DP-EDA-Tiki-Books.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "4cc3d6d4",
   "metadata": {
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    "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5",
    "execution": {
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     "exception": false,
     "start_time": "2022-12-12T14:39:58.626678",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/kaggle/input/tiki-books-dataset/comments.csv\n",
      "/kaggle/input/tiki-books-dataset/book_data.csv\n",
      "/kaggle/input/tiki-books-dataset/book_id.csv\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "for dirname, _, filenames in os.walk('/kaggle/input'):\n",
    "    for filename in filenames:\n",
    "        print(os.path.join(dirname, filename))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "90eceb1b",
   "metadata": {
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     "start_time": "2022-12-12T14:39:58.700764",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# 1. Import Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c414fa83",
   "metadata": {
    "execution": {
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import os\n",
    "import matplotlib.pyplot as plt\n",
    "import plotly.express as px\n",
    "import seaborn as sns\n",
    "import plotly.express as px\n",
    "import cv2\n",
    "from PIL import Image\n",
    "\n",
    "plt.style.use(\"seaborn\")\n",
    "plt.rcParams['figure.figsize'] = (13, 7)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d3b1f3d8",
   "metadata": {
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     "exception": false,
     "start_time": "2022-12-12T14:40:01.374272",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# 2. Load Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1532b12b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:01.429865Z",
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     "iopub.status.idle": "2022-12-12T14:40:02.709181Z",
     "shell.execute_reply": "2022-12-12T14:40:02.707941Z"
    },
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     "duration": 1.301858,
     "end_time": "2022-12-12T14:40:02.712080",
     "exception": false,
     "start_time": "2022-12-12T14:40:01.410222",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "id_df = pd.read_csv(\"/kaggle/input/tiki-books-dataset/book_id.csv\")\n",
    "data_df = pd.read_csv(\"/kaggle/input/tiki-books-dataset/book_data.csv\")\n",
    "cmt_df = pd.read_csv(\"/kaggle/input/tiki-books-dataset/comments.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c55f2d64",
   "metadata": {
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     "duration": 0.017762,
     "end_time": "2022-12-12T14:40:02.748323",
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     "start_time": "2022-12-12T14:40:02.730561",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Let focus on data_df (main file)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "4d4f2bad",
   "metadata": {
    "execution": {
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     "exception": false,
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     "status": "completed"
    },
    "tags": []
   },
   "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",
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       "    }\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>product_id</th>\n",
       "      <th>title</th>\n",
       "      <th>authors</th>\n",
       "      <th>original_price</th>\n",
       "      <th>current_price</th>\n",
       "      <th>quantity</th>\n",
       "      <th>category</th>\n",
       "      <th>n_review</th>\n",
       "      <th>avg_rating</th>\n",
       "      <th>pages</th>\n",
       "      <th>manufacturer</th>\n",
       "      <th>cover_link</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>74021317</td>\n",
       "      <td>Cây Cam Ngọt Của Tôi</td>\n",
       "      <td>José Mauro de Vasconcelos</td>\n",
       "      <td>108000</td>\n",
       "      <td>64800</td>\n",
       "      <td>53075.0</td>\n",
       "      <td>Tiểu Thuyết</td>\n",
       "      <td>11481</td>\n",
       "      <td>5.0</td>\n",
       "      <td>244</td>\n",
       "      <td>Nhà Xuất Bản Hội Nhà Văn</td>\n",
       "      <td>https://salt.tikicdn.com/ts/product/5e/18/24/2...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>74021317</td>\n",
       "      <td>Cây Cam Ngọt Của Tôi</td>\n",
       "      <td>José Mauro de Vasconcelos</td>\n",
       "      <td>108000</td>\n",
       "      <td>64800</td>\n",
       "      <td>53075.0</td>\n",
       "      <td>Tiểu Thuyết</td>\n",
       "      <td>11481</td>\n",
       "      <td>5.0</td>\n",
       "      <td>244</td>\n",
       "      <td>Nhà Xuất Bản Hội Nhà Văn</td>\n",
       "      <td>https://salt.tikicdn.com/ts/product/5e/18/24/2...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>184466860</td>\n",
       "      <td>Hành Tinh Của Một Kẻ Nghĩ Nhiều</td>\n",
       "      <td>Nguyễn Đoàn Minh Thư</td>\n",
       "      <td>86000</td>\n",
       "      <td>59900</td>\n",
       "      <td>7929.0</td>\n",
       "      <td>Sách tư duy - Kỹ năng sống</td>\n",
       "      <td>780</td>\n",
       "      <td>4.8</td>\n",
       "      <td>184</td>\n",
       "      <td>Nhà Xuất Bản Thế Giới</td>\n",
       "      <td>https://salt.tikicdn.com/ts/product/d7/99/24/1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>73787185</td>\n",
       "      <td>Những Tù Nhân Của Địa Lý</td>\n",
       "      <td>Tim Marshall</td>\n",
       "      <td>210000</td>\n",
       "      <td>126000</td>\n",
       "      <td>17896.0</td>\n",
       "      <td>Lĩnh vực khác</td>\n",
       "      <td>3623</td>\n",
       "      <td>4.8</td>\n",
       "      <td>430</td>\n",
       "      <td>Nhà Xuất Bản Hội Nhà Văn</td>\n",
       "      <td>https://salt.tikicdn.com/ts/product/8d/96/9e/c...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>52789367</td>\n",
       "      <td>Nhà Giả Kim (Tái Bản 2020)</td>\n",
       "      <td>Paulo Coelho</td>\n",
       "      <td>79000</td>\n",
       "      <td>47400</td>\n",
       "      <td>24668.0</td>\n",
       "      <td>Tác phẩm kinh điển</td>\n",
       "      <td>5131</td>\n",
       "      <td>5.0</td>\n",
       "      <td>228</td>\n",
       "      <td>Nhà Xuất Bản Hà Nội</td>\n",
       "      <td>https://salt.tikicdn.com/ts/product/45/3b/fc/a...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   product_id                            title                    authors  \\\n",
       "0    74021317             Cây Cam Ngọt Của Tôi  José Mauro de Vasconcelos   \n",
       "1    74021317             Cây Cam Ngọt Của Tôi  José Mauro de Vasconcelos   \n",
       "2   184466860  Hành Tinh Của Một Kẻ Nghĩ Nhiều       Nguyễn Đoàn Minh Thư   \n",
       "3    73787185         Những Tù Nhân Của Địa Lý               Tim Marshall   \n",
       "4    52789367       Nhà Giả Kim (Tái Bản 2020)               Paulo Coelho   \n",
       "\n",
       "   original_price  current_price  quantity                    category  \\\n",
       "0          108000          64800   53075.0                 Tiểu Thuyết   \n",
       "1          108000          64800   53075.0                 Tiểu Thuyết   \n",
       "2           86000          59900    7929.0  Sách tư duy - Kỹ năng sống   \n",
       "3          210000         126000   17896.0               Lĩnh vực khác   \n",
       "4           79000          47400   24668.0          Tác phẩm kinh điển   \n",
       "\n",
       "   n_review  avg_rating pages              manufacturer  \\\n",
       "0     11481         5.0   244  Nhà Xuất Bản Hội Nhà Văn   \n",
       "1     11481         5.0   244  Nhà Xuất Bản Hội Nhà Văn   \n",
       "2       780         4.8   184     Nhà Xuất Bản Thế Giới   \n",
       "3      3623         4.8   430  Nhà Xuất Bản Hội Nhà Văn   \n",
       "4      5131         5.0   228       Nhà Xuất Bản Hà Nội   \n",
       "\n",
       "                                          cover_link  \n",
       "0  https://salt.tikicdn.com/ts/product/5e/18/24/2...  \n",
       "1  https://salt.tikicdn.com/ts/product/5e/18/24/2...  \n",
       "2  https://salt.tikicdn.com/ts/product/d7/99/24/1...  \n",
       "3  https://salt.tikicdn.com/ts/product/8d/96/9e/c...  \n",
       "4  https://salt.tikicdn.com/ts/product/45/3b/fc/a...  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f65e9193",
   "metadata": {
    "execution": {
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1796 entries, 0 to 1795\n",
      "Data columns (total 12 columns):\n",
      " #   Column          Non-Null Count  Dtype  \n",
      "---  ------          --------------  -----  \n",
      " 0   product_id      1796 non-null   int64  \n",
      " 1   title           1796 non-null   object \n",
      " 2   authors         1653 non-null   object \n",
      " 3   original_price  1796 non-null   int64  \n",
      " 4   current_price   1796 non-null   int64  \n",
      " 5   quantity        1751 non-null   float64\n",
      " 6   category        1796 non-null   object \n",
      " 7   n_review        1796 non-null   int64  \n",
      " 8   avg_rating      1796 non-null   float64\n",
      " 9   pages           1546 non-null   object \n",
      " 10  manufacturer    1523 non-null   object \n",
      " 11  cover_link      1796 non-null   object \n",
      "dtypes: float64(2), int64(4), object(6)\n",
      "memory usage: 168.5+ KB\n"
     ]
    }
   ],
   "source": [
    "data_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "8dfa91b5",
   "metadata": {
    "execution": {
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2024 entries, 0 to 2023\n",
      "Data columns (total 1 columns):\n",
      " #   Column  Non-Null Count  Dtype\n",
      "---  ------  --------------  -----\n",
      " 0   id      2024 non-null   int64\n",
      "dtypes: int64(1)\n",
      "memory usage: 15.9 KB\n"
     ]
    }
   ],
   "source": [
    "id_df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc495100",
   "metadata": {
    "papermill": {
     "duration": 0.018692,
     "end_time": "2022-12-12T14:40:02.978556",
     "exception": false,
     "start_time": "2022-12-12T14:40:02.959864",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "We have 1796 books with duplicated. But in the id_df, we have 2024 ids. The reason for this issue is we crawled some thing not a book. Anaway, that isn't a big problem."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "416d16d4",
   "metadata": {
    "papermill": {
     "duration": 0.018577,
     "end_time": "2022-12-12T14:40:03.017023",
     "exception": false,
     "start_time": "2022-12-12T14:40:02.998446",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# 3. Data Preparation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "05e7969f",
   "metadata": {
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     "duration": 0.018564,
     "end_time": "2022-12-12T14:40:03.056063",
     "exception": false,
     "start_time": "2022-12-12T14:40:03.037499",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## 3.1 Handle Value and Missing Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "3545c100",
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2022-12-12T14:40:03.106258Z"
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     "exception": false,
     "start_time": "2022-12-12T14:40:03.076847",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "product_id          0\n",
       "title               0\n",
       "authors           143\n",
       "original_price      0\n",
       "current_price       0\n",
       "quantity           45\n",
       "category            0\n",
       "n_review            0\n",
       "avg_rating          0\n",
       "pages             250\n",
       "manufacturer      273\n",
       "cover_link          0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b6acf856",
   "metadata": {
    "papermill": {
     "duration": 0.018024,
     "end_time": "2022-12-12T14:40:03.145858",
     "exception": false,
     "start_time": "2022-12-12T14:40:03.127834",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Title\n",
    "Remove duplicated titles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "61eef0fa",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:03.184563Z",
     "iopub.status.busy": "2022-12-12T14:40:03.184129Z",
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     "start_time": "2022-12-12T14:40:03.164265",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "data_df = data_df.drop_duplicates(subset=['title'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ae6d60f7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:03.234651Z",
     "iopub.status.busy": "2022-12-12T14:40:03.233667Z",
     "iopub.status.idle": "2022-12-12T14:40:03.246305Z",
     "shell.execute_reply": "2022-12-12T14:40:03.245135Z"
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     "start_time": "2022-12-12T14:40:03.213896",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Nguyễn Nhật Ánh    24\n",
       "Higashino Keigo    20\n",
       ".                  18\n",
       "Thích Nhất Hạnh    16\n",
       "Haruki Murakami    15\n",
       "                   ..\n",
       "Urako Kanamori      1\n",
       "Cổ Viên             1\n",
       "Robert Winston      1\n",
       "Yongchul Kwon       1\n",
       "John C. Maxwell     1\n",
       "Name: authors, Length: 1083, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_df.authors.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a061e9c",
   "metadata": {
    "papermill": {
     "duration": 0.018432,
     "end_time": "2022-12-12T14:40:03.286304",
     "exception": false,
     "start_time": "2022-12-12T14:40:03.267872",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "As we can see, there are 18 \".\" authors, that's so weird hahaa. Let throw it away!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "2daecfe7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:03.325572Z",
     "iopub.status.busy": "2022-12-12T14:40:03.325134Z",
     "iopub.status.idle": "2022-12-12T14:40:03.332904Z",
     "shell.execute_reply": "2022-12-12T14:40:03.331617Z"
    },
    "papermill": {
     "duration": 0.030467,
     "end_time": "2022-12-12T14:40:03.335624",
     "exception": false,
     "start_time": "2022-12-12T14:40:03.305157",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "data_df.loc[data_df.authors == '.' , 'authors'] = \"Unknown\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d89ab6f8",
   "metadata": {
    "papermill": {
     "duration": 0.018313,
     "end_time": "2022-12-12T14:40:03.372547",
     "exception": false,
     "start_time": "2022-12-12T14:40:03.354234",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Author"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f5f62d47",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:03.411912Z",
     "iopub.status.busy": "2022-12-12T14:40:03.411494Z",
     "iopub.status.idle": "2022-12-12T14:40:03.421286Z",
     "shell.execute_reply": "2022-12-12T14:40:03.420203Z"
    },
    "papermill": {
     "duration": 0.032441,
     "end_time": "2022-12-12T14:40:03.423530",
     "exception": false,
     "start_time": "2022-12-12T14:40:03.391089",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Nguyễn Nhật Ánh    24\n",
       "Higashino Keigo    20\n",
       "Unknown            18\n",
       "Thích Nhất Hạnh    16\n",
       "Haruki Murakami    15\n",
       "                   ..\n",
       "Urako Kanamori      1\n",
       "Cổ Viên             1\n",
       "Robert Winston      1\n",
       "Yongchul Kwon       1\n",
       "John C. Maxwell     1\n",
       "Name: authors, Length: 1083, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_df.authors.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "5a5181c8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:03.462906Z",
     "iopub.status.busy": "2022-12-12T14:40:03.462470Z",
     "iopub.status.idle": "2022-12-12T14:40:03.468756Z",
     "shell.execute_reply": "2022-12-12T14:40:03.467643Z"
    },
    "papermill": {
     "duration": 0.028941,
     "end_time": "2022-12-12T14:40:03.471274",
     "exception": false,
     "start_time": "2022-12-12T14:40:03.442333",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "data_df.authors = data_df.authors.fillna(\"Unknown\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6b30862",
   "metadata": {
    "papermill": {
     "duration": 0.018404,
     "end_time": "2022-12-12T14:40:03.508525",
     "exception": false,
     "start_time": "2022-12-12T14:40:03.490121",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Quantity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "52e592ed",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:03.547951Z",
     "iopub.status.busy": "2022-12-12T14:40:03.547519Z",
     "iopub.status.idle": "2022-12-12T14:40:03.552979Z",
     "shell.execute_reply": "2022-12-12T14:40:03.552049Z"
    },
    "papermill": {
     "duration": 0.027912,
     "end_time": "2022-12-12T14:40:03.555106",
     "exception": false,
     "start_time": "2022-12-12T14:40:03.527194",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "data_df.quantity = data_df.quantity.fillna(np.mean(data_df.quantity))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "88dc7514",
   "metadata": {
    "papermill": {
     "duration": 0.018156,
     "end_time": "2022-12-12T14:40:03.592015",
     "exception": false,
     "start_time": "2022-12-12T14:40:03.573859",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Category"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "d8d3c06b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:03.632251Z",
     "iopub.status.busy": "2022-12-12T14:40:03.631067Z",
     "iopub.status.idle": "2022-12-12T14:40:03.641879Z",
     "shell.execute_reply": "2022-12-12T14:40:03.640781Z"
    },
    "papermill": {
     "duration": 0.034008,
     "end_time": "2022-12-12T14:40:03.644523",
     "exception": false,
     "start_time": "2022-12-12T14:40:03.610515",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Sách tư duy - Kỹ năng sống                 292\n",
       "Tiểu Thuyết                                133\n",
       "Truyện ngắn - Tản văn - Tạp Văn            109\n",
       "Sách nghệ thuật sống đẹp                    58\n",
       "Sách kỹ năng làm việc                       55\n",
       "                                          ... \n",
       "Shaman King - Tập 19                         1\n",
       "Blue Period - Tập 07                         1\n",
       "Komi - Nữ Thần Sợ Giao Tiếp - Tập 14         1\n",
       "Bên Rặng Tuyết Sơn (Tái Bản)                 1\n",
       "Kaguya-Sama: Cuộc Chiến Tỏ Tình - Tập 3      1\n",
       "Name: category, Length: 354, dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_df.category.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d2ba766a",
   "metadata": {
    "papermill": {
     "duration": 0.019415,
     "end_time": "2022-12-12T14:40:03.684248",
     "exception": false,
     "start_time": "2022-12-12T14:40:03.664833",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "We have lot of wrong values. Just considering top 30 categories."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "ba8a68a2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:03.723155Z",
     "iopub.status.busy": "2022-12-12T14:40:03.722709Z",
     "iopub.status.idle": "2022-12-12T14:40:03.733641Z",
     "shell.execute_reply": "2022-12-12T14:40:03.732527Z"
    },
    "papermill": {
     "duration": 0.033204,
     "end_time": "2022-12-12T14:40:03.735981",
     "exception": false,
     "start_time": "2022-12-12T14:40:03.702777",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Tiểu Thuyết',\n",
       " 'Truyện ngắn - Tản văn - Tạp Văn',\n",
       " 'Sách nghệ thuật sống đẹp',\n",
       " 'Sách kỹ năng làm việc',\n",
       " 'Bài học kinh doanh',\n",
       " 'Truyện trinh thám',\n",
       " 'Sách Học Tiếng Anh',\n",
       " 'Sách Marketing - Bán hàng ',\n",
       " 'Sách tài chính, tiền tệ',\n",
       " 'Tác phẩm kinh điển',\n",
       " 'Truyện Giả tưởng - Huyền Bí - Phiêu Lưu',\n",
       " 'Kiến thức - Bách khoa',\n",
       " 'Sách Làm Cha Mẹ',\n",
       " 'Lĩnh vực khác',\n",
       " 'Truyện dài',\n",
       " 'Kiến Thức Bách Khoa',\n",
       " 'Văn học thiếu nhi',\n",
       " 'Light novel',\n",
       " 'Truyện kể cho bé',\n",
       " 'Sách quản trị, lãnh đạo',\n",
       " 'Truyện đam mỹ',\n",
       " 'Tiểu sử - Hồi ký',\n",
       " 'Lịch Sử Thế Giới',\n",
       " 'Sách Chiêm Tinh - Horoscope',\n",
       " 'Sách Học Tiếng Hoa',\n",
       " 'Truyện tranh Ehon',\n",
       " 'Sách kinh tế học',\n",
       " 'Sách giáo dục',\n",
       " 'Tô màu - Luyện chữ  ']"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "keeping_values = list(pd.DataFrame(data_df.category.value_counts()[1:30]).T.columns)\n",
    "keeping_values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "afe09429",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:03.782460Z",
     "iopub.status.busy": "2022-12-12T14:40:03.781886Z",
     "iopub.status.idle": "2022-12-12T14:40:03.793677Z",
     "shell.execute_reply": "2022-12-12T14:40:03.792449Z"
    },
    "papermill": {
     "duration": 0.042132,
     "end_time": "2022-12-12T14:40:03.797316",
     "exception": false,
     "start_time": "2022-12-12T14:40:03.755184",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def handle_category(category):\n",
    "    if category not in keeping_values:\n",
    "        return \"Others\"\n",
    "    return category\n",
    "\n",
    "data_df.category = data_df.category.apply(lambda category: handle_category(category))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "456320b0",
   "metadata": {
    "papermill": {
     "duration": 0.018584,
     "end_time": "2022-12-12T14:40:03.837782",
     "exception": false,
     "start_time": "2022-12-12T14:40:03.819198",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Pages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "ade7a382",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:03.881496Z",
     "iopub.status.busy": "2022-12-12T14:40:03.880473Z",
     "iopub.status.idle": "2022-12-12T14:40:03.890033Z",
     "shell.execute_reply": "2022-12-12T14:40:03.888809Z"
    },
    "papermill": {
     "duration": 0.036011,
     "end_time": "2022-12-12T14:40:03.892674",
     "exception": false,
     "start_time": "2022-12-12T14:40:03.856663",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def handle_pages(lst_pages):\n",
    "    lst_int = []\n",
    "    for page in lst_pages:\n",
    "        try:\n",
    "            lst_int.append(int(page))\n",
    "        except:\n",
    "            continue\n",
    "            \n",
    "    return np.mean(lst_int)\n",
    "    \n",
    "mean_pages = handle_pages(list(data_df.pages))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "f6c99fe7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:03.934525Z",
     "iopub.status.busy": "2022-12-12T14:40:03.933555Z",
     "iopub.status.idle": "2022-12-12T14:40:03.940658Z",
     "shell.execute_reply": "2022-12-12T14:40:03.939510Z"
    },
    "papermill": {
     "duration": 0.031232,
     "end_time": "2022-12-12T14:40:03.943273",
     "exception": false,
     "start_time": "2022-12-12T14:40:03.912041",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "data_df.pages = data_df.pages.fillna(str(mean_pages))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "a1257913",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:03.987591Z",
     "iopub.status.busy": "2022-12-12T14:40:03.986839Z",
     "iopub.status.idle": "2022-12-12T14:40:04.005884Z",
     "shell.execute_reply": "2022-12-12T14:40:04.004991Z"
    },
    "papermill": {
     "duration": 0.046398,
     "end_time": "2022-12-12T14:40:04.008599",
     "exception": false,
     "start_time": "2022-12-12T14:40:03.962201",
     "status": "completed"
    },
    "tags": []
   },
   "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>product_id</th>\n",
       "      <th>title</th>\n",
       "      <th>authors</th>\n",
       "      <th>original_price</th>\n",
       "      <th>current_price</th>\n",
       "      <th>quantity</th>\n",
       "      <th>category</th>\n",
       "      <th>n_review</th>\n",
       "      <th>avg_rating</th>\n",
       "      <th>pages</th>\n",
       "      <th>manufacturer</th>\n",
       "      <th>cover_link</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1266</th>\n",
       "      <td>197639028</td>\n",
       "      <td>Động Từ Bất Quy Tắc Và Ngữ Pháp Tiếng Anh Căn Bản</td>\n",
       "      <td>Mai Lan Hương</td>\n",
       "      <td>18000</td>\n",
       "      <td>12000</td>\n",
       "      <td>136.0</td>\n",
       "      <td>Sách Học Tiếng Anh</td>\n",
       "      <td>2</td>\n",
       "      <td>5.0</td>\n",
       "      <td>Cuốn</td>\n",
       "      <td>Nhà Xuất Bản Đà Nẵng</td>\n",
       "      <td>https://salt.tikicdn.com/ts/product/28/8e/9e/0...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      product_id                                              title  \\\n",
       "1266   197639028  Động Từ Bất Quy Tắc Và Ngữ Pháp Tiếng Anh Căn Bản   \n",
       "\n",
       "            authors  original_price  current_price  quantity  \\\n",
       "1266  Mai Lan Hương           18000          12000     136.0   \n",
       "\n",
       "                category  n_review  avg_rating pages          manufacturer  \\\n",
       "1266  Sách Học Tiếng Anh         2         5.0  Cuốn  Nhà Xuất Bản Đà Nẵng   \n",
       "\n",
       "                                             cover_link  \n",
       "1266  https://salt.tikicdn.com/ts/product/28/8e/9e/0...  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# There is one product having the value of pages is \"Cuốn\".\n",
    "data_df.query('pages == \"Cuốn\"')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "27f45df2",
   "metadata": {
    "papermill": {
     "duration": 0.02031,
     "end_time": "2022-12-12T14:40:04.056570",
     "exception": false,
     "start_time": "2022-12-12T14:40:04.036260",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Let remove it!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "bee0b4da",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:04.097977Z",
     "iopub.status.busy": "2022-12-12T14:40:04.096992Z",
     "iopub.status.idle": "2022-12-12T14:40:04.106936Z",
     "shell.execute_reply": "2022-12-12T14:40:04.105788Z"
    },
    "papermill": {
     "duration": 0.033578,
     "end_time": "2022-12-12T14:40:04.109594",
     "exception": false,
     "start_time": "2022-12-12T14:40:04.076016",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "data_df = data_df.query('pages != \"Cuốn\"')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1c093df5",
   "metadata": {
    "papermill": {
     "duration": 0.0228,
     "end_time": "2022-12-12T14:40:04.153653",
     "exception": false,
     "start_time": "2022-12-12T14:40:04.130853",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Let change datatype."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "a49316bb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:04.197856Z",
     "iopub.status.busy": "2022-12-12T14:40:04.197048Z",
     "iopub.status.idle": "2022-12-12T14:40:04.206214Z",
     "shell.execute_reply": "2022-12-12T14:40:04.205237Z"
    },
    "papermill": {
     "duration": 0.034677,
     "end_time": "2022-12-12T14:40:04.209472",
     "exception": false,
     "start_time": "2022-12-12T14:40:04.174795",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "data_df.pages = data_df.pages.apply(lambda page: round(float(page)))\n",
    "data_df.pages = data_df.pages.astype(\"int64\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "85dc41c4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:04.254469Z",
     "iopub.status.busy": "2022-12-12T14:40:04.254048Z",
     "iopub.status.idle": "2022-12-12T14:40:04.268701Z",
     "shell.execute_reply": "2022-12-12T14:40:04.267415Z"
    },
    "papermill": {
     "duration": 0.038351,
     "end_time": "2022-12-12T14:40:04.271510",
     "exception": false,
     "start_time": "2022-12-12T14:40:04.233159",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count      1768.000000\n",
       "mean        455.603507\n",
       "std        4561.569635\n",
       "min          10.000000\n",
       "25%         220.000000\n",
       "50%         332.000000\n",
       "75%         456.000000\n",
       "max      192000.000000\n",
       "Name: pages, dtype: float64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_df.pages.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "b5ef77ab",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:04.312600Z",
     "iopub.status.busy": "2022-12-12T14:40:04.311831Z",
     "iopub.status.idle": "2022-12-12T14:40:04.329038Z",
     "shell.execute_reply": "2022-12-12T14:40:04.327823Z"
    },
    "papermill": {
     "duration": 0.040586,
     "end_time": "2022-12-12T14:40:04.331513",
     "exception": false,
     "start_time": "2022-12-12T14:40:04.290927",
     "status": "completed"
    },
    "tags": []
   },
   "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>product_id</th>\n",
       "      <th>title</th>\n",
       "      <th>authors</th>\n",
       "      <th>original_price</th>\n",
       "      <th>current_price</th>\n",
       "      <th>quantity</th>\n",
       "      <th>category</th>\n",
       "      <th>n_review</th>\n",
       "      <th>avg_rating</th>\n",
       "      <th>pages</th>\n",
       "      <th>manufacturer</th>\n",
       "      <th>cover_link</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>650</th>\n",
       "      <td>201687274</td>\n",
       "      <td>Có Một Nổi Buồn Vừa Ngang Qua Đây</td>\n",
       "      <td>Gã</td>\n",
       "      <td>88000</td>\n",
       "      <td>64900</td>\n",
       "      <td>114.0</td>\n",
       "      <td>Truyện ngắn - Tản văn - Tạp Văn</td>\n",
       "      <td>6</td>\n",
       "      <td>5.0</td>\n",
       "      <td>192000</td>\n",
       "      <td>Nhà Xuất Bản Văn Học</td>\n",
       "      <td>https://salt.tikicdn.com/ts/product/08/fd/a5/0...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     product_id                              title authors  original_price  \\\n",
       "650   201687274  Có Một Nổi Buồn Vừa Ngang Qua Đây      Gã           88000   \n",
       "\n",
       "     current_price  quantity                         category  n_review  \\\n",
       "650          64900     114.0  Truyện ngắn - Tản văn - Tạp Văn         6   \n",
       "\n",
       "     avg_rating   pages          manufacturer  \\\n",
       "650         5.0  192000  Nhà Xuất Bản Văn Học   \n",
       "\n",
       "                                            cover_link  \n",
       "650  https://salt.tikicdn.com/ts/product/08/fd/a5/0...  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_df[data_df.pages > 3000]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9bd32c72",
   "metadata": {
    "papermill": {
     "duration": 0.019317,
     "end_time": "2022-12-12T14:40:04.370409",
     "exception": false,
     "start_time": "2022-12-12T14:40:04.351092",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Oh, there is one book with 192000 pages."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "cb710366",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:04.414861Z",
     "iopub.status.busy": "2022-12-12T14:40:04.414163Z",
     "iopub.status.idle": "2022-12-12T14:40:04.424118Z",
     "shell.execute_reply": "2022-12-12T14:40:04.423233Z"
    },
    "papermill": {
     "duration": 0.036356,
     "end_time": "2022-12-12T14:40:04.426604",
     "exception": false,
     "start_time": "2022-12-12T14:40:04.390248",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "data_df = data_df.query('pages < 3000')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59235f1c",
   "metadata": {
    "papermill": {
     "duration": 0.019503,
     "end_time": "2022-12-12T14:40:04.465630",
     "exception": false,
     "start_time": "2022-12-12T14:40:04.446127",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Manufacturer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "8032de12",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:04.506467Z",
     "iopub.status.busy": "2022-12-12T14:40:04.505812Z",
     "iopub.status.idle": "2022-12-12T14:40:04.515260Z",
     "shell.execute_reply": "2022-12-12T14:40:04.513939Z"
    },
    "papermill": {
     "duration": 0.032523,
     "end_time": "2022-12-12T14:40:04.517597",
     "exception": false,
     "start_time": "2022-12-12T14:40:04.485074",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Nhà Xuất Bản Thế Giới                            247\n",
       "NXB Trẻ                                          143\n",
       "Nhà Xuất Bản Hà Nội                              128\n",
       "Nhà Xuất Bản Dân Trí                             126\n",
       "Nhà Xuất Bản Kim Đồng                            113\n",
       "Nhà Xuất Bản Hội Nhà Văn                         111\n",
       "Nhà Xuất Bản Thanh Niên                           97\n",
       "Nhà Xuất Bản Tổng hợp TP.HCM                      91\n",
       "Nhà Xuất Bản Lao Động                             89\n",
       "Nhà Xuất Bản Văn Học                              76\n",
       "Nhà Xuất Bản Hồng Đức                             56\n",
       "Nhà Xuất Bản Công Thương                          46\n",
       "Nhà Xuất Bản Phụ Nữ Việt Nam                      38\n",
       "Nhà Xuất Bản Phụ Nữ                               30\n",
       "Nhà Xuất Bản Đà Nẵng                              16\n",
       "Nhà Xuất Bản Đại Học Quốc Gia Hà Nội              13\n",
       "Nhà Xuất Bản Mỹ Thuật                              8\n",
       "Nhà Xuất Bản Tri Thức                              7\n",
       "Nhà Xuất Bản Lao Động Xã Hội                       7\n",
       "NXB Dân Trí                                        6\n",
       "Nhiều Nhà Xuất Bản                                 6\n",
       "Nhà Xuất Bản Khoa Học Xã Hội                       5\n",
       "Nhà Xuất Bản Tài Chính                             5\n",
       "Nhà Xuất Bản Chính Trị Quốc Gia Sự Thật            4\n",
       "Nhà Xuất Bản Thông Tin Và Truyền Thông             3\n",
       "hong duc                                           3\n",
       "Nhà Xuất Bản Văn Hóa - Văn Nghệ TP.HCM             3\n",
       "Nhà Xuất Bản Kinh Tế TPHCM                         3\n",
       "Nhà Xuất Bản Đồng Nai                              3\n",
       "NXB Đại học Kinh Tế Quốc Dân                       3\n",
       "Nhà Xuất Bản Thông Tấn                             2\n",
       "Nhà Xuất Bản Đại Học Kinh Tế Quốc Dân              2\n",
       "Forbes Việt Nam                                    2\n",
       "Nhà Xuất Bản Khoa học & kỹ thuật                   2\n",
       "Nhà Xuất Bản Tôn Giáo                              2\n",
       "Nhà Xuất Bản Văn Hoá Dân Tộc                       1\n",
       "ĐHQG Hà Nội                                        1\n",
       "Nhà Xuất Bản Hồng Đức - Hội Luật Gia Việt Nam      1\n",
       "Nhà Xuất Bản Compass Publishing                    1\n",
       "Nhà Xuất Bản Thời Đại                              1\n",
       "Nhà Xuất Bản Giáo Dục Việt Nam                     1\n",
       "Name: manufacturer, dtype: int64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_df.manufacturer.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e0fe5e74",
   "metadata": {
    "papermill": {
     "duration": 0.019231,
     "end_time": "2022-12-12T14:40:04.556432",
     "exception": false,
     "start_time": "2022-12-12T14:40:04.537201",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "We can see some values using in the difference way:\n",
    "* Nhà Xuất Bản Hồng Đức & hong duc\n",
    "* Nhà Xuất Bản Dân Trí & NXB Dân Trí\n",
    "* Nhà Xuất Bản Đại Học Quốc Gia Hà Nội & ĐHQG Hà Nội\n",
    "\n",
    "\n",
    "Let grouping them"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "d9a78273",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:04.598699Z",
     "iopub.status.busy": "2022-12-12T14:40:04.597628Z",
     "iopub.status.idle": "2022-12-12T14:40:04.605884Z",
     "shell.execute_reply": "2022-12-12T14:40:04.605055Z"
    },
    "papermill": {
     "duration": 0.031895,
     "end_time": "2022-12-12T14:40:04.608240",
     "exception": false,
     "start_time": "2022-12-12T14:40:04.576345",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def handle_manufactuner(manufactuner):\n",
    "    if manufactuner == \"hong duc\":\n",
    "        return \"Nhà Xuất Bản Hồng Đức\"\n",
    "    elif manufactuner == \"NXB Dân Trí\":\n",
    "        return \"Nhà Xuất Bản Dân Trí\"\n",
    "    elif manufactuner == \"ĐHQG Hà Nội\":\n",
    "        return \"Nhà Xuất Bản Đại Học Quốc Gia Hà Nội\"\n",
    "    else:\n",
    "        return manufactuner\n",
    "    \n",
    "data_df.manufacturer = data_df.manufacturer.apply(lambda manufacturer: handle_manufactuner(manufacturer))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d0084440",
   "metadata": {
    "papermill": {
     "duration": 0.019444,
     "end_time": "2022-12-12T14:40:04.647211",
     "exception": false,
     "start_time": "2022-12-12T14:40:04.627767",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Handle missing values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "446404c4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:04.688818Z",
     "iopub.status.busy": "2022-12-12T14:40:04.687591Z",
     "iopub.status.idle": "2022-12-12T14:40:04.694239Z",
     "shell.execute_reply": "2022-12-12T14:40:04.693376Z"
    },
    "papermill": {
     "duration": 0.0298,
     "end_time": "2022-12-12T14:40:04.696611",
     "exception": false,
     "start_time": "2022-12-12T14:40:04.666811",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "data_df.manufacturer = data_df.manufacturer.fillna(\"Unknown\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "130dd3a8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:04.740648Z",
     "iopub.status.busy": "2022-12-12T14:40:04.739444Z",
     "iopub.status.idle": "2022-12-12T14:40:04.757800Z",
     "shell.execute_reply": "2022-12-12T14:40:04.756506Z"
    },
    "papermill": {
     "duration": 0.042028,
     "end_time": "2022-12-12T14:40:04.760449",
     "exception": false,
     "start_time": "2022-12-12T14:40:04.718421",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>product_id</th>\n",
       "      <th>title</th>\n",
       "      <th>authors</th>\n",
       "      <th>original_price</th>\n",
       "      <th>current_price</th>\n",
       "      <th>quantity</th>\n",
       "      <th>category</th>\n",
       "      <th>n_review</th>\n",
       "      <th>avg_rating</th>\n",
       "      <th>pages</th>\n",
       "      <th>manufacturer</th>\n",
       "      <th>cover_link</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>74021317</td>\n",
       "      <td>Cây Cam Ngọt Của Tôi</td>\n",
       "      <td>José Mauro de Vasconcelos</td>\n",
       "      <td>108000</td>\n",
       "      <td>64800</td>\n",
       "      <td>53075.0</td>\n",
       "      <td>Tiểu Thuyết</td>\n",
       "      <td>11481</td>\n",
       "      <td>5.0</td>\n",
       "      <td>244</td>\n",
       "      <td>Nhà Xuất Bản Hội Nhà Văn</td>\n",
       "      <td>https://salt.tikicdn.com/ts/product/5e/18/24/2...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>184466860</td>\n",
       "      <td>Hành Tinh Của Một Kẻ Nghĩ Nhiều</td>\n",
       "      <td>Nguyễn Đoàn Minh Thư</td>\n",
       "      <td>86000</td>\n",
       "      <td>59900</td>\n",
       "      <td>7929.0</td>\n",
       "      <td>Others</td>\n",
       "      <td>780</td>\n",
       "      <td>4.8</td>\n",
       "      <td>184</td>\n",
       "      <td>Nhà Xuất Bản Thế Giới</td>\n",
       "      <td>https://salt.tikicdn.com/ts/product/d7/99/24/1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>73787185</td>\n",
       "      <td>Những Tù Nhân Của Địa Lý</td>\n",
       "      <td>Tim Marshall</td>\n",
       "      <td>210000</td>\n",
       "      <td>126000</td>\n",
       "      <td>17896.0</td>\n",
       "      <td>Lĩnh vực khác</td>\n",
       "      <td>3623</td>\n",
       "      <td>4.8</td>\n",
       "      <td>430</td>\n",
       "      <td>Nhà Xuất Bản Hội Nhà Văn</td>\n",
       "      <td>https://salt.tikicdn.com/ts/product/8d/96/9e/c...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>52789367</td>\n",
       "      <td>Nhà Giả Kim (Tái Bản 2020)</td>\n",
       "      <td>Paulo Coelho</td>\n",
       "      <td>79000</td>\n",
       "      <td>47400</td>\n",
       "      <td>24668.0</td>\n",
       "      <td>Tác phẩm kinh điển</td>\n",
       "      <td>5131</td>\n",
       "      <td>5.0</td>\n",
       "      <td>228</td>\n",
       "      <td>Nhà Xuất Bản Hà Nội</td>\n",
       "      <td>https://salt.tikicdn.com/ts/product/45/3b/fc/a...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>147920903</td>\n",
       "      <td>Một Thoáng Ta Rực Rỡ Ở Nhân Gian</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>135000</td>\n",
       "      <td>81000</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>Tiểu Thuyết</td>\n",
       "      <td>1636</td>\n",
       "      <td>4.8</td>\n",
       "      <td>304</td>\n",
       "      <td>Nhà Xuất Bản Hội Nhà Văn</td>\n",
       "      <td>https://salt.tikicdn.com/ts/product/2f/b5/4e/a...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   product_id                             title                    authors  \\\n",
       "0    74021317              Cây Cam Ngọt Của Tôi  José Mauro de Vasconcelos   \n",
       "2   184466860   Hành Tinh Của Một Kẻ Nghĩ Nhiều       Nguyễn Đoàn Minh Thư   \n",
       "3    73787185          Những Tù Nhân Của Địa Lý               Tim Marshall   \n",
       "4    52789367        Nhà Giả Kim (Tái Bản 2020)               Paulo Coelho   \n",
       "5   147920903  Một Thoáng Ta Rực Rỡ Ở Nhân Gian                    Unknown   \n",
       "\n",
       "   original_price  current_price  quantity            category  n_review  \\\n",
       "0          108000          64800   53075.0         Tiểu Thuyết     11481   \n",
       "2           86000          59900    7929.0              Others       780   \n",
       "3          210000         126000   17896.0       Lĩnh vực khác      3623   \n",
       "4           79000          47400   24668.0  Tác phẩm kinh điển      5131   \n",
       "5          135000          81000   10000.0         Tiểu Thuyết      1636   \n",
       "\n",
       "   avg_rating  pages              manufacturer  \\\n",
       "0         5.0    244  Nhà Xuất Bản Hội Nhà Văn   \n",
       "2         4.8    184     Nhà Xuất Bản Thế Giới   \n",
       "3         4.8    430  Nhà Xuất Bản Hội Nhà Văn   \n",
       "4         5.0    228       Nhà Xuất Bản Hà Nội   \n",
       "5         4.8    304  Nhà Xuất Bản Hội Nhà Văn   \n",
       "\n",
       "                                          cover_link  \n",
       "0  https://salt.tikicdn.com/ts/product/5e/18/24/2...  \n",
       "2  https://salt.tikicdn.com/ts/product/d7/99/24/1...  \n",
       "3  https://salt.tikicdn.com/ts/product/8d/96/9e/c...  \n",
       "4  https://salt.tikicdn.com/ts/product/45/3b/fc/a...  \n",
       "5  https://salt.tikicdn.com/ts/product/2f/b5/4e/a...  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "797deb40",
   "metadata": {
    "papermill": {
     "duration": 0.019701,
     "end_time": "2022-12-12T14:40:04.800798",
     "exception": false,
     "start_time": "2022-12-12T14:40:04.781097",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Create new column(s)\n",
    "We have both original and current prices, let create discount column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "b03636c1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:04.842877Z",
     "iopub.status.busy": "2022-12-12T14:40:04.841790Z",
     "iopub.status.idle": "2022-12-12T14:40:04.848525Z",
     "shell.execute_reply": "2022-12-12T14:40:04.847306Z"
    },
    "papermill": {
     "duration": 0.030056,
     "end_time": "2022-12-12T14:40:04.850816",
     "exception": false,
     "start_time": "2022-12-12T14:40:04.820760",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "data_df['discount'] = round(1 - data_df['current_price']/data_df['original_price'],2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "186ba05e",
   "metadata": {
    "papermill": {
     "duration": 0.01977,
     "end_time": "2022-12-12T14:40:04.890832",
     "exception": false,
     "start_time": "2022-12-12T14:40:04.871062",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "The Vietnamese Dong currency is still long for visualization, so I decided to convert them into USD."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "9ebb05b7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:04.933204Z",
     "iopub.status.busy": "2022-12-12T14:40:04.931908Z",
     "iopub.status.idle": "2022-12-12T14:40:04.945680Z",
     "shell.execute_reply": "2022-12-12T14:40:04.944672Z"
    },
    "papermill": {
     "duration": 0.037592,
     "end_time": "2022-12-12T14:40:04.948293",
     "exception": false,
     "start_time": "2022-12-12T14:40:04.910701",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def convert_to_usd(vietnamdong):\n",
    "    usd = vietnamdong/23700\n",
    "    usd = round(usd, 2)\n",
    "    \n",
    "    return usd\n",
    "\n",
    "data_df.original_price = data_df.original_price.apply(lambda vietnamdong: convert_to_usd(vietnamdong))\n",
    "data_df.current_price = data_df.current_price.apply(lambda vietnamdong: convert_to_usd(vietnamdong))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8bd509a1",
   "metadata": {
    "papermill": {
     "duration": 0.019707,
     "end_time": "2022-12-12T14:40:04.988217",
     "exception": false,
     "start_time": "2022-12-12T14:40:04.968510",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## 3.2 Change Datatype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "a5c70918",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:05.030873Z",
     "iopub.status.busy": "2022-12-12T14:40:05.030175Z",
     "iopub.status.idle": "2022-12-12T14:40:05.045282Z",
     "shell.execute_reply": "2022-12-12T14:40:05.043833Z"
    },
    "papermill": {
     "duration": 0.039834,
     "end_time": "2022-12-12T14:40:05.048535",
     "exception": false,
     "start_time": "2022-12-12T14:40:05.008701",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 1767 entries, 0 to 1795\n",
      "Data columns (total 13 columns):\n",
      " #   Column          Non-Null Count  Dtype  \n",
      "---  ------          --------------  -----  \n",
      " 0   product_id      1767 non-null   int64  \n",
      " 1   title           1767 non-null   object \n",
      " 2   authors         1767 non-null   object \n",
      " 3   original_price  1767 non-null   float64\n",
      " 4   current_price   1767 non-null   float64\n",
      " 5   quantity        1767 non-null   float64\n",
      " 6   category        1767 non-null   object \n",
      " 7   n_review        1767 non-null   int64  \n",
      " 8   avg_rating      1767 non-null   float64\n",
      " 9   pages           1767 non-null   int64  \n",
      " 10  manufacturer    1767 non-null   object \n",
      " 11  cover_link      1767 non-null   object \n",
      " 12  discount        1766 non-null   float64\n",
      "dtypes: float64(5), int64(3), object(5)\n",
      "memory usage: 193.3+ KB\n"
     ]
    }
   ],
   "source": [
    "data_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "dcbfc07d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:05.091810Z",
     "iopub.status.busy": "2022-12-12T14:40:05.091131Z",
     "iopub.status.idle": "2022-12-12T14:40:05.103476Z",
     "shell.execute_reply": "2022-12-12T14:40:05.102566Z"
    },
    "papermill": {
     "duration": 0.03631,
     "end_time": "2022-12-12T14:40:05.105883",
     "exception": false,
     "start_time": "2022-12-12T14:40:05.069573",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "data_df.title = data_df.title.astype(\"string\")\n",
    "data_df.authors = data_df.authors.astype(\"string\")\n",
    "data_df.category = data_df.category.astype(\"string\")\n",
    "data_df.manufacturer = data_df.manufacturer.astype(\"string\")\n",
    "data_df.cover_link = data_df.cover_link.astype(\"string\")\n",
    "\n",
    "data_df.quantity = data_df.quantity.apply(lambda quantity: round(float(quantity)))\n",
    "data_df.quantity = data_df.quantity.astype(\"int64\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a15e0af",
   "metadata": {
    "papermill": {
     "duration": 0.020118,
     "end_time": "2022-12-12T14:40:05.146268",
     "exception": false,
     "start_time": "2022-12-12T14:40:05.126150",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Save File For Tableau"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "eea9f70e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:05.188117Z",
     "iopub.status.busy": "2022-12-12T14:40:05.187673Z",
     "iopub.status.idle": "2022-12-12T14:40:05.217241Z",
     "shell.execute_reply": "2022-12-12T14:40:05.216037Z"
    },
    "papermill": {
     "duration": 0.053524,
     "end_time": "2022-12-12T14:40:05.219757",
     "exception": false,
     "start_time": "2022-12-12T14:40:05.166233",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "data_df.to_csv(\"prepared_data_book.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "760228b5",
   "metadata": {
    "papermill": {
     "duration": 0.019693,
     "end_time": "2022-12-12T14:40:05.259560",
     "exception": false,
     "start_time": "2022-12-12T14:40:05.239867",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# 4. Exploratory Data Analysis (EDA)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "fba8aa17",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:05.302795Z",
     "iopub.status.busy": "2022-12-12T14:40:05.301477Z",
     "iopub.status.idle": "2022-12-12T14:40:05.320003Z",
     "shell.execute_reply": "2022-12-12T14:40:05.318722Z"
    },
    "papermill": {
     "duration": 0.04277,
     "end_time": "2022-12-12T14:40:05.322430",
     "exception": false,
     "start_time": "2022-12-12T14:40:05.279660",
     "status": "completed"
    },
    "tags": []
   },
   "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>product_id</th>\n",
       "      <th>title</th>\n",
       "      <th>authors</th>\n",
       "      <th>original_price</th>\n",
       "      <th>current_price</th>\n",
       "      <th>quantity</th>\n",
       "      <th>category</th>\n",
       "      <th>n_review</th>\n",
       "      <th>avg_rating</th>\n",
       "      <th>pages</th>\n",
       "      <th>manufacturer</th>\n",
       "      <th>cover_link</th>\n",
       "      <th>discount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>74021317</td>\n",
       "      <td>Cây Cam Ngọt Của Tôi</td>\n",
       "      <td>José Mauro de Vasconcelos</td>\n",
       "      <td>4.56</td>\n",
       "      <td>2.73</td>\n",
       "      <td>53075</td>\n",
       "      <td>Tiểu Thuyết</td>\n",
       "      <td>11481</td>\n",
       "      <td>5.0</td>\n",
       "      <td>244</td>\n",
       "      <td>Nhà Xuất Bản Hội Nhà Văn</td>\n",
       "      <td>https://salt.tikicdn.com/ts/product/5e/18/24/2...</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   product_id                 title                    authors  \\\n",
       "0    74021317  Cây Cam Ngọt Của Tôi  José Mauro de Vasconcelos   \n",
       "\n",
       "   original_price  current_price  quantity     category  n_review  avg_rating  \\\n",
       "0            4.56           2.73     53075  Tiểu Thuyết     11481         5.0   \n",
       "\n",
       "   pages              manufacturer  \\\n",
       "0    244  Nhà Xuất Bản Hội Nhà Văn   \n",
       "\n",
       "                                          cover_link  discount  \n",
       "0  https://salt.tikicdn.com/ts/product/5e/18/24/2...       0.4  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_df.head(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99ac5354",
   "metadata": {
    "papermill": {
     "duration": 0.020196,
     "end_time": "2022-12-12T14:40:05.363031",
     "exception": false,
     "start_time": "2022-12-12T14:40:05.342835",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Let create a new dataset to visualization easily."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "88221024",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:05.405661Z",
     "iopub.status.busy": "2022-12-12T14:40:05.405190Z",
     "iopub.status.idle": "2022-12-12T14:40:05.413160Z",
     "shell.execute_reply": "2022-12-12T14:40:05.411810Z"
    },
    "papermill": {
     "duration": 0.032331,
     "end_time": "2022-12-12T14:40:05.415806",
     "exception": false,
     "start_time": "2022-12-12T14:40:05.383475",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "eda_df = data_df.drop(['product_id', 'cover_link'], axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e2180996",
   "metadata": {
    "papermill": {
     "duration": 0.019998,
     "end_time": "2022-12-12T14:40:05.456324",
     "exception": false,
     "start_time": "2022-12-12T14:40:05.436326",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## 4.1 Data Overviewing"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d766ba11",
   "metadata": {
    "papermill": {
     "duration": 0.019983,
     "end_time": "2022-12-12T14:40:05.496650",
     "exception": false,
     "start_time": "2022-12-12T14:40:05.476667",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Price\n",
    "* original_price\n",
    "* current_price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "2f8879b6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:05.539576Z",
     "iopub.status.busy": "2022-12-12T14:40:05.538990Z",
     "iopub.status.idle": "2022-12-12T14:40:05.822041Z",
     "shell.execute_reply": "2022-12-12T14:40:05.821112Z"
    },
    "papermill": {
     "duration": 0.307548,
     "end_time": "2022-12-12T14:40:05.824705",
     "exception": false,
     "start_time": "2022-12-12T14:40:05.517157",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.subplots(figsize=(10, 7))\n",
    "\n",
    "ax = sns.kdeplot(eda_df.original_price, color='gray', shade=True, label='Original')\n",
    "ax = sns.kdeplot(eda_df.current_price, color='g', shade=True, label='Current')\n",
    "\n",
    "plt.xlabel('Price')\n",
    "plt.title('Density of Original and Current Price')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b4766284",
   "metadata": {
    "papermill": {
     "duration": 0.020763,
     "end_time": "2022-12-12T14:40:05.867659",
     "exception": false,
     "start_time": "2022-12-12T14:40:05.846896",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Look at the picture, the price of almost books is less than $20. There is a intering thing, that the price of books in Vietnam is so cheap."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8aeaee34",
   "metadata": {
    "papermill": {
     "duration": 0.021252,
     "end_time": "2022-12-12T14:40:05.910250",
     "exception": false,
     "start_time": "2022-12-12T14:40:05.888998",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Discount per Category"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d8c6e69a",
   "metadata": {
    "papermill": {
     "duration": 0.020739,
     "end_time": "2022-12-12T14:40:05.952440",
     "exception": false,
     "start_time": "2022-12-12T14:40:05.931701",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "We will focus on the discount baseded on category."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "26a65f36",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:05.996913Z",
     "iopub.status.busy": "2022-12-12T14:40:05.996181Z",
     "iopub.status.idle": "2022-12-12T14:40:06.008011Z",
     "shell.execute_reply": "2022-12-12T14:40:06.006902Z"
    },
    "papermill": {
     "duration": 0.037043,
     "end_time": "2022-12-12T14:40:06.010723",
     "exception": false,
     "start_time": "2022-12-12T14:40:05.973680",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "category\n",
       "Bài học kinh doanh                         0.263962\n",
       "Kiến Thức Bách Khoa                        0.311739\n",
       "Kiến thức - Bách khoa                      0.308485\n",
       "Light novel                                0.250000\n",
       "Lĩnh vực khác                              0.316774\n",
       "Lịch Sử Thế Giới                           0.314286\n",
       "Others                                     0.230339\n",
       "Sách Chiêm Tinh - Horoscope                0.259286\n",
       "Sách Học Tiếng Anh                         0.310750\n",
       "Sách Học Tiếng Hoa                         0.182857\n",
       "Sách Làm Cha Mẹ                            0.308125\n",
       "Sách Marketing - Bán hàng                  0.254500\n",
       "Sách giáo dục                              0.291538\n",
       "Sách kinh tế học                           0.324615\n",
       "Sách kỹ năng làm việc                      0.296364\n",
       "Sách nghệ thuật sống đẹp                   0.281552\n",
       "Sách quản trị, lãnh đạo                    0.286667\n",
       "Sách tài chính, tiền tệ                    0.121750\n",
       "Tiểu Thuyết                                0.353910\n",
       "Tiểu sử - Hồi ký                           0.363750\n",
       "Truyện Giả tưởng - Huyền Bí - Phiêu Lưu    0.345946\n",
       "Truyện dài                                 0.363043\n",
       "Truyện kể cho bé                           0.339444\n",
       "Truyện ngắn - Tản văn - Tạp Văn            0.325000\n",
       "Truyện tranh Ehon                          0.301429\n",
       "Truyện trinh thám                          0.325385\n",
       "Truyện đam mỹ                              0.267222\n",
       "Tác phẩm kinh điển                         0.350000\n",
       "Tô màu - Luyện chữ                         0.380833\n",
       "Văn học thiếu nhi                          0.282857\n",
       "Name: discount, dtype: float64"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Finding the mean of discount for each category.\n",
    "eda_df.groupby('category').discount.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "e4428964",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:06.055480Z",
     "iopub.status.busy": "2022-12-12T14:40:06.054394Z",
     "iopub.status.idle": "2022-12-12T14:40:06.446978Z",
     "shell.execute_reply": "2022-12-12T14:40:06.445588Z"
    },
    "papermill": {
     "duration": 0.418121,
     "end_time": "2022-12-12T14:40:06.450016",
     "exception": false,
     "start_time": "2022-12-12T14:40:06.031895",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(10,10))\n",
    "\n",
    "ax=eda_df.groupby('category').discount.mean().sort_values(ascending=True).plot(kind='barh', color='gray')\n",
    "\n",
    "plt.xlabel('Discount rating')\n",
    "plt.ylabel('Category')\n",
    "plt.title('The Mean Discounting of Categories')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f79cee4d",
   "metadata": {
    "papermill": {
     "duration": 0.022176,
     "end_time": "2022-12-12T14:40:06.494814",
     "exception": false,
     "start_time": "2022-12-12T14:40:06.472638",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Most of the discounted categories is tale (contain 'Truyen')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e9ffedbc",
   "metadata": {
    "papermill": {
     "duration": 0.02213,
     "end_time": "2022-12-12T14:40:06.539376",
     "exception": false,
     "start_time": "2022-12-12T14:40:06.517246",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Quantity per Category All of Time"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b70f8466",
   "metadata": {
    "papermill": {
     "duration": 0.022331,
     "end_time": "2022-12-12T14:40:06.584531",
     "exception": false,
     "start_time": "2022-12-12T14:40:06.562200",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Let see how the mean of selled books by each category."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "ccd7f8b4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:06.632039Z",
     "iopub.status.busy": "2022-12-12T14:40:06.631527Z",
     "iopub.status.idle": "2022-12-12T14:40:07.021528Z",
     "shell.execute_reply": "2022-12-12T14:40:07.020338Z"
    },
    "papermill": {
     "duration": 0.417082,
     "end_time": "2022-12-12T14:40:07.024173",
     "exception": false,
     "start_time": "2022-12-12T14:40:06.607091",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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evdu8fefOnbRt25YaNWrkuK3Y2FiCgoI4fvw4tWvXtjim7PTs2ZOePXvi5uZGQEBAnrYtIiIi8rhT8VEAYmNjcXR0xM7ODgAnJyfzvvnz5xMWFkZKSgouLi5MmTIFKysrIiMj8fPzIz4+HoPBQGBgIADJycn4+Phw6tQp6tWrx6xZs7CyssrUX//+/WnYsCHh4eEkJiYydepUXF1duXnzJr6+vpw+fZpnnnmGK1euMGnSJBo0aADAnDlzCAsLo2jRoixcuJCyZcsSHx+Pn58fly5dAmDChAk0adLE3Fdqairz5s3j1q1bHDp0yDwyc+bMGfr378+lS5cYOHAgAwYMICoqinfeeYdvv/0WgM8//5zk5GRGjBjBpk2bWL16NWlpaTz99NO0atWKEydOsGvXLn755RcWLVpEUFAQVatWNfe9detWFixYgLW1NQ4ODqxYsYKUlBTWrl3LsWPHMBgM+Pr68sILLxAcHMyuXbu4efMmFy9exN3dnfHjxwOwdu1alixZgoODA7Vr18bOzo5JkyZlymlCQgJjxowhJiaG559/HpPJZN4XGhrKV199RVpaGo0aNcLPzw+DwYCLiwu9e/dm//79lC1bljlz5mT624uIiIjkNUse/FcQbd2haVcF4KWXXuLy5cu0b9+eyZMn88svv5j3vfHGG6xfv55NmzaRnJxMWFgYAGPHjuX1119n48aNrFq1CmdnZwCOHz/OhAkT2LJlC1FRURw6dCjbPo1GI+vWrWPChAnMnz8fgG+++YZSpUqxZcsWRo4cyW+//WY+Pjk5mUaNGrFx40ZcXV1Zs2YNAFOnTmXgwIGsX7+eoKAgPvjgg0z92NnZ4ePjg6enJ6GhoXh6egJw/vx5Pv/8c9auXcuCBQsyjfRkx8PDg/Xr17Nx40aeffZZ1q1bR+PGjXFzc2P8+PGEhoZmKjwAFi5cyOeff87GjRtZtGgRACtWrABg06ZNfPLJJ/j6+pKSkgLcHqGZO3cumzZtYuvWrVy+fJmYmBgWLVrE6tWrWblyJefOncs2vgULFtC4cWM2b96Mh4eHuRg7e/YsW7duZeXKlYSGhmJtbc2mTZvMOa1fvz6bN2+madOm5r+DiIiISH6JjU3Mk39y0pYlNPJRAIoXL05wcDAHDx4kPDycUaNGMWbMGHr06MHBgwf58ssvMRqNXLlyhVq1atGsWTNiYmLw8PAAoEiRIua2GjZsSIUKFQCoXbs20dHRuLq6Zunzzrn16tUjOjoagEOHDjFgwAAAatasSa1atczH29ra8vLLLwNQv3599u/fD8CPP/6Yac3FjRs3SEpKonjx4ve85jZt2mBnZ4eTkxNOTk73Xax++vRp5s6dS2JiIklJSbRs2fKex8PtdSq+vr507NjRfL2HDh3ijTfeAKB69epUqlSJ8+fPA9CiRQscHBzM+6Kjo/nrr79o2rQppUuXBqBDhw5cuHAhS18HDhwwFw9t27alVKlSAPz0008cO3aMXr16AXDr1i3KlCkDgLW1tbkY8/LyYvjw4fe9JhEREZHHmYqPAmIwGGjevDnNmzenZs2ahISE0LlzZ/z8/AgJCcHZ2Zl58+aZf6W/mztTt+60md0C8L8fZ21tfddj/s7W1tY8fevv52RkZLBmzZpMBVBO/DPO9PR0bGxsyMjIMG//+7X6+vqycOFCateuTXBwcKbRobuZMmUKhw8fZvfu3fTs2ZP169fnKqac5OV+TCYT3bt3Z8yYMfc99p/T40RERESeNJp2VQDOnTuX6df0EydOUKlSJW7dukVGRgYODg4kJSWxY8cOAEqUKEGFChXYuXMncHtdxc2bNx84jsaNG7N161bg9pqMU6dO3fecli1b8tVXX2WK/Z+KFy9OUlLSfdsqU6YMV69eJSEhgdTU1EwLy5OSknB2diYtLc08bel+bf/xxx80atSIkSNH4ujoyJ9//omrq6v5/PPnz3P58mWeffbZu8bUoEEDDhw4wLVr10hPTzf/Df6padOm5nb37NnDtWvXgNujKdu3bzeP7Pz111/mkaaMjAy2b98O3J4G9ve1MiIiIiJPIo18FIDk5GQCAgK4fv06BoOBp59+milTplCyZEl69epF586dKVu2rHnhN8CMGTOYNGkSgYGB2NramhecP4jXXnsNX19fPD09efbZZ6lRo4Z5GtLdTJw4kSlTptClSxeMRiOurq5MmTIl0zHNmzdn8eLFeHl53fNWwLa2trz77rv07t2b8uXLZyoKRo4cSe/evXFycqJRo0bmgsPT05MPP/yQr776innz5mVa9zFjxgwiIyMxmUy88MIL1K5dm2effZbJkyfTpUsXDAYD06ZNyzTi8U/ly5dn6NCh9O7dm1KlSvHss89mm5N3332XMWPG0KlTJ1xcXKhUqRIANWrU4L333uOtt94iIyMDW1tbJk2aROXKlbG3t+fIkSMsWrQIJycn5s6de89cA/j5+Vk8h/JJ5uzsoLxZSLmzjPJmOeXOMsqb5ZS7h4uV6e+37ZHHmtFoJD09nSJFivDHH38waNAgtm3bds8v50+CO2tY0tPTGT58OD179jSvIXkQLi4uRERE5Po8/R9k7uk/LJZT7iyjvFlOubOM8mY55c4yOcmbJXfD0sjHE+TmzZsMGDCA9PR0TCYTfn5+OS48atWqxffff0+VKlXyLb6QkBBu3rxJv3798q2P7MyfP58ff/yRlJQUWrZsibu7e67b+P777zl79ixDhgzJhwhFREREHg8a+RB5yOjXmdzTr1qWU+4so7xZTrmzjPJmOeXOMvk18qEF5yIiIiIiUiBUfIiIiIiISIFQ8SEiIiIiIgVCxYeIiIiIiBQIFR8iIiIiIlIgdKtdkYeIv79/YYcgInJX3t6jCzsEEXnEaeRDnmi7d+9m3759edrmd999x4ULF/K0TREREZHHgYoPeeglJCTg5eWFl5cXL730Eq1atTK/T01NtbjdI0eOEBERwc8//8zp06cfKEYXFxfz67p16zJ9+nQyMjIyHdO3b98H6kNERETkUadpV/LQc3R0JDQ0FICgoCDs7e15++23zfvT09Oxscn9R7lhw4Y0bNgwz+K8o3LlygwePJiLFy/y9NNPm7evWrUqz/sSEREReZSo+JBHkq+vL3Z2dpw4cYLGjRtTokSJTEVJ586d+fTTT1m/fj2lSpVi0KBBAMyZMwcnJycGDhzIkiVL2Lp1K6mpqXh4eODj40NUVBSDBw+mSZMmREREUL58eRYuXEjRokUz9X/x4kXGjh1LcnIybm5u5u1JSUl4e3tz/fp10tPTGTlyJO7u7sDt0ZGIiIiCSZCISD6w5GnG+dnOk0Z5s5xyZ5n8yJuKD3lkxcTEsGrVKgwGA0FBQdke07NnT0aMGMGgQYPIyMhg8+bNrF27ln379hEZGcm6deswmUwMGzaMAwcOULFiRSIjI5k9ezYBAQGMHDmS7du34+XllandqVOn0q9fP7p168aKFSvM24sUKcKCBQsoUaIE8fHxvPrqq7Rr1w4rK6t8zYWISEGIjU184DacnR3ypJ0njfJmOeXOMjnJmyXFiYoPeWR16NABg8Fwz2OqVKlC6dKlOX78OHFxcdStWxdHR0f279/P/v376datGwDJyclcuHCBihUrUqVKFerUqQNAvXr1iI6OztJuRESEueDx8vJi1qxZAJhMJmbPns2BAwewtrYmJiaGuLg4nJ2d8/DKRURERB5NKj7kkVWsWDHza4PBkGmBd0pKivl17969CQ4OJi4ujp49ewK3i4QhQ4ZkWQQeFRWFnZ1dpnb/3tbfZTeasWnTJuLj4wkODsbW1hY3N7e7ni8iIiLypNHdruSxULlyZY4fPw7Ab7/9RlRUlHmfu7s7P/zwA0ePHqVly5YAtGzZkvXr15OUlATcnsJ19erVHPfn4uLC5s2bAdi4caN5e2JiImXKlMHW1paff/4521ETERERkSeVRj7ksdC+fXtCQ0Pp1KkTDRs2pFq1auZ9dnZ2NG/enJIlS5qnabVs2ZKzZ8+aRz7s7e2ZOXMm1tY5q8cnTpzI2LFjWbJkSaYF5126dGHYsGF06dKF+vXr8+yzz+bqOvz8/DQv1QKaz2s55c4yypuIiGWsTCaTqbCDEMlPGRkZdO/encDAwExFycNKX2hyT18ELafcWUZ5s5xyZxnlzXLKnWXya8G5pl3JY+3MmTN4eHjQokWLbAsPLy8v8214RURERCR/adqVPNZq1KjB999/f9f9dx5eKCIiIiL5TyMfIiIiIiJSIFR8iIiIiIhIgVDxISIiIiIiBULFh4iIiIiIFAgVHyIiIiIiUiB0tyspUCEhISxduhRvb286dOhQ2OE8dPz9/Qs7BJE85+09urBDEBGRh4RGPqRAvfzyywQEBHD+/PkHbuvMmTP07duX6dOn50Fk2btw4QI+Pj4YjUaL27h48SL9+/cnJSUlDyMTERERefRo5EMeSEJCgvkhfXFxcVhbW+Pk5MQff/yBl5cXkydPBm5/iZ8yZQr16tXDxsYGb2/vB+77mWee4f333zcXBikpKdjY2GAwGO57bnh4OEuXLuWzzz4zb/P19aVt27Z06NABk8lEQEAAycnJdOnSheTkZBwcHJg4cSJvvvkmNWrUyNSem5sb69atw8nJKdP2jIwMZs6cyccff0yRIkUe+JpFREREHmUqPuSBODo6mh/UFxQUhL29PW+//XaW465evcqCBQs4duwYjRo1wtbW9oH7NhgMuLi4mN9v376dqlWr8vzzzz9w22lpabz77rs4OjoSGxuLg4MDAFOnTs1VO9bW1sybN++B4xERERF5HGjaleSL8PBwhg4dCkBycjLr1q2jf//+TJ06lb179wIQHBzMlClTzOcMHTqU8PDwLG3NmjULT09PunTpwscffwzcHqXYtm2b+ZhatWoREhJC1apV8yT+Q4cO8dZbb9G1a1fmzJlDamoqAP379+fo0aN3Pe/WrVv861//YtWqVbzyyivEx8cDt0dAPDw8zO9FREREnkQa+ZB89+mnn/LCCy8wbdo0rl+/Tu/evXnxxRdzdG5CQgLfffcd27Ztw8rKiuvXr2d7nL29PUuXLs1VXAcPHsTLy8v8/vLly7Rt25aUlBR8fX1ZtmwZzzzzDOPHj+ebb74xTy+7m+TkZEaPHk23bt3o1q0bcXFxbNy4kUGDBvHjjz9Su3btLNOyRJ4Ezs4OhR1Cvnhcr6sgKHeWUd4sp9xZJj/ypuJD8t2+ffvYtWuXuThISUnh8uXLOTrXwcGBIkWKMGHCBF5++WXatm2bZ3G5urpmWfMBcP78eapUqcIzzzwDQPfu3VmxYsV9iw9vb2/+9a9/0bVrVwB69uyJt7c3gwYNYv369fTo0SPPYhd5lMTGJhZ2CHnO2dnhsbyugqDcWUZ5s5xyZ5mc5M2S4kTTrqRAzJs3j9DQUEJDQ9m9ezfVq1fHYDCQkZFhPia7u0HZ2Niwbt06OnToQFhYGP/6178AMp2bkZFBWlpalnNXrFiBl5cXXl5exMTE5NOV/Z/GjRvzww8/YDKZAKhYsSJlypThp59+4siRI7Ru3TrfYxARERF5mKn4kHzXsmVLvv76a/OX8uPHjwNQuXJlTp48SUZGBpcvX+bIkSNZzk1KSiIxMZE2bdowYcIEfv/9d/O5v/32GwC7du3Ktvh4/fXXzQVP+fLlcxzvM888Q3R0NJGRkQCEhobStGnT+57n4+NDqVKlMj2ro3fv3owbN44OHTrk6C5cIiIiIo8zTbuSfOft7c1HH31E165dycjIoEqVKnz22Wc0adKEypUr4+npSfXq1alXr16Wc5OSkvD29jaPityZGtWnTx+8vb3p2rUrbdq0wd7ePs/iLVKkCNOmTWPkyJEYjUbq169Pv379cnTuxIkTmTBhAjNmzGD8+PG4ubnx73//O8dTrvz8/DQ0bAENqVtOuRMRkYJkZbrzc7SI5LmjR48ybdo0vvnmmxyfoy+Cuacv0JZT7iyjvFlOubOM8mY55c4y+bXmQyMfIvlk8eLFrFy5kpkzZxZ2KCIiIiIPBRUfIvlkyJAhDBkypLDDEBEREXloaMG5iIiIiIgUCBUfIiIiIiJSIFR8iIiIiIhIgVDxISIiIiIiBULFh4iIiIiIFAjd7UrkIfL3p6OL5Ddv79GFHYKIiDxhNPIhWXz33XdcuHChsMMQERERkceMio8nVJ06dfDy8qJr1650796dX3/91byvbt26TJ8+nYyMjEzn9O3bN0s7UVFRdO7cOU9ju1ubR48eJSAgwKJz78fFxSXX59xP//79OXr0aJ63KyIiIvKo0rSrJ1TRokUJDQ0F4IcffmD27Nl8/fXXAFSuXJnBgwdz8eJFnn76afM5q1atKpRY72jQoAENGjQo1BhERERExHIa+RBu3LhByZIlAUhKSmLgwIEEBAQwfPhwdu7caT7ubqMDRqORDz74gE6dOvHWW29x69YtAE6cOEGfPn3o0qUL7777LteuXQMgMjKSQYMGmUdd/vjjj7vGdvHiRbp168aRI0cIDw9n6NChAAQFBfHvf/+b/v37065dO5YvX37feP7Z7quvvkqXLl2YM2eOebvJZOLjjz+mc+fOdOnShS1btmTKS/fu3enSpYs5L1FRUXTs2PGu/W3bto1evXrRvn17Dh48eI+/goiIiMjjTyMfT6hbt27h5eVFSkoKsbGxfPnllwAUKVKEBQsWUKJECeLj43n11Vdp164dVlZWd20rMjKS2bNnExAQwMiRI9m+fTteXl6MHz+eDz/8kGbNmhEYGMj8+fOZOHEiY8eOZciQIXh4eJCSkpJletcd586dY/To0UyfPp3atWsTHh6eaf/58+dZvnw5N27coGPHjvTr1++e8fzd1KlT6devH926dWPFihXm7Tt27ODkyZOEhoaSkJBAr169cHV1xcnJKdu83K8/o9HIunXr2LNnD/Pnz2fZsmW5+0OJ5CNnZ4dM/5bcUd4sp9xZRnmznHJnmfzIm4qPJ9Tfp11FRETw/vvv8+2332IymZg9ezYHDhzA2tqamJgY4uLicHZ2vmtbVapUoU6dOgDUq1eP6OhoEhMTSUxMpFmzZgB0796dkSNHcuPGDWJiYvDw8ABuFzvZiY+Px9vbm/nz51OjRo1sj2nTpg12dnY4OTnh5OTE1atX7xrPP0VERBAUFASAl5cXs2bNAuDQoUN06tQJg8FA2bJladq0KUePHqV169bZ5uV+/d25zrvFIVKYYmMTcXZ2IDY2sbBDeeQob5ZT7iyjvFlOubNMTvJmSXGi4kNwcXEhISGB+Ph49uzZQ3x8PMHBwdja2uLm5kZKSso9z7ezszO/NhgM9z0+JxwcHKhUqRKHDh26a/Hxz37T09NzFc+9RnP+adOmTXfNy736u7PP2toao9GY4/5EREREHkda8yGcPXsWo9FI6dKlSUxMpEyZMtja2vLzzz9b/Gu9g4MDJUuWNK9zCA0NpWnTppQoUYIKFSqY10ykpqZy8+bNLOfb2toyf/58QkJC2LRpk+UXdxcuLi5s3rwZgI0bN5q3u7q6snXrVoxGI/Hx8Rw8eJCGDRvmWV5EREREnmQa+XhC3VnzAf+3yNpgMNClSxeGDRtGly5dqF+/Ps8++6zFfXz88cf4+flx8+ZNnnrqKaZNmwbAjBkzmDRpEoGBgdja2hIYGMhTTz2V5Xx7e3s+++wz3nzzTezt7SlRooTFsfzTnbUnS5Yswc3Nzbzdw8ODiIgIvLy8sLKyYty4cTg7O+dpXu7Fz89PQ8MW0JC6iIjIo8HKZDKZCjsIEfk/+hKdeyo+LKfcWUZ5s5xyZxnlzXLKnWXya82Hpl1Jvrp+/TqDBw8u7DBERERE5CGg4kPyVcmSJfnvf/9b2GGIiIiIyENAxYeIiIiIiBQIFR8iIiIiIlIgVHyIiIiIiEiBUPEhIiIiIiIFQsWHiIiIiIgUCD1k8BH1yy+/UKpUKWrVqlXYoUge8vf3L+wQ5BHg7T26sEMQERGxiEY+8sDu3bvZt29fgfV348YNvvjii3x7yvY/HT58mF69erFkyZIC6U9EREREHk9PzMhHQkICgwYNAiAuLg5ra2ucnJwAWLt2LXZ2dha1e+TIESIiIjAajZQvX57nnnsur0LOVlRUFDNmzMDGxoY9e/bg7u7+wG2uX7+e5cuXA3D27FmeeeYZrK2tadWqFWPHjqVOnTrMmDGDH3/88YH7uuPnn39m9uzZWFtb89577/HCCy88cJuLFi1i27ZtAJw6dYqaNWsC0LNnTwYMGGBxu/3792fIkCG0atXKvG3ZsmWcP38ef39/vvjiC7799ltKlCjBJ598QtmyZR/sQkREREQeU1Ymk8lU2EEUtKCgIOzt7Xn77bfN29LT07GxeWJqsbtyc3Nj3bp15sLsjoMHD+Lq6lpIUeWei4sLERERedLW6tWr+d///se0adPM2/r06cO4ceNo2rRpnvRxh6ZdSU7k5bQrZ2cHYmMT86y9J4XyZjnlzjLKm+WUO8vkJG/Ozg65bveJ/rbt6+uLnZ0dJ06coHHjxpQoUSJTUdK5c2c+/fRT1q9fT6lSpcwjJ3PmzMHJyYmBAweyZMkStm7dSmpqKh4eHvj4+BAVFcXgwYNp0qQJERERlC9fnoULF1K0aNEs/ZcoUYJjx44RGxvLuHHj6NChAxkZGUyZMoWff/6ZihUrYmNjQ8+ePenQoQPz588nLCyMlJQUXFxcmDJlClZWVvTv35+GDRsSHh5OYmIiU6dOzZNi4ciRI0ydOpWUlBSKFi3KRx99xLPPPktwcDC7du3i5s2bXLx4EXd3d8aPH5/p3L1797Ju3TrmzZsHQHh4OEuXLuWzzz5jwoQJnDx5kpSUFNq3b4+Pjw9wu/jp1q0bYWFhpKenM3fuXKpXr/7A17Fr1y4WLVpEWloapUuXZtasWZQtW5agoCD++OMP/vjjDxISEvjXv/5Fnz59Mp3bvn175s6dS2pqKnZ2dkRFRXHlyhVcXV25du0aw4cP58aNG6SnpzNy5Ejc3d1z/BkQEREReZI80cUHQExMDKtWrcJgMBAUFJTtMT179mTEiBEMGjSIjIwMNm/ezNq1a9m3bx+RkZGsW7cOk8nEsGHDOHDgABUrViQyMpLZs2cTEBDAyJEj2b59O15eXlnavnLlCt988w3nzp1j2LBhdOjQgR07dhAdHc2WLVu4evUqnp6e9OzZE4A33niD4cOHYzKZGDt2LGFhYbi5uQFgNBpZt24de/bsYf78+SxbtuyB8/Pss8+yYsUKbGxs+PHHH5kzZ445TydOnCAkJAQ7Ozs6dOhA//79qVixovncF198kUmTJpGcnIy9vT1btmzB09MTgPHjx1O6dGnS09MZOHAgJ0+epHbt2gA4OjqyYcMGVqxYwdKlS5k6deoDX0eTJk1Ys2YNVlZWrF27liVLluDr6wvA77//zpo1a0hOTqZ79+60adOG8uXLm88tXbo0DRs2ZO/evbi7u7NlyxY6duyIlZUVxYoVY9GiRZQoUYKrV6/y6quv0q5dO4AcfwZEcsuSX5oKsr0nhfJmOeXOMsqb5ZQ7y+RH3p744qNDhw4YDIZ7HlOlShVKly7N8ePHiYuLo27dujg6OrJ//372799Pt27dAEhOTubChQtUrFiRKlWqUKdOHQDq1atHdHR0tm27u7tjbW1NjRo1iIuLA+DQoUN06NABa2trnJ2dad68ufn4gwcP8uWXX2I0Grly5Qq1atUyFx8eHh737S+3EhMTef/994mMjMTKyoq0tDTzvhYtWuDgcPtDWb16daKjozMVHzY2NrRq1YqwsDDat2/Pnj17GDduHADfffcdwcHBWFlZcfHiRc6ePWsuPl555RUA6tevz3fffZcn1/Hnn38yatQoYmNjSU1NpUqVKuZ97dq1o2jRohQtWpTmzZtz9OjRTMUHQKdOndiyZQvu7u5s3rzZXBBZW1sTFBTE4cOHsbGxIS4uzvx3zOlnQCS38nL6gKYjWEZ5s5xyZxnlzXLKnWU07SqfFCtWzPzaYDCQkZFhfp+SkmJ+3bt3b4KDg4mLizOPQphMJoYMGULfvn0ztRkVFZVpAbvBYMjU1t/lZqF7amoqH374IRs2bKBChQoEBQVlavdOW9bW1hiNxiznz5kzh927dwMQGhqaoz4DAwNp3rw5CxYsICoqKtPC7X9eY3Z9enp6smLFCkqVKkX9+vUpUaIEUVFRfPrpp2zYsIGSJUvi6+ub6TpsbW3veR3//ve/OX78OOXKleO///1vjq4jICCAQYMG0a5dO8LDw5k/f755n5WV1X3Pb9euHdOmTeO3337j1q1b1K9fH4BNmzZx+fJlvv76a2xsbHBzczNfS04/AyIiIiJPCt1q928qV67M8ePHAfjtt9+Iiooy73N3d+eHH37g6NGjtGzZEoCWLVuyfv16kpKSgNtTuK5evfrAcTRu3JgdO3aQkZFBXFwcv/zyCwC3bt3CxsaGcuXKYTQa2bNnT67aHTVqFKGhoTkuPOD2yMedUYANGzbkqj+AZs2acfz4cdasWWOecpWYmEiZMmUoWbIkycnJ/Pzzz7lqc9q0aYSGhua48LjT553rCAkJybTv+++/JyUlhYSEBH755RcaNGiQ5fzixYvTvHlzJkyYQKdOnczbr127RtWqVbGxseHkyZNcunQpV9ciIiIi8iR54kc+/q59+/aEhobSqVMnGjZsSLVq1cz77OzsaN68OSVLljRP02rZsiVnz541j3zY29szc+ZMrK0frKZr3749P/30E56enlSsWJG6devi4OBAyZIl6datG2+++SZly5bNFF9++de//oWvry+LFi2iTZs2uT7fYDDQtm1bNmzYwMcffwxA7dq1qVatGkOHDqVkyZLm6Vb5afjw4YwcOZJSpUrRvHnzTIVlrVq1GDBgAAkJCXh7e2eZcnVH586deffdd5k9e7Z5W9euXRkxYgSjR4/G0dGRqlWrPlCcfn5+Ghq2gIbURUREHg1P5K12LZGRkUH37t0JDAwskC/9SUlJFC9enISEBHr37s3KlStxdnbO936fNNnddrmw6Ut07qn4sJxyZxnlzXLKnWWUN8spd5bRmo9CdObMGYYOHYqHh0e2hYeXlxeOjo55cnepO9555x2uX79OWloa3t7eKjzywI8//siBAwcYOXJkYYciIiIi8kTSyIfIQ0a/zuSeftWynHJnGeXNcsqdZZQ3yyl3lsmvkQ8tOBcRERERkQKh4kNERERERAqEig8RERERESkQKj5ERERERKRAqPgQEREREZECoVvtijxE/P39CzsEech5e48u7BBEREQsppEPEREREREpECo+HnOnT59m165d+dL2xYsX2bp1a760fUdwcDAxMTH52kd2tmzZQmBg4AO3c+PGDT799FNu3bqVB1GJiIiIPNpUfDziFi1aRKdOnejSpQteXl4cPnzYvC89PZ3p06dTr169e7YRHh7O0KFD79vXPwuBp556ip07d3Ly5MlMxwUGBvLjjz/mKP579b13714OHz5M+fLl73q+r68v27Zty1Ffd3z66aeZ3vft29f8OiEhgfHjx7Nnzx5efPFFcvMMzp07d3LmzJlM22bNmkXt2rWZO3durmIUEREReRxpzccjLCIigt27d7Nhwwbs7OyIj48nLS3NvD8yMhIfH597fnnPjQ0bNvDcc89las/f358ff/yR2rVrm7eNHDkyT/qLi4vjgw8+yJO2/u6zzz7jnXfeMb9ftWqV+bW1tTX+/v6YTCaMRiNWVlY5bnfnzp20bduWGjVqmLdNnjwZgLZt2z5w3CIiIiKPOhUfj7DY2FgcHR2xs7MDwMnJybxv/vz5hIWFkZKSgouLC1OmTMHKyorIyEj8/PyIj4/HYDCYpxYlJyfj4+PDqVOnqFevHrNmzcr0xXvbtm0cO3aMsWPHUrRoUVavXs2SJUvMffzwww/mPnx9fWnbti0dOnTIFG9u+75T7DRo0AAXFxcGDBhAWFgYRYsWZeHChZQtWxaAgwcPsmzZMmJjYxk3blyWfv9u1qxZ3Lp1Cy8vL2rUqMEnn3yCi4sLERERAKxdu5atW7eSmpqKh4cHPj4+REVFMXjwYJo0aUJERATly5dn4cKFFC1a1Nzur7/+yq5du/jll19YtGgRQUFBwO3iLCEhgaJFi/Kf//yH6tWrW/z3FgFwdnZ4JNp8EihvllPuLKO8WU65s0x+5E3FxyPspZdeYsGCBbRv354WLVrg6elJs2bNAHjjjTcYPnw4JpOJsWPHEhYWhpubG2PHjmXIkCF4eHiQkpJCRkYGly9f5vjx42zevJly5crRr18/Dh06hKurq7mvDh06sGLFCsaPH0+DBg0y9QEwbtw4cx93Y2nfcLtAadSoEaNGjWLGjBmsWbMGb29vAK5cucI333zDuXPnGDZs2D2Lj7Fjx7JixQpCQ0Oz7Nu3bx+RkZGsW7cOk8nEsGHDOHDgABUrViQyMpLZs2cTEBDAyJEj2b59O15eXuZzGzdujJubW6aia+DAgfj7+1OtWjUOHz6Mv78/y5cvv+ffVOR+YmMT87Q9Z2eHPG/zSaC8WU65s4zyZjnlzjI5yZslxYmKj0dY8eLFCQ4O5uDBg4SHhzNq1CjGjBlDjx49OHjwIF9++SVGo5ErV65Qq1YtmjVrRkxMDB4eHgAUKVLE3FbDhg2pUKECALVr1yY6OjpLAfBP4eHhLFmyhFu3bvHXX3/x3HPP3bX4uHHjxgP1bWtry8svvwxA/fr12b9/v3mfu7s71tbW1KhRg7i4uBzlLjv79+9n//79dOvWDbhd8Fy4cIGKFStSpUoV6tSpA0C9evWIjo6+Z1tJSUlERERkmoKWmppqcWwiIiIijwMVH484g8FA8+bNad68OTVr1iQkJITOnTvj5+dHSEgIzs7OzJs3j5SUlHu2c2fq1p02jUbjPY9PSUnB39+f9evXU7FiRYKCgu7bx4P0bWtra54GZm1tnemYv5//IEwmE0OGDMm0AB0gKioqS4z3u1aTyUTJkiWzHWEREREReVKp+HiEnTt3Dmtra6pVqwbAiRMnqFSpErdu3SIjIwMHBweSkpLYsWMH7du3p0SJElSoUIGdO3fi7u5OamrqfYuMvytevDhJSUkA5i/fjo6OJCUlsX37dtq3b3/Xcx+0b0t06NAh2zth2djYkJaWhq2tbabtLVu2JDAwkC5dulC8eHFiYmKwscn5/0T+np8SJUpQpUoVtm7dSseOHTGZTPz++++ZFuZnx8/PT0PDFtCQuoiIyKNBxccjLDk5mYCAAK5fv47BYODpp59mypQplCxZkl69etG5c2fKli1rXqMBMGPGDCZNmkRgYCC2tra5epZF9+7d8fPzMy847927d7Z93M2D9J1b8fHxd71Nbp8+fejatSt169blk08+MW9v2bIlZ8+eNY982NvbM3PmTKytc3ZHak9PTz788EO++uor5s2bx8yZM5k8eTKLFi0iPT0dT0/P+xYfIiIiIo8zK1NuHmQg8ogICwvj4sWLDBgwoLBDyTX9gp97GvmwnHJnGeXNcsqdZZQ3yyl3ltGCc5FcuLM4/WFQq1Ytfv/998IOQ0RERKTQ6QnnIvlMhYeIiIjIbSo+RERERESkQKj4EBERERGRAqHiQ0RERERECoSKDxERERERKRC625XIQ8Tf37+wQ5CHiLf36MIOQUREJE9p5ENy7fTp0+zatStf+/juu++4cOFCvvYhIiIiIgVLxYdksWjRIjp16kSXLl3w8vLi8OHD5n3p6elMnz6devXq3bON8PBwhg4det++fH192bZtW5btdevWZfr06WRkZOT+Av7hyJEjvP7667Rv355u3boxceJEbt68SVBQEJ9//rnF7fbv35+2bdtmepK6t7c3Li4uDxyziIiIyONI064kk4iICHbv3s2GDRuws7MjPj6etLQ08/7IyEh8fHwoX758vsZRuXJlBg8ezMWLF3n66actbicuLo6RI0cye/Zsc1Gwbds2kpKS8iROBwcHDh06hKurK9evXyc2NjZP2hURERF5HKn4kExiY2NxdHTEzs4OACcnJ/O++fPnExYWRkpKCi4uLkyZMgUrKysiIyPx8/MjPj4eg8FAYGAgAMnJyfj4+HDq1Cnq1avHrFmzsLKyum8MSUlJeHt7c/36ddLT0xk5ciTu7u5ERUXxr3/9i+eff56IiAjq169Pz549mTdvHvHx8cyaNYuGDRtmamvFihV069Yt02hEhw4dzK/PnDlD//79uXTpEgMHDmTAgAHA7RGMP//8k5SUFAYMGMCrr76abaydOnViy5YtuLq6smPHDjw8PDhz5ox5/5IlS9i6dSupqal4eHjg4+Nz3+sXEREReVyp+JBMXnrpJRYsWED79u1p0aIFnp6eNGvWDIA33niD4cOHYzKZGDt2LGFhYbi5uTF27FiGDBmCh4cHKSkpZGRkcPnyZY4fP87mzZspV64c/fr1M48Q3E+RIkVYsGABJUqUID4+nldffZV27doB8McffxAYGMhHH31Er1692LRpEytXruT777/n008/ZeHChZnaOn36NN26dbtrX+fPn2f58uXcuHGDjh070q9fP2xtbfnoo48oXbo0t27dolevXrzyyis4OjpmOb9FixZ88MEHGI1GtmzZwpQpU1i0aBEA+/btIzIyknXr1mEymRg2bBgHDhygadOmOf1zyBPO2dnhserncaO8WU65s4zyZjnlzjL5kTcVH5JJ8eLFCQ4O5uDBg4SHhzNq1CjGjBlDjx49OHjwIF9++SVGo5ErV65Qq1YtmjVrRkxMDB4eHsDtwuGOhg0bUqFCBQBq165NdHR0jooPk8nE7NmzOXDgANbW1sTExBAXFwdAlSpVqFWrFgA1atSgRYsWWFlZUatWLaKjo3N9vW3atMHOzg4nJyecnJy4evUqFSpU4KuvvuK7774D4PLly0RGRmZbfFhbW9OkSRM2b97MrVu3qFKlinnf/v372b9/v7n4SU5O5sKFCyo+JMdiYxPzvQ9nZ4cC6edxo7xZTrmzjPJmOeXOMjnJmyXFiYoPycJgMNC8eXOaN29OzZo1CQkJoXPnzvj5+RESEoKzszPz5s0jJSXlnu3cmbp1p02j0Zij/jdt2kR8fDzBwcHY2tri5uZm7uvvbVpbW5vfW1lZZdt+jRo1+O2333B3d89RjOnp6YSHh/Pjjz+yevVqihUrRv/+/e95rZ06dWL48OEMHz4803aTycSQIUPo27dvjq5bRERE5HGnu11JJufOnct0i9sTJ05QqVIlbt26RUZGBg4ODiQlJbFjxw4ASpQoQYUKFdi5cycAqamp3Lx584FiSExMpEyZMtja2vLzzz9bNKJxxxtvvEFISEimO3bt2LHDPJJyt/5LlSpFsWLFOHv2LP/73//u2YerqytDhgyhU6dOmba3bNmS9evXmxe3x8TEcPXqVYuvRURERORRp5EPySQ5OZmAgACuX7+OwWDg6aefZsqUKZQsWZJevXrRuXNnypYtS4MGDcznzJgxg0mTJhEYGIitra15wXlO+fn58dFHHwFQsWJFFi1axLBhw+jSpQv169fn2Weftfh6ypYty+zZs/n444+5evUq1tbWNG3alFatWt31nNatW7Nq1So6duzIM888w/PPP3/PPqysrHj77bezbG/ZsiVnz541j3zY29szc+ZMypQpY/H1iIiIiDzKrEx/f0iBiBQ6zUvNPc3ntZxyZxnlzXLKnWWUN8spd5bJrzUfmnYlks9WrlxJSEhIYYchIiIiUug07Uokn/Xr16+wQxARERF5KGjkQ0RERERECoSKDxERERERKRAqPkREREREpECo+BARERERkQKh4kNERERERAqEig8RERERESkQutXuY+j06dNcvHgRNze3wg6l0Fy7do0dO3bQu3fvAuvz0KFDxMTE4OnpaXEb/v7+eRiRPOy8vUcXdggiIiIFSiMfj6BFixbRqVMnunTpgpeXF4cPHzbvS09PZ/r06dSrV++ebYSHhzN06ND79tW/f3+OHj2aZfvvv//O66+/zpAhQ1i8eHGu4k9NTWXIkCH07NmTmTNn5urcewkKCuLzzz8HoFSpUpw7d449e/bkWfv/NHjwYK5fvw7AxYsX2bhxIzExMfz000/51qeIiIjIo0wjH4+YiIgIdu/ezYYNG7CzsyM+Pp60tDTz/sjISHx8fChfvny+xlGrVi1WrFhh0bl2dna5LlgsMWbMGLZs2ZJv7f/3v/81v37qqac0aiEiIiJyHyo+HjGxsbE4OjpiZ2cHgJOTk3nf/PnzCQsLIyUlBRcXF6ZMmYKVlRWRkZH4+fkRHx+PwWAgMDAQgOTkZHx8fDh16hT16tVj1qxZWFlZZdtvRkYGEyZMoHz58tSoUYODBw+av2yvXbuW06dPM2HChEznuLi4MGDAAMLCwihatCgLFy6kbNmy7Nixg8WLF5Oeno6joyMzZ86kbNmyBAUFcenSJaKiorh06RIDBw5kwIABACxYsICNGzfi5ORExYoVqVevHm+//fZd87RmzRpWr15NWloa3333HTNmzKBYsWL4+vpSpEgRTpw4wdWrV/noo48ICQnhf//7H40aNWL69OmZ2tm7dy/r1q1j3rx5wO0Ro6VLl/LZZ5/h5ubGunXrcHJyIjQ0lK+++oq0tDQaNWqEn58fBoOBvXv3MmfOHIxGI46Ojnz55Ze5+XOLiIiIPFZUfDxiXnrpJRYsWED79u1p0aIFnp6eNGvWDIA33niD4cOHYzKZGDt2LGFhYbi5uTF27FiGDBmCh4cHKSkpZGRkcPnyZY4fP87mzZspV64c/fr149ChQ7i6umbp02g0MnbsWJ577jmGDRtGSkoKc+fOJTU1FTs7O9avX8/kyZOznJecnEyjRo0YNWoUM2bMYM2aNXh7e9OsWTM8PDywsrJi1apVLFmyBF9fXwDOnz/P8uXLuXHjBh07dqRfv36cOHGCHTt2sHHjRtLS0ujRo8d9p5V5eHjQp08fAObMmcO6devo378/ANevX2f16tV8//33DBs2jJUrV/Lcc8/Rq1cvTpw4QZ06dcztvPjii0yaNInk5GTs7e3ZsmVLljUdZ8+eZevWraxcuRJbW1smT57Mpk2baN26NR9++CFff/01Tz31FH/99VeO/87yZHB2dijsEICHJ45HjfJmOeXOMsqb5ZQ7y+RH3lR8PGKKFy9OcHAwBw8eJDw8nFGjRjFmzBh69OjBwYMH+fLLLzEajVy5coVatWrRrFkzYmJi8PDwAKBIkSLmtho2bEiFChUAqF27NtHR0dkWH5MmTaJjx44MGzbM3EabNm3YuXMnderUITU1ldq1a2c5z9bWlpdffhmA+vXrs3//fuD26I2vry/Xrl0jJSUFR0dH8zlt2rTBzs4OJycnnJycuHr1Kr/++ivt2rWjSJEiFClSxNzmvZw+fZq5c+eSmJhIUlISLVu2NO97+eWXsbKyolatWpQtW5ZatWoBUKNGDaKjozMVHzY2NrRq1YqwsDDat2/Pnj17GDduXKa+fvrpJ44dO0avXr0AuHXrFmXKlOF///sfrq6uPPXUUwCULl36vnHLkyU2NrGwQ8DZ2eGhiONRo7xZTrmzjPJmOeXOMjnJmyXFiYqPR5DBYKB58+Y0b96cmjVrEhISQufOnfHz8yMkJARnZ2fmzZtHSkrKPdu5M3XrTptGozHb41xcXAgPD+ett94yFy+9evVizpw5nDx5ku7du2d7nq2trXkal7W1tbn9KVOmMHDgQNzd3QkPD2f+/Pl3jSk9PT0HGcnK19eXhQsXUrt2bYKDg/nll1+y9GFlZZWpP2tr62z78/T0ZMWKFZQqVYr69etTokSJTPtNJhPdu3dnzJgxmbbv2rXLothFREREHle629Uj5ty5c1y4cMH8/sSJE1SqVIlbt26RkZGBg4MDSUlJ7NixA4ASJUpQoUIFdu7cCdy+09TNmzdz1WevXr1o06YNI0eONH85r1u3LgkJCYSGhtK5c+dctXf9+nWeeeYZIGdf0Bs3bmxey5KUlMTu3bvve05SUhLOzs6kpaWxadOmXMX3T82aNeP48eOsWbMm29votmjRgu3bt3P16lUA/vrrL6Kjo3n++ec5ePAgFy9eNG8XEREReZJp5OMRk5ycTEBAANevX8dgMPD0008zZcoUSpYsSa9evejcuTNly5alQYMG5nNmzJjBpEmTCAwMxNbW1rzgPDfefPNNEhMTGT9+PLNmzcLa2pqOHTty+PDhTNOmcuLdd9/F19eXZ599lpIlS973+IYNG+Lm5kbXrl0pU6YMNWvWxMHh3sN8I0eOpHfv3jg5OdGoUSOSkpJyFePfGQwG2rZty4YNG/j444+z7K9Rowbvvfceb731FhkZGdja2jJp0iSef/55pkyZwogRI8jIyKBMmTJ88cUXFschIiIi8qizMplMpsIOQh5NPj4+9O7dm1atWuV7X0lJSRQvXpybN2/y+uuv85///Oe+i84fVZqXmnuaz2s55c4yypvllDvLKG+WU+4sk19rPjTtSnLtxo0btG/fnvT09EwLufPTpEmT8PLyonv37rRv3/6hLDwmTpyY7YJ9EREREblNIx8iDxn9OpN7+lXLcsqdZZQ3yyl3llHeLKfcWUYjHyIiIiIi8khT8SEiIiIiIgVCxYeIiIiIiBQIFR8iIiIiIlIgVHyIiIiIiEiBUPEhIiIiIiIFQk84l0dSSEgIS5cuxdvbmw4dOhR2OHnG39+/sEOQB+DtPbqwQxAREXmoqfiQR9LLL7/Ms88+y/79+ws7lLvasmULv//+O6NGjSrsUEREREQeCio+5KGQkJDAoEGDAIiLi8Pa2honJyf++OMPvLy8mDx5MgAXLlxgypQp1KtXDxsbG7y9vXPU/rvvvktUVBTJycnEx8dTpUoVAPz8/Bg7dizr1q3Dycnpga8jJSWF0aNHYzAYeO2113jvvfe4fv06mzZt4vXXX3/g9kVEREQeZSo+5KHg6OhIaGgoAEFBQdjb2/P2229nOe7q1assWLCAY8eO0ahRI2xtbXPU/oIFCwAIDw9n6dKlfPbZZ3kX/N/ExMTg6+tLeno6RYoUwcrKiuvXr7Ny5UoVHyIiIvLEU/EhD7W/FwvJycmsW7eO06dPk56ezvDhw3F3dyc4OJhjx44xadIkAIYOHcpbb71F8+bNc9zP119/TVhYGOnp6cydO5fq1atnKYI6d+7Mp59+yvr16ylVqpR5pGbOnDk4OTkxcOBAduzYwdatW0lNTcXDwwMfHx8++eQT8wjOiy++yPvvv5/neZKHg7OzQ2GHYJFHNe7CprxZTrmzjPJmOeXOMvmRNxUf8sj49NNPeeGFF5g2bRrXr1+nd+/evPjii3nStqOjIxs2bGDFihUsXbqUqVOn3vXYnj17MmLECAYNGkRGRgabN29m7dq17Nu3jwsXLrBu3ToyMjJ45513+OWXXxgzZgynT582j+zI4ys2NrGwQ8g1Z2eHRzLuwqa8WU65s4zyZjnlzjI5yZslxYmKD3lk7Nu3j127drF06VLg9vqKy5cv50nbr7zyCgD169fnu+++u+exVapUoXTp0hw/fpy4uDjq1q2Lo6Mj+/fvJyIiggEDBgBw/fp1oqKiqFSpUp7EKCIiIvKoU/Ehj5R58+bx7LPPZtp27NgxMjIyzO9TUlJy3e6dtSPW1tYYjUYADAbDXdvt3bs3wcHBxMXF0bNnTwBMJhNvvPEG/fr1y9R2VFRUruMREREReRzpIYPyyGjZsiVff/01JpMJgOPHjwNQuXJlTp48SUZGBpcvX+bIkSN50l/lypXNffz222+Zigh3d3d++OEHjh49SsuWLc3xBQcHk5SUBMCff/7J1atXKV68uHmbiIiIyJNMIx/yyPD29uajjz6ia9euZGRkUKVKFT777DOaNGlC5cqV8fT0pHr16tSrVy9P+mvfvj2hoaF06tSJhg0bUq1aNfM+Ozs7mjdvTsmSJTEYDMDt4uPs2bP07dsXAHt7e2bOnEnVqlVp3LgxnTt3plWrVvdccO7n56d5qRbQfF4REZFHg5Xpzs/IIpJjGRkZdO/encDAwExFSV7Ql+jcU/FhOeXOMsqb5ZQ7yyhvllPuLJNfC8417Uokl86cOYOHhwctWrTI88JDRERE5HGmaVciuVSjRg2+//77wg5DRERE5JGjkQ8RERERESkQKj5ERERERKRAqPgQEREREZECoeJDREREREQKhIoPEREREREpELrblRSar7/+mtWrVzNu3Dhat25d2OHkiY8++ogDBw4we/ZsnnnmmVyf7+/vnw9RSX7y9h5d2CGIiIg8MjTyIWYxMTGEhIQUWH9du3Zl7NixXLx4scD6zG/vvvsunTp14urVq4UdioiIiMhDRyMfT5iEhAQGDRoEQFxcHNbW1jg5OQFQpUoVRowYkSf99O/fn/Hjx9OgQYMs+86ePcvUqVNp3rw5N27cYNSoURb1ERQUhL29PW+//Xam7YGBgTRt2pQXX3wx1+feTe/evYmNjeXWrVvMnj2byMhIihUrRrdu3QD49ttvWb16NX379iU1NRVXV1eLrklERETkcabi4wnj6OhIaGgokPkL+JUrV/j999+pXbt2vseQkJDAp59+yq+//kqzZs2wts7bAbiRI0fmaXsAa9euJTg4mGPHjvHiiy9mKWxKly7NV199xf79++nUqVOe9y8iIiLyOFDxIaxZs4bVq1eTmprKmjVrmDFjBsWKFSMuLg4/Pz/ztKjJkyfTuHHjTOe6uLjQu3dv9u/fT9myZZkzZ455JGXbtm34+/uTmJjI1KlTcXV1JSoqitmzZ3Pz5k0APvzwQxo3bkx4eDhBQUE4ODhw6tQpOnbsSM2aNVm+fDkpKSksWLCAqlWr3vMaduzYwfz585k8eTJt27alQ4cOuLm50a1bN8LCwkhPT2fu3LlUr14dgDNnztC/f38uXbrEwIEDGTBgQJZ2169fz+LFi3FwcKB27drY2dkBmQu3P/74gy+++ILZs2dTtGhRKlSoQPXq1fH19aVEiRIcO3aM2NhYxo0bR4cOHR78DyYPFWdnh8IO4YE9DtdQGJQ3yyl3llHeLKfcWSY/8qbiQ/Dw8KBPnz4AfPLJJ6xbt47+/fsTEBBA06ZNWbBgAUajkeTk5CznJicnU79+fSZMmMD8+fOZP38+kyZNAsBoNLJu3Tr27NnD/PnzWbZsGWXKlOGLL76gSJEiXLhwgdGjRxMcHAzAyZMn2bJlC6VLl6Zdu3b07t2bdevW8eWXX/LVV18xceLEbOP/+uuv2b9/PwsXLjQXB3/n6OjIhg0bWLFiBUuXLmXq1KkAnD9/nuXLl3Pjxg06duxIv379sLW1NZ935coVgoKCCA4OpkSJEgwYMIC6detmaf/DDz/E39+fatWqcfjwYfz9/Vm+fLm5jW+++YZz584xbNgwFR+PodjYxMIO4YE4Ozs88tdQGJQ3yyl3llHeLKfcWSYnebOkOFHxIZw9e5aFCxdy69Ytrl27RpMmTQD4+eefmTFjBgAGgwEHh6wfMGtrazw9PQHw8vJi+PDh5n0eHh4A1KtXj+joaADS09OZMmUKJ0+exNramgsXLpiPb9CgAeXKlQOgatWqvPTSSwDUrFmT8PDwbGMPCQmhYsWKLFiwIFPh8HevvPIKAPXr1+e7774zb2/Tpg12dnY4OTnh5OTE1atXqVChgnn/kSNHaNasmXkkx9PTM1O8AElJSURERGSa6pWammp+7e7ujrW1NTVq1CAuLi7b+ERERESeFCo+hPfff5/FixdTvXp11q9fz4EDByxuy8rKyvz6ziiEtbU1RqMRgGXLllG2bFlCQ0PJyMigYcOGWY6/c0525/9TzZo1OXnyJH/++SdPPfVUtsfcKUr+2c7f+zMYDKSnp+fqWgFMJhMlS5Y0r6P5p+xGYkRERESeVLrVrnDjxg1Kly5NWloamzZtMm9v0aIF33zzDXB7ClViYtaht4yMDLZv3w7Apk2bzKMmd5OYmIizszPW1taEhobetajIqbp16+Lv74+3tzcxMTEP1NY/NWzYkAMHDpCQkEBaWhrbtm3LckyJEiWoUqUKW7duBW4XIydPnszTOEREREQeFxr5EHx8fOjduzdOTk40atSIpKQkACZOnMiHH37I+vXrsba2ZvLkybi4uGQ6197eniNHjrBo0SKcnJyYO3fuPft67bXXGDFiBCEhIbRq1Qp7e/sHjt/V1ZXx48czdOhQli5d+sDt3VGuXDmGDx9O3759cXBwoE6dOtkeN3PmTCZPnsyiRYtIT0/H09PT4ruG+fn5aV6qBTSfV0RE5NFgZTKZTIUdhDy6XFxciIiIKOwwHiv6Ep17Kj4sp9xZRnmznHJnGeXNcsqdZfJrwbmmXYmIiIiISIFQ8SEPRKMeIiIiIpJTKj5ERERERKRAqPgQEREREZECoeJDREREREQKhIoPEREREREpECo+RERERESkQOghgyIPEX9//8IOQXLJ23t0YYcgIiLyyNDIhwBw+vRpdu3aVdhh5KnIyEi8vb1JTU0t7FBEREREBBUfT4xFixbRqVMnunTpgpeXF4cPHzbvS09PZ/r06dSrV++ebYSHhzN06ND79uXr68u2bdsybXNxcbEs8P9v0aJFeHl54eXlRZ06dcyvly9fzsSJEzlz5oz52ICAAP71r39x/vx5Pv74Y+zs7B6o7ztOnDhBrVq12Lt3b46O79+/P0ePHs2TvkVEREQeB5p29QSIiIhg9+7dbNiwATs7O+Lj40lLSzPvj4yMxMfHh/LlyxdilPc2bNgwhg0bBtwuZEJDQ7M97ubNm3Ts2JFatWpx9uxZHBwc8iyGb7/9liZNmrB582Zat26dZ+2KiIiIPClUfDwBYmNjcXR0NI8AODk5mffNnz+fsLAwUlJScHFxYcqUKVhZWREZGYmfnx/x8fEYDAYCAwMBSE5OxsfHh1OnTlGvXj1mzZqFlZVVjmMxmUzMmDGDH374ASsrK4YNG4anpycAixcvZtOmTVhZWdG6dWvGjh2bozb79+/P+PHjadCgAYcOHSIoKIiUlBSqVq3KtGnTKF68OG5ubnTr1o2wsDDS09OZO3cu1atXJz4+njFjxnDlyhWef/55fvzxR9avX58pR3fi3rZtG1988QWvvfYaKSkpFClShKioKAYPHkyTJk2IiIigfPnyLFy4kKJFiwKwbds2/P39SUxMZOrUqbi6uuY4V/JocHbOuwK3sDwO11AYlDfLKXeWUd4sp9xZJj/ypuLjCfDSSy+xYMEC2rdvT4sWLfD09KRZs2YAvPHGGwwfPhyTycTYsWMJCwvDzc2NsWPHMmTIEDw8PEhJSSEjI4PLly9z/PhxNm/eTLly5ejXrx+HDh3K9gv1jBkzWLRoUZbtO3bs4OTJk4SGhpKQkECvXr1wdXXlxIkT7Nq1izVr1lCsWDH++uuvXF9nfHw8CxYs4IsvvsDe3p7PPvuML774guHDhwPg6OjIhg0bWLFiBUuXLmXq1KnMnz+fF154gaFDh7J3717WrVuXbdu//vorVapUoWrVqjRv3pzdu3fTvn174PbI0ezZswkICGDkyJFs374dLy8vAIxGI+vWrWPPnj3Mnz+fZcuW5fq65OEWG5tY2CE8EGdnh0f+GgqD8mY55c4yypvllDvL5CRvlhQnKj6eAMWLFyc4OJiDBw8SHh7OqFGjGDNmDD169ODgwYN8+eWXGI1Grly5Qq1atWjWrBkxMTF4eHgAUKRIEXNbDRs2pEKFCgDUrl2b6OjobIuP8ePH06FDB/P7O2s+Dh06RKdOnTAYDJQtW5amTZty9OhRDhw4QI8ePShWrBgApUuXzvV1Hj58mKioKPO6lJSUFGrXrm3e/8orrwBQv359vvvuO3M88+fPB6B169aUKlUq27Y3b95Mp06dAPD09CQ0NNRcfFSpUoU6deoAUK9ePaKjo83n3cnhP7eLiIiIPIlUfDwhDAYDzZs3p3nz5tSsWZOQkBA6d+6Mn58fISEhODs7M2/ePFJSUu7Zzt8XbxsMBoxGY36HnmMmkwlXV1fmzJmT7X5bW1sArK2tcxW30Whkx44dfP/993z66aeYTCb++usvbty4AWTNyd9zeGdfbvsUEREReRzpbldPgHPnznHhwgXz+xMnTlCpUiVu3bpFRkYGDg4OJCUlsWPHDgBKlChBhQoV2LlzJwCpqancvHkzT2JxdXVl69atGI1G4uPjOXjwIA0bNuTFF18kODjY3I8l066ef/55fv31VyIjI4Hb61POnTt3z3MaN27M1q1bAdi3bx/Xrl3LcsxPP/1ErVq12LNnD7t27SIsLIxXXnnFnB8RERERyRmNfDwBkpOTCQgI4Pr16xgMBp5++mmmTJlCyZIl6dWrF507d6Zs2bI0aNDAfM6MGTOYNGkSgYGB2NramhecPygPDw8iIiLw8vLCysqKcePG4ezsjLOzMydPnqRnz57Y2trSpk0bRo/O3cPbnJycmD59OqNHjzY/2+O9997j2Wefves5w4cPZ/To0WzcuJHnn38eZ2dnSpQokemYzZs34+7unmnbK6+8wsqVK/N8Abmfn5/mpVpA83lFREQeDVYmk8lU2EGIFJbU1FSsra2xsbEhIiKCyZMn3/U2vgVFX6JzT8WH5ZQ7yyhvllPuLKO8WU65s4wWnMtjZfHixVSvXp127doVahyXLl3ivffeIyMjA1tbW/7zn/8UajwiIiIijzMVH1IohgwZUtghAFCtWjVCQkIKOwwRERGRJ4IWnIuIiIiISIFQ8SEiIiIiIgVCxYeIiIiIiBQIFR8iIiIiIlIgVHyIiIiIiEiB0N2uRB4i/v7+hR2C/I23d+4edCkiIiL3ppEPEREREREpECo+JM+cPn2aXbt2FXYYeeK///0va9asKewwRERERB4rKj4kxxYtWkSnTp3o0qULXl5eHD582LwvPT2d6dOnU69evXu2ER4eztChQ+/bV//+/Tl69GiW7YMHD+b69esWnft3UVFRbNq0KdO2+Ph4hgwZwr///W9cXFzo06dPlnM6d+5839hFREREJHta8yE5EhERwe7du9mwYQN2dnbEx8eTlpZm3h8ZGYmPjw/ly5fP1zj++9//5kk70dHRfPvtt3Tp0sW8LSYmhunTp3Pp0iWqVKmSJ/2IiIiIyP9R8SE5Ehsbi6OjI3Z2dgA4OTmZ982fP5+wsDBSUlJwcXFhypQpWFlZERkZiZ+fH/Hx8RgMBgIDAwFITk7Gx8eHU6dOUa9ePWbNmoWVlVW2/WZkZDBhwgTKly/PqFGjcHNzY926dSQnJzN48GCaNGlCREQE5cuXZ+HChRQtWhSAbdu24e/vT2JiIlOnTsXV1TVTu5988glnz57Fy8uL7t27079/fzZu3Mgvv/xCamoqr7/+On379s0Sj9Fo5IMPPsjS54kTJ/Dz8+PmzZtUrVqVjz76iFKlSmWbg6pVq+bJ30Tyn7OzQ2GHUCCelOvMa8qb5ZQ7yyhvllPuLJMfeVPxITny0ksvsWDBAtq3b0+LFi3w9PSkWbNmALzxxhsMHz4ck8nE2LFjCQsLw83NjbFjxzJkyBA8PDxISUkhIyODy5cvc/z4cTZv3ky5cuXo168fhw4dylIcwO0v+mPHjuW5555j2LBhWfZHRkYye/ZsAgICGDlyJNu3b8fLy8t87rp169izZw/z589n2bJlmc4dM2YMS5cu5bPPPgNg9erVlChRgvXr15OSkkLfvn156aWXeOqpp3LU5/jx4/nwww9p1qwZgYGBzJ8/n4kTJ2abA3l0xMYmFnYI+c7Z2eGJuM68prxZTrmzjPJmOeXOMjnJmyXFiYoPyZHixYsTHBzMwYMHCQ8PZ9SoUYwZM4YePXpw8OBBvvzyS4xGI1euXKFWrVo0a9aMmJgYPDw8AChSpIi5rYYNG1KhQgUAateuTXR0dLbFx6RJk+jYsWO2hQdAlSpVqFOnDgD16tUjOjravO9Ov//cfjf79+8nKiqKn3/+GYC0tDQuXryYpfjIrs/ExEQSExPNxVj37t0ZOXIkN27cuGsORERERJ5EKj4kxwwGA82bN6d58+bUrFmTkJAQOnfujJ+fHyEhITg7OzNv3jxSUlLu2c6dqVt32jQajdke5+LiQnh4OG+99Va2X9z/2c7f+72zz9ra+q7t/53JZOK9996jdevWuYr9ftcqIiIiIv9HxYfkyLlz57C2tqZatWoAnDhxgkqVKnHr1i0yMjJwcHAgKSmJHTt20L59e0qUKEGFChXYuXMn7u7upKam5qgI+LtevXpx8OBBRo4cyfz587GxybuPa/HixUlKSjK/b9myJatWraJFixbY2tpy7tw5KlSogL29/X3bcnBwoGTJkhw8eBBXV1dCQ0Np2rTpXXNQrFixu7bl5+enoWELaEhdRETk0aDiQ3IkOTmZgIAArl+/jsFg4Omnn2bKlCmULFmSXr160blzZ8qWLUuDBg3M58yYMYNJkyYRGBiIra2tecF5brz55pskJiYyfvx4Zs2alWfXU6tWLaytrenatSs9evRgwIABREdH06NHD0wmE46OjixcuDDH7X388cfmBedPPfUU06ZNA7LPwT+ncomIiIg8KaxMJpOpsIMQkf+jX/BzTyMfllPuLKO8WU65s4zyZjnlzjL5teBcDxkUySPXr19n8ODBhR2GiIiIyENLxYdIHilZsmSePQRRRERE5HGk4kNERERERAqEig8RERERESkQKj5ERERERKRAqPgQEREREZECoed8iDxE/P39CzsE+f+8vUcXdggiIiKPHY18yGNp1KhR9OnTh4SEhMIORURERET+PxUfUmh2797Nvn378qXtyZMn06hRI27cuJEv7efWpk2buHTpUmGHISIiIlKoNO1K7ikhIYFBgwYBEBcXh7W1NU5OTgCsXbsWOzs7i9o9cuQIERERGI1Gypcvz3PPPZfjc319fWnbti0dOnTIsm/x4sX8+OOPvPbaazz77LM89dRT920vKiqKd955h2+//TZX15CTeOB2npKSkqhUqZJF7YuIiIg8LlR8yD05OjoSGhoKQFBQEPb29rz99tvm/enp6djY5P5j1LBhQxo2bJhncQJkZGTQoEED3nzzTX799VdeeeWVPG3fUr179y7sEEREREQeCio+JNd8fX2xs7PjxIkTNG7cmBIlSmQqSjp37synn37K+vXrKVWqlHnkZM6cOTg5OTFw4ECWLFnC1q1bSU1NxcPDAx8fH6Kiohg8eDBNmjQhIiKC8uXLs3DhQooWLXrXWObOncuff/7J1KlTOXHiBAsWLCA5ORlHR0eeeeYZypUrl+n4uLg4/Pz8uHjxInB7ela5cuUwGo188MEHWfo9ceIEfn5+3Lx5k6pVq/LRRx9RqlSpLHH8+OOPLF68mKSkJHx9fXn55ZcxGo3MmjWLX375hdTUVF5//XX69u2bR38FyW/Ozg6FHUKBeZKuNS8pb5ZT7iyjvFlOubNMfuRNxYdYJCYmhlWrVmEwGAgKCsr2mJ49ezJixAgGDRpERkYGmzdvZu3atezbt4/IyEjWrVuHyWRi2LBhHDhwgIoVKxIZGcns2bMJCAhg5MiRbN++HS8vr2zb//jjj0lKSmLatGmkp6cTEBDAwoULcXJyYsuWLcyZM4dp06ZlOicgIICmTZuyYMECjEYjycnJXLt27a79jh8/ng8//JBmzZoRGBjI/PnzmThxYpZYoqOjWbduHX/88QcDBgzgxRdfJCQkBAcHB9avX09qaip9+/blpZdeytFUMCl8sbGJhR1CgXB2dnhirjUvKW+WU+4so7xZTrmzTE7yZklxouJDLNKhQwcMBsM9j6lSpQqlS5fm+PHjxMXFUbduXRwdHdm/fz/79++nW7duACQnJ3PhwgUqVqxIlSpVqFOnDgD16tUjOjo627YXLlxIo0aN+M9//gPA+fPnOXXqFG+++SZwewqWs7NzlvN+/vlnZsyYAYDBYMDBwYFr165l229iYiKJiYk0a9YMgO7duzNy5Mhs4+nYsSPW1tZUq1aNp556inPnzrF//35+//13tm/fDkBiYiKRkZEqPkREROSJpeJDLFKsWDHza4PBQEZGhvl9SkqK+XXv3r0JDg4mLi6Onj17AmAymRgyZEiWKUhRUVGZFrAbDIZMbf1dgwYN+O233/jrr78oXbo0JpOJ5557jtWrV1t0PTnt926srKyyvDeZTHzwwQe0atXKophEREREHjcqPuSBVa5cmd27dwPw22+/ERUVZd7n7u5OYGAg6enpfPLJJwC0bNmSwMBAunTpQvHixYmJicn1ovVWrVrRsmVLhg4dyueff84zzzxDfHw8ERERuLi4kJaWxoULF7LcRatFixZ88803DBo0yDzt6m4cHBwoWbIkBw8exNXVldDQUJo2bZrtsdu2baN79+5ERUVx8eJFnnnmGVq2bMnKlSt54YUXsLW15fz585QvXx57e/u79unn56ehYQtoSF1EROTRoOJDHlj79u0JDQ2lU6dONGzYkGrVqpn32dnZ0bx5c0qWLGmeptWyZUvOnj1rHvmwt7dn5syZWFvn7rEzHTt2JCkpiWHDhvHf//6XefPmERAQQGJiIkajkYEDB2YpPiZOnMiHH37I+vXrsba2ZvLkydlOz7rj448/Ni84f+qpp7KsIbmjYsWK9OrVi6SkJPz9/SlSpAi9e/cmOjqaHj16YDKZcHR0ZOHChbm6RhEREZHHiZXJZDIVdhDy+MrIyKB79+4EBgZmKkrk7vQLfu5p5MNyyp1llDfLKXeWUd4sp9xZJr8WnOsJ55Jvzpw5g4eHBy1atMi28PDy8jLfhldEREREHn+adiX5pkaNGnz//fd33X/n4YUiIiIi8mTQyIeIiIiIiBQIFR8iIiIiIlIgVHyIiIiIiEiBUPEhIiIiIiIFQgvORR4i/v7+hR2CAN7eows7BBERkceSRj5E8tDp06fZtWtXYYchIiIi8lBS8SH5zsXFJdP7NWvW0Lt3b3x8fO55K97g4GCmTJmSp7EkJSXl6Lh/xgwQHh7O0KFD73pOeno606dPp169ehbHJyIiIvI407QrKXB9+vShT58+hdL3J598wqRJk/Kl7cjISHx8fChfvny+tC8iIiLyqNPIhxSKoKAgPv/8cwD69+/PzJkz6dWrF+3bt+fgwYPm465cucLbb7/NK6+8wowZM7K0s3fvXnx8fMzv/z468ffRi61bt1KrVi3s7OyIi4vj3XffpWvXrnTt2pVff/31rnHGx8fz6quvsnv3bgCSk5Px8fGhQ4cOjBkzBpPJBMD8+fMZP348EydO5MMPPzRvj4yMZNCgQXTt2pXu3bvzxx9/WJgxERERkUefRj7koWA0Glm3bh179uxh/vz5LFu2DIATJ04QEhKCnZ0dHTp0oH///lSsWNF83osvvsikSZNITk7G3t6eLVu24OnpmaV9Kysrunfvjq+vL++99x5NmzZlwYIFGI1GkpOTs40pLi6OYcOG8d577/HSSy8RHh7O8ePH2bx5M+XKlaNfv34cOnQIV1dX3njjDYYPH47JZGLs2LGEhYXh5ubG2LFjGTJkCB4eHqSkpJCRkZEv+ZO85ezsUNghFKgn7XrzivJmOeXOMsqb5ZQ7y+RH3lR8yEPBw8MDgHr16hEdHW3e3qJFCxwcbn/wq1evTnR0dKbiw8bGhlatWhEWFkb79u3Zs2cP48aNu2dfP//8s3kUxWAwmNv/u7S0NAYNGsSkSZNo1qyZeXvDhg2pUKECALVr1yY6OhpXV1cOHjzIl19+idFo5MqVK9SqVYtmzZoRExNjvrYiRYpYkhopBLGxiYUdQoFxdnZ4oq43ryhvllPuLKO8WU65s0xO8mZJcaLiQx4KdnZ2AFhbW2M0GrNsh9uFwt/33eHp6cmKFSsoVaoU9evXp0SJElmOSUlJyVU8NjY21KtXj3379mUqPrKLJzU1FT8/P0JCQnB2dmbevHm57k9ERETkSaA1H/LIa9asGcePH2fNmjWZplyVLVuWs2fPkpGRwc6dO83bW7RowTfffAPcnu6VmJi1qreysuKjjz7i3LlzLF68+J7937p1i4yMDBwcHEhKSmLHjh0AlChRggoVKpj7Tk1N5ebNmw98vSIiIiKPqhyNfKSkpGjKiFjs5s2btG7d2vz+zTffzNP2DQYDbdu2ZcOGDXz88cfm7WPGjGHo0KE4OTnRsGFDbty4AWBeFL5+/Xqsra2ZPHlytrfWNRgMzJ49m2HDhlG8eHFq1KiRbf8lS5akV69edO7cmbJly9KgQQPzvhkzZjBp0iQCAwOxtbUlMDCQp5566q7X4ufnp6FhC2hIXURE5NFgZbpzW557eOmll+jSpQuvvfYaVatWLYi4RJ5Y+hKdeyo+LKfcWUZ5s5xyZxnlzXLKnWXya81HjqZdbdy4kZIlSzJw4ED+9a9/ERYWluuORArD0aNHCQgIKOwwRERERIQcjnzcYTQa+f777/noo4+wtrbmjTfe4PXXX9eULJE8pF9nck+/allOubOM8mY55c4yypvllDvLFOrIB9yet7927Vrmz59P1apVGTVqFOfOnWPw4MG57lRERERERJ48OVpwPmXKFHbs2IGbmxuzZs2iZs2aAHTp0oUOHTrka4AiIiIiIvJ4yFHxUblyZTZv3kypUqWy7Fu+fHmeByUiIiIiIo+f+067MhqNfPvtt9kWHgDlypXL86BEREREROTxc9/iw2AwYG9vryc2i4iIiIjIA8nRtKtnnnmG119/nfbt22Nvb2/e/vrrr+dbYCJPIn9//8IO4Ynm7T26sEMQERF5rOWo+DAajTz33HOcO3cuv+MREREREZHHVI6Kj2nTpuV3HCKFKiAggNatW9O6devCDkVERETksZWj53yYTCZWrVqFj48PPj4+rFmzhlw8m1AeMf379+eHH37ItG3ZsmX4+fkB8MUXX9CzZ08GDhxIXFxcrtr29fVl27ZteRYrwM6dOzlz5oz5ff/+/Tl69GiW4/75tPMLFy7w1ltvMX36dLp06ZInhUdQUBCff/55tvv69u37wO2LiIiIPMpyNPIxY8YMTpw4QY8ePQAICQnhwoULjB8/Pl+Dk8LRuXNntmzZQqtWrczbtmzZwrhx4wB48803efPNNwsrvCx27txJ27ZtqVGjxj2Pa9CgAQ0aNDC/v3r1KgsWLODYsWPUqVMnv8Nk1apV+d6HiIiIyMMsR8XHvn372LBhAzY2tw/v2LEjPXr0UPHxmGrfvj1z584lNTUVOzs7oqKiuHLlCq6urly7do3hw4dz48YN0tPTGTlyJO7u7kRFRTF48GCaNGlCREQE5cuXZ+HChRQtWjRL+wcPHmTZsmXExsYybtw4OnTogMlkYsaMGfzwww9YWVkxbNgwPD09AVi8eDGbNm3CysqK1q1bM3bsWHNbv/76K7t27eKXX35h0aJFBAUFAbBt2zb8/f1JTExk6tSpuLq6Eh4eztKlS/nss89ITk5m3bp1nDp1ivT0dEaMGIG7uzvBwcEcO3aMSZMmATB06FDeeustmjdvnuka3Nzc6NatG2FhYaSnpzN37lyqV68OwJkzZ+jfvz+XLl1i4MCBDBgwAAAXFxciIiLy/g8mecbZ2aGwQygUT+p1PyjlzXLKnWWUN8spd5bJj7zlqPgAsLKyyva1PH5Kly5Nw4YN2bt3L+7u7mzZsoWOHTtiZWVFsWLFWLRoESVKlODq1au8+uqrtGvXDoDIyEhmz55NQEAAI0eOZPv27Xh5eWVp/8qVK3zzzTecO3eOYcOG0aFDB3bs2MHJkycJDQ0lISGBXr164erqyokTJ9i1axdr1qyhWLFi/PXXX5naaty4MW5ubrRt25YOHTqYtxuNRtatW8eePXuYP38+y5Yty3Tep59+SvPmzZk2bRrXrl2jd+/evPjii7nKk6OjIxs2bGDFihUsXbqUqVOnAnD+/HmWL1/OjRs36NixI/369cPW1jZXbUvhiI1NLOwQCpyzs8MTed0PSnmznHJnGeXNcsqdZXKSN0uKkxwVHy1btmTw4MF0794duD3tqmXLlrnuTB4dnTp1YsuWLbi7u7N582bzF2tra2uCgoI4fPgwNjY2xMXFmdd9VKlSxTx9qV69ekRHR2fbtru7O9bW1tSoUcN87qFDh+jUqRMGg4GyZcvStGlTjh49yoEDB+jRowfFihUDbhdGOeHh4XHPOPbt28cvv/zC+vXrzdd1+fLlHGbntldeeQWA+vXr891335m3t2nTBjs7O5ycnHBycuLq1atUqFAhV22LiIiIPI5yVHyMGzeOVatWmb9gubu78+qrr+ZrYFK42rVrx7Rp0/jtt9+4desW9evXB2DTpk1cvnyZr7/+GhsbG9zc3MwPoLSzszOfbzAY7vpgyr8fl1/u9GFtbY3RaMz2mKlTp5qnSt1x7NgxMjIyzO/v9XDNO6MZ/+zjn3lIT0/P/QWIiIiIPIZyVHxYW1vz2muv8dprr+V3PPKQKF68OM2bN2fChAl06tTJvP3atWtUrVoVGxsbTp48yaVLl/KkP1dXV1avXk337t25du0aBw8eZPz48dja2rJw4UK6dOlinnb1z9GP4sWLk5SUlKv+WrZsyYoVK/jwww+xsrLi2LFj1K9fn8qVK7Ny5UoyMjKIiYnhyJEjeXJ9OeXn56ehYQtoSF1EROTRkKPiw8fHJ8s6DwcHB55//nl69OiBtXWO7tgrj5jOnTvz7rvvMnv2bPO2rl27MmLECEaPHo2joyNVq1bNk748PDyIiIjAy8sLKysrxo0bh7OzM87Ozpw8eZKePXtia2tLmzZtGD0681OoPT09+fDDD/nqq6+YN29ejvrz9vbmo48+omvXrmRkZFClShU+++wzmjRpQuXKlfH09KR69erUq1cvT65PRERERMDKlIMHdvznP//h2LFj5l/At2zZQo0aNbh8+TLPPPMMH3zwQb4HKvKk0C/4uaeRD8spd5ZR3iyn3FlGebOccmeZQl1wfvLkSb766ivzXPZXX32VQYMG8eWXX9KtW7dcdypyN4sXL6Z69ermO2iJiIiIyOMjR8VHXFxcpluF2tjYkJCQgJ2dXYEsHpYnx5AhQwo7BBERERHJJzkqPpo1a8aQIUPMz2zYtGkTrq6uJCUlqfgQEREREZEcyVHxMWnSJFatWsX27duB23cK6tu3L7a2tqxZsyZfAxQRERERkcdDjooPW1tb+vfvT//+/fM7HhEREREReUzl6B6558+fp1+/fri5uQHw22+/ERQUlK+BiYiIiIjI4yVHxYe/vz/Dhg3DweH27bTq1KnDtm3b8jUwERERERF5vORo2lViYiKtW7c2P2zO2to6092vRO5m9+7d2NjY0LJly8IO5ZHg7+9f2CE8Uby9R9//IBEREckzOSo+DAYDaWlp5qecx8TE6Knmj5GEhAQGDRoE3L6tsrW1NU5OTgCsXbvW4juaHTlyhIiICIxGI+XLl+e5557L8bk7d+6kWrVq1KhRw6K+/ykqKop33nmHb7/99p7HBQUFsWbNGvP1A3z11Vfs3LmTY8eOMWnSpDyJR0RERORJlKPi47XXXmP48OEkJCQQFBRESEgIo0aNyu/YpIA4OjoSGhoK3P7ybW9vz9tvv23en56ejo1Njj4qmTRs2JCGDRtaFNPOnTtp27ZttsWHpfHk1KBBgzJdv4iIiIjkjRx9g+vWrRtVqlQhLCyMmzdv8vHHH+Pq6prfsUkh8vX1xc7OjhMnTtC4cWNKlCiRqSjp3Lkzn376KevXr6dUqVLmkZM5c+bg5OTEwIEDWbJkCVu3biU1NRUPDw98fHyIiopi8ODBNGnShIiICMqXL8/ChQspWrSoue9ff/2VXbt28csvv7Bo0SKCgoKYOHEitWvX5tChQ3Tu3Jlq1aqxaNEi0tLSKF26NLNmzaJs2bIEBQVx6dIloqKiuHTpEgMHDmTAgAEAGI1GPvjgg7v2ez9Xrlzh7bff5uLFi7i7uzN+/HgAvv32Wz777DNMJhNt2rRh3LhxALi4uDBgwADCwsIoWrQoCxcupGzZsnnx5xERERF5JOWo+AgNDcXLyytTwXFnmzy+YmJiWLVqFQaD4a53N+vZsycjRoxg0KBBZGRksHnzZtauXcu+ffuIjIxk3bp1mEwmhg0bxoEDB6hYsSKRkZHMnj2bgIAARo4cyfbt2zN9lho3boybmxtt27alQ4cO5u1paWkEBwcDcO3aNdasWYOVlRVr165lyZIl+Pr6ArfvzrZ8+XJu3LhBx44d6devH8B9+71j2bJlbNy4EYCSJUvy1VdfAXDixAlCQkKws7OjQ4cO9O/fH2tra2bNmkVwcDAlS5bkrbfeYufOnbi7u5OcnEyjRo0YNWoUM2bMYM2aNXh7e+fBX0byirOzQ2GH8FBQHiyjvFlOubOM8mY55c4y+ZG3HBUfy5Yty/IlLbtt8njp0KEDBoPhnsdUqVKF0qVLc/z4ceLi4qhbty6Ojo7s37+f/fv3061bNwCSk5O5cOECFStWpEqVKtSpUweAevXqER0dnaN4PD09za///PNPRo0aRWxsLKmpqVSpUsW8r02bNtjZ2eHk5ISTkxNXr141x5qTfu827apFixbmO75Vr16d6Oho/vrrL5o1a2ZeI9KlSxcOHDiAu7s7tra2vPzyywDUr1+f/fv35+g6peDExiYWdgiFztnZQXmwgPJmOeXOMsqb5ZQ7y+Qkb5YUJ/csPo4ePcqRI0dISEhgxYoV5u03btwgLS0t153Jo6VYsWLm1waDgYyMDPP7lJQU8+vevXsTHBxMXFwcPXv2BMBkMjFkyBD69u2bqc2oqKhMC9gNBkOmtnIaT0BAAIMGDaJdu3aEh4czf/58875/tp+enp7t9pz2e7d2jUbjPY+3tbU136TB2tr6vseLiIiIPO7uecuqmJgYjh07xs2bNzl27Jj5n9jYWKZNm1ZQMcpDoHLlyhw/fhy4/ZDJqKgo8z53d3d++OEHjh49ar6lbsuWLVm/fj1JSUnA7c/SnRGInChevLj53OwkJiZSvnx5AEJCQnJ7OXmmYcOGHDhwgPj4eIxGI5s3b6Zp06aFFo+IiIjIw+yeIx/u7u64u7uzb98+PafhCde+fXtCQ0Pp1KkTDRs2pFq1auZ9dnZ2NG/enJIlS5qnabVs2ZKzZ8+aRz7s7e2ZOXNmjm/R7OnpyYcffshXX33FvHnzsuwfPnw4I0eOpFSpUjRv3jxTMfSg/r7mA2DBggV3PbZcuXKMGTOGgQMHmhecu7u751ksIiIiIo8TK5PJZMrJgefOnePkyZOkpqaat92Zzy9PtoyMDLp3705gYGCmokQso3mpuaf5vJZT7iyjvFlOubOM8mY55c4yhbLm447ly5ezevVqYmNjadCgAQcPHqRp06YqPoQzZ84wdOhQPDw8si08vLy8cHR0ZNmyZQUem4iIiIg8XHJUfKxZs4a1a9fSr18/Pv/8c06dOnXPqSjy5KhRowbff//9XfffeXihiIiIiEiOJuDb2dlhb29PRkYGJpOJmjVrcuHChXwOTUREREREHic5GvkoVqwYaWlp1K5dm5kzZ1KxYsVMt10VERERERG5n3uOfBiNRm7evImfnx9paWn4+vpy7do1Dhw4oFvtioiIiIhIrtyz+Jg1axbffvstNWvWxN7enjJlyjB16lRatWrFli1bCipGERERERF5DNyz+AgPDzc/sfrvevbsyd69e/MtKBERERERefzcd9pVdg+Fs7a2xsrKKt+CEhERERGRx889F5zfunWLmzdvUqxYsUzbk5KSMj1sUETyhr+/f2GH8Fjx9h5d2CGIiIjI39xz5MPT05P333+fGzdumLclJibywQcf0KFDh3wPTiQ//PnnnwwbNoxXXnkFd3d3AgICSE1N5cSJE+zZs8d8XFBQEJ9//nkhRioiIiLyeLln8fHuu+9iZ2dHq1at6N69O927d6d169ZYW1szYsSIgopRJM+YTCaGDx+Ou7s7O3bsYPv27SQnJzNnzpwsxceDMhqNedaWiIiIyOPgntOubGxsmDVrFpGRkRw/fhyAunXr8vTTTxdIcCJ57eeff6ZIkSLmGykYDAYmTJjAyy+/jI2NDSaTiUOHDjF06FAAzpw5Q//+/bl06RIDBw5kwIABwO0nt3/11VekpaXRqFEj/Pz8MBgMuLi48Oqrr/Ljjz8yadIkdu/eza5duzAYDLRs2ZL333+/0K5dREREpLDl6CGDTz/9tAoOeSycPn2aevXqZdpWokQJKleuTI8ePbhw4QKTJk0Cbk+7On/+PMuXL+fGjRt07NiRfv368ccff7B161ZWrlyJra0tkydPZtOmTXTr1o3k5GQaNmyIr68vCQkJTJw4kW3btmFlZcX169cL45KfaM7ODoUdwiNBebKM8mY55c4yypvllDvL5EfeclR8iDyp2rRpg52dHU5OTjg5OXH16lV++uknjh07Rq9evYDbN2YoU6YMcHskpX379gA4ODhQpEgR88hK27ZtC+synlixsYmFHcJDz9nZQXmygPJmOeXOMsqb5ZQ7y+Qkb5YUJyo+5IlSo0YNtm/fnmnbjRs3uHz5MgaDIcvxdnZ25tcGg4H09HRMJhPdu3dnzJgxWY4vUqSIuR0bGxvWrVvHTz/9xLZt2/j6669Zvnx5Hl+RiIiIyKPjngvORR43LVq04ObNm4SEhAC3F4VPnz6d7t27U7ZsWZKSknLUxvbt27l69SoAf/31F9HR0VmOS0pKIjExkTZt2jBhwgR+//33PL0WERERkUeNRj7kiWJlZcWCBQvw9/dn4cKFZGRk0KZNG0aPHk1ycjKLFy/Gy8vLvOA8OzVq1OC9997jrbfeIiMjA1tbWyZNmkTlypUzHZeUlIS3tzcpKSkA+Pr65uu1iYiIiDzsrEwmk6mwgxCR/6N5qbmn+byWU+4so7xZTrmzjPJmOeXOMvm15kPTrkREREREpECo+BARERERkQKh4kNERERERAqEig8RERERESkQKj5ERERERKRAqPgQEREREZECoeJDREREREQKhIoPEREREREpEHrCuchDxN/fv7BDeGR5e48u7BBERETkPjTyISIiIiIiBULFhzwy4uLi6N+/P2PGjMmX9k0mE6NGjeL48eMP3NaNGzdYtWoVJpMpDyITEREReTxo2pXkmouLCxEREZm2rVy5kmLFitGtW7dszwkPD2fp0qV89tln92z7f//7H1OnTiU1NZXU1FQ8PT0ZMWIEAE5OTkyePJnIyEgAUlNTsbKywtbWFoDevXuTmprKtWvXuHXrFuXLlwdgwYIFdOnSJUvMdxw8eJB58+bxwgsv8M4771CrVq0sxxw5coSZM2cSExND8eLFcXZ2ZsyYMdSqVSvLtaelpfHJJ58waNAg0tLSAFi/fv098yMiIiLyJFDxIXmiX79+edLO+++/T2BgILVr18ZoNHL+/HnzPmtra6pXr0716tUBOHr0KH/++SedOnUCYO3atQAEBwdz7NgxJk2alKM+09LSWLZsGT///DM1a9bMsj8uLo733nuPWbNm0bhxY+B2wXLx4kVq1aqV5dptbW3x8/MDbhctv/32W57lR+7O2dmhsEN4ZCl3llHeLKfcWUZ5s5xyZ5n8yJuKD8kTQUFB2Nvb8/bbbxMZGYmfnx/x8fEYDAYCAwMBSE5OxsfHh1OnTlGvXj1mzZqFlZVVpnbi4+NxdnYGwGAwUKNGjSztA9SqVYtq1aqxcOHCHMc4Z84cwsLCKFq0KAsXLqRs2bLEx8fzzTffMHPmTKysrJgwYQJNmjTJdN7XX39Nt27dzIUHgKura7bXHhUVxYQJE0hISODUqVNUrlyZwMDALPFL3ouNTSzsEB5Jzs4Oyp0FlDfLKXeWUd4sp9xZJid5s6Q40ZoPyXNjx47l9ddfZ+PGjaxatcpcTBw/fpwJEyawZcsWoqKiOHToUJZzBw4cSIcOHXj33XdZtWoVKSkp2fbx3HPP8fnnn5tHQe4nOTmZRo0asXHjRlxdXVmzZg0AU6dOZeDAgQQHBxMYGMjEiROznHvmzBnq1q2bo34CAgLo3r07mzZtYurUqdSuXZsGDRrk6FwRERGRx51GPiRP3bhxg5iYGDw8PAAoUqSIeV/Dhg2pUKECALVr1yY6OjrTCALA8OHD6dq1K/v27ePbb79l8+bNfPXVVw8cl62tLS+//DIA9evXZ//+/QD8+OOPXLlyxXyc0WgkKSmJ4sWL37Wt3r17c+PGDV566SU++OCDTPsiIiIICgoCwMvLi5kzZz5w7CIiIiKPCxUfUmDs7OzMrw0GA0ajMdvjqlatymuvvUafPn1o0aIFCQkJGAwGMjIyzMfcbUTkbmxtbc1TvKytrc19Z2Rk8N///peiRYve9dwaNWpw/Phx3N3dgdtrS7Zt28bu3btzFYOIiIjIk07Fh+SpEiVKUKFCBXbu3Im7uzupqal3LTKys3v3btq0aYOVlRWRkZFYW1tTsmRJKleubP6y/9tvvxEdHZ0n8bZs2ZKvvvqKwYMHA3Ds2DHq16+f6ZjXX3+dPn360LJlS/O6j1u3bmXbnouLC5s3b6Zbt25s2rQpy8jO/fj5+WleqgU0n1dEROTRoOJDcu3mzZu0bt3a/P7NN9/MtH/GjBlMmjSJwMBAbG1tzQvOcyI0NJRp06ZRtGhRDAYDs2bNwmAw0L59e0JDQ+nUqRONGjXi6aefzpNrmThxIlOmTKFLly4YjUZcXV2zFB/Ozs7MmTOHWbNmERMTQ5kyZShdujTvvvtulvY+/PBD/v3vf/P555/j5OTEtGnT8iROERERkceBlUlPQRN5qOgX/NzTyIfllDvLKG+WU+4so7xZTrmzjO52JQ+1lStXEhISUthhiIiIiMhDTNOuJE/oIXoiIiL/r717D+yx/v8/ft/eNqcNm8YcOjiEHJZpjJxqjDXb3o5FJSufiJgcP04Za3LM+ZwkkhKzhaQcQ+yDlkNUDGMSZo472nb9/vDz/rYM27vZmMftn8/e1+u6Xq/n9XR94rnX63W9ReReNPMhIiIiIiJ5QsWHiIiIiIjkCRUfIiIiIiKSJ1R8iIiIiIhIntCG80dcamoqffr0YfTo0ZQvX/6+jpWUlER4eDivvPIKtra5V/cePXqU06dP4+XllWt95pcxY8bkdwgPnd69B+R3CCIiIpJNmvkoYNzd3S0/b9u2jdatW3PmzJnbXoW7du1aunbtSlhYGCNHjsxW4XHp0iXMZjNms5nGjRvTtGlTy+cTJ07g5+d3x2vT09P56KOPaNCgAba2tiQmJmbrfoYOHYqXlxdmsxkfHx9mzZqVqT0tLY3x48dTq1atu/YTGRlJz549szXed999B8Dly5dp27Ytq1atyvb1IiIiInJnmvkooHbt2kVoaCiffPIJFSpUuO1VuKVKlWLp0qXs3LmTJ554Ilt9Ojk5ERERAcDMmTMpVqwY3bt3ByA2Nvau15pMJkaOHGn5/Nlnn9GxY0dcXFzuOe6QIUPw8fEhJSUFX19fzGYzjz/+OAAxMTEEBQVRtmzZbN1Ddl27do3u3bvz8ssv06FDByIjI3O1fxEREZFHkYqPAmjPnj2MHDmSBQsWWAqLvxcLp06d4tNPP2XKlCkUKVIEV1dXqlSpwtChQ3FwcODQoUNcuHCBwYMH4+Pjk+1x09PTGTlyJFFRUZQtW5Y5c+ZQpEgRunbtypAhQ6hTpw7x8fE0atSI5s2b0717dyZMmMD27duxsbHh5ZdfpmvXrnfsPyUlBYBixYoBMGvWLLZs2UJKSgru7u6EhIRgY2NDTEwMwcHBxMfHYzKZmD59OgCJiYkEBQXxxx9/UKtWLSZPnoyNjc1t4yQmJvL222/j7+/Pq6++mul4Vtfv2rWLCRMmkJ6eTu3atRkzZgz29vZ3jE9ERETkUaXio4BJTU3l3XffZcmSJVSpUiXLc0aOHElISAhPPfUUUVFRjB49mqVLlwJw/vx5vvjiC44fP06vXr1yVHzExMQwZcoUQkND6devHxs2bMBsNt92XoUKFViwYAFffPEFZ86cITw8nEKFCnH58uUs+504cSJz587l1KlTdO3aldKlSwPw+uuv06dPHwzDYNCgQWzZsgUvLy8GDRpEjx498Pb2JiUlhYyMDM6ePcvhw4dZt24dZcqUoUuXLuzbtw8PD4/bxhs/fjwdO3YkMDAw0/Gsrq9Tpw5Dhw5l8eLFVKpUiSFDhvDFF18QGBhoiQ9g8ODBlvgkd7m4OGb6X8k55c46ypv1lDvrKG/WU+6scz/ypuKjgClUqBDu7u6sXLky0zKnWxISEjhw4ADvv/++5djVq1ctP7ds2RJbW1uqVq1KXFxcjsauWLEizzzzDAC1atXizJkzdz1/165ddO7cmUKFbj6GpUqVyvK8W8uuEhISCAwM5Oeff6ZevXrs3buXzz77jPT0dM6fP0/16tVp0KAB586dw9vbG4DChQtb+nFzc8PV1RWAGjVqcObMmSyLj4YNG7Jp0ya6d+9uKXTudL2DgwMVK1akUqVKALRr145ly5YRGBhIZGQkCxcuJDk5mcuXL/P000+r+LgPLly4houLIxcuXMvvUB5Kyp11lDfrKXfWUd6sp9xZJzt5s6Y4UfFRwNja2jJt2jQCAwOZN28e77zzTqZ2wzBwcHCwzHT8k729vdVj//1ak8lkWSZlMpkwDAO4OTNjreLFi9OgQQP27dtH7dq1CQ4OJjw8HBcXF2bMmGEZL7vxpaenZ3mer68v9erV4+2332bJkiU4ODjk6Hq4uURszJgxrFq1inLlyjFz5sx7xiciIiJS0OltVwVQ0aJFmT9/PmvWrOHrr7/O1HbrN/XffvstABkZGRw+fPi+xlOhQgUOHToEwIYNGyzHn3/+eb766ivS0tIA7rjs6pa0tDQOHDjAE088QXJyMhkZGTg6OpKQkMD3338P3Lw/V1dXNm7cCNwsdpKSknIcc2BgII0aNaJv3753LZgqVarEmTNniImJASAiIoL69etbCg0nJycSEhIy3beIiIjIo0rFRwFVqlQpFi5cyNy5c9m0aVOmtkmTJrFq1SoCAgLw8/Nj8+bN9zWWt956i+XLl9O2bdtMBUanTp0oV64cAQEBBAQEsHbt2iyvnzhxImazmYCAAKpVq0arVq0oUaIEHTt2xM/Pj+7du1OnTp1M5y9ZsgR/f386d+6c4+VjtwwePBhXV1eGDBlCRkZGlucULlyYcePG0a9fP/z9/bGxsaFLly6UKFGCTp06ZRmfiIiIyKPKxri1HkZEHghal5pzWs9rPeXOOsqb9ZQ76yhv1lPurHO/9nxo5kNERERERPKEig8REREREckTKj5ERERERCRPqPgQEREREZE8oeJDRERERETyhIoPERERERHJEyo+REREREQkT6j4EBERERGRPFEovwMQkf8zZsyY/A7hgdW794D8DkFERET+Jc185LKjR4+yefPm/A7DIi0tjY8//phLly7ldygiIiIi8ohT8ZFDc+fOpU2bNvj7+2M2m9m/f7+lLS0tjfHjx1OrVq279hEZGUnPnj2zNd4nn3yCj48PZrOZDh06EB4eDoCXlxfx8fG3nb9p0yYWLFhg+Txr1iwqV67MRx99RHp6erbG/KcxY8ZgNpvx9fXFzc0Ns9mM2Wzmu+++4+233+bq1at3vb5r164cPHjQqrEBwsLCCAkJydU+RURERCTvadlVDkRFRbF161ZWr16Nvb098fHx3Lhxw9IeExNDUFAQZcuWzZXxli9fzk8//cTKlStxcHDg+vXr/PDDD3e9pkWLFrRo0cLy+b333rMct1ZwcDAAsbGxvPPOO0RERFjafHx8rO43L6Wnp2MymfI7DBEREZFHmoqPHLhw4QJOTk7Y29sD4OzsbGmbNWsWW7ZsISUlBXd3d0JCQrCxsSEmJobg4GDi4+MxmUxMnz4dgMTERIKCgvjjjz+oVasWkydPxsbGJtN48+fPZ+nSpTg4OADg4OBAu3btLO2ff/45W7ZsIS0tjWnTplGlShXCwsI4dOgQo0aNIj4+nuDgYP78808Ahg8fznPPPcfMmTOJjY3l9OnTnD17lmHDhvHLL7+wfft2ypQpw7x587Czs8tWTry8vFi5ciWJiYm8/fbbPPfcc0RFRVG2bFnmzJlDkSJFAPjuu+8YM2YM165dY+zYsXh4eFj5p3C7tWvXMn/+fAzDoHnz5gwePBgAd3d3XnnlFX766SdGjRrFwYMHWbVqFQAdO3YkMDCQxMRE3nvvPf766y8yMjLo3bs3vr6+HDhwgA8//JDExETs7e1ZvHgxdnZ2jB49mkOHDmEymRg6dCgNGzYkLCyMH374gevXr3Pu3DkCAgLo06cPABERESxdupQbN27w7LPPEhwcrCJIREREHlkqPnKgcePGzJ49m9atW9OoUSN8fX1p0KABAK+//jp9+vTBMAwGDRrEli1b8PLyYtCgQfTo0QNvb29SUlLIyMjg7NmzHD58mHXr1lGmTBm6dOnCvn37Mv2D/Pr16yQkJPD444/fMR4nJydWr17NsmXLWLRoEWPHjs3UPnbsWLp164aHhwd//vkn3bt3Z/369QCcOnWKJUuWEB0dzSuvvMKMGTMYMmQI7777Ltu2baNly5Y5zk9MTAxTpkwhNDSUfv36sWHDBsxmM3Bz5mHlypVs27aNWbNmsXjx4hz1/e2337Jv3z7L51OnTgFw7tw5Jk+eTFhYGCVKlOCtt95i48aNtGzZksTERNzc3Bg6dCiHDh0iLCyMFStWYBgGL7/8Mg0aNOD06dOUKVPGslTt2rVrpKam0r9/f6ZOnYqbmxvXr1+nSJEiLFmyBIA1a9YQHR1N9+7d2bBhAwAHDx5kzZo1FC1alI4dO9K8eXOKFSvG+vXrWb58uaVwWbNmDW3bts1xbgVcXBz/VbvcmXJnHeXNesqddZQ36yl31rkfeVPxkQPFixcnLCyMvXv3EhkZSf/+/Rk4cCDt27dn7969fPbZZ6Snp3P+/HmqV69OgwYNOHfuHN7e3gAULlzY0pebmxuurq4A1KhRgzNnzuR4NqBVq1YA1K5dO8vlWD/99BPHjh2zfL5V0AA0a9YMOzs7qlWrRnp6Os2aNQOgWrVqxMbG5iiOWypWrMgzzzwDQK1atThz5oyl7VYO/nk8u3x9fRk1apTlc9euXYGb/+hv0KCBZRbK39+fPXv20LJlS0wmE61btwZg3759tGzZkmLFilni2bt3L02bNmXChAlMmjSJF198EQ8PD37//XdcXFxwc3MDsMw87du3j9dffx2AKlWqUL58eU6cOAHA888/j5OTk6Xvffv2UahQIQ4dOkTHjh0BSE5OpnTp0jm+d7npwoVrd2xzcXG8a7vcmXJnHeXNesqddZQ36yl31slO3qwpTlR85JDJZMLT0xNPT0+qVatGeHg4fn5+BAcHEx4ejouLCzNmzCAlJeWu/dxaunWrz39uBndwcKBYsWKcPn36jrMft5ZG2draZrmZPCMjgxUrVmQqev45vq2tLXZ2dpYlX3fqKzv+eU9/z8Hfx8uq/6lTp7J161aATHtK/o3ChQvfc4lTpUqVCAsLY9u2bUybNo2GDRtaCqWc+OeSORsbGwzDoF27dgwcODDH/YmIiIgURHrbVQ4cP36ckydPWj4fOXKE8uXLk5ycTEZGBo6OjiQkJPD9998DNwsIV1dXNm7cCEBqaipJSUnZHq9Hjx6MGTOG69evA5CQkGB521V2NGnShKVLl2aK90HVv39/IiIiclx4uLm5sWfPHuLj40lPT2fdunXUr1//tvM8PDzYuHEjSUlJJCYmsnHjRjw8PDh37hxFixbFbDbTvXt3Dh8+TKVKlbhw4QIHDhwAbs4YpaWl4eHhwZo1awA4ceIEZ8+epXLlygDs3LmTy5cvk5yczMaNG6lXrx6NGjViw4YNXLx4EYDLly9bNesjIiIiUlBo5iMHEhMTCQ0N5erVq5hMJp588klCQkIoUaIEHTt2xM/Pj8cee4w6depYrpk4cSKjRo1i+vTp2NnZWTacZ8err75KYmIiHTp0wM7OjkKFCvHmm29m+/oRI0YQEhKCv78/6enpeHh43PbK2oddmTJlGDhwIN26dbNsOM9qv0qtWrVo3749nTp1Am5uOK9Zsybbt29n4sSJ2NraUqhQIUaPHo29vT1Tp04lNDSU5ORkihQpwqeffsqrr77K6NGj8ff3x2QyMW7cOMuMjpubG3379rVsOL/1DLz33nu89dZbZGRkYGdnx6hRo6hQocId7yc4OFhTwyIiIlJg2RiGYeR3ECIPs7+/YSw3qPjIOa3ntZ5yZx3lzXrKnXWUN+spd9a5X3s+tOxKRERERETyhJZdifxL7du3p3379vkdhoiIiMgDTzMfIiIiIiKSJ1R8iIiIiIhInlDxISIiIiIieULFh4iIiIiI5AkVHyIiIiIikif0tiuRB8iYMWPyO4QHSu/eA/I7BBEREclFmvmQPLF161Z27NiR32HkqoSEBJYtW5bfYYiIiIg8NFR8iMWlS5cwm82YzWYaN25M06ZNLZ9TU1Ot7vfAgQNERUWxe/dujh49mqNrN27cyLFjx+7Yvnz5csLDw+/aR1hYGCEhIfcca/HixSQlJVk+u7u73/X8qVOn8uSTT96zXxERERG5ScuuxMLJyYmIiAgAZs6cSbFixejevbulPS0tjUKFcv7IuLm54ebmZlVMGzdu5IUXXqBq1aq3taWlpdGlSxer+s3KkiVLCAgIoGjRovc8Nykpieeee44mTZrk2vgiIiIiBZ2KD7mroUOHYm9vz5EjR6hXrx4ODg6ZihI/Pz/mzZvHqlWrKFmyJIGBgcDNWQFnZ2e6devGwoULWb9+PampqXh7exMUFERsbCxvv/02zz33HFFRUZQtW5Y5c+ZQpEgRy9g///wzmzdv5n//+x9z585l5syZjBgxgho1arBv3z78/PxISEiwxNO1a1fc3NyIjIzk2rVrjB07Fg8PDwDOnz9P9+7dOX36NC1btmTIkCGZ7nPJkiWcP3+ebt26UapUKZYuXWq5jy1btlCkSBHmzJnDY489xubNm5k7dy6pqal89dVXTJ48mccee4yZM2cSGxvL6dOnOXv2LMOGDeOXX35h+/btlClThnnz5mFnZ5cHf2oiIiIiDyYVH3JP586d48svv8RkMjFz5swsz+nQoQN9+/YlMDCQjIwM1q1bx9dff82OHTuIiYlh5cqVGIZBr1692LNnD+XKlSMmJoYpU6YQGhpKv3792LBhA2az2dJnvXr18PLy4oUXXsDHx8dy/MaNG4SFhQHcFk96ejorV65k27ZtzJo1i8WLFwNw5MgRwsPDsbe3x8fHh65du1KuXDnLdW+88QaLFy/ms88+w9nZGYDExESeffZZ+vfvz8SJE1mxYgW9e/fmueeeY8WKFdjY2PDll1+ycOFChg4dCsCpU6dYsmQJ0dHRvPLKK8yYMYMhQ4bw7rvvsm3bNlq2bPnv/0AeIS4ujvflXMlMubOO8mY95c46ypv1lDvr3I+8qfiQe/Lx8cFkMt31nIoVK1KqVCkOHz5MXFwcNWvWxMnJiZ07d7Jz507atm0L3PwH/cmTJylXrhwVK1bkmWeeAaBWrVqcOXMmW/H4+vresc3b2zvL/ho1aoSj483/A1WpUoUzZ85kKj6yYmdnx4svvghA7dq12blzJ3BzFuW///0vV69eJTk5GScnJ8s1zZo1w87OjmrVqpGenk6zZs0AqFatGrGxsdm6P/k/Fy5cy9Z5Li6O2T5XMlPurKO8WU+5s47yZj3lzjrZyZs1xYmKD7mnv++BMJlMZGRkWD6npKRYfu7UqRNhYWHExcXRoUMHAAzDoEePHnTu3DlTn7Gxsdjb22fq9+99ZTeef7rVp62tLenp6bcdvzXW39vuxM7ODhsbm9v6CwkJ4e2336ZZs2bs3r2b2bNnZzn+na4XEREReVTpbVeSIxUqVODw4cMA/Prrr5l+m9+yZUu2b9/OwYMHLRuxmzRpwqpVq0hISABuLuG6ePFitscrXry45dr7LbtjXb161bI0615v2hIRERGR/6OZD8mR1q1bExERQZs2bXBzc+Opp56ytNnb2+Pp6UmJEiUsy7SaNGlCdHS0ZeajWLFiTJo0CVvb7NW9vr6+vP/++yxdupQZM2bk+v383csvv8x//vMfypQpY9lwnpV3332XoKAgSpUqhaenZ7aXi2VHcHCwpoZFRESkwLIxDMPI7yCkYMjIyKBdu3ZMnz49U1EiOaPiI+e0ntd6yp11lDfrKXfWUd6sp9xZ537t+dCyK8kVx44dw9vbm0aNGmVZeJjNZstreEVERETk0aRlV5IrqlatyqZNm+7YfuvLC0VERETk0aWZDxERERERyRMqPkREREREJE+o+BARERERkTyh4kNERERERPKEig8REREREckTetuVyANkzJgx+R3CA6N37wH5HYKIiIjkMs185LGjR4+yefPm/A6jwNq6dSu///57rvW3e/duDhw4kGv9iYiIiDzKVHzksrlz59KmTRv8/f0xm83s37/f0paWlsb48eOpVavWXfuIjIykZ8+e9xxr6NChPPvss1y/ft1ybOzYsVSvXp34+Pgcxe3l5ZXta44cOcK2bdssnzdt2sSCBQtyNJ41vLy8LHn19/dn48aNmdpjY2NZvnw5VapUyVG/M2fO5JNPPsmyrWbNmkybNo3ExESr4xYRERGRm7TsKhdFRUWxdetWVq9ejb29PfHx8dy4ccPSHhMTQ1BQEGXLls21MZ944gk2bdqE2WwmIyOD3bt357j/9PT0HJ1/5MgRDh06RPPmzQFo0aIFLVq0yFEf1vrss89wdnbm+PHjdO/enZYtW1rajh8/ztixYylUKPce6xIlSjBs2DCio6OpU6dOrvUrIiIi8ihS8ZGLLly4gJOTE/b29gA4Oztb2mbNmsWWLVtISUnB3d2dkJAQbGxsiImJITg4mPj4eEwmE9OnTwcgMTGRoKAg/vjjD2rVqsXkyZOxsbG5bcw2bdqwfv16zGYzkZGR1KtXj+3bt1vae/fuzV9//UVKSgpvvPEGr7zyCgDu7u688sor/PTTT4waNcpyfnJyMn369KFVq1b4+fnxwQcfcPToUdLS0ujTpw/NmjVjxowZJCcns2/fPnr27ElycjKHDh1i1KhRDB06FAcHBw4dOsSFCxcYPHgwPj4+ZGRkEBISwu7duylXrhyFChWiQ4cO+Pj4WJXr69evU6JEidvuMzk5mW7dumW6zzfeeIMtW7ZQpEgR5syZw2OPPXZbf8eOHaNr1678+eefdOvWjTfeeOOe+cuq31OnTjFo0CCSkpLw8vJiyZIlREVFWXWPIiIiIgWNio9c1LhxY2bPnk3r1q1p1KgRvr6+NGjQAIDXX3+dPn36YBgGgwYNYsuWLXh5eTFo0CB69OiBt7c3KSkpZGRkcPbsWQ4fPsy6desoU6YMXbp0Yd++fXh4eNw25lNPPcXmzZu5cuUK69atIyAgIFPx8eGHH1KqVCmSk5Pp2LEjrVq1wsnJicTERNzc3Bg6dKjl3MTERAYMGEDbtm1p27YtU6ZMoWHDhowbN46rV6/SqVMnnn/+eYKCgizFBkBYWFimmM6fP88XX3zB8ePH6dWrFz4+Pnz//fecOXOGb7/9losXL+Lr60uHDh1ynONu3bphGAanT59m2rRpt91nUlISHTp0yHSfzz77LP3792fixImsWLGC3r1739bviRMnWLJkCdevX+ell16iS5cu2NnZ3TV/WfU7duxY3njjDfz8/Fi+fHmO70/+j4uL4309X/6Pcmcd5c16yp11lDfrKXfWuR95U/GRi4oXL05YWBh79+4lMjKS/v37M3DgQNq3b8/evXv57LPPSE9P5/z581SvXp0GDRpw7tw5vL29AShcuLClLzc3N1xdXQGoUaMGZ86cybL4APD29mbdunXs37+fkJCQTG1Lly7lhx9+AODs2bPExMTg5OSEyWSidevWmc7t3bs3//nPfwgICABgx44dbN68mUWLFgGQkpLC2bNn75mHli1bYmtrS9WqVYmLiwNg3759+Pj4YGtri4uLC56envfsJyu3ll2dOnWKwMBAGjRoQPHixVm+fDnbtm2jUKFCXLx40XKfdnZ2vPjiiwDUrl2bnTt3Ztlv8+bNsbe3x9nZGWdnZy5evIirq+sd83enfn/55Rdmz54NgL+/PxMnTrTqPgUuXLiW7XNdXBxzdL78H+XOOsqb9ZQ76yhv1lPurJOdvFlTnKj4yGUmkwlPT088PT2pVq0a4eHh+Pn5ERwcTHh4OC4uLsyYMYOUlJS79nNr6datPu+2L8PX15f27dvTrl07bG3/7x0CkZGR/PTTT3z11VcULVqUrl27WsYtXLgwJpMpUz+3lmz5+/tblnjNmDGDypUrZzrv75vo7xV7Tpw9e5Z33nkHgM6dO9OlS5c7nvvEE09QunRpoqOjSU5OZseOHSxZsgR7e3tef/11y33a2dlZ7sXW1vaOefxnvtPS0u6av+z2KyIiIiL/R2+7ykXHjx/n5MmTls9HjhyhfPnyJCcnk5GRgaOjIwkJCXz//fcAODg44OrqanlrU2pqKklJSTket0KFCvTv359XX3010/Fr165RsmRJihYtSnR0NL/88std+wkKCqJkyZKW75po0qQJn3/+OYZhAHD48GHg5gxPQkJCjmKsV68e33//PRkZGcTFxfG///3vtnPKlStHREQEERERdy08AC5evEhsbCzly5fn6tWrODo6Ym9vT3R09D2Lo+zKaf4Ann32Wcuf77p163IlDhEREZGCQjMfuSgxMZHQ0FCuXr2KyWTiySefJCQkhBIlStCxY0f8/Px47LHHMr01aeLEiYwaNYrp06djZ2dn2XCeU507d77tWLNmzfjyyy956aWXqFSpEnXr1r1nPyNGjGD48OFMnDiRoKAgPvzwQwICAsjIyKBixYrMnz8fT09PFixYgNlsztYrgQFat27Nrl278PX1pVy5ctSsWRNHx5xP1XXr1g1bW1vS0tIYOHAgjz32GE2bNmX58uU5us/ssCZ/w4cPZ/DgwcydO5emTZvi4OCQozGDg4M1NSwiIiIFlo1x69faIvdZQkICxYsX59KlS3Tq1Inly5fj4uKS32HlqqSkJIoUKYKNjQ3r1q1j7dq1zJ07N0d9qPjIOa3ntZ5yZx3lzXrKnXWUN+spd9bRng956L3zzjtcvXqVGzdu0Lt37wJXeAD8+uuvhISEYBgGJUqU4MMPP8zvkEREREQeGCo+JM8sXbo0v0O47zw8PPjmm2/yOwwRERGRB5I2nIuIiIiISJ5Q8SEiIiIiInlCxYeIiIiIiOQJFR8iIiIiIpInVHyIiIiIiEie0NuuRB4gt75d/lHTu/eA/A5BRERE8oBmPh4xqamp9OjRgz///PO+jXHx4kVWr1593/rPyjfffMPZs2fzdEwRERERyRkVHw85d3d3y8/btm2jdevWnDlzhuXLlxMeHm5pW7t2LV27diUsLIyRI0dSvnz5bPV/9epVli1bZvkcGRlJz54973h+UlIS06ZNo3HjxsDNbzX/t5555hnMZjMBAQG0a9eOn3/+OVP7gQMH2LlzJ+XKlbtrP0OHDuW777676zmxsbH4+fnddjwsLIyQkJCcBy8iIiIiFio+Cohdu3YRGhrKxx9/TIUKFejSpQtt27a1tJcqVYqlS5fy+OOP88QTT2S736tXr7J8+fJsn1+0aFE++OADypQpA8BHH32U7WvvpEiRIkRERPDNN98wYMAApkyZkqn9zJkzjB49+l+PIyIiIiL3l4qPAmDPnj2MHDmSefPmWQqLmTNn8sknnwBw6tQpPv30U9q3b8/s2bOJjo4Gbs4EhIaG0rlzZ1q0aJHlrMBHH33EqVOnMJvNTJgwAYDExESCgoLw8fFh4MCBGIYBgJeXF/Hx8QAcPHiQ6tWrc+XKFRISEhg2bBj+/v74+/uzYcMGq+/1+vXrlChRArg5q9KtWzcWLFhAp06d2Lhxo+W88PBw/P39CQgIYPDgwZbje/fuvev9/t3p06dp27YtBw4cAOD8+fN0796dVq1aMXHiRMt5a9euxd/fHz8/PyZNmmQ5HhwcTPv27WnTpg0zZsyw+p5FRERECgptOH/Ipaam8u6777JkyRKqVKmS5TkjR44kJCSEp556iqioKEaPHs3SpUuBm/+g/uKLLzh+/Di9evXCx8cn07UDBw7k6NGjREREADeXXR0+fJh169ZRpkwZunTpwr59+/Dw8Lht3AYNGvDRRx8xadIkHBwcWLNmDQBXrlzJ0T0mJydjNptJSUnhwoULfPbZZwAULlyY2bNn4+DgwMWLF3nllVdo0aIFx44dY+7cuSxfvhxnZ2cuX75s6ete93vL8ePHGTBgAOPHj6dGjRocO3aMI0eOEB4ejr29PT4+PnTt2hVbW1smT55MWFgYJUqU4K233mLjxo20bNmS/v37U6pUKdLT0wkMDOS3336jRo0aObr3R4WLi+MD0cejSrmzjvJmPeXOOsqb9ZQ769yPvKn4eMgVKlQId3d3Vq5cyciRI29rT0hI4MCBA7z//vuWY1evXrX83LJlS2xtbalatSpxcXHZGtPNzQ1XV1cAatSowZkzZ7IsPm7ZtWtXpqVSJUuWzNY4t9xadgUQFRXFf//7X9auXQvcnOHZv38/dnZ2xMXFERcXx+7du/Hx8cHZ2Rm4ueQsJ/cbHx9P7969mTVrFlWrVrUcb9SoEY6ON/9PWKVKFc6cOcPly5dp0KCBZSx/f3/27NlDy5YtWb9+PStWrCAtLY0LFy4QHR2t4uMOLly49q+ud3Fx/Nd9PKqUO+sob9ZT7qyjvFlPubNOdvJmTXGi4uMhZ2try7Rp0wgMDGTevHm88847mdoNw8DBwcEy0/FP9vb2OR7z79eYTCbS09MtP99agpWSkpLt/vbv38+oUaMACAoKokWLFnc8193dnUuXLhEfH8+PP/5IXFwcy5Ytw2Qy8eKLL95z3Ozcr6OjI+XLl2ffvn2Zio873XdWTp8+zaJFi1i5ciUlS5Zk6NChOcqJiIiISEGkPR8FQNGiRZk/fz5r1qzh66+/ztTm4OBAxYoV+fbbbwHIyMjg8OHD2e67ePHi2X5jVYUKFTh06BAA33//veX4888/n+mNWf9cdvXss88SERFBRETEXQsPgOjoaNLT0ylVqhRXrlyhVKlSmEwmdu/ebXl9cMOGDfnuu++4dOkSQKZlV9lhZ2fHrFmzCA8PtywVuxM3Nzf27NlDfHw86enprFu3jvr165OQkEDRokVxdHQkLi6OH3/8MUcxiIiIiBREmvkoIEqVKsXChQt57bXXLEuAbpk0aRKjR49m3rx5pKWl4evrS82aNbPVr5OTE/Xq1cPPz4+mTZvywgsv3PHcPn36MGLECKZPn07Dhg0tx3v16kVISAh+fn7Y2trSp08fWrVqle17u7XnA27O5EyYMAGTyURAQAA9e/bE39+f2rVrU7lyZQCefvpp3nnnHcuejJo1azJ+/PhsjwdQrFgx5s+fz5tvvkmxYsXueF6ZMmUYOHAg3bp1wzAMmjdvTsuWLQGoWbMmL730Eq6urtSrVy9b4wYHB2tqWERERAosG+PWOhkReSCo+Mg5ree1nnJnHeXNesqddZQ36yl31rlfez607EpERERERPKEig8REREREckTKj5ERERERCRPqPgQEREREZE8oeJDRERERETyhIoPERERERHJEyo+REREREQkT+hLBkUeIGPGjMnvEPJc794D8jsEERERySOa+RARERERkTyh4kMAOHr0KJs3b87vMHJVTEwMvXv3JjU1Nb9DERERERFUfDwy5s6dS5s2bfD398dsNrN//35LW1paGuPHj6dWrVp37SMyMpKePXvec6yhQ4fy3XffZTrm7u5uXeD/39y5czGbzZjNZp555hnLz0uWLGHEiBEcO3bMcm5oaCj/+c9/OHHiBBMmTMDe3v5fjQ3g5eVFfHy85XN2cyEiIiIi/0d7Ph4BUVFRbN26ldWrV2Nvb098fDw3btywtMfExBAUFETZsmXzMcq769WrF7169QJuFjIRERFZnpeUlMRLL71E9erViY6OxtHRMS/DFBEREZG7UPHxCLhw4QJOTk6WGQBnZ2dL26xZs9iyZQspKSm4u7sTEhKCjY0NMTExBAcHEx8fj8lkYvr06QAkJiYSFBTEH3/8Qa1atZg8eTI2NjbZjsUwDCZOnMj27duxsbGhV69e+Pr6ArBgwQLWrFmDjY0NzZo1Y9CgQdnqs2vXrgwZMoQ6deqwb98+Zs6cSUpKCk888QTjxo2jePHieHl50bZtW7Zs2UJaWhrTpk2jSpUqxMfHM3DgQM6fP0/dunX56aefWLVqVaYc3cvly5cZPnw4p0+fpmjRooSEhFCjRg0OHDjA2LFjSUlJoUiRInz44YdUrlw52/0+KlxccqdAzK1+HkXKnXWUN+spd9ZR3qyn3FnnfuRNxccjoHHjxsyePZvWrVvTqFEjfH19adCgAQCvv/46ffr0wTAMBg0axJYtW/Dy8mLQoEH06NEDb29vUlJSyMjI4OzZsxw+fJh169ZRpkwZunTpwr59+/Dw8LhtzIkTJzJ37tzbjn///ff89ttvREREcOnSJTp27IiHhwdHjhxh8+bNrFixgqJFi3L58uUc32d8fDyzZ8/m008/pVixYsyfP59PP/2UPn36AODk5MTq1atZtmwZixYtYuzYscyaNYuGDRvSs2dPfvzxR1auXHnH/rt164at7c2ViomJiZZCYubMmdSsWZM5c+awa9cu/vvf/xIREUHlypVZtmwZhQoV4qeffmLq1KnMnDkzx/dV0F24cO1f9+Hi4pgr/TyKlDvrKG/WU+6so7xZT7mzTnbyZk1xouLjEVC8eHHCwsLYu3cvkZGR9O/fn4EDB9K+fXv27t3LZ599Rnp6OufPn6d69eo0aNCAc+fO4e3tDUDhwoUtfbm5ueHq6gpAjRo1OHPmTJbFx5AhQ/Dx8bF8vrXnY9++fbRp0waTycRjjz1G/fr1OXjwIHv27KF9+/YULVoUgFKlSuX4Pvfv309sbKxlL0ZKSgo1atSwtLdq1QqA2rVr88MPP1jimTVrFgDNmjWjZMmSd+z/s88+s8yIREZGsmjRIksft4qKRo0acfnyZa5fv861a9f473//S0xMDDY2NpmWuomIiIg8ilR8PCJMJhOenp54enpSrVo1wsPD8fPzIzg4mPDwcFxcXJgxYwYpKSl37efvm7dNJhPp6en3O/RsMwwDDw8Ppk6dmmW7nZ0dALa2tnkS9/Tp0/H09GT27NnExsbyxhtv3PcxRURERB5ketvVI+D48eOcPHnS8vnIkSOUL1+e5ORkMjIycHR0JCEhge+//x4ABwcHXF1d2bhxIwCpqakkJSXlSiweHh6sX7+e9PR04uPj2bt3L25ubjz//POEhYVZxrFm2VXdunX5+eefiYmJAW4ujTp+/Phdr6lXrx7r168HYMeOHVy5ciXH43p4ePDNN98AN2dEnJyccHBw4Nq1a5ZN/KtXr85xvyIiIiIFjWY+HgGJiYmEhoZy9epVTCYTTz75JCEhIZQoUYKOHTvi5+fHY489Rp06dSzXTJw4kVGjRjF9+nTs7OwsG87/LW9vb6KiojCbzdjY2DB48GBcXFxwcXHht99+o0OHDtjZ2dG8eXMGDMjZN187Ozszfvx4BgwYYPluj/fee++um7z79OnDgAED+Oabb6hbty4uLi44ODjkaNw+ffowfPhw/P39KVq0KOPHjwfgP//5D0OHDmXu3Lk0b948W30FBwdrXaqIiIgUWDaGYRj5HYRIfklNTcXW1pZChQoRFRXF6NGj7/ga37yi4iPntJnQesqddZQ36yl31lHerKfcWUcbzqVAWbBgAVWqVKFFixb5Gseff/7Je++9R0ZGBnZ2dnzwwQf5Go+IiIhIQabiQ/JFjx498jsEAJ566inCw8PzOwwRERGRR4I2nIuIiIiISJ5Q8SEiIiIiInlCxYeIiIiIiOQJFR8iIiIiIpInVHyIiIiIiEie0NuuRB4gY8aMye8Qcl3v3jn7skgREREpuB66mY+tW7eyY8eO+z5OcHAwnTp14uLFi/+6r/Pnz9O1a1f69u2bC5Hln+joaPr27UtaWlqu9XnkyBG2bduWa/1lx7Jlyzh16lSejikiIiIi96n4uHTpEmazGbPZTOPGjWnatKnlc2pqqtX9HjhwgKioKHbv3s3Ro0dzfH1ERAT+/v60adOGgIAARowYwdWrVwEYMWIEx44ds5w7fPhwmjVrhq1t1ikKCwvj3Llzdx0vISEBgNKlSxMcHIzZbMYwDBITE3Mce04MHTqU7777LtMxd3d3q/szDIOQkBAWLlyI2WzOUfyRkZE899xzmM1m/P39CQwMtBR0iYmJjB8/ntq1a2e7v6FDh+Ll5YXZbKZdu3ZERUUB0LVrVw4ePHjb+QcPHiQ0NNTyedmyZZQsWZI5c+bk+M/hTmP8U3p6OikpKTnqW0RERORRcF+WXTk5OREREQHAzJkzKVasGN27d7e0p6WlUahQzod2c3PDzc3Nqph+/PFHPvvsMxYuXEjZsmVJT09n9erVxMXFUaJECcaOHZvp/NTUVLy9vXFycsqyv9WrV/P0009TtmzZO4750UcfMWrUKEwmE1WrVqVq1aoYhkFoaCgffvihVfeRH27cuEGfPn0oVaqUJV854eHhwfz584GbOVm2bBlBQUEcPXqUYcOGUbp06Rz1N2TIEHx8fNixYwejRo1izZo1dzy3Tp061KlTx/L5tddeA8DPzy9HY+ZEXFwcERERD8wXKYqIiIg8KPJsz8fQoUOxt7fnyJEj1KtXDwcHh0xFiZ+fH/PmzWPVqlWULFmSwMBAAKZOnYqzszPdunVj4cKFrF+/3lIYBAUFERsby9tvv81zzz1HVFQUZcuWZc6cORQpUiTT+PPmzWPIkCGWYsFkMtGxY0dLe9euXRkyZAh16tQhODiYgwcPkpKSQuvWrQkKCsrU13fffcehQ4cYNGgQRYoU4auvvsLX15eVK1fi7OzMwYMH6dixI35+fqSkpDB69GgOHTrEiRMnSEtLY/To0YSFhbF582aSkpI4ffo0LVu2ZMiQIQB8/fXXLFy4EEdHR2rUqIG9vT2jRo3KlT+HyMhIFi1aZCkGQkJCqF27NuXKlWPp0qXMmTMHgJ07d/LFF18we/Zs/ve//zFz5kxSU1N5/PHHGTduHMWLF8fLy4u2bduyZcsW0tLSmDZtGlWqVLnj2IZhkJCQwBNPPAHcXMZ16NAhq++tfv36mZZPfffdd4wZM4Zr164xduxYPDw8Mt1vYmIiH3zwAUePHiUtLY0+ffrQsmVLwsLCMsXRs2dP3nrrLTw9Pe8Zwz+vbdWqFXFxccydOxd3d3fLzMx3333H1q1bGT9+vFX3+jBzcXEsUOMURMqddZQ36yl31lHerKfcWed+5C1PN5yfO3eOL7/8EpPJxMyZM7M8p0OHDvTt25fAwEAyMjJYt24dX3/9NTt27CAmJoaVK1diGAa9evViz549lCtXjpiYGKZMmUJoaCj9+vVjw4YNmM3mTP0eO3aMWrVqZSvO/v37U6pUKdLT0wkMDOS3336jRo0alnYfHx+WLVtmKVay0qBBAz766CMWLVoEwJo1a4iOjqZ79+60a9eOdevWceTIEcLDw7G3t8fHx4euXbtia2vL3LlzCQsLo3jx4nTr1i3T2Nk1ceJE5s6dm+3zGzZsyJgxY4iPj8fZ2ZmwsDA6dOhAfHw8c+fO5dNPP6VYsWIsWLCATz/9lD59+gA3Z7lWr17NsmXLWLRo0W0zSAB79+7FbDZz+fJlihYtyoABubMBefPmzVSrVs3yOT09nZUrV7Jt2zZmzZrF4sWLM50/b948GjZsyLhx47h69SqdOnXi+eefz5VYbqlUqRIffPBBtgqXR8WFC9fu+xguLo55Mk5BpNxZR3mznnJnHeXNesqddbKTN2uKkzwtPnx8fDCZTHc9p2LFipQqVYrDhw8TFxdHzZo1cXJyYufOnezcuZO2bdsCN/cLnDx5knLlylGxYkWeeeYZAGrVqsWZM2fuOsbvv//OkCFDSEhIYMCAAfj6+mZqX79+PStWrCAtLY0LFy4QHR1tVQEAsG/fPl5//XUAqlSpQvny5Tlx4gQAjRo1wtHR0dJ25swZLl++TP369SlVqhRwM2cnT57M8bi3libdcq89HzY2NpjNZr755hvat29PVFQUEyZMYPv27Rw7dowuXboAN5dg1a1b13Jdq1atAKhduzY//PBDln3/fdnVggULmDhxIiEhITm+p1tuFVbOzs6Zih1vb2/gzs/Ajh072Lx5s6UgTElJ4ezZs1bHISIiIiI5k6fFR9GiRS0/m0wmMjIyLJ//vkG3U6dOhIWFERcXR4cOHYCbS3Z69OhB586dM/UZGxuLvb19pn6z2uxbtWpVfv31Vxo2bEj16tWJiIggJCSE5OTkTOedPn2aRYsWsXLlSkqWLMnQoUOztXnYZDJhGMZt93I3/4w7PT09W9cBdO/enbi4OGrXrp3lbMPd4rxT3tu3b0+vXr0sMzGFChXCMAwaN27MlClTsuzPzs4OAFtb22zF36JFi3u+9ete9/bPwuqWW/m8WywzZsygcuXKmY4dOnTojjm5l7vl8++0AV1EREQkH1+1W6FCBQ4fPgzAr7/+SmxsrKWtZcuWbN++nYMHD9KkSRMAmjRpwqpVqyxvkDp37lyOXoPbs2dPJk6cyF9//WU59s/CA26+oapo0aI4OjoSFxfHjz/+mGV/xYsXt8Ry634OHToEwPfff2857uHhYdkQfeLECc6ePXvbP37/rk6dOuzZs4crV66QlpaWqa+/++STT4iIiMhR4XErzujoaFJTU7l69Sq7du2ytJUtW5YyZcowd+5cS9FXt25dfv75Z2JiYoCbM063Zm6ssW/fPsuejzux9t7upUmTJnz++eeWIvHW81ehQgV+++03MjIyOHv2LAcOHMh2n3e79rHHHiM6OpqMjAw2btyYq/ciIiIi8jDKty8ZbN26NREREbRp0wY3NzeeeuopS5u9vT2enp6UKFHCskyrSZMmREdHW2Y+ihUrxqRJk+74Ktx/at68OfHx8bz99tukp6dTokQJnn76aUtxc0uNGjWoWbMmL730Eq6urtSrVy/L/tq1a0dwcLBlw3mfPn0YMWIE06dPp2HDhpbzXn31VUaPHo2/vz8mk4lx48ZlmvH4p7Jly9KzZ086depEyZIlqVy5smVpVm4oV64cPj4++Pn5UbFiRWrWrJmp3d/fn/j4eMvGcWdnZ8aNG8eAAQMsr0l+7733qFSpUrbHvLXnwzAMHB0dM736Ni/17t2bDz/8kICAADIyMqhYsSLz58/nueeeo0KFCvj6+lKlSpW77g3q2bOn5U1tdevWZfr06ZZrq1atmunagQMH0rNnT5ydnaldu3a2Xu0bHBysdakiIiJSYNkYt34N/ADJyMigXbt2TJ8+PVNR8qhISEigePHiljcydejQwbKf4X4LCQnhmWeeoVOnTnkyntxOxUfOaTOh9ZQ76yhv1lPurKO8WU+5s8792nD+wH3D+bFjx/D29qZRo0ZZFh5ms9nyGt6CatasWZjNZsvsRMuWLfNk3Pbt2/P777/f9qYwEREREZHc8EDOfIg8yvTbmZzTb7Wsp9xZR3mznnJnHeXNesqddR6ZmQ8RERERESmYVHyIiIiIiEieUPEhIiIiIiJ5QsWHiIiIiIjkCRUfIiIiIiKSJ/LtSwZF5HZjxozJ7xByXe/eA/I7BBEREXlAaOajADh69CibN2/O1xiCg4Pp1KkTFy9ezNc4REREROTBpeLjITB37lzatGmDv78/ZrOZ/fv3W9rS0tIYP348tWrVumsfkZGR9OzZ877FOHz4cJo1a4atbc4eqSNHjrBt27Y7th88eJDQ0NC79hEbG4ufn5/l86RJk+jcuTPvvfce58+fv2cMXl5exMfHZyve7du3YzabcXd315cxioiIiOSQll094KKioti6dSurV6/G3t6e+Ph4bty4YWmPiYkhKCiIsmXL5mOUkJqaire3N05OTjm67siRIxw6dIjmzZvf1paWlkadOnWoU6dOjvocPHhwjs7PiaZNm9K0aVO6du3KkCFD7ts4IiIiIgWRio8H3IULF3BycsLe3h4AZ2dnS9usWbPYsmULKSkpuLu7ExISgo2NDTExMQQHBxMfH4/JZGL69OkAJCYmEhQUxB9//EGtWrWYPHkyNjY2mcY7dOgQw4cPB6Bx48Zs376dtWvXEhYWxqFDhxg1ahQAPXv25K233sLT05Pg4GAOHjxISkoKrVu3JigoCLg5o9C2bVu2bNlCWloa06ZNo0qVKpaxUlNTmTFjBsnJyezbt4+ePXsSHR3NqVOnOH36NOXLl+eVV15h0aJFzJ8/P1v5io2NZciQISQlJQHw/vvvU69ePSIjI5k1axZOTk5Z3v/nn39+xzgBkpOTGTZsGL/99huVK1cmOTnZ0nan+9+1axcTJkwgPT2d2rVrM2bMGMuf46PEmm8/fZDHKYiUO+sob9ZT7qyjvFlPubPO/cibio8HXOPGjZk9ezatW7emUaNG+Pr60qBBAwBef/11+vTpg2EYDBo0iC1btuDl5cWgQYPo0aMH3t7epKSkkJGRwdmzZzl8+DDr1q2jTJkydOnShX379uHh4ZFpvGHDhjFq1Cjq16/PhAkTshVj//79KVWqFOnp6QQGBvLbb79Ro0YNAJycnFi9ejXLli1j0aJFjB071nKdvb09QUFBmYqamTNnEh0dzRdffEGRIkWIjIzMUb5Kly7Np59+SuHChTl58iQDBgwgLCwM4K73f7c4AZYvX06RIkVYv349v/32G+3bt7/r/VeqVImhQ4eyePFiKlWqxJAhQ/jiiy8IDAzM0f0UBBcuXLvvY7i4OObJOAWRcmcd5c16yp11lDfrKXfWyU7erClOtOfjAVe8eHHCwsIICQnB2dmZ/v37W/4xvXfvXrp27cprr73G/v37OXbsGNevX+fcuXN4e3sDULhwYYoWLQqAm5sbrq6u2NraUqNGDc6cOZNprKtXr3Lt2jXq168PkO09DevXr6ddu3a0bduWo0ePEh0dbWlr1aoVALVr175tvDvx8vKiSJEi2Tr3n9LS0hg5ciT+/v7069cvUyx3u/97xblnzx4CAgIAqFGjBtWrV7e0ZXX/J06coGLFilSqVAmAdu3asXfvXqvuSURERKSg0MzHQ8BkMuHp6YmnpyfVqlUjPDwcPz8/goODCQ8Px8XFhRkzZpCSknLXfv6+5MdkMpGenp6jGDIyMiyfb411+vRpFi1axMqVKylZsiRDhw7NFIednR0Atra22R7vVrFkjcWLF/PYY48RERFBRkYGbm5ulra73b81ccK9719ERERE/o9mPh5wx48f5+TJk5bPR44coXz58iQnJ5ORkYGjoyMJCQl8//33ADg4OODq6srGjRuBm/sqbu1/uJcSJUrg6Oho+Q39mjVrLG0VKlTgt99+syzhOnDgAAAJCQkULVoUR0dH4uLi+PHHH3N0f8WLFychISFb5x44cOCem7yvXbuGi4sLtra2RERE5KiQuJv69euzdu1aAP744w9+//134M73X6lSJc6cOUNMTAwAERERlhklERERkUeVZj4ecImJiYSGhnL16lVMJhNPPvkkISEhlChRgo4dO+Ln58djjz2W6Y1QEydOZNSoUUyfPh07OzvLhvPsGDduHMOHD8fGxobGjRtbjj/33HNUqFABX19fqlSpYnm1b40aNahZsyYvvfQSrq6u1KtXL0f35+npyYIFCzCbzfd8FfCff/55z+VYr776Kn379iU8PJymTZtSrFixHMVzJ126dGHYsGG89NJL2br/woULM27cOPr162fZcN6lS5d7jhMcHKx1qSIiIlJg2RiGYeR3EPJgio2N5Z133rH8xj+/TZgwAbPZbNnMXlCp+Mg5bSa0nnJnHeXNesqddZQ36yl31tGGc3kk/f1LBv/73/8+sIVHaGgoBw8ezO8wRERERB5omvkQecDotzM5p99qWU+5s47yZj3lzjrKm/WUO+to5kNERERERB5qKj5ERERERCRPqPgQEREREZE8oeJDRERERETyhIoPERERERHJE/qSQZEHyJgxY/I7hDvq3XtAfocgIiIiDznNfEi+Onr0KJs3b87zcdPT01m8eDFpaWl5PraIiIjIo0rFh9xXc+fOpU2bNvj7+2M2m9m/f7+lLS0tjfHjx1OrVq279hEZGUnPnj2tjuHvX1R4y+LFiylevDiFClk/+Td06FC+++47q68XERERedRo2ZXcN1FRUWzdupXVq1djb29PfHw8N27csLTHxMQQFBRE2bJl72scderUoU6dOpbPGRkZlC5dmrZt297XcUVEREQkMxUfct9cuHABJycn7O3tAXB2dra0zZo1iy1btpCSkoK7uzshISHY2NgQExNDcHAw8fHxmEwmpk+fDkBiYiJBQUH88ccf1KpVi8mTJ2NjY5NpvAMHDjBixAhsbW15/vnn2b59O2vXriUyMpJFixYxf/58Dhw4wNixY0lJSeHLL7/kww8/pHLlyqSkpDB69GgOHTqEyWRi6NChNGzYMFP/hmHwwQcfsHPnTsqVK4ednZ2lzcvLi5UrV+Ls7MzBgweZOHEiS5cuJSEhgdDQUA4dOgRAnz59aN269X3J9/1mzbeY5qUHPb4HmXJnHeXNesqddZQ36yl31rkfeVPxIfdN48aNmT17Nq1bt6ZRo0b4+vrSoEEDAF5//XX69OmDYRgMGjSILVu24OXlxaBBg+jRowfe3t6kpKSQkZHB2bNnOXz4MOvWraNMmTJ06dKFffv24eHhkWm84cOH88EHH+Du7s7kyZOzjKly5cosW7aMQoUKsX37dqZOncrMmTNZtmwZAGvWrCE6Opru3buzYcMGChcubLn2hx9+4MSJE3z77bfExcXRpk0bOnTocNcczJkzBwcHB9asWQPAlStXrM5nfrtw4Vp+h3BHLi6OD3R8DzLlzjrKm/WUO+sob9ZT7qyTnbxZU5xoz4fcN8WLFycsLIyQkBCcnZ3p378/YWFhAOzdu5euXbvy2muvsX//fo4dO8b169c5d+4c3t7eABQuXJiiRYsC4ObmhqurK7a2ttSoUYMzZ85kGuvq1askJCTg7u4OgJ+fX5YxJSQkMGjQILp06cLs2bM5evQoAPv27SMgIACAKlWqUL58eU6cOJHp2j179tCmTRtMJhNly5a9bWYkK7t27eK1116zfC5ZsuQ9rxEREREpqDTzIfeVyWTC09MTT09PqlWrRnh4OH5+fgQHBxMeHo6LiwszZswgJSXlrv3cWrp1q8/09HSr4pk2bRqenp506dKF06dP061bN6v6+SeTyYRhGAD3vBcRERGRR5VmPuS+OX78OCdPnrR8PnLkCOXLlyc5OZmMjAwcHR1JSEjg+++/B8DBwQFXV1c2btwIQGpqKklJSdkaq0SJEhQvXtzyNq1vv/02y/OuXLli2XuyevVqy3EPDw/L0qgTJ05w9uxZKleunOna+vXrs379etLT0zl//jyRkZGWtgoVKlj2ddy6H4Dnn3/esqTr1vgiIiIijyrNfMh9k5iYSGhoKFevXsVkMvHkk08SEhJCiRIl6NixI35+fjz22GOZ3kQ1ceJERo0axfTp07Gzs7NsOM+OsWPHMnLkSGxtbalfvz4ODg63ndO9e3eGDx/O3Llzad68ueX4q6++yujRo/H398dkMjFu3LhMsy0A3t7e7N69G19fX8qXL0/dunUtbX369GHEiBFMnz4dT09Py/FevXoREhKCn58ftra29OnTh1atWt3xHoKDg7UuVURERAosG+PWWhGRh1xCQgLFixcHYMGCBZw/f56RI0fmc1Q5p+Ij57SZ0HrKnXWUN+spd9ZR3qyn3FlHG85F7mHbtm2YzWb8/PzYu3cvvXv3ztPxz507R1BQUJ6OKSIiIvIw0bIrKTB8fX3x9fXNt/HLli3LjBkz8m18ERERkQedZj5ERERERCRPqPgQEREREZE8oeJDRERERETyhIoPERERERHJEyo+REREREQkT+htVyIPkDFjxtzznN69B+RBJCIiIiK5TzMf8kByd3e/7djy5csJDw+/63VhYWGEhIRk2TZv3rzcCM0qM2fO5JNPPsm38UVEREQeBCo+5KHRpUsX2rZta/X18+fPz71gRERERCTHVHzIQ+PvswcHDhzA398fs9nMhAkT8PPzs5x3/vx5unfvTqtWrZg4cSIAkydPJjk5GbPZzMCBA2/r293dnalTpxIQEMDLL79MXFwcALGxsbzxxhv4+/vTrVs3/vzzT65du8aLL75IRkYGAImJiTRv3pwbN25w6tQpunfvTvv27Xn11VeJjo6+32kREREReWio+JCH0vDhwwkJCSEiIgKTyZSp7ciRI0ybNo01a9awfv16zp49y6BBgyhSpAgRERF89NFHt/WXmJjIs88+yzfffIOHhwcrVqwAIDQ0lHbt2rFmzRr8/f0JDQ3F0dGRGjVq8L///Q+ArVu30qRJE+zs7Hj//fd5//33CQsL47///W+29nCIiIiIPCq04VweOlevXiUhIcGyL8TPz4+tW7da2hs1aoSjoyMAVapU4cyZM5QrV+6ufdrZ2fHiiy8CULt2bXbu3AlAVFQUM2fOBMBsNjNp0iQAfH19+fbbb2nYsCHr1q3j1VdfJSEhgaioKPr162fpNzU1NXdu+m9cXBxzvc+CQHmxnnJnHeXNesqddZQ36yl31rkfeVPxIQWOvb295WeTyUR6evo9r7Gzs8PGxgYAW1vbe17j5eXF1KlTuXz5Mr/++isNGzYkKSmJEiVKEBER8e9u4B4uXLh2X/t/GLm4OCovVlLurKO8WU+5s47yZj3lzjrZyZs1xYmWXclDp0SJEhQvXpz9+/cD8O2332brukKFCnHjxo0cjeXu7s66desAWLNmDR4eHgAUL16c2rVrM3bsWF544QVMJhMODg5UrFiR9evXA2AYBr/99luOxhMREREpyDTzIQ+kpKQkmjVrZvn85ptvZmofO3YsI0eOxNbWlvr16+Pg4HDPPl9++WUCAgKoWbNmlvs+svL+++8zbNgwPvnkE5ydnRk3bpylzdfXl379+rF06VLLsUmTJjF69Gjmzp1LWloavr6+1KhRI1tjiYiIiBR0NoZhGPkdhEhOJSQkULx4cQAWLFjA+fPnGTlyZD5HlTs0NZxzmlK3nnJnHeXNesqddZQ36yl31rlfy6408yEPpW3btjF//nzS09MpX74848ePz++QREREROQeVHzIQ8nX1xdfX9/8DkNEREREckAbzkVEREREJE+o+BARERERkTyh4kNERERERPKEig8REREREckTKj5ERERERCRPqPgQEREREZE8oVftijxAxowZc9f23r0H5FEkIiIiIrlPMx+PmC+//JLjx4//qz5SU1NZsmQJhmHkUlS5Ly0tjQULFnDx4sX8DkVERERE/j8VHwXQpUuXMJvNmM1mGjduTNOmTTGbzbi7u1OkSBE+/vhjrl+/bnX/9vb22Nra8sUXX+Ri1BAbG4ufn1+u9DVr1iyqVKnCtGnTSE9P/9f9zZw5k08++STLtiNHjtC5c2feeecdlixZAkBCQsK/HlNERESkoNGyqwLIycmJiIgI4OY/mosVK0b37t0t7W3btv3XY7z++uuEh4djGAY2Njb/ur/c9t577wHQokWL+z7WM888w5dffpnp2EcffcSoUaPu+9giIiIiDxPNfDwiUlJSGDZsGP7+/rRt25bdu3ffdk5kZCSvv/46vXr1okWLFkyePJlvvvmGjh074u/vz6lTpwDYvHkznTp1YvHixbz55pvExcUBt88O+Pn5ERsb+69j9/LyIj4+HoCDBw/StWtXMjIyaNWqleV4RkYG3t7exMfHEx8fT9++fenQoQMdOnRg3759lviGDRtG165dadGihWWW4p9+/PFH2rVrR0BAAN26dbMcP3bs2G3X/nO2ZtasWVSvXp0KFSr86/sWERERKWg08/GIWLZsGQBr1qwhOjqa7t27s2HDBgoXLpzpvN9++41vv/2WUqVK0aJFCzp16sTKlSv57LPPWLp0KSNGjOC5555jxYoV2NjY8PXXX7Nw4UKGDh2ap/dja2tLQEAA33zzDYGBgfz000/UqFEDZ2dnBg4cSLdu3fDw8ODPP/+ke/furF+/HoATJ06wZMkSrl+/zksvvUSXLl2ws7Oz9BsfH8/777/P559/zuOPP87ly5ctbVld+09FixalT58+mWaacpOLi+N96bcgUG6sp9xZR3mznnJnHeXNesqdde5H3lR8PCL27dvH66+/DkCVKlUoX748J06coEaNGpnOq1OnDmXKlAHgiSeeoHHjxgBUq1aNyMhIAP766y/69+/PhQsXSE1NpWLFinl4J/+nQ4cO9O7dm8DAQFatWkX79u0B+Omnnzh27JjlvOvXr1v2YDRv3hx7e3ucnZ1xdnbm4sWLuLq6Ws795Zdf8PDw4PHHHwegVKlSlrasrs1rFy5cy/MxHwYuLo7KjZWUO+sob9ZT7qyjvFlPubNOdvJmTXGi4kMysbe3t/xsa2tr+Wxra2vZuB0aGkpgYCAtWrQgMjKSWbNmAWAymcjIyLBcn5KSclv/P/zwg+X80NBQ6tSpc8+YTCaT5c1af++zXLlylC5dml27dnHgwAEmT54M3FyCtWLFittmdf55fyaTibS0tHuOf7drCxUqdM97FhEREZGbtOfjEeHh4cGaNWuAm8uHzp49S+XKla3q69q1a5QtWxaA8PBwy/EKFSpw+PBhAH799dcs93t4e3sTERFBREREtgqPW/0eOnQIgO+//z5TW6dOnRg8eDA+Pj6YTCYAmjRpwtKlSy3nHDlyJNv3VrduXfbu3cvp06cBMi27ykrp0qW5ePEily5dIjU1la1bt2Z7LBEREZFHjWY+HhGvvvoqo0ePxt/fH5PJxLhx4zL9Jj8n+vTpQ79+/ShZsiSenp6WIqN169ZERETQpk0b3NzceOqpp3Lc94kTJ2jWrJnl87Bhw+jTpw8jRoxg+vTpeHp6Zjrfy8uLYcOGWZZcAYwYMYKQkBD8/f1JT0/Hw8ODkJCQbI3v7OxMSEgIffv2JSMjg9KlS/Ppp5/e8Xw7OzveffddOnXqRNmyZalSpUoO7ziz4OBgTQ2LiIhIgWVjPMjfFCdyDwcPHmTcuHG5/p0j+UnFR85pPa/1lDvrKG/WU+6so7xZT7mzzv3a86FlV/LQWrBgAUFBQQwYMCDL9urVq+fKq35FREREJHdo2ZU8tHr06EGPHj3u2P7777/nYTQiIiIici+a+RARERERkTyh4kNERERERPKEig8REREREckTKj5ERERERCRPqPgQEREREZE8obddiTxAxowZc9f23r2zfq2wiIiIyMNAMx/yQNq6dSs7duzI7zBEREREJBdp5kOsdunSJQIDAwGIi4vD1tYWZ2dnAL7++mvs7e2t6vfAgQNERUWRnp5O2bJlefrpp3Pcx9y5c/nuu+/4448/eO211xg5cqRVsfwbycnJ9OvXj6SkJCpUqMDYsWOxtVW9LyIiIo8uG8MwjPwOQh5+M2fOpFixYnTv3t1yLC0tjUKF8re+dXd3JyoqKl9jyAktu7KOi4sjFy5cy+8wHkrKnXWUN+spd9ZR3qyn3FknO3lzcXHMcb+a+ZBcNXToUOzt7Tly5Aj16tXDwcEhU1Hi5+fHvHnzWLVqFSVLlrTMnEydOhVnZ2e6devGwoULWb9+PampqXh7exMUFERsbCxvv/02zz33HFFRUZQtW5Y5c+ZQpEiRTOOfPn2aQYMGkZiYiJeXl+V4QkICvXv35urVq6SlpdGvXz9atmxJbGws//nPf6hbty5RUVHUrl2bDh06MGPGDOLj45k8eTJubm6ZxggLC2Pjxo0kJSURExPDW2+9xY0bN4iIiMDe3p4FCxaQlJTE22+/zdq1awE4efIk/fv3Z/Xq1fcx+yIiIiIPNhUfkuvOnTvHl19+iclkYubMmVme06FDB/r27UtgYCAZGRmsW7eOr7/+mh07dhATE8PKlSsxDINevXqxZ88eypUrR0xMDFOmTCE0NJR+/fqxYcMGzGZzpn7Hjh1Lly5daNu2LcuWLbMcL1y4MLNnz8bBwYH4+HheeeUVWrRoAcCpU6eYPn06H374IR07dmTNmjUsX76cTZs2MW/ePObMmXNb/EePHmX16tWWAmnQoEGEh4fz4YcfEh4eTmBgIK6uruzfv59nn32W1atX065du3+dW2t+w/CoUG6sp9xZR3mznnJnHeXNesqdde5H3lR8SK7z8fHBZDLd9ZyKFStSqlQpDh8+TFxcHDVr1sTJyYmdO3eyc+dO2rZtC0BiYiInT56kXLlyVKxYkWeeeQaAWrVqcebMmdv6jYqKshQ8ZrOZyZMnA2AYBlOmTGHPnj3Y2tpy7tw54uLiLLFUr14dgKpVq9KoUSNsbGyoXr16lmMAeHp64uDgAICjo6NllqVatWr8/vvvAHTs2JGwsDDq1KljKa7+LU0bZ01T6tZT7qyjvFlPubOO8mY95c46WnYlD42iRYtafjaZTGRkZFg+p6SkWH7u1KkTYWFhxMXF0aFDB+BmkdCjRw86d+6cqc/Y2NhMG9hNJlOmvv7OxsbmtmNr1qwhPj6esLAw7Ozs8PLyslz/935tbW0tn21sbEhPT89yjH9eY2dnZ/n51jVeXl5MnTqVLVu28Mwzz+Dk5JRlXyIiIiKPCr16R+6rChUqcPjwYQB+/fVXYmNjLW0tW7Zk+/btHDx4kCZNmgDQpEkTVq1aRUJCAnBzCdfFixezPZ67uzvr1q0D4JtvvrEcv3btGqVLl8bOzo7du3ffcUYjN9nb2/PCCy8QHBxM+/bt7/t4IiIiIg86zXzIfdW6dWsiIiJo06YNbm5uPPXUU5Y2e3t7PD09KVGihGWZVpMmTYiOjrbMfBQrVoxJkyZl+xW1I0aMYNCgQSxcuDDThnN/f3969eqFv78/tWvXpnLlyrl3k3fh5+fHunXraNq0abbODw4O1tSwiIiIFFh61a7km4yMDNq1a8f06dMzFSUFyeeff865c+cYOHBgtq9R8ZFzWs9rPeXOOsqb9ZQ76yhv1lPurHO/9nxo2ZXki2PHjuHt7U2jRo2yLDzMZrPlNbwPq6CgIJYvX063bt3yOxQRERGRB4KWXUm+qFq1Kps2bbpje0RERB5Gc3/MmDEjv0MQEREReaBo5kNERERERPKE9nyIiIiIiEie0MyHiIiIiIjkCRUfIiIiIiKSJ1R8iIiIiIhInlDxISIiIiIieULFh4iIiIiI5AkVHyIiIiIikidUfIiIiIiISJ5Q8SHyAPjxxx9p3bo13t7eLFiwIL/DyXdnz56la9eu+Pr60qZNGz777DMALl++zJtvvkmrVq148803uXLlCgCGYRAaGoq3tzf+/v78+uuvlr5Wr15Nq1ataNWqFatXr86X+8kP6enptG3blp49ewJw+vRpOnXqhLe3N++99x6pqakApKam8t577+Ht7U2nTp2IjY219DF//ny8vb1p3bo127dvz5f7yEtXr14lKCgIHx8fXnrpJaKiovTMZdPixYtp06YNfn5+DBgwgJSUFD1zdzBs2DAaNWqEn5+f5VhuPmeHDh3C398fb29vQkNDKShf55ZV3iZMmICPjw/+/v68++67XL161dJ2p2fpTn/f3ul5LQiyyt0tixYtonr16sTHxwN59MwZIpKv0tLSjBYtWhinTp0yUlJSDH9/f+Po0aP5HVa+OnfunHHo0CHDMAzj2rVrRqtWrYyjR48aEyZMMObPn28YhmHMnz/fmDhxomEYhrF161aje/fuRkZGhhEVFWV07NjRMAzDuHTpkuHl5WVcunTJuHz5suHl5WVcvnw5f24qjy1atMgYMGCA0aNHD8MwDCMoKMhYu3atYRiG8f777xvLli0zDMMwPv/8c+P99983DMMw1q5da/Tr188wDMM4evSo4e/vb6SkpBinTp0yWrRoYaSlpeX9jeShIUOGGCtWrDAMwzBSUlKMK1eu6JnLhr/++st48cUXjaSkJMMwbj5rq1at0jN3B//73/+MQ4cOGW3atLEcy83nrEOHDkZUVJSRkZFhdO/e3di6dWse3+H9kVXetm/fbty4ccMwDMOYOHGiJW93epbu9vftnZ7XgiCr3BmGYfz555/GW2+9ZbzwwgvGxYsXDcPIm2dOMx8i+ezAgQM8+eSTPP7449jb29OmTRs2bdqU32HlqzJlylCrVi0AHBwcqFy5MufOnWPTpk20bdsWgLZt27Jx40YAy3EbGxvq1q3L1atXOX/+PDt27KBx48aUKlWKkiVL0rhx4wL729S/++uvv9i6dSsdO3YEbv4ma/fu3bRu3RqAdu3aWZ6xzZs3065dOwBat27Nrl27MAyDTZs20aZNG+zt7Xn88cd58sknOXDgQP7cUB64du0ae/bsseTM3t6eEiVK6JnLpvT0dJKTk0lLSyM5ORkXFxc9c3dQv359SpYsmelYbj1n58+f5/r169StWxcbGxvatm1bYP4+ySpvTZo0oVChQgDUrVuXv/76C+COz9Kd/r69238jC4Kscgcwbtw4Bg8ejI2NjeVYXjxzKj5E8tm5c+dwdXW1fC5btiznzp3Lx4geLLGxsRw5coRnn32WixcvUqZMGQBcXFy4ePEicHsOXV1dOXfu3COb2w8//JDBgwdja3vzP/GXLl2iRIkSlr+kb+UHbuauXLlyABQqVAhHR0cuXbr0yOUuNjYWZ2dnhg0bRtu2bRkxYgSJiYl65rKhbNmyvPXWW7z44os0adIEBwcHatWqpWcuB3LrObvT+Y+CVatW0axZM+DOf6/e6fjd/htZUG3cuJEyZcpQo0aNTMfz4plT8SEiD6yEhASCgoIYPnw4Dg4OmdpsbGwy/bZGbtqyZQvOzs7Url07v0N5qKSlpXH48GG6dOlCeHg4RYsWvW3/lZ65rF25coVNmzaxadMmtm/fTlJS0iMx23O/6DnLublz52IymQgICMjvUB4KSUlJzJ8/n379+uXL+Co+RPJZ2bJlLVPFcPO3DmXLls3HiB4MN27cICgoCH9/f1q1agVA6dKlOX/+PADnz5/H2dkZuD2Hf/31F2XLln0kc/vzzz+zefNmvLy8GDBgALt372bs2LFcvXqVtLQ04P/yAzdzd/bsWeDmP8CvXbuGk5PTI5c7V1dXXF1defbZZwHw8fHh8OHDeuay4aeffqJixYo4OztjZ2dHq1at+Pnnn/XM5UBuPWd3Or8gCwsLY+vWrUyePNlStGU3P7eOOzk53fF5LYhOnTpFbGwsZrMZLy8v/vrrL9q3b8+FCxfy5JlT8SGSz+rUqcPJkyc5ffo0qamprFu3Di8vr/wOK18ZhsGIESOoXLkyb775puW4l5cX4eHhAISHh9OiRYtMxw3D4JdffsHR0ZEyZcrQpEkTduzYwZUrV7hy5Qo7duygSZMm+XFLeWbgwIH8+OOPbN68mSlTptCwYUM++ugjPD092bBhA3DzjSW3njEvLy/LW0s2bNhAw4YNsbGxwcvLi3Xr1pGamsrp06c5efIkbm5u+XZf95uLiwuurq4cP34cgF27dlGlShU9c9lQvnx59u/fT1JSEoZhsGvXLqpWrapnLgdy6zkrU6YMDg4O/PLLLxiGkamvgujHH39k4cKFzJ07l6JFi1qO3+lZutPftzY2Nnd8Xgui6tWrs2vXLjZv3szmzZtxdXUlLCwMFxeXvHnmcmkjvYj8C1u3bjVatWpltGjRwpgzZ05+h5Pv9uzZY1SrVs3w8/MzAgICjICAAGPr1q1GfHy88cYbbxje3t5Gt27djEuXLhmGYRgZGRnG6NGjjRYtWhh+fn7GgQMHLH19/fXXRsuWLY2WLVsaK1euzKc7yh+7d++2vO3q1KlTRocOHYyWLVsaffv2NVJSUgzDMIzk5GSjb9++RsuWLY0OHToYp06dslw/Z84co0WLFkarVq0KzBtz7ubw4cNGu3btDD8/P6NXr17G5cuX9cxl0/Tp043WrVsbbdq0MQYNGmR5y5Ceudv179/faNy4sVGzZk2jadOmxooVK3L1OTtw4IDRpk0bo0WLFsaYMWOMjIyMvL7F+yKrvLVs2dJo1qyZ5e+JW29RM4w7P0t3+vv2Ts9rQZBV7v7uxRdftLztKi+eORvDKCAvgBYRERERkQeall2JiIiIiEieUPEhIiIiIiJ5QsWHiIiIiIjkCRUfIiIiIiKSJ1R8iIiIiIhInlDxISIikg1eXl74+fmRkZGR6dgff/yRa2PExsbi6emZa/1l17Bhw2jTpg3vvffebW1du3alRYsWmM1mfH196du3L9euXftX4+V23kTk4aHiQ0REJJsSExOJiIjI7zDuKT09PdvnxsXFsWHDBtasWcO0adOyPGfkyJFERESwbt06TCYTy5cvz6VIReRRo+JDREQkm/r06cOsWbNITU29re2fv83/+2cvLy+mTp3KK6+8wgsvvMCaNWtYvHgxHTt2xNvbmz179mTqa/z48fj7++Pv78/evXstx7dt20bnzp1p3749r7zyCr/88gsAkZGR+Pv7M2zYMMxmMz/++ONt8YWHh1v6fPfdd7l48SLXr1/njTfeIDk5mXbt2rF48eK73n9aWhrJycmULFkSuFnkTJgwAT8/P/z8/JgwYYKl8ImLi+Pdd9+1jHnrG7z/adGiRXTr1o1r166xceNG/P39MZvN+Pn5ERkZedd4ROThUyi/AxAREXlY1K5dm1q1arF8+XK6deuWo2tTU1P56quvOHDgAG+88QaDBw9m5cqVfPvtt0yZMsUym3D58mVq1KjB0KFDiYyMZMCAAWzcuJG//vqLOXPm8Mknn+Dg4MDRo0d5++232bp1KwDHjh0jJCQEd3f328b+448/mDx5MmFhYZQpU4Zp06bxwQcfMG3aNBYsWECHDh3uOqMTGhrKtGnTOHv2LJUqVaJdu3YAfPXVVxw5coSwsDAA3n77bb766iteffVVQkNDefrpp5k9ezbnz5+nffv21KxZk2rVqgGQkZFBaGgoly5d4uOPP8be3p4ZM2ZY7iE9PZ2kpKQc5VhEHnya+RAREcmB9957j48//piEhIQcXefr6wtArVq1SEpK4qWXXgJuFjSnTp2ynGdnZ0dAQAAAnp6eFClShOPHj7N9+3ZOnTrFa6+9htlsZtCgQaSlpREXFwfAk08+mWXhATdnRpo3b06ZMmUA6Ny5M7t27cp27LeWXe3atYunn36aSZMmAbBr1y7atWuHvb099vb2tG/f3tLvrl276Ny5MwBlypShefPmmWYyhg8fDsDkyZOxt7cHoGHDhowbN46FCxcSHR2Ng4NDtmMUkYeDZj5ERERyoHLlyjRv3pxPP/0003GTyZRpM3pKSkqm9sKFC1vO+/tnW1tb0tLSsjV206ZNmThx4m3Ho6OjKVasWPZvwkomkwlvb+8sY8ip+vXr87///Y/4+HhKly4N3CxIfv/9d3bv3k2/fv148803efnll//1WCLy4NDMh4iISA717duXL774ItPsxxNPPMHBgweBm7/1vzUjkVM3btxgzZo1AOzdu5fk5GQqV65M48aN2b59O0ePHrWce+DAgWz16enpybZt27hw4QIAK1as4Pnnn7cqvsjISJ566ikAGjVqRHh4ODdu3ODGjRuEh4db+m3UqBErVqwA4MKFC2zbto2GDRta+unQoQNvvvkmgYGBnDt3DoDjx49TvXp1unXrRkBAgCWfIlJwaOZDREQkh1xdXTGbzSxatMhyrF+/fgwdOpTPP/+chg0bUr58eav6LlWqFL/99hsLFy4EYMqUKdjb2/PUU08xadIkRowYQXJyMjdu3KBevXq4ubnds89q1aoxaNAg3nrrLQAef/xxQkJCsh3TrT0faWlplCtXjjFjxgDwyiuvcOrUKcsekCZNmlhmKkaOHMmoUaPw9/cHYNCgQTz99NOZ+g0ICKBw4cIEBgby8ccf89FHHxETE4PJZKJEiRKMHTs22zGKyMPBxjAMI7+DEBERERGRgk/LrkREREREJE+o+BARERERkTyh4kNERERERPKEig8REREREckTKj5ERERERCRPqPgQEREREZE8oeJDRERERETyxP8D7A3SDhJ93+AAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(10,10))\n",
    "\n",
    "ax=eda_df.groupby('category').quantity.mean().sort_values(ascending=True).plot(kind='barh', color='gray')\n",
    "\n",
    "plt.xlabel('Number of Books')\n",
    "plt.ylabel('Category')\n",
    "plt.title('The Sum Quantity of Categories')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b2e110e7",
   "metadata": {
    "papermill": {
     "duration": 0.023625,
     "end_time": "2022-12-12T14:40:07.071772",
     "exception": false,
     "start_time": "2022-12-12T14:40:07.048147",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Rating per Category"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "dccc0ee1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:07.121286Z",
     "iopub.status.busy": "2022-12-12T14:40:07.120860Z",
     "iopub.status.idle": "2022-12-12T14:40:07.631044Z",
     "shell.execute_reply": "2022-12-12T14:40:07.629804Z"
    },
    "papermill": {
     "duration": 0.538767,
     "end_time": "2022-12-12T14:40:07.634167",
     "exception": false,
     "start_time": "2022-12-12T14:40:07.095400",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(10,10))\n",
    "\n",
    "ax=eda_df.groupby('category').avg_rating.mean().sort_values(ascending=True).plot(kind='barh', color='gray')\n",
    "\n",
    "plt.xlabel('Avg. Rating')\n",
    "plt.ylabel('Category')\n",
    "plt.title('Avg, Rating of Categories')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0c232fe5",
   "metadata": {
    "papermill": {
     "duration": 0.024837,
     "end_time": "2022-12-12T14:40:07.684373",
     "exception": false,
     "start_time": "2022-12-12T14:40:07.659536",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "All of categories have the mean of average rating larger than 4.0."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ab3ef61",
   "metadata": {
    "papermill": {
     "duration": 0.025125,
     "end_time": "2022-12-12T14:40:07.734946",
     "exception": false,
     "start_time": "2022-12-12T14:40:07.709821",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## 4.2 EDA"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7837f791",
   "metadata": {
    "papermill": {
     "duration": 0.024458,
     "end_time": "2022-12-12T14:40:07.785163",
     "exception": false,
     "start_time": "2022-12-12T14:40:07.760705",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### The more pages, the more expensive?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "bf3a267a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:07.836638Z",
     "iopub.status.busy": "2022-12-12T14:40:07.836227Z",
     "iopub.status.idle": "2022-12-12T14:40:08.037930Z",
     "shell.execute_reply": "2022-12-12T14:40:08.036705Z"
    },
    "papermill": {
     "duration": 0.230616,
     "end_time": "2022-12-12T14:40:08.040688",
     "exception": false,
     "start_time": "2022-12-12T14:40:07.810072",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.subplots(figsize=(10, 7))\n",
    "\n",
    "ax=sns.scatterplot(data=eda_df, x='pages', y='current_price')#, color=\"\",color_continuous_scale='RdBu_r')\n",
    "\n",
    "plt.xlabel('Number of Pages')\n",
    "plt.ylabel('Price')\n",
    "plt.title('Scatter of Pages and Price')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c2dc39e",
   "metadata": {
    "papermill": {
     "duration": 0.025255,
     "end_time": "2022-12-12T14:40:08.092056",
     "exception": false,
     "start_time": "2022-12-12T14:40:08.066801",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "There are some books with lartger pages and low price, and vice versa."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37f911e2",
   "metadata": {
    "papermill": {
     "duration": 0.025551,
     "end_time": "2022-12-12T14:40:08.143485",
     "exception": false,
     "start_time": "2022-12-12T14:40:08.117934",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### What is the largest authors?"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e8bb7f0",
   "metadata": {
    "papermill": {
     "duration": 0.025171,
     "end_time": "2022-12-12T14:40:08.194356",
     "exception": false,
     "start_time": "2022-12-12T14:40:08.169185",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "The assumption is that the author always in top 5 of:\n",
    "* Quantity\n",
    "* Number of Reviews\n",
    "* Average Rating"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "9cbfc409",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:08.247967Z",
     "iopub.status.busy": "2022-12-12T14:40:08.246806Z",
     "iopub.status.idle": "2022-12-12T14:40:08.252563Z",
     "shell.execute_reply": "2022-12-12T14:40:08.251650Z"
    },
    "papermill": {
     "duration": 0.035149,
     "end_time": "2022-12-12T14:40:08.254982",
     "exception": false,
     "start_time": "2022-12-12T14:40:08.219833",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def sort_authors_by_col(col):\n",
    "    res = eda_df.groupby('authors')[col]\\\n",
    "        .mean()\\\n",
    "        .sort_values(ascending=False)\\\n",
    "        .index.tolist()\n",
    "    \n",
    "    return res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "a5bab589",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:08.313922Z",
     "iopub.status.busy": "2022-12-12T14:40:08.313076Z",
     "iopub.status.idle": "2022-12-12T14:40:08.326528Z",
     "shell.execute_reply": "2022-12-12T14:40:08.325211Z"
    },
    "papermill": {
     "duration": 0.043913,
     "end_time": "2022-12-12T14:40:08.329315",
     "exception": false,
     "start_time": "2022-12-12T14:40:08.285402",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "quantity_lst = sort_authors_by_col(\"quantity\")\n",
    "n_reviews_lst = sort_authors_by_col(\"n_review\")\n",
    "avg_rating_lst = sort_authors_by_col(\"avg_rating\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "14279858",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:08.383924Z",
     "iopub.status.busy": "2022-12-12T14:40:08.382649Z",
     "iopub.status.idle": "2022-12-12T14:40:08.391550Z",
     "shell.execute_reply": "2022-12-12T14:40:08.390624Z"
    },
    "papermill": {
     "duration": 0.03895,
     "end_time": "2022-12-12T14:40:08.393911",
     "exception": false,
     "start_time": "2022-12-12T14:40:08.354961",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Thái Phạm', 'GEORGE SAMUEL CLASON', 'Jack Canfield & DD.Watkins']"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def top_k_common_elements(list1, list2, list3, k=10):\n",
    "    list1, list2, list3 = list1[:k], list2[:k], list3[:k]\n",
    "    return list(set(list1) & set(list2) & set(list3))\n",
    "        \n",
    "result = top_k_common_elements(quantity_lst, n_reviews_lst, avg_rating_lst, 100)\n",
    "result"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "460b0945",
   "metadata": {
    "papermill": {
     "duration": 0.026125,
     "end_time": "2022-12-12T14:40:08.446675",
     "exception": false,
     "start_time": "2022-12-12T14:40:08.420550",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "In the top 100 of the defined-assumption, we found three authors:\n",
    "* Jack Canfield & DD.Watkins\n",
    "* GEORGE SAMUEL CLASON\n",
    "* Thái Phạm\n",
    "\n",
    "Let see these book(s)!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "09dc177a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:08.501348Z",
     "iopub.status.busy": "2022-12-12T14:40:08.500316Z",
     "iopub.status.idle": "2022-12-12T14:40:08.520681Z",
     "shell.execute_reply": "2022-12-12T14:40:08.519704Z"
    },
    "papermill": {
     "duration": 0.050598,
     "end_time": "2022-12-12T14:40:08.523030",
     "exception": false,
     "start_time": "2022-12-12T14:40:08.472432",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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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>title</th>\n",
       "      <th>original_price</th>\n",
       "      <th>current_price</th>\n",
       "      <th>quantity</th>\n",
       "      <th>category</th>\n",
       "      <th>n_review</th>\n",
       "      <th>avg_rating</th>\n",
       "      <th>pages</th>\n",
       "      <th>manufacturer</th>\n",
       "      <th>discount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Người Nam Châm (Tái Bản 2019)</td>\n",
       "      <td>2.74</td>\n",
       "      <td>1.94</td>\n",
       "      <td>14075</td>\n",
       "      <td>Sách kỹ năng làm việc</td>\n",
       "      <td>1774</td>\n",
       "      <td>5.0</td>\n",
       "      <td>194</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>0.29</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           title  original_price  current_price  quantity  \\\n",
       "0  Người Nam Châm (Tái Bản 2019)            2.74           1.94     14075   \n",
       "\n",
       "                category  n_review  avg_rating  pages manufacturer  discount  \n",
       "0  Sách kỹ năng làm việc      1774         5.0    194      Unknown      0.29  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Jack Canfield & DD.Watkins\n",
    "eda_df.query('authors == \"Jack Canfield & DD.Watkins\"')\\\n",
    "        .sort_values(by='quantity', ascending=False)\\\n",
    "        .reset_index(drop=True)\\\n",
    "        .drop(['authors'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "b79d8a6b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:08.578518Z",
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     "shell.execute_reply": "2022-12-12T14:40:08.597621Z"
    },
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     "duration": 0.05209,
     "end_time": "2022-12-12T14:40:08.601817",
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     "status": "completed"
    },
    "tags": []
   },
   "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>title</th>\n",
       "      <th>original_price</th>\n",
       "      <th>current_price</th>\n",
       "      <th>quantity</th>\n",
       "      <th>category</th>\n",
       "      <th>n_review</th>\n",
       "      <th>avg_rating</th>\n",
       "      <th>pages</th>\n",
       "      <th>manufacturer</th>\n",
       "      <th>discount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Thiết Kế Cuộc Đời Thịnh Vượng - Design a Prosp...</td>\n",
       "      <td>12.62</td>\n",
       "      <td>12.62</td>\n",
       "      <td>15571</td>\n",
       "      <td>Others</td>\n",
       "      <td>2808</td>\n",
       "      <td>5.0</td>\n",
       "      <td>352</td>\n",
       "      <td>Nhà Xuất Bản Thế Giới</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>101 Lời Khuyên Tài Chính Cá Nhân Từ Thái Phạm</td>\n",
       "      <td>12.62</td>\n",
       "      <td>12.62</td>\n",
       "      <td>381</td>\n",
       "      <td>Sách tài chính, tiền tệ</td>\n",
       "      <td>52</td>\n",
       "      <td>5.0</td>\n",
       "      <td>408</td>\n",
       "      <td>Nhà Xuất Bản Thế Giới</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
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       "                                               title  original_price  \\\n",
       "0  Thiết Kế Cuộc Đời Thịnh Vượng - Design a Prosp...           12.62   \n",
       "1      101 Lời Khuyên Tài Chính Cá Nhân Từ Thái Phạm           12.62   \n",
       "\n",
       "   current_price  quantity                 category  n_review  avg_rating  \\\n",
       "0          12.62     15571                   Others      2808         5.0   \n",
       "1          12.62       381  Sách tài chính, tiền tệ        52         5.0   \n",
       "\n",
       "   pages           manufacturer  discount  \n",
       "0    352  Nhà Xuất Bản Thế Giới       0.0  \n",
       "1    408  Nhà Xuất Bản Thế Giới       0.0  "
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Thái Phạm\n",
    "eda_df.query('authors == \"Thái Phạm\"')\\\n",
    "        .sort_values(by='quantity', ascending=False)\\\n",
    "        .reset_index(drop=True)\\\n",
    "        .drop(['authors'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "896f8e42",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:08.660516Z",
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     "iopub.status.idle": "2022-12-12T14:40:08.682022Z",
     "shell.execute_reply": "2022-12-12T14:40:08.680711Z"
    },
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     "duration": 0.053982,
     "end_time": "2022-12-12T14:40:08.684612",
     "exception": false,
     "start_time": "2022-12-12T14:40:08.630630",
     "status": "completed"
    },
    "tags": []
   },
   "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>title</th>\n",
       "      <th>original_price</th>\n",
       "      <th>current_price</th>\n",
       "      <th>quantity</th>\n",
       "      <th>category</th>\n",
       "      <th>n_review</th>\n",
       "      <th>avg_rating</th>\n",
       "      <th>pages</th>\n",
       "      <th>manufacturer</th>\n",
       "      <th>discount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Người Giàu Có Nhất Thành Babylon (Tái Bản 2020)</td>\n",
       "      <td>4.14</td>\n",
       "      <td>2.73</td>\n",
       "      <td>12729</td>\n",
       "      <td>Bài học kinh doanh</td>\n",
       "      <td>2134</td>\n",
       "      <td>5.0</td>\n",
       "      <td>216</td>\n",
       "      <td>Nhà Xuất Bản Tổng hợp TP.HCM</td>\n",
       "      <td>0.34</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                             title  original_price  \\\n",
       "0  Người Giàu Có Nhất Thành Babylon (Tái Bản 2020)            4.14   \n",
       "\n",
       "   current_price  quantity            category  n_review  avg_rating  pages  \\\n",
       "0           2.73     12729  Bài học kinh doanh      2134         5.0    216   \n",
       "\n",
       "                   manufacturer  discount  \n",
       "0  Nhà Xuất Bản Tổng hợp TP.HCM      0.34  "
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# GEORGE SAMUEL CLASON\n",
    "eda_df.query('authors == \"GEORGE SAMUEL CLASON\"')\\\n",
    "        .sort_values(by='quantity', ascending=False)\\\n",
    "        .reset_index(drop=True)\\\n",
    "        .drop(['authors'], axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "807ef13a",
   "metadata": {
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     "duration": 0.026856,
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     "exception": false,
     "start_time": "2022-12-12T14:40:08.712388",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### What is the best seller book?\n",
    "The assumsion is that the book always in top 5 of:\n",
    "* Quantity\n",
    "* Number of Reviews\n",
    "* Average Rating"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "93197710",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:08.795835Z",
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def sort_title_by_col(col):\n",
    "    # I used a trick here, because we group by title (without duplicated value).\n",
    "    # The aim is to map with title against.\n",
    "    res = eda_df.groupby(\"title\")[col].max()\\\n",
    "        .sort_values(ascending=False)\\\n",
    "        .index.tolist()\n",
    "    \n",
    "    return res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "11f0c185",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:08.858212Z",
     "iopub.status.busy": "2022-12-12T14:40:08.856958Z",
     "iopub.status.idle": "2022-12-12T14:40:08.877023Z",
     "shell.execute_reply": "2022-12-12T14:40:08.875934Z"
    },
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     "start_time": "2022-12-12T14:40:08.829390",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "quantity_lst = sort_title_by_col(\"quantity\")\n",
    "n_reviews_lst = sort_title_by_col(\"n_review\")\n",
    "avg_rating_lst = sort_title_by_col(\"avg_rating\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "d0812aa6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:08.934037Z",
     "iopub.status.busy": "2022-12-12T14:40:08.933586Z",
     "iopub.status.idle": "2022-12-12T14:40:08.943444Z",
     "shell.execute_reply": "2022-12-12T14:40:08.942138Z"
    },
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     "duration": 0.039907,
     "end_time": "2022-12-12T14:40:08.945832",
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Giải Thích Ngữ Pháp Tiếng Anh (Với Bài Tập Và Đáp Án) (Tái Bản)',\n",
       " 'Muôn Kiếp Nhân Sinh 2',\n",
       " 'Làm Bạn Với Bầu Trời (Bìa Mềm) (Tặng Kèm Khung Ảnh Số Lượng Có Hạn)',\n",
       " 'Muôn Kiếp Nhân Sinh (Bìa Cứng)',\n",
       " 'Không Sợ Chậm Chỉ Sợ Dừng\\xa0',\n",
       " 'Từ Tốt Đến Vĩ Đại (Tái bản 2021)']"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def top_k_common_elements(list1, list2, list3, k=10):\n",
    "    list1, list2, list3 = list1[:k], list2[:k], list3[:k]\n",
    "    return list(set(list1) & set(list2) & set(list3))\n",
    "        \n",
    "result = top_k_common_elements(quantity_lst, n_reviews_lst, avg_rating_lst, 200)\n",
    "result"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a62d9fb8",
   "metadata": {
    "papermill": {
     "duration": 0.025929,
     "end_time": "2022-12-12T14:40:08.998250",
     "exception": false,
     "start_time": "2022-12-12T14:40:08.972321",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "In the top 200 of the defined-assumption, we found some titles. Let see these book(s)!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "6a7e7117",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-12T14:40:09.053029Z",
     "iopub.status.busy": "2022-12-12T14:40:09.052200Z",
     "iopub.status.idle": "2022-12-12T14:40:09.073070Z",
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     "start_time": "2022-12-12T14:40:09.024566",
     "status": "completed"
    },
    "tags": []
   },
   "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",
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       "    }\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>title</th>\n",
       "      <th>authors</th>\n",
       "      <th>original_price</th>\n",
       "      <th>current_price</th>\n",
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       "      <th>category</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Giải Thích Ngữ Pháp Tiếng Anh (Với Bài Tập Và ...</td>\n",
       "      <td>Mai Lan Hương</td>\n",
       "      <td>9.28</td>\n",
       "      <td>6.41</td>\n",
       "      <td>5616</td>\n",
       "      <td>Sách Học Tiếng Anh</td>\n",
       "      <td>1014</td>\n",
       "      <td>5.0</td>\n",
       "      <td>560</td>\n",
       "      <td>Nhà Xuất Bản Đà Nẵng</td>\n",
       "      <td>0.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Không Sợ Chậm Chỉ Sợ Dừng</td>\n",
       "      <td>Vãn Tình</td>\n",
       "      <td>5.44</td>\n",
       "      <td>3.50</td>\n",
       "      <td>13655</td>\n",
       "      <td>Sách nghệ thuật sống đẹp</td>\n",
       "      <td>2802</td>\n",
       "      <td>5.0</td>\n",
       "      <td>364</td>\n",
       "      <td>Nhà Xuất Bản Thế Giới</td>\n",
       "      <td>0.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Từ Tốt Đến Vĩ Đại (Tái bản 2021)</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>5.49</td>\n",
       "      <td>3.96</td>\n",
       "      <td>8235</td>\n",
       "      <td>Sách kinh tế học</td>\n",
       "      <td>1119</td>\n",
       "      <td>5.0</td>\n",
       "      <td>484</td>\n",
       "      <td>NXB Trẻ</td>\n",
       "      <td>0.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Muôn Kiếp Nhân Sinh (Bìa Cứng)</td>\n",
       "      <td>Nguyên Phong</td>\n",
       "      <td>9.62</td>\n",
       "      <td>6.35</td>\n",
       "      <td>7391</td>\n",
       "      <td>Others</td>\n",
       "      <td>1421</td>\n",
       "      <td>5.0</td>\n",
       "      <td>424</td>\n",
       "      <td>Nhà Xuất Bản Tổng hợp TP.HCM</td>\n",
       "      <td>0.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Làm Bạn Với Bầu Trời (Bìa Mềm) (Tặng Kèm Khung...</td>\n",
       "      <td>Nguyễn Nhật Ánh</td>\n",
       "      <td>4.64</td>\n",
       "      <td>3.16</td>\n",
       "      <td>26282</td>\n",
       "      <td>Truyện dài</td>\n",
       "      <td>2043</td>\n",
       "      <td>5.0</td>\n",
       "      <td>220</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>0.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Muôn Kiếp Nhân Sinh 2</td>\n",
       "      <td>Nguyên Phong</td>\n",
       "      <td>11.31</td>\n",
       "      <td>7.46</td>\n",
       "      <td>23606</td>\n",
       "      <td>Others</td>\n",
       "      <td>5447</td>\n",
       "      <td>5.0</td>\n",
       "      <td>540</td>\n",
       "      <td>Nhà Xuất Bản Tổng hợp TP.HCM</td>\n",
       "      <td>0.34</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               title          authors  \\\n",
       "0  Giải Thích Ngữ Pháp Tiếng Anh (Với Bài Tập Và ...    Mai Lan Hương   \n",
       "1                         Không Sợ Chậm Chỉ Sợ Dừng          Vãn Tình   \n",
       "2                   Từ Tốt Đến Vĩ Đại (Tái bản 2021)          Unknown   \n",
       "3                     Muôn Kiếp Nhân Sinh (Bìa Cứng)     Nguyên Phong   \n",
       "4  Làm Bạn Với Bầu Trời (Bìa Mềm) (Tặng Kèm Khung...  Nguyễn Nhật Ánh   \n",
       "5                              Muôn Kiếp Nhân Sinh 2     Nguyên Phong   \n",
       "\n",
       "   original_price  current_price  quantity                  category  \\\n",
       "0            9.28           6.41      5616        Sách Học Tiếng Anh   \n",
       "1            5.44           3.50     13655  Sách nghệ thuật sống đẹp   \n",
       "2            5.49           3.96      8235          Sách kinh tế học   \n",
       "3            9.62           6.35      7391                    Others   \n",
       "4            4.64           3.16     26282                Truyện dài   \n",
       "5           11.31           7.46     23606                    Others   \n",
       "\n",
       "   n_review  avg_rating  pages                  manufacturer  discount  \n",
       "0      1014         5.0    560          Nhà Xuất Bản Đà Nẵng      0.31  \n",
       "1      2802         5.0    364         Nhà Xuất Bản Thế Giới      0.36  \n",
       "2      1119         5.0    484                       NXB Trẻ      0.28  \n",
       "3      1421         5.0    424  Nhà Xuất Bản Tổng hợp TP.HCM      0.34  \n",
       "4      2043         5.0    220                       Unknown      0.32  \n",
       "5      5447         5.0    540  Nhà Xuất Bản Tổng hợp TP.HCM      0.34  "
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eda_df.loc[eda_df.title.isin(result)].reset_index(drop=True)"
   ]
  }
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