quantity Ordered  Price Each   Month  Sales\n",
       "City                                                            \n",
       "Atlanta  (GA)                   16602       16602  104794  21184\n",
       "Austin  (TX)                    11153       11153   69829  14469\n",
       "Boston  (MA)                    22528       22528  141112  29600\n",
       "Dallas  (TX)                    16730       16730  104620  21964\n",
       "Los Angeles  (CA)               33289       33289  208325  43241\n",
       "New York City  (NY)             27932       27932  175741  36106\n",
       "Portland  (ME)                   2750        2750   17144   3500\n",
       "Portland  (OR)                  11303       11303   70621  14849\n",
       "San Francisco  (CA)             50239       50239  315520  65223\n",
       "Seattle  (WA)                   16553       16553  104941  21407"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_data.groupby(['City']).sum()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "28199b84",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "keys = [city for city, df in all_data.groupby(['City'])]\n",
    "\n",
    "plt.bar(keys,all_data.groupby(['City']).sum()['Sales'], color='g')\n",
    "plt.ylabel('Sales in USD ($)', color='r')\n",
    "plt.xlabel('Month number', color='r')\n",
    "plt.xticks(keys, rotation='vertical',size=8, color='b')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "548a5e81",
   "metadata": {},
   "source": [
    "### Question 3: What time should we display advertisements to maximize likelihood of customer's buying product?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "871f4d75",
   "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>Product</th>\n",
       "      <th>Quantity Ordered</th>\n",
       "      <th>Price Each</th>\n",
       "      <th>Order Date</th>\n",
       "      <th>Purchase Address</th>\n",
       "      <th>Month</th>\n",
       "      <th>Sales</th>\n",
       "      <th>City</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Minute</th>\n",
       "      <th>Count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>176558</td>\n",
       "      <td>USB-C Charging Cable</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>04/19/19 08:46</td>\n",
       "      <td>917 1st St, Dallas, TX 75001</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>Dallas  (TX)</td>\n",
       "      <td>8</td>\n",
       "      <td>46</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>176559</td>\n",
       "      <td>Bose SoundSport Headphones</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>04/07/19 22:30</td>\n",
       "      <td>682 Chestnut St, Boston, MA 02215</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>Boston  (MA)</td>\n",
       "      <td>22</td>\n",
       "      <td>30</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>176560</td>\n",
       "      <td>Google Phone</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>04/12/19 14:38</td>\n",
       "      <td>669 Spruce St, Los Angeles, CA 90001</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>Los Angeles  (CA)</td>\n",
       "      <td>14</td>\n",
       "      <td>38</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>176560</td>\n",
       "      <td>Wired Headphones</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>04/12/19 14:38</td>\n",
       "      <td>669 Spruce St, Los Angeles, CA 90001</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>Los Angeles  (CA)</td>\n",
       "      <td>14</td>\n",
       "      <td>38</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>176561</td>\n",
       "      <td>Wired Headphones</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>04/30/19 09:27</td>\n",
       "      <td>333 8th St, Los Angeles, CA 90001</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>Los Angeles  (CA)</td>\n",
       "      <td>9</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Order ID                     Product  Quantity Ordered  Price Each  \\\n",
       "0   176558        USB-C Charging Cable                 2           2   \n",
       "2   176559  Bose SoundSport Headphones                 1           1   \n",
       "3   176560                Google Phone                 1           1   \n",
       "4   176560            Wired Headphones                 1           1   \n",
       "5   176561            Wired Headphones                 1           1   \n",
       "\n",
       "       Order Date                      Purchase Address  Month  Sales  \\\n",
       "0  04/19/19 08:46          917 1st St, Dallas, TX 75001      4      4   \n",
       "2  04/07/19 22:30     682 Chestnut St, Boston, MA 02215      4      1   \n",
       "3  04/12/19 14:38  669 Spruce St, Los Angeles, CA 90001      4      1   \n",
       "4  04/12/19 14:38  669 Spruce St, Los Angeles, CA 90001      4      1   \n",
       "5  04/30/19 09:27     333 8th St, Los Angeles, CA 90001      4      1   \n",
       "\n",
       "                City  Hour  Minute  Count  \n",
       "0       Dallas  (TX)     8      46      1  \n",
       "2       Boston  (MA)    22      30      1  \n",
       "3  Los Angeles  (CA)    14      38      1  \n",
       "4  Los Angeles  (CA)    14      38      1  \n",
       "5  Los Angeles  (CA)     9      27      1  "
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Add hour column\n",
    "all_data['Hour'] = pd.to_datetime(all_data['Order Date']).dt.hour\n",
    "all_data['Minute'] = pd.to_datetime(all_data['Order Date']).dt.minute\n",
    "all_data['Count'] = 1\n",
    "all_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "f632b172",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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BAyGXyxEfH4+ZM2cCALKzs5Gamoply5YBAEJCQqBWq5GUlIQhQ4YAAA4ePAi1Wm1ohkJCQvDuu+8iOzsbnp6eAIC4uDgoFAoMHDjwttkUCgUUCsUtj8vlcpP+A7RUbVPnbC/ZTF2P2Vq+3pq9GQCABwd6w9vFwayyNdbMQd7YfjwXhy4W4d1f07AmYpDZZLOU77nckirEJGUCAJaEBcLa2rpF87XEa/W0k2PeyK74+LezWPHbeUzq09moS53m/D3SUvUaq8lfzbKyMqSkpCAlJQUAkJ6ejpSUFFy6dAm1tbV48MEHcfjwYXz99dfQarXIyclBTk6OYX0bpVKJuXPnYsmSJfjtt99w9OhRPPbYYwgODjbMwurZsycmTpyIefPm4cCBAzhw4ADmzZuHKVOmIDAwEAAQFhaGXr16ISIiAkePHsVvv/2GF154AfPmzeOMK6I27FhWMfacyYdMKsE/RncTO47RpFIJ3pkeDCupBDtP5OK3U9y52tQ+/eMcqmt1GOTrhJH+rmLHMdq8UV3hYm+N9Kvl+OZQpthxLE6TG53Dhw+jf//+6N+/PwBg8eLF6N+/P/75z38iKysL27dvR1ZWFvr16wdPT0/Dn7rZUgCwYsUKTJ8+HTNnzkRoaCjs7Ozw008/QSa7vhvx119/jeDgYISFhSEsLAx9+vTB5s2bDR+XyWT4+eefYWNjg9DQUMycORPTp0/Hv//97+Z8PYhIZP+5NtNqWl8VfFza9r1zgR4OmDvSDwDwzx9PoLJG28AzqLEuF1fiv9fO5iwOCxB9P6vm6KCwwqKx+kUEV+46i/Jq850a3xY1+dLVmDFjcLf7lxtzb7ONjQ1WrVqFVatW3XGMs7MztmzZctc6Pj4+2LFjR4Ofj4jahjO5pdh5Qn/m4+kxbfdszo2eG+uPHX9l43JxJT75/SxenthD7EgWYfXv51Cj1WFYV2cM79Z2z+bU+fsQH6zfl45LhRX4cl86Fl5rfKj5xN80hojomk+vnc2Z2NsD/u63vzenrbGztkLUtN4AgHV7LuBMbqnIidq+zMIKfHv4+r05lsDaSooXJuhfy5o9F1BQVt3AM6ix2OgQkVnIKCjH9r/0++I9c093kdOY1vhe7hjX0x21OgGv/5DaqDPfdGef/HYWtToBI/1dMbiLs9hxTGZKsCeCOjuirLrWsFgmNR8bHSIyC58nnIdOAEYHdEKwl+Uthx81rRds5TIkpRfiuyOXxY7TZqVfLcf3R/Vfv8XjA0ROY1pSqQSvTOwJANhyIIMbfpoIGx0iEl22uhL/l5wFAHj2Xss6m1PHy8kOz43T33cR/cspFJVz009jfPLbWWh1Au7t4Yb+Pk4NP6GNGeHvipH+rtBoBXwUx60hTIGNDhGJbu2eC9BoBQzxc7aoSxE3mzvCDwHuHVBYXoNlO0+LHafNOZdXih9S9Gdznh9nWWdzblR3w/oPKVeQelktcpq2j40OEYnqalk1/pt0CQDwrIXdm3MzuUyKdx8IBgD8NymTm3420cpdZyEIQFgvd4u8vFknqLMS0/rqN6xetpNndZqLjQ4RierLfemo0ujQx0vZphd9a6zBXZwxc5AXAOC1banQaNvWPl5iOZ1Tgh3HsgEAz1vYvTm380JYIOQyCfacycef566KHadNY6NDRKJRV2qweb9+u4dn7unephd9a4pXJvVERzs5TueUYuOfF8WO0yasjD8LAJgc7Imenpa/+r2Pix0eHeoLAHj/19PQ6ThTz1hsdIhINF8lXkRpdS0C3DtgfM/bb8ZriZztrfHqJP3smhW7zuBKcaXIicxb6mU1Yk/kQCIBIse1n4X0nr23O+ytZTh+WY1fUrPFjtNmsdEhIlGUV9fiyz/TAejP5kil7eNsTp0HB3phkK8TKmq0eOunE2LHMWsr4s8A0G8LYikLSTaGawcF5o/SrxD+4c40XuY0EhsdIhLFf5MuoahCAx9nO0wO9hQ7TquTSiV454EgbvrZgJTMYvx2Og9SiX47jfbmyZF+cO1gjYyCCmy9dtM+NQ0bHSJqdVUaLdbuuQAA+MeYbrCStc+3oh4ejoZNP9/czk0/b2f5tbM5MwZ4oWunDiKnaX32CitDg/fxb9zw0xjt892FiET1f8lZyCuthoejDWYM6Cx2HFE9N9YfnTvaIquoEqt+Pyt2HLNy+GIh9pzJh5VUgkX3tr+zOXUeGeKDLi52uFpWgy/2posdp81ho0NErapWq8PnCecBAPNHdYXCSiZyInHduOnn2j0XcJabfhrUnc15aJAXfFzsRE4jHrns+oafa/ecx1Vu+NkkbHSIqFVt/+sKsooq4WJvjb8P8RE7jlm4cdPP17jpJwBg//kCJJ4vgFwmsbhNXo1xX5An+ngpUV6jxerfueFnU7DRIaJWo9MJ+HS3/mzOEyP8YGvdvs/m3Iibfl4nCIJhptUjg33g5dR+z+bU0W/4qd8a4uuDGcgoKBc5UdvBRoeIWk3cqTycyyuDg40VIkJ8xY5jVm7e9LO4ov1u+rnv3FUkXSyEtZWUZ3NuMLy7K0YFdLq24ecZseO0GWx0iKhVCALwWYJ+ptXs4V3gaCMXOZH5uXHTzw9i2+emn4IgGO7NeXSoDzyUNiInMi8vT9Tfq7P9L2742VhsdIioVZwqluBkdils5TLMCfUTO45ZunnTzyOXisUNJIKEs1dx9FIxbORS/GNMN7HjmJ3eKiWm99Nv+Nlem+GmYqNDRC1OEATEXda/3Tw61AfO9tYiJzJfN276+eb2k9C2o/uSBQH4+Df9PVyPh3SBmwPP5tzOkmsbfu49exX7zhWIHcfssdEhohaXdLEI6aUSyGUSzBvVVew4Zs+w6WduGfZkt5+tMVKLJEi9UgI7axkW8Pvkjryd7fDYMP09bv+OPwPu93l3bHSIqMV9lqBf5OzBAZ3h7sjf0hty46afv2RKcaYdrK2j0wn4JVP/I2lOaBe4dFCInMi8PXtPd3RQWOHElVKkFLSfZtgYbHSIqEUdz1Ljz/MFkELAvJFdxI7TZjw40AshXZ1Ro5Pgyc1HkVtSJXakFrXzZC6uVEjQQWGFeSN5NqchLh0UhrNeOy5JUVPLDT/vhI0OEbWoH1P0a8L0dRHgzfVQGk0qleCTh/vCzUZAtroKT2w8ZLH7HBVX1GDltXtz5gz3QUc73sPVGHOvbfhZUC3Bz8dzxI5jttjoEFGLEQQBsSf0b8D9XXgjQVN1tJNjQU8tnO3lOHGlBM/GHEGt1rJ+c09KL8R9H+/FhavlsLMSMJvrKzWanbUVHh3iDQBsdO6CjQ4RtZgTV0qQVVQJG7kUPTuy0TGGqw2w9rEBsJFL8UdaPv65/YRFbBGh1Qn4eNdZPLJ2P66oq9DFxQ7P9NLC0ZbrKzXFpCAPAMCf5wugrtCInMY8sdEhohaz89rZnFH+ruBuD8br66XEJ4/0h0QCxBy8hDV7LogdqVmy1ZUIX3cAK3bpZwzNGNAZ2/4xDF72Yidre7p1sofKTkCtTsDOkzyrcztsdIioxcSm6t94w3q5i5yk7Qvr7YF/TukFAHj/19P46a8rIicyzq6Tubjv4704mF4Ie2sZVjzcF8tn9kMHhZXY0dqs/i76y5k/H8sWOYl5YqNDRC3iXF4ZzuaVQS6T4J4AV7HjWIQ5oX544tqq0kv+9xcOXSwUOVHjVddqEbX9BJ786jCKKjQI6uyIHYtG4oH+XmJHa/P6Xbv/7c9zV1FU3n73SLsTNjpE1CLqLlsN7+bK+y5M6LXJPTGhtztqtDrM++owzueXiR2pQefzy/DAfxKxMfEiAP2eXt/9Yzj8XHmtyhTcbIGeHg6o1QmI4+WrW7DRIaIWUXfZauK1myXJNGRSCVY+3B/9vDuiuEKDORsO4WpZtdixbksQBHx7OBNTV+3DyewSONtbY8PswXhjSi8orHjTlindF6S/PLyDl69uwUaHiEwuq6gCxy+rIZUA43l/jsnZWsvwxaxB8HG2w6XCCjy56TAqa7Rix6qntEqDyG9S8OL/HUNFjRbDu7ng1+dG4p4ebmJHs0h1s68SzxegkJev6mGjQ0Qmt/NELgD9BpWuXMq/Rbh2UGDjnMHoaCdHSmYxIr85Cq2ZbHp0LKsYU1btw48pVyCTSvDihEBsnjuU23+0IF8XOwR1doRWJxguG5MeGx0iMrmdvGzVKrp26oC1EYNgLZNi54lcvPvzKVHz6HQC1u25gL99loiMggp07miL/y0Yhmfu6Q6ZlPsxtbTJwSoAnH11MzY6RGRS+aXVOJShnw00oTcbnZY2xM8ZH83sCwD48s90bPgzXZQcV8uqMWfjIbz7yylotAImBXngl0UjMdDXWZQ87dHkYE8AQOL5qygw0/u2xMBGh4hMKv5kLgRBv8idqqOt2HHahal9VXh5Yg8AwNs7Trb6pYt9Z69i0sd7kXAmHworKd59IAifPjoASjvOtmtNPi52CO6shE6AYesVYqNDRCZW9wY7gZetWtVTo7sifKgPBAF4butRpGQWt/jn1OqAf8edRcSXB5FfWo0A9w7Y/uwIPDrUFxIJL1WJYXIf/VkdXr66jo0OEZmMulKDxHNXAQATedmqVUkkErw9rTfuCeyEKo0OczcewqWCihb5XDqdgKOZxfjkhAxr9qZDEIDwoT748ZkRCPRwaJHPSY1Td/nqwIUC5Jfy8hXARoeITOi3U7mo1QkIdHdA104dxI7T7ljJpFgdPgC9VY4oKK/B7I1JKK4wzVTjsupaxKZm48Vv/8KQ6F2YuTYJF8skcLCxwqePDkD0A8Gw5YZmovN2tkNfL16+uhE3FyEik6lbJJCXrcRjr7DCl7MH44H//IkL+eWYvzkZm+cOMWqBvoyCcvx2Kg+/n87DwfQCaLTXp693UFghoEMNPpoVAj83R1O+BGqmyX088VeWGj8fu4KIYb5ixxEdGx0iMomKmloknMkHwMtWYnN3tMGGOUPw4GeJSEovxIvfHsPKh/s1+DyNVofkjCL8fjoPv53Kxfn88nof7+Jih7E93TG2hxv6dnbArrhYeDnxhnNzc1+wJ6J/OY2D6YXIK62Cm0P7Xr+IjQ4RmURCWj6qa3XwcbZDT0/epyG2QA8HfB4xELO+TML2v67Ay8kWz4/tdsu4ovIaJJzJx2+n85CQloeSqlrDx6ykEgzu4oyxPd1wbw+3epcjNRpNq7wOajovJzv08+6IlMxi7EzNQURIF7EjiYqNDhGZRN39ABODPDjjxkyEdnfF+3/rgxe+/Quf7j4PT0cFHATgbG4ZEs4V4vfTuUjOKMKNCyo72clxT6Ab7u3phpH+naDkhqxt0pQ+nkjJLMaOY9lsdMQOQERtX3WtFr+fygPARQLNzYMDvZBVVIGVu84iascpKOUyFB5IrDemh4cD7u3hhrE93dDP24mrGFuAScGeeOfnU0i6WIi8kiq4tePtN9joEFGzJZ4vQGl1LdwcFOjv3VHsOHST58b6I6uoEv+XnIXCagmsraQI7eaCe3u6494ebujMhR0tTueOthjg0xFHLhXj19QczBreRexIomny9PI9e/Zg6tSpUKlUkEgk+OGHH+p9XBAEREVFQaVSwdbWFmPGjMGJEyfqjamursbChQvh6uoKe3t7TJs2DVlZWfXGFBUVISIiAkqlEkqlEhERESguLq435tKlS5g6dSrs7e3h6uqKRYsWoaaGu7YStba6va0m9PaAlGcDzI5EIsF7M4Lxzv298GSgFoeWjsGGOUMQMcyXTY4Fm9yHe18BRjQ65eXl6Nu3L1avXn3bjy9btgzLly/H6tWrcejQIXh4eGD8+PEoLS01jImMjMS2bduwdetW7Nu3D2VlZZgyZQq0Wq1hTHh4OFJSUhAbG4vY2FikpKQgIiLC8HGtVovJkyejvLwc+/btw9atW/Hdd99hyZIlTX1JRNQMtVod4k7qdyufxGnlZksuk+LhQV4IdhZgZ82T+e3BfcH64/FQRiFy1FUipxFPk7/bJ02ahEmTJt32Y4IgYOXKlXjttdcwY8YMAMCmTZvg7u6OmJgYLFiwAGq1GuvXr8fmzZsxbtw4AMCWLVvg7e2NXbt2YcKECTh16hRiY2Nx4MABDB06FACwbt06hISEIC0tDYGBgYiLi8PJkyeRmZkJlUrftX700UeYPXs23n33XTg6cl0HotZw6GIRCstr0NFOjiF+3MCRyFx4Km0x0NcJyRlF+DU1G3NC/cSOJAqTtvXp6enIyclBWFiY4TGFQoHRo0cjMTERCxYsQHJyMjQaTb0xKpUKQUFBSExMxIQJE7B//34olUpDkwMAw4YNg1KpRGJiIgIDA7F//34EBQUZmhwAmDBhAqqrq5GcnIx77rnnlnzV1dWorr6+JHZJSQkA/TRJU0+VrKtnirqmrGXqeuaczdT1mO32fjl+BQAwtkcnCDotNDrtLWMs5bW2dj1mM496bTnbxN5uSM4owo6/ruCxIV6tmq0l6t1ctzEkgiAIDQ+7w5MlEmzbtg3Tp08HACQmJiI0NBSXL1+u14DMnz8fGRkZ2LlzJ2JiYjBnzpx6DQcAhIWFwc/PD2vWrEF0dDQ2btyIM2fO1BsTEBCAOXPmYOnSpZg/fz4uXryIuLi4emMUCgU2btyIv//977fkjYqKwltvvXXL4zExMbCzszP2y0DUbukEIOqIDOoaCeb10CLIyei3EyJqAcXVwJtH9Oc03hpQi44KkQOZSEVFBcLDw6FWqxu8gtMiF2pvXkNDEIQG19W4ecztxhsz5kZLly7F4sWLDX8vKSmBt7c3wsLCTH6pS6PRID4+HuPHj4dc3rx1KExZqz1lM3U9ZrvVX1lqqA8chL21DM/NHAuF/PbbDFjCaxWjHrOZR722nu2ngiQczihGtXtv3Df87ltCmPNrvVHdFZnGMGmj4+Ghv/EpJycHnp6ehsfz8vLg7u5uGFNTU4OioiI4OTnVGzN8+HDDmNzc3Fvq5+fn16tz8ODBeh8vKiqCRqMxjLmZQqGAQnFrOyuXy036D9BStU2ds71kM3U9Zrtu12n9TuX39HBDB7uG1+loy69VzHrMZh712mq2KX1UOJxRjNgTuZg/unurZ2upeo1l0t3L/fz84OHhgfj4eMNjNTU1SEhIMDQxAwcOhFwurzcmOzsbqamphjEhISFQq9VISkoyjDl48CDUanW9MampqcjOvj5tLi4uDgqFAgMHDjTlyyKi2xAEAbGp+uNvImdbEZmtScGekEiAI5eKcbm4Uuw4ra7JZ3TKyspw7tw5w9/T09ORkpICZ2dn+Pj4IDIyEtHR0fD394e/vz+io6NhZ2eH8PBwAIBSqcTcuXOxZMkSuLi4wNnZGS+88AKCg4MNs7B69uyJiRMnYt68eVizZg0A/X0+U6ZMQWBgIAD9PT29evVCREQEPvzwQxQWFuKFF17AvHnzOOOKqBWcyS3DxYIKWFtJcU+gm9hxiOgO3B1tMLiLM5LSC/Hr8Ww8ObKr2JFaVZMbncOHD9eb0VR3z8usWbOwceNGvPTSS6isrMTTTz+NoqIiDB06FHFxcXBwuL7J34oVK2BlZYWZM2eisrISY8eOxcaNGyGTXb++//XXX2PRokWG2VnTpk2rt3aPTCbDzz//jKeffhqhoaGwtbVFeHg4/v3vfzf9q0BETfbrtbM5o/w7wV7BdVmIzNmUPp5ISi/EjmNsdBo0ZswY3G2ilkQiQVRUFKKiou44xsbGBqtWrcKqVavuOMbZ2Rlbtmy5axYfHx/s2LGjwcxEZHqxqdc38SQi8zYxyANvbj+BlMxiZBZWwNu5/cw0Nuk9OkTUPly8Wo7TOaWQSSUY15OXrYjMnZuDDYZeW9Cz7mxse8FGh4iabOcJ/dmckK4u6GhnLXIaImqM9rr3FRsdImqy2GuNzgRetiJqMyb29oBUol//KrOwQuw4rYaNDhE1SY66CkcvFUMiASb0uv2aVURkfjo5KDDUzwUA8Mvx9nNWh40OETVJ3En92ZwBPk5wc2x4kUAiMh+T++gX8/2ZjQ4R0e3VzbaaxMtWRG3OxCD95atjWWpcKmgfl6/Y6BBRoxWW1+BgeiEAYEJvNjpEbY1rBwVCuukvX7WXszpsdIio0XadzIVWJ6C3yrFdrcNBZEkmB1+bfXX8ishJWgcbHSJqtLrZVhN5NoeozZrQ2x0yqQSpl0tw8Wq52HFaHBsdImqU0ioN9p3V71bO1ZCJ2i6XDgoMb0eXr9joEFGj/JGWjxqtDl072aO7Wwex4xBRM0wOvjb7qh0sHshGh4gaZWfq9ctWEolE5DRE1BwTentAJpXgZHYJLuSXiR2nRbHRIaIGVWm0+CMtDwAwKchT5DRE1FxO9tYI7e4KwPIXD2SjQ0QN2nv2KipqtOjc0RZBnR3FjkNEJjDl2uWrHRZ++YqNDhE1qG6RwAm8bEVkMcJ6u8NKKsHpnFKcy7Pcy1dsdIjorjRaHXadygXA2VZElqSjXfu4fMVGh4ju6sCFAqgrNXDtYI2Bvk5ixyEiEzLsfWXBl6/Y6BDRXdVdthrfSz9Lg4gsx4ReHpDLJEjLLcW5vFKx47QINjpEdEdanYCdJ3jZishSKe3kGHHt8tXPx3JETtMy2OgQ0R2lZBbjalk1HGysENLVRew4RNQCJvex7L2v2OgQ0R3FndSvnTO+pzusrfh2QWSJxvdyh1wmwZncMpzNtbzZV3znIqLbEgQg7qT+stUEXrYislhKWzlG+XcCAPx6wvIuX7HRIaLbulwBZBVXwVYuM7wJEpFlqpt99UtqLgRB5DAmxkaHiG7rrwL928OYwE6wtZaJnIaIWtK4Xu6wlklxPr8c2ZVipzEtNjpEdFt/FeqnknO2FZHlc7SRY1SA/sxtylXLag0s69UQkUmcyytDbqUEcpkE9/RwEzsOEbWCKdcuXx0tsKz1stjoENEt4k/pZ1sN7+oCRxu5yGmIqDWM7ekGK6kEeVUSZBRUiB3HZNjoENEt6qaVT+jNszlE7YWDjRwDfDoCAPaduypuGBNio0NE9eSWVCH1SgkkEHBvIGdbEbUnI7rrFwbde65A5CSmw0aHiOrZcyYfAODTAXDpoBA5DRG1ppHXtoM4cKEQNbU6kdOYBhsdIqpn97VGp0dHC1tMg4ga1MvTAR2sBJTXaHHkUpHYcUyCjQ4RGdRqddh3Vn9tvmdHy/htjogaTyqVIPDaLzl1Z3fbOjY6RGTwV1Yx1JUaKG2t4NtB7DREJIa6s7l7z1rGDclsdIjIICFN/xvciG6ukFrWUhpE1EiBSn2jk3pFjYKyapHTNB8bHSIySLh2qnqkv4vISYhILEproId7BwiCZUwzZ6NDRACAgrJqHLusBgCM9HcVOQ0RiWnEtfeABAu4T4eNDhEB0F+PFwSgl6cj3Bw4rZyoPRtZt57O2asQ2vh25mx0iAgAsDtNvxryaC4SSNTuDfR1go1civzSapzOKRU7TrOw0SEi6HQC9lybYTEmgI0OUXunsJJiWFf9WZ22Ps2cjQ4RIfWKGoXlNXBQWGGAr5PYcYjIDIzy1//Ss+csGx0iauN2X5tWHtrdFXIZ3xaICBh17ezuofQiVNTUipzGeHxHIyLDzAren0NEdbp1skfnjrao0epw8EKh2HGMxkaHqJ1TV2hw9NqeNqN5fw4RXSORSDAqQD/NvC1fvmKjQ9TO7T2XD50ABLh3gKqjrdhxiMiMjKy7T6cN35DMRoeonavb9oFnc4joZqHXtoM5n1+Oy8WVYscxiskbndraWrz++uvw8/ODra0tunbtirfffhs63fWdkAVBQFRUFFQqFWxtbTFmzBicOHGiXp3q6mosXLgQrq6usLe3x7Rp05CVlVVvTFFRESIiIqBUKqFUKhEREYHi4mJTvyQiiyUIwvX7cwLcRE5DROZGaSdHP++OANruWR2TNzoffPABPv/8c6xevRqnTp3CsmXL8OGHH2LVqlWGMcuWLcPy5cuxevVqHDp0CB4eHhg/fjxKS68vShQZGYlt27Zh69at2LdvH8rKyjBlyhRotVrDmPDwcKSkpCA2NhaxsbFISUlBRESEqV8SkcU6lV2KvNJq2MplGOzHaeVEdKu62VdttdGxMnXB/fv34/7778fkyZMBAF26dMF///tfHD58GID+N8iVK1fitddew4wZMwAAmzZtgru7O2JiYrBgwQKo1WqsX78emzdvxrhx4wAAW7Zsgbe3N3bt2oUJEybg1KlTiI2NxYEDBzB06FAAwLp16xASEoK0tDQEBgaa+qURWZy6sznDu7lAYSUTOQ0RmaNRAZ2wctdZ/HnuKmq1Oli1sSUoTN7ojBgxAp9//jnOnDmDgIAA/PXXX9i3bx9WrlwJAEhPT0dOTg7CwsIMz1EoFBg9ejQSExOxYMECJCcnQ6PR1BujUqkQFBSExMRETJgwAfv374dSqTQ0OQAwbNgwKJVKJCYm3rbRqa6uRnX19S3nS0pKAAAajQYajcakX4e6eqaoa8papq5nztlMXc8Ss/1xOhcAMKK7c73nWuJrbYv1mM086rX3bL3c7eFoY4WSqlocuViA/j4dRct3c93GkAgm3q1LEAS8+uqr+OCDDyCTyaDVavHuu+9i6dKlAIDExESEhobi8uXLUKlUhufNnz8fGRkZ2LlzJ2JiYjBnzpx6TQkAhIWFwc/PD2vWrEF0dDQ2btyIM2fO1BsTEBCAOXPmGD7fjaKiovDWW2/d8nhMTAzs7OxM8fKJ2oyqWmDpYRl0ggRv9K+Fq43YiYjIXG1IkyKlUIqJXjpM8tY1/IQWVlFRgfDwcKjVajg6Ot51rMnP6HzzzTfYsmULYmJi0Lt3b6SkpCAyMhIqlQqzZs0yjJNIJPWeJwjCLY/d7OYxtxt/tzpLly7F4sWLDX8vKSmBt7c3wsLCGvxCNZVGo0F8fDzGjx8PuVxuNrXaUzZT17O0bHEnc6E79Be6uNjh8RkjWiybqeuZczZT12M286jHbECZWxZSfjyJHIkT7rtv6F0qtGy+OnVXZBrD5I3Oiy++iFdeeQWPPPIIACA4OBgZGRl47733MGvWLHh4eAAAcnJy4OnpaXheXl4e3N3dAQAeHh6oqalBUVERnJyc6o0ZPny4YUxubu4tnz8/P99Q52YKhQIKheKWx+VyuUn/AVqqtqlztpdspq5nKdn2ndcvEjgm0O2Oz7GU19rW6zGbedRrz9nu6ekB/HgSx7LUqNDoZ2OJna+xTH5HUUVFBaTS+mVlMplhermfnx88PDwQHx9v+HhNTQ0SEhIMTczAgQMhl8vrjcnOzkZqaqphTEhICNRqNZKSkgxjDh48CLVabRhDRLcnCIJhBgW3fSCihqg62qK7WwfoBODP81fFjtMkJj+jM3XqVLz77rvw8fFB7969cfToUSxfvhxPPPEEAP3lpsjISERHR8Pf3x/+/v6Ijo6GnZ0dwsPDAQBKpRJz587FkiVL4OLiAmdnZ7zwwgsIDg42zMLq2bMnJk6ciHnz5mHNmjUA9Pf5TJkyhTOuiBpwLq8Ml4srYW0lxTA/F7HjEFEbMMq/E87llWHPmXzcF+zZ8BPMhMkbnVWrVuGNN97A008/jby8PKhUKixYsAD//Oc/DWNeeuklVFZW4umnn0ZRURGGDh2KuLg4ODg4GMasWLECVlZWmDlzJiorKzF27Fhs3LgRMtn1KbBff/01Fi1aZJidNW3aNKxevdrUL4nI4tRNKx/W1QW21pxWTkQNGxngii//TMeeM/mNuq/WXJi80XFwcMDKlSsN08lvRyKRICoqClFRUXccY2Njg1WrVtVbaPBmzs7O2LJlSzPSErVP11dD5mUrImqcYX4usLaS4oq6Cufzy9DdzaHhJ5mBtrXqDxE1W0VNLQ5eKATARoeIGs/WWoYhXZwBAAln2s59Omx0iNqZAxcKUKPVwcvJFt062Ysdh4jakFEBrgCAvWfbznYQbHSI2pndN+xW3lausROReajb9+rAhQJUabQNjDYPbHSI2hnen0NExgp0d4CbgwJVGh0OXywSO06jsNEhakcuXi1HRkEF5DIJhnd3FTsOEbUxEokEI/2v7WbeRi5fsdEhakd2p+UBAAb5OqODwuSTLomoHai7T6du0VFzx0aHqB2pu2w1hqshE5GRRvp3gkQCnM4pRV5JldhxGsRGh6idqNJosf9CAQBu+0BExnO2t0ZwZyUAYM9Z859mzkaHqJ1ISi9ElUYHD0cbBLq3jYW+iMg8jfRvO5ev2OgQtRM3zrbitHIiao5R125I3nfuKnQ6QeQ0d8dGh6idqLsRmZetiKi5Bvg6oYPCCoXlNUi9ohY7zl2x0SFqBzILK3A+vxwyqQShnFZORM0kl0kR0s0FALDXzO/TYaND1A7UrXcxwKcjlLZykdMQkSWoWyU5wczv02GjQ9QO3LjtAxGRKYy+dp/OkYwilFZpRE5zZ2x0iCxcTa0Oief0p5ZHB7iJnIaILIWPix18XexQqxOw/3yB2HHuiI0OkYU7nFGI8hotXDtYo7fKUew4RGRBRrWB7SDY6BBZuLrr56P8O0Eq5bRyIjKduvt0zPmGZDY6RBYuoe7+HE4rJyITC+nmAiupBBkFFcgoKBc7zm2x0SGyYDnqKpzOKYVEAsOOw0REptJBYYWBvk4AzHeVZDY6RBas7o2nj1dHONtbi5yGiCzR9Wnm5nn5io0OkQXbfUa/GvIYTisnohZSd0Py/vNXUVOrEznNrdjoEFmoWq3OcIMg788hopbSW+UIF3trlNdocfRSkdhxbsFGh8hCpWQWo7SqFh3t5Ojr1VHsOERkoaRSCUbU7WZuhtPM2egQWai61ZBH+neCjNPKiagFGdbTMcP7dNjoEFmouvVzuO0DEbW0kdfO6KReUaOgrFrkNPWx0SGyQFfLqnH8shoAMCqAu5UTUctyc7RBDw8HCAKw75x5ndVho0NkgeqmlfdWOcLNwUbkNETUHtSdPTa3y1dsdIgsEC9bEVFru74dRD4EQRA5zXVsdIgsjFYnGM7ojAnkbuVE1DoGdXGCjVyKvNJqnM4pFTuOARsdIgtz/LIaRRUaOCis0N+no9hxiKidUFjJMKyrCwDz2g6CjQ6RhanbxDO0uyvkMh7iRNR66qaZm9Nu5nwXJLIwhm0fuBoyEbWyuvt0ki4WorJGK3IaPTY6RBakqKIGf2UWA7j+hkNE1Fq6dbJH5462qKnV4UB6gdhxALDRIbIof54rgE4AAtw7QNXRVuw4RNTOSCQSw9pd5nKfDhsdIguy55z+NyjOtiIisYw0bAfBRoeITEgnXL8BkOvnEJFYQru5QioBzueX40pxpdhx2OgQWYorFcDVshrYWcswqIuT2HGIqJ1S2snRz7sjAGDfOfHv02GjQ2QhThXrdygf3s0FCiuZyGmIqD0zrJLMRoeITOVUkf5w5mUrIhJbXaOTeL4AWpF3g2CjQ2QBSqs0SL+24vroAN6ITETi6uvVEY42ViipqsWlMnGzsNEhsgCJ5wuhgwR+LnbwcbETOw4RtXMyqQQj/PXTzE9fu6wuFjY6RBZg9xn9bKuR195YiIjEVrcdRFG1uI2OlaifnYiaTasT8Ntp/bYPY3vw/hwiMg+T+3hiTIALDibsEjUHGx2iNu7wxUIUVWhgJxMwmNPKichMONjIYWMGE0Bb5NLV5cuX8dhjj8HFxQV2dnbo168fkpOTDR8XBAFRUVFQqVSwtbXFmDFjcOLEiXo1qqursXDhQri6usLe3h7Tpk1DVlZWvTFFRUWIiIiAUqmEUqlEREQEiouLW+IlEZmtuJO5AIDeTgJ3KyciuonJ3xWLiooQGhoKuVyOX3/9FSdPnsRHH32Ejh07GsYsW7YMy5cvx+rVq3Ho0CF4eHhg/PjxKC0tNYyJjIzEtm3bsHXrVuzbtw9lZWWYMmUKtNrru6GGh4cjJSUFsbGxiI2NRUpKCiIiIkz9kojMliAIiDuZAwAIdhZ5DicRkRky+aWrDz74AN7e3tiwYYPhsS5duhj+XxAErFy5Eq+99hpmzJgBANi0aRPc3d0RExODBQsWQK1WY/369di8eTPGjRsHANiyZQu8vb2xa9cuTJgwAadOnUJsbCwOHDiAoUOHAgDWrVuHkJAQpKWlITAw0NQvjcjsnM4pRWZhJRRWUvToWCt2HCIis2PyMzrbt2/HoEGD8NBDD8HNzQ39+/fHunXrDB9PT09HTk4OwsLCDI8pFAqMHj0aiYmJAIDk5GRoNJp6Y1QqFYKCggxj9u/fD6VSaWhyAGDYsGFQKpWGMUSWbucJ/dmcEd1doDCDa+FERObG5Gd0Lly4gM8++wyLFy/Gq6++iqSkJCxatAgKhQKPP/44cnL0b8zu7u71nufu7o6MjAwAQE5ODqytreHk5HTLmLrn5+TkwM3t1oXR3NzcDGNuVl1djerqasPfS0pKAAAajQYajcbIV3x7dfVMUdeUtUxdz5yzmbqeOWbbmar/Xr8nwAXIzzarbC1Vz5yzmboes5lHPWYzn3o3120MiSAIJr2wb21tjUGDBtU7q7Jo0SIcOnQI+/fvR2JiIkJDQ3HlyhV4enoaxsybNw+ZmZmIjY1FTEwM5syZU68pAYDx48ejW7du+PzzzxEdHY1NmzYhLS2t3hh/f3/MnTsXr7zyyi3ZoqKi8NZbb93yeExMDOzsuMgatS0FVcDbR60ggYB3BmnRQS52IiKi1lFRUYHw8HCo1Wo4OjredazJz+h4enqiV69e9R7r2bMnvvvuOwCAh4cHAP0ZmRsbnby8PMNZHg8PD9TU1KCoqKjeWZ28vDwMHz7cMCY3N/eWz5+fn3/L2aI6S5cuxeLFiw1/Lykpgbe3N8LCwhr8QjWVRqNBfHw8xo8fD7m8eT+BTFmrPWUzdT1zy7YhMQNAGgZ3ccYD9/Uzq2wtWc+cs5m6HrOZRz1mM596dequyDSGyRud0NDQW86ynDlzBr6+vgAAPz8/eHh4ID4+Hv379wcA1NTUICEhAR988AEAYODAgZDL5YiPj8fMmTMBANnZ2UhNTcWyZcsAACEhIVCr1UhKSsKQIUMAAAcPHoRarTY0QzdTKBRQKBS3PC6Xy036D9BStU2ds71kM3U9c8n22+l8AMCEIE/D880lW2vUM+dspq7HbOZRj9nMq15jmbzRef755zF8+HBER0dj5syZSEpKwtq1a7F27VoAgEQiQWRkJKKjo+Hv7w9/f39ER0fDzs4O4eHhAAClUom5c+diyZIlcHFxgbOzM1544QUEBwcbZmH17NkTEydOxLx587BmzRoAwPz58zFlyhTOuCKLV1heg0MXCwEAYb1ufwaTiIhaoNEZPHgwtm3bhqVLl+Ltt9+Gn58fVq5ciUcffdQw5qWXXkJlZSWefvppFBUVYejQoYiLi4ODg4NhzIoVK2BlZYWZM2eisrISY8eOxcaNGyGTXZ9a8vXXX2PRokWG2VnTpk3D6tWrTf2SiMzOrlO50AlAL09HeDvbmfxGPyIiS9EiW0BMmTIFU6ZMuePHJRIJoqKiEBUVdccxNjY2WLVqFVatWnXHMc7OztiyZUtzohK1SXEn9PenhfXm2RwiorvhevFEbUxFTS32ntXfnxPWy0PkNERE5o2NDlEbs+dMPqprdfB2tkVPT4eGn0BE1I6x0SFqYwyXrXp5QCKRiJyGiMi8sdEhakM0Wh1+O50HgLOtiIgag40OURuSlF4IdaUGzvbWGNTFWew4RERmj40OURsSd20Tz3E93SCT8rIVEVFD2OgQtRGCICDu5PX7c4iIqGFsdIjaiOOX1chWV8HOWoYR/q5ixyEiahPY6BC1EXWzrUYHdIKNXNbAaCIiAtjoELUZcSf19+dwNWQiosZjo0PUBqRfLceZ3DJYSSW4N5CNDhFRY7HRIWoD6mZbDevqAqWdXOQ0RERtBxsdojbAMNuKl62IiJqEjQ6RmcsrrcKRS0UAgPFcDZmIqEnY6BCZuV0n8yAIQF8vJTyVtmLHISJqU9joEJm567OtuEggEVFTsdEhMmOlVRoknisAAEzg/TlERE3GRofIjO1Oy0eNVoeurvbo1qmD2HGIiNocNjpEZqxuttX43u6QSLiJJxFRU7HRITJT1bVa/HE6DwAwgffnEBEZhY0OkZnaf74AZdW16OSgQD+vjmLHISJqk9joEJkpw2WrXu6QSnnZiojIGGx0iMyQTicg/lqjw8tWRETGY6NDZIaOZhYjv7QaDgorhHR1ETsOEVGbxUaHyAzVLRI4pocbrK14mBIRGYvvoERmRhAExJ2ou2zFRQKJiJqDjQ6RmTmXV4b0q+WwlkkxOqCT2HGIiNo0NjpEZqZuttXw7i5wsJGLnIaIqG1jo0NkZuJO6O/P4WwrIqLmY6NDZEay1ZX4K0sNiQQY29NN7DhERG0eGx0iM1K3ds4AHye4OdiInIaIqO1jo0NkRjjbiojItNjoEJkJdYUGBy4UAADG9+L9OUREpsBGh8hM/J6Wi1qdgAD3DvBztRc7DhGRRWCjQ2Qmrl+24tkcIiJTYaNDZAaqNFrsTssHAITxshURkcmw0SEyA/vOXkWlRguV0gZBnR3FjkNEZDHY6BCZgbpNPMN6e0AikYichojIcrDRIRJZrVaHXafyAABhvTitnIjIlNjoEInsSGYxCstroLSVY7Cfs9hxiIgsChsdIpHtOqW/CXlsTzfIZTwkiYhMyUrsAETtmSAA8af008o524qIyPT46yORiK5UAFnFVVBYSTEqwFXsOEREFoeNDpGIjhXqZ1iNCugEO2ueYCUiMjU2OkQiOl6oPwQ524qIqGW0eKPz3nvvQSKRIDIy0vCYIAiIioqCSqWCra0txowZgxMnTtR7XnV1NRYuXAhXV1fY29tj2rRpyMrKqjemqKgIERERUCqVUCqViIiIQHFxcUu/JCKTyCyqwOUKCaQSYGxPNjpERC2hRRudQ4cOYe3atejTp0+9x5ctW4bly5dj9erVOHToEDw8PDB+/HiUlpYaxkRGRmLbtm3YunUr9u3bh7KyMkyZMgVardYwJjw8HCkpKYiNjUVsbCxSUlIQERHRki+JyGTqZlsN7uIEZ3trkdMQEVmmFmt0ysrK8Oijj2LdunVwcnIyPC4IAlauXInXXnsNM2bMQFBQEDZt2oSKigrExMQAANRqNdavX4+PPvoI48aNQ//+/bFlyxYcP34cu3btAgCcOnUKsbGx+OKLLxASEoKQkBCsW7cOO3bsQFpaWku9LCKTib+2SOC4nm4iJyEislwtdvfjM888g8mTJ2PcuHF45513DI+np6cjJycHYWFhhscUCgVGjx6NxMRELFiwAMnJydBoNPXGqFQqBAUFITExERMmTMD+/fuhVCoxdOhQw5hhw4ZBqVQiMTERgYGBt2Sqrq5GdXW14e8lJSUAAI1GA41GY9LXX1fPFHVNWcvU9cw5m6nrmbLW1bJqJGcUAQDGdHdqdk1z/rqZup45ZzN1PWYzj3rMZj71bq7bGBJBEASTfnYAW7duxTvvvIPDhw/DxsYGY8aMQb9+/bBy5UokJiYiNDQUly9fhkqlMjxn/vz5yMjIwM6dOxETE4M5c+bUa0oAICwsDH5+flizZg2io6OxceNGnDlzpt6YgIAAzJkzB0uXLr0lV1RUFN56661bHo+JiYGdnZ2JXj1Rw36+JEXcZSm6dBDwfLC24ScQEZFBRUUFwsPDoVar4eh4942QTX5GJzMzE8899xzi4uJgY2Nzx3E3b1woCEKDmxnePOZ24+9WZ+nSpVi8eLHh7yUlJfD29kZYWFiDX6imEAQBv5/KxcWTR/D4/eMhl8ubVU+j0SA+Ph7jxze/lqnrmXM2U9czVa3y6lr886M9AGpxr0pnVtnaQj1zzmbqesxmHvWYzXzq1am7ItMYJm90kpOTkZeXh4EDBxoe02q12LNnD1avXm24fyYnJweenp6GMXl5eXB318888fDwQE1NDYqKiurd35OXl4fhw4cbxuTm5t7y+fPz8w11bqZQKKBQKG55XC6Xm/Qf4L1fT2FNwgUMcJFirglrmzqnKeuZczZT12turW1JWVBX1qKLix2CnUvMKltbqmfO2Uxdj9nMox6zmVe9xjL5zchjx47F8ePHkZKSYvgzaNAgPProo0hJSUHXrl3h4eGB+Ph4w3NqamqQkJBgaGIGDhwIuVxeb0x2djZSU1MNY0JCQqBWq5GUlGQYc/DgQajVasMYsUzrq78kl1IgweXiSlGzkHnRaHX4Ym86AGBuaBdI734Sk4iImsnkZ3QcHBwQFBRU7zF7e3u4uLgYHo+MjER0dDT8/f3h7++P6Oho2NnZITw8HACgVCoxd+5cLFmyBC4uLnB2dsYLL7yA4OBgjBs3DgDQs2dPTJw4EfPmzcOaNWsA6O/zmTJlym1vRG5NvVVKDO/mjMTzhdi0/xLenBbU8JOoXfjleDYuF1fCtYM1Hujnid/ij4kdiYjIoomy5vxLL72EyspKPP300ygqKsLQoUMRFxcHBwcHw5gVK1bAysoKM2fORGVlJcaOHYuNGzdCJpMZxnz99ddYtGiRYXbWtGnTsHr16lZ/PbczN7QLEs8X4n+HsxA5PhBKW9OdsqO2SRAEfJ5wAQAwJ9QPCrmsgWcQEVFztUqjs3v37np/l0gkiIqKQlRU1B2fY2Njg1WrVmHVqlV3HOPs7IwtW7aYKKVpjezuAk9bAdmVWmxNuoQFo7uJHYlEtvfsVZzKLoGdtQyPDfUVOw4RUbvAva5aiEQiwRiVDgCw4c+LqKnViZyIxLZmz3kAwN+H+EBpxzN8REStgY1OCxrkKqBTB2vklFTh5+NXxI5DIjqepcaf5wpgJZXgiRF+YschImo32Oi0ICsp8PgwHwDA2j3paIG1GamNqDubM62vCp072oqchoio/WCj08IeGewNW7kMp7JL8Oe5ArHjkAguFVTgl+PZAIB5o7qKnIaIqH1ho9PCOtrJ8fBgbwDAur0XRE5DYvhi3wXoBGB0QCf09DTdCtxERNQwNjqt4IlQP0glQMKZfKTllIodh1pRQVk1/nc4EwCwYDTP5hARtTY2Oq3Ax8UOE4M8APCsTnvz1f4MVGl06OOlREhXF7HjEBG1O2x0Wsm8kfrf5n9MuYy8kiqR01BrqKipxVf7LwIAFozq1uCmtUREZHpsdFpJfx8nDPJ1gkYrYGPiRbHjUCv49nAWiio08HG+fkaPiIhaFxudVlQ34+brg5dQXl0rchpqSbVaneEy5bxRXSHj7p1ERKJgo9OKxvV0RxcXO6grNfj22g2qZJl+Sc1BVlElXOyt8dBAL7HjEBG1W2x0WpFMKsHca/fqrP8zHVodFxC0RIIgYE2CfoHAWcO7wIabdxIRiYaNTit7cIAXnOzkyCysxM4TOWLHoRbw57kCnLhSAlu5DBHDuHknEZGY2Oi0Mlvr6z/81uy5wG0hLFDddg8PD/aGk721yGmIiNo3NjoiiAjpAmsrKf7KLMbhjCKx45AJpV5WY+/Zq/rLlNy8k4hIdGx0RNDJQYEZ/TsDANbt4QKClqRuptWUPp7wdrYTOQ0REbHREcmTI/W/7cefykX61XKR05ApZBZWYMcx/ead87l5JxGRWWCjI5Lubg64t4cbBAFYv49ndSzB+n36mXQj/V3RW6UUOw4REYGNjqjqtoX49nAWCsqqRU5DzVFUXoNvDl3bvHNUN5HTEBFRHTY6IhrW1RnBnZWortVhy4FLYsehZth8IAOVGi16qxwR2p2bdxIRmQs2OiKSSCSGe3W+2n8RVRqtyInIGFUarWH/sgWjuXknEZE5YaMjsvuCPdG5oy0Kymuw7ehlseOQEb5NzkJheQ28nGxxHzfvJCIyK2x0RCaXSTEntAsA4Iu9F6DjthBtilYnGJYImDeyK6xkPKSIiMwJ35XNwMODveGgsML5/HL8kZYndhxqgtjUHFwqrICTnRwPDeLmnURE5oaNjhlwsJEjfKgPAGAtFxBsMwRBwOfXNu98PKQL7KytRE5EREQ3Y6NjJmaHdoGVVIKD6YU4llUsdhxqhP0XCnD8sho2cikeD+HmnURE5oiNjpnwVNpial8VAGDd3nSR01BjrEnQn32bOcgbLh0UIqchIqLbYaNjRuqmmv9yPBtZRRUip6G7OZVdgoQz+ZBKgCdHcLsHIiJzxUbHjPRWKRHa3QVanYANf14UOw7dRd29VPcFe8LHhZt3EhGZKzY6ZqZuW4itSZegrtSInIZu53JxJbb/dQUAt3sgIjJ3bHTMzOiATghw74DyGi22JnFbCHO0MTEDWp2A0O4uCPbi5p1EROaMjY6Z0W8LoT+rs+HPi6ip1YmciG5UrgH+l6xfwXo+z+YQEZk9Njpm6P5+KnRyUCCnpAo7jl0ROw7d4M9cCSpqtOjh4YBR/q5ixyEiogaw0TFDCisZZg/vAkA/1VwQuC2EOajWaJGQoz9knuLmnUREbQIbHTP16FAf2MplOJVdgsQLhWLHIQDbUrJRppFApbTB5D6eYschIqJGYKNjpjraWWPmtb2TvuRUc9GVV9fiP7v12z3MHu4LOTfvJCJqE/hubcaeGOEHqQTYc7YAV7h+oKg++f0sckqq4aIQ8PfB3LyTiKitYKNjxnxd7DGhtwcA4I8r/KcSy5ncUqy/ti3HDD8dbOQykRMREVFj8aenmZs3Sj/VPPmqBNnqKpHTtD+CIOCNH1JRqxMwrkcnBDnxxnAioraEjY6ZG+DjhEG+HaEVJIj+NU3sOO3OjylXcDC9EDZyKV6f3EPsOERE1ERsdNqAf07uCSkExJ7IRfzJXLHjtBvqSg3e+fkUAGDhvf7o3NFW5ERERNRUbHTagJ6eDrhHpb9k8sYPqSit4h5YrWFF/BlcLatG1072hj3IiIiobWGj00ZM9NLBx9kWOSVV+HAnL2G1tNTLany1/yIA4F/3B8HaiocKEVFbxHfvNsJaBrw9rRcAYPOBDCRnFImcyHLpdAJe/yEVOgGY0scTod251QMRUVvFRqcNCe3mgr8N8IIgAEu/P8YNP1vI/w5nIiWzGB0UVnhjSi+x4xARUTOYvNF57733MHjwYDg4OMDNzQ3Tp09HWlr9Sy2CICAqKgoqlQq2trYYM2YMTpw4UW9MdXU1Fi5cCFdXV9jb22PatGnIysqqN6aoqAgRERFQKpVQKpWIiIhAcXGxqV+SWXl9ck+42FvjTG4ZPk84L3Yci1NYXoP3Y08DACLH+cPd0UbkRERE1Bwmb3QSEhLwzDPP4MCBA4iPj0dtbS3CwsJQXl5uGLNs2TIsX74cq1evxqFDh+Dh4YHx48ejtLTUMCYyMhLbtm3D1q1bsW/fPpSVlWHKlCnQarWGMeHh4UhJSUFsbCxiY2ORkpKCiIgIU78ks+Jkb41/TtWfZVj9+zmcyysTOZFlWRZ7GsUVGvTwcDBsrEpERG2XlakLxsbG1vv7hg0b4ObmhuTkZIwaNQqCIGDlypV47bXXMGPGDADApk2b4O7ujpiYGCxYsABqtRrr16/H5s2bMW7cOADAli1b4O3tjV27dmHChAk4deoUYmNjceDAAQwdOhQAsG7dOoSEhCAtLQ2BgYGmfmlmY1pfFb4/chkJZ/Lx6vfHsXX+MEil3Em7uY5cKsLWQ5kAgH9ND4IV97MiImrzTN7o3EytVgMAnJ2dAQDp6enIyclBWFiYYYxCocDo0aORmJiIBQsWIDk5GRqNpt4YlUqFoKAgJCYmYsKECdi/fz+USqWhyQGAYcOGQalUIjEx8baNTnV1Naqrqw1/LykpAQBoNBpoNKadsl1XzxR1b1crakoP3LeqAEkXCxFz8CIeHtT4/ZdaOltbrFer1eH1bccBADP6q9Cvs8MtzzHn12rO2Uxdz5yzmboes5lHPWYzn3o3120MiSAILbamvSAIuP/++1FUVIS9e/cCABITExEaGorLly9DpVIZxs6fPx8ZGRnYuXMnYmJiMGfOnHpNCQCEhYXBz88Pa9asQXR0NDZu3IgzZ87UGxMQEIA5c+Zg6dKlt+SJiorCW2+9dcvjMTExsLOzM8VLblV/XJHghwwZbGUClvbTQmktdqK2a0+2BN9d1H8tX+uvhYNc7ERERHQnFRUVCA8Ph1qthqOj413HtugZnWeffRbHjh3Dvn37bvmYRFL/UosgCLc8drObx9xu/N3qLF26FIsXLzb8vaSkBN7e3ggLC2vwC9VUGo0G8fHxGD9+POTy5v3UvFOtCToB59cexPHLJUis6oxV0/uaTba2VC+/tBqvffwngFq8cl8vPDzE22yyiVHL3OuZczZT12M286jHbOZTr07dFZnGaLFGZ+HChdi+fTv27NkDL6/rl1U8PPS7cefk5MDT09PweF5eHtzd3Q1jampqUFRUBCcnp3pjhg8fbhiTm3vrdgj5+fmGOjdTKBRQKBS3PC6Xy036D9BStW+uJQfwwd/6YurqfYg9kYvdZwsxvtftX3trZ2tL9T6MP4Gy6lr08VLisRA/yBq438mcX6s5ZzN1PXPOZup6zGYe9ZjNvOo1lsnvthQEAc8++yy+//57/P777/Dz86v3cT8/P3h4eCA+Pt7wWE1NDRISEgxNzMCBAyGXy+uNyc7ORmpqqmFMSEgI1Go1kpKSDGMOHjwItVptGNMe9FI5GrYn4PYQTbf/fAG2Hb0MiQR4Z3pQg00OERG1LSZvdJ555hls2bIFMTExcHBwQE5ODnJyclBZWQlAf7kpMjIS0dHR2LZtG1JTUzF79mzY2dkhPDwcAKBUKjF37lwsWbIEv/32G44ePYrHHnsMwcHBhllYPXv2xMSJEzFv3jwcOHAABw4cwLx58zBlyhSLnnF1O5Hj/OHrYsftIZpIo9Xhnz+mAgAeHeqDPl4dxQ1EREQmZ/JG57PPPoNarcaYMWPg6elp+PPNN98Yxrz00kuIjIzE008/jUGDBuHy5cuIi4uDg4ODYcyKFSswffp0zJw5E6GhobCzs8NPP/0EmUxmGPP1118jODgYYWFhCAsLQ58+fbB582ZTvySzZyOXIfqBYADcHqIpvtyXjrN5ZXCxt8aLYT3EjkNERC3A5PfoNGYSl0QiQVRUFKKiou44xsbGBqtWrcKqVavuOMbZ2RlbtmwxJqbFCe3uigcHeuH/krOw9Ptj2LFwJDeivIsrxZVYuessAOCVST2gtOM0KyIiS8SfhBbktfuubw+xhttD3NW/dpxEpUaLwV2c8LcBjV+DiIiI2hY2Ohbkxu0hVv1+DufzuT3E7exOy8OvqTmQSSX41/QgripNRGTB2OhYmGl9VRgd0Ak1Wh2Wfn8cOl2LrQfZJlVptHhzu34D2dnDu6CHh2nXTyIiIvPCRsfCSCQSvDM9CLZyGZLSC/HN4UyxI5mVNQkXkFFQAXdHBSLH+Ysdh4iIWhgbHQvk7WyHJWEBAIDoX04hr6RK5ETmIaOgHP/ZfQ4A8PrkXnCw4Q3IRESWjo2OhZoT6oc+XkqUVtUi6qcTYscRnSAIiNp+AjW1Oozo7oopfTwbfhIREbV5bHQslEwqwfsz+kAmleCX4zmIP3nrdhntya5T+fgjLR9ymQRv3d+7wX3ViIjIMrDRsWDcHkKvWgu888tpAMD8UV3RrVMHkRMREVFrYaNj4bg9BBCXJcUVdRU6d7TFs/fwBmQiovaEjY6Fa+/bQ5zPL8cf2frLVG9O7QVba1kDzyAiIkvCRqcdqNseQhCApd8fQ02tTuxIrUIQBLy14xS0ggT3BLpifC93sSMREVErY6PTTty4PcS6fRfFjtPiiitq8Pw3Kdh/oRByiYA3JvfgDchERO0QG5124sbtIf6z+zxyK0UO1IJ2nsjBuOV78EPKFUglwPQuOng72Ykdi4iIRMBGpx2Z1leFMYGdoNEKWJ8mw2ELu1+nsLwGi/57FAs2J+NqWTW6u3XAN/OGYIQHt8EgImqv2Oi0I3XbQzjby5FbKcHfvziE57YeRY667a+c/OvxbIStSMD2v/Rncf4xpht2LByBft4dxY5GREQiYqPTzng52eGXhaEY7q6DRAL8mHIF9360G//54xyqNFqx4zXZ1bJqPPP1Efzj6yO4WlaDAPcO2PZ0KF6e2AM2cs6wIiJq79jotEMu9tZ4uKsO254ahkG+Tqio0eLDnWkIW7EH8SdzIQjmf6lHEATsOHYFYSv24Ofj2ZBJJXj2nu74aeEI9OVZHCIiusZK7AAknt4qR3z7VAi2/3UF0b+cwqXCCsz76jBG+rvizam90N3NQeyIt5VfWo1//piKX1NzAAA9PBzw4YN9EeylFDkZERGZG57RaeckEgnu79cZvy8Zg6fHdIO1TIq9Z69i4sq9+NeOkygxo20jBEHAjymXEbYiAb+m5sBKKsGisf7Y/uwINjlERHRbbHQIAGCvsMJLE3sgfvEojOvpjlqdgPX70nHvv3fjf4cyodOJezkrr6QK8zcn47mtKSiq0KCnpyN+eCYUi8cHwNqK38ZERHR7/AlB9fi62OOLWYOwcc5gdO1kj6tlNXjpu2OY/umfOHKp9aejC4KAbUezMP7a/UNWUgmeHxeAH58JRVBnnsUhIqK74z06dFtjAt0wvJsrvtp/ESt3ncWxLDVmfJqIGQM645WJPeDmaNPiGXJLqvDatuPYdSoPABDU2REfPtgXPT0dW/xzExGRZWCjQ3dkbSXFkyO7Ylo/FT6MTcO3yVn4/shl7EzNwcKx/pgT2qVFTgkKAvD90ct495c0lFTVQi6T4Lmx/lgwuhvkMp6EJCKixmOjQw1yc7DBhw/1xaPDfBG1/QRSMovx/q+n8c2hTLw6KcComoIgoEarQ3WtDlUaLao1+v8vKqvE2tNSnDxwAgAQ3FmJfz/UF4Ee5jkDjIiIzBsbHWq0ft4d8f0/huP7o5fx/q+nkX61HPM2H0WAUopEzQnUaIHqWn3TUlV7vXmp0mhRXatDda0WVRr9f6trdbjzcj1SyGUSPD8+APNHdoUVz+IQEZGR2OhQk0ilEjw40AsTertj1e/nsOHPdJxRS3Hm8OVm1bWRS6GwkkFhJYWTtBIrHh+BXp2dTJSaiIjaKzY6ZBQHGzleva8n/tbPEx9v24OAgEDYKaygsJIZmpYbmxeFXP9fw2NyKWyuPWYtk0IikQAANBoNfvnlF/i7dRD5FRIRkSVgo0PN0rWTPSZ4CbhvTFfI5XKx4xAREdXDmx+IiIjIYrHRISIiIovFRoeIiIgsFhsdIiIislhsdIiIiMhisdEhIiIii8VGh4iIiCwWGx0iIiKyWGx0iIiIyGKx0SEiIiKLxUaHiIiILBYbHSIiIrJYbHSIiIjIYrXr3csFQQAAlJSUmLy2RqNBRUUFSkpKmr2rtylrtadspq7HbOZRz5yzmboes5lHPWYzn3p16n5u1/0cv5t23eiUlpYCALy9vUVOQkRERE1VWloKpVJ51zESoTHtkIXS6XS4cuUKHBwcIJFITFq7pKQE3t7eyMzMhKOjo9nUak/ZTF2P2cyjnjlnM3U9ZjOPesxmPvXqCIKA0tJSqFQqSKV3vwunXZ/RkUql8PLyatHP4ejoaLJ/XFPWMnU9c85m6nrMZh71zDmbqesxm3nUYzbzqQegwTM5dXgzMhEREVksNjpERERksdjotBCFQoE333wTCoXCrGqZup45ZzN1PWYzj3rmnM3U9ZjNPOoxm/nUM0a7vhmZiIiILBvP6BAREZHFYqNDREREFouNDhEREVksNjpERERksdjotIBPP/0Ufn5+sLGxwcCBA7F3716j6uzZswdTp06FSqWCRCLBDz/8YHSm9957D4MHD4aDgwPc3Nwwffp0pKWlGV3vs88+Q58+fQyLQIWEhODXX381ut7NWSUSCSIjI416flRUFCQSSb0/Hh4ezcp0+fJlPPbYY3BxcYGdnR369euH5ORko2p16dLllnwSiQTPPPNMk2vV1tbi9ddfh5+fH2xtbdG1a1e8/fbb0Ol0RmUD9EuqR0ZGwtfXF7a2thg+fDgOHTrU4PMa+n4VBAFRUVFQqVSwtbXFmDFjcOLECaPrff/995gwYQJcXV0hkUiQkpJidD6NRoOXX34ZwcHBsLe3h0qlwuOPP44rV64YlS0qKgo9evSAvb09nJycMG7cOBw8eNDo13qjBQsWQCKRYOXKlUbVmj179i3fe8OGDWtWtlOnTmHatGlQKpVwcHDAsGHDcOnSJaPq3e7YkEgk+PDDD5tcq6ysDM8++yy8vLxga2uLnj174rPPPjP6tebm5mL27NlQqVSws7PDxIkTcfbs2dvWasx7bmOPicbUasrx0FC9ph4PjcnX1GPClNjomNg333yDyMhIvPbaazh69ChGjhyJSZMm3fGgv5vy8nL07dsXq1evbnauhIQEPPPMMzhw4ADi4+NRW1uLsLAwlJeXG1XPy8sL77//Pg4fPozDhw/j3nvvxf3333/XH1yNcejQIaxduxZ9+vRpVp3evXsjOzvb8Of48eNG1yoqKkJoaCjkcjl+/fVXnDx5Eh999BE6duxoVL1Dhw7VyxYfHw8AeOihh5pc64MPPsDnn3+O1atX49SpU1i2bBk+/PBDrFq1yqhsAPDkk08iPj4emzdvxvHjxxEWFoZx48bh8uXLd31eQ9+vy5Ytw/Lly7F69WocOnQIHh4eGD9+vGHPuabWKy8vR2hoKN5///1Gva671auoqMCRI0fwxhtv4MiRI/j+++9x5swZTJs2zahsAQEBWL16NY4fP459+/ahS5cuCAsLQ35+vlH16vzwww84ePAgVCqVUa+zzsSJE+t9D/7yyy9G1zt//jxGjBiBHj16YPfu3fjrr7/wxhtvwMbGxqh6N+bKzs7Gl19+CYlEgr/97W9NrvX8888jNjYWW7ZswalTp/D8889j4cKF+PHHH5ucTRAETJ8+HRcuXMCPP/6Io0ePwtfXF+PGjbvt+2hj3nMbe0w0plZTjoeG6jX1eGhMvqYeEyYlkEkNGTJEeOqpp+o91qNHD+GVV15pVl0AwrZt25pV40Z5eXkCACEhIcFkNZ2cnIQvvvjC6OeXlpYK/v7+Qnx8vDB69GjhueeeM6rOm2++KfTt29foHDd7+eWXhREjRpis3s2ee+45oVu3boJOp2vycydPniw88cQT9R6bMWOG8NhjjxmVpaKiQpDJZMKOHTvqPd63b1/htddea3Sdm79fdTqd4OHhIbz//vuGx6qqqgSlUil8/vnnTa53o/T0dAGAcPToUaPz3U5SUpIAQMjIyGh2LbVaLQAQdu3aZXS2rKwsoXPnzkJqaqrg6+srrFixwqhas2bNEu6///4Gn9vYeg8//LDR32+N+drdf//9wr333mtUrd69ewtvv/12vccGDBggvP76602ul5aWJgAQUlNTDY/V1tYKzs7Owrp16xqsd/N7bnOOibu9fxtzPDTm50Fjj4fG1mvKMdFcPKNjQjU1NUhOTkZYWFi9x8PCwpCYmChSqttTq9UAAGdn52bX0mq12Lp1K8rLyxESEmJ0nWeeeQaTJ0/GuHHjmp3p7NmzUKlU8PPzwyOPPIILFy4YXWv79u0YNGgQHnroIbi5uaF///5Yt25dszMC+u+ZLVu24IknnjBqY9kRI0bgt99+w5kzZwAAf/31F/bt24f77rvPqDy1tbXQarW3/DZua2uLffv2GVUTANLT05GTk1Pv2FAoFBg9erTZHRt11Go1JBKJ0Wfu6tTU1GDt2rVQKpXo27evUTV0Oh0iIiLw4osvonfv3s3KAwC7d++Gm5sbAgICMG/ePOTl5Rmd6+eff0ZAQAAmTJgANzc3DB06tFmX2W+Um5uLn3/+GXPnzjXq+SNGjMD27dtx+fJlCIKAP/74A2fOnMGECROaXKu6uhoA6h0bMpkM1tbWjTo2bn7Pbc4xYcr378bWa8rx0FA9UxwTTcFGx4SuXr0KrVYLd3f3eo+7u7sjJydHpFS3EgQBixcvxogRIxAUFGR0nePHj6NDhw5QKBR46qmnsG3bNvTq1cuoWlu3bkVycjLee+89o/PUGTp0KL766ivs3LkT69atQ05ODoYPH46CggKj6l24cAGfffYZ/P39sXPnTjz11FNYtGgRvvrqq2Zn/eGHH1BcXIzZs2cb9fyXX34Zf//739GjRw/I5XL0798fkZGR+Pvf/25UPQcHB4SEhOBf//oXrly5Aq1Wiy1btuDgwYPIzs42qiYAw/e/uR8bdaqqqvDKK68gPDzc6I0Id+zYgQ4dOsDGxgYrVqxAfHw8XF1djar1wQcfwMrKCosWLTLq+TeaNGkSvv76a/z+++/46KOPcOjQIdx7772GH+RNkZeXh7KyMrz//vuYOHEi4uLi8MADD2DGjBlISEhodtZNmzbBwcEBM2bMMOr5n3zyCXr16gUvLy9YW1tj4sSJ+PTTTzFixIgm1+rRowd8fX2xdOlSFBUVoaamBu+//z5ycnIaPDZu955r7DFhqvfvptRryvFwt3qmPCaaol3vXt5Sbv7NXBAEo35bbynPPvssjh071qzf0AEgMDAQKSkpKC4uxnfffYdZs2YhISGhyc1OZmYmnnvuOcTFxd3xun5TTJo0yfD/wcHBCAkJQbdu3bBp0yYsXry4yfV0Oh0GDRqE6OhoAED//v1x4sQJfPbZZ3j88ceblXX9+vWYNGnSXe+5uJtvvvkGW7ZsQUxMDHr37o2UlBRERkZCpVJh1qxZRtXcvHkznnjiCXTu3BkymQwDBgxAeHg4jhw5YlS9G5n7sQHob8R85JFHoNPp8Omnnxpd55577kFKSgquXr2KdevWYebMmTh48CDc3NyaVCc5ORkff/wxjhw5YpKv1cMPP2z4/6CgIAwaNAi+vr74+eefm9xQ1N30fv/99+P5558HAPTr1w+JiYn4/PPPMXr06GZl/fLLL/Hoo48a/b7wySef4MCBA9i+fTt8fX2xZ88ePP300/D09GzymWO5XI7vvvsOc+fOhbOzM2QyGcaNG1fv/eZO7vae29RjwlTv342t19Tj4W71THVMNBXP6JiQq6srZDLZLd14Xl7eLV27WBYuXIjt27fjjz/+gJeXV7NqWVtbo3v37hg0aBDee+899O3bFx9//HGT6yQnJyMvLw8DBw6ElZUVrKyskJCQgE8++QRWVlbQarXNymlvb4/g4OA7zo5oiKen5y3NW8+ePY26wfxGGRkZ2LVrF5588kmja7z44ot45ZVX8MgjjyA4OBgRERF4/vnnm3VmrFu3bkhISEBZWRkyMzORlJQEjUYDPz8/o2vWzXoz52MD0L+pz5w5E+np6YiPjzf6bA6g/77r3r07hg0bhvXr18PKygrr169vcp29e/ciLy8PPj4+huMjIyMDS5YsQZcuXYzOV8fT0xO+vr5GHR+urq6wsrJqkeNj7969SEtLM/r4qKysxKuvvorly5dj6tSp6NOnD5599lk8/PDD+Pe//21UzYEDBxp+ucvOzkZsbCwKCgruemzc6T3XmGPClO/fjanX1OOhoXqmOiaaio2OCVlbW2PgwIGGWTR14uPjMXz4cJFS6QmCgGeffRbff/89fv/992b90Lrb5zDm9PfYsWNx/PhxpKSkGP4MGjQIjz76KFJSUiCTyZqVq7q6GqdOnYKnp6dRzw8NDb1lquSZM2fg6+vbrFwbNmyAm5sbJk+ebHSNiooKSKX1D2OZTNas6eV17O3t4enpiaKiIuzcuRP333+/0bX8/Pzg4eFR79ioqalBQkKC6MdGnbo39bNnz2LXrl1wcXExaX1jj4+IiAgcO3as3vGhUqnw4osvYufOnc3OVVBQgMzMTKOOD2trawwePLhFjo/169dj4MCBRt/DodFooNFoWuT4UCqV6NSpE86ePYvDhw/f9tho6D23KceEqd+/G1OvKceDsfmMPSaaipeuTGzx4sWIiIjAoEGDEBISgrVr1+LSpUt46qmnmlyrrKwM586dM/w9PT0dKSkpcHZ2ho+PT5NqPfPMM4iJicGPP/4IBwcHw28RSqUStra2Tc726quvYtKkSfD29kZpaSm2bt2K3bt3IzY2tsm1HBwcbrmWa29vDxcXF6OuQb/wwguYOnUqfHx8kJeXh3feeQclJSVGX8p5/vnnMXz4cERHR2PmzJlISkrC2rVrsXbtWqPqAfpT/hs2bMCsWbNgZWX8YTh16lS8++678PHxQe/evXH06FEsX74cTzzxhNE1d+7cCUEQEBgYiHPnzuHFF19EYGAg5syZc9fnNfT9GhkZiejoaPj7+8Pf3x/R0dGws7NDeHi4UfUKCwtx6dIlw9oedT9sPTw8brtu0t3qqVQqPPjggzhy5Ah27NgBrVZrOEacnZ1hbW3d6FouLi549913MW3aNHh6eqKgoACffvopsrKy7riEQEOv9eYfMnK5HB4eHggMDGxSLWdnZ0RFReFvf/sbPD09cfHiRbz66qtwdXXFAw88YFS2F198EQ8//DBGjRqFe+65B7Gxsfjpp5+we/duo+oBQElJCb799lt89NFHt63R2FqjR4/Giy++CFtbW/j6+iIhIQFfffUVli9fblS9b7/9Fp06dYKPjw+OHz+O5557DtOnT79lAgrQ8Htu3VphjTkmGvP+3ZTjoaF6tbW1TToeGqpXXl7e5GPCpFp8Xlc79J///Efw9fUVrK2thQEDBhg9hfuPP/4QANzyZ9asWU2udbs6AIQNGzYYle2JJ54wvMZOnToJY8eOFeLi4oyqdTvNmV7+8MMPC56enoJcLhdUKpUwY8YM4cSJE83K89NPPwlBQUGCQqEQevToIaxdu7ZZ9Xbu3CkAENLS0ppVp6SkRHjuuecEHx8fwcbGRujatavw2muvCdXV1UbX/Oabb4SuXbsK1tbWgoeHh/DMM88IxcXFDT6voe9XnU4nvPnmm4KHh4egUCiEUaNGCcePHze63oYNG2778TfffLPJ9eqm5N7uzx9//NGkWpWVlcIDDzwgqFQqwdraWvD09BSmTZsmJCUlGf1ab3a36eV3q1VRUSGEhYUJnTp1EuRyueDj4yPMmjVLuHTpUrOyrV+/XujevbtgY2Mj9O3bV/jhhx+aVW/NmjWCra1tg993DdXKzs4WZs+eLahUKsHGxkYIDAwUPvroozsu5dBQvY8//ljw8vIyfO1ef/31Ox5rjXnPbewx0ZhaTTkeGqrX1OOhoXrGHBOmJLkWkoiIiMji8B4dIiIislhsdIiIiMhisdEhIiIii8VGh4iIiCwWGx0iIiKyWGx0iIiIyGKx0SEiIiKLxUaHiIiILBYbHSIiIrJYbHSIiIjIYrHRISIiIovFRoeIiIgs1v8DnK2P7zVjDpMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "keys = [pair for pair, df in all_data.groupby(['Hour'])]\n",
    "\n",
    "plt.plot(keys, all_data.groupby(['Hour']).count()['Count'])\n",
    "plt.xticks(keys)\n",
    "plt.grid()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "85729294",
   "metadata": {},
   "source": [
    "### Question 4: What products are most often sold together?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "61a216a4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('iPhone', 'Lightning Charging Cable') 1005\n",
      "('Google Phone', 'USB-C Charging Cable') 987\n",
      "('iPhone', 'Wired Headphones') 447\n",
      "('Google Phone', 'Wired Headphones') 414\n",
      "('Vareebadd Phone', 'USB-C Charging Cable') 361\n",
      "('iPhone', 'Apple Airpods Headphones') 360\n",
      "('Google Phone', 'Bose SoundSport Headphones') 220\n",
      "('USB-C Charging Cable', 'Wired Headphones') 160\n",
      "('Vareebadd Phone', 'Wired Headphones') 143\n",
      "('Lightning Charging Cable', 'Wired Headphones') 92\n"
     ]
    }
   ],
   "source": [
    "# Referenced: https://stackoverflow.com/questions/52195887/counting-unique-pairs-of-numbers-into-a-python-dictionary\n",
    "from itertools import combinations\n",
    "from collections import Counter\n",
    "\n",
    "count = Counter()\n",
    "\n",
    "for row in df2['Grouped']:\n",
    "    row_list = row.split(',')\n",
    "    count.update(Counter(combinations(row_list, 2)))\n",
    "\n",
    "for key,value in count.most_common(10):\n",
    "    print(key, value)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "95d5c6e0",
   "metadata": {},
   "source": [
    "### Question 5:What product sold the most? Why do you think it sold the most?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "20605d08",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "product_group = all_data.groupby('Product')\n",
    "quantity_ordered = product_group.sum()['Quantity Ordered']\n",
    "\n",
    "keys = [pair for pair, df in product_group]\n",
    "plt.bar(keys, quantity_ordered)\n",
    "plt.xticks(keys, rotation='vertical', size=8)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "5d0a3ac7",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Admin\\AppData\\Local\\Temp\\ipykernel_3276\\148863181.py:14: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  ax1.set_xticklabels(keys, rotation='vertical', size=8)\n",
      "C:\\Users\\Admin\\AppData\\Local\\Temp\\ipykernel_3276\\148863181.py:16: UserWarning: Matplotlib is currently using module://matplotlib_inline.backend_inline, which is a non-GUI backend, so cannot show the figure.\n",
      "  fig.show()\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Referenced: https://stackoverflow.com/questions/14762181/adding-a-y-axis-label-to-secondary-y-axis-in-matplotlib\n",
    "\n",
    "prices = all_data.groupby('Product').mean()['Price Each']\n",
    "\n",
    "fig, ax1 = plt.subplots()\n",
    "\n",
    "ax2 = ax1.twinx()\n",
    "ax1.bar(keys, quantity_ordered, color='g')\n",
    "ax2.plot(keys, prices, color='r')\n",
    "\n",
    "ax1.set_xlabel('Product Name')\n",
    "ax1.set_ylabel('Quantity Ordered', color='g')\n",
    "ax2.set_ylabel('Price ($)', color='b')\n",
    "ax1.set_xticklabels(keys, rotation='vertical', size=8)\n",
    "\n",
    "fig.show()"
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