Project.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Amazon reviews\n",
    "\n",
    "> To get a better notebook formatting, [click here](https://nbviewer.jupyter.org/github/Coac/epfl-ada/blob/master/Project/Project.ipynb).\n",
    "\n",
    "> Check out the data story [here](https://adamazon.github.io/).\n",
    "\n",
    "> Please also check the [readme](https://github.com/Coac/epfl-ada/blob/master/Project/README.md) containing additional explanations.\n",
    "\n",
    "This notebook contains an exploratory analysis of one specific category of products of the Amazon reviews. Our objective is to be able to understand how reviews are distributed and find some useful insights to provide a deeper analysis to answer our research questions.\n",
    "\n",
    "## Summary\n",
    "\n",
    "1. [Data importation](#Data-importation)\n",
    "2. [Descriptive analysis](#Descriptive-analysis)\n",
    "3. [Correlations](#Correlations)\n",
    "4. [Words occurences](#Words-occurences)\n",
    "5. [Machine learning exploratory](#Machine-learning-exploratory)\n",
    "6. [Deeper analysis](#Deeper-analysis)\n",
    "\n",
    "   a. [Regression model](#Regression-model)  \n",
    "   b. [Classification](#Classification)    \n",
    "   \n",
    "7. [Conclusion](#Conclusion)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 309,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import warnings\n",
    "from datetime import datetime\n",
    "from matplotlib import pyplot as plt\n",
    "import math as math\n",
    "\n",
    "import pickle\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "sns.set()\n",
    "sns.set_context(\"poster\")\n",
    "from operator import itemgetter\n",
    "\n",
    "from functions.py import * \n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.pipeline import FeatureUnion\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn.linear_model import SGDClassifier\n",
    "from sklearn.metrics import classification_report\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
    "from sklearn.feature_extraction import DictVectorizer\n",
    "from sklearn.cross_validation import train_test_split\n",
    "from sklearn.decomposition import TruncatedSVD\n",
    "from sklearn.ensemble import GradientBoostingClassifier\n",
    "\n",
    "from sklearn import datasets\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.metrics import classification_report\n",
    "from sklearn.svm import SVC\n",
    "\n",
    "import string\n",
    "\n",
    "from nltk.corpus import stopwords as sw\n",
    "from nltk.corpus import wordnet as wn\n",
    "from nltk import wordpunct_tokenize\n",
    "from nltk import WordNetLemmatizer\n",
    "from nltk import sent_tokenize\n",
    "from nltk import pos_tag\n",
    "\n",
    "from sklearn.base import BaseEstimator, TransformerMixin"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data importation\n",
    "\n",
    "We first start by importing data. Because we focus on one specific category (*video games*), we won't need to use Spark here.\n",
    "\n",
    "### Download the data\n",
    "\n",
    "We will use the 5-core reviews which can be downloaded here: http://jmcauley.ucsd.edu/data/amazon/links.html. The exact file used for video games import is http://snap.stanford.edu/data/amazon/productGraph/categoryFiles/reviews_Video_Games_5.json.gz.\n",
    "\n",
    "### File preparation\n",
    "\n",
    "After downloading the file, we turn it to a valid, json array to ease importation. We use the following sed commands to do so:\n",
    "\n",
    "```sh\n",
    "sed -i '1s/^/[/' data/file.json # Starts JSON array\n",
    "sed -i 's/$/,/' data/file.json # Separate objects with commas\n",
    "sed -i '$ s/,$/]/g' data/file.json # Ends JSON array\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pandas importation\n",
    "\n",
    "#### Load products reviews\n",
    "\n",
    "\n",
    "We import data and start by doing some simple cleaning. Dates are stored in two different formats (`reviewTime` and `unixReviewTime`). We will use the latest one to create a new `date` field with standard DateTime format, which will be easier to handle.\n",
    "\n",
    "We create a two-level index to allow grouping reviews per product and reviewer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "helpful                 object\n",
       "overall                  int64\n",
       "reviewText              object\n",
       "reviewerName            object\n",
       "summary                 object\n",
       "date            datetime64[ns]\n",
       "dtype: object"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "video_games = pd.read_json('./data/video-games.json')\n",
    "\n",
    "# Cleaning dates\n",
    "del video_games['reviewTime'] # Duplicated information (already in unix review time)\n",
    "video_games['date'] = pd.to_datetime(video_games['unixReviewTime'], unit='s')\n",
    "del video_games['unixReviewTime']\n",
    "\n",
    "video_games.set_index(['asin', 'reviewerID'], inplace=True)\n",
    "\n",
    "assert video_games.index.is_unique, 'There should be no more than one review per person per product'\n",
    "\n",
    "video_games.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see data types are already guessed by Pandas. We need, however, to reformat the `helpful` field. It is currently stored as an array of two values, the first one describing how many users voted the review was helpful and the second one describing how many votes the review received."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data formatting\n",
    "\n",
    "To ease data handling, we will calculate the `helpfulRate` of each comment. It will help us extracting which reviewers are providing the best reviews on one or multiple products. When a review does not have any helpful votes, the rate will be set to `-1`.\n",
    "\n",
    "We also store the number of total reviews in a new row so we can take rid of the helpful array."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>overall</th>\n",
       "      <th>reviewText</th>\n",
       "      <th>reviewerName</th>\n",
       "      <th>summary</th>\n",
       "      <th>date</th>\n",
       "      <th>helpfulRate</th>\n",
       "      <th>helpfulCount</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>asin</th>\n",
       "      <th>reviewerID</th>\n",
       "      <th></th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">0700099867</th>\n",
       "      <th>A2HD75EMZR8QLN</th>\n",
       "      <td>1</td>\n",
       "      <td>Installing the game was a struggle (because of...</td>\n",
       "      <td>123</td>\n",
       "      <td>Pay to unlock content? I don't think so.</td>\n",
       "      <td>2012-07-09</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A3UR8NLLY1ZHCX</th>\n",
       "      <td>4</td>\n",
       "      <td>If you like rally cars get this game you will ...</td>\n",
       "      <td>Alejandro Henao \"Electronic Junky\"</td>\n",
       "      <td>Good rally game</td>\n",
       "      <td>2013-06-30</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A1INA0F5CWW3J4</th>\n",
       "      <td>1</td>\n",
       "      <td>1st shipment received a book instead of the ga...</td>\n",
       "      <td>Amazon Shopper \"Mr.Repsol\"</td>\n",
       "      <td>Wrong key</td>\n",
       "      <td>2014-06-28</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A1DLMTOTHQ4AST</th>\n",
       "      <td>3</td>\n",
       "      <td>I got this version instead of the PS3 version,...</td>\n",
       "      <td>ampgreen</td>\n",
       "      <td>awesome game, if it did not crash frequently !!</td>\n",
       "      <td>2011-09-14</td>\n",
       "      <td>0.700000</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A361M14PU2GUEG</th>\n",
       "      <td>4</td>\n",
       "      <td>I had Dirt 2 on Xbox 360 and it was an okay ga...</td>\n",
       "      <td>Angry Ryan \"Ryan A. Forrest\"</td>\n",
       "      <td>DIRT 3</td>\n",
       "      <td>2011-06-14</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           overall  \\\n",
       "asin       reviewerID                \n",
       "0700099867 A2HD75EMZR8QLN        1   \n",
       "           A3UR8NLLY1ZHCX        4   \n",
       "           A1INA0F5CWW3J4        1   \n",
       "           A1DLMTOTHQ4AST        3   \n",
       "           A361M14PU2GUEG        4   \n",
       "\n",
       "                                                                  reviewText  \\\n",
       "asin       reviewerID                                                          \n",
       "0700099867 A2HD75EMZR8QLN  Installing the game was a struggle (because of...   \n",
       "           A3UR8NLLY1ZHCX  If you like rally cars get this game you will ...   \n",
       "           A1INA0F5CWW3J4  1st shipment received a book instead of the ga...   \n",
       "           A1DLMTOTHQ4AST  I got this version instead of the PS3 version,...   \n",
       "           A361M14PU2GUEG  I had Dirt 2 on Xbox 360 and it was an okay ga...   \n",
       "\n",
       "                                                 reviewerName  \\\n",
       "asin       reviewerID                                           \n",
       "0700099867 A2HD75EMZR8QLN                                 123   \n",
       "           A3UR8NLLY1ZHCX  Alejandro Henao \"Electronic Junky\"   \n",
       "           A1INA0F5CWW3J4          Amazon Shopper \"Mr.Repsol\"   \n",
       "           A1DLMTOTHQ4AST                            ampgreen   \n",
       "           A361M14PU2GUEG        Angry Ryan \"Ryan A. Forrest\"   \n",
       "\n",
       "                                                                   summary  \\\n",
       "asin       reviewerID                                                        \n",
       "0700099867 A2HD75EMZR8QLN         Pay to unlock content? I don't think so.   \n",
       "           A3UR8NLLY1ZHCX                                  Good rally game   \n",
       "           A1INA0F5CWW3J4                                        Wrong key   \n",
       "           A1DLMTOTHQ4AST  awesome game, if it did not crash frequently !!   \n",
       "           A361M14PU2GUEG                                           DIRT 3   \n",
       "\n",
       "                                date  helpfulRate  helpfulCount  \n",
       "asin       reviewerID                                            \n",
       "0700099867 A2HD75EMZR8QLN 2012-07-09     0.666667            12  \n",
       "           A3UR8NLLY1ZHCX 2013-06-30    -1.000000             0  \n",
       "           A1INA0F5CWW3J4 2014-06-28    -1.000000             0  \n",
       "           A1DLMTOTHQ4AST 2011-09-14     0.700000            10  \n",
       "           A361M14PU2GUEG 2011-06-14     1.000000             2  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def helpful_rate(row):\n",
    "    '''\n",
    "    Calculates the helpful rate of a review by determining what\n",
    "    percentage of the votes described the review as \"helpful\".\n",
    "    '''\n",
    "    was_helpful = row.helpful[0]\n",
    "    total_evaluations = row.helpful[1]\n",
    "    \n",
    "    if total_evaluations == 0:\n",
    "        return -1\n",
    "    \n",
    "    return was_helpful/total_evaluations\n",
    "\n",
    "def helpful_count(row):\n",
    "    '''\n",
    "    Gets the total number of helpful votes for a review\n",
    "    '''\n",
    "    return row.helpful[1]\n",
    "\n",
    "video_games['helpfulRate'] = video_games.apply(helpful_rate, axis=1)\n",
    "video_games['helpfulCount'] = video_games.apply(helpful_count, axis=1)\n",
    "del video_games['helpful']\n",
    "\n",
    "assert len(video_games[video_games['helpfulCount'] == 0]) == len(video_games[video_games['helpfulRate'] == -1])\n",
    "\n",
    "video_games.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here is a first view of the data. All the reviews are grouped by product described by its product ID (`asin`). Then, for each product, all the reviews are indexed by the reviewer.\n",
    "\n",
    "Each column of the dataframe is self-descriptive (notice that `overall` is the grade given from the reviewer in a scale between 1 and 5) and data types are allowing us to perform our analysis.\n",
    "\n",
    "#### Load products reviews\n",
    "\n",
    "We now load *video games* metadata. The exact file used here is: http://snap.stanford.edu/data/amazon/productGraph/categoryFiles/meta_Video_Games.json.gz. We had some trouble importing the file, so we had to make some transformations in addition to the `sed` ones, because strings were surrounded by simple quotes instead of double quotes. Here is the Python script we used:\n",
    "\n",
    "```python\n",
    "import ast\n",
    "import json\n",
    "\n",
    "with open('./data/video-games.meta.json', 'r') as metadata:\n",
    "    raw_data = metadata.read().replace('\\n', '')\n",
    "    parsed_data = ast.literal_eval(raw_data)\n",
    "\n",
    "with open('./data/video-games.meta.parsed.json', 'w') as parsed:\n",
    "    json.dump(parsed_data, parsed)\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>brand</th>\n",
       "      <th>description</th>\n",
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       "      <th>salesRank</th>\n",
       "      <th>title</th>\n",
       "    </tr>\n",
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       "      <th>asin</th>\n",
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       "      <th>0078764343</th>\n",
       "      <td></td>\n",
       "      <td>Brand new sealed!</td>\n",
       "      <td>37.98</td>\n",
       "      <td>{'Video Games': 28655}</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>043933702X</th>\n",
       "      <td></td>\n",
       "      <td>In Stock NOW.  Eligible for FREE Super Saving ...</td>\n",
       "      <td>23.50</td>\n",
       "      <td>{'Video Games': 44080}</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0439339987</th>\n",
       "      <td></td>\n",
       "      <td>Grandma Groupers kelp seeds are missing and wi...</td>\n",
       "      <td>8.95</td>\n",
       "      <td>{'Video Games': 49836}</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0439342260</th>\n",
       "      <td></td>\n",
       "      <td>This software is BRAND NEW. Packaging may diff...</td>\n",
       "      <td>-1.00</td>\n",
       "      <td>{'Video Games': 49156}</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0439339960</th>\n",
       "      <td></td>\n",
       "      <td>a scholastic clubs fairs cd rom game</td>\n",
       "      <td>-1.00</td>\n",
       "      <td>{'Video Games': 52262}</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "           brand                                        description  price  \\\n",
       "asin                                                                         \n",
       "0078764343                                        Brand new sealed!  37.98   \n",
       "043933702X        In Stock NOW.  Eligible for FREE Super Saving ...  23.50   \n",
       "0439339987        Grandma Groupers kelp seeds are missing and wi...   8.95   \n",
       "0439342260        This software is BRAND NEW. Packaging may diff...  -1.00   \n",
       "0439339960                     a scholastic clubs fairs cd rom game  -1.00   \n",
       "\n",
       "                         salesRank title  \n",
       "asin                                      \n",
       "0078764343  {'Video Games': 28655}        \n",
       "043933702X  {'Video Games': 44080}        \n",
       "0439339987  {'Video Games': 49836}        \n",
       "0439342260  {'Video Games': 49156}        \n",
       "0439339960  {'Video Games': 52262}        "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "video_games_meta = pd.read_json('./data/video-games.meta.parsed.json')\n",
    "\n",
    "del video_games_meta['imUrl']\n",
    "del video_games_meta['related'] # For now we remove related (also bought, also viewed and buy after viewing) products\n",
    "del video_games_meta['categories'] # We get rid of the sub categories for now\n",
    "\n",
    "video_games_meta.price.fillna(-1, inplace=True)\n",
    "video_games_meta.title.fillna('', inplace=True)\n",
    "video_games_meta.brand.fillna('', inplace=True)\n",
    "video_games_meta.description.fillna('', inplace=True)\n",
    "\n",
    "# The following line can be understood as:\n",
    "# video_games_meta.salesRank.fillna({}, inplace=True)\n",
    "# It is done using this process because Pandas won't take into account the empty {} with fillna()\n",
    "video_games_meta.loc[video_games_meta['salesRank'].isnull(), ['salesRank']] = video_games_meta.loc[video_games_meta['salesRank'].isnull(), 'salesRank'].apply(lambda x: {})\n",
    "\n",
    "video_games_meta.set_index(['asin'], inplace=True)\n",
    "\n",
    "video_games_meta.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We need to get rid of the nested objects and arrays. We will take into account only the `salesRank` for video games section."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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       "      <td>Brand new sealed!</td>\n",
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       "      <td>28655</td>\n",
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       "      <th>043933702X</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>0439339987</th>\n",
       "      <td></td>\n",
       "      <td>Grandma Groupers kelp seeds are missing and wi...</td>\n",
       "      <td>8.95</td>\n",
       "      <td></td>\n",
       "      <td>49836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0439342260</th>\n",
       "      <td></td>\n",
       "      <td>This software is BRAND NEW. Packaging may diff...</td>\n",
       "      <td>-1.00</td>\n",
       "      <td></td>\n",
       "      <td>49156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0439339960</th>\n",
       "      <td></td>\n",
       "      <td>a scholastic clubs fairs cd rom game</td>\n",
       "      <td>-1.00</td>\n",
       "      <td></td>\n",
       "      <td>52262</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           brand                                        description  price  \\\n",
       "asin                                                                         \n",
       "0078764343                                        Brand new sealed!  37.98   \n",
       "043933702X        In Stock NOW.  Eligible for FREE Super Saving ...  23.50   \n",
       "0439339987        Grandma Groupers kelp seeds are missing and wi...   8.95   \n",
       "0439342260        This software is BRAND NEW. Packaging may diff...  -1.00   \n",
       "0439339960                     a scholastic clubs fairs cd rom game  -1.00   \n",
       "\n",
       "           title   rank  \n",
       "asin                     \n",
       "0078764343        28655  \n",
       "043933702X        44080  \n",
       "0439339987        49836  \n",
       "0439342260        49156  \n",
       "0439339960        52262  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def sales_rank(row):\n",
    "    '''\n",
    "    Returns the video games sales rank from the sub object\n",
    "    '''\n",
    "\n",
    "    if not 'Video Games' in row.salesRank.keys():\n",
    "        return -1\n",
    "    \n",
    "    return row.salesRank['Video Games']\n",
    "    \n",
    "video_games_meta['rank'] = video_games_meta.apply(sales_rank, axis=1)\n",
    "del video_games_meta['salesRank']\n",
    "\n",
    "video_games_meta.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Things are now clean in off to merge the two dataframes. We will allow to have duplicate `brand`, `description`, `price`, `title` and `rank` for each review as it will help finding correlations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>overall</th>\n",
       "      <th>reviewText</th>\n",
       "      <th>reviewerName</th>\n",
       "      <th>summary</th>\n",
       "      <th>date</th>\n",
       "      <th>helpfulRate</th>\n",
       "      <th>helpfulCount</th>\n",
       "      <th>rank</th>\n",
       "      <th>description</th>\n",
       "      <th>price</th>\n",
       "      <th>title</th>\n",
       "      <th>brand</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>asin</th>\n",
       "      <th>reviewerID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">0700099867</th>\n",
       "      <th>A2HD75EMZR8QLN</th>\n",
       "      <td>1</td>\n",
       "      <td>Installing the game was a struggle (because of...</td>\n",
       "      <td>123</td>\n",
       "      <td>Pay to unlock content? I don't think so.</td>\n",
       "      <td>2012-07-09</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>12</td>\n",
       "      <td>6629</td>\n",
       "      <td>Dirt 3 is a popular rally racing game for Play...</td>\n",
       "      <td>246.63</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A3UR8NLLY1ZHCX</th>\n",
       "      <td>4</td>\n",
       "      <td>If you like rally cars get this game you will ...</td>\n",
       "      <td>Alejandro Henao \"Electronic Junky\"</td>\n",
       "      <td>Good rally game</td>\n",
       "      <td>2013-06-30</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>6629</td>\n",
       "      <td>Dirt 3 is a popular rally racing game for Play...</td>\n",
       "      <td>246.63</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A1INA0F5CWW3J4</th>\n",
       "      <td>1</td>\n",
       "      <td>1st shipment received a book instead of the ga...</td>\n",
       "      <td>Amazon Shopper \"Mr.Repsol\"</td>\n",
       "      <td>Wrong key</td>\n",
       "      <td>2014-06-28</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>6629</td>\n",
       "      <td>Dirt 3 is a popular rally racing game for Play...</td>\n",
       "      <td>246.63</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A1DLMTOTHQ4AST</th>\n",
       "      <td>3</td>\n",
       "      <td>I got this version instead of the PS3 version,...</td>\n",
       "      <td>ampgreen</td>\n",
       "      <td>awesome game, if it did not crash frequently !!</td>\n",
       "      <td>2011-09-14</td>\n",
       "      <td>0.700000</td>\n",
       "      <td>10</td>\n",
       "      <td>6629</td>\n",
       "      <td>Dirt 3 is a popular rally racing game for Play...</td>\n",
       "      <td>246.63</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A361M14PU2GUEG</th>\n",
       "      <td>4</td>\n",
       "      <td>I had Dirt 2 on Xbox 360 and it was an okay ga...</td>\n",
       "      <td>Angry Ryan \"Ryan A. Forrest\"</td>\n",
       "      <td>DIRT 3</td>\n",
       "      <td>2011-06-14</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2</td>\n",
       "      <td>6629</td>\n",
       "      <td>Dirt 3 is a popular rally racing game for Play...</td>\n",
       "      <td>246.63</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           overall  \\\n",
       "asin       reviewerID                \n",
       "0700099867 A2HD75EMZR8QLN        1   \n",
       "           A3UR8NLLY1ZHCX        4   \n",
       "           A1INA0F5CWW3J4        1   \n",
       "           A1DLMTOTHQ4AST        3   \n",
       "           A361M14PU2GUEG        4   \n",
       "\n",
       "                                                                  reviewText  \\\n",
       "asin       reviewerID                                                          \n",
       "0700099867 A2HD75EMZR8QLN  Installing the game was a struggle (because of...   \n",
       "           A3UR8NLLY1ZHCX  If you like rally cars get this game you will ...   \n",
       "           A1INA0F5CWW3J4  1st shipment received a book instead of the ga...   \n",
       "           A1DLMTOTHQ4AST  I got this version instead of the PS3 version,...   \n",
       "           A361M14PU2GUEG  I had Dirt 2 on Xbox 360 and it was an okay ga...   \n",
       "\n",
       "                                                 reviewerName  \\\n",
       "asin       reviewerID                                           \n",
       "0700099867 A2HD75EMZR8QLN                                 123   \n",
       "           A3UR8NLLY1ZHCX  Alejandro Henao \"Electronic Junky\"   \n",
       "           A1INA0F5CWW3J4          Amazon Shopper \"Mr.Repsol\"   \n",
       "           A1DLMTOTHQ4AST                            ampgreen   \n",
       "           A361M14PU2GUEG        Angry Ryan \"Ryan A. Forrest\"   \n",
       "\n",
       "                                                                   summary  \\\n",
       "asin       reviewerID                                                        \n",
       "0700099867 A2HD75EMZR8QLN         Pay to unlock content? I don't think so.   \n",
       "           A3UR8NLLY1ZHCX                                  Good rally game   \n",
       "           A1INA0F5CWW3J4                                        Wrong key   \n",
       "           A1DLMTOTHQ4AST  awesome game, if it did not crash frequently !!   \n",
       "           A361M14PU2GUEG                                           DIRT 3   \n",
       "\n",
       "                                date  helpfulRate  helpfulCount  rank  \\\n",
       "asin       reviewerID                                                   \n",
       "0700099867 A2HD75EMZR8QLN 2012-07-09     0.666667            12  6629   \n",
       "           A3UR8NLLY1ZHCX 2013-06-30    -1.000000             0  6629   \n",
       "           A1INA0F5CWW3J4 2014-06-28    -1.000000             0  6629   \n",
       "           A1DLMTOTHQ4AST 2011-09-14     0.700000            10  6629   \n",
       "           A361M14PU2GUEG 2011-06-14     1.000000             2  6629   \n",
       "\n",
       "                                                                 description  \\\n",
       "asin       reviewerID                                                          \n",
       "0700099867 A2HD75EMZR8QLN  Dirt 3 is a popular rally racing game for Play...   \n",
       "           A3UR8NLLY1ZHCX  Dirt 3 is a popular rally racing game for Play...   \n",
       "           A1INA0F5CWW3J4  Dirt 3 is a popular rally racing game for Play...   \n",
       "           A1DLMTOTHQ4AST  Dirt 3 is a popular rally racing game for Play...   \n",
       "           A361M14PU2GUEG  Dirt 3 is a popular rally racing game for Play...   \n",
       "\n",
       "                            price title brand  \n",
       "asin       reviewerID                          \n",
       "0700099867 A2HD75EMZR8QLN  246.63              \n",
       "           A3UR8NLLY1ZHCX  246.63              \n",
       "           A1INA0F5CWW3J4  246.63              \n",
       "           A1DLMTOTHQ4AST  246.63              \n",
       "           A361M14PU2GUEG  246.63              "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# We concatenate our dataframes based on the product ID index\n",
    "video_games_ids = video_games.index.get_level_values('asin')\n",
    "\n",
    "video_games['rank'] = video_games_meta.loc[video_games_ids]['rank'].values\n",
    "video_games['description'] = video_games_meta.loc[video_games_ids]['description'].values\n",
    "video_games['price'] = video_games_meta.loc[video_games_ids]['price'].values\n",
    "video_games['title'] = video_games_meta.loc[video_games_ids]['title'].values\n",
    "video_games['brand'] = video_games_meta.loc[video_games_ids]['brand'].values\n",
    "\n",
    "video_games.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Missing values\n",
    "We check if our data frame contains missing data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 2813 rows containing missing values\n",
      "Columns with missing datas: ['reviewerName']\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>overall</th>\n",
       "      <th>reviewText</th>\n",
       "      <th>reviewerName</th>\n",
       "      <th>summary</th>\n",
       "      <th>date</th>\n",
       "      <th>helpfulRate</th>\n",
       "      <th>helpfulCount</th>\n",
       "      <th>rank</th>\n",
       "      <th>description</th>\n",
       "      <th>price</th>\n",
       "      <th>title</th>\n",
       "      <th>brand</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>asin</th>\n",
       "      <th>reviewerID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9861019731</th>\n",
       "      <th>A26HSO6VAFB2V4</th>\n",
       "      <td>5</td>\n",
       "      <td>It works perfectly! Nothing is wrong with it.</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Perfect!</td>\n",
       "      <td>2014-07-13</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>579</td>\n",
       "      <td>Compatible with:\\nNINTENDO Wii &amp; Gamecube\\nPac...</td>\n",
       "      <td>4.42</td>\n",
       "      <td>64MB 1019 Block Memory Card compatible for Wii...</td>\n",
       "      <td>Generic</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B00000F1GM</th>\n",
       "      <th>A2WTO0ST2SUUY9</th>\n",
       "      <td>5</td>\n",
       "      <td>For those of you who haven't played Super Mari...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Super Mario 64 Review</td>\n",
       "      <td>2013-01-10</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3</td>\n",
       "      <td>699</td>\n",
       "      <td>The game that launched the Nintendo 64 system ...</td>\n",
       "      <td>299.99</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">B00000I1BF</th>\n",
       "      <th>A3OU09O34BC73</th>\n",
       "      <td>5</td>\n",
       "      <td>classic game for the ps1. i love it and it sti...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>so fun!!</td>\n",
       "      <td>2014-07-13</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2059</td>\n",
       "      <td>Spyro is a cute purple dragon in a bit of a pi...</td>\n",
       "      <td>90.00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ANLC4FX4QK23V</th>\n",
       "      <td>5</td>\n",
       "      <td>I was feeling nostalgic so I bought this game ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Blast from the past!</td>\n",
       "      <td>2013-06-17</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2059</td>\n",
       "      <td>Spyro is a cute purple dragon in a bit of a pi...</td>\n",
       "      <td>90.00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B00000IWYT</th>\n",
       "      <th>A1OYBF92TASIWN</th>\n",
       "      <td>5</td>\n",
       "      <td>Wow...the only Game Boy games that even come c...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>By far, the best Game Boy game ever</td>\n",
       "      <td>2001-04-16</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>4422</td>\n",
       "      <td>The legendary Link of Hirule tackles a new que...</td>\n",
       "      <td>186.74</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           overall  \\\n",
       "asin       reviewerID                \n",
       "9861019731 A26HSO6VAFB2V4        5   \n",
       "B00000F1GM A2WTO0ST2SUUY9        5   \n",
       "B00000I1BF A3OU09O34BC73         5   \n",
       "           ANLC4FX4QK23V         5   \n",
       "B00000IWYT A1OYBF92TASIWN        5   \n",
       "\n",
       "                                                                  reviewText  \\\n",
       "asin       reviewerID                                                          \n",
       "9861019731 A26HSO6VAFB2V4      It works perfectly! Nothing is wrong with it.   \n",
       "B00000F1GM A2WTO0ST2SUUY9  For those of you who haven't played Super Mari...   \n",
       "B00000I1BF A3OU09O34BC73   classic game for the ps1. i love it and it sti...   \n",
       "           ANLC4FX4QK23V   I was feeling nostalgic so I bought this game ...   \n",
       "B00000IWYT A1OYBF92TASIWN  Wow...the only Game Boy games that even come c...   \n",
       "\n",
       "                          reviewerName                              summary  \\\n",
       "asin       reviewerID                                                         \n",
       "9861019731 A26HSO6VAFB2V4          NaN                             Perfect!   \n",
       "B00000F1GM A2WTO0ST2SUUY9          NaN                Super Mario 64 Review   \n",
       "B00000I1BF A3OU09O34BC73           NaN                             so fun!!   \n",
       "           ANLC4FX4QK23V           NaN                 Blast from the past!   \n",
       "B00000IWYT A1OYBF92TASIWN          NaN  By far, the best Game Boy game ever   \n",
       "\n",
       "                                date  helpfulRate  helpfulCount  rank  \\\n",
       "asin       reviewerID                                                   \n",
       "9861019731 A26HSO6VAFB2V4 2014-07-13         -1.0             0   579   \n",
       "B00000F1GM A2WTO0ST2SUUY9 2013-01-10          1.0             3   699   \n",
       "B00000I1BF A3OU09O34BC73  2014-07-13         -1.0             0  2059   \n",
       "           ANLC4FX4QK23V  2013-06-17         -1.0             0  2059   \n",
       "B00000IWYT A1OYBF92TASIWN 2001-04-16         -1.0             0  4422   \n",
       "\n",
       "                                                                 description  \\\n",
       "asin       reviewerID                                                          \n",
       "9861019731 A26HSO6VAFB2V4  Compatible with:\\nNINTENDO Wii & Gamecube\\nPac...   \n",
       "B00000F1GM A2WTO0ST2SUUY9  The game that launched the Nintendo 64 system ...   \n",
       "B00000I1BF A3OU09O34BC73   Spyro is a cute purple dragon in a bit of a pi...   \n",
       "           ANLC4FX4QK23V   Spyro is a cute purple dragon in a bit of a pi...   \n",
       "B00000IWYT A1OYBF92TASIWN  The legendary Link of Hirule tackles a new que...   \n",
       "\n",
       "                            price  \\\n",
       "asin       reviewerID               \n",
       "9861019731 A26HSO6VAFB2V4    4.42   \n",
       "B00000F1GM A2WTO0ST2SUUY9  299.99   \n",
       "B00000I1BF A3OU09O34BC73    90.00   \n",
       "           ANLC4FX4QK23V    90.00   \n",
       "B00000IWYT A1OYBF92TASIWN  186.74   \n",
       "\n",
       "                                                                       title  \\\n",
       "asin       reviewerID                                                          \n",
       "9861019731 A26HSO6VAFB2V4  64MB 1019 Block Memory Card compatible for Wii...   \n",
       "B00000F1GM A2WTO0ST2SUUY9                                                      \n",
       "B00000I1BF A3OU09O34BC73                                                       \n",
       "           ANLC4FX4QK23V                                                       \n",
       "B00000IWYT A1OYBF92TASIWN                                                      \n",
       "\n",
       "                             brand  \n",
       "asin       reviewerID               \n",
       "9861019731 A26HSO6VAFB2V4  Generic  \n",
       "B00000F1GM A2WTO0ST2SUUY9           \n",
       "B00000I1BF A3OU09O34BC73            \n",
       "           ANLC4FX4QK23V            \n",
       "B00000IWYT A1OYBF92TASIWN           "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "null_data = video_games[video_games.isnull().any(axis=1)]\n",
    "print(\"There are\", len(null_data), \"rows containing missing values\")\n",
    "\n",
    "print(\"Columns with missing datas:\", list(video_games.columns[video_games.isnull().any()]))\n",
    "\n",
    "null_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our dataframe contains missing values. However, it's only true for two columns : `reviewerName` and `reviewerNameLength`. These informations are not crucial for our analysis, so we can ignore this."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Descriptive analysis\n",
    "\n",
    "Our descriptive analysis will focus on several metrics taken from the above dataframe. We will first focus on the distribution of reviews grade (`overall`) and then analyse \"helpful evaluations\" of reviews. Finally, we will start searching for patterns in data distribution to prepare work for the next milestone.\n",
    "\n",
    "### Distribution of possible review grades\n",
    "\n",
    "We start by using a box plot to visualize how grades are distributed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x22cf01899b0>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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7WvQO4K6q+gVAku8Afwq8KcnvAmPAT6vqeJJbgXcDj3XfeyGzof4j4IcvB3vnfUmmmP17\nswn4Q8Bw16uS4a7Xkm8B1wMXA9/oxgL8Q1V9fm5hkgngF3OOfx/4KPAnVfXTJF8GLlj9lqXlcc5d\nLXoY+Mskv53kDcBfdWPfAHYxG/Df6mr/DfjrJBcCJNmc5E0LXPONzIb9mSRvBq5e5T+DtCI+uas5\nVXWoe7L+fjf0hap6DCDJRcDJqjrV1f57kj8A/rtbHPsss/PzL8275g+SPAY8DRwH/ut8/Fmk5fIT\nqpLUIKdlJKlBhrskNchwl6QGGe6S1CDDXZIaZLhLUoMMd0lqkOEuSQ36f1m8QokiII+LAAAAAElF\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x22cf0180cc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "video_games.boxplot(column=['overall'], figsize=(8, 8), grid=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see that there is definitely more high grades (4, 5) than low ones. Let's describe data to get some insights."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    231780.000000\n",
       "mean          4.086397\n",
       "std           1.202330\n",
       "min           1.000000\n",
       "25%           4.000000\n",
       "50%           5.000000\n",
       "75%           5.000000\n",
       "max           5.000000\n",
       "Name: overall, dtype: float64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "video_games.overall.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have 231780 reviews, with a mean of 4.08 and a standard deviation of 1.20.\n",
    "\n",
    "When focusing at **robust statistics** only, we can see that the median is 5, and more than 75% of the reviews have awarded 4 or 5 grade to the product.\n",
    "\n",
    "Let's see data distribution using a bar plot:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x22cf0180ac8>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x22cf0223f98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.xlabel('Score')\n",
    "plt.ylabel('Number of review')\n",
    "video_games.overall.value_counts(ascending=True).sort_index().plot(kind='bar', rot=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This confirms what was found before. We can do some assumptions about this distribution:\n",
    "\n",
    "- The people may be more likely to thank the product quality by posting a review than to say their displeasure\n",
    "- Amazon sell more good quality product (here video game) than bad one\n",
    "- The 5 stars review can be due to the presence of fakes/paid review\n",
    "\n",
    "We also can see that there are more reviews with `1` grade than `2`. This could be understood as people underrating products when they are not fully satisfied. It may also be used by customers to counterbalance a too high grade on a product, based on their opinions.\n",
    "\n",
    "We now count the number of reviews per product to see if products are equally reviewed:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x22cf02bf080>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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2AT8D3hbpDPZe4DOSJpMCwKcK5fkM8JF8DtlLRMwBNndO74qkljzvj3eR5VCt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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x22cf0294dd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "reviews_count_per_product = video_games.groupby(['asin']).overall.count().sort_values(ascending=False)\n",
    "\n",
    "reviews_count_per_product.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We seem to have a power law. However when using a logarithmic plot, we can see it is not:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x22cf01fdc88>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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6TZX+M9RrLCJprVXDWhzfrRnHd2tGnRo5VdJeqM4SEckYOVlWJaU0SoQikjFy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\nWlufzC+7AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x22cf0359fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "warnings.simplefilter('ignore') # Ignoring warning about non positive xlimit\n",
    "\n",
    "reviews_count_per_product.plot(logy=True, logx=True, rot=90, figsize=(5, 5))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's see if users tend to review products when they are pricy:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x22cf04d43c8>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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5hmO2J9mVZNfevXuHV5wkdczQgyDJG4DXAP+2qupEx1XVDVU1U1UzU1NTQ6tPkrpmxTA7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\n6jiDQJI6ziCQpI77/z+qoieJIxWJAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x22cf04f1630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nb_reviews_per_product = pd.DataFrame()\n",
    "\n",
    "# We count the number of reviews per product\n",
    "nb_reviews_per_product['count'] = video_games[video_games.price > 0].groupby('asin').overall.count()\n",
    "# We also add the product price\n",
    "nb_reviews_per_product['price'] = video_games[video_games.price > 0].groupby('asin').price.mean()\n",
    "\n",
    "# We create price beans because we have more products in specific price ranges\n",
    "bins = range(0, 1000, 100)\n",
    "nb_reviews_per_product['price_group'] = pd.cut(nb_reviews_per_product['price'], bins, labels=range(1, 10))#.plot(kind='scatter', x='price', y='count')\n",
    "\n",
    "nb_reviews_per_product.groupby(['price_group']).mean().plot(kind='scatter', x='price', y='count')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can't conclude much here. We can see a spike around 600$ which is due to existing game consoles at this price range, which are clearly more popular."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x22cf05ba4a8>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Sqb6DiUZuiYgUJt+Z7d8ysybgsiDpXe6+O7xshWdcdZR4P0GkJmYauSUiUqC8m6eCwFGW\nwSPXyc4U1VGjs0cwqY4a//LnS7h68YwRypmISHkqeBn5ctdQNwaz3umdKedj923TqC0RkQJVXCCZ\nMr6GO65bTKSPYBJPukZtiYgUqOICCcDSeVOpivYRSdCoLRGRQlVkIMmM3Oq76J0pjdoSESlERQaS\nhroxdPYxKRHg/ZfO06gtEZECVGQgebT5FfoaAVwVhasueNXwZ0hEpIyFFkjMrNbMnjSz7Wa2y8w+\nHaRPNrMHzWxP8Jo7Y/5WM2s2s+fM7Iow8tXaHmf1xu30Nbk9YsbVX3lUI7dERAoQZo0kDlzm7ouB\nJcCVZnYxsAbY6u7zga3Be8xsAZm93RcCVwJ3mlm01Jlqaesgkex7QmI86VpvS0SkQKEFEs9oD95W\nBT8OLAfWB+nrgWuC4+XAve4ed/cXgGbgwlLnK5FMkR7kHI3cEhHJX6h9JMEmWNuAw8CD7v4EMM3d\nDwSnHASmBcczgX05l7cEaSX1YuupQc/RelsiIvkLNZC4e8rdlwANwIVmdkGPz51MLSVvZnaTmTWZ\nWdORI0cKztOSWZMG/Lw6qvW2REQKMSyjttz9KPAwmb6PQ2Y2HSB4PRycth+YlXNZQ5DW817r3L3R\n3Rvr60u7bXzM4K5Vf8yyJSWvCImInLXCHLVVb2aTguMxwFuBZ4EtwKrgtFXA5uB4C7DSzGrMbC4w\nH3iy1Pnatu9ov58lHfa1Dd70JSIiZ4S5OdV0YH0w8ioCbHD3B8zsMWCDmd0I7CWzFzzuvsvMNpBZ\nYTgJ3Ozufc8aLMJgTVuffWA3F82ZzMnOFA11Y9TEJSIyiNACibvvoI/teN29Fbi8n2vWEvKGWXXj\nqolGjNQAuyS+/V9/Tk0sSiKd5vZrF6mpS0RkABU3s72lrYOxVf1PTzmdSNOZck7Ek5pTIiKSh4oL\nJA11YzjdxzpbY6siVMci1PRYFVhzSkREBlZxgQQgM+q4u0Ta+csLG8B6pmtOiYjIQMLsbB+VWto6\niJqR7DF9JZFy7v7lS8QiEIvAmKpYVx+JOtxFRPpXcYFkXHWUeF9L/waSaaiJRfjq9a9n4YxzFERE\nRAZRcU1bzx48Meg5sagxcUyVgoiISB4qLpA8c+DYoOd0JtUvIiKSr4oLJPks7PW+N89VbUREJE8V\nF0iqo4MXuXF2Hdv3HdX8ERGRPFRcZ/sreQSHG7/1FNXBfJJPLVvI9RedF3a2RETKVsXVSC6YMTGv\n8zpTTmfK+eT9O7nn8b0h50pEpHxVXCB568JXFXzNP/5gl5q5RET6UXGBpO1kZ8HXxCKmZVJERPpR\ncYFkoP1I+pN2ONaRUK1ERKQPFRdI5kwZW9D5mSXn09x8z9Ms/dxDbNnWa9NGEZGKVnGjtqpi/S8h\nn/UPbz+f8191Dsc7Enzsvm3Ek3AingRg9aYdLJ03VfNMREQCYW61O8vMHjaz3Wa2y8w+FKRPNrMH\nzWxP8FqXc82tZtZsZs+Z2RVh5Gtc9eCB5AsP/paFM85h1uSxVEe7n69l5UVEuguzaSsJfMzdFwAX\nAzeb2QJgDbDV3ecDW4P3BJ+tBBYCVwJ3Btv0ltTJzvx2721p66ChbgyJdLpbupaVFxHpLrRA4u4H\n3P3p4PgE8AwwE1gOrA9OWw9cExwvB+5197i7vwA0AxeWOl+vnDg96DmnE2nGVUeZMr6G269dRG1V\nhAk1MWqrIlpWXkSkh2HpIzGzOWT2b38CmObuB4KPDgLTguOZwOM5l7UEaSX12PO/H/ScqGVGd9WN\nq2bZkpksnTe1q4aiICIi0l3oo7bMbDywCfiwux/P/cwzWxXms45i7v1uMrMmM2s6cuRIwfmJ2eDn\npDwzCTE7SmvK+BoWz5qkICIi0odQA4mZVZEJIve4+/eC5ENmNj34fDpwOEjfD8zKubwhSOvG3de5\ne6O7N9bX1xecp/Y8+0ja4ylOJ9Ks3rRD80dERAYQ5qgtA74OPOPuX8j5aAuwKjheBWzOSV9pZjVm\nNheYDzxZ6nwtnHFOQedrlJaIyMDC7CNZCvwV8Bsz2xak/QNwG7DBzG4E9gIrANx9l5ltAHaTGfF1\ns7vnV30owPxzxxd0vkZpiYgMLLRA4u6PAv31SFzezzVrgbVh5QngxdZTeZ9bHbVQR2m1tsfViS8i\nZa/iZrYvmTUp73O/sGIJVy+e0fXAH1cd5WRnqiQP/s3b9nPLph1URSIk0mluv3YRy5aUfJCaiEjo\nKi6QHD2V/+q/r7THuefxvXz2h7uBzPySmqhhESvqwd/aHueWTTs4nUhzmsyERy29IiLlquICyXd+\n9VLe5/7TA7tJ9hicHE85pLyoB39LWwdVkUhXEIEznfoKJCJSbipu9d/WE/nXSHoGkVzFjObS0isi\ncjapuEAyZUJ1Se4z0IO/tT3O9n1H+51/UujSK4PdT0RkJFVc09Zr6gsb/tuXgUZz5duJnu/SK+qU\nF5HRruICyRMvthV1fXUswo8+8CbmTZvQ67NCO9GnjK8ZsE9EnfIiUg4qrmlrbB77kQzkmiUz+gwi\ncKYTPVcxfSlDvZ+awkRkOFVcIPmjApdI6WlDUwv3PL63z89K3Yk+lPtt3rafpZ97iBvuekJbA4vI\nsKi4QPJo8ytF3+PTP9hF86ETvf7qL/X+JUPplM82hZ2IJ7XopIgMi4rrI3mlRA/Vt//rz4lFI6TS\nzh3XnekAL+X+Ja3tcc6bMo4H3v+mvGbUa36KiIyEigsk54ypBk4WdY/OlAevmTUlP3bf9m4d4IN1\nouejr9FaiwdZ3kXzU0RkJFRc09ZgD+OBVBlURXuvQ5lIOY/9rvgms6yhNlFpa2ARGQkVVyNJpoa+\nMn3C4S9eN5PvNrX0+uyjG3Zw7HSSC2ZMzKtJa6CVf4tpotLWwCIy3CoukBwpYImUvmx8ej8RIN0j\nvTOV5pP372RsVYREKs31F53HZX94LgtnTOz1MB9skmGxTVSlaFoTEclXxTVtpbygLeJ7X592bIB9\n308l0iTScPdje3nPN37Fxf+8tdsQ3HyarbSEioiUk9BqJGb2DeBq4LC7XxCkTQa+C8wBXgRWuHtb\n8NmtwI1ACvigu/8kjHydTvasSxQuVUAsSqScT2w8Mxs932arvpqo+moO0xIqIjLSwqyR3A1c2SNt\nDbDV3ecDW4P3mNkCYCWwMLjmTjMrbgp6P7yQKFAi0YjR0tZBa3ucYx0JOlP5NVtNGV/D4lmTmDK+\nps+Jhpo3IiKjQWiBxN0fAX7fI3k5sD44Xg9ck5N+r7vH3f0FoBm4MIx8/fbQiTBuO6BU2tm5/xhL\nP/cQN9/zNKl0mqqo5T2yqr+AsevlYyVdkkVEZCiGu7N9mrsfCI4PAtOC45nA4znntQRpvZjZTcBN\nALNnzy44AzVVpY+dsQj012JWFTX+7zsX8NkHdndbfLEq6vzzuy7gkj8YfAHG/prDwDRvRERG3Ih1\ntru7AwW3M7n7OndvdPfG+vr6gr93QZFrbfWl/yACP/7gm7lgxsReNYdECj563w5+0fzKoJ3l/Y3i\nWjjjHM0bEZERN9w1kkNmNt3dD5jZdOBwkL4fmJVzXkOQVnJ/NGMiD/zmUEnvGYsYGCR79L/UxmJd\nS5v0DAQAnck0H92wjWgkQlXU6Ew5n3rnAq6/6Lyuc1rb4+x6+RjvfeMcvvGLF6mOnulUnzK+RvNG\nRGTEDXcg2QKsAm4LXjfnpH/bzL4AzADmA0+GkYFHm1tLfs9k2rlq4bn8eNfhbunZZqbscN6P37e9\na3mVM9dCMp0mnsy8/+T9O8Hh+ovPY/O2/Xz8vu0kgmuiBu+/dB5/edHsbgFjoHkjA018FBEphdCa\ntszsO8BjwGvNrMXMbiQTQN5qZnuAPw3e4+67gA3AbuC/gZvdfehT0Adw8Hg4HdE9gwjA/3nHgq6H\n97IlM/nRB99MdWzwX3l2deHVG3d0BRHIDDv+8kO/zTtPWlJeRIZDaDUSd393Px9d3s/5a4G1YeUn\n6+ipZNhf0aWl7RQAzYdOsG3fUeZMGcsHLp3HVx5uJp1Kk+inhygWMbZsf5lIHxMfO1Pw7Sde4gOX\nzx/wu/vaXfETG7ezYPo5ea0kLCKSr4pbIuVUZ3FLpBTi64++QGt7nA1PnakJZNd8HGg6y6lEmv94\n5Hk6+unF//JDe3o1b/XU10iveNK58ks/Z0xVVJMXRaRkKi6QxCJRMpPnh0duEIH8Z8X3F0QAYpEI\nu14+xsQx1YyrjvLysQ7AWDjjnK7g0lA3pmuZ+1zJtHMi6JDR/u8iUgoVF0gS6eELIj071kt33xR/\n+60mcIjnfEcsAl9YsYRlS2YyZXwN7790Pv/y4MB9Kv2tKKxOehHJV+Ut2lj8UlsjKts0Fk96tyAC\nmRFgn9i4vWs+ylUXvIqB+vZPJ9KMq+69Ek1/y7FoYUgR6UvF1Ujiw1chKbmqCKy+8nw+/5Pfkuy1\nkP0ZDz97mNaTndzxk+f6nSwJUBM1TnZ2/4X01Un/sfu2EzGojubXt6LajEhlqbhAUq6iBhe9egpr\nf/TsgOfFk87HN+7I654WMcZVR9m+72jXQ7+vTvrsEOR4cvC+lc3b9rN64w6iEeu1n30xFJxERi8F\nkjKR8tJNpqwN1htb8YYG3vHlnxO1CMl0mg9cNp9LXj2Z+CDtf/3t1tjaHu82gRJ672c/FFoqX2R0\nUyCpQOm08+33XcTK/3g8aPrKNG9lO+az/Sq1VRHcIZVOd2si629hyLt+/ny3IAKZ2syul4/xltec\n2+v8fGoZfTW1ZWtEgGopIqOAAkkFMoyHnzvcb/9JNj2RTPNP11xA2uEzD+wiahFSnu5zYcjW9jh3\n/fz5Pu93vCPB9n1HGVcd7ZoM+WjzK3nVMvpb+fieJ17izp81q5YiMgookFSgeCrNV3/W90M/V8rh\n1vt3YkAsakQjgGeGjfWsTbS0dVAdi5Lo7D2a4UP3biMaySxKWR0BNyOddlJOr1pGzwDV14KXnakU\nX324mXiydy1FNROpBKOtz1CBRAblZJqoEsEEx498dxsY1EQjJNLO+948l2tf10DK+543k3JIBU1e\nnensHbvL3ZAr9x9IdsHL1Tm1l5v/ZB7rHnmeeDLd6/rR8I8qX6PtYSDlYTT2GSqQSMFSwU4yp4Ka\nwr/97Hn+45HnWTD9HHbsPz6ke3Ykkuzcf4y/WPdYr38gPZfKB/jqz5q7Xd9fv81wP6zz/b7R+DCQ\n0W+gPsOR/GNEgURKIplmyEEEIO3wqS07Saa7N3dlF5nMTpxsO9nJyc4UyxbPYENTS9f1Kxobuv1D\nam2Pc88TL/HVh/cQi0ToTKW5/sLZXPaH57JwxsRQ/tHlGxxG68Mg12ABUbWpkdFfn+FI18YVSGRU\nSHvmJ1cyleZtX3yEWCSz6nHEMudURSDRY6DAtx9/iWWLZrDncDv/s/sQjza/cmb+SzAq7e7H9nL3\nY3uJGvzVJedx2fnTmDGxttdqyJnNxI4DzsIZE2k72dm1enNVLNrnwzOf4JBdBbq2KjoqHwaQG4Cb\nu22ilhsQewbM//OOBVwwc+KIB5VKCG797ZY60ttrK5DIqJXtAsn232cDTc8gApB0uO5rj+d135TD\n3b/cy92/3AtAVbDD5RULpjG+JsaGppZ+1w2IGsSiEf73/3o1LW0dxBMpFs+a1K2/JitixmO/a+Wc\nMTHueuR5HsmZBxS17nsEdKYGb5qDwYc7556fDYBLZk1i3rQJg/5eMpNJtxNPZieg9g6IfQXMT35/\nJ+NroiRS3ufGa8OhUpoKs32Gn9i4fcBRlMNt1AUSM7sS+BIQBe5y99tGOEtylksEEeqB3xwc9NyU\nQyqZ5otbz/TR/KCf6051pnj/d37dz326V7/iyTSf/cEu3vWGBhbOmAjAPU+8xFce+i2xSJTTiRQW\ngdpYlJR7rwdltiaRPf9UovvoufdcMpvPLP+jbmk9g9TqjTu6gkiuiFnXXKC+mlYA2uNn5iJ95eE9\n3HHd4pI/yLP5zR1GDrDr5eNB3kdvU2GptLbHebH1FJD54yc7inKkjapAYmZR4KvAW4EW4FdmtsXd\nd49szkTC9/3tB/j+9gNEIwbuXVsOdG0HkKZrbbTcB2V2WZpsDaKv7QO+9dhLvOfiOV01k55/wV92\nfn2ftSrQiuCXAAAJbUlEQVTIBMS//VYTd1y3mKXzpvZqWukpnvSSP8iz+YXMYqM1USMNuDvV0Wiv\nvI+WpsJS6lljzBoNQXO0rf57IdDs7s+7eydwL7B8hPMkMqxSaR9035qoGS1tHV1NTf0FgVzb9h0F\nuvfnnIgnOZ1I86PfHBrw2mxwALj92kXUVkUYW93/4yN3OHexujWnBe2a8ZSTSDnJNL1qXzA6+g1K\n6cx/54GHzo+U0RZIZgL7ct63BGkikiMR9Klkm5rysWTWJIC8r4n2OCX7wFq2ZCa/uOUyPrPsAqqj\nfTetlPJBXkgZx1ZHqa2KjIp+g1Ia6HcwGoLmqGrayoeZ3QTcBDB79uwRzo3IyPjUOxd2PSgHa2qC\nTB9Jtlmrr5E/PVVHwSxCKue83AfWlPE1XHr+uUQi1mvbz5pYaR/k+eQ3873Gv9/w+tCGd4+k/n4H\npf5dD9Voq5HsB2blvG8I0rq4+zp3b3T3xvr6+oK/4MXb3lFcDkVCFo0YsciZVZojwR/9NbEI1bEI\na//sAq6/+DzgzCie2qoINUHtoDoaoSYW4R+uOp/PX7eIn37kLd062nOvmVATo7Yqwnsumd3t/ef/\nfAl3XNf9nJ4PrJ73qYkZH3vra/jlmstK2tGe+z3Z30lN1KiKZn5P2fzdcd1i3vKac0f8oRqG4fpd\nD5V5P8tajAQziwG/BS4nE0B+Bfylu+/q6/zGxkZvamoa0nfNWfPDoWZTCmRATSS7PErmr5doFFKp\nzIdpz5xTNzZKdVWMSbUx2jtTRCNGbSxCMg3VsQh/MHUcB0/E6ehMMmVcDa+aVEs8keLIiU4m1saI\nRIxk2vn9yU7iiSQdiXRXZ/KY6ig1sSiTx1dzKp4knXYmj63m2UMn6EikGFsdZfbkcVx6/rmcO6GG\nx1/4PeOqo3SmMrtIXjR3CnsOt/PL5iPUVEVZ+cezmVs/nl0vH+d4R4ITpxO0tJ3EMerGVtN2qpNx\n1VGuWDido6c6eWTPKyxumEhHIs0r7ae5YMbEoG3fSCRTPP7C7zl3Qg2vfdWErlFbuSOUckcqDTRB\ncLDz+rome25f8zDyXaF5OOZv9Ddq62yfO5KrVL9rM3vK3RtLla9RFUgAzOztwBfJDP/9hruv7e/c\nYgKJiEilKnUgGXV9JO7+I+BHI50PERHJz2jrIxERkTKjQCIiIkVRIBERkaIokIiISFFG3aitQpjZ\nEWBvEbeYCrxSouyMBirP6Ha2lQfOvjJVSnnOc/fCJ+L1o6wDSbHMrKmUQ+BGmsozup1t5YGzr0wq\nz9CoaUtERIqiQCIiIkWp9ECybqQzUGIqz+h2tpUHzr4yqTxDUNF9JCIiUrxKr5GIiEiRKjKQmNmV\nZvacmTWb2ZqRzk8uM5tlZg+b2W4z22VmHwrSJ5vZg2a2J3ity7nm1qAsz5nZFTnpbzCz3wSf/auZ\nWZBeY2bfDdKfMLM5w1CuqJn92sweKPfymNkkM9toZs+a2TNmdkmZl+cjwf9rO83sO2ZWW27lMbNv\nmNlhM9uZkzYsZTCzVcF37DGzVSGW547g/7kdZna/mU0aNeVx94r6IbOq8O+AVwPVwHZgwUjnKyd/\n04HXB8cTyCyrvwC4HVgTpK8BPhccLwjKUAPMDcoWDT57EriYzCrtPwauCtL/Hvj34Hgl8N1hKNdH\ngW8DDwTvy7Y8wHrgfcFxNTCpXMtDZgfSF4AxwfsNwF+XW3mAtwCvB3bmpIVeBmAy8HzwWhcc14VU\nnrcBseD4c6OpPKE+PEbjD3AJ8JOc97cCt450vgbI72bgrcBzwPQgbTrwXF/5B34SlHE68GxO+ruB\nr+WeExzHyExYshDL0ABsBS7jTCApy/IAE8k8eK1HermWJ7u99eTgux4IHlhlVx5gDt0fvKGXIfec\n4LOvAe8Oozw9Pvsz4J7RUp5KbNoqm33hg+rm64AngGnufiD46CAwLTjurzwzg+Oe6d2ucfckcAyY\nUvICnPFFYDWQu1douZZnLnAE+GbQVHeXmY2jTMvj7vuBzwMvAQeAY+7+P5RpeXoYjjKM1PPkb8jU\nMLrlrUcehq08lRhIyoKZjQc2AR929+O5n3nmT4WyGG5nZlcDh939qf7OKafykPnr7fXAv7n764CT\nZJpNupRTeYJ+g+VkAuQMYJyZ3ZB7TjmVpz9nQxmyzOyTQBK4Z6TzklWJgWTQfeFHmplVkQki97j7\n94LkQ2Y2Pfh8OnA4SO+vPPuD457p3a6xzPbGE4HW0pcEgKXAMjN7EbgXuMzM/ovyLU8L0OLuTwTv\nN5IJLOVanj8FXnD3I+6eAL4HvJHyLU+u4SjDsD5PzOyvgauB64Pg2C1vPfIwbOWpxEDyK2C+mc01\ns2oyHU1bRjhPXYJRFV8HnnH3L+R8tAXIjqBYRabvJJu+MhiFMReYDzwZVOmPm9nFwT3f0+Oa7L2u\nAx7K+Z+ypNz9VndvcPc5ZH7XD7n7DWVcnoPAPjN7bZB0ObC7XMtDpknrYjMbG+TjcuCZMi5PruEo\nw0+At5lZXVC7e1uQVnJmdiWZJuJl7n6qRzlHtjyl7Owqlx/g7WRGQ/0O+ORI56dH3t5Epgq+A9gW\n/LydTPvlVmAP8FNgcs41nwzK8hzBqIwgvRHYGXz2Fc5MQK0F7gOayYzqePUwle1PONPZXrblAZYA\nTcF/o++TGd1SzuX5NPBskJf/JDP6p6zKA3yHTB9Pgkyt8cbhKgOZ/orm4Oe9IZanmUz/Rfa58O+j\npTya2S4iIkWpxKYtEREpIQUSEREpigKJiIgURYFERESKokAiIiJFUSARGUZm9o9m9vGRzodIKSmQ\niAyRZejfkFQ8/SMQKYCZzQn2fPgWmYleXzezJsvs5/HpnPNeNLNPm9nTwX4Q5/dxr781sx+b2Zjh\nLINIqcVGOgMiZWg+sMrdHzezye7+ezOLAlvNbJG77wjOe8XdX29mfw98HHhf9gZm9n4y2wNc4+7x\nYS+BSAmpRiJSuL3u/nhwvMLMngZ+DSwks8lQVnbBzafI7C2R9R7gKuA6BRE5GyiQiBTuJECwQN7H\ngcvdfRHwQzJrGGVlg0SK7rX/35AJLLkrs4qULQUSkaE7h0xQOWZm08jUMvLxa+DvgC1mNiOszIkM\nFwUSkSFy9+1kgsKzZPaj/0UB1z5KpjbzQzObGk4ORYaHVv8VEZGiqEYiIiJFUSAREZGiKJCIiEhR\nFEhERKQoCiQiIlIUBRIRESmKAomIiBRFgURERIry/wHiy8wpI6IdugAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x22cf04ffd30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nb_reviews_per_product = pd.DataFrame()\n",
    "\n",
    "nb_reviews_per_product['count'] = video_games.groupby('asin').overall.count()\n",
    "nb_reviews_per_product['rank'] = video_games.groupby('asin').rank.mean()\n",
    "\n",
    "nb_reviews_per_product.plot(kind='scatter', x='rank', y='count')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>rank</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.443484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rank</th>\n",
       "      <td>-0.443484</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          count      rank\n",
       "count  1.000000 -0.443484\n",
       "rank  -0.443484  1.000000"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# We use spearman correlation here because we definitely\n",
    "# can't have a linear relation between the two based on above graph\n",
    "nb_reviews_per_product.corr(method='spearman') "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Results seems logical, if a product is well-ranked, it is most likely because it has a lot of reviews, and has actually being purchased. The correlation is however weak as it only concerns the maximum number of reviews. We can still find high ranked products with few reviews."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's focus on the most reviewed product. The product is the \"PlayStation 4 500GB Console\". Notice that the price is not logical. After verification, there was no issue with the data importation. We will have to proceed with caution when using it as a feature."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>overall</th>\n",
       "      <th>reviewText</th>\n",
       "      <th>reviewerName</th>\n",
       "      <th>summary</th>\n",
       "      <th>date</th>\n",
       "      <th>helpfulRate</th>\n",
       "      <th>helpfulCount</th>\n",
       "      <th>rank</th>\n",
       "      <th>description</th>\n",
       "      <th>price</th>\n",
       "      <th>title</th>\n",
       "      <th>brand</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>reviewerID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A386ZNRX0TFFHX</th>\n",
       "      <td>4</td>\n",
       "      <td>I gave it 4 out of 5 stars because of lack of ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Great System, But...</td>\n",
       "      <td>2013-12-18</td>\n",
       "      <td>0.727273</td>\n",
       "      <td>11</td>\n",
       "      <td>13</td>\n",
       "      <td></td>\n",
       "      <td>28.12</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A2QYAFX7OCNRMO</th>\n",
       "      <td>3</td>\n",
       "      <td>PlayStation 4 is kind of hard to review right ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Has potential...</td>\n",
       "      <td>2014-03-05</td>\n",
       "      <td>0.727273</td>\n",
       "      <td>11</td>\n",
       "      <td>13</td>\n",
       "      <td></td>\n",
       "      <td>28.12</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A3OQ3DU03L2GGO</th>\n",
       "      <td>5</td>\n",
       "      <td>Simply amazing. A huge step up from the PS3 an...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Stunning.</td>\n",
       "      <td>2013-12-01</td>\n",
       "      <td>0.727273</td>\n",
       "      <td>11</td>\n",
       "      <td>13</td>\n",
       "      <td></td>\n",
       "      <td>28.12</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A3H99DFEG68SR</th>\n",
       "      <td>3</td>\n",
       "      <td>So I've had the PS4 since launch and I have to...</td>\n",
       "      <td>1m2</td>\n",
       "      <td>I guess I expected more</td>\n",
       "      <td>2014-03-21</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td></td>\n",
       "      <td>28.12</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A15LG7HS4WKKKS</th>\n",
       "      <td>5</td>\n",
       "      <td>Huge overall improvement over the PS3. The use...</td>\n",
       "      <td>A. A. BADER \"Q8  AL BADER\"</td>\n",
       "      <td>Best purchase all year.,</td>\n",
       "      <td>2014-03-06</td>\n",
       "      <td>0.700000</td>\n",
       "      <td>10</td>\n",
       "      <td>13</td>\n",
       "      <td></td>\n",
       "      <td>28.12</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                overall                                         reviewText  \\\n",
       "reviewerID                                                                   \n",
       "A386ZNRX0TFFHX        4  I gave it 4 out of 5 stars because of lack of ...   \n",
       "A2QYAFX7OCNRMO        3  PlayStation 4 is kind of hard to review right ...   \n",
       "A3OQ3DU03L2GGO        5  Simply amazing. A huge step up from the PS3 an...   \n",
       "A3H99DFEG68SR         3  So I've had the PS4 since launch and I have to...   \n",
       "A15LG7HS4WKKKS        5  Huge overall improvement over the PS3. The use...   \n",
       "\n",
       "                              reviewerName                   summary  \\\n",
       "reviewerID                                                             \n",
       "A386ZNRX0TFFHX                         NaN      Great System, But...   \n",
       "A2QYAFX7OCNRMO                         NaN          Has potential...   \n",
       "A3OQ3DU03L2GGO                         NaN                 Stunning.   \n",
       "A3H99DFEG68SR                          1m2   I guess I expected more   \n",
       "A15LG7HS4WKKKS  A. A. BADER \"Q8  AL BADER\"  Best purchase all year.,   \n",
       "\n",
       "                     date  helpfulRate  helpfulCount  rank description  price  \\\n",
       "reviewerID                                                                      \n",
       "A386ZNRX0TFFHX 2013-12-18     0.727273            11    13              28.12   \n",
       "A2QYAFX7OCNRMO 2014-03-05     0.727273            11    13              28.12   \n",
       "A3OQ3DU03L2GGO 2013-12-01     0.727273            11    13              28.12   \n",
       "A3H99DFEG68SR  2014-03-21    -1.000000             0    13              28.12   \n",
       "A15LG7HS4WKKKS 2014-03-06     0.700000            10    13              28.12   \n",
       "\n",
       "               title brand  \n",
       "reviewerID                  \n",
       "A386ZNRX0TFFHX              \n",
       "A2QYAFX7OCNRMO              \n",
       "A3OQ3DU03L2GGO              \n",
       "A3H99DFEG68SR               \n",
       "A15LG7HS4WKKKS              "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "most_reviewed = reviews_count_per_product.index[0]\n",
    "most_reviewed_reviews = video_games.loc[most_reviewed]\n",
    "\n",
    "most_reviewed_reviews.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We try to see if there are any trends in the reviews over time:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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oAQAAYAEBNQAAACwgoAYAAIAFBNQAAACwgIAaAAAAFhBQAwAAwAICagAAAFhAQA0AAAAL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ejnj3C9Wk1Fs59SV59VV00H3KT9jrPqqNIQWVRG8mo8GFEobW74ey0fApNsl2lFxAR6fkoZRV5S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\n4UlzhQ3iubz8Tjdf1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VnYV5zUblgQVLimrP9HlXysNkDc8VEHDbi8y7vT1pg901cT92Y3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\nuc+40sDdsu9xkvcolK9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89Yy/cYe6bMT3lY34S0VqkSsRd/BAz0BdWRyUC53eLlPW9R6w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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x22cf033d438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "most_reviewed_reviews.sort_values(by=['date'], inplace=True)\n",
    "most_reviewed_reviews.overall.plot(kind='bar', figsize=(17, 8), rot=90);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It is impossible to visually see any kind of trend. However, it may be possible using machine learning to determine if some grades can be deducted from the previous ones."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Distribution of helpful rates\n",
    "\n",
    "We do the same analysis for the helpful rate (after removing the reviews without evaluation):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x22cf06b1cc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "video_games[video_games.helpfulRate >= 0].boxplot(column=['helpfulRate'], figsize=(8, 8), grid=False);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here, we can see rates are more widely distributed, let's do the same description as before."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    139855.000000\n",
       "mean          0.622347\n",
       "std           0.369065\n",
       "min           0.000000\n",
       "25%           0.333333\n",
       "50%           0.695652\n",
       "75%           1.000000\n",
       "max           1.000000\n",
       "Name: helpfulRate, dtype: float64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "video_games[video_games.helpfulRate >= 0].helpfulRate.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Distribution seems more balanced, since first quartile is 0.33, median is 0.69 and last quartile is 0.75. We may however do the assumption that helpful reviews are more likely to be evaluated as even more helpful as Amazon will display those reviews first.\n",
    "\n",
    "We now look at the distribution of helpful rates, considering all the sold products."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "60.34% of reviews are evaluated\n"
     ]
    },
    {
     "data": {
      "image/png": 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h+bPDpaUZvt4ztN+V5ElTqx81tN01TC9tf8g6VbUlyWOT3Le0H9395u4+obtP2Lp16zwO\nDQAAYL+2yNFQK8lbkny0u391atblSc4cps9M8s6p9jOGEU6PzmQgm+uGS1YfqKqThm2+fMk6u7Z1\nWpKrhrOVAAAArMGWBW7725P8UJKbquqGoe0/JLkgyaVVdXaSTyU5PUm6++aqujTJLZmMpHpOdz84\nrPfqJBcmOTjJu4dHMgmjb62qHUnuz2Q0VQAAANZoYWGxu/8iye5GJj15N+ucn+T8Zdq3JzlumfYv\nJnnpGroJAADAMvbJaKgAAABsLsIiAAAAI8IiAAAAI8IiAAAAI8IiAAAAI8IiAAAAI8IiAAAAI8Ii\nAAAAI8IiAAAAI8IiAAAAI8IiAAAAI8IiAAAAI8IiAAAAI8IiAAAAI8IiAAAAI8IiAAAAI8IiAAAA\nI1vWuwMAHJi2nfuu9e7CTG6/4IXr3QUAWBfOLAIAADAiLAIAADAiLAIAADAiLAIAADAiLAIAADAi\nLAIAADAiLAIAADAiLAIAADAiLAIAADAiLAIAADAiLAIAADAiLAIAADAiLAIAADAiLAIAADAiLAIA\nADAiLAIAADAiLAIAADAiLAIAADAiLAIAADAiLAIAADAiLAIAADAiLAIAADAiLAIAADCyZb07AADA\n/mvbue9a7y7M5PYLXrjeXYANx5lFAAAARhYWFqvqd6rqnqr6yFTb46vqiqq6bfh66NS886pqR1Xd\nWlUvmGp/ZlXdNMx7Q1XV0P6Iqnr70H5tVW1b1LEAAAAcaBZ5ZvHCJKcsaTs3yZXdfUySK4fnqapj\nk5yR5GnDOm+sqoOGdd6U5BVJjhkeu7Z5dpLPdfdTkrw+yesWdiQAAAAHmIXds9jdf77M2b5Tkzx3\nmL4oyXuT/NzQfkl3fynJJ6tqR5ITq+r2JId09zVJUlUXJ3lxkncP67x22NZlSX69qqq7ezFHBAAc\nCNxjBzCxr+9ZPLy77x6mP5Pk8GH6yCR3TC1359B25DC9tP0h63T3ziSfT/KE5XZaVa+squ1Vtf3e\ne++dx3EAAADs19ZtgJvhDOA+OQvY3W/u7hO6+4StW7fui10CAABsavs6LH62qo5IkuHrPUP7XUme\nNLXcUUPbXcP00vaHrFNVW5I8Nsl9C+s5AADAAWRfh8XLk5w5TJ+Z5J1T7WcMI5wenclANtcNl6w+\nUFUnDaOgvnzJOru2dVqSq9yvCAAAMB8LG+Cmqt6WyWA2h1XVnUn+7yQXJLm0qs5O8qkkpydJd99c\nVZcmuSXJziTndPeDw6ZencnIqgdnMrDNu4f2tyR56zAYzv2ZjKYKAADAHCxyNNSX7WbWybtZ/vwk\n5y/Tvj3Jccu0fzHJS9fSRwAAAJa3bgPcAAAAsHEJiwAAAIwIiwAAAIwIiwAAAIwsbIAbAABgvrad\n+6717sKKbr/ghevdBebEmUUAAABGhEUAAABGhEUAAABG3LMIMKPNcJ9I4l4RAGA+nFkEAABgRFgE\nAABgRFgEAABgRFgEAABgRFgEAABgRFgEAABgRFgEAABgRFgEAABgRFgEAABgRFgEAABgRFgEAABg\nRFgEAABgRFgEAABgZMt6dwAAWLtt575rvbuwotsveOF6dwGAveDMIgAAACPOLLLhbIZPx5PN8Qm5\nWgIAsFrOLAIAADAiLAIAADAiLAIAADAiLAIAADAiLAIAADAiLAIAADAiLAIAADAiLAIAADAiLAIA\nADAiLAIAADAiLAIAADAiLAIAADAiLAIAADAiLAIAADAiLAIAADAiLAIAADAiLAIAADCy6cNiVZ1S\nVbdW1Y6qOne9+wMAALA/2NRhsaoOSvIbSf51kmOTvKyqjl3fXgEAAGx+mzosJjkxyY7u/kR3/2OS\nS5Kcus59AgAA2PQ2e1g8MskdU8/vHNoAAABYg+ru9e7DqlXVaUlO6e4fHp7/UJJv6+7XLFnulUle\nOTz950lu3acdXZ3DkvzNendiP6Ke86OW86We86We86OW86We86We86We87NZavn13b11pYW27Iue\nLNBdSZ409fyooe0huvvNSd68rzo1D1W1vbtPWO9+7C/Uc37Ucr7Uc77Uc37Ucr7Uc77Uc77Uc372\nt1pu9stQP5DkmKo6uqoenuSMJJevc58AAAA2vU19ZrG7d1bVa5K8J8lBSX6nu29e524BAABseps6\nLCZJd/9Jkj9Z734swKa6bHYTUM/5Ucv5Us/5Us/5Ucv5Us/5Us/5Us/52a9quakHuAEAAGAxNvs9\niwAAACyAsAgAAMCIsLiCqjq4qt5XVQctM+8RVfX2qtpRVddW1bbdbOOZVXXTsNwbqqr2tH5VHV9V\n76+qm6vqxqr6/hn6OWtfzq+qO6rqC0vaf7KqPl1Vv77SvhZpab2r6syqum14nLmbdZ5TVR+sqp3D\n/96cZT/Lfk+WLPPdVXX9sNz1VfW8qXlXV9UXqmrDDo28ylr+VFXdMrzurqyqr59hP7PU8sSqumF4\nfLiqXjI1b8PXMll1PV811OaGqvqLqjp2hv2sWM+pZb9uqN3PTLXtt/WcWvf7qqpnOcYZX5/bquof\npl6jvzk1b8PXc5WvzbOq6t6pY/7hGfYz02uzqr65vvo37KaqeuTQvuFrmaz+tVlVpw+/P2+uqt+b\nYT+zvDZ/YOp7dENVfbmqjh/m7bf1rKrXTx3zx6vqb2fYzyz1/JqqumhY7qNVdd7UvP25nl83HN+H\navL3/d/MsJ9Z6vnwqvpvw3IfrqrnTs3b8PVcZS2/vibvj26sqvdW1VEz7GfZ997LLHfeUO9bq+oF\nU+3rW8vu9tjDI8k5SX58N/NeneQ3h+kzkrx9N8tdl+SkJJXk3Un+9Z7WT/LUJMcM0/8syd1JHrdC\nP2fty0lJjkjyhWXmnZXk1zdKvZM8Psknhq+HDtOHLrPOtiTfnOTiJKfNuJ9lvydLlnlGkn82TB+X\n5K4l89+b5IT1fo3OuZbfleRRw/SP7O51tIpaPirJlmH6iCT37Hq+GWq5hnoeMjX9oiR/Oo96Ti17\nWZLfT/Izm+m1udp6Dss+JsmfJ7lmlmOc8fW5LclH9rCNDV3PVb42z8pe/r6fsZZbktyY5FuG509I\nctBmqeUa6nlMkg/tmpfkifOo55Lln57krzbTa3O19Vyy/o9mMtr9PF6f/zbJJcP0o5LcnmTb/l7P\nTAZc+ZFh+tgkt8+pnuck+W/D9BOTXJ/kYZulnqus5e8nOXOYfl6St86wn92+955a5tgkH07yiCRH\nJ/mrjfK705nFlf1AknfuZt6pSS4api9LcvLST16q6ohM3jBe05Pv9sVJXryn9bv74919W5J0919n\n8sZ66wr9XLEvw/au6e67V9jWepqu9wuSXNHd93f355JckeSUpSt09+3dfWOSL8+ygxW+J9Pb/dBQ\n/yS5OcnBVfWIvT6i9bOaWl7d3X8/PL0myR4/MduLWv59d+8cnj4yyWYcWWs19Xxg6unXZoXjnrWe\nw7IvTvLJTF6bm9Fe13Pwn5K8LskXV9rB3tRzk1ttLWe2F7V8fpIbu/vDSdLd93X3g2vd/z62mnq+\nIslvDMuku+/Z0w5W+dp8WZJLZj+MDWOtr8+XJXnbnhbYi3p2kq+tqi1JDk7yj0keWGa5jWw19ewk\nhwzTj03y18ss8xV7Uc9jk1yVfOU1/7dJNuyZxGWsppZfOeYkV2fy/nuPZnzvfWomH2R8qbs/mWRH\nkhNnOIaFExb3oKoenuTJ3X37bhY5MskdyeR/Pib5fCafoi5d5s6p53cObTOtX1UnJnl4Jp8w7Mks\nfdnQlqn3V45pMF27tdjT92R3vi/JB7v7S3PY/8LNqZZnZ/Jp4p7MXMuq+raqujnJTUleNRUeN7y1\n1LOqzqmqv0ryS0l+bIVdzVTPqnp0kp9L8guz9H+jWW09q+pbkzypu98146725mf96OGSt/dV1XfM\nuP11t8af9e8bLh+7rKqetMKuZq3lU5N0Vb2nJrcH/PsVD2IDWUM9n5rkqVX1l1V1TVWtFIBW83fo\n+7NCaNpo1vq3qCa3Qhydr745351Z63lZkr/L5IqtTyf5le6+f4VtbxhrqOdrk/xgVd2Zyb+b+9EV\ndjVrPT+c5EVVtaWqjk7yzCQr/S7ZENZQyw8n+d5h+iVJHlNV83i/vaj3vGsmLO7ZYZl8SrIuhk92\n3prk/+jumc6abXLrWu/dqaqnZXIm49+td1/2wppqWVU/mMmng788rw5197Xd/bQkz0pyXg33MW0S\nq65nd/9Gd39DJuHuP86pP69N8vru3uP9DxvYXtezqh6W5FeT/PQC+nN3kq/r7uOT/FSS36uqQ1ZY\nZ6NY7WvzjzK5/O7pmXyCftEKy89qS5JnZ/KJ/bOTvKSqTp7TtveF1dZzSyaXoj43kzNh/7WqHjev\nTlXVtyX5++7+yLy2uY+s9e/6GUkum+PZ6ROTPJjJLT5HJ/npqnrynLa9L6y2ni9LcmF3H5Xk3yR5\n6/A7da1+J5NQsz3JryX5/zOp72aw2lr+TJLvrKoPJfnOJHdl8xzzqgiLe/YPmVwyl+QrN6jeUFU3\nDE13ZfgEZbik4bFJ7luyjbvy0Ev5jhra9rj+8EblXUl+vruvmaGvs/Rlo3tIvTN1TIPp2q3Fnr4n\nDzHcuPyOJC/v7pXO7m4kq65lVf2rJD+f5EUznEmduZa7dPdHk3whk/tAN4t5vDYvycqXmc1az29L\n8ktVdXuSn0jyH6rqNStseyNZTT0fk8lr5r3DcZ+U5PIVbvifqZ7DZT/3DdPXZ3Ilx1NnOpL1t6rX\n5nB56K6f79/O5IzAnsz62rwzyZ93998Ml7T/SZJvXWHbG8lqf9bvTHJ5d//TcAnZxzMJj7uzt787\nz8gmO6s4WOvvzlmPe9Z6/ttM7h3/p+Gyyb/M5rpscrX1PDvJpUnS3e8ftnHYHvYz6+/Ond39k919\nfHefmuRxmbz2N4PV/u786+7+3u5+RibvldLd8zjRsaj3vGsmLO7BcM3yQbvOgHT3zw8/EMcPi1ye\nZNdoSacluWq4tnt6G3cneaCqThruIXx5vnp99LLrD6fG35Hk4u6+bHp7VfVfamokySkr9mWjW1rv\nJO9J8vyqOrSqDs3kXpj37M02q+pjy+xnT9+T6XUfl0lgP7e7/3LvjmZ9rbaWVfWMJL+VSVC8Z8m8\ntdTy6OFDjF2XFX1jJgMLbAprqOf0m8UXJrltat6q69nd39Hd27p7Wyaf5v7n7l7XkYz3xmrq2d2f\n7+7Dpo77mkxep9uTNb8+t9ZXR8N7ciZv8j8xp8NdqDW8No+YevqiJB+dmrfqWg77enpVPWr4mf/O\nJLes7uj2vTX8HfrvmZxVTFUdlsmHDZ8Ynq+lnrvOqp+eTXi/4lr+rlfVN2Yy0Mj7l7SvpZ6fzmRQ\nklTV12byodNoexvVGur56SQnJ0lVfVMmIene4flafnc+aqhjquq7k+zs7k3x876G352HTZ2VPS+T\ns6u75q3ltXR5kjNq8t8Njs7k79B1a9je3AiLK/uzTC6lWc5bkjyhqnZkcunSubtmTJ19TCYjlf52\nJjer/lW+eh/Y7tY/PclzkpxVXx06eldAfXqSz6y2L1X1SzW5Zv1RVXVnVb12hePf175S7+E+gv+U\n5APD4xd33VtQVb9YVS8app81HNNLk/xWTe6L2/UHe3f/dmDZ70lVvaiqfnFY5jVJnpLk/5r6Pjxx\n3ge8QHtdy0wuO310kt8fjvfyYZm11vLZST48vBbfkeTV3f038zzYfWA19XxNTYbRvyGTn8szh2XW\nWs/9wWrquaw51PM5SW4cvk+XZXJP7aa5jymrq+WPDa/ND2dyL+1ZwzJrquXwBuxXh33fkMm93rPe\nY7pRrKae70lyX1XdksmgFz/b3ffN6Wf9OUnu6O5N8QHGMlb7s35GJgN+fOWD7znU8zeSPHp4n/CB\nTEbyvHEuR7nvrKaeP53kFcPP+9uSnDWcnFhrPZ+Y5INV9dFMbrX4obke6eKtppbPTXJrVX08yeFJ\nzh+W2W0td/fee8nvzpszOft7S5I/TXLOHC+/XpveAEPXbuRHJpfPrDgs7j7sz3sWuO2zsv7/OmNu\n9U7yPUl+bIF9fW829pDQaqme61439VTLzVRL9VRP9Txw6qmWsz22rJAlD3jd/cGa/DPMg3oDJPzu\nfsHKS+1uQam4AAAC/UlEQVS9qvrJJK9K8geL2P6s5lnv7v7jefVrqaq6OsmTk/zTovaxVmo5X+o5\nX+o5P2o5X+o5X+o5X+o5P2o54/6HtAoAAABf4Z5FAAAARoRFAAAARoRFAAAARoRFAA5oVfWFJc/P\nqqo9/t/KWZYZlntbVd04DCK2u2WeW1WrHhyhqh5XVa9e7foAsDtGQwWABaiq/y3Js7r7KXPY1pbu\n3rmb2Y/L5H+ivXGt+wGAac4sAsBuVNXWqvqDqvrA8Pj2ZZa5sKp+s6q2V9XHq+p7hll/luTIqrqh\nqr6jqt5bVScM6xxWVbevsO+zquryqroqyZVV9eiqurKqPlhVN1XVqcOiFyT5hmE/vzys+7NDf2+s\nql+YVz0AOLA4swjAge7gqrph6vnjk1w+TP8/SV7f3X9RVV+X5D1JvmmZbWxLcmKSb0hydVU9JcmL\nkvxxdx+fJFW1mr59a5Jv7u77q2pLkpd09wNVdViSa6rq8iTnJjluaj/PT3LM0J9KcnlVPae7/3w1\nHQDgwCUsAnCg+4ddQSuZnNFLcsLw9F8lOXYq6B1SVY9eZhuXdveXk9xWVZ9I8o1J/nYOfbuiu+/f\n1bUk/7mqnpPky0mOTHL4Mus8f3h8aHj+6EzCo7AIwF4RFgFg9x6W5KTu/uJ04zJnCXuF50myM1+9\n/eORM+7/76amfyDJ1iTP7O5/Gi5jXW47leS/dPdvzbgPAFiWexYBYPf+LMmP7npSVcfvZrmXVtXD\nquobkjw5ya3LLHN7kmcO06etoi+PTXLPEBS/K8nXD+3/M8ljppZ7T5L/c9cZ0Ko6sqqeuIr9AXCA\nExYBYPd+LMkJw0AxtyR51W6W+3SS65K8O8mrlp6JHPxKkh+pqg8lOWwVffndoS83JXl5ko8lSXff\nl+Qvq+ojVfXL3f1nSX4vyfuHZS/LQ8MkAMykupe7UgYAmEVVXZjJQDaXrXdfAGCenFkEAABgxJlF\nAAAARpxZBAAAYERYBAAAYERYBAAAYERYBAAAYERYBAAAYOR/AVQECOLiyDSYAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x22cf02e6048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# We get all the \"helpfulness rates\" (removing the unrated comments)\n",
    "helpfulRates = video_games[video_games.helpfulRate >= 0].helpfulRate\n",
    "\n",
    "print(str(round(len(helpfulRates) * 100 / len(video_games.helpfulRate), 2)) + '% of reviews are evaluated')\n",
    "\n",
    "plt.xlabel('Helpful rate')\n",
    "plt.ylabel('Count')\n",
    "helpfulRates.value_counts(ascending=True, bins=10).sort_index().plot(kind='bar', rot=0, figsize=(15, 5));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see two outsiders for reviews with less than 10% positive reviews and more than 90% positive reviews. This could be explained by the assumption made previously: the more a review is well rated, the more it is likely to get good rates. In the contrary, reviews with bad rates may be less visible on Amazon and may keep their low rates.\n",
    "\n",
    "We will now sort the reviewers based on their helpful rate mean, to see if there are some top reviewers or very bad ones."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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OGrmevyRHAB8C5gGnVNV7p7p2tvb8zWZ33PcAd9zbv8CczgPri2/8aPJe0Efr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\n13AAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x22cf2f3c1d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "count_evaluations = video_games.groupby('reviewerID').overall.count().sort_values(ascending=False)\n",
    "\n",
    "plt.ylabel('Reviews count')\n",
    "count_evaluations.plot(rot=90, figsize=(15, 5));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    24303.000000\n",
       "mean         9.537094\n",
       "std         12.789697\n",
       "min          5.000000\n",
       "25%          5.000000\n",
       "50%          7.000000\n",
       "75%         10.000000\n",
       "max        773.000000\n",
       "Name: overall, dtype: float64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "count_evaluations.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We try to zoom to get only evaluators with more than 30 evaluations. We can see that evaluations are done by a restricted number of evaluators providing the majority of evaluations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1st best evaluator: 773\n",
      "2nd best evaluator: 635\n",
      "3rd best evaluator: 456\n",
      "4th best evaluator: 450\n",
      "5th best evaluator: 404\n",
      "6th best evaluator: 320\n",
      "7th best evaluator: 272\n",
      "8th best evaluator: 268\n",
      "9th best evaluator: 224\n",
      "10th best evaluator: 220\n"
     ]
    },
    {
     "data": {
      "image/png": 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RiR2tpdQlSZIkqXmMZrVPw99BWrNlJz994HFueehxrrhpOQBzpnTyqT84jVMX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\niIiIEZDBX0RERERExAj4b1NdMEgP3bFxAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x22cf2b410b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "top_count_evaluations = count_evaluations[count_evaluations > 30]\n",
    "plt.ylabel('Reviews count')\n",
    "top_count_evaluations.plot(rot=90, figsize=(15, 5))\n",
    "\n",
    "print('1st best evaluator: ' + str(top_count_evaluations[0]))\n",
    "print('2nd best evaluator: ' + str(top_count_evaluations[1]))\n",
    "print('3rd best evaluator: ' + str(top_count_evaluations[2]))\n",
    "print('4th best evaluator: ' + str(top_count_evaluations[3]))\n",
    "print('5th best evaluator: ' + str(top_count_evaluations[4]))\n",
    "print('6th best evaluator: ' + str(top_count_evaluations[5]))\n",
    "print('7th best evaluator: ' + str(top_count_evaluations[6]))\n",
    "print('8th best evaluator: ' + str(top_count_evaluations[7]))\n",
    "print('9th best evaluator: ' + str(top_count_evaluations[8]))\n",
    "print('10th best evaluator: ' + str(top_count_evaluations[9]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We seem to have a power law here. We try to confirm this using a logarithmic plot:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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8o0zbSip0w0uzlVdUJklqnRqnCb8crqRYBtQBhJf6Pl3I/7sBCLiMlDhlpMTp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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x22cf27d0588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "warnings.simplefilter('ignore') # Ignoring warning about non positive xlimit\n",
    "\n",
    "count_evaluations.plot(logy=True, logx=True, rot=90, figsize=(10, 10));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We indeed have a power law.\n",
    "\n",
    "### Analysis of the more productive reviewer\n",
    "\n",
    "Focusing on the best evaluator, let's see if he provides well rated evaluations:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of reviews: 773\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "overall            5.000000\n",
       "helpfulRate        0.888889\n",
       "helpfulCount       9.000000\n",
       "rank            8736.000000\n",
       "price             29.990000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "best_reviewer_id = top_count_evaluations.index[0]\n",
    "\n",
    "print('Number of reviews: ' + str(video_games.groupby('reviewerID').get_group(best_reviewer_id).overall.count()))\n",
    "video_games.groupby('reviewerID').get_group(best_reviewer_id).median()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Comparing it with the other reviewers:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5.0"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "video_games.overall.median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6956521739130435"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "video_games[video_games.helpfulRate >= 0].helpfulRate.median()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The best evaluator seems to be a normal person, his `helpfulRate` is above to the median (allowing to believe he does not flooded the products with fake reviews). He also gave more than 50% of 5 star grades. We don't get a lot of information here."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Correlations\n",
    "\n",
    "We add columns `reviewLength`, `summaryLength` and `reviewerNameLength` to the dataframe to take into account more metrics."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>overall</th>\n",
       "      <th>reviewText</th>\n",
       "      <th>reviewerName</th>\n",
       "      <th>summary</th>\n",
       "      <th>date</th>\n",
       "      <th>helpfulRate</th>\n",
       "      <th>helpfulCount</th>\n",
       "      <th>rank</th>\n",
       "      <th>description</th>\n",
       "      <th>price</th>\n",
       "      <th>title</th>\n",
       "      <th>brand</th>\n",
       "      <th>reviewLength</th>\n",
       "      <th>summaryLength</th>\n",
       "      <th>reviewerNameLength</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>asin</th>\n",
       "      <th>reviewerID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">0700099867</th>\n",
       "      <th>A2HD75EMZR8QLN</th>\n",
       "      <td>1</td>\n",
       "      <td>Installing the game was a struggle (because of...</td>\n",
       "      <td>123</td>\n",
       "      <td>Pay to unlock content? I don't think so.</td>\n",
       "      <td>2012-07-09</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>12</td>\n",
       "      <td>6629</td>\n",
       "      <td>Dirt 3 is a popular rally racing game for Play...</td>\n",
       "      <td>246.63</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>779</td>\n",
       "      <td>40</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A3UR8NLLY1ZHCX</th>\n",
       "      <td>4</td>\n",
       "      <td>If you like rally cars get this game you will ...</td>\n",
       "      <td>Alejandro Henao \"Electronic Junky\"</td>\n",
       "      <td>Good rally game</td>\n",
       "      <td>2013-06-30</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>6629</td>\n",
       "      <td>Dirt 3 is a popular rally racing game for Play...</td>\n",
       "      <td>246.63</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>304</td>\n",
       "      <td>15</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A1INA0F5CWW3J4</th>\n",
       "      <td>1</td>\n",
       "      <td>1st shipment received a book instead of the ga...</td>\n",
       "      <td>Amazon Shopper \"Mr.Repsol\"</td>\n",
       "      <td>Wrong key</td>\n",
       "      <td>2014-06-28</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>6629</td>\n",
       "      <td>Dirt 3 is a popular rally racing game for Play...</td>\n",
       "      <td>246.63</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>282</td>\n",
       "      <td>9</td>\n",
       "      <td>26.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A1DLMTOTHQ4AST</th>\n",
       "      <td>3</td>\n",
       "      <td>I got this version instead of the PS3 version,...</td>\n",
       "      <td>ampgreen</td>\n",
       "      <td>awesome game, if it did not crash frequently !!</td>\n",
       "      <td>2011-09-14</td>\n",
       "      <td>0.700000</td>\n",
       "      <td>10</td>\n",
       "      <td>6629</td>\n",
       "      <td>Dirt 3 is a popular rally racing game for Play...</td>\n",
       "      <td>246.63</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>3489</td>\n",
       "      <td>47</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A361M14PU2GUEG</th>\n",
       "      <td>4</td>\n",
       "      <td>I had Dirt 2 on Xbox 360 and it was an okay ga...</td>\n",
       "      <td>Angry Ryan \"Ryan A. Forrest\"</td>\n",
       "      <td>DIRT 3</td>\n",
       "      <td>2011-06-14</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2</td>\n",
       "      <td>6629</td>\n",
       "      <td>Dirt 3 is a popular rally racing game for Play...</td>\n",
       "      <td>246.63</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>294</td>\n",
       "      <td>6</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           overall  \\\n",
       "asin       reviewerID                \n",
       "0700099867 A2HD75EMZR8QLN        1   \n",
       "           A3UR8NLLY1ZHCX        4   \n",
       "           A1INA0F5CWW3J4        1   \n",
       "           A1DLMTOTHQ4AST        3   \n",
       "           A361M14PU2GUEG        4   \n",
       "\n",
       "                                                                  reviewText  \\\n",
       "asin       reviewerID                                                          \n",
       "0700099867 A2HD75EMZR8QLN  Installing the game was a struggle (because of...   \n",
       "           A3UR8NLLY1ZHCX  If you like rally cars get this game you will ...   \n",
       "           A1INA0F5CWW3J4  1st shipment received a book instead of the ga...   \n",
       "           A1DLMTOTHQ4AST  I got this version instead of the PS3 version,...   \n",
       "           A361M14PU2GUEG  I had Dirt 2 on Xbox 360 and it was an okay ga...   \n",
       "\n",
       "                                                 reviewerName  \\\n",
       "asin       reviewerID                                           \n",
       "0700099867 A2HD75EMZR8QLN                                 123   \n",
       "           A3UR8NLLY1ZHCX  Alejandro Henao \"Electronic Junky\"   \n",
       "           A1INA0F5CWW3J4          Amazon Shopper \"Mr.Repsol\"   \n",
       "           A1DLMTOTHQ4AST                            ampgreen   \n",
       "           A361M14PU2GUEG        Angry Ryan \"Ryan A. Forrest\"   \n",
       "\n",
       "                                                                   summary  \\\n",
       "asin       reviewerID                                                        \n",
       "0700099867 A2HD75EMZR8QLN         Pay to unlock content? I don't think so.   \n",
       "           A3UR8NLLY1ZHCX                                  Good rally game   \n",
       "           A1INA0F5CWW3J4                                        Wrong key   \n",
       "           A1DLMTOTHQ4AST  awesome game, if it did not crash frequently !!   \n",
       "           A361M14PU2GUEG                                           DIRT 3   \n",
       "\n",
       "                                date  helpfulRate  helpfulCount  rank  \\\n",
       "asin       reviewerID                                                   \n",
       "0700099867 A2HD75EMZR8QLN 2012-07-09     0.666667            12  6629   \n",
       "           A3UR8NLLY1ZHCX 2013-06-30    -1.000000             0  6629   \n",
       "           A1INA0F5CWW3J4 2014-06-28    -1.000000             0  6629   \n",
       "           A1DLMTOTHQ4AST 2011-09-14     0.700000            10  6629   \n",
       "           A361M14PU2GUEG 2011-06-14     1.000000             2  6629   \n",
       "\n",
       "                                                                 description  \\\n",
       "asin       reviewerID                                                          \n",
       "0700099867 A2HD75EMZR8QLN  Dirt 3 is a popular rally racing game for Play...   \n",
       "           A3UR8NLLY1ZHCX  Dirt 3 is a popular rally racing game for Play...   \n",
       "           A1INA0F5CWW3J4  Dirt 3 is a popular rally racing game for Play...   \n",
       "           A1DLMTOTHQ4AST  Dirt 3 is a popular rally racing game for Play...   \n",
       "           A361M14PU2GUEG  Dirt 3 is a popular rally racing game for Play...   \n",
       "\n",
       "                            price title brand  reviewLength  summaryLength  \\\n",
       "asin       reviewerID                                                        \n",
       "0700099867 A2HD75EMZR8QLN  246.63                       779             40   \n",
       "           A3UR8NLLY1ZHCX  246.63                       304             15   \n",
       "           A1INA0F5CWW3J4  246.63                       282              9   \n",
       "           A1DLMTOTHQ4AST  246.63                      3489             47   \n",
       "           A361M14PU2GUEG  246.63                       294              6   \n",
       "\n",
       "                           reviewerNameLength  \n",
       "asin       reviewerID                          \n",
       "0700099867 A2HD75EMZR8QLN                 3.0  \n",
       "           A3UR8NLLY1ZHCX                34.0  \n",
       "           A1INA0F5CWW3J4                26.0  \n",
       "           A1DLMTOTHQ4AST                 8.0  \n",
       "           A361M14PU2GUEG                28.0  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "video_games['reviewLength'] = video_games['reviewText'].str.len()\n",
    "video_games['summaryLength'] = video_games['summary'].str.len()\n",
    "video_games['reviewerNameLength'] = video_games['reviewerName'].str.len()\n",
    "\n",
    "video_games.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before displaying the correlations, let's study how review's length are distributed (we only take into account reviews with at least one word)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x22cf2687208>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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XzdK5nSye28Wink6WzO1kybzGdheLy9cLujucqEaSJEmzmqFPtdbR3sahC+Zw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\nJjh4AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x22cf268df60>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "reviews_length = video_games[video_games.reviewLength > 0].reviewLength.sort_values(ascending=False)\n",
    "reviews_length.plot(rot=90, figsize=(15, 5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    231736.000000\n",
       "mean       1134.123628\n",
       "std        1567.258380\n",
       "min           3.000000\n",
       "25%         235.000000\n",
       "50%         576.000000\n",
       "75%        1373.000000\n",
       "max       32689.000000\n",
       "Name: reviewLength, dtype: float64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reviews_length.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we can see, 50% of reviews have less than 576 words and 75% have less than 1373 words."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We display the correlation matrix and scatter plot:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>overall</th>\n",
       "      <th>helpfulRate</th>\n",
       "      <th>helpfulCount</th>\n",
       "      <th>rank</th>\n",
       "      <th>price</th>\n",
       "      <th>reviewLength</th>\n",
       "      <th>summaryLength</th>\n",
       "      <th>reviewerNameLength</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>overall</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.133272</td>\n",
       "      <td>-0.086515</td>\n",
       "      <td>-0.103580</td>\n",
       "      <td>0.054490</td>\n",
       "      <td>-0.062702</td>\n",
       "      <td>-0.074934</td>\n",
       "      <td>-0.009812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>helpfulRate</th>\n",
       "      <td>-0.133272</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.121019</td>\n",
       "      <td>0.111745</td>\n",
       "      <td>0.024150</td>\n",
       "      <td>0.294168</td>\n",
       "      <td>0.176459</td>\n",
       "      <td>0.099486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>helpfulCount</th>\n",
       "      <td>-0.086515</td>\n",
       "      <td>0.121019</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.004194</td>\n",
       "      <td>0.007926</td>\n",
       "      <td>0.132578</td>\n",
       "      <td>0.056005</td>\n",
       "      <td>0.024202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rank</th>\n",
       "      <td>-0.103580</td>\n",
       "      <td>0.111745</td>\n",
       "      <td>-0.004194</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.044552</td>\n",
       "      <td>0.025594</td>\n",
       "      <td>0.024808</td>\n",
       "      <td>0.068894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>price</th>\n",
       "      <td>0.054490</td>\n",
       "      <td>0.024150</td>\n",
       "      <td>0.007926</td>\n",
       "      <td>-0.044552</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.018523</td>\n",
       "      <td>0.021714</td>\n",
       "      <td>0.011590</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>reviewLength</th>\n",
       "      <td>-0.062702</td>\n",
       "      <td>0.294168</td>\n",
       "      <td>0.132578</td>\n",
       "      <td>0.025594</td>\n",
       "      <td>0.018523</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.309684</td>\n",
       "      <td>0.098276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>summaryLength</th>\n",
       "      <td>-0.074934</td>\n",
       "      <td>0.176459</td>\n",
       "      <td>0.056005</td>\n",
       "      <td>0.024808</td>\n",
       "      <td>0.021714</td>\n",
       "      <td>0.309684</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.094540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>reviewerNameLength</th>\n",
       "      <td>-0.009812</td>\n",
       "      <td>0.099486</td>\n",
       "      <td>0.024202</td>\n",
       "      <td>0.068894</td>\n",
       "      <td>0.011590</td>\n",
       "      <td>0.098276</td>\n",
       "      <td>0.094540</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     overall  helpfulRate  helpfulCount      rank     price  \\\n",
       "overall             1.000000    -0.133272     -0.086515 -0.103580  0.054490   \n",
       "helpfulRate        -0.133272     1.000000      0.121019  0.111745  0.024150   \n",
       "helpfulCount       -0.086515     0.121019      1.000000 -0.004194  0.007926   \n",
       "rank               -0.103580     0.111745     -0.004194  1.000000 -0.044552   \n",
       "price               0.054490     0.024150      0.007926 -0.044552  1.000000   \n",
       "reviewLength       -0.062702     0.294168      0.132578  0.025594  0.018523   \n",
       "summaryLength      -0.074934     0.176459      0.056005  0.024808  0.021714   \n",
       "reviewerNameLength -0.009812     0.099486      0.024202  0.068894  0.011590   \n",
       "\n",
       "                    reviewLength  summaryLength  reviewerNameLength  \n",
       "overall                -0.062702      -0.074934           -0.009812  \n",
       "helpfulRate             0.294168       0.176459            0.099486  \n",
       "helpfulCount            0.132578       0.056005            0.024202  \n",
       "rank                    0.025594       0.024808            0.068894  \n",
       "price                   0.018523       0.021714            0.011590  \n",
       "reviewLength            1.000000       0.309684            0.098276  \n",
       "summaryLength           0.309684       1.000000            0.094540  \n",
       "reviewerNameLength      0.098276       0.094540            1.000000  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "video_games.corr()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We plot the scatter matrix for each columns to avoid to fall in some bias (e.g. Simpson's paradox) by just looking at the correlation table."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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CoVAoFIPkjTEIXAFcBkQBpJQtQCCnEuUpb+zuBeD19+CrFE0qY1ChUCgUCsV+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\nDgR9CmGfSk/aoGA6FAybTInF4soQPo/CxY2lLKkKc3mTq43Xm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GE+p3LGGTIEAb7+B5ew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fdpqopg/bwZzifPS658hYA1Ew6Mpjk4libktnPTsjqe2DNK2ZDEsiVMCUirp1vKk/NQvlzZ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\nLEj4Is4tg8kCX/55J1JKPvPmDXTUhaomR5MpmeeYGkzHR25eyZPHR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TAsEnkdVQG7HEh6\nqixlVw07ur8BviGlPLbQx5oNiav/87bMPGM48OTxUdY0hPB71FmVdZa5PJPyCqqAY4NpVtSFGEoV\nsR3JSLrEN5/v5vhwhoJh0xD2srd7AsN2aK8N8vn7NrGtLXrBPifyrpRIe22A7e0X/vtSYH1zDW21\nAfZ0TzCUKlQCwKJp8dl7NmDYDhM5nf/9+CnAleRZ1zh9f6XjSLK6RcR/bvCRKZkEPepls68Fw0IR\n4orRfqwJauR1G8OWFMZyeBS3BzNZMMnpFjesihH0afxwXz/posmOjlqaIn6EcPssRzMlNEXwzMk4\nq+pDbGmtYUNzkxsYXqKBv2ssR9dYjh0dUVpfo6pATrdm1S84yZqGEOubwjxx7OoJBrOGWXXnjcXA\nzfZrBH0aI7rN7s44axtC+DTXAg+grba6PYPVqLscB74uhNgjhPiUEOKKuCPPXmVwmdc7kxZB0ZCH\n99/Q4WYRSsurivli8gEd8ClEQ14awh6iAQ/1IS9HB9P85NAwL3dPMJQsktdt0kWLvG6RzBsMXEQD\n9KkTYxwbyvDEsVHSxaX5uxrLlDjQl2IgWSBrnO2nKpkOIZ/GiliQoE9FVdxAWgjBeM5gX2+Sp06M\nVqzYAB4+NMQ/P9fNTw4PV157oWucb+zu5nt7+7Au0a91Jp7j689288/Pd087gbsYaIo72AVutkW3\n3AlPw5bEszqDqSJbW2voHs/TO57n1EiWd13bxp2bGl0v57zbW1gb9GLYDg+8OsDDB4fon7i4pqxl\nOzx6eJjjwxkeOzLymq8hW3IzmnPh3q3N7OmeuECSaKmyojZ4xSw0FhobQEDBMOkczfHEsRGmymIe\nGqxuz2A1dAb/SUp5O6624GrgkBDiu0KIuxb62MssM9/UBjXu29rMDatiPPDqAP+0u5unTizr/cwH\nUoJHUagN+BicKPLE8TjposmJ4Qx7uifIFA1SRZNoUOO2dfW8d1cbm1sibGuLcMNFHCImLcL8HnXW\nPVlXCpmCwS9OxRlKFtnSfDbjJ6AifL67M0FN2T0j4FH41os9PHsqzsH+NC90JSo/01tuSu+d0pze\nW5YnGc8Z5PWLNzv1J4sYlk1BtxlOL74AP0A8Z6EqgqBXxe9RCPkEWjkoRrge13u6J8jrFjnD4thw\nhm++0ONKGTmSupCXa9ujrKwLksjpNNf4kRL6LiHZoghRqQrMRyk5p5szlpU5n3u3NmM7kqdPjr3m\n87gSiGf0Jbtomy3Zgs6xoQxZ3aFoOuw9b4q62lO2ValzCSFUYHP5zzhwEPicEOKTUsoPVeMcllnm\nteJT3abenx4ZRVNVhtNufvlMPM/dV59NaNWRgO04jGRKCOnKpCholCwHr2HRVhtgdX2QkNdDbdDL\np9+0ntFMiY664EVtue7e3MT6pjD1Ye+SzTgYJiTzOh5VYWTKZZoOrK53BwfGczqxkI90ycSwbA4P\nprluZQzbkecEGm/c2MjRoTQ7VpztKbxtXT3PnorTURckGrx4cFMf9NI5liPgUWm8giaVTcvBoyoo\nQqBbkrBPo6HGi2FKNFVweCBDpmhilj2MbcdBUxQCHoXDg1nGswaRgEZj2BWprg16uf4iiwsARRF8\n6KYORtIlVsRe++BGqmDOeT87V9TSWOPjiWOjvOe69td8LovNvr7kjN2nljqJgn1OwDeRvzAI3tdb\nPZmdavQM/i3wTuAp4C+llHvL//RFIcTJhT7+MsvMF2GfhpSgWw5PHh/lfdevIJ7VuXFNXWWbomGz\nrzdJXchb0YBbZuaYDtiGDdItG2dLJrYEgUrQq7GqPogiBA/tH6CxxnfZPkBVEaxpcIdL0gWTkG/6\nvjgpJaYt8V6B2cMSgCUpWvY5mTsJfOvFXn7t9jXct62VRw4OYTqQKdqsrPXxoZs6yOt2JWAE2NlR\ne8FwiVouK2dLFte0Ryt+x+eTKBhsaqlBAPGcTlPkyhBdNxwwnLPlbatoUTJtYkEPilAxLBuQaAo0\nhn1saokwmi3RNZoj7NNQFcFgsshEwWDXyhgfvnnVJfsFwfUwXnuRvszZMpbVL+p9fDkURXDPlmZ+\nfGAQ3bLxaUtzwTNJ2+tIyH8mAjrVdF1a0GBQuB3KE8BOKeV0Ks83LeTxl1lmPnGAOzc1MpgqsbIu\nyK3rGgh5zw0unu2Mc2zILd3Vh700XyEPzKVExRxInp2sK5oO4zm3hNSTyOE4cHQow5fefy3XrazD\nsp2LDj84jsPvf/8gz3WN0x4L8A8fvZ6WKU3/jiP54asDDCaL3Lau/oqWDDq/iPv0iRH29yVZ3+QO\n20xuc3Aww3+8OsCHblzFseEM6aLJ9ati+DQVKSWOdAPlbMnkfzx8lP39SVojAW5aU3fRYLA+5OXk\nSAb/JTKDtiPZ35dECMGulYsz0ewAliNJl2yiAYHPo6IqCtvbo3z45lXcvLaO777UR0PYS7Jgsq21\nhs7RLMFyYDiSLl02GLwcRwbTZEpn3/OLYdoOE3mDppq5Z1rfuq2Z7+3t4+kT8QV3S1lopHx9ZAWn\n43wNPoCbpiQaFpoFDQallFII8QEp5Z9f5N/TC3n8ZZaZT/K6xYdvWoVHU4gFvTzXOc6p0Sy7VsV4\n08ZGgEopUlUE3tepLt5CYDuSbMkkq9uUNXoZzpQ4PpwBKfhFZ5yWiJ/3Xb/igqAwXTR5rmucdNGk\naNo8czLOh6ZoeuUNi8HyAMqpsdwVHQyez/HhHH5vgX19KaaYIHByNEdtaII1DSGODGYQQqBbDres\nqed7e3vJ6TbvuLYV25F0jxfIFi0Mq3DJgahE3mBLq5uJjed0GsI+zoznGc2U2LUyRsCrcnAgxe7O\ncQD8nsX5/AvAoyrU+DRW1oXoTeQJeFWEcL+Xf/P4SQ72p1AUhXfvaGXvmQl02yZdMMkUDV4I+1hV\nH5pzlrh/osATx9w+YsNyuHNT00W3Hc+5EwNNNXNfNN6xvoGmGh8/eKV/yQeDB/tfv7YKqnCHn6ZS\nTcmsavQMviqEuFFK+XIVjrXMMguGYcOXnzjOzesa2bUyxqnRDCA4MZypBIN3rG+gOeIjFvQSq7Kd\n0NWM208ocab4teV1m58eGeGhA8Nsaq5BSjfwqwt5z5FNCXg1mmp85HSLkE9jU/O5Eqg1fg/XrojS\nPZ7nxtVzK9ctFn6PQsFwON9q3bYdFAGv9CQ5NJBibWMNPlXhh/v6eezoKC0RP52jOW5aEyNV0N0+\nLeG4UzwXYVtbhL5EHq+msOdMgq881cVAskDQp3HP5mZ+841rzxnSWayBnYhPwXTcKeP7d7TwrRf7\nMG2JRxGcHstxaiTHaEanJeLniWNjpIsGuuWwrjHMppYIE3mDibwxZ+9xn6YghPtWXi6gjJfHRxtf\nQ2ZQUxXed/0K/uEXpxnNlJZ0NWLq5PvrjfMDQaju+1GNb+vNwItCiNNCiENCiMNCiEOz3YkQYrUQ\nYlQI8YwQ4vHya38ghHhOCPEdIcSyP9gyC85TpxJ88/ke/v7pLsYyOkXT4obVZ1P5qiLY3BJZ0jfk\nK5VkwcI474Z5sC/FeLbEQKrA5pYaBpJF/u6pLh7YN1DxpPV7VH7jjrXcvr6B9+9qZ33zub1eXWNZ\naoNefuW21WxuWVp9nrGQj9aoH+95d3JVEWhC4cRIFt2WFA2LkyNZTo1kiQY8ZHWLa1dEGc8ZeDQF\nteJtfO5+siWTPWcSDKeLxIJetrdHWd8Y5onjY/QnCwykSkgJI2UHj62tETY2h9naGrmo1uFCIXCl\nZvKmRLccsrrFIwdH2NlRSyzo4fpVdaxpDOHRFBprfHhUwao6t13AsiU3r6kjGvCwrin8moKzpnKG\n+r7tLdyy5tJZ5rHMZGbwtQ3kfOCGDhy59L2Kr19dvbLoUuDnx6s3JV6NzOBb53FfT0gpPwoghGgC\n7pJS3iGE+EPgPcAP5vFYyyxzAQpQMm3OjOUYz+rcuq6B1tdR0/Nicv7CWQIZ3caRJTY0hxlIFhlI\nuiLVfRMF0kWTiZzOd/f2cXwoQ7JokimarDw8wgdudK3ahtNFHj7oau7ldKuS4V0qNIS9eDWFfMnE\nKJ2N5AxLMpYruVPGQS+HBlIMpUtYjsO9W1vY2VFLW22AkmnTGPYRz7q6gY8cGiRnWLx7ZzuqIvjp\n4REGU0Ve6U1yTVuEb+/pRVMVIj4NAWxr9bK+KVx5P5/vGufvnupCSknYX91hBglYDqjC7YnM6zYH\nB1L0TRQI+zR6JgpoqsLv3r2eEyNZrmmPsq4pxH9/8Ai2lAgh+M03rJ2Xc5npdPDYPGQGAVY3hLht\nXT3f3dPHJ9+4dslaNzbV+PGqZ4WXX+9UU8JpwYNBKWUvVIK31/rUvEsIsRt4EDgJPFN+/UngIywH\ng8ssMCGf2y/oZp0Eo5kSqYJB2xRbupF0iaF0kS0tEQLepT3dtxQQQlDj99A1lmN1Q5DeRIGCYfLf\n/+MQPRNFfJpCPKuTKZlkS1rFhxZATPH/nI0lqu1IHj44xGCqyJu3XLwnbKE5OZLl2hW1nG/bYAOO\n7VQ080qmQ7JgsrI+yKfetK6ynd+jsrmlhv5kEUW4k/K9iQLJgkHE7+H4SIaxTIkNzTU8dXKMo+Xh\nqNX1QfKGzXt2tp/jfvHTIyMMJl2NvocPDi38GzAN6mQnvgDDdMiUTIqGjdGXJJ4p8cEbOnjTxkZ+\ndmSEH74ygNejkiwYDKWKHBpI8VzXOC0RfyUgng+yJZNTozlW1Z8bJE6WiRvmQarnV29bzSe+tY8n\nj49y3/bW17y/amPaDg8fGFwOBKdQTZerakjLvAv4G6ANGANW4bqSbJvlroaBjYAOPATUlPcHkAZe\nH2acyywq6aID6AS9Gg1l/9JfnBpnc0sERREUDZsf7uvHtCX9EwXevXPpa39d6RQMm5FUCRSB3ytQ\nFHf6+Hg8jy0lkYCH2qAHTXEnSzvqzgbuLVE/77munUzRZNsspIDGczo/OzJCVjcr5ejFwLQdLNvB\nnMY5pMbvoWRJUgW3J04gsWyHA/0p1jSEiAY8DCQLdI3lcKQk4NFYWR9idUOQWNDL40dHODqUIV8y\n2doaYXVDiFjQiyMlPYkCihD87MjIOcHgNW1RHjs6gpRyUaSVFOHKvoT9GumCiW47+FRBwKswmikx\nltX5s0eO8tfv28GJkSzg9l02hH30JAo8cmiIgEejN1HgiWMjnBnPs60tetGMcf9EgVTBZEtrzbTZ\nOMeR/PTICA8fHKIu5KWj7txgcCxboi7knRdJozdvaWZFLMA3n+9ZksFg0XT1MZc5y8aWmstvNE9U\nI+z8c+AW4Ekp5XVl55GPznYnUkodNxBECPEIkAEmn7QRYNoxJCHEJ4BPAKiRpVUCWubKQwI53Sbs\n14iFPMSCXiSSs2oostKD77yOZRKqiS3dKeD33bCCM2N5CqbFYLJATUAj5NN42/ZWtrXV8KP9QwgB\nG6cMkOiWzcvdCV7uSdIY8fGOa1qn9Ti+AOn+fh1HLurv2XGgM54lb1wYDGZKFjV+tSLia9iS3kSB\nv3jkGI01Pv7o7Vv42rOnOT6cRbccvKrC+3atYFOrG8RZjkMiVyJXsknkdd59XTv7+1IEPCrHRzIk\ncgZ15w1J7VpVyw2r6gDJte3VX5+XE/ZYjsTrUfF7VRwpSeZNipZEIDk8kCboVdnQHOb0WI722gCP\nHxuhNRrAkRKPKmiO+Dkdz2FYrlTOGzc0nDOUBO6C4IFXB5ASEnn9gqnhsUyJztEcx4czGLbNaKZE\ne+xcH+N4Vp83AW9VEXz81lX85aMnODaUWXI6p5qikCvpl9/wdcS3nuuu2rGqEQyaUsqEEEIRQiq5\nd/AAACAASURBVChSyqeFEF+e7U6EEDVSymz5f28H/g74MPAl4B7gpel+Tkr5NeBrAL7WDctP52Ve\nM6qA29Y28t7r2hGKaxg/WU4KejXeu6udwWTxsoLIy8wfkYBGjU9ja1uEl84kaKrxs2tVjFvW1FMf\ndvva/B5XR25L69mH5C9OxvmP/YMk8gYbmmp4tS81o2CwPuzlnq3NjKRL3L158crENq7I9HQMpgqs\naQjh1xRM28aRkNVt9vUlK8VxVREYtoODK7ETz+lsKv/b9avqKJkOliM5Hc/TNZajxqehqQq3rK6j\nd6LA+3at4HQ8x9MnxmiNug4xm8rZjJmI6i4EuZJFrmTh86h4VFG+BvdsJBALehBC8M5r20gXTP7v\nU6ewHegZL3D7+oZK3+Czp+K82pdka2vkgkAQ3FaByXXA+dnhvG7x/Vf6MSyHbMlkU3OEFbEA92xt\n5ptTthvL6jRF5s/N5YM3rORvn+jkX17o4Yvvu3be9lsNLMdB01QuVNN8/fJ0WaapGlQjGEwJIcLA\ns8B3hBBjwHQC1JfjDUKIP8fNDu6WUu4RQjwrhHgO6ANmHWAus8xs0YAVdUF+9+51ZHWbtY2hC2zO\nVsSClQbyF06Pc3w4y/WrYhc4PywzP6gCCrrFY0dHuXVtPSXTRlEEjiN5sTtBpmiyuiHEmbEc65rC\nru1a2VO2b6KAR1VwHEk0oLFlhmUZVXG7DfO6ueiex9OJ1YI7fe3E8wS9KtkpziWOLA9CWTZhn1aR\npdFN5xx5CQXXh9ejChwJZ+JZHjk0jCJkRYfvsWMjrK4P8dKZBDV+D3/8zs001fgomTY7V1T/865w\nVqLDMmy8KgS9KqalgHSIBjRuXFNH/0QBw3ZYUx+iOeKnLuRlZV2gEsiCa933hmkygpM0R/y889pW\nJvIGO88T2LalxHbcftZdq2K0Rv188/keOsfOdZSIZ3XWNsyfllw06OG9u9p5YN8Af/i2zRdkbq9k\n/JqKkPPTo3m1UE0R7moEg+/GdVT6LO6QRxT4n7PdiZTyUeDR8177IvDFeTjHZZaZEaoCqxuC/OtL\nvZi2pCHs5bfvWn/RzMGeMxMA7DmTuKKDwee7XAHtm9bUzaxMegVhSxjO6KSKFkPJPKbjig63R328\neCaJ5ThlT1rXt3ZtY4i7NzcDsL09SrZkcvPaet57XRtttTObAu1N5Pmn3WcomU5FHmQxUIV7/dMh\ngWzJwpgSrCrC7ZELeTV+7+71vNqXqkxT2xK+vaeXzW1R6kJejo5kiAQ0+pNFNjSFeL4rgeU4SMeh\nf6JIyKfi96i0Rv3oloNm2rx4eoIflwdHGucx4zVTHNyAcDIradgQURSuX1uL36NSsm1W1Ab45vPd\n6JbDe69r5xNvXMet6+op6DZbWyOcHMnSWusn4ncziOmCyUimxJqGC4WoN5ynWWlYDo8eHianW9y+\nvh7DctjRUctfP3ayol84iZTSLRPP8/v0q7et5rt7+vje3j5++67187rvhcS0HWIeFXj9ag2eTzVb\nUBZ8SSulzEspbSAIPAx8m+kXssssc8UjFMHBvhRPnRjluc44r/Qm2dM9Me22qiJY1+RqrW1srl4j\n8GzRLZu93ROkCiYvnZn+Wq50HOkOkozmzIrTyFDa1YHM6RbZkkXBsEnkDc7EzxYmbllbz81r3If2\nD14ZZCxbusRRzlIybPK6hW475BdRKPdyzwpVEUjcoFFTwKsq1Id8XL8qxnje5AevDJxzM97fN8H3\n9vZRMCwKJYveRIFcyeLHB4YqzeyaqrCxOUx7bYC1DWHWNYZZ3xjilrWuLWA8qzOWLRFfpCA56FWo\nLcvaKLhBlxSwqj7IcKrEv77Yy8+Pj9E1luPxo6N0jmZZXR/i5rX1/OTwMN9+qYdvvdiL7Uhyuskf\n/+gwX/rZCX64r/+yx+5J5OkezxPPutaJt61vwKMqCNyScMh3toqQLpoYtvOa3EemY2NzDXduauTr\nu89c0lHmSsNyJBO55Z7BqTSGq5fZXfBgUAjxSSHECHAIeAXYV/7vMsssOUqW26HuVd2syIam8CVV\n4t+1o43fumsddy1iX9nl8KoKK8tTjusaq2d/NN9MBjWOBMOyWV0fRLccLFviKwsr1wY9FM7TrtDL\nk7iOlJSmGcSYjomCSSzoQUXyju1t83kZs+JyZ+v3KAQ0pRwQCkzboWBYnBjJ8viREYbO0zHL6Sam\n7WBakh0dteiWK0+TKVn4hDtc4dUU6sNeVFVhIOlar2VKFobl0Bbzs6o+SEcsyPqmxVkANYR9rKwP\n4dNcxZ1k0eLoYJrdXeNM5A1M20EIaK/1E8/p/PNz3fzBDw7xcneCl84kODWa45WeCRwp6RrNMZbV\nied0jgxmLnvslqifcNnjeHW5/NubyBMJeLhvWwsfuKGjsu18uI9cjN+/dxOpgsk3qjiA8FpxHEl2\nOSl4DmubqifcXo0y8X8Ftkspq9cJucwyC4imwnUra7lnawuaIipm4lJKnj45xlhG502bGmmNupOD\nlzKqvxIQQvBLu9opmc6S1kUMamAjsGyJV1UomDYNYR/JvIHE1eyqC3q57rz+rlvX1nNyJEu6YGDP\nsCwTz5VIl2wkglf7kwtwNfODIyWT8a2iCHyKQFMEjTWum8iLZ8ZJF88+gVfGQrxteyvRoAe/R8FX\nHj4JeTVe7k2720pX37A+7CNpWNSHfShCYNqSWMCL5UgsW9IarX6ZGCBdMkkWTSynvECQVNoENFXB\nsh3u3tzA9vYoPYkCB/tT2FLyi1NxLMehZNqsawyhlQO6WNBDKmEihDsYEvJpvHg6Qfd4nlvW1rF2\nitNKxO/h125fjS1l5XvfHPUT8qkoQrB+ysN9UnD6tbqPTMc1K6Lct62Ff9rdza/cunpJWGM6XLz/\n9fXKyZHc5TeaJ6oRDJ4GClU4zjLLVAXTclhdH+ING9wS0CSjGZ2D/a5O1t7uiYrGYDyrI6Wk6Qq2\nqBNCLOlA0K8KfvQ7t/HAvmG+/0o/qipoDPvY0lLD/v4U6YKJlJKcYVeyoOAGCY8dGWFfzwRrGsM8\n3zXOmhk09G9qjmDZNqbj6vhdqUjpDjM40hWUDnlVNjTXcPOaOt6yrZmusSz/+lJfZfu6Gl9liGIo\nVcQjBD5NEPQpDKZLlWGTVNEk4NVoifh557VtCGBNY4gXOsfZe2YcCTywb7D6F4w7OCM4G1h4VIHt\nQCKnE/apeBSVsUyJ/Y6kxudhZV0QTXXF5IumjUCwsdmdIK4NennLthZOj+XQVAXdcgCLx4+O4NMU\nbCnPCQbBLaNPfbC6AeIabEeeM2y2kJlBgM+9ZSOPHRvhq784zRfevmVBjjGfBDwKhpjeo/f1SlGv\nXqq0GsHgfwNeEELsoawTCCCl/L0qHHuZZeadomnzbOc49WEfb7+mtRJE1QY9RAIeMkWzIi7blyjw\n4H5Xi+z+Ha2LVjq72inZkp+fGGcgVcByHDyaym3r6/n7p1IUDBsh3IyYlJITIxlW1bsBX08iz0MH\nBtjbnWR/X4r/+tZNlzmSS9ivIYTAtNyA8ErEo8LNa+p45pRblJm0aEvkDA4PptnaFiWeOzeQ9Sln\nFzdn4jmKlo1ly7LV29midMiroqmCVQ0h7t9xtkz+hQcPMzm4/MSxkYW7uMsgqZiQoCkQ8mmEfSrj\nOR2hCPb2JGmO+LlnazNvu6aDdU1hFODfXu4n7POwa9XZ7PGbNzdT4/fQUp46fqFrnN5EgZJls6Ut\nQv9Egdao/5IWcB5V4TzRgUp/6kJkBsHtHfzA9R1847lu3nFNKzuu4AE2cC0Ur9Cv0qKRucqCwX8E\nngIOM6XFRQjRCPxnYPXU85BS/noVzmmZZeZMwZQcGUqxvT3CkaEgN5bN1f0elY/fuoqiaRPxu9Il\nyYJRafJPFpZOM/dS5F9f6CZdNCvBCwhG0kUsR6KpgrqQj3WNYYZSZ4dE3P65HEXDRrccnj4xxodu\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KkIegV6e5cjKwbSoP0FYdIpEzuXdDzZwD+FVThmkUdXkWuATgUQW587rQvZqCqipEvB6C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      "text/plain": [
       "<matplotlib.figure.Figure at 0x22cf25c9278>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pandas.tools.plotting import scatter_matrix\n",
    "\n",
    "axes = scatter_matrix(video_games, alpha=0.5, diagonal='kde', figsize=(10, 10))\n",
    "corr = video_games.corr().as_matrix()\n",
    "for i, j in zip(*plt.np.triu_indices_from(axes, k=1)):\n",
    "    axes[i, j].annotate(\"%.3f\" %corr[i,j], (0.8, 0.8), xycoords='axes fraction', ha='center', va='center')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- There is some correlation between between `reviewLength` and the `helpfulRate`. We can think that more the `reviewLength` is high, more the review can contain more descriptions and arguments, so it can increase the helpfullness.   \n",
    "- Then, the `summaryLength` and the `reviewLength` seems to be also correlated. The more the review text is lengthy, the more the summary needs letters to summarize it."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Serialize video_games using pickle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "\n",
    "with open('pickle/video_games.pkl', 'wb') as output:\n",
    "    pickle.dump(video_games, output, pickle.HIGHEST_PROTOCOL)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Words occurences\n",
    "\n",
    "To do our `reviewText` words occurences, we will use the product which has the most reviews \"PlayStation 4 500GB Console\"\n",
    "\n",
    "### Unigram\n",
    "\n",
    "We print the top 10 words for each review grouped by the overall score."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Score 1</th>\n",
       "      <th>Score 2</th>\n",
       "      <th>Score 3</th>\n",
       "      <th>Score 4</th>\n",
       "      <th>Score 5</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ps4</td>\n",
       "      <td>ps4</td>\n",
       "      <td>ps4</td>\n",
       "      <td>ps4</td>\n",
       "      <td>ps4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>sony</td>\n",
       "      <td>games</td>\n",
       "      <td>games</td>\n",
       "      <td>games</td>\n",
       "      <td>games</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>console</td>\n",
       "      <td>ps3</td>\n",
       "      <td>ps3</td>\n",
       "      <td>like</td>\n",
       "      <td>console</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>just</td>\n",
       "      <td>sony</td>\n",
       "      <td>sony</td>\n",
       "      <td>controller</td>\n",
       "      <td>controller</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>xbox</td>\n",
       "      <td>console</td>\n",
       "      <td>like</td>\n",
       "      <td>game</td>\n",
       "      <td>ps3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>amazon</td>\n",
       "      <td>just</td>\n",
       "      <td>just</td>\n",
       "      <td>ps3</td>\n",
       "      <td>game</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>games</td>\n",
       "      <td>play</td>\n",
       "      <td>console</td>\n",
       "      <td>just</td>\n",
       "      <td>like</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>34</td>\n",
       "      <td>like</td>\n",
       "      <td>game</td>\n",
       "      <td>console</td>\n",
       "      <td>xbox</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>work</td>\n",
       "      <td>does</td>\n",
       "      <td>play</td>\n",
       "      <td>sony</td>\n",
       "      <td>great</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>like</td>\n",
       "      <td>really</td>\n",
       "      <td>controller</td>\n",
       "      <td>better</td>\n",
       "      <td>just</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Score 1  Score 2     Score 3     Score 4     Score 5\n",
       "0      ps4      ps4         ps4         ps4         ps4\n",
       "1     sony    games       games       games       games\n",
       "2  console      ps3         ps3        like     console\n",
       "3     just     sony        sony  controller  controller\n",
       "4     xbox  console        like        game         ps3\n",
       "5   amazon     just        just         ps3        game\n",
       "6    games     play     console        just        like\n",
       "7       34     like        game     console        xbox\n",
       "8     work     does        play        sony       great\n",
       "9     like   really  controller      better        just"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.feature_extraction.text import TfidfVectorizer, CountVectorizer\n",
    "\n",
    "def get_top_words(text_series, ngram):\n",
    "    word_vectorizer = CountVectorizer(ngram_range=(ngram, ngram), analyzer='word', stop_words='english')\n",
    "    sparse_matrix = word_vectorizer.fit_transform(text_series)\n",
    "    frequencies = sum(sparse_matrix).toarray()[0]\n",
    "    bigrams_freq = pd.DataFrame(frequencies, index=word_vectorizer.get_feature_names(), columns=['frequency']).sort_values(by=['frequency'], ascending=False)\n",
    "\n",
    "    bigrams_freq = bigrams_freq.iloc[0:10]\n",
    "\n",
    "    return bigrams_freq.index\n",
    "\n",
    "\n",
    "top_words_per_overall = pd.DataFrame()\n",
    "\n",
    "for i in range(5):\n",
    "    top_words_per_overall[\"Score \" + str(i+1)] = get_top_words(most_reviewed_reviews[most_reviewed_reviews.overall == (i+1)].reviewText, 1)\n",
    "top_words_per_overall"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The words are kind of neutral, there is not real positive or negative sentiment word. Except for \"great\" for Score 5 but only at 9th position. We were waiting for the postive word to be more in Score 5 and negative Score 1. The top word for each overall score is \"ps4\" which is the product name.\n",
    "\n",
    "But only one word can miss some context, it's a better idea to search for multiple words.\n",
    "\n",
    "### Bigram\n",
    "\n",
    "So we now display the top bigram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Score 1</th>\n",
       "      <th>Score 2</th>\n",
       "      <th>Score 3</th>\n",
       "      <th>Score 4</th>\n",
       "      <th>Score 5</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>blue light</td>\n",
       "      <td>blu ray</td>\n",
       "      <td>touch pad</td>\n",
       "      <td>hard drive</td>\n",
       "      <td>xbox 360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>safe mode</td>\n",
       "      <td>ps3 ps4</td>\n",
       "      <td>hard drive</td>\n",
       "      <td>play games</td>\n",
       "      <td>free games</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>hard drive</td>\n",
       "      <td>steam pc</td>\n",
       "      <td>ps4 does</td>\n",
       "      <td>free games</td>\n",
       "      <td>user interface</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>doesn work</td>\n",
       "      <td>firmware update</td>\n",
       "      <td>ps3 ps4</td>\n",
       "      <td>new controller</td>\n",
       "      <td>hard drive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>light death</td>\n",
       "      <td>looking forward</td>\n",
       "      <td>like ps3</td>\n",
       "      <td>blu ray</td>\n",
       "      <td>remote play</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>customer service</td>\n",
       "      <td>incremental services</td>\n",
       "      <td>blu ray</td>\n",
       "      <td>xbox 360</td>\n",
       "      <td>games like</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>blinking blue</td>\n",
       "      <td>pc games</td>\n",
       "      <td>better ps3</td>\n",
       "      <td>games like</td>\n",
       "      <td>games look</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>59 99</td>\n",
       "      <td>ps2 ps3</td>\n",
       "      <td>sony support</td>\n",
       "      <td>remote play</td>\n",
       "      <td>ps plus</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>xbox ps4</td>\n",
       "      <td>ability play</td>\n",
       "      <td>looks like</td>\n",
       "      <td>blue light</td>\n",
       "      <td>play games</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>launch day</td>\n",
       "      <td>usb port</td>\n",
       "      <td>feel like</td>\n",
       "      <td>just like</td>\n",
       "      <td>blu ray</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Score 1               Score 2       Score 3         Score 4  \\\n",
       "0        blue light               blu ray     touch pad      hard drive   \n",
       "1         safe mode               ps3 ps4    hard drive      play games   \n",
       "2        hard drive              steam pc      ps4 does      free games   \n",
       "3        doesn work       firmware update       ps3 ps4  new controller   \n",
       "4       light death       looking forward      like ps3         blu ray   \n",
       "5  customer service  incremental services       blu ray        xbox 360   \n",
       "6     blinking blue              pc games    better ps3      games like   \n",
       "7             59 99               ps2 ps3  sony support     remote play   \n",
       "8          xbox ps4          ability play    looks like      blue light   \n",
       "9        launch day              usb port     feel like       just like   \n",
       "\n",
       "          Score 5  \n",
       "0        xbox 360  \n",
       "1      free games  \n",
       "2  user interface  \n",
       "3      hard drive  \n",
       "4     remote play  \n",
       "5      games like  \n",
       "6      games look  \n",
       "7         ps plus  \n",
       "8      play games  \n",
       "9         blu ray  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_words_per_overall = pd.DataFrame()\n",
    "for i in range(5):\n",
    "    top_words_per_overall[\"Score \" + str(i+1)] = get_top_words(most_reviewed_reviews[most_reviewed_reviews.overall == (i+1)].reviewText, 2)\n",
    "top_words_per_overall"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Unfortunately, two words does not capture the sentiment of the review. The most of the outputed bigram are just common nouns. We can't say by having just \"xbox 360\" or \"blue light\" determine if the score will be 5 or 1."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Machine learning exploratory\n",
    "\n",
    "We now use some machine learning methods to improve our analysis.\n",
    "\n",
    "### TF-IDF \n",
    "We transform the review text to TF-IDF features to to the clustering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "vectorizer = TfidfVectorizer(stop_words = 'english', min_df=5)\n",
    "tfidf_matrix = vectorizer.fit_transform(most_reviewed_reviews.reviewText)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Clustering attempt\n",
    "\n",
    "We try to determine if the occurences of certain word are specific to the a certain score. We try to cluster, using unsupervised learning, the reviews based on the tf-idf features to 5 groups. We hope we will find on each group the same overall score : 1 group for review score 1, another for score 2 etc...\n",
    "\n",
    "##### KMeans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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eAlyS5rxhzmL6X8BXklxOd8nvFwJHj7QqSdLYDXOQ+p/aJb73bk3HVdX3RluWJGnchtmC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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x22cf210f438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.cluster import KMeans\n",
    "\n",
    "k = 5\n",
    "km = KMeans(n_clusters=k, init='k-means++', max_iter=100, n_init=5)\n",
    "km.fit(tfidf_matrix)\n",
    "\n",
    "plt.hist(km.labels_, bins=k)\n",
    "plt.xlabel('Review score')\n",
    "plt.ylabel('Review count')\n",
    "\n",
    "plt.title('Number of reviews by classes')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "clusters = {}\n",
    "\n",
    "for i in set(km.labels_):\n",
    "    cluster = [most_reviewed_reviews.iloc[x] for x in np.where(km.labels_ == i)[0]]\n",
    "    clusters[i] = pd.DataFrame(cluster)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x22cf484fe10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x22cf492df28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x22cf493f1d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x22cf49ec278>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x22cf4847be0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.title(\"Cluster 1\")\n",
    "plt.xlabel('Review score')\n",
    "clusters[0].overall.plot(kind=\"hist\");\n",
    "plt.show()\n",
    "\n",
    "plt.title(\"Cluster 2\")\n",
    "plt.xlabel('Review score')\n",
    "clusters[1].overall.plot(kind=\"hist\");\n",
    "plt.show()\n",
    "\n",
    "plt.title(\"Cluster 3\")\n",
    "plt.xlabel('Review score')\n",
    "clusters[2].overall.plot(kind=\"hist\");\n",
    "plt.show()\n",
    "\n",
    "plt.title(\"Cluster 4\")\n",
    "plt.xlabel('Review score')\n",
    "clusters[3].overall.plot(kind=\"hist\");\n",
    "plt.show()\n",
    "\n",
    "plt.title(\"Cluster 5\")\n",
    "plt.xlabel('Review score')\n",
    "clusters[4].overall.plot(kind=\"hist\");\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It's not a great success. We dont have in each cluster only review with same score, but a mix. TF-IDF is unstable for such short document lengths."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr />\n",
    "\n",
    "This is the beggining of the work for milestone 3.\n",
    "\n",
    "## Deeper analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Regression model\n",
    "\n",
    "#### Linear regression\n",
    "\n",
    "We will now try to do some `helpfulRate` prediction using simple linear regression. We start by producting a scatter plot based on the insights we found previously. More precisely, we will here visualize the `helpfulRate` compared to the `reviewLength` to see if we can visually anticipate a linear correlation between the two:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x22cf4879358>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Uud8zkU9Y9yVz95vMzl3jc7ymxrGuxeeaGsf67sON7bt6qItlCvm6WLjsz3tQ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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x22cf43d2860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "video_games[video_games.helpfulRate >= 0].plot(kind='scatter', x='helpfulRate', y='reviewLength')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see that it does not seem to have an explicit linear correlation here. We can still do the linear regression, as it is simple to implement. We, however, expect poor result here."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.12411981897969659"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn import linear_model\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import explained_variance_score\n",
    "\n",
    "lreg = linear_model.LinearRegression()\n",
    "\n",
    "X = video_games[video_games.helpfulRate >= 0].loc[:,['reviewLength', 'summaryLength', 'rank', 'overall']]\n",
    "x_train, x_cv, y_train, y_cv = train_test_split(X,video_games[video_games.helpfulRate >= 0].helpfulRate)\n",
    "\n",
    "lreg.fit(x_train,y_train)\n",
    "pred = lreg.predict(x_cv)\n",
    "\n",
    "explained_variance_score(y_cv, pred)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After several testings on multiple features, we found the best features combination to get a `variance score` of about 0.12. This is a really poor result considering the best possible score is 1.0.\n",
    "\n",
    "### Classification\n",
    "\n",
    "The task to predict directly a continuous value for the `helpfulRate` seems to be too complicated. We switched to a classification task, predicting if the review is `helpful` or `not helpful`.\n",
    "\n",
    "Let's plot the distribution of the helpfulness."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 391,
   "metadata": {},
   "outputs": [],
   "source": [
    "# We only analyse reviews with an helpful rate...\n",
    "helpful_video_games = video_games[video_games.helpfulRate >= 0]\n",
    "\n",
    "# We also take only reviews with a minimum of three evaluations, to avoid bias\n",
    "helpful_video_games = helpful_video_games[video_games.helpfulCount > 3]\n",
    "\n",
    "# We clusterize our data into two categories: helpful and non-helpful reviews\n",
    "helpful_video_games['wasHelpful'] = helpful_video_games['helpfulRate'].apply(lambda x: 'helpful' if x > 0.5 else 'notHelpful')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 392,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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RpEkTDB8+HBMnTlQ71WRhYYHt27dj2bJlOHjwIHJzc9GyZUt8/vnnGDVqlMa6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\nuChFALj8ANXC/nVzOA6fAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x22c85d8f7b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "groupby_helpful = helpful_video_games.groupby('wasHelpful')\n",
    "\n",
    "groupby_helpful['overall'].count().plot.bar(title='Helpful distribution for ' + str(len(helpful_video_games)) + ' video games reviews');\n",
    "ax1 = plt.axes()\n",
    "ax1.xaxis.label.set_visible(False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see that there are a lot more helpful review than not helpful. We are facing to an imbalanced dataset. So we will use the `f1-score` metrics to evaluate our future models. We will use `macro` average because we want to give the same importance to each classes."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are many features that we can take into account for our classification task, including for example using the review text itself. However, we will first use a simple neural networks model and basic features to see the behaviour.\n",
    "\n",
    "#### First draft with basic features\n",
    "\n",
    "Considering the data distribution, usage of linear regression seems to be innapropriate. We chose to change completely our strategy by using neural networks. As we have important data aggregates, we may succeed in training a neural network to predict helpfulness.\n",
    "\n",
    "##### Using only overall\n",
    "We start by a naive approach, by trying to predict if a review was helpful only using the `overall` feature; meaning answering the question: \"How well can we predict if a review is helpful based on the review grade?\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 498,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn.metrics import f1_score\n",
    "\n",
    "label_encoder = LabelEncoder()\n",
    "label_encoder.fit_transform(helpful_video_games['wasHelpful'])\n",
    "    \n",
    "def train_network(dataset, features, max_iter, predict=False):\n",
    "    y = dataset['wasHelpful']\n",
    "    y = label_encoder.fit_transform(y)\n",
    "    \n",
    "    x = dataset.loc[:, features]\n",
    "\n",
    "    x_train, x_test, y_train, y_test = train_test_split(x,y, test_size=0.25)\n",
    "\n",
    "    clf = MLPClassifier(hidden_layer_sizes=(100,100,100), max_iter=max_iter, alpha=0.0001,\n",
    "                     solver='sgd', verbose=False,  random_state=21, tol=0.000000001)\n",
    "\n",
    "    clf.fit(x_train, y_train)\n",
    "    y_pred = clf.predict(x_test)\n",
    "\n",
    "    if predict:\n",
    "        print(\"f1-score:\", f1_score(y_test, y_pred, average='macro'))\n",
    "   \n",
    "\n",
    "    \n",
    "    return clf, x, y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 499,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "f1-score: 0.638557252743\n"
     ]
    }
   ],
   "source": [
    "from sklearn.neural_network import MLPClassifier\n",
    "from sklearn.metrics import accuracy_score\n",
    "    \n",
    "clf, x, y = train_network(helpful_video_games, ['overall'], 20, True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The f1-score is around 0.63 by only taking into account the initial rate, which is clearly better than a simple linear regression. Let's find out how our classifier works..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 479,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 star review: ['notHelpful']\n",
      "2 star review: ['notHelpful']\n",
      "3 star review: ['helpful']\n",
      "4 star review: ['helpful']\n",
      "5 star review: ['helpful']\n"
     ]
    }
   ],
   "source": [
    "for i in range(1, 6):\n",
    "    print(str(i) + ' star review: ' + str(label_encoder.inverse_transform(clf.predict(i))))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We get here a new insight about data distribution. One star reviews seems to have a lower helpful rate than other reviews. This may be due to overstated reviews and product bashing. Let's do a short descriptive analysis to confirm this new information.\n",
    "\n",
    "Because we know we have high differences in the number of evaluations in each grade category, we use the standard error instead of the standard deviation to draw the error bars. This allows to mitigate the observations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 480,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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LCH50aXPmzFGfPn2UkZGhTZs2qUePHpowYYKWLVumsLAwVz9/f3/dcMMN2r17\nt9ttnnP+7//+T8OHD1deXp7WrVun4OBgzZo1Sw888ICCgoIuWMPatWvVs2dP/e53v9Mbb7yhK664\nQsnJyRoxYoSWL1+uP//5z4qOjvb6uQPnw0YsAGAY7vEDgGEIfgAwDMEPAIYh+AHAMAQ/ABiG4AcA\nwxD8AGAYgh8ADEPwA4Bh/h8ZsyXDCnZczwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x22c822f6668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "grouped_helpful_reviews = helpful_video_games.groupby(['overall']).helpfulRate\n",
    "grouped_helpful_reviews.mean().plot(kind='bar', yerr=grouped_helpful_reviews.std()/math.sqrt(len(grouped_helpful_reviews)));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see that errors are important, due to the high variance of the results. This may be explained by the fact that using the overall only to find the final rank is not as good as taking multiple features into account.\n",
    "\n",
    "After seing this plot and data distribution, we can understand why only 1 star reviews are getting are immediately considered as not helpful. We now cross validate to ensure results were representative of the reality."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 500,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "crossval f1-score: 0.617901082767\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import cross_val_score\n",
    "scores = cross_val_score(clf, x, y, cv=4, scoring='f1_macro')\n",
    "print(\"crossval f1-score:\", np.mean(scores))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After cross-validation, we get even less: f1-score=0.61.\n",
    "\n",
    "However, predicting the helpfulness of a review by sorting it as `true` or `false` based on the grade is not very helpful and creates an unwanted segregation in data. Considering Amazon would use these results to promote specific reviews, it may create an incentive for posting fake 5 star reviews to be put forward.\n",
    "\n",
    "###### Predicting 3 class\n",
    "\n",
    "Before testing against more features, we will create three clusters to determine if a review was helpful:\n",
    "\n",
    "- 0 will mean the review is not helpful at all (less than 33% of the evaluations said it was useful)\n",
    "- 1 will mean the review may be polemical (less than 66% of the evaluations said it was useful)\n",
    "- 2 will mean the review was useful (more than 66% of the evaluations said it was useful)\n",
    "\n",
    "Lets plot the distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 482,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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bt2/HoUOHUKdOHQwcOBCjR49WO9VkYWGBrVu3YtGiRThw4ACysrLQqFEjTJo0\nCYMHDy4xbdURSkWezqM6I1HWPaoviqenJ9566y1kZGRoPCX7tGbNmmHLli344YcfsHnzZiiVSnh6\nemLMmDHSwxZUKvO58O2338LBwQGbN29GeHg4DA0NYW9vj5CQELRv377cuoKDg1G3bl2sX78e33//\nPWrXro0+ffpAqVRi5cqVUr9Y3759kZeXh40bN2LOnDkwNTVFs2bNsHDhQvz111+IiorC6dOnn2s/\nUjExMcHGjRsRFRWFAwcO4Ndff4W5uTmcnJwwcuRI6WgHAObPn4/ly5fjl19+QWxsLPT19WFnZ4el\nS5dWaPlLM3PmTDg4OGDr1q344YcfYGhoCGtra/zwww8az8JVdn+oX78+tm/fjoiICPz+++/YsWMH\nLCws4O3tjVGjRpW4+EkVig0bNlTrC1SFYrt27dT6MOvUqYN169ZhyZIlOHDgAO7evQtTU1O4u7sj\nODi41PupnyQTyrsa4jXj5+eHkydP4q+//tJ2KURUBameJqTpy7fqoQCxsbEVOkon3cPfUySiN8qF\nCxfg4uJSok9OoVAgLi4O9erVeyWnoun1pNMPBCciepqjo6P0W44ZGRmwtbVFVlYWoqOjkZGRgXnz\n5r3wW4Oo6mAoEtEbxcDAAGvXrsXy5cvx22+/YevWrTAyMoKDgwOmT58ONzc3bZdIWlTl+hSJiIhe\nljf6SDE9/cVdTv26MTd/fJtBVlbJZzPS643brmp7E7ZfvXqv5jdLtYEX2hAREYkYikRERCKGIhER\nkYihSEREJGIoEhERiRiKREREIoYiERGRiKFIREQkYigSERGJGIpERESiN/oxb0QVNWRWnLZLeKlW\nhnTUdglErwUeKRIREYkYikRERCKGIhERkYihSEREJGIoEhERiRiKREREIoYiERGRiKFIREQkYigS\nERGJGIpEREQihiIREZGIoUhERCRiKBIREYkYikRERCKGIhERkYihSEREJGIoEhERiRiKREREIoYi\nERGRiKFIREQkYigSERGJGIpEREQihiIREZGIoUhERCRiKBIREYkYikRERCKGIhERkYihSEREJGIo\nEhERiRiKREREogqFolKpxA8//IAOHTrAyckJ/v7+OH/+vDReEARERkbCy8sLjo6OCAwMxJUrV0pM\nY+bMmWjbti2cnZ3x5Zdf4s6dO2ptsrOzERISAjc3N7Ru3RqTJ0+GQqFQa3Pr1i18/vnncHFxgaen\nJ+bMmQOB/Fo4AAAgAElEQVSlUvmsy09ERCSpUCiGhYVh3bp1GDZsGCIiImBkZAR/f3/cvHkTABAR\nEYHIyEgMGTIE4eHhePjwIQICAvDw4UNpGtOmTcOuXbswbtw4hIWF4eLFixg+fDiKioqkNl988QWS\nkpIwffp0hIaGIi4uDuPGjZPGK5VKDBkyBP/++y/mzJmDUaNG4aeffsKsWbNe1PogIqI3mEF5DR4+\nfIitW7di3LhxGDhwIADAxcUFbm5u2LVrF/z9/bFixQoEBwfD398fAODq6ooOHTpg27ZtCAwMREpK\nCnbu3Il58+bB19cXAGBra4uuXbsiNjYWnTt3RkJCAhITE7FlyxY4OjoCABo0aICAgACcP38ednZ2\n2LNnD1JSUhAbG4sGDRoAAKpXr47p06dj1KhRqFu37ktZSURE9GYo90jRyMgIW7ZsQe/evaVhBgYG\nkMlkUCqVOHPmDHJzc+Ht7S2NNzMzQ5s2bXDkyBEAQEJCAgDAy8tLamNlZYV33nlHahMfHw8LCwsp\nEAHAzc0NJiYmUpvjx4+jRYsWUiACgI+PDwoLCxEfH/8sy09ERCQp90jRwMAALVq0AAAUFxfj5s2b\nWLRoEWQyGT788EMpjBo3bqz2ukaNGiEuLg4AcO3aNdStWxc1a9Ys0eb69etSmyZNmqiN19PTg6Wl\npdTm+vXrsLKyUmtTu3ZtmJiYSG0qw9y8ZvmNqigDg8ffd3R5GenF4X7y4vC9V7VV6urTJUuWwMfH\nB7t27UJQUBCaN28OhUIBQ0NDGBoaqrU1NjaWLpLJycmBsbFxielVto1CoSi3DRER0bMq90jxST4+\nPmjTpg0SExOxZMkSFBQUoEaNGpDJZBrbq4YLglChNnp6mjP6yeGlTae015YlKyu30q+pKlTfUnV5\nGenF4X7y4rwJ77169Uy1XcJLU6lQtLW1BQC0adMGOTk5WLFiBcaPHw+lUomCggJUq1ZNapuTkwNT\n08crzsTEBDk5OSWm93Sb9PR0jW2aNWtW7nRMTEwqsyhEREQllHt4lZ6eju3bt5c4Pfnuu+9CqVTC\nzMwMgiAgLS1NbXxaWpoUZlZWVsjIyEB+fn6ZbVJTU9XGq/own2zz9Hzu378PhUIhtSEiInpW5Ybi\ngwcPEBoaigMHDqgNP3bsGCwsLODj44Pq1asjJiZGGpednY2kpCR4eHgAADw8PFBUVCRdeAM8vmjm\n0qVLam3S09Nx9uxZqU1iYiIUCoXUxt3dHefOncPt27elNjExMahWrRpat279LMtPREQkKff0qbW1\nNbp06YLZs2ejoKAAjRs3xq+//opdu3Zh5syZMDExwaBBg7BgwQLo6enBysoKUVFRMDExQd++fQEA\nTZo0QdeuXTFlyhQoFArUqlUL4eHhsLGxgY+PD4DHgefo6Ijg4GBMmDABhYWFmD17Nry8vGBvbw8A\n6N69OyIjIxEUFITRo0fj7t27+P7779GvXz/Uq1fvJa4mIiJ6E8gEQRDKa5SXl4fFixdj//79uHv3\nLt5++22MGDECXbt2BQAUFhZi/vz52LFjB3Jzc+Hs7IzJkyfD2tpamkZubi7CwsJw4MABFBcXw9PT\nE5MnT0b9+vWlNvfu3cM333yDQ4cOwdDQEN7e3ggNDVXrL7xx4wZmzJiB5ORkmJqaokePHhg7dqxa\nf2ZFpac/LL9RFfUmdPa/SkNmxZXfqApbGdJR2yXojDfhvafLF9pUKBR1FUORKoqhSBX1Jrz3dDkU\n+SsZREREIoYiERGRiKFIREQkYigSERGJGIpEREQihiIREZGIoUhERCRiKBIREYkYikRERCKGIhER\nkYihSEREJGIoEhERiRiKREREIoYiERGRiKFIREQkYigSERGJGIpEREQihiIREZGIoUhERCRiKBIR\nEYkYikRERCKGIhERkYihSEREJGIoEhERiRiKREREIoYiERGRiKFIREQkYigSERGJGIpEREQihiIR\nEZGIoUhERCRiKBIREYkYikRERCKGIhERkYihSEREJGIoEhERiRiKREREIoYiERGRiKFIREQkYigS\nERGJGIpEREQihiIREZGIoUhERCRiKBIREYkqFIpFRUVYtWoVunXrBicnJ/j6+mL9+vUQBAEAIAgC\nIiMj4eXlBUdHRwQGBuLKlStq01AqlZg5cybatm0LZ2dnfPnll7hz545am+zsbISEhMDNzQ2tW7fG\n5MmToVAo1NrcunULn3/+OVxcXODp6Yk5c+ZAqVQ+zzogIiICABhUpNGSJUuwbNkyjBo1Ck5OTkhO\nTsbMmTORl5eHYcOGISIiAsuWLcP48eNhaWmJyMhIBAQEYN++fTA1NQUATJs2DXFxcZg4cSJq1qyJ\n8PBwDB8+HNHR0dDX1wcAfPHFF0hLS8P06dORn5+POXPmICMjA0uXLgXwOFiHDBmCGjVqYM6cObh1\n6xbmzp2L/Px8TJ069SWtIiIielOUG4qqo8ShQ4di5MiRAAAPDw9kZmZi5cqVGDBgAFasWIHg4GD4\n+/sDAFxdXdGhQwds27YNgYGBSElJwc6dOzFv3jz4+voCAGxtbdG1a1fExsaic+fOSEhIQGJiIrZs\n2QJHR0cAQIMGDRAQEIDz58/Dzs4Oe/bsQUpKCmJjY9GgQQMAQPXq1TF9+nSMGjUKdevWfSkriYiI\n3gzlnj5VKBTo2bMnOnfurDa8WbNmyMzMREJCAnJzc+Ht7S2NMzMzQ5s2bXDkyBEAQEJCAgDAy8tL\namNlZYV33nlHahMfHw8LCwspEAHAzc0NJiYmUpvjx4+jRYsWUiACgI+PDwoLCxEfH1/ZZSciIlJT\n7pGimZmZxlOTBw8eRIMGDaR+wcaNG6uNb9SoEeLi4gAA165dQ926dVGzZs0Sba5fvy61adKkidp4\nPT09WFpaSm2uX78OKysrtTa1a9eGiYmJ1KYyzM1rlt+oijIwePx9R5eXkV4c7icvDt97VdszXX26\ndetWHD9+HEFBQVAoFDA0NIShoaFaG2NjY+kimZycHBgbG5eYTmXbKBSKctsQERE9qwpdaPOk3bt3\nY9q0aejSpQsGDRqEpUuXQiaTaWyrGi4IQoXa6Olpzugnh5c2ndJeW5asrNxKv6aqUH1L1eVlpBeH\n+8mL8ya89+rVM9V2CS9NpZJk1apVmDBhAry8vDB37lzIZDKYmppCqVSioKBArW1OTo505amJiQly\ncnJKTK+ibUxMTCrchoiI6FlVOBTDw8Mxa9YsfPTRR1i4cKF0urRp06YQBAFpaWlq7dPS0tCsWTMA\njy+qycjIQH5+fpltUlNT1cYXFxfj5s2bam2ens/9+/ehUCikNkRERM+qQqG4Zs0aLF26FP7+/pg1\naxYMDP7/rKuzszOqV6+OmJgYaVh2djaSkpLg4eEB4PEtHEVFRdKFN8Dji2YuXbqk1iY9PR1nz56V\n2iQmJkKhUEht3N3dce7cOdy+fVtqExMTg2rVqqF169bPsvxERESScvsU7969i7lz50Iul+ODDz7A\nmTNn1Mbb29tj0KBBWLBgAfT09GBlZYWoqCiYmJigb9++AIAmTZqga9eumDJlChQKBWrVqoXw8HDY\n2NjAx8cHwOPAc3R0RHBwMCZMmIDCwkLMnj0bXl5esLe3BwB0794dkZGRCAoKwujRo3H37l18//33\n6NevH+rVq/ei1w0REb1hZILqWW2liI6OxqRJk0odHx8fj1q1amH+/PnYsWMHcnNz4ezsjMmTJ8Pa\n2lpql5ubi7CwMBw4cADFxcXw9PTE5MmTUb9+fanNvXv38M033+DQoUMwNDSEt7c3QkND1foLb9y4\ngRkzZiA5ORmmpqbo0aMHxo4di2rVqlV64dPTH1b6NVXFm9DZ/yoNmRVXfqMqbGVIR22XoDPehPee\nLl9oU24o6jKGIlUUQ5Eq6k147+lyKPJXMoiIiEQMRSIiIhFDkYiISMRQJCIiEjEUiYiIRAxFIiIi\nEUORiIhIxFAkIiISMRSJiIhEDEUiIiJRpX9kmJ6dLj8qjI8JIyJdwCNFIiIiEUORiIhIxFAkIiIS\nMRSJiIhEDEUiIiIRQ5GIiEjEUCQiIhIxFImIiEQMRSIiIhFDkYiISMRQJCIiEjEUiYiIRAxFIiIi\nEUORiIhIxFAkIiISMRSJiIhEDEUiIiKRgbYLICJ62YbMitN2CS/VypCO2i5BZ/BIkYiISMRQJCIi\nEjEUiYiIRAxFIiIiEUORiIhIxFAkIiISMRSJiIhEDEUiIiIRQ5GIiEjEUCQiIhIxFImIiEQMRSIi\nIhFDkYiISMRQJCIiEjEUiYiIRJUOxdjYWDg7O6sNEwQBkZGR8PLygqOjIwIDA3HlyhW1NkqlEjNn\nzkTbtm3h7OyML7/8Enfu3FFrk52djZCQELi5uaF169aYPHkyFAqFWptbt27h888/h4uLCzw9PTFn\nzhwolcrKLgYREVEJlfqR4VOnTuG///1vieERERFYtmwZxo8fD0tLS0RGRiIgIAD79u2DqakpAGDa\ntGmIi4vDxIkTUbNmTYSHh2P48OGIjo6Gvr4+AOCLL75AWloapk+fjvz8fMyZMwcZGRlYunQpgMfB\nOmTIENSoUQNz5szBrVu3MHfuXOTn52Pq1KnPuy6IiOgNV6FQVCqVWLNmDRYsWICaNWuioKBAGqdQ\nKLBixQoEBwfD398fAODq6ooOHTpg27ZtCAwMREpKCnbu3Il58+bB19cXAGBra4uuXbsiNjYWnTt3\nRkJCAhITE7FlyxY4OjoCABo0aICAgACcP38ednZ22LNnD1JSUhAbG4sGDRoAAKpXr47p06dj1KhR\nqFu37gtdOURE9Gap0OnTw4cPY9myZZgwYQIGDRqkNu7MmTPIzc2Ft7e3NMzMzAxt2rTBkSNHAAAJ\nCQkAAC8vL6mNlZUV3nnnHalNfHw8LCwspEAEADc3N5iYmEhtjh8/jhYtWkiBCAA+Pj4oLCxEfHx8\nZZabiIiohAodKbZs2RKxsbGoVasWFi1apDbu+vXrAIDGjRurDW/UqBHi4uIAANeuXUPdunVRs2bN\nEm1Ur7927RqaNGmiNl5PTw+WlpZSm+vXr8PKykqtTe3atWFiYiK1qQxz85rlN6IK4bqs2rj9qjZu\nvxenQqFYv379UscpFAoYGhrC0NBQbbixsbF0kUxOTg6MjY1LvNbY2Bi3b98ut41qOgqFotw2RERE\nz6pSF9poIggCZDKZxnGq4RVto6en+Wzuk8NLm05pry1LVlZupV9DmnFdVm3cflXbq95+9eqZvtL5\nvUrPfZ+iqakplEql2sU3wOMjP9WVpyYmJsjJySnx2oq2MTExqXAbIiKiZ/Xcodi0aVMIgoC0tDS1\n4WlpaWjWrBmAxxfVZGRkID8/v8w2qampauOLi4tx8+ZNtTZPz+f+/ftQKBRSGyIiomf13KHo7OyM\n6tWrIyYmRhqWnZ2NpKQkeHh4AAA8PDxQVFQkXXgDPL5o5tKlS2pt0tPTcfbsWalNYmIiFAqF1Mbd\n3R3nzp2T+iEBICYmBtWqVUPr1q2fd1GIiOgN99x9isbGxhg0aBAWLFgAPT09WFlZISoqCiYmJujb\nty8AoEmTJujatSumTJkChUKBWrVqITw8HDY2NvDx8QHwOPAcHR0RHByMCRMmoLCwELNnz4aXlxfs\n7e0BAN27d0dkZCSCgoIwevRo3L17F99//z369euHevXqPe+iEBHRG+65QxEAxo4dCz09PaxcuRK5\nublwdnbGrFmzpP5CAAgLC0NYWBjmzp2L4uJieHp6YvLkydLTbGQyGSIjI/HNN99gypQpMDQ0hLe3\nN0JDQ6VpGBkZYdWqVZgxYwbGjx8PU1NTDBgwAGPHjn0Ri0FERG84mSAIgraL0Jb09IevdH5DZsWV\n36iKWhnSUdslvFS6vO0Abr+q7lVvP159SkRE9AZgKBIREYkYikRERCKGIhERkYihSEREJGIoEhER\niRiKREREIoYiERGRiKFIREQkYigSERGJGIpEREQihiIREZGIoUhERCRiKBIREYkYikRERCKGIhER\nkYihSEREJGIoEhERiRiKREREIoYiERGRiKFIREQkYigSERGJGIpEREQihiIREZGIoUhERCRiKBIR\nEYkYikRERCKGIhERkYihSEREJGIoEhERiRiKREREIoYiERGRiKFIREQkYigSERGJGIpEREQihiIR\nEZGIoUhERCRiKBIREYkYikRERCKGIhERkYihSEREJGIoEhERiRiKREREIoYiERGRqEqG4pYtW9C5\nc2c4ODigf//+OH36tLZLIiIiHVDlQnHHjh2YNm0aPvzwQyxatAimpqYYOnQoUlNTtV0aERFVcVUq\nFAVBwKJFi9CvXz8EBwejffv2iIyMRO3atbFmzRptl0dERFVclQrFGzdu4ObNm+jYsaM0rFq1avDy\n8sKRI0e0WBkREekCA20XUBnXr18HADRt2lRteOPGjZGSkoKioiLo6+tXeHrm5jVfZHlvNK7Lqo3b\nr2rj9ntxqlQoKhQKAICxsbHacGNjYxQXFyMvLw8mJiYVnl61ahUP0Bdhz7yPXun86MXhtqvauP2o\noqrU6VNBEAAAMplM4/jShhMREVVElQpFU1NTAEBOTo7a8JycHOjr65c4giQiIqqMKhWKqr7Ep2+/\nSE1NhZWVlRYqIiIiXVKlQtHKygpvvfUWYmJipGEFBQX4/fff4eHhocXKiIhIF1SpC21kMhmGDRuG\nb775BmZmZmjVqhXWr1+P+/fvIyAgQNvlERFRFScTVFevVCErV67E2rVrcf/+fbz77ruYOHEinJ2d\ntV0WERFVcVUyFImIiF6GKtWnSERE9DIxFImIiEQMRSIiIhFDkYiISMRQJCIiEjEUiYiIRFXq5n0i\nXZKVlVWp9ubm5i+pEiJS4X2KVdiIESMq3FYmkyEyMvIlVkOVZWtrW6lfdrlw4cJLrIYqw9nZucLb\nTiaT4eTJky+5InpReKRYhT39ayFUtcycOZM/d1ZFDRkyhNtOR/FIkYiISMQjRR2Tl5cHpVIp/SCz\nIAjIz8/H6dOn4evrq+XqqDSLFy8ut01wcPArqIQqa+fOneW26dmz5yuohF4EHinqiH/++QeTJk3C\nX3/9VWob9km9vlq3bl1iWF5eHgoLC1GrVi00adIE27Zt00JlVB5bW1uNw2UyGQwNDVGzZk3Ex8e/\n4qroWfFIUUfMmjUL6enpmDhxIg4ePIhq1aqhY8eOOHz4MA4dOoTVq1dru0Qqw4kTJzQOP336NEJC\nQip1URW9Wpq2XW5uLk6cOIHw8HB8//33WqiKnhWPFHVEq1atMHXqVPTs2RNbt25FdHQ0Nm7cCAAY\nN24cHj16VKFTdPT6+fnnn7FkyRLs27dP26VQJW3duhUbN25EdHS0tkuhCuLN+zqisLAQjRo1AgA0\na9YMFy9elMb17NkTZ86c0VZp9JxMTU2Rlpam7TLoGVhaWuLy5cvaLoMqgadPdUTTpk1x8eJFuLq6\nonnz5sjLy8OVK1dgbW2NoqIiKBQKbZdIZTh//nyJYcXFxbh79y4WLFgAGxsbLVRFFaHpIQyqbRcZ\nGYkmTZpooSp6VgxFHfHxxx9jzpw5yM3NxfDhw9GqVStMnjwZ/fr1w5o1a0q9GIBeD3369NF435sg\nCKhfvz4WLFighaqoItzd3Uu9Z9HQ0JDbrophn6IOWbFiBW7fvo3JkyfjypUrGDlyJFJSUtCwYUMs\nXrwYLVq00HaJ9IRbt27hrbfeAgAkJSWVGC+TyWBiYgIbGxvo6bGn43VSWFgIA4PHxxQ7duwoMV61\n7dzc3GBqavqqy6PnwFDUYYIgIDMzExYWFtouhTRwc3PDkiVL4OLigkmTJmHUqFFo3LixtsuiCnjv\nvfewePFiODk5YfHixejbty/q16+v7bLoBeDp0yrs/PnzsLa2Ro0aNTT2Sancvn0bAGBnZ/eqSqMK\nUCqV+OOPP9C8eXPs2LEDPXr0KPOogg8Ef308fPgQKSkpcHJyQkREBNq1a8dQ1BE8UqzCbG1tsWXL\nFjg4OJT5cGlBECCTyXjz/mtm/Pjx+PnnnyGTyaRtVBZuv9fHsGHDcPToUdSoUQN5eXkwMjIqdfvx\ngeBVC0OxCktKSoKdnR2MjY019kk9rU2bNq+gKqqowsJCHDlyBFlZWZg0aRJGjhxZ5pWKvXr1eoXV\nUVkePnyIXbt2ISsrC4sXL8bHH3+MBg0alNqej+irOhiKOqygoAAKhQK1a9fWdilUDvYpVl1+fn6Y\nPn06rK2ttV0KvQAMRR2hVCoRERGB5s2b46OPPsLRo0cxduxYPHz4EK6urliwYAHq1Kmj7TKpHMnJ\nyUhOTkZ2djbq1KkDd3d3tGzZUttlUQX8+++/OHnypLTtWrdujXr16mm7LKokhqKOCAsLw6ZNmzB1\n6lT06dMHPj4+MDIywtChQxEVFQUnJyfMmjVL22VSKR48eICRI0fi5MmTMDAwgLm5ObKyslBUVAQv\nLy8sWLAAhoaG2i6TNFAqlZg8eTJ+/vlnPPlxqq+vj4EDByI0NJS/vViVCKQT2rVrJ2zcuFEQBEE4\nc+aMYGNjI+zdu1cQBEHYv3+/4Obmps3yqBxjx44VPDw8hN9//10aVlxcLMTGxgoeHh7Cd999p8Xq\nqCwzZswQnJychPXr1wu3b98WHj16JNy6dUtYu3at4OTkJERERGi7RKoE3hGsI+7fv4+3334bAPD7\n77/DwMAA7dq1AwCYmZnh0aNH2iyPynH48GFMnDgR7du3l4bJZDJ07NgR48aNw549e7RYHZVl3759\nGD9+PD799FPUr18fhoaGaNCgAfz8/PDVV19h8+bN2i6RKoGhqCOaNGmCU6dOoaCgAPv374eLiwtM\nTEwAPH7TNmvWTMsVUlmqVasGIyMjjePMzc1RXFz8iiuiiiosLETDhg01jmvatCkePnz4iiui58FQ\n1BFDhw7F/Pnz4eHhgevXryMwMBAA0L9/f2zfvh3Dhg3TcoVUliFDhmDu3Lm4evWq2vA7d+4gIiIC\nQ4cO1VJlVJ4+ffogIiIC2dnZasMfPXqE1atXo2/fvlqqjJ4FL7TRIcnJyTh16hRcXFzg4uICAFi8\neDHc3Nw0/rI7vT5GjBiB5ORk5ObmwsbGBvXq1UNWVhYuXryIgoIC6dQ48Pi06u7du7VYLT3p66+/\nxp49e1BcXAxPT09p2yUmJiIrKwvvvfee9OxamUyGyMhILVdMZWEo6ojPP/8cgwcP5g36VdSkSZMq\n1T4sLOwlVUKV5efnV6n269ate0mV0IvAUNQRzs7OiIyMhLu7u7ZLISKqsvhAcB3RsWNHbN26Ffb2\n9tIFNvR6K+sh7prwge6vD00/LFwWPsy96uCRoo74/PPPcejQIRQVFaFOnTolnl7DfqjXT1kPcX+S\nwAe6v3Yquu1UuO2qDh4p6ohatWqhR48e2i6DKmHt2rXaLoGe0cyZM/mUGh3FI0Wi10xhYSHu37+P\n2rVrS7/uTkSvBt9xOqSwsBB79+5FQkIC0tPT8b///Q8nT56EnZ0dbG1ttV0eleOPP/7A/PnzcfLk\nSRQVFWHr1q1YtWoVLC0t8dVXX2m7PCpDamoqoqKiEB8fj4yMDGzcuBG7d+/G22+/zfsUqxjevK8j\n7t+/j379+iE0NBTnz5/HsWPHkJOTg99++w0DBgzAmTNntF0ilSE+Ph6DBg0CAHz11VfSg6Xlcjl+\n/PFHrFq1SpvlURkuXLiAXr164eTJk+jYsSMKCgoAPO4Lnjp1Knbu3KnlCqkyGIo6IiwsDAqFAr/+\n+iuio6OlD9WFCxfCwcEB4eHhWq6QyjJ37lz4+vpi9erV8Pf3l7bf8OHDMWLECD4/8zU2c+ZMODk5\nYd++fQgJCZG2XWhoKD755BN+oaliGIo64uDBgxgzZgwsLS3VLgAwNDTEkCFDKn35P71aly5dwocf\nfggAJS7gcHNzw7///quNsqgCzp49Cz8/P+jp6ZXYdl27dsWNGze0VBk9C4aijigqKkL16tU1jiss\nLASvp3q9WVhY4PLlyxrHXblyBRYWFq+4IqooExMTpKenaxx369Yt3jdcxTAUdYS7u3uJhxLLZDIU\nFBRg7dq1fPbpa65nz55YsGABtm/fjszMTACPv+gcP34cixcvRvfu3bVcIZWma9euCA8PR0JCgvTl\nUyaT4dq1a1i8eDG8vb21XCFVBm/J0BEpKSkYMGAACgoK4OTkhCNHjqBdu3a4evUqHjx4gJ9++gnW\n1tbaLpNKUVRUhP/973/YsWMHZDIZBEGAnp4eBEFAp06dMG/ePFSrVk3bZZIGeXl5GDFiBBITE2Fk\nZIS8vDzUrVsXmZmZsLe3x8qVK3m0WIUwFHXIvXv3sHr1aiQlJSErKwsmJiZwcXFBYGAg3nrrLW2X\nRxVw5coVJCUlITs7G6ampnBxceHtNFXEkSNHSrz3OnbsKP1CBlUNDEUdkZqaisaNG2u7DCKiKo2h\nqCNsbW3h6OiI7t27w9fXlxdmVDFFRUXYtGkTEhMT8eDBAxQXF6uNl8lkWLNmjZaqo6dV5jYLmUyG\ngICAl1cMvVAMRR3x+++/Y//+/YiLi0Nubi7atGmD7t27o3PnzjA1NdV2eVSOsLAwrFmzBnK5HJaW\nlhpPuUVERGihMtJE0yltVV+wpuF8IHjVwVDUMUqlEkeOHMH+/fvx+++/Q6lU4v3330f37t3RrVs3\nbZdHpXB3d8eAAQMwevRobZdCz6CwsBD29vbYvn07f+KriuOzT3WMoaEhvL294e3tjQcPHuCHH37A\nli1bEBcXx1B8jSmVSv5AdBXGX8zQHQxFHZOXl4eDBw/il19+wZEjR1BcXAwfHx/+rNRrrkOHDvjt\nt9/g5uam7VKI3mgMRR2xd+9eHDhwAIcPH0ZhYSHc3d0xbdo0dOrUCcbGxtoujzR48mKNRo0aYfny\n5UhJSYGTkxOMjIzU2vJiDaJXg32KOsLW1hZOTk7o0aMHunXrhjp16mi7JCpHZe4/5MUar7eioiLY\n2Zs4RXoAAAcBSURBVNmxT1EH8EhRR8TGxsLS0lLbZVAlXLx4Udsl0AvGvsWqj0eKOiQ9PR0rV67E\niRMnoFAoYG5uDhcXF/j7+6N+/fraLo9IZzg7O5cIwNzcXBgZGZUYLpPJcPLkyVdZHj0HHinqiBs3\nbmDgwIHIz8+Hh4cHLCwspF8Aj46OxqZNm9C0aVNtl0mkE4YMGcKjQh3FI0UdMWrUKKSlpWHNmjWo\nXbu2NDwzMxNDhw5F48aNsXDhQi1WSPRmKi4u5vNPqxBuKR2RkJCA4OBgtUAEgDp16mDEiBFISEjQ\nUmVEus3b27vU/uGzZ8/Cw8PjFVdEz4OnT3VEjRo1Sv02KpPJUFhY+IorItJdP/30Ex49egQAuHnz\nJrZv346GDRuWaHfy5MkSz7Gl1xtDUUe0bt0aS5YsQevWrWFmZiYNz8rKQmRkJNq0aaPF6oh0y/37\n97Fo0SIAj790rlu3rkQbPT09mJqaYsyYMa+6PHoO7FPUEWlpaejbty+USiXc3NxQt25dZGRkIDEx\nEQYGBvyRYaKXxNbWFlu2bIGDg4O2S6EXgKGoQ+7cuYNVq1YhOTkZDx48gJmZGVxcXBAQEIAGDRpo\nuzwinZebm4ucnByYmZnB0NBQ2+XQM2Ao6ohvv/0WPXv2hL29vbZLIXrjHDt2DOHh4bhw4YL081F2\ndnb44osv0L59ey1XR5XBq091xNatW/HgwQNtl0H0xjl27BiGDx+OatWqISQkBPPmzcPEiROhr6+P\nkSNH4tixY9oukSqBR4o6YujQoXj77bcxadIkbZdC9Ebp27cvGjZsiAULFpQYN2bMGNy5cwcbN27U\nQmX0LHj1qY6wtLTEhg0bsHPnTjRt2rTEA8FlMhkiIyO1VB2R7vrnn3/w5ZdfahzXp0+fUsfR64mh\nqCOuXbsGZ2dn6e+cnBwtVkP05qhbty5u376tcdytW7dK/AwYvd4YijpC031ST+INxEQvR+fOnREe\nHg5LS0t4enpKw48dO4b58+ejU6dOWqyOKot9ijrC29sbERERGn+j7+zZsxg2bBgSExO1UBmRbsvN\nzcXQoUNx+vRpmJiYwOL/2rt7kFayOArg5xJt1Ehi/ABtxNJiELRII0yhSBIE0SaSgBaKCMHSQkWN\nRbQRFQnaWGgRIQg2EiwCUexMYwq/URQUBDGQqAiiyRbryi7G3fd4b2cyl/Mrc1McsDhz7538tdnw\n8PCA5+dnKIqClZUVlJSU6B2TfhB3igbGUVNE+isqKkIoFEIsFkM8Hsfj4+Pnb4RVVeUwcIPhTtHA\ngsHgP0ZN5fpT/jVqamhoCB6PR+uIRESGwlKUBEdNEekjk8kgHA5jd3cXLy8vX05lhBBYXV3VKR39\nLB6fSuK7f11DRP+vmZkZrK2tob6+HlVVVTwuNTjuFCWyt7f3r0+rgUBAp2RE8rLb7fB6vfD5fHpH\nod+AO0VJLC8vY35+HhaLBZWVlV+eVoUQOiUjktvr6yuampr0jkG/CUtREqFQCG63GxMTEyxAIg2p\nqopoNAq73a53FPoNWIqSSKfTcDgcLEQijTU3N2N6eho3NzdQFOXLBBshBHp7e/UJRz+Nd4qS6Ovr\nQ0NDA+81iDSWa2DG3wkhcHx8rFEa+lUsRUnEYjGMjIzA6XTmfFoF/hxHRURE32MpSoJPq0REv46l\nKInb29v//E5NTY0GSYiIjIulKJlsNouLiws8PT3BYrGgtrZW70hERIbBt08lsrGxgbm5OSSTyc/P\nbDYbfD4f3G63jsmIiIyBpSiJra0tjI2NweVywel0ory8HPf394hEIvD7/TCbzXC5XHrHJCLKazw+\nlUR7ezsaGxsxOTn5Zc3v9+Pg4ACbm5vaByMiMhBOrpXE9fX1tz+5aGlpweXlpcaJiIiMh6Uoierq\napydneVcOz09hcVi0TgREZHx8E5REp2dnVhYWEBxcTHa2tpQWlqKdDqN7e1tLC4uwuv16h2RiCjv\n8U5REm9vbxgeHkYkEoEQAiaTCe/v7wCA1tZWzM7OorCwUOeURET5jTtFSRQUFMDj8aCurg5WqxXp\ndBpCCBwdHWFgYICFSET0A3inKIloNIqenh7E43F4PB4MDg5CVVXc3d2hu7sb+/v7ekckIsp7PD6V\nREdHBxRFwdTU1Je18fFxnJycIBwO65CMiMg4uFOUxNXVFZxOZ841h8OB8/NzjRMRERkPS1ESFRUV\nSCQSOdcODw9htVo1TkREZDx80UYSXV1dCAaDyGazUFUVNpsNyWQSOzs7WFpaQn9/v94RiYjyHu8U\nJZHJZBAIBLC+vo5MJvP5uclkgtvtxujoKIQQOiYkIsp/LEXJpFIpJBIJpFIpmM1mKIqCsrIyvWMR\nERkCS5GIiOgDX7QhIiL6wFIkIiL6wFIkIiL6wFIkIiL68AdNXgzDhd+LKQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x22c84c356a0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "helpful_video_games2 = helpful_video_games.copy()\n",
    "helpful_video_games2['wasHelpful'] = helpful_video_games.helpfulRate.map(lambda x: 'notHelpful' if x < 0.33 else 'controversial' if x < 0.66 else 'helpful')\n",
    "\n",
    "label_encoder2 = LabelEncoder()\n",
    "label_encoder2.fit_transform(helpful_video_games2['wasHelpful'])\n",
    "\n",
    "groupby_helpful = helpful_video_games2.groupby('wasHelpful')\n",
    "\n",
    "groupby_helpful['overall'].count().plot.bar(title='Helpful distribution for ' + str(len(helpful_video_games2)) + ' video games reviews');\n",
    "ax1 = plt.axes()\n",
    "ax1.xaxis.label.set_visible(False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We see that ther are still more helpful review than the others type, the dataset is still imbalanced.\n",
    "\n",
    "Let's retest with our **using only overall** feature:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 501,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "crossval f1-score: 0.399567548002\n"
     ]
    }
   ],
   "source": [
    "clf, x, y = train_network(helpful_video_games2, ['overall'], 100)\n",
    "scores = cross_val_score(clf, x, y, cv=4, scoring='f1_macro')\n",
    "print(\"crossval f1-score:\", np.mean(scores))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The f1-score of our network dropped significantly. Let's find out how he classified our data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 484,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 star review: ['notHelpful']\n",
      "2 star review: ['helpful']\n",
      "3 star review: ['helpful']\n",
      "4 star review: ['helpful']\n",
      "5 star review: ['helpful']\n"
     ]
    }
   ],
   "source": [
    "for i in range(1, 6):\n",
    "    print(str(i) + ' star review: ' + str(label_encoder2.inverse_transform(clf.predict(i))))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see that our neural networks is limited here, and have some difficulties determining when the reviews should be \"polemical\".\n",
    "##### Using only reviewLength\n",
    "We will now introduce more features to see if we can improve our f1-score score which dropped a lot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 502,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "crossval f1-score: 0.235087840403\n"
     ]
    }
   ],
   "source": [
    "# We increase the number of iterations as we have a higher scope of possibilities\n",
    "clf, x, y = train_network(helpful_video_games2, ['reviewLength'], 1000)\n",
    "scores = cross_val_score(clf, x, y, cv=4, scoring='f1_macro')\n",
    "print(\"crossval f1-score:\", np.mean(scores))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(0, 100000):\n",
    "    if clf.predict(i)[0] != label_encoder2.transform(['helpful'])[0]:\n",
    "        print(i)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see with the previous code that our classifer always return *helpful* as the level of helpfulness of the review; it does not find any trends in the dataset.\n",
    "\n",
    "##### Using only summaryLength\n",
    "\n",
    "By using only the review length, we get a really lower range. It is not possible, only considering the review length, to determine if it would be helpful. We will need to go deeper and analyse the review contents."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "crossval f1-score: 0.235138637116\n"
     ]
    }
   ],
   "source": [
    "clf, x, y = train_network(helpful_video_games2, ['summaryLength'], 1000)\n",
    "scores = cross_val_score(clf, x, y, cv=3, scoring='f1_macro')\n",
    "print(\"crossval f1-score:\", np.mean(scores))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our 3-class `helpful`, `notHelpful` and `controversial` predictions ares not very good. We will go back to an easier task, the binary classification `helpful` and `notHelpful`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### More features and analysis\n",
    "\n",
    "We already have the `overall`, `reviewLength` and `summaryLength`.\n",
    "\n",
    "We will start now with more features declined from text to increase our prediction scores :\n",
    "- **exclamationCount** : A text with a lot of \"!\" probably written by a irritated guy\n",
    "- **questionCount** : Maybe including questions in the review can impact the helpfulness\n",
    "- **threeDotsCount** : The elipsis mark can signify some fed-up from the reviewer\n",
    "- **uppercaseCount** : A review written in full CAPS-LOCK can be considered as a bad review\n",
    "\n",
    "We add also these products related features :\n",
    "- **price** : A product with a high price might have better quality review ?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 414,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>reviewText</th>\n",
       "      <th>wasHelpful</th>\n",
       "      <th>exclamationCount</th>\n",
       "      <th>questionCount</th>\n",
       "      <th>threeDotsCount</th>\n",
       "      <th>uppercaseCount</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>asin</th>\n",
       "      <th>reviewerID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">0700099867</th>\n",
       "      <th>A2HD75EMZR8QLN</th>\n",
       "      <td>Installing the game was a struggle (because of...</td>\n",
       "      <td>helpful</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A1DLMTOTHQ4AST</th>\n",
       "      <td>I got this version instead of the PS3 version,...</td>\n",
       "      <td>helpful</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AN3YYDZAS3O1Y</th>\n",
       "      <td>Loved playing Dirt 2 and I thought the graphic...</td>\n",
       "      <td>helpful</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AQTC623NCESZW</th>\n",
       "      <td>I can't tell you what a piece of dog**** this ...</td>\n",
       "      <td>notHelpful</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A10AYT89XSCE46</th>\n",
       "      <td>This game is bug landFirst had problems instal...</td>\n",
       "      <td>notHelpful</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                  reviewText  \\\n",
       "asin       reviewerID                                                          \n",
       "0700099867 A2HD75EMZR8QLN  Installing the game was a struggle (because of...   \n",
       "           A1DLMTOTHQ4AST  I got this version instead of the PS3 version,...   \n",
       "           AN3YYDZAS3O1Y   Loved playing Dirt 2 and I thought the graphic...   \n",
       "           AQTC623NCESZW   I can't tell you what a piece of dog**** this ...   \n",
       "           A10AYT89XSCE46  This game is bug landFirst had problems instal...   \n",
       "\n",
       "                           wasHelpful  exclamationCount  questionCount  \\\n",
       "asin       reviewerID                                                    \n",
       "0700099867 A2HD75EMZR8QLN     helpful                 1              2   \n",
       "           A1DLMTOTHQ4AST     helpful                 2              0   \n",
       "           AN3YYDZAS3O1Y      helpful                 2              0   \n",
       "           AQTC623NCESZW   notHelpful                 0              0   \n",
       "           A10AYT89XSCE46  notHelpful                 2              0   \n",
       "\n",
       "                           threeDotsCount  uppercaseCount  \n",
       "asin       reviewerID                                      \n",
       "0700099867 A2HD75EMZR8QLN               0              27  \n",
       "           A1DLMTOTHQ4AST               0              60  \n",
       "           AN3YYDZAS3O1Y                3              23  \n",
       "           AQTC623NCESZW                0              22  \n",
       "           A10AYT89XSCE46               0              26  "
      ]
     },
     "execution_count": 414,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Add features\n",
    "helpful_video_games['exclamationCount'] = helpful_video_games['reviewText'].str.count('!') + helpful_video_games['summary'].str.count('!')\n",
    "helpful_video_games['questionCount'] = helpful_video_games['reviewText'].str.count('\\?') + helpful_video_games['summary'].str.count('\\?')\n",
    "helpful_video_games['threeDotsCount'] = helpful_video_games['reviewText'].str.count('\\.\\.\\.') + helpful_video_games['summary'].str.count('\\.\\.\\.')\n",
    "helpful_video_games['uppercaseCount'] = helpful_video_games['reviewText'].str.count('[A-Z]') + helpful_video_games['summary'].str.count('[A-Z]')\n",
    "\n",
    "helpful_video_games[['reviewText','wasHelpful', 'exclamationCount', 'questionCount', 'threeDotsCount', 'uppercaseCount']].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's plot how these features separate the reviews helpfulness"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 335,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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9W1evXnUbv3Xrlt5991317dvXS8kqPtbEDZGSkqK0tDQ9/fTTCg8PV2hoqBwO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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x22c83d42940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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RGRkJe3t7nW/kCoUC27dvx/Tp0/HLL78gIiICO3fuhLOzM7Zu3frYSdn68vT0hL+/PwoK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\npgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x22c83a1f470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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ODtaGKJueMnzfTZNUKuF73wgMEgaVlZUAgD/96U946623AAADBgxAcXEx5HI5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\nICIiMAyIiAgMAyIiAsOAiIgA/B/nJBPiSlVbPQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x22c839671d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "groupby_helpful = helpful_video_games.groupby('wasHelpful')\n",
    "\n",
    "def plot_bar_chart(title, column):\n",
    "    groupby_helpful[column].mean().plot.bar(title=title, yerr=groupby_helpful[column].std()/2);\n",
    "    ax1 = plt.axes()\n",
    "    ax1.xaxis.label.set_visible(False)\n",
    "    plt.show()\n",
    "    \n",
    "plot_bar_chart('Average Overall', 'overall')\n",
    "plot_bar_chart('Average Review length', 'reviewLength')\n",
    "plot_bar_chart('Average Uppercase letter count', 'uppercaseCount')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We see that the feature `reviewLength` \"separate\" the most, and so gives the most information about that. The others features `overall` and `uppercase count` are give little less but still acceptable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 336,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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OrzvVVfVh36w0xCVJAgDIZLIyl5fXLrL4pUMNXUKl+pz8Avfu5cK6WRMh6qXn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\nxhAnIhIYQ5yISGD/D3xUrCLgA7XoAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x22c83c50748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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RyDD4iYhEhsFPRCQyDH4iIpFh8BMRiQyDn4hIZBj8REQiw+AnIhIZBj8Rkcgw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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x22c82770be0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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p74s/d6qqqsOxKcsIIi8vDwBgY2Nj0G5jYwOdToeCggKjfdLS0qDVamFjY4OF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\nJIkBQUREkhgQREQkiQFBRESS/g/RbYFLeOxzpwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x22c8272b080>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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JrtpBf/DgQbi4uGi0SZKE6OhoeHp6wsnJCdOmTUN6errOiiQiopqrVtCfO3cO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\nGSbcCQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x22c8242f0f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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VYWFhMDExgYmJidY2DRs2RHZ2tk6LJSKiiisz6CVJgre3N1JSUrBs2TLY2Njg1KlTCAkJ\ngbm5OSRJgkwmK3Hb0tpfRqVSV3gbermiIomfK1VLPDd1p2lTs1L7ygz65ORkJCcnY/369RgxYgQA\noE+fPigsLMQnn3yCefPmIS8vD/n5+TA2NtZsl5OTAzOz0g9MRET6UebF2Pv37wMAunfvrtXeo0cP\n5ObmQiaTQZIkpKWlafWnpaWhffv2OiyViIgqo8ygt7a2BgCcP39eq/3ixYswMjLC0KFDUbduXcTH\nx2v6MjMzkZSUBCcnJ91WS0REFVbm0o2dnR1cXFywYsUKqFQq2NjYICkpCdu2bcP06dPRvHlzeHh4\nIDg4GHK5HNbW1ggNDYWpqSnc3d318T0QEdFLlOuum+DgYKxfvx6hoaHIzMxEu3btsHjxYkyePBkA\nMH/+fMjlckRERECtVsPBwQGBgYFcoyciqgZkkiRJhi7ifz16xNcm6Mq4cSPw6NEjNG7cBPv3f2vo\ncog0eG7q3svuuuHbK4mIBMegJyISHIOeiEhwDHoiIsEx6ImIBMegJyISHIOeiEhwDHoiIsEx6ImI\nBMegJyISHIOeiEhwDHoiIsEx6ImIBMegJyISHIOeiEhwDHoiIsEx6ImIBMegJyISHIOeiEhwDHoi\nIsEx6ImIBMegJyISHIOeiEhwDHoiIsEx6ImIBMegJyISHIOeiEhwDHoiIsEx6ImIBMegJyISXLmD\nPjExEe7u7rC3t8fAgQOxYcMGFBYWAgAkSYJSqYSLiwu6deuGGTNmICUlpcqKJiKi8itX0CcnJ8PH\nxwc2NjYICwvD1KlTsXXrViiVSgBASEgIlEolvLy8EBQUhKysLHh6eiIrK6tKiyciorIZlWfQp59+\nir59+yIwMBAA4OTkBJVKhTNnzsDT0xPh4eHw8/PD9OnTAQA9e/bEwIEDER0djRkzZlRd9UREVKYy\nZ/Tp6ek4f/483njjDa12f39/REVF4eLFi1Cr1XB1ddX0WVhYoHfv3khISNB9xUREVCFlBv2vv/4K\nSZLQoEEDzJw5E127doWTkxM2btyIoqIipKamAgDatGmjtV3r1q01fUREZDhlLt1kZGQAAD744AO4\nubnB09MTZ8+ehVKpRN26dSFJEkxMTGBiYqK1XcOGDZGdnV3hgiwtG1R4G3o5uVzGz5WqJZ6b+lFm\n0Ofn5wMA/u///g8LFiwAADg6OiIjIwNKpRK+vr6QyWQlbltaOxER6U+ZQd+wYUMAQL9+/bTanZ2d\n8cUXX8Dc3Bx5eXnIz8+HsbGxpj8nJwdmZmYVLkilUld4G3q5oiKJnytVSzw3dadp09Lztsw1+rZt\n2wL478z+uYKCAgCAkZERJElCWlqaVn9aWhrat29f4WKJiEi3ygz6V155Bc2aNcO3336r1X78+HH8\n7W9/w6hRo1C3bl3Ex8dr+jIzM5GUlAQnJyfdV0xERBVS5tKNXC7H/PnzsWDBAixbtgzDhw/HqVOn\nEBcXh+XLl8PU1BQeHh4IDg6GXC6HtbU1QkNDYWpqCnd3d318D0RE9BLlemBq7NixMDIyQlhYGGJj\nY9GiRQusWLECkyZNAgDMnz8fcrkcERERUKvVcHBwQGBgYKXW6ImISLfKFfQA4ObmBjc3t5J3YmQE\nf39/+Pv766wwIiLSjXIHPRHVDF6BRw1dQpnS//gTAKDKflrt640IGGToEv4yvqaYiEhwDHoiIsEx\n6ImIBMegJyISHC/GVlJ1v4AE8IIXET3DGT0RkeAY9EREgmPQExEJjkFPRCQ4Bj0RkeAY9EREgmPQ\nExEJjkFPRCQ4Bj0RkeAY9EREgmPQExEJjkFPRCQ4Bj0RkeAY9EREgmPQExEJjkFPRCQ4Bj0RkeAY\n9EREgmPQExEJjkFPRCQ4Bj0RkeAY9EREgmPQExEJjkFPRCQ4Bj0RkeAqFPR5eXkYMWIEAgICNG2S\nJEGpVMLFxQXdunXDjBkzkJKSovNCiYiocioU9Js2bcL169e12kJCQqBUKuHl5YWgoCBkZWXB09MT\nWVlZOi2UiIgqp9xB/8svvyAqKgpWVlaatuzsbISHh8PPzw/Tp0+Hq6srwsPDkZOTg+jo6CopmIiI\nKqZcQV9QUIBFixbB29sbzZo107RfvHgRarUarq6umjYLCwv07t0bCQkJuq+WiIgqrFxBv3XrVuTn\n58PX11erPTU1FQDQpk0brfbWrVtr+oiIyLCMyhqQkpKC0NBQ7NixAyYmJlp92dnZMDExKdbesGFD\nZGdnV6ogS8sGldqOajb+3Km6EuHcfOmMvqioCIsXL8bEiRPh4OBQrF+SJMhkshK3La2diIj066Uz\n+qioKNy7dw9btmxBQUGBpl2SJBQUFMDMzAx5eXnIz8+HsbGxpj8nJwdmZmaVKkilUldqO6rZ+HOn\n6qqmnJtNm5aeuS+d0cfHx+P+/fvo1asXunTpgi5duuDq1avYt28funTpAiMjI0iShLS0NK3t0tLS\n0L59e91UT0REf8lLZ/QrVqxATk6OVpu/vz/at2+POXPmoH379vj4448RHx8PHx8fAEBmZiaSkpLg\n5+dXdVUTEVG5vTToO3ToUKytXr16sLS0RNeuXQEAHh4eCA4Ohlwuh7W1NUJDQ2Fqagp3d/eqqZiI\niCqkzLtuyjJ//nzI5XJERERArVbDwcEBgYGBlV6jJyIi3apw0O/fv197B0ZG8Pf3h7+/v86KIiIi\n3eHbK4mIBMegJyISHIOeiEhwDHoiIsEx6ImIBMegJyISHIOeiEhwDHoiIsEx6ImIBMegJyISHIOe\niEhwDHoiIsEx6ImIBMegJyISHIOeiEhwDHoiIsEx6ImIBMegJyISHIOeiEhwDHoiIsEx6ImIBMeg\nJyISHIOeiEhwDHoiIsEx6ImIBMegJyISHIOeiEhwDHoiIsEx6ImIBMegJyISHIOeiEhw5Qr6wsJC\nbN++HSNGjED37t0xcuRIfP7555AkCQAgSRKUSiVcXFzQrVs3zJgxAykpKVVaOBERlU+5gn7z5s0I\nCgrC6NGjoVQqMWLECKxatQrbtm0DAISEhECpVMLLywtBQUHIysqCp6cnsrKyqrR4IiIqm1FZA57P\n5r29vTFr1iwAgJOTE9LT0xEREYEpU6YgPDwcfn5+mD59OgCgZ8+eGDhwIKKjozFjxoyq/Q6IiOil\nypzRZ2dnY+zYsRg6dKhWe/v27ZGeno7Tp09DrVbD1dVV02dhYYHevXsjISFB9xUTEVGFlDmjt7Cw\nwIcfflis/dixY2jevDkePHgAAGjTpo1Wf+vWrXH06FEdlUlERJVVZtCXZO/evTh16hSWLFmC7Oxs\nmJiYwMTERGtMw4YNkZ2dXeF9W1o2qExJVMPx507VlQjnZoVvrzxw4ACWLVuGYcOGwcPDA5IkQSaT\nlTi2tHYiItKfCs3ot2/fjjVr1mDQoEFYt24dZDIZzMzMkJeXh/z8fBgbG2vG5uTkwMzMrMIFqVTq\nCm9DNR9/7lRd1ZRzs2nT0vO23EEfFBSEsLAwjB07Fh9//DGMjJ5t2q5dO0iShLS0NLRv314z/sWv\niYies+rQH0UFTyE3qmvoUmqFci3dREZGIiwsDNOnT0dgYKAm5AHAwcEBdevWRXx8vKYtMzMTSUlJ\ncHJy0n3FRFTjNbIZgCa2Q9HIZoChS6kVypzRP3z4EOvWrYNCocCoUaNw8eJFrX47Ozt4eHggODgY\ncrkc1tbWCA0NhampKdzd3auscCIiKp8yg/7EiRPIy8vDb7/9hkmTJhXrT0xMxPz58yGXyxEREQG1\nWg0HBwcEBgZWao2eiIh0q8ygHz9+PMaPH1/mjvz9/eHv76+Tokg3uA5KREAl76OnmoHrn0QE8DXF\nRETCY9ATEQmOQU9EJDgGPRGR4Bj0RESCY9ATEQmOQU9EJDgGPRGR4Bj0RESCY9ATEQmOQU9EJDgG\nPRGR4Bj0RESCY9ATEQmOQU9EJDgGPRGR4Bj0RESCY9ATEQmOQU9EJDgGPRGR4Bj0RESCY9ATEQmO\nQU9EJDgGPRGR4Bj0RESCY9ATEQmOQU9EJDgGPRGR4Bj0RESCY9ATEQlOp0G/Z88eDB06FPb29pg0\naRIuXLigy90TEVEl6Czo4+LisGzZMowePRobN26EmZkZvL29cfv2bV0dgoiIKkEnQS9JEjZu3Ig3\n3ngDfn5+GDBgAJRKJaysrBAZGamLQxARUSXpJOhv3ryJO3fuYNCgQZo2Y2NjuLi4ICEhQReHICKi\nSjLSxU5SU1MBAO3atdNqb9OmDW7duoXCwkLUqVOnXPuytGygi5KohuHPnaorEc5NnQR9dnY2AKBh\nw4Za7Q0bNkRRURFyc3Nhamparn0ZG5fvPwiGdvDTMYYugahEPDfpRTpbowcAmUxWYn9p7UREVPV0\nEvRmZmYAgJycHK32nJwc1KlTp9hMn4iI9EcnQf98bf7FWylv374Na2trXRyCiIgqSSdBb21tjRYt\nWiA+Pl7Tlp+fjx9++AFOTk66OAQREVWSTi7GymQy+Pj4YOXKlbCwsMBrr72Gzz//HBkZGfD09NTF\nIYiIqJJk0vMrqToQERGBnTt3IiMjA506dcKCBQvg4OCgq90TEVEl6DToiYio+uHbK4mIBMegJyIS\nHIOeiEhwDHoiIsEx6ImIBMegJyISnE4emCLDUalUFRpvaWlZRZUQUXXF++hruI4dO1bo7aBXrlyp\nwmqItDk4OJT7/JTJZEhOTq7iimonzuhruFWrVvE10FRteXl58fysBjijJyISHGf0Atm0aVOZY/z8\n/PRQCVFx+/btK3PM2LFj9VBJ7cMZvUB69epVrC03NxcFBQUwNzdH27ZtER0dbYDKiJ5dTyqJTCaD\niYkJGjRogMTERD1XVTtwRi+Qs2fPlth+4cIFBAQEYObMmXquiOi/Sjo/1Wo1zp49i6CgIHzyyScG\nqKp24Iy+ljh06BA2b96Mw4cPG7oUomL27t2LXbt2ITY21tClCIkPTNUSZmZmSEtLM3QZRCVq1aoV\nrl27ZugyhMWlG4Fcvny5WFtRUREePnyI4OBg2NraGqAqomdKerjv+fmpVCrRtm1bA1RVOzDoBTJh\nwoQS71mWJAnNmjVDcHCwAaoiesbR0bHUe+pNTEx4flYhrtHXcPfu3UOLFi0AAElJScX6ZTIZTE1N\nYWtrC7mcK3WkXwUFBTAyejafjIuLK9b//Pzs06cPzMzM9F1ercEZfQ03duxYbN68GT169EBcXBxm\nz56NNm3aGLosIgCAi4sLNm3ahO7du+POnTtwd3dHs2bNDF1WrcMpXg2Xl5eHH3/8ERkZGYiLi8Pt\n27ehUqlK/UekT1lZWbh16xYAICQkBA8ePDBwRbUTl25qOH9/fxw6dAgymQySJJX5XhG+1Iz0ycfH\nBydOnEC9evWQm5uL+vXrl3qO8qVmVYdBX8MVFBQgISEBKpUKCxcuxKxZs15698K4ceP0WB3VdllZ\nWdi/fz9UKhU2bdqEiRMnonnz5qWO5ys6qgaDXiALFy7kGj1VW9OmTcPy5cthY2Nj6FJqHQa9gM6d\nO4dz584hMzMTjRo1gqOjI7p27WrosogAAHfv3kVycrLm/OzVqxeaNm1q6LKExqAXyB9//IFZs2Yh\nOTkZRkZGsLS0hEqlQmFhIVxcXBAcHAwTExNDl0m1VF5eHhYvXoxDhw7hf2OnTp06ePPNN7Fo0SK+\nu76K8PZKgaxYsQI3btxAWFgYBgwYAODZw1LHjh3DkiVLsG7dOixatMjAVVJttWbNGsTHx2PJkiUY\nPHgwrKyskJ6ejiNHjiAoKAhWVlaYPXu2ocsUEmf0AunVqxeWLFmCMWPGFOuLiYnBunXr+BpYMhgn\nJyf4+flh6tSpxfp27tyJ8PBwHD9+3ACViY/30QvE2NgY9evXL7HP0tISRUVFeq6I6L8KCgrQsmXL\nEvvatWuHrKwsPVdUezDoBeLl5YV169bh+vXrWu0PHjxASEgIvL29DVQZ0bN3MYWEhCAzM1Or/enT\np9ixYwfc3d0NVJn4uEYvkHPnziE9PR1ubm6wtbVF06ZNoVKpcPXqVeTn5yM/Px8HDx4E8OzhlAMH\nDhi4YqpNnj59itTUVAwcOBDOzs6a8/PMmTNQqVQwNjbW/HEcmUwGpVJp4IrFwaAXiJWVFYYMGaLV\n1rhxY97nT/FkAAAF/UlEQVS3TNXCtWvX0KlTJwBAZmamZmb//PzMzc01WG2i48VYIiLBcUZfw5X0\nx0ZepkuXLlVUCVFxFX2RnqWlZRVVUrtxRl/DdezYsVwPmTx/4Rlfakb6VN7z8zmen1WDM/oabufO\nnYYugahUq1at4tOu1QBn9IIqKChARkYGrKysNH/hh4hqJyaAYH788UesX78eycnJKCwsxN69e7F9\n+3a0atUK8+bNM3R5VMvdvn0boaGhSExMxOPHj7Fr1y4cOHAAr7zyCu+jr0J8YEogiYmJ8PDwAADM\nmzdP8+IohUKBrVu3Yvv27YYsj2q5K1euYNy4cUhOTsagQYOQn58P4Nn1ow8//BD79u0zcIXi4tKN\nQCZMmAAbGxusXbsWBQUFsLOzQ0xMDLp06YINGzbg8OHD+Pbbbw1dJtVS06ZNQ926dbFlyxYUFRVp\nnZ8rVqzA+fPnsX//fkOXKSTO6AXy+++/Y/To0QBQ7AJYnz59cPfuXUOURQQAuHTpEqZNmwa5XF7s\n/Bw+fDhu3rxpoMrEx6AXSOPGjXHt2rUS+1JSUtC4cWM9V0T0X6ampnj06FGJfffu3YOpqameK6o9\nGPQCGTt2LIKDgxETE4P09HQAQGFhIU6dOoVNmzbBzc3NwBVSbTZ8+HAEBQXh9OnTmutHMpkMN27c\nwKZNm+Dq6mrgCsXFNXqBFBYWYsmSJYiLi4NMJoMkSZDL5ZAkCUOGDMGnn34KY2NjQ5dJtVRubi5m\nzpyJM2fOoH79+sjNzUWTJk2Qnp4OOzs7REREcFZfRRj0AkpJSUFSUhIyMzNhZmaGHj16oGPHjoYu\niwgAkJCQgKSkJKhUKpiamqJHjx4YNGgQ5HIuMFQVBj0RkeD4wJRACgsLsXv3bpw5cwZ//PFHsb8o\nJZPJEBkZaaDqqDaqyLMbMpkMnp6eVVdMLcYZvUBWr16NyMhIKBQKtGrVqsRfhUNCQgxQGdVWJS0Z\nPr9+VFI7X2pWNRj0AnF0dMSUKVPw7rvvGroUohK9+CAf6QevfggkLy8Pjo6Ohi6DqFR8k6VhMOgF\nMnDgQBw5csTQZRBRNcOLsTXc/17sat26NbZt24Zbt26he/fuqF+/vtZYXuwiqp24Rl/DVeT+eF7s\nIkMrLCxEly5duEavZ5zR13BXr141dAlEFca1ev3ijJ6IqoyDg0OxUFer1ahfv36xdplMhuTkZH2W\nV2twRk9EVcbLy4uz92qAM3oiqhaKior4vpsqwk+ViPTC1dW11GtKly5dgpOTk54rqj24dENEVebL\nL7/E06dPAQB37txBTEwMWrZsWWxccnJysXczke4w6ImoymRkZGDjxo0Anl1sjYqKKjZGLpfDzMwM\nc+fO1Xd5tQbX6IlILzp27Ig9e/bA3t7e0KXUOgx6ItI7tVqNnJwcWFhYwMTExNDlCI9LN0SkNydP\nnkRQUBCuXLmieVVxly5d8Pe//x0DBgwwcHXi4oyeiPTi5MmT8PX1RdeuXTFy5Eg0adIEDx8+xDff\nfIOffvoJW7duRd++fQ1dppAY9ESkF+7u7mjZsiWCg4OL9c2dOxcPHjzArl27DFCZ+HgfPRHpxW+/\n/YaJEyeW2DdhwgS+t6kKMeiJSC+aNGmC+/fvl9h37969Yq/VJt1h0BORXgwdOhRBQUE4deqUVvvJ\nkyexfv16DBkyxECViY9r9ESkF2q1Gt7e3rhw4QJMTU3RuHFjPHnyBDk5ObC3t0d4eDhMTU0NXaaQ\nGPREpDeSJOHYsWM4e/YssrKyYGFhgR49esDFxYUvNKtCDHoiIsHxgSki0ouioiLs2bMHx48fR25u\nbrGXmMlkMkRGRhqoOrEx6IlILwIDA7Fz50507twZzZo141KNHnHphoj0wtHRER4eHvDz8zN0KbUO\n/5NKRHqRl5eHnj17GrqMWolBT0R64eLigvj4eEOXUStxjZ6I9KJfv35YvXo10tLSYG9vX+xJWJlM\nBk9PT8MUJziu0RORXnTs2PGl/TKZDFeuXNFTNbULg56ISHBcoyciEhyDnohIcAx6IiLBMeiJiATH\noCciEtz/A4PwIALlHhcnAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x22c82570a58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_bar_chart('Average Exclamation mark count \"!\"', 'exclamationCount')\n",
    "plot_bar_chart('Average Question mark count \"?\"', 'questionCount')\n",
    "plot_bar_chart('Average Three dots count \"...\"', 'threeDotsCount')\n",
    "plot_bar_chart('Average Summary length', 'summaryLength')\n",
    "plot_bar_chart('Average price', 'price')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We are more mitigated concerning the `threeDotsCount`, `questionCount`, `exclamationCount`. We see that there is a low usage of these in the review. Then `summaryLength` and `price` separate also separate poorly the helpfulness. These are probably bad features. \n",
    "But maybe the combinations of these with others features can give us a lot of information concerning the helpfulness. We will see later.\n",
    "\n",
    "\n",
    "We now have 8 features. We will start now using words embeddings to exploit the full potential of the content of each review.\n",
    "\n",
    "#### Text features : word2vec\n",
    "To use the word2vec embeddings, we need to train the a model with our review text words.\n",
    "\n",
    "Let's first obtain these words by tokenization.\n",
    "\n",
    "##### Text preprocessing\n",
    "\n",
    "We create a NLTK preprocessor, sklearn pipeline compatible, that will have the job to preprocess our text :\n",
    "- Break the raw text into sentences\n",
    "- Divide the sentences into words\n",
    "- Convert to lower case\n",
    "- Remove the english stopwords and punctuation\n",
    "- Lemmatize each tokens"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Source: https://bbengfort.github.io/tutorials/2016/05/19/text-classification-nltk-sckit-learn.html\n",
    "\n",
    "class NLTKPreprocessor(BaseEstimator, TransformerMixin):\n",
    "\n",
    "    def __init__(self, stopwords=None, punct=None,\n",
    "                 lower=True, strip=True):\n",
    "        self.lower      = lower\n",
    "        self.strip      = strip\n",
    "        self.stopwords  = stopwords or set(sw.words('english'))\n",
    "        self.punct      = punct or set(string.punctuation)\n",
    "        self.lemmatizer = WordNetLemmatizer()\n",
    "\n",
    "    def fit(self, X, y=None):\n",
    "        return self\n",
    "\n",
    "    def inverse_transform(self, X):\n",
    "        return [\" \".join(doc) for doc in X]\n",
    "\n",
    "    def transform(self, X):\n",
    "        return [\n",
    "            list(self.tokenize(doc)) for doc in X\n",
    "        ]\n",
    "\n",
    "    def tokenize(self, document):\n",
    "        # Break the document into sentences\n",
    "        for sent in sent_tokenize(document):\n",
    "            # Break the sentence into part of speech tagged tokens\n",
    "            for token, tag in pos_tag(wordpunct_tokenize(sent)):\n",
    "                # Apply preprocessing to the token\n",
    "                token = token.lower() if self.lower else token\n",
    "                token = token.strip() if self.strip else token\n",
    "                token = token.strip('_') if self.strip else token\n",
    "                token = token.strip('*') if self.strip else token\n",
    "\n",
    "                # If stopword, ignore token and continue\n",
    "                if token in self.stopwords:\n",
    "                    continue\n",
    "\n",
    "                # If punctuation, ignore token and continue\n",
    "                if all(char in self.punct for char in token):\n",
    "                    continue\n",
    "\n",
    "                # Lemmatize the token and yield\n",
    "                lemma = self.lemmatize(token, tag)\n",
    "                yield lemma\n",
    "\n",
    "    def lemmatize(self, token, tag):\n",
    "        tag = {\n",
    "            'N': wn.NOUN,\n",
    "            'V': wn.VERB,\n",
    "            'R': wn.ADV,\n",
    "            'J': wn.ADJ\n",
    "        }.get(tag[0], wn.NOUN)\n",
    "\n",
    "        return self.lemmatizer.lemmatize(token, tag)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original review text:\n",
      "I purchased these for my Wii as Nintendo no longer produces Wavebird controllers by virtue of them being sued by a patent owner over the technology. I didn't want to pay for a used Wavebird on eBay, so I bought some of these. I sit back from my HDTV about 9 feet so I needed these for the wired Gamecube controllers and they work very well. Even with Mario Kart Wii, there is some lag with the Wavebird, but there is no lag with these extension cables. Highly recommended!\n",
      "\n",
      "Preprocessed text:\n",
      "['purchase', 'wii', 'nintendo', 'longer', 'produce', 'wavebird', 'controller', 'virtue', 'sue', 'patent', 'owner', 'technology', 'want', 'pay', 'used', 'wavebird', 'ebay', 'buy', 'sit', 'back', 'hdtv', '9', 'foot', 'need', 'wired', 'gamecube', 'controller', 'work', 'well', 'even', 'mario', 'kart', 'wii', 'lag', 'wavebird', 'lag', 'extension', 'cable', 'highly', 'recommended']\n"
     ]
    }
   ],
   "source": [
    "print('Original review text:')\n",
    "print(helpful_video_games.iloc[19].reviewText)\n",
    "print()\n",
    "print('Preprocessed text:')\n",
    "print(NLTKPreprocessor().transform([helpful_video_games.iloc[19].reviewText])[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Training the word2vec model\n",
    "(This part has been done in another [notebook](https://nbviewer.jupyter.org/github/Coac/epfl-ada/blob/master/Project/Helpful%20score%20prediction.ipynb#Train-w2v) to avoid to surcharge this main notebook)\n",
    "\n",
    "We trained it with all the review and summary text (1,868,601 raw sentences) from all the video games review.\n",
    "The vocabulary length is 59397.\n",
    "\n",
    "\n",
    "We will just load the trained model.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model loaded\n"
     ]
    }
   ],
   "source": [
    "import gensim\n",
    "w2v_model = gensim.models.word2vec.Word2Vec.load(\"w2v/video_games.w2v\")\n",
    "print(\"Model loaded\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's now plot the words into a 2d-space"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "word_vectors_matrix shape is  (10000, 300)\n",
      "word_vectors_matrix_2d shape is  (10000, 2)\n",
      "Points DataFrame built\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>word</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>instal</td>\n",
       "      <td>-6.611094</td>\n",
       "      <td>60.431065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>game</td>\n",
       "      <td>-20.650276</td>\n",
       "      <td>33.084148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>struggle</td>\n",
       "      <td>16.045649</td>\n",
       "      <td>4.731496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>window</td>\n",
       "      <td>-15.079869</td>\n",
       "      <td>59.436687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>live</td>\n",
       "      <td>-11.985738</td>\n",
       "      <td>8.099268</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       word          x          y\n",
       "0    instal  -6.611094  60.431065\n",
       "1      game -20.650276  33.084148\n",
       "2  struggle  16.045649   4.731496\n",
       "3    window -15.079869  59.436687\n",
       "4      live -11.985738   8.099268"
      ]
     },
     "execution_count": 192,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "count = 10000\n",
    "word_vectors_matrix = np.ndarray(shape=(count, 300), dtype='float64')\n",
    "word_list = []\n",
    "i = 0\n",
    "for word in w2v_model.wv.vocab:\n",
    "    word_vectors_matrix[i] = w2v_model[word]\n",
    "    word_list.append(word)\n",
    "    i = i+1\n",
    "    if i == count:\n",
    "        break\n",
    "print(\"word_vectors_matrix shape is \", word_vectors_matrix.shape)\n",
    "\n",
    "# Compress the word vectors into 2D space\n",
    "import sklearn.manifold\n",
    "tsne = sklearn.manifold.TSNE(n_components=2, random_state=0)\n",
    "word_vectors_matrix_2d = tsne.fit_transform(word_vectors_matrix)\n",
    "print(\"word_vectors_matrix_2d shape is \", word_vectors_matrix_2d.shape)\n",
    "\n",
    "points = pd.DataFrame(\n",
    "    [\n",
    "        (word, coords[0], coords[1]) \n",
    "        for word, coords in [\n",
    "            (word, word_vectors_matrix_2d[word_list.index(word)])\n",
    "            for word in word_list\n",
    "        ]\n",
    "    ],\n",
    "    columns=[\"word\", \"x\", \"y\"]\n",
    ")\n",
    "print(\"Points DataFrame built\")\n",
    "points.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 287,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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cJKDltAN6bYEUlAKCgYlPrarA7tbwguKjY5FbAi65/dPWpYsMmDyxKbc6wnU73Nj6UhPG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\n+9qNYeMaco+goCBYaL2gIB/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eP/6f3x4Ju2/AFezUli07DnROeztZYl2hRzcuTzgTRsyg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CDa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\neT7xdAtO7amRrbTrH5nFP3ynnVZUa6mzZJBTYgtUMd+XbAt7UmHw4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vzjD27hUhffHDmZ\nSqLcqMZX3+jA+fZxUR+gfDx3+kdncbUn7fejUACfYszz2TZ5++Y4GqtNVDHAjglCRchCMCo6BpA4\nyGaqzUJo7P/yc5vQUl9B7/NCR1rFFIrEUW834vDWddLqEwkvOQAoVShweNs6+m/23rsGZxBmKlDq\n1GX4kxe3YV2lHrtcNpw57gIASYP9M8ddOLLdST2d2u9MYdjtx+CED2dPuDAwPo8Rtx/lRjU67kzR\nqnyhCNcX37wyTD2lAI6kG/UG0DM8g011HOmJFGhciMXvmNePV77dimsCfyUAeP1X/egbmcPUfBin\n9tRig9MMk14lq6JlYw1HzoTDsVUpGkLeJ+sdJtHCAWLfzfbuUatKsd5hwuxCGBc6OO+4YDiOs8dd\nOLTVjg8+sQG/vnEfQ4wKNRpPomd4RlTdulSlqxy8eWUId8fTvpg6dRn+8ANbZbcpd30ldC4Ri6do\nhb6lXm+lWQu1qgTdi95txM+MjQO5KGSFCPHpunhrgpKtwONRoXm5KK4b8sdyCuAUKgolDorm5zJR\nJKaKWAtY7Th4ECRGIUFs4g6ANznzBaJwzwQxNL6ASCyBcoMaHzklvaB+EJAbBw+y6p5cw9OViLF8\n0kWA7ORTvseSg1xtIVzEi5m3s9dFTKt9gSi++bM+Hrnz0jMt0KjKEA7FeLH8/OH19FxiCw2SIuqo\n0GFHkxVnTzSh2mag6bU+f5Qu/glpJRXzcghesfMtpzJi/8gsvvj6DVzu9uByjxvbGipgs2hxcHNm\n1bUGpxFGLeeXxVbeEiPgShR8JU4qBShLS3gpiADXxgNjPty4M4mZ+QjveFKpRrmIT5a806pK8Llz\nO3mpf2ybxBJJXLrlxt7FioTCMYEs0KfmQ5JjQL7kn82ilSRdjVoVLnVNUHNnIDeBz7ZNhVGNEEM2\nvfzeTbw0HX4qT4Km35kMSvzJC9vw6s/7cPGWGxMzAex0VfJIoZ2uSlSYNZS0ImmB3rkQz0g/GI6j\ntc/NM+OutRnQPZQ2xq40q3F7dF70fgKhOG7cmcTFTjcvLoTxS9N0A+nxm4wB076w7AWRWGyR1N7J\n6QCtVKfXlEmS5PmMx+z75HKXG6f21ODQZgevUInYd+W8e4T3cua4i6a4eaaDvGcg1TZyiJX+kVm8\n/st+lBvVomlg2Y7BzhcUAD53bkfemzAVRk1Ghb7lLnqrLDrJOJA7V8w1FhQCaWXSq9BUY8alxY2Z\nx6VC83JRXD/mj5XesCwEFEocFIkpmSgSU0WsBaxmHDxIEqNQIFS3AMArr1/HxU53RhnpSIxbNMXi\nCRze6niobSM3Dlba+wlY3gR1JWMsn53xXOTTau6yi0FMPfTCkcaM80diCUz7wou74pmqlLPHXdix\naMZ6884kVZ+kUkA4msD3fnublrBnFxpEOTQxG8CuJhvPU8WkV2GnqxKHtjhkk0hylRlqVSnqHUas\nd5hytrU/GEPbbS/iiRRsFg0aHGaUlSrQPzoLfzCGL323nSqdItEEbtyZxOEt62DSq1BnN2ZMKjvu\nTPEqBgpxaEsV3rNtHRqrTagwqhCKJKh/0paGCqpIAIDN9RZMLpo2k6p0kWhC1HMmH+IzEkvgnc5x\nBMNxlBvVeO7g+gwV3ds3xxFLpMkf0qelxoRsY0A28s8XiOJKrxv/66e9ePtmuhy9zaIVJV3VqlJs\n22DFjX4PIrEkrZKXTY3Fts2HjjVih8uKhWAUn3q2JcM43x+M4XKXGylwMfafPrQd2xutOHPMhfHp\ngGSVtUAojtZ+D1p7vRib8uPoDie9FmE/1GlKEQinybFgOI69m2wYnwpQj6mPntqY9s7SKfHMgVrM\n+KIIhuMw6pRYWCSb2LgQLmw6703h3U5+LBK/NaG6K9uCSCy2NBol5vwR/O03r+J8+zgGxubx8nOb\nRT348h2PebEEoH9kDmNTAV6bin5XxrsnWz9h/dAIcSzmtZWLZO0fmcU/fKcdntkQLt5yo6XOwiOn\nch2DnS986llpvzgpkFTUJ7auQ9fgjGhsLAVScQDInysKxwJHhQ7D7gUMeXxQlpbgK9/rwIWOcbT2\nTUKtKkGFUfNQFuqVZi32Nj9+FZqXg+L6MX+sxoblw0ahxEGRmJKJIjGVRiHsjBQhjtWMg9UgMdYC\niLoFQIbZtFgZ6UJoG7lxsNKpHFwK2nVc6JgQTT/LhYcZY8shn3yBKH7XcR/n28bgnQ+jyqLNepxc\nY6haVYrN9eXUHPljT2aaI495/TySdH+LXTQlieyMKxUK+rfSEmBk0s8rYc8ap+dKIyTXmI1EEipp\nmmtzG3zLxZjXjy++3ka9lpBKobXfi9+1j+F6nxdtt70Z6XeRaJLeI5lUOip0cNWYYdAo8fqv+nmm\n0ixKFMBLT27ED98eRNvtKdz3BqBTl+LciSacOe5CbZWRZ4D9H963mZIT9got/uzDO9BSb8Hzh9dT\n0232eU7Nh9AxMAVHhS6nSoxNZ5oPRNFUkzZGVqu4ynViigGpMSHbGCC1K0wW6BdvuakBfDAch92q\nlVRA+QJRDLl9OL2/Hi31Fjy5p5ZnOC5GFJB7Is8sm3H+l7/bjvBiPKdSwPZGK/YtHlNMbUOej1Gn\nhD8ofg+kH7b2eRCNJ6EsLUGMMZLWa8uwwWHGeqcRrmozjDoVqsq1WFehx44mK156ciN2uGw4sMkO\nu1WLu2M+2l42iwb/+cwO0XhACvSZAMCORis+/VwLbIvjSrYFkVDxIxzXNBol2von8atrowCyq67y\nHY/ZWCIIhjkSo95hlPyu2LtHbIyUGqNJwQNSDEOsTeWk3rz+y354ZtM+dwvBKA5uceQ8hnCsk6MM\nFoIlvQbG5umYsVKLXrE4AOTPFYUm8v0jc7jczb0jWvs8mFv0OwxF4rg5MJ21T6825Kqzi+BQKITE\nWsOD3rBcbRRKHBSJKZkoElMc5Ow6FfHwsJpxsBp+FGsJwl1sk0HJ2x0nKIS2kRsHK+39dKXXTatZ\n5VqoimEtxpgvEMUXvtWK631ejHoD6B6cQWvfJA5uFh8b2TH0ws37cFVnVg7yBaL46hsd6B6cxeRs\nCCadCuVGNW/3X6wi3wanOcM76IdvD2BgbB7Tc2Gc3l8HZZmCLjYJTAYlzhxziaquxNII5bQJ+57Y\nVFeOf/n3HtwbX8DA2Dz2t9gRiSWWvMHxo3fuYXAi7SnDkgUAEE+keNXQgEwFRSSWwL/9vBcXb7nR\ndseLGV+E932iZgE4BcZCMMo7ZyiSwKGtdppORCpjPrmnFuPTAZzaXUMXljaLFtWVBlEfoP6RWbzy\n2g1ZqhSjVkWVIQBw3+vPiDUpxUA4nkRb/yTUZSWSKg/2+0S9wd4HuS52gc5il8uWQUCQY5F46Bme\nwQef2IAht4+3yLdbtfDOhbLGgxShe7XHg6uMF5VJp8SZ4y4eoSGssraprhzKMgXqHQZef2ipK4er\nOk2ctg940drLmfwL40xZpkDHwDS6B2fRPzKHYfcCLt5yo2NgCu6ZII5sd1JVnDAt8OxxF7Y1Wnnx\nQO5vcjaM9jvp6mye2RC6BmcoQSy1IMql+AG4d4NRr8KVrglKMqxfZxRVuGQbj8WeBYklz0wA3vkw\nPY5YyqZY3JFj5vLfEgNpE7E+BshLvSk3qnmqyU8928JrP/YYJoMSp/dxBRZWYk4sJL2UZQocWlR4\nrgbynSuyfcheocX1vnThC7pBwOBR8d15HFAohEQRDxeFEgdFYkomisQUh0fR8O1RwmrGwYM2sC40\niJlNs+XNT+2uyerV8SCRTxys5O7iiNvPK3cttVDNdi1rLcY6703xFpwAt2ssNTayY2g8kcLlLjf2\nNNskd/eD4Tg6BqZ4i57zHWO4wVTE06gUeO9i5Se+d9A1DNz3ofveDDoGptA1OIOzJ1zovDtNyQ2j\nTok//sBWjE8HqBG0nDTCXG3CvieSqRRNdQuE4jDrVfjXn3Xz1F5yj+8LRPG/z9+l1y8GBThyIhJL\notygxrlTrgyfG6EnkUFXhmgsCatJjXMnmvC+Q/WUdC4tUcA9E6KpeEC6dD1Z0BNlDllQEwImV1XB\nL75+naq7cqlS1KpSDLvncd8boJ+JxZqwT/sCUXzh1Vb84uoIJQrZFDqx7wuJJPY+2LGwtIS7bpNO\nifcdXk+rELKkhdi8wWnVo+2OF5FoAjaLBnfu+3ChQ3pxL6YQJN/pG57leQyd3l+HHa7KjLYjhAUh\nfjvvzmBiJogYs7A26ZRoqrHQYwvHNIO2DNF4EiadEv6QdAzmKqLAEmfCNh+b8qOsRMHz4yJEfzby\nLpfiB+DeDRpVGbavr4CjQoc79+dwqcuDSz0T2NbAfw9kIy2lyBgSS6yCUKqIARt37DGvdLupAkfO\nPFOOil9O6k2lWYuWOotkuqhaVYpNdeVou+OFzx9Dz/AMykpKKCnK+tXlTbqngBt3JhGJJqk/3VKI\nLpKGPeTxZU2nW8pckYxx3/7FbZ661GrSQKcuRSiSkEylLKJwUSiERBEPF4USB0ViSiaKxBSHR9Hw\n7VHCasfB4yyRZie2xGyafF5daUCleWkS/qWi7fYkvv6Tbpj0SqxbLI1N8LBeMOVGNSU1bBZtVkNs\nKTyMGHu3cxz/4wed0KnLUGeXT6QBRMXiQSiS9p6xmjR48ag4mWPUqnDh5n3EF9UXKWSSEew4S0AW\nPf5gDP/ykx7eMeMJoGtwmpdyx6bhEATDcdQtKkSCYc4D548/uBWv/ryPLjKPbHdiV1OlZBqhrFRu\nZpFls2gwMRWkRukKAMMeHxaC6ep1+WxwiBGBYiCL+nCU83zbIEgf5KemaFCqKEEoEodBq8LZE1z/\n3t/CN0pPpYDjO504sMmOIY8Pl7o8PNVbvhs3nfemcLk7rfQpUSCnSnBqPozuwTQJY9QqcSZHP+u8\nN4XftY3R67rS48bl7kxvMfb72dRM7Fh4YlcNugZn4AvEaNU5Qs4RssNZaeApTZ7Yug7/9OMuzC5E\nodWUYHO9Ff2jc5LtJqUQJN8ZGJ/jeXztaLLCVS1eIVJ4fzGB2uO+N8BrF+GY9ufndsJWroFaWYZA\nKMar/seCFBggzzIXMSIkoz/4xAaMTvpoHFtNGgyMZSfvcil+gPS7IZVMYnIuSFNDI9GkaAU4sfE4\nV5yzCsIXjjTKGsuv9njotccZZZrVpMaGdWaeYpSFFEkmZtouJ/VGKl2UoH90liqnA6E4Rjw+qhgq\nUQAnd9fkTFEVjqG+QBRf+V4HZn0RaNWl9Hj5jo1y07CBpc8RhIraYzud+L/evwXHdlZnTaUsonBR\nKIREEQ8XhRIHRWJKJorEFIdH0fDtUUKhDCxrFbkq8hRKTnnb7Ul87YddmA9Eca13EpFIHLV245L9\nI1YK/AWJ+PiwUh51K1Uh8t3OcXzzzT6EIgm035mC1aTOi5zi/E0cMBmUMOtUOLxtHT721Mas5c9d\n1WaeUbOQjCDjrN2qxfhUkFNLVGhxancNvvL99oyUIiAz5Y5Lwxnj+b3YLFpsrLHgUhe3sIrEktBr\nynhG0HarFt/59R10D85iaj5M05EA+VXavvpGB2bmIzAbVHhqTy2u3/byvsOmfrBphHJg1Kp4VasA\nQKsqwe8904z+kTnEEknYLFroNWW03cQ2UNh3WYPDjMvd7ox2VKtKM4zSf/99WxCMxOiCnlW9sQSM\n2HmFMcuSY1p1CT53ll9lTwxVlrTRs0Fbhr98abeocTUPAs8isvAnz1uYZiUk7cTUTGQsHJzw8Rbq\nrO8eITtO7KrGTlclVZq0D3hpxbl4PIX7Xr+oMTzB1R4PrvZ46L+FMTPuDfJUTfua7RlKTV8gisMH\np8sAACAASURBVPMdY7h4axyNTjMGxubp/WlVZTwFXiAUx/i0H7VVBtgsWt6YFo0l8D9/3I2RST9i\n8STef3g9Dm614/T+OiwEo1SxlEoBLfWWDMJG6v0h3PT76JMbcWJ3DexWLXa5bGiuTfdbKcJCTPEj\nHG/Zd4OwL8mtACdng5Koa7KZ27PP5htv9oh6vJWWKHCtb1I2idrgNAIprGihFrYNWR8/k0FJCXaA\n22QQjqdiJKtwDO24M0WfbTyRomrPfDd/80nDXuocQfjsf/99W3hKXalUyiIKF8V1QxFA4cRBkZiS\niSIxlUahLM6LyEShDCxrEXL8OQoFX/9JN+YD6TFpYJwv+1+NOJBLBKlVpfAHY/jur29jcj4Ip9WQ\nF7Eh91pWauHxP37QyVM7jXgW8PSid4hccGSTBbubq+CqNue8p0qzFnuabQhHE6i26bHOqsfghC/D\n6He9w0QXxcSXh1XYsDDpynB6fz1tB5KGk1RwVevq7SZ8/OmNqHcYM1KKWKPupmoLVS4IU1NGvf6M\nvwkXPcIUuX0tVegfmeGpIAgUCuDPPpxfSXW1qhTbGqy42uOh1efiiRQObrHj3MkmSiAc3eGE3crd\nj8OqE/W0Iu+ycqNacqEtthkjpXrb01wluXEjFrNEldXgNOLcyY2y2oE1ej57oikrKSXlWcRifCqY\noaoQknbZCBGxFDWilgPSZMdCKEYJLKExPUAMyyvw6Wc38e5JSFqYdEp8/iO7eN/JpdTkfOCuo7Vv\nEsNuPy53ufEnL2zD9kYrXjjSiGM7nTwSGOB8ndjnROY8QkPweocB7zvUgEqzFpvXV0iaxQtjT/iZ\nWJyRMaDeYcwaoyxYxY/YeEuKIYTDMdqXSEplrmsWiw+pDcp8xnrW1F+IXOohYfyd2l2D/+/8ANwz\naYJQWaZAnd2YdUNE6n6F93FkuxM7XZVQlinw/OEG3B6d56U9nz3BH0+Fz0lMjTjk9mHY7aff+cCR\nBhzd4RRt22zPRW41V2Dpc8WHsTm9UptQRYijuG4oAiicOCgSUzJRJKaKWAsoxsHSIcefo1Bg0itx\nrZdPULAT93ziQI6CKR8iiBB83vkw+kfmcbXHjUOL6SEr5VEnVi2q3Khe0uRVpy7jLdo/eqop73S+\npWAhGMXrv+zH6GQAF2+5cb3PK7qAYzcChAqbP/zAFjQ4TBidXIAvGEfP8EzG73/8ziDujM7jvteP\nrsEZHN3hxJHtTp4RNLvQcFh1GQs9kpo1PhXMqUQSqm021lhwcIsdrX1cvApNybcvGkDnA5NehR0u\nKyVAyLWwu/WRWAKvvtWHi7fcuNg1gYu33Hj75kRGG4uZfAOckf+I20/jid2MyaZ6k9q4kapwtpSN\nHjlqFKFnkVGnQiCUOR5IqSrkkHbke0JjcTGyg1Wa6LVlGSl0xMdLGMNC0uIjTzZh24ZM/6i0+XwN\nhtx8kleY/kmULc/sr6ekECGBx6f9PNWTMM02myG42KJdjKCJxBL0sxu3vVApS1Bh5AijaV8YamVp\nxrNdCiEgNt421nC+SeTdYNKrcHiLI+Oav/CtVrx9cwJv3xrDjsbKjPPlitt8xnp2zCg3qHlpv1aT\nBqGIPOXjqcU0unvj6SIFpSUKfOhYY9b0OikSzReI4s0rQ6KK0s67M7g1OI2PPdkEnbqMpj0Lx1Nh\nu4mpEXuGZqk3k82iwceebKZFFVjkIvtIP3BU6LCjyYqzJ5ok42Q5c8UHuTm9kptQy0UuRf1aRXHd\nUARQOHFQJKZkokhMFbEWUIyDpUOOP0ehYJ1Vj9oqPca9fiigQCTG3+2WGwdyd7XllA0nBNcvr43w\nKjKFmfSQlfKoEy4OTx+ow1e+17GkyWud3QirSY0RzwI+eqoJT2x35n092cDu9gKgJOCbV4YwxOyS\nA9ILONK2lWYtJZXOndyI9etMmPWHJVVMwupphITY4DRnEC2E6GDPIayeFgzHcfa4C4e22iUXx2Sh\nqFaVoHd4Ftf7vRj2LOBTz7YgHI3jzPFGDHsWlh0D3IJ6XcaCmrRv+4CXtks0lqSpWsIy70KTbwD4\nu39rxZUeDzoGpnDjtlfUp4Wo3uQa9edTcZKtTtY/Okv/y3rS5Oq3Qs+i33uuBfs22zE4Np+XSbFw\n4S8kfch3WKLMZtFmkB3scZ49UI/Ou1MIRRIoN6hwcLOdVjyUaxoupjhCCvjy99szDNKF1QylvLzU\nqlLUVhmyPqdcBRrIop0o9MRUhtO+MO/ZED+gdzoncKFjHG/fHMe13sz0tWyEgNgGg9h4mypRoK1/\nEtFonD4vIfH6u477tOpaLJ7CtT4Pnti2Lr9+yqSPCv22hGBjY0O1CTcHpunfzp5sxOGtjqxkHGmX\n/tFZ3ni3vbECf/LCNkwx7S02xoqRaEatCq+8dh237qX93EpLFNhYY6Fm55FoEq19kxhyL/DSnrM9\nJyk1YgrA0/tq8Jn3bpa8Tzlkn1pVinqHEesdpqzPa63MFeXMPR4E1pKiPl+slVgoYnVRKHEgRUyV\nPeDrKKKIIoqQjTGvH+90juPIdueKVW5rrivHX760C29dHcazB+ozKvIUGnZvrMLujVVU8dFcW86b\n0M75I2jt82R8zqJ/dBaexZQHz0wI/aOz2Ndiz/jeke1O/ObGGBLJFEpLFDgiIG/IQtkzE0K5gf9S\nKTeo4LTq6bX81cf2iF5vPqi2GfC3n95HY+CdznEkklx6UCKZwjud4/jIqY2yj/fEdueKE1JAerc3\nkUzh19fvo9yowbQvDHuFFgc3Z7azvUKL5lp+3LFta6/Q4q8+tof3jJpry2Gv0NK/s7/n/qaDZyYI\ngPOYEh4/1znY49ssWqQUqZzPbiEYxU/eHQJJ2PLMhPDtX/bD54/BMxvCZ1/YhvHpAL2WXHEqvFY2\nfsh1svdgs2iQzKxgntEGYvE/44tg1h+h3/fOSfeLaptBVpz5AlGMTwfwf39kJ9rveLOOW+x9lJYo\nkEimoECaRCL9J1e/FcbFvk0OWAxqNDvN6B+dhdOqp8+AkHpS/dKkV6G5thyvvHYD3jkuDv76E3sy\nqviRc5Hn67Tqecdkn9fffHIf2ge8UKQUaKw2oXdkVjSGTXpVxpghFq8A8JXvd1CDdLZdTHoV/uaT\ne/Hza0O4dW8GLxzZwGt/9t6FY4tRp8qIz2qbAc8dXM8ROzqVaLpVOha1sFk08M6FefdGng2Bdy5N\n5pOxLNuYLDzfK69dh3cuDIOuDH/50d2othky2g4A/ss/X8L4VIDGFmk/9h4mmesCOBJE7Dqyxcz4\ndIA3Jt8d86HaZpD8DYkNXyCKn1eM0Ge7yyV/k0EY8y8/x5E8Rp1KcowU+11zbTnaB7y8Z0LuQ6su\ng8mgpHFGfNvkPivhvdqvpc/73EFp8k7qOuUi27MqZOSaezwovHV1OOPfhT5HLKKIRwlFxZQARcVU\nEWsBj0McrKa0O1dFnkKE2O5sOJ7Ef/nnS/hd21hWJZRcBVMulQC7kxuOJvCBJ9ajVAEc2mbHh4+5\neGkUR7Y7RdMU8gVbLSofNcqDBG+3F+Cpdg5useP+ZAChCJe+8pGTTThz3AUAPOWDnApYUqkjalUp\nnjxQD6dNj631FTh7wgWTXpWRkpDtHOT4bGn5XJ4xb14Zwt3xdEVAVVkJguEEPX5LvQX7BClNcjzH\nsimFhAoh1swaAFUI6TVlOLrDmZEaSeL/er+H5/eiVZfi3EnxcvdyMOb145VvX8fFW27cHp3HZ967\nOasvFHsfKYEVE3k2ZOGcy3yajQv74vNMJZMZJsVyFFhXezxU3REMx2E2qOCqNmdccyAUR9sdL97t\ndFPlD6nOR75r1HIxSlIte4Zn8NkXtqHOYUClWYOOAS9sZm1GNbVILIGrPR5c7pmgVfhYFRLxsAIy\nDdKn5kP45s/6MB+I4Ua/l7432HsnaXX1dhP2NFcBgGSKF/n8UtcEoACqLDrJWHxqbw3UyhKcOe5C\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UlA0hsk2KLnZN0AUeAJQqFHhyb23ePizCBZ3Qu+r+ZIBnqDwfiGD3Rhu6Bqdpm45PBbP6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NTuzb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      "text/plain": [
       "<matplotlib.figure.Figure at 0x22c813f44a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "points.plot.scatter(\"x\", \"y\", s=10, figsize=(20, 12));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can zoom into a certain region to see which words are close to each others."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 355,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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w9urVKwBcXFwYM0aV/VWnTh3i4uJYvnw5np6eGo8lVq1axYoVK+jXrx+urq75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\nSt5EREREbIiSNxEREREb8v/yQcgefrYQnwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x22cff163be0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_region(x_bounds, y_bounds):\n",
    "    slice = points[\n",
    "        (x_bounds[0] <= points.x) &\n",
    "        (points.x <= x_bounds[1]) &\n",
    "        (y_bounds[0] <= points.y) &\n",
    "        (points.y <= y_bounds[1]) \n",
    "    ]\n",
    "     \n",
    "    ax = slice.plot.scatter(\"x\", \"y\", s=35, figsize=(10, 8))\n",
    "    for i, point in slice.iterrows():\n",
    "        ax.text(point.x + 0.005, point.y + 0.005, point.word, fontsize=11)\n",
    "        \n",
    "    return ax\n",
    "\n",
    "plot_region(x_bounds=(-17, -8), y_bounds=(52, 66));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We zoomed to a cluster than contain a word related to hardware/PC."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's try to get some similar words of \"mario\" word :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 256,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('bros', 0.7767923474311829),\n",
       " ('kart', 0.7274721264839172),\n",
       " ('luigi', 0.6836210489273071),\n",
       " ('sunshine', 0.6641625165939331),\n",
       " ('nsmb', 0.6625683307647705),\n",
       " ('wiimario', 0.6515724062919617),\n",
       " ('smb', 0.6476815342903137),\n",
       " ('nsmb2', 0.6301655173301697),\n",
       " ('marioworld', 0.6247094869613647),\n",
       " ('mariokart', 0.6150649785995483)]"
      ]
     },
     "execution_count": 256,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w2v_model.wv.most_similar(\"mario\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The results are coherent. The output words are all related to the mario games."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Using the word2vec features\n",
    "\n",
    "We create a sklearn compatible vectorizer for word2vec. \n",
    "\n",
    "As the review text contains multiple words, we will use an average of the word2vec vectors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "metadata": {},
   "outputs": [],
   "source": [
    "import collections\n",
    "# Modified for python 3 from https://nadbordrozd.github.io/blog/2016/05/20/text-classification-with-word2vec/\n",
    "\n",
    "class MeanEmbeddingVectorizer(BaseEstimator, TransformerMixin):\n",
    "    def __init__(self, word2vec):\n",
    "        self.word2vec = word2vec\n",
    "        self.dim = len(next(iter(word2vec.values())))\n",
    "\n",
    "    def fit(self, X, y):\n",
    "        return self\n",
    "\n",
    "    def transform(self, X):\n",
    "        return np.array([\n",
    "            np.mean([self.word2vec[w] for w in words if w in self.word2vec]\n",
    "                    or [np.zeros(self.dim)], axis=0)\n",
    "            for words in X\n",
    "        ])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "metadata": {},
   "outputs": [],
   "source": [
    "w2v = dict(zip(w2v_model.wv.index2word, w2v_model.wv.syn0))\n",
    "w2v_vectorizer = MeanEmbeddingVectorizer(w2v)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### The model\n",
    "\n",
    "We create now the classification pipeline with the NTLK preprocessor and the word2vec vectorizer for the text.\n",
    "\n",
    "The pipeline includes also the others features."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 239,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.svm import SVC\n",
    "\n",
    "class MultipleItemSelector(BaseEstimator, TransformerMixin):\n",
    "    def __init__(self, keys):\n",
    "        self.keys = keys\n",
    "\n",
    "    def fit(self, x, y=None):\n",
    "        return self\n",
    "\n",
    "    def transform(self, data_dict):\n",
    "        if not isinstance(data_dict[:, self.keys][0], str):\n",
    "            return np.array(list(data_dict[:, self.keys])).reshape(len(data_dict), 1)\n",
    "        return data_dict[:, self.keys]\n",
    "\n",
    "def create_pipeline(classifier=SGDClassifier):\n",
    "    if isinstance(classifier, type):\n",
    "        classifier = classifier()\n",
    "\n",
    "    model = Pipeline([\n",
    "        ('union', FeatureUnion(\n",
    "            transformer_list=[\n",
    "                ('summary', Pipeline([\n",
    "                    ('selector', MultipleItemSelector(keys=0)),\n",
    "                    ('preprocessor', NLTKPreprocessor()),\n",
    "                    ('vectorize', w2v_vectorizer),\n",
    "                ])),\n",
    "                ('reviewText', Pipeline([\n",
    "                    ('selector', MultipleItemSelector(keys=1)),\n",
    "                    ('preprocessor', NLTKPreprocessor()),\n",
    "                    ('vectorize', w2v_vectorizer),\n",
    "                ])),\n",
    "                ('reviewText_length', Pipeline([\n",
    "                    ('selector', MultipleItemSelector(keys=2)),\n",
    "                ])),\n",
    "                ('overall', Pipeline([\n",
    "                    ('selector', MultipleItemSelector(keys=3)),\n",
    "                ])),\n",
    "                ('exclamationCount', Pipeline([\n",
    "                    ('selector', MultipleItemSelector(keys=4)),\n",
    "                ])),\n",
    "                ('questionCount', Pipeline([\n",
    "                    ('selector', MultipleItemSelector(keys=5)),\n",
    "                ])),\n",
    "                ('threeDotsCount', Pipeline([\n",
    "                    ('selector', MultipleItemSelector(keys=6)),\n",
    "                ])),\n",
    "                ('uppercaseCount', Pipeline([\n",
    "                    ('selector', MultipleItemSelector(keys=7)),\n",
    "                ])),\n",
    "                ('summaryLength', Pipeline([\n",
    "                    ('selector', MultipleItemSelector(keys=8)),\n",
    "                ])),\n",
    "                ('price', Pipeline([\n",
    "                    ('selector', MultipleItemSelector(keys=9)),\n",
    "                ])),\n",
    "                \n",
    "            ],\n",
    "            transformer_weights={\n",
    "                'summary': 1.0,\n",
    "                'reviewText': 1.0,\n",
    "                'reviewText_length': 1.0,\n",
    "                'overall': 1.0,\n",
    "                'exclamationCount': 1.0,\n",
    "                'questionCount': 1.0,\n",
    "                'threeDotsCount': 1.0,\n",
    "                'uppercaseCount': 1.0,\n",
    "                'summaryLength': 1.0,\n",
    "                'price': 1.0,\n",
    "\n",
    "            },\n",
    "        )),\n",
    "\n",
    "        ('classifier', classifier),\n",
    "    ])\n",
    "        \n",
    "\n",
    "    return model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "We create our X (features + word2vec) and ou y (helpful or not) for our classification."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 351,
   "metadata": {},
   "outputs": [],
   "source": [
    "label_encoder = LabelEncoder()\n",
    "label_encoder.fit(helpful_video_games.wasHelpful.values)\n",
    "features_name = ['summary', 'reviewText', 'reviewLength', 'overall', 'exclamationCount', 'questionCount', 'threeDotsCount', 'uppercaseCount', 'summaryLength', 'price']\n",
    "\n",
    "def get_X_Y_from_df(helpful_video_games, test_size=0.2):\n",
    "    X = helpful_video_games.summary.values\n",
    "    X = X.reshape(len(X), 1)\n",
    "    X = np.append(X, np.array(helpful_video_games.reviewText.values).reshape(len(X), 1), 1)\n",
    "    X = np.append(X, np.array(helpful_video_games.reviewLength.values).reshape(len(X), 1), 1)\n",
    "    X = np.append(X, np.array(helpful_video_games.overall.values).reshape(len(X), 1), 1)\n",
    "\n",
    "    X = np.append(X, np.array(helpful_video_games.exclamationCount.values).reshape(len(X), 1), 1)\n",
    "    X = np.append(X, np.array(helpful_video_games.questionCount.values).reshape(len(X), 1), 1)\n",
    "    X = np.append(X, np.array(helpful_video_games.threeDotsCount.values).reshape(len(X), 1), 1)\n",
    "    X = np.append(X, np.array(helpful_video_games.uppercaseCount.values).reshape(len(X), 1), 1)\n",
    "    X = np.append(X, np.array(helpful_video_games.summaryLength.values).reshape(len(X), 1), 1)\n",
    "    X = np.append(X, np.array(helpful_video_games.price.values).reshape(len(X), 1), 1)\n",
    "\n",
    "    label_encoder = LabelEncoder()\n",
    "    y = label_encoder.fit_transform(helpful_video_games.wasHelpful.values)\n",
    "\n",
    "    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=test_size, random_state=42)\n",
    "    return X_train, X_test, y_train, y_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 540,
   "metadata": {},
   "outputs": [],
   "source": [
    "# We use all the available reviews\n",
    "X_train, X_test, y_train, y_test = get_X_Y_from_df(helpful_video_games)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will use the Gradient Boosting classifier to do our task, it's widely use and provides in general good accuracy.  \n",
    "(The following cell takes more than 1 hour to compute because of the number of reviews ~66k)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 432,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train F1-score: 0.7296546205\n",
      "Test F1-score: 0.714394884311\n"
     ]
    }
   ],
   "source": [
    "clf = GradientBoostingClassifier()\n",
    "\n",
    "model = create_pipeline(classifier=clf)\n",
    "model.fit(X_train, y_train)\n",
    "\n",
    "y_pred = model.predict(X_train)\n",
    "print(\"Train F1-score:\", f1_score(y_train, y_pred, average=\"macro\"))\n",
    "\n",
    "y_pred = model.predict(X_test)\n",
    "print(\"Test F1-score:\", f1_score(y_test, y_pred, average=\"macro\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our f1-score better than our draft model.\n",
    "\n",
    "We plot now the confusion matrices for the test set :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 463,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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RFBTEgAEDOHnyJGZmZgwaNIh169ZJK8heh5UrVxIREcGAAQOkCfLibLOge5mfpy+7VWwG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\nUUhIYAshRCEhgS2EEIWEBLYQQhQS/w+roSMitP3SegAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x22cff1f2438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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aVNYss7RQMLBLAx5HxbL72F969/vr5kPuPIjC2dEWCwvtr9fHHwRha2PFvpNX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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x22c842dd6a0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plots_confusion_matrices(y_test, y_pred, label_encoder.classes_) # function from functions.py"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We see that the scarce class `notHelpful` get a lower score.\n",
    "\n",
    "We can now plot the features importance of theGradient Boosting classifier. For the word2vec features, we summed each composant of the vector to get its feature importance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 561,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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RENYCAAAAABQBYS0AAAAAQBEQ1gIAAAAAFAFhLQAAAABAERDWAgAA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\nUZG3hV8I1eeVQJVu+k9kz+bIwkhLS0Pfvn3Rrl0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      "text/plain": [
       "<matplotlib.figure.Figure at 0x22c83c8e668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "w2c_dim = 300\n",
    "importants = []\n",
    "\n",
    "importants.append(np.sum(clf.feature_importances_[0:w2c_dim]))\n",
    "importants.append(np.sum(clf.feature_importances_[w2c_dim:w2c_dim*2]))\n",
    "\n",
    "for i in range(w2c_dim*2, w2c_dim*2+8):\n",
    "    importants.append(clf.feature_importances_[i])\n",
    "\n",
    "plt.figure(figsize=(24, 5))\n",
    "\n",
    "\n",
    "plt.bar(range(10), importants, align='center')\n",
    "plt.xticks(range(10), features_name)\n",
    "plt.title('Features importance')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see that the `questionCount` and `threeDotsCount` are not used by the classifier. Also the `exclamationCount` and `summaryLength` are quite low. These confirm what we said before from the previous plots. \n",
    "\n",
    "The `reviewText` contributes the most for our prediction.\n",
    "Interpretation : The text that the reviewer write has some impact on the helpfullness. This seems to be logical.\n",
    "\n",
    "We save our model for future usage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 337,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('pickle/trained_model.pkl', 'wb') as output:\n",
    "    pickle.dump(model, output, pickle.HIGHEST_PROTOCOL)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "However, because text preprocessing is taking a consequent time, it will be difficult to improve the model by tuning the parameters using Gridsearch and cross validation.\n",
    "\n",
    "We can decrease the number of reviews."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Our trained model on 1000 PC games\n",
    "\n",
    "Now we can test our trained model to a subset of the dataset : 1000 PC games.  \n",
    "These games were selected using a *NearestNeighbour* method started from one PC game. You can check the method on our other notebook [Similar products.ipynb](https://github.com/Coac/epfl-ada/blob/master/Project/Similar%20products.ipynb)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 539,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('pickle/trained_model.pkl', 'rb') as output:\n",
    "    model = pickle.load(output)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 416,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PC games reviews count: 1634\n"
     ]
    }
   ],
   "source": [
    "asins = ['B000810NAS', 'B004V7W3EO', 'B000WJOYAQ', 'B000J55YSE', 'B00001ZT4C', 'B002JZ7STU', 'B00025LDKO', 'B0007TYMLW', 'B00003IEL1', 'B000IK3XJW', 'B00HFTOTI8', 'B0046LVG3Y', 'B001514JP0', 'B000760OV2', 'B000GDAZXI', 'B00005JDNJ', 'B0000ZUA78', 'B00004UE0I', 'B000LO68JC', 'B000IO2HNQ', 'B00079MUXE', 'B000077W0H', 'B00004WI4B', 'B00HFU41OY', 'B000059XP2', 'B000RJTZTG', 'B001SN6YGC', 'B004BDBSQW', 'B0009HK2MK', 'B000056EZG', 'B009GFBRZ2', 'B0061ABD90', 'B005A2JVN0', 'B00002S7YP', 'B000IWQUO0', 'B00162L5OG', '1557556741', 'B000RS5C4E', 'B004KIV29G', 'B0012DPHKW', 'B0001PKEXM', 'B0017WKITS', 'B00079MVHY', 'B001QINBBK', 'B000NJFMR4', 'B000WA8V3Q', 'B000GJWGI4', 'B000KHIRCG', 'B000P59QE6', 'B002XNW6T0', 'B003SEKKRI', 'B000J14PBA', 'B001FS7FE0', 'B00005BU82', 'B000W2UHQ8', 'B000MQX8CO', 'B00005QCQM', 'B00004Y2MN', 'B00G2HSXL8', 'B000F1RFV6', 'B000PMPUVW', 'B000HCW0QI', 'B000663RU8', 'B00DJ427M8', 'B00CP1QA1U', 'B001BNDPO8', 'B000TV7QTS', 'B0077W6882', 'B005Y7ML3I', 'B001Q24UAM', 'B005G2TWT2', 'B004EIJHG2', 'B00002SW31', 'B00AYABX9I', 'B00003IEKQ', 'B00AQF345C', 'B00004T0QO', 'B00AQF317I', 'B00B5GZORW', 'B00AQF30XS', 'B009VURIHI', 'B003VUPTJS', 'B0030VKCVI', 'B001H0NPFY', 'B00130UXH6', 'B001IRFWJS', 'B004FLK3CA', 'B00001QEQW', 'B004CJB2UC', 'B0000645W3', 'B00EVVO1CM', 'B000AFKJLU', 'B007R06KSC', 'B00014WYOK', 'B000HWZYF2', 'B00002S6C7', 'B00005V13Z', 'B0002X5MEO', 'B0000EYVZQ', 'B00006JL1P', 'B00004TCUI', 'B00003IEEB', 'B004YU06J2', 'B0002SLAYA', 'B0000EZ0XS', 'B0002B1074', 'B003L7EKNC', 'B000TTIVA8', 'B000ES5S2S', 'B000088NRW', 'B0002ULC5K', 'B00004UE15', 'B00004XRZ0', 'B00002S6FD', 'B000ZPPPKU', 'B00007M9SN', 'B000RQHB5Y', 'B000EP3ZLC', 'B00001QEQA', 'B0015L74G6', 'B00D02ARRQ', 'B00007BGOG', 'B005CFDBF4', 'B0006BAXNC', 'B00003IELX', 'B0000DYLDC', 'B00019G50Y', 'B001AZMO76', 'B000J18SVI', 'B000JVWCK6', 'B00002S6EC', 'B000WWHEBO', 'B002WP4AZC', 'B0090WC246', 'B004PAGJMO', 'B00002CF8U', 'B0002BQRGS', 'B0050GZ0J0', 'B00BJEY9EO', 'B00BXE4W4C', 'B00BKWZ18I', 'B002JZ12EC', 'B002MFQKXM', 'B000WQ1XIA', 'B0043OIHCC', 'B004TJE4QE', 'B000YSYDOC', 'B00AR7GMHG', 'B000M38ADY', 'B000QB059E', 'B009ZVIMB4', 'B004TLLPZU', 'B000EXU98G', 'B0050SZ7LO', 'B001DBJGW8', 'B004W6O6AI', 'B002IRX8KC', 'B000FOZD5S', 'B000LUA6VW', 'B0018RWMRI', 'B00002K13E', 'B00FPH9M9S', 'B0009WPZM2', 'B00067ZEIK', 'B00H4BBTCQ', 'B0007W54X4', 'B000056W4I', 'B001AMGCYK', 'B0037BSTYS', 'B00017K08O', 'B000CSNKWU', 'B0040JGNKI', 'B001IKC3QA', 'B004UD0TC2', 'B00F4Q3HTG', 'B004GWVZWU', 'B00001LCDQ', 'B00002S8OT', 'B00005NZT1', 'B0000501B1', 'B000W8LY78', 'B004Y37O4E', 'B007RE76CW', 'B00002SSSF', 'B000930DOG', 'B00196HEIK', 'B002CZ3N3C', 'B0033WTK4O', 'B00B2QL2Y4', 'B0016PZYLS', 'B0016Q2172', 'B005BTC9WW', 'B000F9AP4C', 'B00002NDF7', 'B0029ZUPSQ', 'B000TTZI0E', 'B00G1DKOZ6', 'B00FJWNSWQ', 'B00CF3AKLY', 'B0085Q7ENC', 'B00008JV5G', 'B00DUCPWOY', 'B0031TG9DO', 'B000A6K6DU', 'B0042X8V6G', 'B001REZLYI', 'B000OFA4UW', 'B000R0URXI', 'B000XJO7A2', 'B00005KAY0', 'B001HC65BI', 'B0009ICISK', 'B00002S7YE', 'B0088VH8JE', 'B0034G5R46', 'B0012GUAII', 'B000924J2E', 'B001CU2SE8', 'B001OMU6VQ', 'B000YBW6BQ', 'B001URRH12', 'B002DC8GEK', 'B00005KG5D', 'B002V8KA72', 'B001HBTK8O', 'B001BTPRKC', 'B00009ADDO', 'B00005B43W', 'B00164AU8G', 'B000063N9P', 'B00000F1GK', 'B0001ILYQK', 'B006PDACWC', 'B003OZOAKY', 'B000KGD1GO', 'B002LE88MK', 'B0089X37NW', 'B00J337WNI', 'B00006471Z', 'B00002S78T', 'B007I531DI', 'B000P0QJ1E', 'B00004VX49', 'B00069ZINO', 'B005X6QNWU', 'B000H25YRA', 'B002NGL8M8', 'B000HJQY0Y', 'B000EDNRLC', 'B000OOOIXM', 'B000MAFXTQ', 'B000HKGIOA', 'B000E4FD9U', 'B009APQ9QU', 'B002Z7ELOW', 'B004PFS9OK', 'B004PFN52G', 'B000IO79MU', 'B00001LDBY', 'B00008K2Y3', 'B00001NFSY', 'B00008K2R2', 'B005CTCT76', 'B00006496H', 'B004R8M7AC', 'B00001IVB4', 'B00092CJL2', 'B00CPKUS00', 'B003Z0LFF6', 'B00005ARX4', 'B000ORJF6O', 'B000MK57SI', 'B00IEO41GS', 'B0006FHB74', 'B0002IBEQO', 'B001189HY0', 'B00004VXAX', 'B00008PGIE', 'B00007BGU3', 'B00004RBOT', 'B00FQPQO4A', 'B001GOXQY6', 'B00005AG1L', 'B000P46NK2', 'B0008G2B1C', 'B009GKT2M2', 'B00005V9DA', 'B000I7ZBBI', 'B0002CHIWY', 'B000021Y3X', 'B000067O90', 'B00005BF3V', 'B00002ST5S', 'B008BLOUPQ', 'B000BD3120', 'B00008XKZZ', 'B0002ER29Q', 'B00FQPQMTW', 'B0017XFP86', 'B00BM7NXMW', 'B00FXWJW0E', 'B00FQPQOPY', 'B00FQPQNDW', 'B0002NW8SW', 'B002NQ4820', 'B0009TTJ68', 'B00002SUBS', 'B000FBK6G2', 'B000KJVR9E', 'B00001ZUJW', 'B00005JD6H', 'B0028ZNX7M', 'B0002RQ3H0', 'B0001MBCDQ', 'B00004U5JA', 'B00004U8K5', 'B000KRRBEG', 'B000EBC0PI', 'B00001ZT3P', 'B00002S6EY', 'B00004UEVV', 'B00063BRYO', 'B00004SWM2', 'B000059TCG', 'B00005RKNC', 'B00005V5XH', 'B0056JCFEY', 'B00005ML8J', 'B00001ZUGG', 'B000809QMA', 'B00004SW0C', 'B000035Y9V', 'B0000A082Y', 'B0001I9YG2', 'B000IOD618', 'B008LYNLFI', 'B00A1Y2STQ', 'B000B7RBKE', 'B000092W8R', 'B00006H31K', 'B000EMRVJM', 'B00009X3V2', 'B00000K122', 'B00005B8LM', 'B002NIK174', 'B00005C7OF', 'B00008BR9Y', 'B004LM37FI', 'B00005N7YI', 'B0000Y4138', 'B009O8HH3M', 'B003VUO6H4', 'B000BI5HZO', 'B0010NP3O4', 'B0002MIE0O', 'B000066BPW', 'B0000AI1KG', 'B000BQUV5W', 'B00002STJH', 'B000035Y5Q', 'B00004SW1W', 'B00006RHLV', 'B0002BQT6Q', 'B001W2Q92S', 'B0029ZUPRC', 'B00002S78O', 'B00BBSLITC', 'B000EXZALC', 'B0055NBNWQ', 'B000FNUE9Y', 'B002S7NI2K', 'B00BKEDUCU', 'B000BFHR82', 'B0044DJZ0A', 'B000IZAN7C', 'B0042X8M42', 'B005L38QHA', 'B000TP2UZO', 'B000HXDKA2', 'B000P7V34K', 'B001QRWE28', 'B0000D8MBA', 'B00002SVLS', 'B00004UDVJ', 'B00ESZOAVS', 'B00006C28V', 'B0000CDHP1', 'B005EZ5GW8', 'B00501JRVW', 'B0095ZGOC4', 'B000B6F53U', 'B0095ZGP0K', 'B000T9OXNC', 'B005TOGCWC', 'B000J4T6G6', 'B0054U3MKQ', 'B001CEBU70', 'B00005BRKN', 'B0002AU13O', 'B000J0NV16', 'B000FUG5W2', 'B000GI3LE8', 'B0002BQRFY', 'B004H1T2DY', 'B001L5U18E', 'B000V62BZU', 'B001OAKV3G', 'B0012N8WXQ', 'B00001L2BT', 'B00004Y2MO', 'B000EHK9DW', 'B001EK6DXS', 'B00004Y6GS', 'B0000VJF46', 'B000CRSBLG', 'B0006ZB0ZS', 'B004PG1FKO', 'B0017OCY2U', 'B00079XZII', 'B000AAZVRC', 'B004AHKV4O', 'B000J42FMI', 'B003ESHRL0', 'B000B69E8W', 'B0007DGB4O', 'B0002IWYKY', 'B0001ZDLE6', 'B000AONNS2', 'B00002ST9V', 'B0008GJRTQ', 'B00CFM0ZRY', 'B0000E2HFT', 'B00002S7XF', 'B0007N3KIO', 'B00005YTYR', 'B001MKLN4E', 'B0006NMOCS', 'B0010DZBAA', 'B00067WAHS', 'B001885670', 'B008J16B0U', 'B0011BO364', 'B000ZEXNMS', 'B000JKV0R8', 'B001MIQ46S', 'B000IMW4KY', 'B000MNK4V0', 'B003DU7AW0', 'B000BNDGRK', 'B003BUAVMI', 'B0006OFKOQ', 'B000H5DD0M', 'B00004TSXC', 'B0002LWVSQ', 'B0000C865V', 'B000F7OUWC', 'B000BI4GP6', 'B00005Y4PZ', 'B000VDLZSM', 'B004XTP2GQ', 'B000059OVP', 'B003APN6ZS', 'B0017XBO8G', 'B000ICKL7W', 'B000AMOIYM', 'B0000544GF', 'B000B6DGT0', 'B00004RKER', 'B000TV44FC', 'B00125VVAA', 'B0036F7FX6', 'B00HAZ6BVK', 'B00GPH7Y9M', 'B00002S93J', 'B00B5GZP5S', 'B00B5GZP08', 'B00AQF34NE', 'B00GPH7W6W', 'B000031KJQ', 'B00005NCB2', 'B0009WLIDC', 'B0006DNMYW', 'B009OB3CQU', 'B000S6Q082', 'B000UUGDDS', 'B0002HTAYS', 'B000AODBES', 'B00CMCI218', 'B00D6DPRPQ', 'B00A87S5JI', 'B000GDGXMU', 'B0006ZB60W', 'B009LWQ0H0', 'B00CMC4FFK', 'B00008I8RE', 'B00009YEJL', 'B00004U5VJ', 'B00000K1VJ', 'B003WU3CDW', 'B00002STTN', 'B003HIZJC6', 'B0012QTT9O', 'B00009IAW8', 'B0009J1JIY', 'B0050JN846', 'B003ZNOW2G', 'B00002STLJ', 'B00002EPY1', 'B00003IEIV', 'B000MRB8LQ', 'B00004S9WY', 'B004U9V9W0', 'B0000CDYOH', 'B004U9RBYU', 'B00009X3SY', 'B000NIIM4K', 'B000BC38RO', 'B002S4IDI2', 'B0009XOUGI', 'B005C2D2H4', 'B00ENWZANI', 'B007FTE2VW', 'B00001P4Y9', 'B000V98SZY', 'B003Z14QKQ', 'B000AXS0D6', 'B0006LPCG0', 'B002MCG8MI', 'B001AO1W2K', 'B000NJH6Y6', 'B003GAM9PU', 'B000ULGWA6', 'B000059WIZ', 'B000BKYR0I', 'B00005V97H', 'B001LYGUB2', 'B0009Y6EYS', 'B000FCOIRY', 'B000NKNB4Y', 'B0007IQFYA', 'B00002S6FL', 'B00005Y0IW', 'B0050SZ0AW', 'B008F8AJI2', 'B001COX7N0', 'B00000J96T', 'B000R2USO4', 'B00005O1H4', 'B00H4BBYO4', 'B000IANMSY', 'B001QIJCE0', 'B00004WHWC', 'B009O4NG86', 'B001FDHZAE', 'B0009E3U4K', 'B00005NSSQ', 'B0017XEGOK', 'B0042WXQ62', 'B004NS542Y', 'B0038MUCLE', 'B0001BYH0C', 'B001988XHY', 'B000MAH3NK', 'B00078V9WS', 'B0038PBF62', 'B003VJOS4Q', 'B0006N0DDA', 'B0009YN1T4', 'B002I0JIQW', 'B0001BYH16', 'B0050SZ2EQ', 'B001M041N4', 'B000YFCR8E', 'B00062VFGK', 'B00003IRCC', 'B00005V131', 'B000HCU7CC', 'B0016OWXXG', 'B001DUG0NC', 'B004DDIYP8', 'B001F0J70I', 'B009S4JZKK', 'B009KY3TKU', 'B00000K4KF', 'B000ZN2ZAK', 'B000044UA4', 'B000922E0S', 'B009SHV7Y4', 'B001AWBYRA', 'B0045ZB66I', 'B000059Z7P', 'B00005Y4QC', 'B00002EIV6', 'B003Z19LBK', 'B003VJNW5W', 'B00006G343', 'B000G9SGII', 'B000EXSDB6', 'B001NIR8QM', 'B000O5G1KO', 'B002ZOK7GG', 'B000JV96O6', 'B000BKBZXU', 'B00J952JLK', 'B000E5D198', 'B000BCICVQ', 'B000FOVJVA', 'B001DSM2BS', 'B000FHB8Q8', 'B001AEHWC4', 'B000BCICQ6', 'B00008JON7', 'B003Q65ZLO', 'B0002AL1Z6', 'B000HHZIFS', 'B004CJ8YTO', 'B003Q55Y5C', 'B003ZY3H4E', 'B003TIVSM4', 'B007RLRU1W', 'B0000VMING', 'B000058A57', 'B0067G55XS', 'B0000C4E7C', 'B003TO54TQ', 'B00GGMKSIK', 'B0000AK9LW', 'B002E0JRK8', 'B000GCBOR0', 'B0002MJCY6', 'B002QTZJ90', 'B000AA878M', 'B0002B90BW', 'B004U9VH18', 'B000A0R88W', 'B00004T1N5', 'B0000EZGE6', 'B0000524RC', 'B000MNK4TW', 'B002I0JJ2U', 'B000XXC0CK', 'B000CBP0IO', 'B00008K1YM', 'B000AA87AA', 'B0001AO028', 'B002FJXQQ4', 'B000NV8F58', 'B000B7PHLO', 'B00009YEJV', 'B000R2XJJK', 'B00149X4KE', 'B001EK7S82', 'B0001XM2HU', '8990289432', 'B00001W0HL', 'B0000B0MNH', 'B002E0ISC6', 'B001VBABJ2', 'B003B2EUK0', 'B000KIBABA', 'B001OAIJOY', 'B0012JL5XO', 'B0002RQ3FM', 'B001LVXEC8', 'B000038I9O', 'B00004UE0U', 'B00004WI4G', 'B0008IST98', 'B000O5K3PI', 'B002C1Y0II', 'B001CEIMUI', 'B00001OWYL', 'B000UQURQ6', 'B00064OTNE', 'B003BW0IGU', 'B0076DO5A0', 'B0000696IW', 'B00002CF9F', 'B0007QCNR0', 'B00006LELH', 'B0002CKASI', 'B0038P9DBG', 'B005S0OXVO', 'B003DY2O36', 'B000B8YVDS', 'B000BCICVG', 'B000EDVRUA', 'B00065SISA', 'B00062VFG0', 'B00007E8ED', 'B00EAM8RR2', 'B002V2GOU0', 'B00183MAN8', 'B001DI6O6C', 'B000ZK7ZKS', '3937549064', 'B00020LYUI', 'B0007INLYW', 'B000CQEA9O', 'B002B3I6PA', 'B000O5DY0E', 'B001BPQ1VA', 'B009SIJJB6', 'B000ELWF80', 'B000RMZP24', 'B001B8Y0CO', 'B00004TH9E', 'B00007E8XS', 'B001AWMCMQ', 'B00006GEST', 'B00006JC48', 'B000QGIXDE', 'B004JQDJ8G', 'B0029ZBZ0I', 'B003336KG4', 'B001KQA2SI', 'B000SKUHL4', 'B00005MHMH', 'B000L7LRYA', 'B00008JOMM', 'B002CVTOPC', 'B004ML9WKC', 'B00CJ7IUIQ', 'B000RQMOHO', 'B003YPXZDW', 'B000FU1PFY', 'B004K66O2S', 'B00273Y7V6', 'B005FYK1Y6', 'B0016Q4UJE', 'B00004U2IM', 'B003EZ1KGQ', 'B002X9HB26', 'B00080L3A8', 'B004VF06AY', 'B000302JEC', 'B001CFAX9A', 'B0000CCZSY', 'B000G7WGP4', 'B000UXQGY6', 'B000FUD16A', 'B0002T67KQ', 'B000GURLIS', 'B000EOOZ5S', 'B0008F6J52', 'B000124FVC', 'B001D7798A', 'B000AS20D2', 'B00004NHFM', 'B000ZNW2W6', 'B000292926', 'B000RIV3WE', 'B000070MQK', 'B000BYQJCI', 'B000RHFZTM', 'B000ELW4D6', 'B0007ZF3H8', 'B001TILU88', 'B002DNEX8W', 'B000RSK7K8', 'B0002CTTQC', 'B00005MENF', 'B004U9VBIC', 'B00005BIR2', 'B001BBOZYY', 'B0050SZ61A', 'B000PM1THQ', 'B004U9VA5Q', 'B0026O85EQ', 'B0002YLEB8', 'B0015QFHCE', 'B009DXSUNY', 'B000809QM0', 'B00003TKZK', 'B000AMKYF4', 'B000JMBZVM', 'B00286R3LI', 'B000BC38KG', 'B0007D9OZC', 'B0000BVGOM', 'B0067G555G', 'B00064OTN4', 'B00005O1GM', 'B00013MRTS', 'B00001ZT47', 'B00177W738', 'B00BS5UJGG', 'B000W3CNI2', 'B0012J0I9G', 'B002ZVD0HW', 'B00001X5CL', 'B0012UG8VC', 'B001O4YSTU', 'B000E8H8X0', 'B000N9ZYWC', 'B000IWMVSY', 'B00005NH6C', 'B000FT699C', 'B0006FZUIG', 'B000QS61CM', 'B00006LEM2', 'B00007MFQW', 'B000PS2XES', 'B000088NQP', 'B00002S6F0', 'B000WOUBFS', 'B0007LKBTC', 'B000W6ESAK', 'B000NRGAG8', 'B00003OPES', 'B000N2827I', 'B003L7VS3W', 'B0010L1TVM', 'B00005T834', 'B00022Q0RI', 'B000F6W8AE', 'B0015QSVH2', 'B000WNURKI', 'B000FOZD44', 'B0000VMINQ', 'B00004ZB7P', 'B000QCWU8W', 'B003FH3P0W', 'B001NJKEEE', 'B000FN31NU', 'B0012LGHZI', 'B00005B49Q', 'B001VJBYZY', 'B000Z3VI3K', 'B000H11F9M', 'B0050SZEGM', 'B000Q56VHK', 'B002JXKCK4', 'B000VJA8K2', 'B000EMRVLK', 'B0019R4VF8', 'B001IV0AAK', 'B00153ZO3O', 'B00021KEPI', 'B001E7MMOK', 'B00009IFE6', 'B00005S3TK', 'B009K7QB8O', 'B000MUPX4Q', 'B003O21A2I', 'B003VUO6LU', 'B00000K4M6', 'B00001QEQ8', 'B001EIA2LY', 'B00004ZBQB', 'B00604IHV4', 'B00692FNIM', 'B004BCN05A', 'B00004SW19', 'B000FV83YE', 'B00ACLRK50', 'B000MUU5MG', 'B004H4E1GE', 'B00002SVWS', 'B0058MI0UM', 'B000059Z7Z', 'B004VKZ4ZG', 'B00005OUSB', 'B004122X4E', 'B00002SAML', 'B000WZ6FPW', 'B000N24EO8', 'B00H3SGII0', 'B00GJXMRX0', 'B000UN3KFY', 'B00BPEBG76', 'B00006RVQQ', 'B0001W8WOI', 'B00153939A', 'B000035XZ9', 'B0000859TM', 'B0002EJ8DY', 'B000A41FPA', 'B0010KOVOA', 'B00117PPME', 'B00HMB1GPI', 'B004Q4EQ4M', 'B000JWPGXA', 'B00001W0E6', 'B002E1LIR2', 'B00IDESX2W', 'B00ID2TNI2', 'B00004U5R2', 'B0000663TT', 'B00008YGOF', 'B0090WBXSM', 'B002XISALI', 'B007M5PU10', 'B004TQJDUY', 'B001GQ2PD2', 'B00006RHM0', 'B000646MLQ', 'B002IT6RP8', 'B008BT2FVY', 'B00006LJXO', 'B000BOJPRE', 'B001IDYWA2', 'B00005UJS8', 'B00001QER9', 'B00006DY3F', 'B00BPC0K5C', 'B000HKKPZ8', 'B0076A4F08', 'B005D6O0YI', 'B00025EJ28', 'B00BRA9T5Y', 'B006J38DGK', 'B002I0HCBK', 'B000IVJXMM', 'B0002BQQLO', 'B000EPTFD4', 'B0052GQXE4', 'B00004T782', 'B000J568QG', 'B003VUJ2I2', 'B00002STX0', 'B003QB26WK', 'B000053UIX', 'B00006IKB5', 'B00000JKLW', 'B00JYGT2BY', 'B00006IJIW', 'B000LYCV4S', 'B000P189RU', 'B000059RED', 'B0007PQBMY', 'B00DOD1G1W', 'B00005CF9L', 'B000ZN6MHC', 'B00004SREQ', 'B00C7103JI', 'B000BH7A2I', '7539908920', 'B00004RQ7F', 'B00004Y2P0', 'B000052WM1', 'B0006FHB3S', 'B003RAHE72', 'B00029292G', 'B00000JKMC', 'B001CH2HBK', 'B00002ST65', 'B001LQU1VA', 'B00016OYSM', 'B00005K3AU', 'B001V6SO28', 'B0096E3IXM', 'B001EPXIQS', 'B005OSFUZI', 'B00001WBQ9', 'B00000K1VB', 'B0010F1I5K', 'B002W9CYLK', 'B0002PPW1A', 'B0086V5V7C', 'B000809QLQ', 'B0015RPD7M', 'B00EW14S6A', 'B004K6LQ9E', 'B00HQCWKDA', 'B00006C294', 'B00006IKB4', 'B00005RCR2', 'B000056Q1B', 'B005UI9BT8', 'B0041JZA1U', 'B0012SNQ3M', 'B008P9IO2Y', 'B00149ILCK', 'B003JZ2QX2', 'B004LQRFAM', 'B00005MOMM', 'B00006LU9F', 'B00BS5N0IU', 'B00B3TXJ14', 'B007I56J1E', 'B000OI1CP0', 'B00000IG80', 'B0007KRXG2', 'B00EW47602', 'B0011UEPBI', 'B00008DHNR', 'B0052IUE4M', 'B00005MO5I', 'B00002R289', 'B0045WI7KE', 'B00GJOXHW4', 'B00AWXE87G', 'B00ELN0FUW', 'B0073ESZDK', 'B000AP41ZU', 'B000069BD9', 'B00GCBRVGW', 'B002GDB9Q8', 'B00005LLTO']\n",
    "pc_games_reviews = helpful_video_games.iloc[helpful_video_games.index.get_level_values('asin').isin(asins)]\n",
    "print(\"PC games reviews count:\", len(pc_games_reviews))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 469,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "F1-score for PC games: 0.726631355631\n"
     ]
    }
   ],
   "source": [
    "X_train, _, y_train, _ = get_X_Y_from_df(pc_games_reviews, 0)\n",
    "y_pred = model.predict(X_train)\n",
    "print(\"F1-score for PC games:\", f1_score(y_train, y_pred, average=\"macro\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The model seems to have low variance, the f1-score is close to the training one.\n",
    "\n",
    "##### Our trained model on 1000 low priced gaming accesories\n",
    "We retrieved 1000 similar products from *64MB 1019 Block Memory Card compatible for Wii* at $4.42."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 470,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wii accessories reviews count: 345\n",
      "F1-score for gaming accessories: 0.622213244597\n"
     ]
    }
   ],
   "source": [
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'B001B093Q0', 'B000HKKPTO', 'B007Z0ODOW', 'B0039OIXEO', 'B00EOI2I4A', 'B000809PB2', 'B00005MCYS', 'B00002EIZS', 'B004CMBJVQ', 'B003DS6M26', 'B004KNGAZ2', 'B003WF3PBQ', 'B005EVT4E8', 'B007Z0O9DW', 'B000YMQGWU', 'B000BFICX6', 'B000BHIQUS', 'B0009NEXRO', 'B000GC5V1U', 'B003PMYC68', 'B000AX21UE', 'B008ZAS3OM', 'B00CHHSHV8', 'B0089U00AI', 'B0095QR206', 'B000FDDWSY', 'B0002YIUME', 'B007F3RV8O', 'B0049ICR0A', 'B003BU76ZS', 'B0008G2B7Q', 'B003TK5PEY', 'B00002S7Z2', 'B00005UNWA', 'B000RDIMBY', 'B00007KK0F', 'B003LVJDJE', 'B00005RH4A', 'B0039RHTVE', 'B000QSBR8K', 'B00GUZ6JMW', 'B00HFNRMAG', 'B003981JPK', 'B002OPP23Y', 'B004SFZZYO', 'B000PDP6YM', 'B001FAIUYM', 'B0032GRXEK', 'B00026D14Y', 'B0000A1VEU', 'B000A37FS2', 'B00DI4Q7C0', 'B008KSCEJ4', 'B001PQ5KC6', 'B006FDI35K', 'B006STL2UY', 'B000WMMTE6', 'B00007BGQI', 'B003VEFXTU', 'B000BCZ7I2', 'B00005K1YY', 'B007RE61XM', 'B0001X62BW', 'B0000A2Q7Y', 'B0000A380T', 'B0002UV1LK', 'B00007FRT8', 'B000BYAG7W', 'B0002EXH0E', 'B001AH1CLS', 'B00001N2OE', 'B0014ZL9VE', 'B000OI2COU', 'B0010ED3KO', 'B000F5IA7A', 'B000B6ML0U', 'B0039YZ6X0', 'B003V78AAQ', 'B002BCAM76', 'B005EDH1YG', 'B000FDDWSO', 'B005EDHK4W', 'B000SA8BKI', 'B004DK03EQ', 'B00001QEEP', 'B000TTDLO4', 'B0001AS04C', 'B000050YSB', 'B0007VNGDA', 'B00006I5CN', 'B00007JRBG', 'B002KA20XI', 'B000VOH4IQ', 'B000F8RSKC', 'B0007U9BUI', 'B002MRMYV2', 'B007HHN8P8', 'B001F4PCAS', 'B00029HXTA', 'B00004WGRX', 'B0006VSU3M', 'B004YV9UAM', 'B000WWOWOQ', 'B00004WGVP', 'B004FTGPX8', 'B009W2A8P4', 'B000BQP2RY', 'B00004WHWF', 'B0016PWO52', 'B000BVJZGS', 'B002VBAIS0', 'B0000APUL1', 'B0017TX0IC', 'B000HJMFXY', 'B0001IPY2K', 'B0012DK4EQ', 'B0050B0RAM', 'B0007PHOLG', 'B002C5Z0SS', 'B005NSNYQ6', 'B001VMAU2O', 'B0002VKC3W', 'B005EOP1XI', 'B00004TJ2T', 'B0000789V6', 'B00008YSXJ', 'B000I0396E', 'B002MROL1S', 'B0015A8OSO', 'B000LRJD64', 'B000J4IFUE', 'B00006471I', 'B002JLD5AA', 'B000JSA05S', 'B002JEUDX4', 'B00008W736', 'B0006TQGBM', 'B0058FM2BC', 'B003EYV6Y8', 'B003O219ZG', 'B0001LV6QK', 'B000V728P2', 'B00066LGE2', 'B004EDEP6O', 'B00005M8T9', 'B004ML7WOK', 'B001CUI3SS', 'B000096RDI', 'B0012N2AB6', 'B001DCE2JY', 'B00001XDKK', 'B00005QIQM', 'B005FYK36M', 'B00001ZWQI', 'B00006F7RJ', 'B007MNLMGO', 'B000HJQXSC', 'B000810LWS', 'B000A14PN2', 'B000XJNTPG', '7293000960', 'B000OKU98Y', 'B002NZNGYW', 'B009FA2M66', 'B002AMVW80', 'B0007LWMRG', 'B005X05IWW', 'B001DDO9XW', 'B000059WIG', 'B00005K3X1', 'B000I5KW32', 'B00009W5JT', 'B003WIACPU', 'B003WU5FW8', 'B001AWW1JK', 'B0002DOXJ4', 'B00005TNVQ', 'B0046SGULU', 'B003B1TJ4S', 'B001OKN4MG', 'B0006D3QXY', 'B0079I5J66', 'B0010YI8IQ', 'B0010YCZ1C', 'B0010YI8I6', '9888001167', 'B005ELD3DG', 'B005ELD2OQ', 'B004FL5QOA', 'B0002IQOQY', 'B00005LATC', 'B0006VE8OW', 'B00005BOS7', 'B00005J53A', 'B00GOIJE54', 'B00CEFFFPO', 'B00CEGGMK0', 'B004S3ZHQ2', 'B00EJLJMTQ', 'B000Y8EUVI', 'B0000501KH', 'B00006472K', 'B004E0I48M', 'B000059WIM', 'B000UV3FBK', 'B000G7ZR9Q', 'B00005S0LF', 'B00006DY1Y', 'B0093SR076', 'B00004T9C9', 'B0004M0SDI', 'B0002IWYG8', 'B0053OZZH6', 'B000B7Q4BG', 'B004CGLM1Y', 'B003YUNG1S', 'B0000691KL', 'B009QX3JEQ', 'B00016OYJQ', 'B00009K77W']\n",
    "xbox_games_reviews = helpful_video_games.iloc[helpful_video_games.index.get_level_values('asin').isin(asins)]\n",
    "print(\"Wii accessories reviews count:\", len(xbox_games_reviews))\n",
    "\n",
    "X_train, _, y_train, _ = get_X_Y_from_df(xbox_games_reviews, 0)\n",
    "y_pred = model.predict(X_train)\n",
    "print(\"F1-score for gaming accessories:\", f1_score(y_train, y_pred, average=\"macro\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The result is worse, seems like the model is not generalizing well on this specific subset."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Train a specific model for helpfulcount > 100\n",
    "We filter our dataset to only reviews that has a helpful count greater than 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 562,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of reviews with helpfulcount > 100: 1739\n",
      "Train F1-score: 0.999058802832\n",
      "Test F1-score: 0.899609444346\n"
     ]
    }
   ],
   "source": [
    "X_train, X_test, y_train, y_test = get_X_Y_from_df(helpful_video_games[helpful_video_games.helpfulCount > 100])\n",
    "print(\"Number of reviews with helpfulcount > 100:\", len(helpful_video_games[helpful_video_games.helpfulCount > 100]))\n",
    "\n",
    "clf = GradientBoostingClassifier()\n",
    "\n",
    "model2 = create_pipeline(classifier=clf)\n",
    "model2.fit(X_train, y_train)\n",
    "\n",
    "y_pred = model2.predict(X_train)\n",
    "print(\"Train F1-score:\", f1_score(y_train, y_pred, average=\"macro\"))\n",
    "\n",
    "y_pred = model2.predict(X_test)\n",
    "print(\"Test F1-score:\", f1_score(y_test, y_pred, average=\"macro\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The f1-score is pretty high ! These reviews are voted by enough number of people to have a good estimate of the **real** helpfulness. Our model trained on these kind of review works well."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 564,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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JjB07doXq/SbH5/Fbc82aNSu9evXKW2+9le7du6dfv35ZsGBBHnjg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\nGAwGg8FgMFoB/w9mIfptliRoeAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x22cff53ada0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "w2c_dim = 300\n",
    "importants = []\n",
    "\n",
    "importants.append(np.sum(clf.feature_importances_[0:w2c_dim]))\n",
    "importants.append(np.sum(clf.feature_importances_[w2c_dim:w2c_dim*2]))\n",
    "\n",
    "for i in range(w2c_dim*2, w2c_dim*2+8):\n",
    "    importants.append(clf.feature_importances_[i])\n",
    "\n",
    "plt.figure(figsize=(24, 5))\n",
    "\n",
    "\n",
    "plt.bar(range(10), importants, align='center')\n",
    "plt.xticks(range(10), features_name)\n",
    "plt.title('Features importance')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "However, the classifier, without taking into account the word2vec features, seems to give a great importance to the `overall score`, and also but a lesser to the `review length`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 385,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>reviewLength</th>\n",
       "      <th>overall</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>wasHelpful</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>helpful</th>\n",
       "      <td>4210.717711</td>\n",
       "      <td>4.014695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>notHelpful</th>\n",
       "      <td>1181.988789</td>\n",
       "      <td>1.354260</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            reviewLength   overall\n",
       "wasHelpful                        \n",
       "helpful      4210.717711  4.014695\n",
       "notHelpful   1181.988789  1.354260"
      ]
     },
     "execution_count": 385,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "helpful_video_games[helpful_video_games.helpfulCount > 100].groupby('wasHelpful').mean()[['reviewLength', 'overall']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For this kind of reviews, it seems very easy to predict the helpfulness. There is a clear frontier between the helpful and not helpful in these features. \n",
    "\n",
    "Interpretation : The people are more often declaring `helpful` to reviews that give good score and has a long review text. On the contrary, they give the `notHelpful` to short and negative reviews.\n",
    "\n",
    "However the `summary`and `reviewText` played an even better role for the outcome of the classification. Unfortunately, these features are not very interpretable (unlike TF-IDF), we cannot say more."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Returning to 3 class classification"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 504,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of reviews: 66774\n"
     ]
    }
   ],
   "source": [
    "helpful_video_games2 = helpful_video_games.copy()\n",
    "helpful_video_games2['wasHelpful'] = helpful_video_games.helpfulRate.map(lambda x: 'notHelpful' if x < 0.33 else 'controversial' if x < 0.66 else 'helpful')\n",
    "\n",
    "label_encoder2 = LabelEncoder()\n",
    "label_encoder2.fit_transform(helpful_video_games2['wasHelpful'])\n",
    "\n",
    "X_train, X_test, y_train, y_test = get_X_Y_from_df(helpful_video_games2)\n",
    "print(\"Number of reviews:\", len(helpful_video_games2))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 505,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train F1-score: 0.546027042372\n",
      "Test F1-score: 0.515419264202\n"
     ]
    }
   ],
   "source": [
    "clf = GradientBoostingClassifier(random_state=10)\n",
    "\n",
    "model = create_pipeline(classifier=clf)\n",
    "model.fit(X_train, y_train)\n",
    "\n",
    "y_pred = model.predict(X_train)\n",
    "print(\"Train F1-score:\", f1_score(y_train, y_pred, average=\"macro\"))\n",
    "\n",
    "y_pred = model.predict(X_test)\n",
    "print(\"Test F1-score:\", f1_score(y_test, y_pred, average=\"macro\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 511,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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yrjisXLmSyMhI+vXrJwsSKM02P9WX0ryStFtlxshLJxS3bt1aoMzvv//OL7/8wrVr19DS\n0qJmzZoACjPSkDdZERcXR/Xq1UtMRxUVFYWIHUDmwpDy559/Eh0djZGREV5eXqxZs4bY2Fg8PDx4\n9uxZgatna9WqxZs3bxTqg3/usSTv50tYsmQJ6enpREZGsnLlSsaNG0eXLl1QUVEp9mjqU9y9e5el\nS5fSokULunbtypYtWzh79myx6+vQoQNJSUnExMRw8+ZNWrZsCUDLli15/vw5R48e5e+//y62q6Yw\n1KpVCyDfNQTSNOn3Lf3ByMjIkJMrSTfjpyiKrqXFn3/+yYYNG7C1teXQoUOEhIQwdOhQWrZsWezF\naAcPHmTZsmXY2Ngwffr0f6XNWrVq8fTpU9kb3YdI/86lLt+SoMwYeTs7O9q3b8/Ro0fZuHGjQn5C\nQgLjx48HYOzYsQCYmZlRs2ZN9u7dq+CWWbt2LWlpafmGPBYXAwMD4uPj5XyESUlJCiGLa9aswdPT\nk+vXr8vS1NTUZK9fBY3wnJycAFi2bJlcekJCAj/99BNaWloyY/S1SUxMREtLC0NDQ7l0aXjrh6NL\n6f0W1/hnZGTg5+eHqqoqs2fPJiAggEqVKjFlyhQSExOLVWebNm0oV64cy5YtIzs7Gzs7OwBZ/y5a\ntIhy5crRrl27T9ZTkBurMDg6OqKsrMzq1avlBg/Z2dmyUEnpM1G1alUAhTDBo0ePKhj+L+3vL9W1\ntEhKSkIQBOrWrStzV0De4q9du3YBRXO5XrlyBX9/f2rXrs2yZcvyfastapuFeR6cnJxITk5mw4YN\ncumPHj1i//791KpVq0QXSZYZnzzA3LlzGTlyJCEhIRw4cAAnJycqVKjAw4cPiYyMJDk5GV9fX9nD\npKKiQnBwMCNGjODbb7/F1dUVAwMDLl68yJEjRzAzM2PIkCElpl/Pnj25fPkygwcPxtXVlXfv3rFj\nxw4qVKggN/oeNGgQBw4cYPjw4fTv3x9DQ0Pi4uLYunUr1apVk5t0+pBevXpx+PBhduzYwfPnz7G3\ntycpKYmdO3eSlJTE/Pnz0dTULLH7+RLat29PWFgYQ4cOpXPnzmRlZXHs2DEuXbqEmpoaKSkpMlmp\nf//EiRNUrVq1yD+8Cxcu5P79+wQEBMgm2AMDAxk7dizTp09n+fLlQJ6v89dff8XU1PSzfyTa2trY\n2Nhw7tw5qlatKptoq1evHgYGBjx58oTWrVt/dkGc1Fe6du1aWrVqVaSRf+3atfH19WXp0qX07t2b\nnj17Uq5cOQ4dOsT169cZMGCALJSuVq1aNG/enHPnzjFp0iSsra25d+8ekZGRsjdaKRUrVkRFRYXY\n2Fh27txJq1atFH6Mi0pRdC0tTExMMDIyYteuXaipqVGvXj2eP3/O7t27ZaNq6XqXz/Hy5UtGjx5N\nbm4ubm5uXLhwgaysLDkZIyMjzMzMitRmYZ6HoUOHEhUVxeLFi7l79y7W1ta8fPmSrVu3oqyszJw5\nc4rVPwVRpoy8np4emzZt4ueff2bfvn1s3ryZxMREdHV1sbW1ZdCgQQoPUsuWLdmxYwcrV65k+/bt\npKWlUbNmTcaMGSOLny8p+vTpQ0pKCtu3byckJIRq1arRv39/jIyM8PX1lcnVqVOHn376iZUrV7Jn\nzx5ev35NxYoVcXJywtfXt8A9LFRUVFi1ahXh4eHs27ePefPmoaWlRbNmzRg+fPhXXRr9MaNHj0ZZ\nWZmff/6ZOXPmoKenh0QiYePGjezatYtDhw7x8uVLqlatSp06dfDy8iIiIoLZs2dTs2bNQvsYo6Oj\n2bRpE1ZWVnKLjTp37szhw4c5evQoERER9OnTh0uXLjFlyhR8fHwKNRLq0KED586dk43ipdjZ2bFv\n375CGewBAwZw8eJFdu3axYULF4rs3hk1ahQmJiZs3LiRsLAwIG/R3rx58xSic5YsWcL8+fM5ffo0\nR48exdzcnLVr17J+/Xo5l6WGhgZ+fn6sWbOG4OBggoKC+Pbbb4uk15fqWhqoqamxdu1afvjhB/bt\n20d6ejpVq1bFwcGBIUOG0LlzZ86fP8/gwYM/W9fjx49lb4GzZs3KV6ZXr17MnTu3SG0W5nnQ0tJi\ny5YtrF69miNHjnD8+HEqVKhAu3bt8Pb2zndy+0tQEgobBiEi8v+A5cuXo6amxogRI762KiIiZYIy\n45MXEflSXr16xYEDB2jevPnXVkVEpMwgjuRF/jM8ePCA27dvKywcERH5X0Y08iIiIiL/YcrUxKvI\n1yU5veTj26VoquUtdEnLLJ0xRfTD16VSL4BtnbwNoGIelU48ulXtiqVSr65GXijl2/SSWcmdH5W0\nvsyElLf0KTDv3W8rvqhukTxEIy8iIvL1UBKnBUsb0ciLiIh8PZQ/vfWDyJcjGnkREZGvxxfuvSTy\neUQjLyIi8vUQR/KljugQExER+XooqxR8FZPo6GhcXFxo0qQJ7du3Z9myZbL9ZQRBICwsDHt7eyws\nLPDy8lI45jAzM5M5c+bQqlUrLC0tGTNmjMLRl0lJSfj7+2NjY4O1tTUBAQFyW3mUJUQjLyIi8vUo\nYSN/5coVhg0bhomJCatXr2bgwIGsXbtWtg1DaGgoYWFhDB48mEWLFpGcnIynp6fc/jMzZsxg3759\nTJgwgZCQEO7evcvw4cPlNiLz9fWVnY88depUoqKimDBhwpf1RSkhumtERES+HiXsrlm4cCGtWrVi\n7ty5QN4+RG/evCE2NhZPT0/Wr1+Pj4+PbN94Kysr2rdvT0REBF5eXjx9+pS9e/eycOFC2UaCDRo0\nwNnZmRMnTuDk5ERMTIxs8zcLCwsAqlWrhqenJ7du3cLMzKxE7+lLEUfyIiIiXw9l1YKvIpKQkMCv\nv/5K37595dL9/PzYvHkz165dIy0tDQcHB1lehQoVaNGihexsAunRj/b29jIZY2Nj6tevL5OJjo5G\nX19fZuAh76hDbW3tLzrjoLQQjbyIiMjXQ1mp4KuI3Lt3D0EQ0NTUZOTIkZibm2NnZ8fy5cvJzc3l\n8ePHwD8HoEipWbOmLO/Ro0dUrlxZYUvvj2U+PlNaWVkZQ0NDmUxZQnTXiIiIfD1K0F0j3Tp40qRJ\ndO3aFU9PTy5dukRYWBjq6uoIgoCamprC0XpaWlqySdPU1NR8zw7W0tLixYsXn5Upi5Ov4khepMh4\nuPZFt7xKvlf0+XP5llm4cAHqauXyzQO4e+c2bv37UNuwCoYGenS0b82xX458kZ7PnzwkZOJI+rVt\nRBcLQ9w7NiMsJIDU5LcFltkVHkrnJvkfYycIAvu3bcC7d3u6NTOip3Ud/Ab14NLZEwqyb98ksnLO\nVAZ1sqJ789qM7NWOfVvWF/qA8/zIyclh5fLFtLSywLCyDk0b1cPfbyxvPjodKzEhAX+/sdQxNkJH\nW5OWVhasDl2W76lJd+/cZpBrX+oZVaV29Uo4O7ThxLGjxdaxyJTgxKv00I/WrVszefJkbG1t8fX1\npX///oSFhZGbm1vgObLSdEEQvkimNM6Q/lLEkbxIkblx4zrmTSzwHTteIa++xFQh7dCBnwmYOrXA\n+n69cpmuzg7o6Ojy3Vg/1DU0CF+/hj49u7JtZyTfdO1eZB3jX/7FWNdvyM7KpGt/L6rVNOLOtSv8\nvHU91y6eY8nWw2iUl38lj446QviS2QXWuWHxLHauX04T61YMGR9IZkY6h3ZtJtDblQmzl+HYox8A\n6e/SmDy4N88e3qdLP09q1a3HpbNRrJwzhacP7uE7fX6R7wdg5JBBREbsoGdvF0aM8uH61d9YvyaM\n3369zP4jUaipqZH05g3fONrz5PFDvL1HYVKvHnv27mPq5Ak8e/aUWXMXyOr77dfL9PjGER0dXXy+\nm4CGhjob16+jX+9ubN6+m85d/oXdPEtwJC8dXbdp00YuvWXLlmzZsgVdXV0yMzPJysqSO8ovNTUV\nHR0dIO/EsNTUVIW6P5Z59epVvjJ16tQpsfspKUQjL1IkUlNTefTwAcNGjKL/ALdPyubk5LB00QKC\nZwaSk5OT79m2giAweuRQ1NTVOXbyHEa1awPg5uGJpbkpMwKnFsvIr1s4k5S3b1iy9TCm5nknanXp\nO4h6Dc0JCwng4I4f+dbTW6ZnxIZQNi4PITcnB+V89Lz/+z12bViBrX0nglZsko3kuvTzxLuXPWvm\nz6D9N71RLVeOgzt+5OG9W4z7fjHO3w4EoGs/T2aMdufgzrx2axgVzRj8vGc3kRE7GD1mHN/P+edH\noqZRbWYFTePQ/n30/NaF2d9P5/d7d9i6ay8uvfL6zdVzOC49u7AqdBljxk3EoGpVBEFgjPcw1NXU\nOXLiDLWM8vrd1c0Ta4uGfD894P+dkZf6yT8+xk963rCqqiqCIBAXFydnjD/8bGxsTHx8POnp6Who\naMjJSM8pMDY25tdff5VrIzc3l+fPn5fJba7L3ruFSJnm9q2b5Obm0ugzYWKJiYnYWTclaPpUOnX+\npsCDPGKjL3Dr5g2+G+snM/CQF/UQMm8hLv0GKPzRFobfYs5g0tBcZuCldOyeF3lx40o0AMlJbxjZ\ny54NS2bRoq0j9c0sFOoCOHXyJIIg0NnFXe5VXUtbB7sOnXn7JoEnf9wFICP9HfUamuPQzUWujmYt\n7REEgYf3bhX5fjZuWItexYpMCZwpl+7m4cU4P38qVzHIO3N42084OHaiU+cucnKTpkzDb3IAaWl5\no9SLMRe4fesmPmMnyAw8gG6FCsyat4Bv+/YvVr8XmRJ019SrV4+qVaty5Ii8m+/06dMYGBjQpUsX\n1NXVOX78uCwvKSmJixcvyo6AtLOzIycnh6ioKJnM48ePuX//vpzMq1evuH79ukwmNjaWlJQUhaMk\nywLiSF6kSNy8cQ2Ahg3zjHxqairly5dX8EW+fZtEeno668I307e/K12dO+Rb35kzpwBw7OQM5I2I\n0tLS0NbWpt+AgcXWc9n2o2RlZiqkJ77Oe81Wfm9EUlPekpWZzuR5YXTo+i0TPfM/q7S/60C0jZtQ\nzdBIIe+NtM73bwCuI8fjOlLRlfXHnTyjUDWfOj5FdnY2MRfO0dGpM+XLlwcgLS0NNTU1qhgYMC0o\nGICYC+dISU7GwbGTrGxKSgqCigbWNnZY2/xjgM6eOQ1AR6c82Q/73aWfa5H0+yJKcBdKZWVlxo8f\nz+TJk5kxYwbOzs5cuHCBPXv2EBQUhLa2Nm5ubixduhRlZWWMjY1ZtWpV3j275P0gGxkZ4ezsTGBg\nICkpKejq6rJo0SJMTU1l57Xa2tpiYWGBj48PkyZNIjs7m3nz5mFvb0/jxo1L7H5KCnEkL1IkbtzI\nM1QRu3YgqVOT6pV1qVGlAsMGexD/gZ/S0LAmV2/eo2//TxuMe3fvAFBeU5PhQwbJ6jOT1OGnTeHF\n1rNqjVrUNDZRSI8IXwmARYvWAFSpWoMNh2Lp0PXTB13r6OhQR9KI8lracul/PXvM+ROH0NOvjJGJ\n4nxE+rs0Hv1+m7ULgvhlzzZaO3alfqMmRbqXJ48fkZGRQW1jY3bv3I5d8ybUMqhAzSq6DHLty19/\n/QnA7/fy3iRqGNZk3uzvMaxRjYp6utStWYUZAZPJ/OBH7/699/1eXhPvYZ4YVdWjdrWKWDQ0Ycvm\njUXS74so4RWvPXv2ZOHChfz6668MHz6co0ePMnPmTPr37w/A+PHj8fT0ZMOGDfj5+aGjo0N4eLjM\n3w4QEhLCN998w4IFC5g2bRoNGjRgzZo1MnejkpISYWFhNGvWjMDAQEJCQmjfvj0LFy788v4oBcSR\nvEiRuHXjBpA3WTojeDbaWtqcOnmC8PVruXL5EifPxlChQgVUVQv3aL15kxcZ0rd3dwwMqrIsdDXZ\nOdmsXrmCUSOGkpycgvdo3xLRPerAbo7s/omqNWrRqfcAAFQKqWd+pKWmMHvCMLIyM3DznpnvnMPW\n1YvZsXYpAIa16zLMb0aR25H20bGjR9i4fg0+302gcRMLLl+KZeWyxdy8cY2os7G8eZN3qMnsmdN5\n9y6NwOkzqFKlCtu272TF0kU8eviQTdt2va8zT3ZAn54YGBiweMUqsrOzWRu2gjHew0hJTmbEqJLp\n909SChuUde3ala5du+abp6qqip+fH35+fgWW19TUJDg4mODg4AJl9PX1WbJkyRfr+m/wP2HkPxXy\nJFI0Brqp6wVuAAAgAElEQVR74ODoxHi/yTJD3qPXt9SXNMB/4jiWL13EtOkzP1PLP2Rl5vl9K1XS\n5+DREzK3T+9v+9LCsjHBQdMY6D4IXV3dL9L75MFIFgT4Ul5Ti8AlGxQia4pKytskAr1duX/rGvbf\n9KbbgMH5ytm07YiZZQuePrjHzvUr8P62A3PXRSjMFXwKqdvp/u932bnngMwd06VbD4yMauM31oew\nFUtRfR8x8vffL4i+coP6tQ0BcOzSi6GDlNmzeydnT5+iTTt72ai+kn4l9h0+Luv3nr1daGnVhNnf\nT2eA25f3+2cRd6Esdf7z7poVK1awdevWr61GsYmNjcXU1JQb70fQhcHd3Z0RI0aUij4enkOY5B+g\nMFIfOnwkqqqqRB0/VqT6NLXyjO2Q4SPk/Prly5en/0B3UlJSuHQx5ot03hUeyrzJ3qhrlGfWqm0F\nTq4Wlr//jGO8ezduX71EW+ceTAop+Jg6s2Y22LRzxGWwD/M27CYj/R3rFn5fpPY034cG1qlrIudv\nB3AbNBgVFRVOnTyO1vu+7NajF1WrVpOTGzR4GACnTh6Xq9NrqGK/9xvgRmpKClcuxRZJz+KgrKxc\n4CVSMvzne3L58uWkp6d/bTWKjZmZGTt27MDERNG/XJZQU1Ojgp4eKSnJnxf+AEPDvCXmHxslAAOD\nqgAkvy148dKnyM3NZcUsf9YtmElF/Sr8sHEvjZvbFqsuKQ/u3OA71848+eMu3fp7MeWH1YV2+dQ1\nNaNO/Ybcv3W1SG1K+8igalWFvHLlylGxYiWS3yb/I2eg2JdVDAyAf/rS0LDm+zo/L1uqKH3iEikR\n/vNG/v872traNG3aVGEvja9B3LNn2FpZMHKYl0Je/KtXvI6Pp24Rf4yaW1sD//j6P+TRw7x9vo1q\nGxdZV0EQWBQ4lv3bNlCrbn2WbDtMvYbmRa7nQ/64c4NJg3uTGP83g8dOwydwXr4jzgke3RnZyz7f\nOtJSU1DTKF+kdvUrV6a2cR1+v3dXFvMt5e3bt7x+HY9R7dpYNrcC4PYtxb58/Ogh8E9fNrPK6/fb\nN68XKFvrg5DW0kIcyZc+X7Unc3JyWLVqFR07dsTCwoIePXrIYlizsrJYs2YNnTp1wtzcnG7durF/\n/35Z2bi4OExNTYmKimLIkCFYWFjQpk0b2b7RAKamedEO8+fPp0OHvBA+d3d3AgMDGTJkCE2aNJFN\nrsTFxfHdd99hZ2eHpaUl3t7ess2GpG192D7AqVOnMDU15enTpwA8efKEUaNGYWlpiZWVFRMnTiQh\nIUEm7+/vz6hRo5gwYQJNmzbF2ztvMc6ePXvo0qUL5ubmtG3bljlz5pCRkQEoumsEQeDHH3+kW7du\nmJubY2lpiZeXF/fu3SuZL+UT1DA0JPntWyIjdsoiOaR8HzQNgIFug4pUZ9duPalQoQIrVyyV66tX\nf//Nlp9+pE5dEyyb5R9j/ykiNq7k2N7t1JE0YtHm/VStUevzhT5BYmIiM3zcSXmbxHdBC+k3bEyB\nslWq1eDR77c5d+yAXPrpI/v48+kjWjl0LnL7/V3dSUxIYFXoMrn05YsXIAgCPb91oZZRbVq3acex\no4flXFw5OTmsXLYYFRUVuvXoBcA3XXugW6ECq0KXk/hRv2/bsok6dU1oaln0fi8qopEvfb7qxGtI\nSAjbt2+XGcbDhw8zZswYNm3axNatW4mKisLX1xdTU1N++eUX/Pz8SE9Pl8W0AkyZMoWBAwcydOhQ\nDh8+zJIlS2jUqBHt2rVjx44d9OvXD3d3d3r37i0rExkZyYABA/Dy8kJXV5cXL17g4uJC1apVCQoK\nQhAEQkNDcXV1Zc+ePdSsWRNLS0uOHj0qt6Lt0KFDNGnSBCMjI+Lj43F1daVKlSrMnz+fzMxMlixZ\nwpAhQ9ixY4dsU6TTp0/j5OREWFgYSkpKXLp0ialTpzJmzBiaN2/OH3/8wdy5c1FXV8/3EIINGzaw\nZMkS/Pz8aNiwIXFxcSxevJgpU6YQGRn5Rd+Hptrn3pFVWBEaSu9ePXHu2I5Ro0ejr6/P/p/3c/z4\nMdzdPejn0jvfktKaP25Ds3IFwsJW4eY2kA5tbBjp7Z334x8WRmpKCtu370BL/fN/8LZ19GT/T0xM\nZFtY3vL9fn16k3g3msSP5KtWq459e8XYfV0NVZQ+qk9LXZWQFUuIf/Enjc3NaVSzIk9iDiqUdejo\nROUqVVi2cB4Ol86zYMpoEh5co159Cb/9eoUtm3+kvkTCioXz0K/8T/2aap+ffAyYMpnjvxwiaJo/\nD36/g42NDefPn2frlp9wcOjIkEHuKCsr55161K4NLj2+YfTo0RgaGrJ9+w7Onz9HUNBMzBvUe3+f\nFQkLW4W720Cc7O0YOfJ9v6963+/bdlChfOmbB6Vi7DYpUkSEr0RiYqLQsGFDYcWKFXLpbm5uwvLl\nywWJRCJs27ZNLm/cuHGCra2tkJ2dLTx79kyQSCTCjBkzZPk5OTlCixYthO+//16WJpFIhHXr1snV\nb21tLeTk5MjSQkJChKZNmwqvX7+Wpb1+/VqwtLQUQkJCBEEQhM2bNwvm5uZCSkqKIAiCkJGRITRv\n3lwIDw8XBEEQFixYIDRv3lyujqdPnwoNGzYU9uzZIwiCIEyePFmQSCTCmzdvZDKrV68WLC0thYyM\nDFnazp07ZWViYmIEiUQiXL9+XRAEQQgODhZWrlwp1y/h4eGCRCKR6ebm5iYMHz5csdM/Q3ZObqGu\n02fOCk5OnQRdXV1BXV1daNKkibBs+XIhMyu7wDLt2rUTVFRUCsw/EXVS6ODgIGhrawu6urqCo6OT\ncPbc+ULrlJSWKbt2Re4TgE9e7dp3kCsjvVq3aSuoqKjIpWXn5ApW1tafrfPI8ZOyMrd+fyC4urkL\nVQwMhHLlyglGtY0FnzFjhSd//q3QZlZ2bqGuxDdvhcmT/QVjY2NBTU1NqFOnjhAQME1ISX0nJ/f7\n/QeC60A3oUqVKoKGhobQ1NJSCN/4Y751njhxUujQQb7fz5w9X2idvpSKblsKvERKhq82kr927Ro5\nOTkyN4qUzZs3s2XLFgCcnZ3l8r755hsOHjzIgwcPZD7qpk2byvKVlZUxMDAgLS3tk20bGRnJvQ5e\nunQJGxsbKlWqJEurVKkSdnZ2XLx4EYDOnTsTEhLCqVOn6NKlC2fPniU1NVV2ekxsbCxNmzZFV1dX\n5jetXr06JiYmREdH07NnT1m9FSpUkLXTrFkz0tLS6N69O507d6Z9+/b06dOnwJDPadPy3CIJCQk8\nfPiQhw8fypZgZ2Zm5rsFamFJyyzcDomW1i2J2HdIIT09G/LsnSInok5+sg1ru7bsPfBLsXWKefRG\n9n9dUzuO3vq7SGWkBK6KUMizraPHidPn85UvuE4dBk1ZyKAp8gtk7iYCifL1WNWu+Nl6AVAtz6TA\nYCYFysdvZwiQkf7PDpP61Y1YvjocXY28N4S37/PepivuQtnUpjW7flbc7TM/2fyopPVlJkQcyZc+\nX83xlZSUBCBnWD/MU1VVRU9PTy69cuXKAHJ7Nn+4iRDkGXrhM9u56uvry31++/atrO6P5aQ70unr\n62NrayvbF+Pw4cO0aNECg/eRCG/evOHs2bOYmZnJXb///rvcjnUft21lZcXKlSupUqUKa9aswcXF\nhY4dOxZ4wsyDBw9wdXXFzs6OoUOHEhkZKdtR73P3LSJS1lBSUirwEikZvtpIXrqMODExkaofhIbd\nuXMHJSUlsrOzefPmjZyhj4+PB1Aw/l9KhQoVZHV/SHx8vFxbXbt2JSgoiKSkJE6ePIm/v78sT1tb\nm7Zt2zJmjOKE3OdG1x06dKBDhw4kJydz5swZwsLCGDduHBcuXJCTy83NxdvbGz09Pfbv30+9evVQ\nVlZmy5YtnDuX/z7uIiJlGXGCtfT5aj3cpEkTVFVVOXnypFz69OnTuXUrb5e+j3eTO3ToEPr6+hgb\nGxe6ncI8RM2bNyc2NlYuuiMhIYHo6GiaNWsmS3N0dEQQBBYvXkxGRgZOTk5ydTx8+BBTU1PMzc0x\nNzdHIpGwYsUKrly5UmDby5cvl51JqaOjQ5cuXRgyZAjJyckKp8wkJCTw5MkT+vbti0Qikd1bWTxX\nUkSkMCgpKxV4FYfExERMTU0VLungSxCEvMlpe3ssLCzw8vLiwYMHcnVkZmYyZ84cWrVqhaWlJWPG\njOHly5dyMklJSfj7+2NjY4O1tTUBAQFl8lQo+IojeX19fdmJLaqqqjRu3JjDhw9z584dpk+fjrKy\nMnPnziU1NRVTU1NOnDjBwYMHZXmFRVdXlytXrmBlZSV38O6HeHp6smfPHgYPHiwLawwLC0NNTY1B\ng/4JCdTW1sbe3p6dO3fSrl07Od+6l5cX+/btY+jQoXh4eFCuXDk2bNjA1atXGTt2bIH62djYEBoa\nyrRp0+jSpQtJSUmsWrWK5s2bK7iy9PX1qVGjBj/++CP6+vqoqKiwd+9eTp06BcC7d+8K3S8iImWB\nkh7J372bF9q7YcMGuTdo6Rt5aGgoa9aswc/PD0NDQ8LCwvD09OTQoUMy78KMGTOIiopi8uTJaGpq\nsmjRIoYPH05kZKRsfyJfX1/i4uIICgoiPT2d+fPnEx8fz+rVq0v0fkqCrxpCOXXqVCpWrMiWLVtI\nTEykfv36rF27FnNzcxYsWMDSpUvZuHEjb968oW7duvzwww907160AyR8fHxYsmQJly9fVnB/SKle\nvTpbtmzhhx9+wN/fHxUVFWxsbFi8eDHVqsmvCOzWrRtHjx5V2ACpRo0abN26lR9++IGJEyeipKSE\nmZkZ4eHhNGzYsED9WrRowaJFi1izZg0HDhxAXV2dtm3byrmCpCgpKbF8+XJmzZrFuHHj0NbWxtzc\nnPDwcDw9Pbl69SqGhoZF6h8Rka9JSU+83rt3j8qVK9OqVSuFvJSUFNavX4+Pjw8eHh5A3pxY+/bt\niYiIwMvLi6dPn7J3714WLlwoC6po0KABzs7OnDhxAicnJ2JiYoiNjWXnzp2ygWO1atXw9PTk1q1b\nmH3mrIV/GyVBnK0TeU9yem6p1S2Njy9stExRiX74ulTqhX9i5gsTXVMcCh1dU0Q+jq4pDb40uqbm\nqL0F5sWtzH9v/08xZcoUXr58yYYNGxTyzp8/z+DBgzl06JDcNiEjR44kMzOTDRs2sHPnTmbMmMGV\nK1fkVpl369aNpk2bEhwczOLFi9m1a5fcoDE3Nxdra2uGDRvGyJEji6x3aSLOeoiIiHw1Sjq65t69\ne7x7947+/fvLVpCvW7cOQRBkK9hr1ZJf/VyzZk1Z3qNHj6hcubLCNiIfy0iPGpSirKyMoaGhTKYs\n8T+x1bCIiEjZpCTdNTk5OTx48IDy5cszefJkatSowalTp1i4cCHp6emUK1cONTU12epzKVpaWrJJ\n09TU1Hyj4bS0tHjx4sVnZcri5GuBRv7QIcXFLoVB6scSERER+RwlPfG6atUqatSoQe33m6vZ2NiQ\nlpbGunXrGDlyZIFvCNJ04RNnT3woU5DeZTEktEAjP378eJSUlIq0wEZJSUk08iIiIoWmJEfyKioq\n+R6k3aZNG7Zv30758uXJzMwkKytLtoAQ8kbm0sgabW1t2QLID/lY5sMFjh/K1KlTp6Rup8Qo0Mhv\n2rTp39RDRETkf5CSHPm+fPmSU6dO4ejoKBd+LN3RtUKFCgiCQFxcnJwx/vCzsbEx8fHxpKeny62m\nj4uLo3nz5jKZX3/9Va7t3Nxcnj9/LreBYVmhQCPfokWLf1MPERGR/0FKcveCzMxMpk+fzrt37/D0\n9JSlHz16FGNjYxwdHZk+fTrHjx9n2LC8k7KSkpK4ePEiPj4+ANjZ2ZGTk0NUVJTMK/H48WPu378v\nJ7N69WquX79OkyZ5h7LHxsaSkpKS75vE16ZIE6+pqamEh4dz6tQpXrx4wZIlS1BTU2Pnzp14e3uL\nMdoiIiJFQrkE3TW1atWia9euLF26FCUlJUxMTDhy5Ai//PILoaGhaGlp4ebmxtKlS1FWVsbY2JhV\nq1ahra0t277cyMgIZ2dnAgMDSUlJQVdXl0WLFmFqakrHjh0BsLW1xcLCAh8fHyZNmkR2djbz5s3D\n3t6exo0bl9j9lBSFNvIJCQm4urry7Nkz6tevz+vXr8nKyiIlJYXdu3dz8uRJfvrppzLpkxIRESmb\nlKSRB5g9ezYrV67kxx9/5NWrV5iYmLB8+XIcHByAvLlGZWVlNmzYQFpaGpaWlsydO1fmb4e8cy5C\nQkJYsGABubm5tGzZkoCAANlqVyUlJcLCwggODiYwMBA1NTUcHByYOnVqid5LSVHoxVBTp07ll19+\nYcuWLVSpUoWWLVsSHh6OnZ0dN2/eZNiwYbRo0YKlS5eWts4ipYS4GCp/xMVQBfOli6HMAhS3l5Zy\na7ZTgXkihafQsx4nT57Ezc0NU1NThRCjxo0b4+bm9smNuEREREQ+RllZqcBLpGQo9M9wWlqa3JbA\nH1OhQoUyuRBARESk7FIW48r/axS6h+vVq1fglra5ubkK+0GIiIiIfA4lpYIvkZKh0EZ++PDhREVF\nERgYyG+//QbAq1evOH/+PEOHDuW3336T25ZXRERE5HOI7prSp9Dumk6dOhEUFMT8+fOJiMg7B3Py\n5Ml5laiqMm7cuCJvAywiIvK/jWjMS58iTY3379+frl27cv78eZ49e0Zubi7Vq1enVatW+Z7VKiIi\nIvIpRCNf+hQ5/klbW5tOnTqRkpKCsrKywpacIv9/UVUpvT84qY+1tNroMXBmqdQLcH7LpPdtzC+V\n+hMvrSiVeqVzmprqZXezWdHIlz5F+vYfPXpEaGgoZ8+e5e3btwBUqlQJBwcHfHx8MDAwKBUlRURE\n/psUd994kcJTaCN/69YtPDw8yMjIoG3bthgZGSEIAk+ePGH37t1ERUWxbds2hQ35RURERApCHMmX\nPoU28vPnz0dbW5s9e/YonIry4MEDPDw8CAkJYeXKlSWupIiIyH8T0ciXPoUOobx27RoeHh4KBh7A\nxMQEDw8PoqOjS1Q5ERGR/zZiCGXpU2gjX7FiRd69e1dgfrly5dDW1i4RpURERP43KE0jn5mZSefO\nnfH395elCYJAWFgY9vb2WFhY4OXlxYMHDxTKzZkzh1atWmFpacmYMWN4+fKlnExSUhL+/v7Y2Nhg\nbW1NQEBAmV3xX2gjP3ToUDZu3Jjv/jQPHz5k48aN4mIoERGRIlGaRn7FihU8fPhQLi00NJSwsDAG\nDx7MokWLSE5OxtPTk+TkZJnMjBkz2LdvHxMmTCAkJIS7d+8yfPhwcnL+2ejN19eXixcvEhQUxNSp\nU4mKimLChAlfrHNpUKBPXrqp/ofk5OTg5uaGubk5xsbGKCsr8/z5c3777Td0dHR4+vRpqSorIiLy\n30K5lKJrbt++zebNm6lY8Z8dPlNSUli/fj0+Pj54eHgAYGVlRfv27YmIiMDLy4unT5+yd+9eFi5c\nKDs0pEGDBjg7O3PixAmcnJyIiYkhNjaWnTt3YmFhAUC1atXw9PTk1q1bmJmZlco9FZcCjfzHrzCA\nrMPi4+OJj4+XpUtDJ8+fP1/S+omIiPyHKQ3fe3Z2NlOnTmXIkCEcO3ZMln7t2jXS0tJke8tD3saK\nLVq04OzZs3h5eRETEwOAvb29TMbY2Jj69etz9uxZnJyciI6ORl9fX2bgIe/AcG1tbc6ePfv/x8hH\nRUX9m3qIiIj8D6JSCkZ+7dq1ZGVlMXz4cDkj//jxYwCFMO+aNWvK7N2jR4+oXLmywiLPmjVryso/\nevRIIQBFWVkZQ0NDmUxZokT3+SyrEw8ipUdOTg7t27ZCp3y5T8otXLAAtXIFy9y5fZsBfftQs1pl\nqupXoH3bVvxy9MgX6aasrMQYtw5ciQggIXoRdw/OZOGkPujplC+wjKGBHs9PzePgKp9884e7tCFm\nuz8J0Yv4+9wCfln3HU6tGsnJ3D04k3e/rfjkVRzu3L5NP5feGNesRpWKOjg52HP8mOKhG8d+OYqD\nfRt0tLXQ1dGms5MDFwp4y75z+zb9+36LYVV9DCrpYt+m5Rf3e1FQVlIq8CoODx48YNWqVcyaNQs1\nNTW5vJSUFNTU1BTStbS0ZLYrNTUVLS0thXqLKlOWKNKK14iICM6fP09aWhq5uf+cIpSTk0Nqaip3\n7tzh+vXrJa6kSNklZHYwsTHRsqPR8uPA/p8/eTTalSuX6ezYAR1dXcaO90NDQ4P1a9fQq3sXdkTs\noWu34m18Fz57EH2drYg4eoXQrado2rAWI/q2pblZbRyHLCErW/7EJCUlJdYFu1OpguIfMEDwmO74\neTlx+tLvTFu2Dw21cgzu3Yo9y0YybMZPbD1wEYCJP+xGS1NdoXxLSxOG9WnNz1HXinwv9+7epV1r\nWzQ1NfEe7Yu2tg4/hq+n2zed2LRlOy59+wF5fd33257UrFWLoKCZCILAsuXLcHZsz8Ejx2jTtp2s\nziuXL+Ps2D6v3ydMRENdg/XrVtOz2zfs3L232P1eFEpyJJ+bm0tAQAB9+vTB0tJSIV8QhAJX2ErT\nCytT0D74ZXF//EIb+XXr1rFgwQLU1NTQ1tYmMTGR6tWrk5iYyLt379DQ0GDgwIGlqatIGSM2Jpp5\nIbNRV1cnOztbIT8nJ4fFC39g5oxAcnJy8v0hEAQB72FDUFdX5+Tp8xjVrg2A+yAvmjSSMD1gSrGM\nTa+OTenrbMWSTSeYsniPLP3pXwkE+3ane/sm7D72m1yZse4dsLWom2996mqqjB/UkQOnb+AydrUs\nfW3EOS7tnMK88b3ZeeQy2dm57D+lONDR0ynP9z7deBQXz7AZm4t8PwFTJpGRkcGZ87E0aNgQAA9P\nLywaNyBgyiSZkQ8Omo6GhgbHT56lXp08l0L3Xn2wbNKIgCmTOXM+z+csCAIjhw3O6/czF6j9vt89\nPL0wb1ifwAD//3dGfvPmzfz111+sWbNG7nkUBIHs7Gx0dHTIzMwkKyuLch+8VaampsrOeNXW1iY1\nNVWh7o9lXr16la9MWTzjutA/OxERETRq1Ijo6Gi2bt2KIAiykMrvv/+ejIwMzM3NS1NXkTJEcnIy\ngz3dcerUmRY2tgr5iYmJtGhmwfRpU3Hu3IXmzZvnW09M9AVu3rzB2PF+MgMPeRNi835YRN/+A8jK\nyiqyfkO+bU1CUiozVx6QS/9xzwXmrTvK3wnyr9VNJIbMGN2VmaHy8lJ0tDTyDoDeLe/2SE5NZ//J\n61SuqE2jutUL1GfWdz2pVb0S34Xs4G1KepHuRRAEyqmp0ftbF5mBB9DR0cHG1o5nT5+SkJAAwB9/\n3KdhIzM5n7FxnTo0Nm/C9WtXZWnRF973+4SJMgMP7/t9wWL69XctVr8XlZI8NOT48eO8ePECa2tr\nzMzMMDMz4+7du+zduxczMzNUVVURBIG4uDi5cnFxcTLjbGxsTHx8POnp6Z+UefbsmVx+bm4uz58/\n//9t5J8/f07Pnj3R0tLC2NgYXV1dLl26hLKyMn379qVr165s2rSpNHUVKUNMGPcdKcnJrFy9Nt/8\nt0lJpGekE/7jT+yK3FvgQrnTp04C4NSpM5D3xyL1a/Z3HYj/1Glyo67CoKKiTCtLE85evk96Rp6h\nKq9RDhUVZV4lphAUup+zV+7L5DXUy7ExxJOYa49Y+lP+AQcJSalYuczhzOXfFfIM9PNGeDm5+R9S\n3rBuNQb1sGX/qescu3CnSPcCeW6CbTsiCN/0k1x6dnY2t27eQE9PDz29vMPGTU0b8OTxIzkjlZmZ\nSdyzp9QwNJSlnTmd1++d8un3AcXs9+JQknHyM2fOJCIiQu4yNjaWhUh26dIFdXV1jh8/LiuTlJTE\nxYsXsbOzA8DOzo6cnBy5wJPHjx9z//59OZlXr17JuaZjY2NJSUmRyZQlCu2uUVNTo3z5fyas6tSp\nw927d2WfW7RowZkzZ0pWO5EyyZ7dEfy0aSM7IvYUeO6vYc2a3Lj9+2d9lPfeP0OampoM9RrEnsgI\n3r17Ry0jIwICZ+AxyKvI+hkb6qOhXo7Hf76mr3Nz/Ic507BudTKzsjl05ibj5+3ir1dJMvmQsT2p\nXqUCPUavRBDyN9S5uQK3/vgz37a6t7fg5eu33Hn4V75lA727oKysxIzlPxf5XvIjISGBu3fusGB+\nCPd//51FS5bL+nn+oiV826Mrg9xdCf7+e5SVlZkRFMSLFy9Ysy5cVsfdO3k/Npqamgzx9JDr92mB\nQXh4Fr3fi4NKCcbJ162r6GrT0NBAT09P5mVwc3Nj6dKlKCsrY2xszKpVq9DW1sbFxQUAIyMjnJ2d\nCQwMJCUlBV1dXRYtWoSpqSkdO3YEwNbWFgsLC3x8fJg0aRLZ2dnMmzcPe3t7GjduXGL3U1IU2shL\nJBKio6NlnWFiYiL3SxYfHy83GSvy3+T58+f4jh7JIK/BdOveo0A5VdXCPVqJbxIB+LZnNwyqViU0\nLM+fujJ0OSOHDSElOZlRPmOKpGNFnbzwt06tzBjapzWLfzzB9Xv7adHEmO/cHGgiMaSl63ySUt7h\n1KoRI/u3wyvgR569SCxSO9qa6vw0fwga6uWYvDCS3HxG8rWqVaSbfRMOn73FnYcvilR/QfTu0ZXY\nmLx9orr16In7IE9ZXosWNvh+N47ZwTP5ee8/cxHBc+bKyb153++9e3bFwKAqoavWkpOdzcoVyxgx\nbDDJycmM9i1avxeH0gih/BTjx4/Pc7tt2EBaWhqWlpbMnTtX5m8HCAkJISQkhAULFpCbm0vLli0J\nCAiQzSkpKSkRFhZGcHAwgYGBqKmp4eDg8Mnggq9JoY28q6srEydOJCkpiaVLl9K5c2eGDRtGUFAQ\ndevWZePGjaJP/j+OIAgMH+JJBT09fli4pETqzMrMBKCSvj5HjkXJRqTfuvSlmYUZQdOn4ebhia6u\nbqHrVCuX98fYoG41uo8OlblI9p+6zpM/E1ge0B9ft/as3nGG1UFuRBy9wvZDl4qkdwXt8uxZPpLm\njU28aiYAACAASURBVIzYcfgya3blf8j9kG9bo6qqwtLNJbfuZMLEvGM3z5w+xaqVK2jbyoYTp85R\nsWJFXHr34JejR3B06oS7uzvKysps376dwKn+/P3yJfMXLALyXDgAlSrpc/T4Sbl+t2zSiKDpAbgP\nKlq/F4fS3ohs3759cp9VVVXx8/PDz8+vwDKampoEBwcTHBxcoIy+vj5LlpTM30BpU2iffLdu3QgK\nCuKvv/5CQ0ODNm3a0K9fP7Zv386cOXPQ1NRkypQppanrV8XU1JT169d/UR2xsbGYmppy48aNQpfJ\nysrCz8+Ppk2bYm1tzfPnzz9bJjIyElNTU9lkXEmxbMkiTp2MYt4Pi0hPT5etfJZO0MXHx5OUlPSZ\nWuTR1MwLVxw2fKSca6d8+fK4DnQnJSWFi7ExRaoz9V2eAXvw9JWCD3zj3gtkZ+fgYNuAsBkDUVVR\nZubKg+jrackugHKqKujraVFeQ9EvXataRU6Ej8OuqQkRR68wJLDguaieDhb8+fcbuTmAL6Vb9x50\n696DHxYuZuHiZdy5fZuVK5Zx4vgxfjl6hK7duvPzwSMMHDiQAQMGsCtyHx6DvFi+dDEnjuctDpLG\neQ8f4a3Q7wPdPIrV78VBSUmpwEukZCjyGa/9+/eXfZ45cybDhw8nKSmJevXqKSwyEPlyzp49y/79\n+5kwYQKWlpZUr15wBEdpc+jgAQRBoO+3PfPNN6phQJu27Th6/GSh66xZqyYAVatVU8gzeO/vT35/\nCllhiXuZ54p4+VqxXHZ2Lglv09DR0pCFS97YN11Brk3z+sSdnMesVYfk0ptIDNm7YhTVq1Rg1Y4z\njJ+3q0A/fv3aBpjWqUbo1sL3R1Hp7zqQ73xH8euVy2i+N9zu+cxjDBk2gk0/hnPi+DEcOjpiWDNv\n1We+/W6Q1+9vi9jvxeHfdtf8L/LFhz8aGhpi+MGsvUjJIh0Z9+nT56sflh4yfwFvEhX91lMm+XHr\n1k1+PngEvQ82hCoMVlYtWM1Kbt64TgeHjnJ5jx7m7Z9kZGxcpDpfv0nlUVw8pnWqoaKiTE7OP3NF\nOloaVNbT4vLNJ0xcsDvf8odW+fLbnWcELN3Lo7h4vmmbN5lmYVqTw2vGUEFbg8Bl+1gQfizf8lJa\nN6sHwPHou5+U+xxPHj+mS2dHOnToyLLQMLk86e6JGuXLo66WtwDrw90SpUjTpP9aW7dgdVgoN64r\n9vvD9/1eu7bxF+ldGEpy4lUkfwo08tId2IqCkpISBw8e/CKFyjJv3rxh/PjxnDx5EjU1NXr06MHE\niRNloWbZ2dmEhoayZ88eXr9+Tf369Zk4cWKBYVX+/v4kJiZiZWXFhg0byMrKol27dgQGBqKnp4e/\nvz979uRNntnZ2dGrVy969eqFh4cHERERcnMgVlZWDBo0CF9f31K7/2bN8o9116tY8f/YO+/4Gq83\ngH/vzUCmIIREJEGuLZHYK4k0ZiillCBqK21pjQq1GyN2CX72qFVba4/aQWqUUpvEiBEiN/Mm9/z+\nSPNWJCEkIdXz/XzeD/e8z3vGe3Of97znPAOVSpVOWWQF31YfYznIkh9nz8Svi7/yIHv48CErly/D\nqXTpTNt9FSu3hTCyb3MGdPRkxop9Svmgrt6o1Wp+3h3KgZC/Mr3+6fOYNOcN1Cp+ntEbKwsT+o5d\nxdJNr0+Q41I+Zbb8+5/Zi85qV7IkCQkJrF3zE98MHkqpFx56kwMnANCyVWvc3NwxMDAgeM5sfFu2\nwtjgn5/3vOCUUAreH/kAf993S0t+nD2Dzl1fvu9LU+57Jr4NOYlMDpL7ZKrkCxcu/C778a9g4cKF\ndOzYkblz53LixAnmzZtHyZIl6dy5MwAjR45kx44dfPnll5QpU4atW7fSs2dPli9fTrVq1TKs8/Tp\n01y/fp3vv/+ehIQEJk2aRN++fVm9ejX9+vXDxsaG4OBgFi5cSKlSpbh/P2MzvX8rFhYWzJ4zD/8u\nnahfpwa9evclOTmZBfOD0Wq1rPhp7Vutz05btpdmDSox4etWlC9dnJN/3KSOS2k6tqjBvhOXWfPr\n6Teqr1hhC2ysLTl/JZz4hCQ6NKueTmbv8Us8fvqPk1VZ+6LExSfyMDI6neybYGBgwKwfg2nXphWe\nDevSp+8XmJtb8Osv29i7Zzdt2rbj0/YdUKlUDB/xPePGjKJh3Vr4+fmhVqvZsHEjhw/9xqcdPuMj\nn8bA3/d97nz8O3ekXu3q9OrTL+W+z5uLVqtl5ep172RdXC7X5D6ZKvkVK97c9fpDp06dOowcORJI\nmVnv37+fkJAQOnfuzPXr19m4cSPjx49XzEwbNGjAo0ePmDFjRqaOYjExMaxdu5YyZVJe7QsWLEjv\n3r05efIkNWrUUDwXK1asSKFChXJVyed7y8W71N9pVq7PSKZTx/bY2dowYfx4Jowbg1qtpmatWvz0\n009Zdi45umpIBv1S8TAymvZN3fHzrYkuKZn7j6IoZGnCkZWDX1mfe0UHpc5yjjbk+7vjVZztWDIh\n4+Q4f92MICYuQflc3skGQwODDPv2IsaZh/1RaOXbnAMHf2P8+HEETZ5IYmIiGo2GmTNn0e+LL5QZ\n8ehR31OpYgVmzpjOiBEBJCcnU65cOWbNmk3ffv140W2h02ftsSthw4Tx45gwdvQL9331O3PqkTP5\n3Cfba/L/JV4OemRra6tsTp08mRKcqkGDBmniZjRs2JBp06YpJmsvo9FoFAWfKm9kZMTp06epUaNG\nTg8hV9h/4PUbiwf+lsl4izJl3A0bNszk7NuhF4J7D6O49/DNLH4yWl5JSEji8s03s3PPKbv4VOrW\nrcuOHa+PENm2bVvatm1LqvrM7J5D7tz3NyHvhfP68JBK/g140eMXUiLOpVpWPHv2DEhR8hnxNIMN\nSwBra+s0n1UqFQULFnxjU8ScICF9jLEcI3UGn1tt1O00OXcq5p+3hNxq4+mptws9/DpS3xAS0+/D\n5hj5s6lB5HJN7iOVfA5hbm6OSqVizZo1GUZbtLKyyjChQOrDIRW9Xs/Tp08z3RN5MdxpKkKIVyZZ\nl0jyKlLJ5z7ybSmHcHNzQwiBVqulcuXKynH8+HGWLl2aqZv/5cuXefDgn9f6gwcPkpSURM2aNTOU\nTw309fDhQ6Xs7NmzGYb6lUjyOgbqzA9JziBvZQ5Rvnx5GjduzODBg1m1ahUnTpxg1qxZTJ8+nRIl\nSmQaqCspKYk+ffqwd+9eNmzYQEBAAB4eHmnyR76IRqOhWLFizJw5k4MHD7J9+3aGDh2aJvaGRPJv\nwVClyvR4GxITE5k+fTqenp64uLjQpUsXLl68qJwXQhAcHKz8xrp165Yun3ViYiI//PADdevWxdXV\nlS+//JKIiIg0MlFRUQwbNoyaNWtSvXp1AgIC8mRWKHiL5ZqwsDAOHTrEgwcPaNu2LQUKFCAsLCzT\neOH/JYKCgpg5cyYLFizgyZMn2Nra8s0339C9e/dMrylTpgxNmzZl+PDhqFQqfH19XxlXw8DAgBkz\nZjBhwgT69++PnZ0dgwcPJjg4ONNrJJK8Sk4v1wQGBrJlyxa+/fZbSpUqxfLly+nSpQtbt27F1taW\nOXPmsGDBAr799ltsbW0JDg7G39+fX3/9VZkojRo1iv379zN06FBMTEyYNm0avXr1YuPGjcpS7IAB\nAwgPD2f06NHEx8czefJkHj9+zPz581/VvfeCSmTmk50B06ZNY9GiRSQnJ6NSqVi8eDFarZYBAwbQ\nuHFjpkyZIkMbvAHDhg3jwoULbN+ecaKKd02cLst/Cm9Mbm+8FqqRe05gcuM1c7K78fr9rsxj+oxt\nXPaN6oqOjqZ27dp88803dOuWEtohPj6emjVr0rt3b7p06UL9+vXp27cvvXr1AlJm5J6engwYMIBu\n3bpx584dGjduzNSpUxWH0Fu3btGkSRNmzZqFj48PJ06coGvXrqxbt0554z5+/Dj+/v5s3LiRihUr\nvs2tyDWyvFyzatUqFixYQNeuXVm5cqWy8efu7o6fnx+7du1i4cKFudZRiUTy4WGoVmV6vCkFChRg\n3bp1tGnT5p/6DQ1RqVQkJiZy7tw5YmNjadSokXLe0tKSGjVqcPhwShTREydSgrJ5eHgoMg4ODpQt\nW1aROX78OIULF06zpFqzZk3MzMwUmbzEGyn5Jk2aMGTIEEqXLq2UW1lZMWLECFq1apUurKdEIpG8\nipzceDU0NKRChQpYWlqi1+sJCwtTlkFbtmypWLeVLFkyzXV2dnbKuZs3b1KkSBFMTExeKfNiekVI\nMae2tbXN0ILufZPlWxkWFkatWulzeabi5uaWxkpE8nomTpyYZ5ZqJJL3gYFKlemRHebOnYu3tzdb\ntmyhR48eODk5odVqMTY2TrekbGpqqmyaxsTEKGGYsyOTl8jyilrhwoVfGcv8zz//fO9REiUSyb+L\n3LKT9/b2pkaNGoSEhDB37lx0Oh358+fPNB7Pi/4nWZHJzFrudeku3wdZ7lHTpk1ZtWoVoaGhSlnq\noDdv3szPP//MRx99lPM9lEgkHyxqVeZHdihXrhw1atRgwIABdO7cmUWLFlGgQAESExOVJDepxMTE\nKJY1ZmZmxMTEpKsvqzKZJax/n2R5Jv/ll19y/vx5OnfujI2NDSqVigkTJvD8+XMiIiIoX748X36Z\n+zkhJRLJh0NOzuQfPXrEoUOHaNy4cRplW758eRITE7G0tEQIQXh4OI6Ojsr5Fz87ODjw+PFj4uPj\nyZ8/fxqZVDNxBwcHfv/99zRt6/V67t69i6+vb46NJ6fI8ky+QIECLF++nDFjxuDs7IyTkxM6nY7S\npUszfPhw1q5dmyefYhKJJO+Skxuvz58/Z/jw4ezatStN+dGjRylcuDDe3t7ky5ePvXv3KueioqI4\nefKkEnWzdu3aJCcns3//Pzl5b926xdWrV9PIPHr0iPPnzysyISEhaLXadxa98014IytXAwMD2rVr\np4TSlUgkkuyQk5mhSpcuTePGjZk0aRI6nY6SJUuye/dutmzZwg8//ICZmRl+fn7MnDkTtVqNg4MD\n8+bNw8zMTNFp9vb2NGnShJEjR6LVarGwsGDatGloNBq8vVOS4tSqVYuqVavSv39/hgwZQlJSEpMm\nTcLDw4NKlSrl2Hhyiiwr+RefWq+iSpUqb90ZiUTy3+Jt7OFfxaRJk/jxxx9ZsGABDx8+pEyZMsyc\nOZMmTZoAMGjQINRqNYsXLyY2NhZXV1cmTpyYJixIYGAggYGBBAUFodfrqVOnDgEBAYq3q0qlIjg4\nmHHjxjFy5EiMjY1p1KgRw4cPz9Gx5BRZ9ngtV65cljLFXLp0KdudkrwfpMdrxkiP18zJrsfropOZ\np0bsXsM+03OSrJPlrygwMDBdWXJyMpGRkezevRutVsv48eNztHMSieTDRubxzn2yrORbt26d6bke\nPXrQuXNndu3ahbu7e450TCKRfPjk5Jq8JGNyxHJfrVbj6+srvTclEskbkVser5J/yLHMUPfu3SMh\nIeH1ghKJRPI3MjFU7pNlJf/rr79mWJ6YmMhff/3FypUrqV+/fo51TCKRfPjIGXvuk2UlP2jQIFQq\nFZkZ41SoUIGAgIAc65hEIvnwUUsln+tk2YTy5MmTGZar1Wqsra0pVapUjnZM8u6Jz8U0sbltzvck\nOveWCq3NjQB4FK17jeTbERmTO/WWKVoAgGsPcy/Je2W77Hm5/3zufqbn2lYtnq26JSlkeSa/fv16\nGjdurHh9SSQSSXaRyzW5T5ata3bt2pUuma1EIpFkh9yKQin5hyzP5DUaTZqs5xKJRJJd5Ew+98my\nkm/VqhXTpk3j2rVrVKtWjUKFCqULc6BSqejRo0eOd1IikXyY5PTGa3JyMsuXL2fdunXcv3+fEiVK\n0LFjRzp16qQYjsybN4+1a9fy9OlTqlWrxogRI9KkNE1MTCQoKIhffvmF2NhY6tevT0BAAMWKFVNk\noqKiCAwM5MCBA+j1enx8fPjuu+/yZCTeN4pd89rKVCoZu+ZfjNx4zRi58Zo52d143XnxUabnmlS0\nfuP6Zs+ezYIFC+jXrx8uLi6cPn2a4OBgBg4cSM+ePZXgZd9++y22trYEBwcTERHBr7/+qgQp++67\n79i/fz9Dhw7FxMSEadOmUaBAATZu3KgEKevSpQvh4eEMHjyY+Ph4Jk+eTJUqVZg/f/7b3YhcJMsz\n+X379uVmPyQSyX+QnMyWl5yczJIlS+jevTt9+/YFUmK/R0ZGsnjxYj777DMWLVpE//796dKlCwDu\n7u54enry888/061bN+7cucPmzZuZOnUqzZo1A1ImuE2aNGHfvn34+Phw4sQJQkJCWLduHVWrVgXA\nxsYGf39/Ll68SMWKFXNuUDlAprd48+bNhIeHK59tbW2zdEgkEklWycmwBlqtlo8//hgfH5805Y6O\njkRGRnLixAliY2Np1KiRcs7S0pIaNWpw+PBhAE6cOAGAh4eHIuPg4EDZsmUVmePHj1O4cGFFwQPU\nrFkTMzMzRSYvkamS/+677zhz5sy77ItEIvmPoVapMj3eFEtLS77//nsqVKiQpvzAgQPY2Ngo1oEl\nS5ZMc97Ozo5bt24BcPPmTYoUKYKJickrZezt04ZBVqvV2NraKjJ5iUyVfBaX6iUSieStye0AZevX\nr+fYsWP06NEDrVaLsbExxsbGaWRMTU3RarVASjJuU1PTdPW8qUxeIgdXxCT/FS79+Sft27XBwc4G\naytzfBp5sHfPbuX8imVLKWCkSnMYqFOO1M/jx45W5JOSkvhx1kzcXCpRyMIE59KlGDr4G54/f57j\nff/z4h/4f9aG8qWKUsGhGJ0+acGJY+lfsZ8+jWTksEFUr1QaS3NTXKpWZuG8H0lOTrtzLIRg2aL5\n+DSoQekSBdHYF+GTFt7s37MrXZ1vw/kzp3B1KMjvJ4+9Uu7B/bvUq2RPz8/SJ5IWQrBqcTAfe7nj\nVrowDaqUYtiA7jy4F55BTXBwz690beNDTY0NDV0c+ap7B25e+ytHxvMyOTmTf5mtW7cyatQoGjdu\njJ+fH0KITBMfpZZnV0adk5sMOcQrN16fPXvGvXv33qjCEiVKZKtDkrzNX5cv07BeLUxMTOj7xQDM\nzMxZtmQRvs0as3zVGtp92p569RuweOmKNNcZqFN+HEOHDObp06c0adpcOfdV/34sXvQ/WrVuQ5++\n/bl06U/m/jiLQwcPcODwMfLnz58jfT8TeopPWzVGr9fj370PtiXt2bpxHR0+bsqseUto2SYlz2dU\n1DPaNPXizu2bdO3eh0rly7Jt21ZGD/+Wu2F3GDXhnwxRgWNHMndmELXrNWD4qAkkJMSzatkiunb4\nmOlz/kfbDn5v3d+wWzcY1LNTugfLy+j1egK+7sXzqKcZnp86PoDlC2bjWr0WHbr04v69MH5aPI/T\nJ46wdscRChf5x4pl3YpFjB/+NRWrVGPg8HFEPnnEqkVz6dL6I9b8ehjbkjkbviS3rOSXLFnCpEmT\n8PLyIigoCJVKhbm5OYmJieh0OoyMjBTZmJgYxbLGzMyMmJiYdPW9LPPoUXqroJiYGBwdHXNpRNlA\nZIJGoxHlypV740Py7yVO9/qjeQtfYWxsLM6c/1Mpexj5XBQvUUKUtLfP9LpkvRCTJ08RgJg6fZZS\nfiwkVADis45+aeQnTp4qADFvwaIs9Ss8Mv61R+WqrkKlUom1W3YqZbceakXN2nWFZUEr8cf1eyI8\nMl507dFHAGLp6o0iPDJeJOiSRYIuWTT0+kioVCpx5vJtER4ZL34LOS9UKpX4qElzEfYkTqnz0q2H\nwq6kvbAqVFjcjIh+bb/Oh0WnO2YvWScKWhUSQEpfNuzKUO58WLQYGDBOGOfLJwBRs56HUh6bkCTu\n3H0gDAwMhHP5SuL3m0+Vc5N+XCIA8Xm/gUrZ7pBLIn/+AsK1ei1x+tpjpXzF5r0CEJ927pGu7exy\n/OrTTI+3ZerUqcLZ2VkMGTJE6HQ6pfzw4cPC2dlZ3LhxI4187969RY8ePYQQQqxZs0aUL19exMXF\npZFp0aKFGDVqlFJ/3bp105xPTk4W1apVEwsWLHjrfucWr5zJe3t7o9FocvkxI/m3IITAyNiYNp+0\no1z58kq5ubk5NWvVZvPGDURGRlKoUKF01968eZORI0dQo2Yt+n7RXym/ezecam7u9OrTL42890cp\nFhLnzp3Nkb7fDb/DH+fO4NHIh7r1PZRyQ0NDen3xNd392vHLlg180t6PDWtW4dHIB+/GzdLUMWhI\nAK5u1YmNTZnpHTl0ACEEnbp2T/P6bm5hQeNmLVk0/0euXP6TipWr8iYM7f85O7asx7GMM7Xqe7Fz\n68+Zyl6+eJ4fp4xjwODvmTZhRLrzt27dJDk5mdoNvDA0/Ofn7unT/O/r/1DKtv68mvj4OL4Z+QPG\n+fIp5VXdatL/25EUK57zb+lZyRv9Jixbtoz58+fTpUsXhg8fnqZ+V1dX8uXLx969e+nZsyeQ4tR0\n8uRJ+vdP+ZusXbs2ycnJ7N+/XzGhvHXrFlevXk0jM3/+fM6fP0+VKlUACAkJQavVUrt27RwdT07w\nSiXv4+ODr2/6NT7JfxOVSsXqtekVTlJSEhcv/EHBggUpWLBghtd+990wdDod02f+mOaH18K3JS18\nW6aTP3vmdwBKlXLIkb7fv3sXgPIVK6c75+hUBoBzZ37HuVwFtNpoPL0bK+e1Wi2mpqa41aiFW41a\nSvknn3akRu262Nun7+PjRymWHOq/nWfehBtXL9PvmwC69fmaRXOnZSoXHxfHsAGf4+JWky69BmSo\n5B0dnTAyNk63pn7n1nUAitn8E+nx1PFDFLQqRGWXlBSeOp2O5KQk8hcoQK+vhrzxOLJCTsaoefjw\nIUFBQTg7O9O8eXPOnTuX5nylSpXw8/Nj5syZqNVqHBwcmDdvHmZmZrRrl7JUZ29vT5MmTRg5ciRa\nrRYLCwumTZuGRqNRgjPWqlWLqlWr0r9/f4YMGUJSUhKTJk3Cw8ODSpUq5dyAcogcywwl+e8RGRnJ\n5UuXCJocyNUrV5g2Y3aGG08XL1xg/bp1tPv0U6q5uWVaX1JSEndu32bvnt2MDBiGU+nSdO32eY70\n1eRvawhtdPrN3MjIxwA8jHjA1b8uA1C8hC1TJ45jxZL/8fjRQywtLenQ+XOGjhijWGeYmZtTvkL6\nH/XtWzfY+ctWilgXxVlTPt3517Fq64E0M+nMmDZhBI8iHhC8YlOmG36FCxfm62FjmDo+gHkzJtKi\ndXseRtxnQsAgTM3M6dT9C0X25tW/KG5nz6U/zjJ1fAChIUfR6/VUcnFn6OiJVHWr+cZjeR05OZM/\ncuQIiYmJXLlyhfbt26c7f/z4cQYNGoRarWbx4sXExsbi6urKxIkTlfV2gMDAQAIDAwkKCkKv11On\nTh0CAgIUb1eVSkVwcDDjxo1j5MiRGBsb06hRI4YPH55jY8lJpJKXvDVtWrUg5MRxAHxbfUznrv4Z\nys2ZPROAwYNfPRs8eGA/vs1SZtAmJibMnD030zeDN6WspjyWBa3Ys/NXRo6dqCh9gF+2bgIgPj6O\nqKhnAEweP4q4uFgGDR2Bo10xfv55PfN/nM7tWzdYuHxtpu1oo6Pp+7kfCQkJfD/kH8XwJmRFwR8+\nsJs1yxbww8z/Udy25Ctlm338KaEhR5k7dQJzp04AIH8BE35cuh7n8v94Zz6PeoZKrebzT5vh0/xj\nOvj3JuL+Xf43ewrd2zdnyfqdVHZ1f+PxvIqcXK1p06YNbdq0ea3ct99+y7fffpvpeRMTE8aNG8e4\nceMylSlcuDAzZsx4q36+azK192ndunU6g///AkL6B2SZbwYPZd2GzfT/8mt2/LKdBnVr8vRpWguP\nqKgo1qxeRcOGDXF7xSweUpZmft60leD5C3FyKk3L5k1YuCBnYoEYGRkxYOAQHty/S+f2rTgdcpyb\nN64za+pENq79CSMjIwwNjdAlJgLw6GEE2/YcpsvnvWjzSVt+Wr2Wlq3bsXP7Fo4ePphhG1FRz/Br\n58v5s7/T6pNP6dq9d470/WWePH7E99/0pXGLNrRo0+GVshEREXT09eDgnl/5tHMPpi1YyfeTZmFn\n70Dfzq3ZvX2TIqvTJRJx/y6f+fdi7NRgPmrWCr/u/Vi45hf0yckZLgdlF5Uq80OSM2Sq5AMDA9O4\n7f4X+PHHH/npp5+Uz7Nnz8bV1TVTeY1Gw6JFi7Jc/8aNG9FoNERGRmb5mufPn9OzZ0+qVKlCnTp1\nSPxbCb2K1/U7p/Bt2Qrflq2YMnU6U6fP4tKfKaaPL7Jzx6/ExcXRvsNnr62vrLMzzVv44v95dw4e\nOY6DoyPDhw3OMQeT3v2/5tvvvuds6Ck+bupJffeKrP1pOUtWb0ClUlHQygoTk5QZflPfjylazCbN\n9Z38uwNw+GD6OE53w+/QpqkXp0+ewPfjtswMXpwjfc6IUYP7kZyUxBeDR/A08rFyACTpdDyNfExc\nXCwAc+fM5v7dMAYFjGfED9PxbtqKth278dO2g9g7ODFq8BdEPU35eyzw99jbd+2Vpr2y5SpQ1a0m\nZ04dJz4uZ4Od5aadvCSFvGe5/x6ZPXs28fHx77sbadiyZQuHDh1i7Nix/Pjjj+m89fIKHTp2AuD3\n0NNpyn/ZvhUDAwM++eSTN6rP1NSUFr6tiI6O5spfOeOIo1Kp+HrwcM78dYdNv+5nz5HTHDl9ETs7\nexITE3FwLE1xWzsAir4QVjYVa+uUsujo6DTlF/84R0ufhvx1+U+6du/NnIXL01iy5DSH9u7k2dNI\nWjasRsOqjsoBEBpylIZVHVkSnLKU8Mf58wB83L5zmjryFyiA7yefEaON5vyZUwAUK54Se6qIdfqx\nF7Yuil6vJy4uvQ15dpAz+dxHrsnncaKioihQoAAff/zx++4Kt2/donnTj/Dy8mbWnOA051IVX/4C\nBdKUHzl8iKourhQpUiTDOocPG8KKZUs4dvL3dDFFtH/XWeClOt+WrRvXY2JqinfjZlSvVUcp1aJv\n3AAAIABJREFU3783xTu1Tr0GlHJ0AuDSxQvprr996wYAJV9wCLpw/iztWzXh+fMohn0/jv5fD86R\nvr6KBT9tzbC8V8eWlKtUlUHDx2H3t8VPvr/X9/X69A5VqU5Wqf9WdnHj+pVLXLl0gQqVXdLIht2+\niYmpGQWtCufUMACZyPtd8EHM5DUaDRs3bmTgwIG4urpSs2ZNJkyYQFLSPwHSY2JiFA+4KlWq0LZt\nW44cOZKmDoDJkyfj5eX1Vv2IjY1l3Lhx1KlThypVqtC5c2f+/PPPTOU7d+7M6NGjCQwMxN3dnVq1\najF27FgSEhKU87NnzyYuLg6NRsPs2bMzXPJ5/vy5cg9yE7uSJUlISGDtmp+4/VIgpsmBKRt6LVu1\nVsoiIiK4f+8ebm6Zb9aVKVOWx48fM33qlDTlN65f5+f1a3HWaNLY5GeHJf+by6D+vXj+PEope/Qw\nguBZU6lYuSp16ntgV7IUtes1YP+enYSeClHkkpOTmT9nBgYGBjRrmfLAffbsKd06fkJU1DMmTZ/z\nThQ8QK36nhkeAJYFrahV3xO7Uikz+yZNU2y9V/xvTpo6YmO0bF2/ivwFTHB1TzELbdk25W0seNoP\n6PV6RfbE4QNc+uMsjVu0znG7djmTz30+mJn8Dz/8QKtWrZg7dy6nTp1izpw5ODo60rFjR/R6PT16\n9ODGjRsMHDiQ4sWLs2HDBnr16sX8+fOpX78+a9eupX379nTu3DndDv2LD4vMEELQt29f/vrrLwYN\nGoS1tTUrV66kc+fObNq0KdNN7G3btlGqVCkmTpzIgwcPmDp1KlFRUUydOpVRo0axZMkStm/fzrJl\ny7CxseHYsVfHMMkOxq8zBDEwYO7cYFp/3AqvhnXp1+8LLCws2LZ9G3t276Ztu3b4deyg/EBvXb8C\ngJOjg+K+/nIbPbp3Y81PKwieM5vHjyLw9PQi7M4dgoPnIoRgyZKl5DN8/S8+NbHHqxg5cgStfFvQ\n8eMm+Hf7nPiEeObPC+Zp5BNWr15DUYuUpbB5wcF4eTTAr20L+vb7gpJ2tqxdu5YTR48wavQY3Co5\nAzB78izu37tL5cpVsC5oyp6t6a1uPvJpjLX1q5NfFDLN/GeYes7OKp+SBORVmBipFbl8hmo+9+/K\nhvXr+N/sKUTcucpHPo2JjHzC0sWLuX3zBrN+nIubJmWZpkyrjwjp04/58+YyoLMvbdu1587tW8yd\n8yPFS5Rg2pSJFMtCH94EVa4FNpAovFd/2xzC2dlZcUtO5eOPPxa9e/cWQgixb98+4ezsLA4dOpRG\n5tNPPxWtW7dOU8/ChQuVz7NmzRLOzs6vPFLlDx06JJydncXRo0eV63U6nfDx8RHDhg0TQgixYcMG\n4ezsLJ48eSKEEMLPz0+4uLgon4UQYuXKlcLZ2VmEhYUpfXBxcVHOv1yHEEJERUUJZ2dnsWHDhgyv\nySrJ+qwdhw4fET6NGwtzc3ORL18+UaVKFTFz5iyhS0pOI7f+5w0CEHOD5wm9Xgh9JvVpY2JFQMAI\n4eTkJAwNDUWRIkVE+w4dxJ+XLme5T6mhB153bNm2XdSuXUdYWFiIYsWKiU/athVnz/2RTu7ylWui\nY8dOwtraWuTPn1+4urqKxUuWppFxd6+uhB3I7Nh/4LfX9ik2ISnTY/iIkQIQe/cffKVcbEKSAISn\np5fyOTlZL5KT9SJKGyfGjBsvypUrL4yNjYW5ubnw8PAUW7b9kq6OmHid+HHuPFGlqovIly+fKFq0\nqPDr3EVcvXE7wzazy593tZkekpzhg5nJv2wJVKxYMWJjUywMTp06hampKfXr108j06xZMwIDA9Fq\ntZnmZsyfPz8rV67M8Fzbtm2V/4eEhFCgQAGqV6+eZuZfr1499u/fn2m/a9eunSYMQKNGjRg7diyh\noaHY2dllel1ukNXUfNVr1WXL9p3pypME8EIdLVq1IU6XYpKaapiaURsGxgUYMXocI0ant0vOap+e\nZDE1n1tdb9b/4p2u/OXUfmZF7Jj8Y4rl1Ivp/16U27w7awkiXpc28FXp/zr0HkKH3in+Ba9L43c+\nLDqNXOqM/vbTJFr7f0Vr/6/SXZNRnQ18O9HAt1OasrhMZLOb/i+nl38k6flglPzLm3NqtVqxeX/+\n/HmGG39FihRBCEFMTEymSl6tVlO5cnpX+Jd59uwZcXFxGbo1vxjx7mVefpVPVfhRUVEZiUskHxQ5\nGdZAkjEfjJJ/FZaWljx+/DhdeWq40JzwqjQ3N6dw4cJvnMj32bNnaT4/efIESPGoy4gXY1qnkvrG\nIpH825Az+dzng7CueR1ubm7ExMSky7+4Y8cOKlasqJiZZSfgv5ubG5GRkZiYmFC5cmXl2LZtG1u3\nZmzyBinLPHEvOJjs3bsXtVqNu3vGFimpbxwPHz5Uyk6fPp2hrESS11GrMj+yy759+9I5BQohCA4O\nxsPDg6pVq9KtWzeuX7+eRiYxMZEffviBunXr4urqypdffqmkDkwlKiqKYcOGUbNmTapXr05AQECe\nzAoF/xEln/qFDh48mLVr13Lo0CG+/vprzp07x4ABAxQ5CwsLQkND00Wvywqenp5UrlyZXr16sWnT\nJk6cOMGYMWNYtmwZpUuXzvS6Z8+e0adPH3777TeWL1/OtGnT6NixI8UycMaBlITB+fLlY8KECRw9\nepT169czbdq0POskJZG8EtUrjmzw+++/M3hwepPWOXPmEBwczOeff860adOIjo7G398/jYPbqFGj\n2LJlC9988w2BgYFcvnyZXr16pUneMmDAAE6ePMno0aMZPnw4+/fv55tvvslep3OJ/8RyjYGBAQsX\nLiQoKIjp06cTFxdH+fLlWbBgAQ0aNFDk+vfvz4wZMzh9+vQbmyoaGBiwaNEigoKCmDJlClqtllKl\nShEYGPjKoEn16tXD0dGRr7/+GjMzM7p3707fvn0zlbewsGDGjBkEBQXRu3dvypYty+TJk/niiy8y\nvUYiyavktDNUYmIiy5YtY+bMmZiYmKDT/bOprdVqWbRoEf3796dLly4AuLu74+npyc8//0y3bt24\nc+cOmzdvZurUqUo8+XLlytGkSRP27duHj48PJ06cICQkhHXr1ikGHzY2Nvj7+3Px4kUqVqyYvmPv\nEZUQMiLX+6Jz586YmJi88Tp+bhH/eneAtybVPj6r1jJvypPohNypmLTWNbnBq6xrskOqdc3rrHKy\nQ3ata249yTyMiEPhN0/7uHfvXr777jsGDBjAs2fPWLJkCWfOnAHg6NGjfP755/z6669p3q779OlD\nYmIiixcvZt26dYwaNYrQ0FBMTEwUGV9fX1xcXBg3bhzTp09XEoSnotfrqV69Oj179qRPnz5v3O/c\n5D+xXCORSPImOR2grHLlyuzbt48uXbqk29S99beX9svhM+zs7JRzN2/epEiRImkUfEYyLzs3qtVq\nbG1tFZm8xH9iuUYikeRNctqEMrO9LEhZrjE2Nk63f2VqaqpsmsbExGD6Qq6BF2UePHjwWpm8uPkq\nlfx7ZMWKFe+7CxLJe+bdmVAKITI12XzRNDkrMplZ4mXHQi+3yHs9kkgk/xly04TyZczNzUlMTEyz\nGQspM/PU9H9mZmbExKQPp5xVmcycKt8nUslLJJL3xrtMGlKqVCmEEISHh6cpDw8Px9ExJWqng4MD\njx8/TpdX4mWZsLCwNOf1ej13795VZPISUslLJJL3xrsMNezq6kq+fPnYu3evUhYVFcXJkyepXbs2\nkBJLKjk5OU28qVu3bnH16tU0Mo8ePeL83wlZIMWpUavVKjJ5CbkmL5FI3hvvMmmIqakpfn5+zJw5\nE7VajYODA/PmzcPMzIx27doBYG9vT5MmTRg5ciRarRYLCwumTZuGRqPB2zslsF2tWrWoWrUq/fv3\nZ8iQISQlJTFp0iQ8PDwyjF31vpFKXiKRvDfedeiaQYMGoVarWbx4MbGxsbi6ujJx4kRlvR1S8lsH\nBgYSFBSEXq+nTp06BAQEYGBg8HefVQQHBzNu3DhGjhyJsbExjRo1Yvjw4e92MFlEOkNJFKQzVMZI\nZ6jMya4z1JOYzP/oCr8imYok68i7KJFI3hsyx2vuI5W8RCJ5b0gdn/tIJS+RSN4bciaf+0glL5FI\n3htSx+c+UslLJJL3hpzJ5z5SyUskkveGVPG5j1TyEonkvSFzvOY+0k5eIpFIPmBk7BqJRCL5gJFK\nXiKRSD5gpJKXSCSSDxip5CUSieQDRip5iUQi+YCRSl4ikUg+YKSSl0gkkg8YqeQlEonkA0YqeYlE\nIvmAkUpeIpFIPmCkkpdIJJIPGKnkJRKJ5ANGKnnJB4Ner3+v7UdHRwMgY/5J8hJSyUs+COLj4xkx\nYgRHjhx5L+3fuXMHDw8Pdu/ejUql+uAU/YULFwgODn7f3ZC8BTKevOSD4PTp0/z222+Eh4djbGxM\njRo13mn7SUlJuLi4MHToUIyMjPD09EQI8UHES9fpdPzyyy8sWbIEIQT9+vV7312SvAEGo0ePHv2+\nOyGRZBd7e3tKlCjB4cOHOXv2LHZ2dtjZ2b2z9q2srKhUqRL3799n7ty5lC9fHkdHxw9C0RsYGFCq\nVCnUajWLFy9Gr9e/84eo5O2RSl7yr0ev16NSqShbtiwFCxbk6NGj71TR63Q6DAwMKFSoEJUqVSI8\nPJzg4OAPRtELIbC0tMTR0ZGkpCSWLl0qFf2/CKnkJf9q9Ho9arU6jaI3MzPj+PHj70zRGxgYEBsb\ny6lTp6hYsSJVq1YlLCzsg1D0qfc3KSmJggULUq5cORISEqSi/xchlbzkX0tycjIGBgYA3Lhxg4iI\nCKytrdFoNJibm3Ps2LF3pugHDx7M/PnzKVWqFNWqVftgFL1KpSIxMZFOnToRGxtLnTp1KF++vFT0\n/yKkkpf8K3lRwQcEBDBjxgzWrFnD6dOnadGiBeXKlXunir5GjRr89ttvHDp0iCJFiuDm5vbBKHoD\nAwN27drF5s2bKVy4MO7u7lLR/4uQSl7yr0StTrH+/frrrzl58iR+fn64u7uzefNmQkNDadq0KRUq\nVFAU/R9//EHRokWxt7d/6zbv3LmDkZERBgYGaRR1cnIypqamNG7cmO3bt3PkyJE0ij48PJwFCxbg\n6OhI2bJlsz323CIpKQm1Wq3sMUDK2NRqNS1btuTKlSssXboUa2vrdIpeCCEVfV5FSCT/ApKSktKV\nbdu2TTRr1kyEhoYKIYS4deuW8PPzExqNRvj5+YmEhAQhhBDbt28X9erVEz179hRxcXFv1f7Zs2eF\nRqMRO3bsEEIIERMTI2bMmCGioqLS9C8yMlK0bNlSeHp6KrJhYWGiU6dOws/P763afheEhISIzp07\nC61WK4QQIi4uTsTExAghhNDpdIrcwIEDRZUqVcS6detEcnKyiIiIEOPHjxcajUasX7/+vfRd8mqk\nkpfkeeLi4kSzZs3E6dOn05TPnj1btGzZUlHcq1atEn5+fmLu3LnCzc1NfP755yI+Pl4IIcT+/fvF\n7du336r96Oho4efnJ7p06SKEECIhIUEcOXJEaDQaERAQIKKjo4UQ/yj6Z8+eCU9PT9G4cWPxyy+/\nCL1eLx4+fCiSk5Pfqv3c5vbt26JOnTpi6NChIikpSeh0OtGnTx/h6empjO1FRf/VV18JFxcXsW7d\nOpGYmCju378vlixZkkZGkneQHq+SPI9Wq8Xb2xuNRgP8EzbAxMQEExMTjIyMCA0NZdKkSTRt2pS+\nffvSqFEjjh49iq+vL4cPH8bT0/Otl2rMzMwwNTUlIiKCiIgIhg0bhlqtZuLEiWzdupUJEyag1Wox\nMDBAp9NhaWlJ3759uXv3LsHBwRw7dgxra2vFCiiv8eDBA6Kjo2nVqhUGBgbs3LmTZs2aoVKp6Nat\nG1qtFkNDQ5KSkgAYO3YsNjY2LFq0iNWrV1O0aFH8/f3TyEjyDlLJS/I8RYoUYeDAgZiZmTFmzBh2\n7NgBgLe3N926dUOlUjF69GhatmxJx44dATA1NcXd3R17e3tsbW3fum0hBMnJyfTq1YuYmBi8vb15\n+PAhbm5uNG3alNGjR7N9+3YmTJjA8+fPMTIyAuDp06d4e3vj6elJrVq1lPpS9xLyEkWLFqVq1aoM\nHDiQWrVqcfHiRerVq0dAQACPHj2ia9euREdHY2iY4iCvVquxsLAgMTGRY8eOpdmfSJWR5B3kNyLJ\n04gXrFGioqK4evUqW7ZswdjYGG9vb+zt7Xn+/DmxsbG4ubkB8OTJE8LCwqhduzZffPFFttpXqVQY\nGBhQunRppT8xMTHodDpMTU1p3rw5AKn2Cx07dkStVnPw4EF8fHzw9/cH0loD5TUcHBzw9/dn4MCB\n6PV6ateujZWVFXXq1OH7779n7Nix+Pv7s2TJEkxNTXn69ClWVlZMnz6d4sWLK7F6/m1WQ/8VVEJ8\nYJGUJB8MGSnGyMhIRo0axZEjRwgKCqJRo0ZERETQrFkzPD09qVmzJr///jvHjh1j6dKlODo6vnX7\nqT8NlUrFqVOn2L17N+XKlWPGjBkUL16cxYsXY2ZmRkJCAjt27GDMmDHodDpMTEywtbVl/fr1eX5m\nq9PpMDIyYtiwYVy9ehUhBPfv32fRokVUqFCB+Ph4jh07xvjx4wFwcXHh8uXLGBsbs2HDBgwMDBSH\nKUneRCp5SZ7kRQW/Z88enj59irW1NZ6enjx69IixY8dy9OhRJk+ejLe3N9u2bWP48OFYWFhgZmbG\nzJkzKVeu3Fu3n5SUhKGhYToFlpSUxOHDhxk5ciTFixdnyZIlmJmZAXD79m0OHDiAhYWFsr6dWk9e\n4+UH6LNnzzA0NOTcuXPMmjWLO3fusHDhQipWrEh8fDyXL19m3rx5PHv2DFtbWyZNmpTh/ZHkPaSS\nl+Q5Xnz1//rrrzl//jxRUVE0adKE/v37U7x4cSIiIhgzZgzHjx9nypQpeHt7c/fuXXQ6HRYWFhQq\nVOit209VXDExMYwdO5awsDDi4+Np3749Xl5eWFtbc+DAgQwV/Yvk1SWa1AdPfHw8u3btIi4ujkKF\nCuHj4wNASEgIQUFBhIeHK4o+Fa1Wq4w1rz7AJGmRSl6SZxk/fjx79+5l6tSpFCxYkKJFi2JmZkZ0\ndDQWFhZER0czdOhQTp8+zejRo2nWrFm220xV8ImJifj6+mJpaUnJkiXR6XTs3r0bLy8vvvjiCypW\nrMj+/fsZM2YMxYsX53//+x/m5uY5MOrcJfUBGhMTQ7t27YiPjyc6OhqtVkudOnXo378/rq6unDx5\nUlH0ixYtonz58mkevnIN/l/EOzbZlEgy5UWHp9jYWOHn5ydWrVqlfD569Kj49NNPhZeXl/D39xda\nrVY8f/5cdO7cWTRs2FBx5HlT9Hp9ms8JCQliz549okuXLmls67dv3y5q1Kgh+vfvLyIjI0VCQoLY\nu3evKF++vBgxYsRbtf2u0Ov1yv1NSkoS06dPF506dRJ//fWXuHXrljh48KCoV6+eaN68uTh37pwQ\nQojDhw+Lzz77TGg0GnHz5s332HtJdpBhDSR5Ar1eryxt7N69m5IlS7Jy5UpiYmIwNzdn+vTpzJgx\ng0KFClG1alXOnDnDrVu3aN68OXXq1KFt27ZvtURz4cIFFi5ciJubG8bGxiQlJTFmzBhWr15NbGws\nPXv2VNaeNRoNNjY2zJs3D41GQ4UKFbC1taVu3bp89tlneXJt+saNG+TPnx8jIyPUajXx8fEsXryY\n3377jerVq+Pr60vBggVxcHDAx8eHlStXcvv2bVq0aIG9vT1WVlaYmprSsmXLPDk+yeuR35rkvfPi\n5t2QIUOYOXMmN2/epH379oSEhNCjRw8uX77MwIEDWbt2LWPGjKFOnTo8ffoUgGLFimFjY/NWbV+6\ndIkVK1Ywbdo0YmNjMTQ0pESJEpiYmPDkyRMiIyOVPur1enx9ffH09GTTpk3odDry5cuHu7s7BgYG\nJCcn58wNySGeP39Ojx49aN++PXFxcQAcO3aMNWvWcOnSJQoUKKDI6nQ67OzsGDt2LEeOHOHw4cMA\neHl5MXbs2Dw5PknWkLsmkvdOqoLfunUrd+/eZdiwYVSqVIkyZcpQo0YNnjx5gpOTE8WKFQMgJiaG\nyMhIihYtqgTQetv14VatWgEo5o9jxoyhX79+FCpUiAULFjB+/HjGjh1L4cKFgX8eSBYWForjUyp5\nbZM1f/78fPPNN0yZMoXu3buzePFivLy8SE5OZvLkyWzZsoVatWpRrVo1ZSwlS5bE2NiYhISEdPXl\ntfFJsoZU8pI8wfr161m4cCGxsbE4OTkBYGxsjLOzMwBXr15lw4YNODg4sH//fs6fP8/q1auzrXiM\njY1p1aoVer2ecePGIYRg9OjRdOjQgcTERLZu3cqYMWMYOXIkVlZWhIeHc+/ePWrXrg3k7Q1IY2Nj\nPvroI4yMjBSHpqVLl/LRRx+RnJzMvHnzWLlyJSqVCldXV4QQJCQkYG1tjYmJyfvuviSHkGvykjyB\nWq3m/v37nDlzBoD69eujUqnQ6XTo9Xo2btzI4sWLCQ0NJTExkdmzZysPgLfhReVsYGBA2bJlsba2\nZsGCBURERODh4YGLiwvx8fHs2bOHpUuXsn37dk6dOkV0dDQzZsxIF3I4ryGEwNDQkJIlS1KqVCm2\nbt3KgQMH8PX1pVy5cpiamrJ//3727dtHTEwMx48fZ/ny5RgaGjJw4EC5Bv+BIJW85J2TusTyItbW\n1lSoUIGnT5+ydetWhBBUr14dAwMDDAwMqFixIp988gnNmjWjQ4cO2YpHk5SUpHhqxsfHk5ycjLGx\nMVWqVMHS0jKdojc2NubPP/8kLi6Onj17Mnr0aMXRKS8qwpeXsAwMDChZsiROTk5s2rRJUfQVKlTA\n0tKSI0eOsHPnThISEmjUqBGBgYEYGhpm+D1J/n1IJS95p7zoIJQ6O163bh1CCEqXLk39+vW5f/8+\nO3fuJD4+nurVqwMpM31zc3OsrKzIly9ftto3NDREq9UyePBgVqxYwbJlyzh79iz29vZ4eXkp6/EP\nHjygYcOGVKlSBZVKxfXr17l27RoeHh7KpmVem8mnOijFxcWxZcsWdu/ezYMHDxBCUKtWLRwdHdm4\ncSMHDx5UZvTFixfn2rVrWFlZ0bRpU0qVKqU8CPPa+CRvjlTykndK6sxwwIAB7Nq1i+TkZOLj49m4\ncSOhoaFUqVKFRo0aERYWxo4dO9DpdLi7u+fYjFKtVhMXF8enn36KTqfDy8sLW1tbwsLCCAoKwsXF\nBR8fH2Xp5tGjR9SvXx9XV1eSkpIIDQ1l27ZteHl5Zejl+j4RQmBgYIBWq6Vdu3acPHmS69evs3//\nfg4ePEhCQgJt27ZVlm7279+Pr68vzs7OWFhYcOjQIf744w8KFy6Mk5OTVPAfCu/NQl/yn2XDhg2i\nXr164uzZs0pSijlz5giNRiN++uknIYQQ9+7dE8OGDROVK1cWixYtypF2U52efvrpJ9G8eXNx7do1\n5dy8efOERqMRO3fuFM+fPxdCCLF69Wqh0WjE/PnzFbn//e9/om3btiI8PDxH+pRTpI4tKSlJDBw4\nUHTq1ElcvnxZCCHEkydPxKeffio0Go3i3LVnzx5Rt25d4ePjo2TQ2rVrl2jQoIHo0aOHiI2NfT8D\nkeQ40rpGkuu8HMTq3r17FCxYECcnJ8zMzAgLC2PFihW0a9cOjUbD0qVL8ff3p3v37hgbG+Pl5ZUj\n/UidmUZERBAbG0uRIkUA+PXXX5k+fTrDhw/H0tKSUaNGMWLECNq2bUuRIkXw8PBQ6ujRowft2rXD\n0tIyR/qUHa5fv05UVBTVqlVLM+u+ceMGDRo0UDamQ0NDuXjxIuPGjePatWs8fPgQb29v4uLi+OWX\nX5RrfXx8UKvVaDSaNDb0kn857/spI/nvkBp2YMKECaJOnTpCCCEePHggqlevLr766iuRnJwstmzZ\nItzd3RU3+sTExGy1+WLIglS3/pkzZ4q6desKIYTYsWOH0Gg0Yt68eUIIITZt2iRcXV3FpUuX0tSj\n0+nyTPo+vV4v4uPjRa1atUTz5s3TpEWMiIgQderUUd5+Nm3aJDQajZgzZ46IjY0Vffr0EQEBAUII\noczgX/6/5MNCbp1L3gnjx4+nT58+AHh4eKBSqRg1ahS+vr7Ur1+fMWPGoFarSUpKwsTERJlJvuxw\n9CbodDpUKhXJycnKAdC2bVtiY2Np06YNgwYNYsiQIfTq1Uu5LiM7cUNDwzxjaaJSqciXLx8LFy7k\n0aNHTJkyhdOnTwMpWZ5q1qzJihUrWL16NcOHD+err76iX79+FChQgJiYGJ4/fw6k2NGn8uL/JR8W\neeOvVvLB4+zsTEREBKGhobi4uFC1alXWrl1LyZIlGTduHJaWljx//pyjR49SokQJTE1N36qdiIgI\nHj16BKQ8ILRaLcOGDaNr165MmDCBU6dOUaJECb766iseP35M6dKl6datG3FxcVy/fp1Vq1bh5ORE\nyZIlc3L4OU5ycjIVK1Zk2bJl/PXXX0yePJmQkBAA2rdvj4GBAWPGjKFnz5707dsXIQQ3b97kyZMn\n2YqzL/n3Ia1rJDmOyMAL1NTUlC1btgDg6elJ7dq1uXz5MhEREZw+fZqLFy+yatUqTp06xaxZsyhR\nosQbt6vVavHw8ECn01G1alXy5ctHmzZtePLkCZaWlpw6dYozZ85gb29Ps2bNUKvV7N27l02bNrF5\n82Z27NiBWq1m8eLFih19XrEwSb2nqX1KfespWrQon3zyCdOnT+fx48eUKFGC6tWrY2RkRHh4OFeu\nXMHS0pJ9+/axaNEiACZNmpRn3kokuY9U8pIc5UUFHxsbqyy3FCxYEGNjY4KDg6lZsyZOTk54eHig\nVqu5c+cOd+7cwc7Ojh9++IGyZcu+VdvGxsaUL1+ewMBA1Go1N27c4OHDh0yePJkuXbpQtmxZzp49\ny4EDB3B0dMTX15emTZsSFxdHmTJlqF27NmPGjMHQ0FCxE88rPHnyBBMTkzSKXgiBWq15NMXLAAAX\nMklEQVRGq9WyZMkSbt++zZUrVyhfvjyNGjWiVKlS3L9/nzVr1vD48WOcnJyYP3++dHT6jyGThkhy\nhSFDhhAfH0+TJk2UZB4PHz5k0KBBVK5cma+++or8+fMr8nq9HiBHFM+RI0fo1asX5cqVw87Ojlmz\nZinnDh06xNy5c4mPj+err77C09Mz3fV5LaPT3bt3admyJd27d6dfv34AJCYmYmxszMWLF+nUqROf\nffYZjRs35vPPP6d06dKMHDmSKlWqAClLWIULF1acm2RGp/8WciYvyRXu3LnD2bNn2bx5M7///juF\nChWiTJkyxMXFsWLFCj777DPy58+vhAZQqVQ5tjRib29PtWrVWLhwIYaGhmkcl0qVKkXRokU5d+4c\nx48fx9zcPN2bQ16b4T558oRHjx7x888/Y2RkRLVq1TAwMOCPP/7Az8+Pli1bMnDgQOzt7WnYsCEL\nFy7kzz//pFSpUtja2mJmZqbcY/G3w5Tkv4NU8pJs8/Krf3JyMm5ubnh7e1OlShV2797NgQMHOHTo\nEK1bt+a3337j3r17NGzYMNcUasmSJXF3d2fRokUYGxtTpkwZZTM3VdHv27ePxMREvL29c6UP2SU6\nOpp8+fJhZWVF6dKliYuLY/HixRQtWpRChQrxySef4Ovry/DhwzE1NUWv12NtbU3Dhg1ZtGgRx48f\np3r16oo/AOS9MAyS3Ecu10iyxYtLGwsWLOD69evcvn0bDw8P6tevT8WKFUlMTGT79u388ssvhIaG\nYmVlhUqlYvHixTg4OORq/44ePUr37t3p3bs3nTp1omjRosq5c+fOUalSpTw5s33+/DnLli2jYsWK\nijNYVFQUkydPZuvWreh0Orp27cqgQYOUrE/wz/dx4cIFpk6dysKFC/Pk+CTvDjmTl2SLVOXy9ddf\ns3PnTszMzDAyMmLPnj0cOnQIGxsbypYtS/ny5WnVqhX29vZotVrCw8Pp1KlTrsd/sbe3x8XFhVGj\nRpEvXz5Kly6tzOhtbGxQq9V5chMyMTGRoKAgQkNDsba2ZsSIEXh5eVG1alWSk5O5du0adevWpVat\nWoovgFqtVsZjY2PDxx9/nGfHJ3mHvC8vLMmHw8aNG4WXl5c4c+aM4jm5d+9e4e/vL3x8fMSpU6fS\nyEdHRyvxYd4VR44cEeXKlRPjxo0TkZGR77TtNyXVS/fJkyfC3d1duLq6ihYtWognT54IIYS4du2a\nGDlypKhYsaJYuHChcl1e8ciV5C3k413yxryc6zMsLAwLCws0Go1itdGoUSO6desGwObNm9Hr9cp1\nZmZmmJubv9M+161blzlz5nDhwgUKFiz4Ttt+U1QqFYmJiRQqVAidTkdsbCwGBgZcuXIFgNKlS+Pv\n70+bNm2YPn26Yv+uVqsRcvVV8hJSyUveCL1er6zx7t69m4SEBKKiooiMjKRAgQKo1Wp0Oh0ADRo0\nwMvLi3379imK6n3i5eXF6tWrFSuTvEhqv1LDDEyZMoUlS5Zw9+5dgoKCOH78OABOTk74+/vzySef\nMHPmTMVMVG6sSl5GKnlJlnkxmuS3337LvHnzCA8Pp3r16sTHxzN//nyEEBgZGZGUlASApaUllpaW\necYuO1XB50VlmJSUpDg7RUdHo9VqqVevHrVr12b16tXcvn07naLv3r07np6ehISE5NkHl+T9kjd+\neZI8j/jbuxJSZvC3bt2if//+lC5dmmLFilGpUiU2bdpE/vz56dq1K4aGhjx79kyx185LSjUv9SWV\nFzNWjRgxgvDwcCIjI3FycqJ3795Ur16dNWvW0KFDB2bMmIEQAgcHB1QqFZMmTcLY2DhPP8Ak7w9p\nQinJFJ1Ox2+//YabmxtWVlYALF++nGXLlqHX61mzZg3FihUDUrwqv/32W27evImDgwOOjo7cuXOH\nixcv8tNPP2Ur6fZ/hdSMVfnz56dBgwZotVpCQkK4du0aU6ZMoWnTply9epVOnTphYmJCVFQUGo2G\nNWvWAOnj9kskIE0oJa/gzJkzzJgxAysrKzQaDadPn6Z27dpcuHCBc+fOkZCQoCTUMDMzw8PDA2Nj\nY+7cucP9+/cpWbIkgYGBbx2L5r9C6ux71apVXL9+nWnTpuHj40P9+vVxd3cnMjKS4OBg6tSpQ8WK\nFfH29iYyMpIqVaowdepUZa9DzuAlGSFn8pJX0rlzZy5evIidnR1RUVH89ttvPHjwgHHjxnHu3Dn8\n/PyUOPEvkrq+/L43W/9NfP/991y4cIHVq1cryy8AV65c4ZtvvsHW1pagoCDMzMzQ6XRK8DcZi0by\nKuS7nSRDUgOGrVixAiEEt2/fpnXr1mi1WmxsbBg+fDiVK1dm8+bNLFiwQLku1bLG0NBQKvhX8OLc\nKtW0NCEhgfj4ePLly4dKpVLupbOzM9WrV+fKlSvK9/JiMhWp4CWvQip5STpSN1kTExO5c+cOhQsX\nxsnJiZUrV7Jjxw6io6OxtbUlICAAR0dHNmzYwMKFC4HsZXL6r5D6lpOarSpVcbdp04awsDDGjx8P\npL2X5ubmFCtWTN5fyRsj1+QlaXjRBV6tVlOwYEG6dOlChw4dOHr0KJs2bcLGxgZ7e3usra1xcXHh\n8uXLbNu2DSMjI1xcXN7zCPI2qVY0MTExBAQEsOL/7d15TBT3+8DxNwvIobTisYqieMCuUCCiQD1B\nPKKxtlovVDzRoJbi2Wi1FkRtPGrVgooaiRUxXigetYqxWmvFGi803oqIeILiBSgKO78/jPNjBb7f\n0i+Wsj6vZBNm9jOzz4zx2dnnM/P5rFvHxYsXqVq1Kr6+vmRnZ/Pzzz9z7949/Pz8yMvLIyMjg9Wr\nV+Pi4kK3bt0q+hBEJSM1eaEqOtjYmjVrSEtLQ6/X06JFC1xdXQEYOnQo58+fZ/r06XTt2pVq1arx\n4MEDFixYQGhoKE5OThV5CP9qbzpYX7x4Qd++fdFoNGi1Wq5cuUKNGjWYMWMGbm5uLFmyhI0bN+Lg\n4ICNjQ35+flYWVmRkJCAhYWF3CYpykSSvChm/PjxHDlyhFq1apGenk6bNm0YNWoUrVu3BmDYsGFc\nuHCBQYMGce3aNQICAujbt28FR/3vphSZvm/v3r1s3ryZWbNm0bBhQ/744w+WLVtGXl4eM2bMwMfH\nh+PHj5OQkICNjQ3169dnxIgR6oxVUoMXZSFJXhjdX338+HFmzZpFREQE3t7e7Nu3j4ULF9KwYUNG\njhypJvqRI0dy+fJlCgoKWL16Ne7u7hV5CJVCYWEhgwcPxsrKiho1arBo0SL1vaIzVk2cOBF/f/8S\nt5fObFFWUpMX6k//2bNnc/XqVaysrBg2bBgajYamTZtSq1YtkpKSSE1NRavV0qBBA3r27Im3tzdj\nxox552PCmwqNRkOtWrVYsWIFFhYWBAQElDhjVXJycqWYsUpUDpLkhWr79u0kJiZiY2ND165dsbGx\nAcDFxUVN9Onp6VSvXh0nJyfq1KmDra1tBUdduTRq1Ahvb29Wr15daWesEpWLJPn3lMFgKNZ5161b\nN548ecL+/fupXbs2zs7O6miILi4uaLVaNmzYwJMnTwgICJDa8N/k6OiIl5cXERERVKlSxWgiEycn\nJzw8PBgwYIBcuYtyIUn+PVS0tpuamkpaWhqPHj1Cq9Xi5+dHVlYWsbGx1K5dmyZNmqiJ3tnZmcaN\nG9OjRw+jeUNF2VXWGatE5SOXYu+ZouPBT506lTNnznDjxg3s7OxwdXVl9uzZREZGoigKc+fOBaBn\nz55q7VhKCOWnXbt2xMbGMmrUKHJycggNDVUHggOkk1WUC7m75j0VGRnJoUOHGDduHA4ODly7do21\na9diYWHB0qVLadKkCdOnT2fPnj2EhYURGBioXmmK8nXgwAFWrVqlTmgiRHmSJP8eunPnDmFhYQwc\nOJA+ffqoj9inpqYyYcIEPvjgA3X42smTJ3P06FH27NnDhx9+WMGRm64399HLg06ivEnB7z3wZmyU\nN3Jzc0lNTcXGxkZ9QMfc3BxnZ2fGjx/P+fPn2b17NwALFy5kx44dkuDfMUnw4l2RmryJe7uTNScn\nh1evXmFubs7NmzeLtfP29sbc3JwHDx4Ar5NP7dq1KyT2940kePEuSJI3YUU7WadMmcLZs2e5ceMG\nn3zyCf7+/kRFReHm5mb0dOWjR4+oV68eDg4OFRW2EKIcSZI3YW9uv5szZw4nTpxgypQp1KxZk8zM\nTDw9PcnNzeWLL74gPDwcb29vnj9/zvr168nLy8PT07OCoxdClAdJ8iYuKyuLU6dOMWTIkGLD1I4d\nO5aCggIiIiKws7PD1tYWc3NzVqxYQd26dSsoYiFEeZIkb+IMBgO3b982qve+ecgmJyeHwsJCZs6c\niUajoWbNmri7u6uTcwshKj9J8iauSpUq2NnZkZKSoo42qdFoMDMzw9XVlT///JPBgwfLQ05CmCi5\nhdLE2dvbM2HCBPbt26dO0ffmqj43NxedTqc+5CSPTAhheuRK/j3QuXNngoODWbx4MXfv3qV79+6Y\nmZmRmJjIkydPaNy4MSC38AlhiuSJ1/dEXl4eCQkJLF68GEDtaF2yZAnNmjWr4OiEEO+KJPn3zK1b\nt0hLS8PW1hYnJycZTVIIEydJXgghTJh0vAohhAmTJC+EECZMkrwQQpgwSfJCCGHCJMkLIYQJkyQv\nhBAmTJK8+J98/fXX6PV6o5ebmxs+Pj4MHz6cY8eO/SMxeHh4lLr8V2VkZJRbTNu2bUOv15OSklJq\nm+joaPR6PVlZWWXa9989vtLo9XrCw8PLbX/i30WGNRDlYsGCBerfBoOBhw8fEh8fT3BwMGvXrsXb\n2/sfiyUwMJB27dqVaZuEhATmzZvHiRMn3lFUQlQMSfKiXPTs2bPYug4dOtCjRw9iYmKIjY39x2Lx\n8vLCy8urTNucOHGC/Pz8dxSREBVHyjXinXF2dsbFxYXTp09XdChCvLckyYt3ytzcnMLCQuD1uDl6\nvZ5169bRt29fPDw8mDx5MgAFBQXExMTQpUsX3N3d6dSpE0uXLqWgoMBof9evX2fMmDG0bNmSdu3a\n8dNPPxX7zJJq1levXiU0NBRfX198fX0JCQnhypUrAAwZMoTExERevnyJXq8nOjpa3S4pKYnevXvj\n6elJq1atmDZtGg8fPjTad05ODpGRkbRt2xYvLy+++eYbXr58+bfO19mzZxk7diwff/wxH330Ee3b\ntyc8PJxnz54Va3vs2DE+++wzPDw8+PTTT9m1a1exNpcuXSIkJIQWLVrg5eXFyJEjOX/+/N+KTVRO\nUq4R70xmZibXr1/Hzc3NaP2iRYvo1q0bvXr1QqvVAjB16lT27t1Lv3790Ov1nDt3jqVLl5KamqqO\nnJmVlcWgQYMwMzMjJCQERVFYtWrVf02oqampBAYGYmtry4gRI7C1tWXt2rUMGzaMxMRExowZg8Fg\n4MyZM3z33Xfo9XoANm7cSEREBAEBAfTp04fMzEzi4+M5deoUW7dupVq1aiiKwujRo0lJSSEoKIj6\n9euzY8cOkpKSyny+Ll26RFBQEDqdjtDQUCwtLUlOTmbTpk3k5eWxcOFCtW1BQQGjR4+mR48e9OvX\nj507d/LVV19hMBjU0tmFCxcICgrC0dGRsLAwCgoKSEhIICgoiPj4eNzd3csco6iEFCH+B1OnTlV0\nOp3y8OFD9XXnzh3l8OHDyueff67odDpl3759iqIoSkZGhqLT6ZTevXsb7SM5OVnR6XRKYmKi0fr4\n+HhFp9MpR48eVRRFUebNm6e4ubkpV69eVdukpaUpHh4eiru7u1FMRZfDwsKUFi1aKHfu3DHarlmz\nZkpUVFSJ2zx9+lRp3ry5Mm3aNKOYLl68qLi6uio//vijoiiKcuDAAUWn0ymbNm1S2zx//lzp0aOH\notPplNOnT5d67qKiohSdTqdkZmYqiqIo4eHhire3t/Ls2TOjdoGBgUqrVq2Mjk+n0ynR0dHquvz8\nfKVbt26Kn5+fUlhYqCiKogwcOFDp3r27kp+fr7bLyclRAgIClKCgIHWdTqdTvv3221LjFJWblGtE\nuWjdurX66tChAyNHjuT27duEh4fTpUsXo7YtW7Y0Wt6/fz8WFha0bduW7Oxs9eXv74+ZmRmHDh0C\n4Pfff6dFixY4Ozur2zZq1Og/3kljMBg4fPgwHTt2xMHBwWi7rVu3MnTo0BK3S05OJi8vj44dOxrF\npNVqcXFx4bffflNjsrS0pFevXuq21tbW9OnT56+duCIiIiJISkqiWrVq6rrs7GxsbW3Jy8szaqvR\naBg+fLi6XKVKFQIDA7l37x6XL18mOzubkydP4u/vT05Ojhp/fn4+/v7+nDx5kpycnDLHKCofKdeI\ncrFmzRr1bwsLC+zt7WnSpAnm5ubF2taoUcNo+ebNmxQUFJSarO/evQvA7du38fT0LPZ+48aNOXz4\ncInbPn78mLy8PJycnIq993YZ6e2YAEJDQ0t8v2bNmmpMderUoUqVKsViKiuNRkN2djYxMTFcunSJ\ntLQ09R76t/dfu3Ztoy8DgAYNGqgxvXr1CoDY2NhS72y6f/9+sX0I0yNJXpSLNm3a/OW2Go3xD0iD\nwYC9vT2LFi0qsX3RL4WS6u8Gg6HUz3rT6VtWb/Y5f/58td+gKAuL//+vU9Ktl8rfmKZh165dTJky\nhfr16+Pr60unTp1o3rw569evZ+/evUZt3z6HRT9To9Goxz1ixAj8/PxK/Ly6deuWOUZR+UiSFxXO\nwcGBo0eP4uXlhY2Njbo+Pz+fX3/9FUdHRwAcHR25ceNGse1v375d6r7t7e2xtrbm1q1bxd5bsGAB\nWq3WqOxRNCZ4fcX+9hfYwYMH1StgR0dHDh8+TE5OjtFVcUmf998sXrwYFxcXtmzZgpWVlbq+6N0+\nbzx8+JD8/Hyjdunp6QA0bNgQOzs7ACwtLYvFn5KSQm5ubrFfB8I0SU1eVLgOHTpQWFhYrKywYcMG\nJk6cyKlTpwDo1KkT586dM3oq9e7duxw8eLDUfVtYWNCmTRsOHDjAgwcP1PUZGRnExcWRnZ0NvL76\nLXr13bZtWywtLYmNjTX6NXDu3DnGjh3Lxo0bgdeTpBsMBuLi4tQ2r169YsuWLWU+D48fP8bR0dEo\ncV++fJnjx48X+0Xy8uVLdu7cqS6/ePGCTZs24eTkRNOmTalTpw6urq5s2bJFPUaAZ8+eMWHCBCIj\nI41+jQjTJf/KosJ16tQJPz8/oqOjSUtLw8fHh6tXr7Jx40a8vLzo3r07AKNGjWLXrl2MHj2a4cOH\nY2NjQ3x8PFWrViU3N7fU/U+aNIn+/fvTv39/BgwYgKWlJevWrcPe3l69iq9RowavXr1i+fLltGvX\nDk9PT8aNG8cPP/zA4MGD6d69O0+fPmXdunVUr16dsWPHAq/LVJ07dyYqKop79+6h0+nYvXs39+/f\nL/N58PPzY+/evcyZMwe9Xs/169fZvHkz8Lrs9OLFC6ytrQGwtbVl7ty5pKenU6dOHbZt28atW7dY\nsWIFZmZmAEyfPp3g4GD69OnDgAEDsLW1ZfPmzdy/f5/o6Gi1nTBtkuRFhTMzM2PZsmXExMSwa9cu\nkpKS0Gq1DBo0iC+//FItK9jZ2bFhwwbmz59PXFwcGo2Gfv36YWZmVuJDUW+4uLiwYcMGFi5cSExM\nDFZWVvj4+DBlyhS13h8YGMiRI0dYvnw59+/fx9PTk5CQELRaLXFxcXz//fdUq1YNHx8fJkyYoHZy\nwusyS3R0NNu3b2fnzp20b9+ewYMHM2nSpDKdh5kzZ2Jtbc0vv/zC1q1bqVevHsHBwTg7OzNu3DiO\nHTuGv78/ALVq1WLGjBnMmzePW7du4eLiwqpVq4w6r319fVm/fj1RUVGsXLkSMzMzdDodK1euLLVO\nL0yPTOQthBAmTGryQghhwiTJCyGECZMkL4QQJkySvBBCmDBJ8kIIYcIkyQshhAmTJC+EECZMkrwQ\nQpgwSfJCCGHC/g/3ZfoJJuAQXwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x22c83a654e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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45T9V7l39S2YJrl1X1YqrK7WcZNbl2zevq9x78kimeORfeG1JSs3k4askaqix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      "text/plain": [
       "<matplotlib.figure.Figure at 0x22c83c9a908>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plots_confusion_matrices(y_test, y_pred, label_encoder2.classes_); # function from functions.py"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The f1-score for the 3-class classification is quite bad. It classify well for the `helpful` example, but for `notHelpful` and `controversial` it's not very good. \n",
    "\n",
    "The accuracy for the `controversial` is only 16%.  \n",
    "Interpretation : We can think that a review can be only useful or not useful. But subjectively, it can differ from people, one person will consider the review as useful, but for the other guy it can be completely non-sense. And this is hard for our classifier to captures this notion of controversial from our features."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Grid search\n",
    "\n",
    "We tuned the parameters for our gradient boosting classifier through a grid search. You can see the details there [GridSearch for GBM](https://nbviewer.jupyter.org/github/Coac/epfl-ada/blob/master/Project/Helpful%20score%20prediction.ipynb#Grid-search-for-GBM). The elements used in training were the 1000 PC games. \n",
    "\n",
    "The f1-score result after the grid search were 0.59 f1-score"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusion\n",
    "\n",
    "Thanks to this deeper analysis, we were able to predict the helpful rate of the reviews. This prediction can perform very well if data is reduced to a smaller subset with high constraints (such as a high `helpfulCount`).\n",
    "\n",
    "The main limit to our analysis is that it was only done on a small subset of reviews (*video games*). Training the classifier takes a lot of time because it is required to process a lot of text. This brings difficulties to do cross validations and grid searches. A deeper analysis which could bring new insights could be done on a larger proportion of reviews, and may bring our classifier to give better results or to be more powerful when facing to specific kind of comments.\n",
    "\n",
    "It is also difficult to determine subjective contents of the reviews, bringing poor results for the controversial category.\n",
    "\n",
    "Finally, the usage of other, modern methods to do the text anlysis could allow to better understand the correlation between text contents and final results. Indeed, Word2Vec algorithm is creating features which are difficult to interpret."
   ]
  }
 ],
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