KeywordExtraction.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import re\n",
    "import spacy\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from spacy.lang.en import English\n",
    "from spacy.lang.en.stop_words import STOP_WORDS\n",
    "\n",
    "from gensim.parsing.preprocessing import strip_tags\n",
    "\n",
    "from collections import Counter\n",
    "from sklearn.decomposition import NMF, LatentDirichletAllocation\n",
    "from sklearn.feature_extraction.text import TfidfVectorizer, CountVectorizer\n",
    "\n",
    "try:\n",
    "    import en_core_web_lg\n",
    "    nlp = en_core_web_lg.load()\n",
    "    tokenizer = nlp.tokenizer\n",
    "    tokenizer_tags = nlp\n",
    "    # tokenizer_light = nlp.tokenizer\n",
    "except ImportError:\n",
    "    print('Using default tokenizer')\n",
    "    nlp = English()\n",
    "    tokenizer = nlp.Defaults.create_tokenizer(nlp)\n",
    "    \n",
    "stop_words = STOP_WORDS"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Utils"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def token_spacy(input_text: str):\n",
    "    text = input_text.lower()\n",
    "    text = re.sub(r\"[^A-z]\", \" \", text)\n",
    "    \n",
    "    spacy_tokens = tokenizer(text)\n",
    "    tokens = [token.lemma_.strip() for token in spacy_tokens \n",
    "                    if (len(token.lemma_.strip()) > 1) and not token.lemma_.strip() in stop_words]\n",
    "    \n",
    "    return tokens\n",
    "\n",
    "\n",
    "def token_spacy_v2(input_text: str):\n",
    "    text = strip_tags(input_text.lower())\n",
    "    text = re.sub(r\"[^A-z('t|s)0-9]\", \" \", text)\n",
    "    \n",
    "    spacy_tokens = tokenizer(text)\n",
    "    tokens = []\n",
    "    for token in spacy_tokens:\n",
    "        token_lemma = token.lemma_.strip().replace(u'\\ufeff', '')\n",
    "\n",
    "        if (len(token_lemma) > 1) and not token_lemma in stop_words:\n",
    "            if token_lemma == '-PRON-':\n",
    "                tokens.append(token.text)\n",
    "            else:\n",
    "                tokens.append(token_lemma)\n",
    "    \n",
    "    return tokens\n",
    "\n",
    "\n",
    "def clear_title(text: str):\n",
    "    return re.sub('([0-9]{1,} people found this helpful. Was this review helpful to you Yes No)', '', text)\n",
    "\n",
    "\n",
    "def sort_n_gram(docs_vectors: list, features: list):\n",
    "    sum_words = np.array(docs_vectors.sum(axis=0))[0]\n",
    "    \n",
    "    sorted_indexes = np.argsort(sum_words)[::-1]\n",
    "    features_names = np.array(features)\n",
    "     \n",
    "    return np.column_stack((features_names[sorted_indexes], sum_words[sorted_indexes]))\n",
    "\n",
    "\n",
    "def get_top_n_gram(corpus: np.ndarray, ngram_range: tuple=(2, 3), max_features: int=2000, n: int=20):\n",
    "    vectorizer = TfidfVectorizer(ngram_range=ngram_range, max_features=max_features, tokenizer=token_spacy)\n",
    "    docs_vectors = vectorizer.fit_transform(corpus)\n",
    "     \n",
    "    return sort_n_gram(docs_vectors, vectorizer.get_feature_names())[:n], vectorizer\n",
    "\n",
    "\n",
    "def build_n_gram(vectorizer, corpus: str, n: int=20):\n",
    "    docs_vectors = vectorizer.transform(corpus)\n",
    "    return sort_n_gram(docs_vectors, vectorizer.get_feature_names())[:n]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Read data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_path = 'data'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/work/apps/amazon_reviews_analyzer/lib/python3.7/site-packages/IPython/core/interactiveshell.py:3146: DtypeWarning: Columns (1,10) have mixed types.Specify dtype option on import or set low_memory=False.\n",
      "  interactivity=interactivity, compiler=compiler, result=result)\n"
     ]
    },
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>name</th>\n",
       "      <th>asins</th>\n",
       "      <th>brand</th>\n",
       "      <th>categories</th>\n",
       "      <th>keys</th>\n",
       "      <th>manufacturer</th>\n",
       "      <th>reviews.date</th>\n",
       "      <th>reviews.dateAdded</th>\n",
       "      <th>reviews.dateSeen</th>\n",
       "      <th>...</th>\n",
       "      <th>reviews.doRecommend</th>\n",
       "      <th>reviews.id</th>\n",
       "      <th>reviews.numHelpful</th>\n",
       "      <th>reviews.rating</th>\n",
       "      <th>reviews.sourceURLs</th>\n",
       "      <th>reviews.text</th>\n",
       "      <th>reviews.title</th>\n",
       "      <th>reviews.userCity</th>\n",
       "      <th>reviews.userProvince</th>\n",
       "      <th>reviews.username</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AVqkIhwDv8e3D1O-lebb</td>\n",
       "      <td>All-New Fire HD 8 Tablet, 8 HD Display, Wi-Fi,...</td>\n",
       "      <td>B01AHB9CN2</td>\n",
       "      <td>Amazon</td>\n",
       "      <td>Electronics,iPad &amp; Tablets,All Tablets,Fire Ta...</td>\n",
       "      <td>841667104676,amazon/53004484,amazon/b01ahb9cn2...</td>\n",
       "      <td>Amazon</td>\n",
       "      <td>2017-01-13T00:00:00.000Z</td>\n",
       "      <td>2017-07-03T23:33:15Z</td>\n",
       "      <td>2017-06-07T09:04:00.000Z,2017-04-30T00:45:00.000Z</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>http://reviews.bestbuy.com/3545/5620406/review...</td>\n",
       "      <td>This product so far has not disappointed. My c...</td>\n",
       "      <td>Kindle</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Adapter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AVqkIhwDv8e3D1O-lebb</td>\n",
       "      <td>All-New Fire HD 8 Tablet, 8 HD Display, Wi-Fi,...</td>\n",
       "      <td>B01AHB9CN2</td>\n",
       "      <td>Amazon</td>\n",
       "      <td>Electronics,iPad &amp; Tablets,All Tablets,Fire Ta...</td>\n",
       "      <td>841667104676,amazon/53004484,amazon/b01ahb9cn2...</td>\n",
       "      <td>Amazon</td>\n",
       "      <td>2017-01-13T00:00:00.000Z</td>\n",
       "      <td>2017-07-03T23:33:15Z</td>\n",
       "      <td>2017-06-07T09:04:00.000Z,2017-04-30T00:45:00.000Z</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>http://reviews.bestbuy.com/3545/5620406/review...</td>\n",
       "      <td>great for beginner or experienced person. Boug...</td>\n",
       "      <td>very fast</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>truman</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AVqkIhwDv8e3D1O-lebb</td>\n",
       "      <td>All-New Fire HD 8 Tablet, 8 HD Display, Wi-Fi,...</td>\n",
       "      <td>B01AHB9CN2</td>\n",
       "      <td>Amazon</td>\n",
       "      <td>Electronics,iPad &amp; Tablets,All Tablets,Fire Ta...</td>\n",
       "      <td>841667104676,amazon/53004484,amazon/b01ahb9cn2...</td>\n",
       "      <td>Amazon</td>\n",
       "      <td>2017-01-13T00:00:00.000Z</td>\n",
       "      <td>2017-07-03T23:33:15Z</td>\n",
       "      <td>2017-06-07T09:04:00.000Z,2017-04-30T00:45:00.000Z</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>http://reviews.bestbuy.com/3545/5620406/review...</td>\n",
       "      <td>Inexpensive tablet for him to use and learn on...</td>\n",
       "      <td>Beginner tablet for our 9 year old son.</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DaveZ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AVqkIhwDv8e3D1O-lebb</td>\n",
       "      <td>All-New Fire HD 8 Tablet, 8 HD Display, Wi-Fi,...</td>\n",
       "      <td>B01AHB9CN2</td>\n",
       "      <td>Amazon</td>\n",
       "      <td>Electronics,iPad &amp; Tablets,All Tablets,Fire Ta...</td>\n",
       "      <td>841667104676,amazon/53004484,amazon/b01ahb9cn2...</td>\n",
       "      <td>Amazon</td>\n",
       "      <td>2017-01-13T00:00:00.000Z</td>\n",
       "      <td>2017-07-03T23:33:15Z</td>\n",
       "      <td>2017-06-07T09:04:00.000Z,2017-04-30T00:45:00.000Z</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>http://reviews.bestbuy.com/3545/5620406/review...</td>\n",
       "      <td>I've had my Fire HD 8 two weeks now and I love...</td>\n",
       "      <td>Good!!!</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Shacks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AVqkIhwDv8e3D1O-lebb</td>\n",
       "      <td>All-New Fire HD 8 Tablet, 8 HD Display, Wi-Fi,...</td>\n",
       "      <td>B01AHB9CN2</td>\n",
       "      <td>Amazon</td>\n",
       "      <td>Electronics,iPad &amp; Tablets,All Tablets,Fire Ta...</td>\n",
       "      <td>841667104676,amazon/53004484,amazon/b01ahb9cn2...</td>\n",
       "      <td>Amazon</td>\n",
       "      <td>2017-01-12T00:00:00.000Z</td>\n",
       "      <td>2017-07-03T23:33:15Z</td>\n",
       "      <td>2017-06-07T09:04:00.000Z,2017-04-30T00:45:00.000Z</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>http://reviews.bestbuy.com/3545/5620406/review...</td>\n",
       "      <td>I bought this for my grand daughter when she c...</td>\n",
       "      <td>Fantastic Tablet for kids</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>explore42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34655</th>\n",
       "      <td>AVpfiBlyLJeJML43-4Tp</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B006GWO5WK</td>\n",
       "      <td>Amazon</td>\n",
       "      <td>Computers/Tablets &amp; Networking,Tablet &amp; eBook ...</td>\n",
       "      <td>newamazonkindlefirehd9wpowerfastadaptercharger...</td>\n",
       "      <td>Amazon Digital Services, Inc</td>\n",
       "      <td>2012-09-18T00:00:00Z</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-08-29T00:00:00Z</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>http://www.amazon.com/Amazon-PowerFast-Adapter...</td>\n",
       "      <td>This is not appreciably faster than any other ...</td>\n",
       "      <td>Not appreciably faster than any other 1.8A cha...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Kris</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34656</th>\n",
       "      <td>AVpfiBlyLJeJML43-4Tp</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B006GWO5WK</td>\n",
       "      <td>Amazon</td>\n",
       "      <td>Computers/Tablets &amp; Networking,Tablet &amp; eBook ...</td>\n",
       "      <td>newamazonkindlefirehd9wpowerfastadaptercharger...</td>\n",
       "      <td>Amazon Digital Services, Inc</td>\n",
       "      <td>2012-11-21T00:00:00Z</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-09-02T00:00:00Z</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>http://www.amazon.com/Amazon-PowerFast-Adapter...</td>\n",
       "      <td>Amazon should include this charger with the Ki...</td>\n",
       "      <td>Should be included</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Jonathan Stewart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34657</th>\n",
       "      <td>AVpfiBlyLJeJML43-4Tp</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B006GWO5WK</td>\n",
       "      <td>Amazon</td>\n",
       "      <td>Computers/Tablets &amp; Networking,Tablet &amp; eBook ...</td>\n",
       "      <td>newamazonkindlefirehd9wpowerfastadaptercharger...</td>\n",
       "      <td>Amazon Digital Services, Inc</td>\n",
       "      <td>2012-10-19T00:00:00Z</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-09-04T00:00:00Z</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>http://www.amazon.com/Amazon-PowerFast-Adapter...</td>\n",
       "      <td>Love my Kindle Fire but I am really disappoint...</td>\n",
       "      <td>Disappointing Charger</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>J Lawson</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34658</th>\n",
       "      <td>AVpfiBlyLJeJML43-4Tp</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B006GWO5WK</td>\n",
       "      <td>Amazon</td>\n",
       "      <td>Computers/Tablets &amp; Networking,Tablet &amp; eBook ...</td>\n",
       "      <td>newamazonkindlefirehd9wpowerfastadaptercharger...</td>\n",
       "      <td>Amazon Digital Services, Inc</td>\n",
       "      <td>2012-10-31T00:00:00Z</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-09-01T00:00:00Z</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>http://www.amazon.com/Amazon-PowerFast-Adapter...</td>\n",
       "      <td>I was surprised to find it did not come with a...</td>\n",
       "      <td>Not worth the money</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Just the Buyer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34659</th>\n",
       "      <td>AVpfiBlyLJeJML43-4Tp</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B006GWO5WK</td>\n",
       "      <td>Amazon</td>\n",
       "      <td>Computers/Tablets &amp; Networking,Tablet &amp; eBook ...</td>\n",
       "      <td>newamazonkindlefirehd9wpowerfastadaptercharger...</td>\n",
       "      <td>Amazon Digital Services, Inc</td>\n",
       "      <td>2012-12-23T00:00:00Z</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-01T00:00:00Z</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>http://www.amazon.com/Amazon-PowerFast-Adapter...</td>\n",
       "      <td>to spite the fact that i have nothing but good...</td>\n",
       "      <td>as with everyone else</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sandi</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>34660 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                         id  \\\n",
       "0      AVqkIhwDv8e3D1O-lebb   \n",
       "1      AVqkIhwDv8e3D1O-lebb   \n",
       "2      AVqkIhwDv8e3D1O-lebb   \n",
       "3      AVqkIhwDv8e3D1O-lebb   \n",
       "4      AVqkIhwDv8e3D1O-lebb   \n",
       "...                     ...   \n",
       "34655  AVpfiBlyLJeJML43-4Tp   \n",
       "34656  AVpfiBlyLJeJML43-4Tp   \n",
       "34657  AVpfiBlyLJeJML43-4Tp   \n",
       "34658  AVpfiBlyLJeJML43-4Tp   \n",
       "34659  AVpfiBlyLJeJML43-4Tp   \n",
       "\n",
       "                                                    name       asins   brand  \\\n",
       "0      All-New Fire HD 8 Tablet, 8 HD Display, Wi-Fi,...  B01AHB9CN2  Amazon   \n",
       "1      All-New Fire HD 8 Tablet, 8 HD Display, Wi-Fi,...  B01AHB9CN2  Amazon   \n",
       "2      All-New Fire HD 8 Tablet, 8 HD Display, Wi-Fi,...  B01AHB9CN2  Amazon   \n",
       "3      All-New Fire HD 8 Tablet, 8 HD Display, Wi-Fi,...  B01AHB9CN2  Amazon   \n",
       "4      All-New Fire HD 8 Tablet, 8 HD Display, Wi-Fi,...  B01AHB9CN2  Amazon   \n",
       "...                                                  ...         ...     ...   \n",
       "34655                                                NaN  B006GWO5WK  Amazon   \n",
       "34656                                                NaN  B006GWO5WK  Amazon   \n",
       "34657                                                NaN  B006GWO5WK  Amazon   \n",
       "34658                                                NaN  B006GWO5WK  Amazon   \n",
       "34659                                                NaN  B006GWO5WK  Amazon   \n",
       "\n",
       "                                              categories  \\\n",
       "0      Electronics,iPad & Tablets,All Tablets,Fire Ta...   \n",
       "1      Electronics,iPad & Tablets,All Tablets,Fire Ta...   \n",
       "2      Electronics,iPad & Tablets,All Tablets,Fire Ta...   \n",
       "3      Electronics,iPad & Tablets,All Tablets,Fire Ta...   \n",
       "4      Electronics,iPad & Tablets,All Tablets,Fire Ta...   \n",
       "...                                                  ...   \n",
       "34655  Computers/Tablets & Networking,Tablet & eBook ...   \n",
       "34656  Computers/Tablets & Networking,Tablet & eBook ...   \n",
       "34657  Computers/Tablets & Networking,Tablet & eBook ...   \n",
       "34658  Computers/Tablets & Networking,Tablet & eBook ...   \n",
       "34659  Computers/Tablets & Networking,Tablet & eBook ...   \n",
       "\n",
       "                                                    keys  \\\n",
       "0      841667104676,amazon/53004484,amazon/b01ahb9cn2...   \n",
       "1      841667104676,amazon/53004484,amazon/b01ahb9cn2...   \n",
       "2      841667104676,amazon/53004484,amazon/b01ahb9cn2...   \n",
       "3      841667104676,amazon/53004484,amazon/b01ahb9cn2...   \n",
       "4      841667104676,amazon/53004484,amazon/b01ahb9cn2...   \n",
       "...                                                  ...   \n",
       "34655  newamazonkindlefirehd9wpowerfastadaptercharger...   \n",
       "34656  newamazonkindlefirehd9wpowerfastadaptercharger...   \n",
       "34657  newamazonkindlefirehd9wpowerfastadaptercharger...   \n",
       "34658  newamazonkindlefirehd9wpowerfastadaptercharger...   \n",
       "34659  newamazonkindlefirehd9wpowerfastadaptercharger...   \n",
       "\n",
       "                       manufacturer              reviews.date  \\\n",
       "0                            Amazon  2017-01-13T00:00:00.000Z   \n",
       "1                            Amazon  2017-01-13T00:00:00.000Z   \n",
       "2                            Amazon  2017-01-13T00:00:00.000Z   \n",
       "3                            Amazon  2017-01-13T00:00:00.000Z   \n",
       "4                            Amazon  2017-01-12T00:00:00.000Z   \n",
       "...                             ...                       ...   \n",
       "34655  Amazon Digital Services, Inc      2012-09-18T00:00:00Z   \n",
       "34656  Amazon Digital Services, Inc      2012-11-21T00:00:00Z   \n",
       "34657  Amazon Digital Services, Inc      2012-10-19T00:00:00Z   \n",
       "34658  Amazon Digital Services, Inc      2012-10-31T00:00:00Z   \n",
       "34659  Amazon Digital Services, Inc      2012-12-23T00:00:00Z   \n",
       "\n",
       "          reviews.dateAdded  \\\n",
       "0      2017-07-03T23:33:15Z   \n",
       "1      2017-07-03T23:33:15Z   \n",
       "2      2017-07-03T23:33:15Z   \n",
       "3      2017-07-03T23:33:15Z   \n",
       "4      2017-07-03T23:33:15Z   \n",
       "...                     ...   \n",
       "34655                   NaN   \n",
       "34656                   NaN   \n",
       "34657                   NaN   \n",
       "34658                   NaN   \n",
       "34659                   NaN   \n",
       "\n",
       "                                        reviews.dateSeen  ...  \\\n",
       "0      2017-06-07T09:04:00.000Z,2017-04-30T00:45:00.000Z  ...   \n",
       "1      2017-06-07T09:04:00.000Z,2017-04-30T00:45:00.000Z  ...   \n",
       "2      2017-06-07T09:04:00.000Z,2017-04-30T00:45:00.000Z  ...   \n",
       "3      2017-06-07T09:04:00.000Z,2017-04-30T00:45:00.000Z  ...   \n",
       "4      2017-06-07T09:04:00.000Z,2017-04-30T00:45:00.000Z  ...   \n",
       "...                                                  ...  ...   \n",
       "34655                               2015-08-29T00:00:00Z  ...   \n",
       "34656                               2015-09-02T00:00:00Z  ...   \n",
       "34657                               2015-09-04T00:00:00Z  ...   \n",
       "34658                               2015-09-01T00:00:00Z  ...   \n",
       "34659                               2015-11-01T00:00:00Z  ...   \n",
       "\n",
       "      reviews.doRecommend reviews.id  reviews.numHelpful  reviews.rating  \\\n",
       "0                    True        NaN                 0.0             5.0   \n",
       "1                    True        NaN                 0.0             5.0   \n",
       "2                    True        NaN                 0.0             5.0   \n",
       "3                    True        NaN                 0.0             4.0   \n",
       "4                    True        NaN                 0.0             5.0   \n",
       "...                   ...        ...                 ...             ...   \n",
       "34655                 NaN        NaN                 NaN             3.0   \n",
       "34656                 NaN        NaN                 NaN             1.0   \n",
       "34657                 NaN        NaN                 NaN             1.0   \n",
       "34658                 NaN        NaN                 NaN             1.0   \n",
       "34659                 NaN        NaN                 NaN             1.0   \n",
       "\n",
       "                                      reviews.sourceURLs  \\\n",
       "0      http://reviews.bestbuy.com/3545/5620406/review...   \n",
       "1      http://reviews.bestbuy.com/3545/5620406/review...   \n",
       "2      http://reviews.bestbuy.com/3545/5620406/review...   \n",
       "3      http://reviews.bestbuy.com/3545/5620406/review...   \n",
       "4      http://reviews.bestbuy.com/3545/5620406/review...   \n",
       "...                                                  ...   \n",
       "34655  http://www.amazon.com/Amazon-PowerFast-Adapter...   \n",
       "34656  http://www.amazon.com/Amazon-PowerFast-Adapter...   \n",
       "34657  http://www.amazon.com/Amazon-PowerFast-Adapter...   \n",
       "34658  http://www.amazon.com/Amazon-PowerFast-Adapter...   \n",
       "34659  http://www.amazon.com/Amazon-PowerFast-Adapter...   \n",
       "\n",
       "                                            reviews.text  \\\n",
       "0      This product so far has not disappointed. My c...   \n",
       "1      great for beginner or experienced person. Boug...   \n",
       "2      Inexpensive tablet for him to use and learn on...   \n",
       "3      I've had my Fire HD 8 two weeks now and I love...   \n",
       "4      I bought this for my grand daughter when she c...   \n",
       "...                                                  ...   \n",
       "34655  This is not appreciably faster than any other ...   \n",
       "34656  Amazon should include this charger with the Ki...   \n",
       "34657  Love my Kindle Fire but I am really disappoint...   \n",
       "34658  I was surprised to find it did not come with a...   \n",
       "34659  to spite the fact that i have nothing but good...   \n",
       "\n",
       "                                           reviews.title reviews.userCity  \\\n",
       "0                                                 Kindle              NaN   \n",
       "1                                              very fast              NaN   \n",
       "2                Beginner tablet for our 9 year old son.              NaN   \n",
       "3                                                Good!!!              NaN   \n",
       "4                              Fantastic Tablet for kids              NaN   \n",
       "...                                                  ...              ...   \n",
       "34655  Not appreciably faster than any other 1.8A cha...              NaN   \n",
       "34656                                 Should be included              NaN   \n",
       "34657                              Disappointing Charger              NaN   \n",
       "34658                                Not worth the money              NaN   \n",
       "34659                              as with everyone else              NaN   \n",
       "\n",
       "       reviews.userProvince  reviews.username  \n",
       "0                       NaN           Adapter  \n",
       "1                       NaN            truman  \n",
       "2                       NaN             DaveZ  \n",
       "3                       NaN            Shacks  \n",
       "4                       NaN         explore42  \n",
       "...                     ...               ...  \n",
       "34655                   NaN              Kris  \n",
       "34656                   NaN  Jonathan Stewart  \n",
       "34657                   NaN          J Lawson  \n",
       "34658                   NaN    Just the Buyer  \n",
       "34659                   NaN             sandi  \n",
       "\n",
       "[34660 rows x 21 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reviews_df = pd.read_csv(os.path.join(data_path, '1429_1.csv'))\n",
    "reviews_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# EDA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tabular data analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                      34660\n",
       "name                    27900\n",
       "asins                   34658\n",
       "brand                   34660\n",
       "categories              34660\n",
       "keys                    34660\n",
       "manufacturer            34660\n",
       "reviews.date            34621\n",
       "reviews.dateAdded       24039\n",
       "reviews.dateSeen        34660\n",
       "reviews.didPurchase         1\n",
       "reviews.doRecommend     34066\n",
       "reviews.id                  1\n",
       "reviews.numHelpful      34131\n",
       "reviews.rating          34627\n",
       "reviews.sourceURLs      34660\n",
       "reviews.text            34659\n",
       "reviews.title           34655\n",
       "reviews.userCity            0\n",
       "reviews.userProvince        0\n",
       "reviews.username        34658\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reviews_df.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1728x1008 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "review_counts = reviews_df.asins.value_counts()\n",
    "\n",
    "f, ax = plt.subplots(1,1,figsize=(24, 14))\n",
    "\n",
    "ax.set_title('Reviews per product ID', {'fontsize': 25})\n",
    "\n",
    "sns.barplot(x=review_counts.index, y=review_counts, ax=ax)\n",
    "plt.setp(ax.get_xticklabels(), rotation=70);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Text analysis\n",
    "exploring texts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SUMMARY: Kindle\n",
      "TEXT: This product so far has not disappointed. My children love to use it and I like the ability to monitor control what content they see with ease.\n",
      "\n",
      "SUMMARY: very fast\n",
      "TEXT: great for beginner or experienced person. Bought as a gift and she loves it\n",
      "\n",
      "SUMMARY: Beginner tablet for our 9 year old son.\n",
      "TEXT: Inexpensive tablet for him to use and learn on, step up from the NABI. He was thrilled with it, learn how to Skype on it already...\n",
      "\n",
      "SUMMARY: Good!!!\n",
      "TEXT: I've had my Fire HD 8 two weeks now and I love it. This tablet is a great value.We are Prime Members and that is where this tablet SHINES. I love being able to easily access all of the Prime content as well as movies you can download and watch laterThis has a 1280/800 screen which has some really nice look to it its nice and crisp and very bright infact it is brighter then the ipad pro costing $900 base model. The build on this fire is INSANELY AWESOME running at only 7.7mm thick and the smooth glossy feel on the back it is really amazing to hold its like the futuristic tab in ur hands.\n",
      "\n",
      "SUMMARY: Fantastic Tablet for kids\n",
      "TEXT: I bought this for my grand daughter when she comes over to visit. I set it up with her as the user, entered her age and name and now Amazon makes sure that she only accesses sites and content that are appropriate to her age. Simple to do and she loves the capabilities. I also bought and installed a 64gig SD card which gives this little tablet plenty of storage. For the price I think this tablet is best one out there. You can spend hundreds of dollars more for additional speed and capacity but when it comes to the basics this tablets does everything that most people will ever need at a fraction of the cost.\n",
      "\n",
      "SUMMARY: Just what we expected\n",
      "TEXT: This amazon fire 8 inch tablet is the perfect size. I purchased it for my husband so that he has a bigger screen than just his phone. He had gotten me one a few years ago so I knew it would be a good purchase.\n",
      "\n",
      "SUMMARY: great e-reader tablet\n",
      "TEXT: Great for e-reading on the go, nice and light weight, and for the price point given, definitely worth the purchase.\n",
      "\n",
      "SUMMARY: Great for gifts\n",
      "TEXT: I gave this as a Christmas gift to my inlaws, husband and uncle. They loved it and how easy they are to use with fantastic features!\n",
      "\n",
      "SUMMARY: Great for reading\n",
      "TEXT: Great as a device to read books. I like that it links with my borrowed library e-books. Switched from another popular tablet brand and I am happy with the choice I made. It took some time to get books from my previous non-Kindle reader, but finally figured out a way!\n",
      "\n",
      "SUMMARY: Great and lightweight reader\n",
      "TEXT: I love ordering books and reading them with the reader.\n",
      "\n",
      "SUMMARY: nice tablet for the price\n",
      "TEXT: Not easy for elderly users cease of ads that pop up.\n",
      "\n",
      "SUMMARY: Excellent product\n",
      "TEXT: Excellent product. Easy to use, large screen makes watching movies and reading easier.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "for ind, row in reviews_df.iterrows():\n",
    "    print('SUMMARY:',row['reviews.title'])\n",
    "    print('TEXT:', row['reviews.text'] + '\\n')\n",
    "\n",
    "    if ind > 10:\n",
    "        break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Unique titles: 19767\n"
     ]
    }
   ],
   "source": [
    "print('Unique titles:', np.unique(reviews_df['reviews.title'].dropna()).shape[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Clear scrapped titles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Ships With All Current Kindle Fires... 556 people found this helpful. Was this review helpful to you Yes No'"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remove this from reviews titles\n",
    "# 556 people found this helpful. Was this review helpful to you Yes No.\n",
    "# 53 people found this helpful. Was this review helpful to you Yes No.\n",
    "# 88 people found this helpful. Was this review helpful to you Yes No.\n",
    "\n",
    "reviews_df[reviews_df.asins == 'B006GWO5NE']['reviews.title'].values[2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "reviews_df = reviews_df[reviews_df['reviews.title'].notnull() & reviews_df['reviews.text'].notnull()].copy()\n",
    "reviews_df['reviews.title'] = reviews_df['reviews.title'].apply(clear_title)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Combining title with main text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "reviews_df['all_text'] = reviews_df['reviews.title'] + '. ' + reviews_df['reviews.text']\n",
    "reviews_df = reviews_df[reviews_df.all_text.notnull()]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plotting reviews length"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Longest review: 10724.\n",
      "Shortest review: 12.\n",
      "Mean of reviews: 180.0941016910025\n"
     ]
    }
   ],
   "source": [
    "texts_lengths = reviews_df['all_text'].dropna().apply(len)\n",
    "print(\n",
    "    f'Longest review: {texts_lengths.max()}.', \n",
    "    f'Shortest review: {texts_lengths.min()}.',\n",
    "    f'Mean of reviews: {texts_lengths.mean()}',\n",
    "    sep='\\n'\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1728x1008 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots(1,1,figsize=(24, 14))\n",
    "\n",
    "ax.set_title('Lengths of reviews', {'fontsize': 25})\n",
    "sns.histplot(texts_lengths, kde=False, bins=5, ax=ax);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1728x1008 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots(1,1,figsize=(24, 14))\n",
    "\n",
    "ax.set_title('Lengths of reviews < 1000', {'fontsize': 25})\n",
    "sns.histplot(texts_lengths[texts_lengths < 1000], kde=False, bins=5, ax=ax);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1728x1008 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "words_counter = Counter(token_spacy(' '.join(reviews_df['all_text'].dropna())))\n",
    "top_words = np.array(tuple(words_counter.most_common(20)))\n",
    "\n",
    "f, ax = plt.subplots(1, 1, figsize=(24, 14))\n",
    "\n",
    "ax.set_title('Words counter in corpus', {'fontsize': 25})\n",
    "sns.barplot(x=top_words[:, 0], y=top_words[:, 1].astype('int'), ax=ax)\n",
    "plt.setp(ax.get_xticklabels(), rotation=45, fontsize=18);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "top_n_grams, vectorizer = get_top_n_gram(reviews_df.all_text.dropna(), n=20)\n",
    "top_n_grams_df = pd.DataFrame(top_n_grams)\n",
    "top_n_grams_df.columns=[\"bi_gram\", \"freq\"]\n",
    "top_n_grams_df.freq = top_n_grams_df.freq.astype(np.float16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1728x1008 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots(1,1,figsize=(24, 14))\n",
    "\n",
    "ax.set_title('Top n grams in corpus', {'fontsize': 25})\n",
    "sns.barplot(x=\"bi_gram\", y=\"freq\", data=top_n_grams_df, ax=ax)\n",
    "plt.setp(ax.get_xticklabels(), rotation=45, fontsize=18);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Build keyphrases for each product"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/work/apps/amazon_reviews_analyzer/lib/python3.7/site-packages/sklearn/feature_extraction/text.py:484: UserWarning: The parameter 'token_pattern' will not be used since 'tokenizer' is not None'\n",
      "  warnings.warn(\"The parameter 'token_pattern' will not be used\"\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "TfidfVectorizer(max_features=2000, ngram_range=(2, 3),\n",
       "                tokenizer=<function token_spacy_v2 at 0x7f491ef55ef0>)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vectorizer = TfidfVectorizer(ngram_range=(2, 3), max_features=2000, tokenizer=token_spacy_v2)\n",
    "vectorizer.fit(reviews_df.all_text);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "products_keyphrases_df = []\n",
    "\n",
    "for ind, product_group in reviews_df.groupby('asins'):\n",
    "    top_n_grams = build_n_gram(vectorizer=vectorizer, corpus=product_group.all_text, n=20)\n",
    "    products_keyphrases_df.append({'asin': ind, 'keyphrases': top_n_grams[:,0],'raw_keyphrases': top_n_grams})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>asin</th>\n",
       "      <th>keyphrases</th>\n",
       "      <th>raw_keyphrases</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>B002Y27P3M</td>\n",
       "      <td>[page turn, new kindle, kindle keyboard, use k...</td>\n",
       "      <td>[[page turn, 2.34234933075354], [new kindle, 1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>B002Y27P6Y</td>\n",
       "      <td>[kindle read, kindle work, it easy, work great...</td>\n",
       "      <td>[[kindle read, 1.2621111430206566], [kindle wo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>B005PB2T0S</td>\n",
       "      <td>[kindle keyboard, new kindle, feel like, kindl...</td>\n",
       "      <td>[[kindle keyboard, 1.7086062596953622], [new k...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>B005PB2T2Q</td>\n",
       "      <td>[kindle touch, kindle keyboard, doe it, look l...</td>\n",
       "      <td>[[kindle touch, 1.1339104523521293], [kindle k...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>B006GWO5NE</td>\n",
       "      <td>[kindle fire, need new, kindle fire hd, good k...</td>\n",
       "      <td>[[kindle fire, 1.9297370597577206], [need new,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>B006GWO5WK</td>\n",
       "      <td>[charge kindle, kindle fire, purchase kindle, ...</td>\n",
       "      <td>[[charge kindle, 2.329915134188034], [kindle f...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>B0083Q04TA</td>\n",
       "      <td>[kindle fire, fire hd, year old, kindle keyboa...</td>\n",
       "      <td>[[kindle fire, 1.6981013491860775], [fire hd, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>B00BFJAHF8</td>\n",
       "      <td>[great doe, yr old, good work good, good start...</td>\n",
       "      <td>[[great doe, 1.0], [yr old, 0.0], [good work g...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>B00DU15MU4</td>\n",
       "      <td>[apple tv, easy find, prime movie, i try, amaz...</td>\n",
       "      <td>[[apple tv, 1.6966821556118379], [easy find, 1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>B00IOY8XWQ</td>\n",
       "      <td>[kindle voyage, page turn, great reader, turn ...</td>\n",
       "      <td>[[kindle voyage, 33.678076383063065], [page tu...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>B00IOYAM4I</td>\n",
       "      <td>[kindle voyage, small size, read sunlight, eas...</td>\n",
       "      <td>[[kindle voyage, 2.5620479153303113], [small s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>B00L9EPT8O,B01E6AO69U</td>\n",
       "      <td>[amazon echo, play music, great product, love ...</td>\n",
       "      <td>[[amazon echo, 224.46499785606383], [play musi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>B00LO29KXQ</td>\n",
       "      <td>[fire tv stick, tv stick, fire tv, amazon prim...</td>\n",
       "      <td>[[fire tv stick, 0.9408076339985175], [tv stic...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>B00LW9XOJM</td>\n",
       "      <td>[kindle love, look good, protective case, it h...</td>\n",
       "      <td>[[kindle love, 1.3771673715708075], [look good...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>B00OQVZDJM</td>\n",
       "      <td>[kindle paperwhite, easy read, great reader, l...</td>\n",
       "      <td>[[kindle paperwhite, 118.54757979138726], [eas...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>B00QFQRELG</td>\n",
       "      <td>[charge kindle, charger work, kindle fire, wor...</td>\n",
       "      <td>[[charge kindle, 9.567602583436267], [charger ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>B00QJDU3KY</td>\n",
       "      <td>[new kindle, kindle paperwhite, book amazon, r...</td>\n",
       "      <td>[[new kindle, 1.7620474903082095], [kindle pap...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>B00QL1ZN3G</td>\n",
       "      <td>[kindle purchase, charge kindle, recommend kin...</td>\n",
       "      <td>[[kindle purchase, 1.8874901394146284], [charg...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>B00REQKWGA</td>\n",
       "      <td>[like buy, love small, great travel, good gift...</td>\n",
       "      <td>[[like buy, 1.0886788044160025], [love small, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>B00TSUGXKE</td>\n",
       "      <td>[great tablet, good tablet, easy use, year old...</td>\n",
       "      <td>[[great tablet, 13.248887547665554], [good tab...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>B00U3FPN4U</td>\n",
       "      <td>[fire tv, fire stick, great product, amazon fi...</td>\n",
       "      <td>[[fire tv, 403.2804348717742], [fire stick, 21...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>B00UH4D8G2</td>\n",
       "      <td>[fire tv, fire tv box, tv box, apple tv, amazo...</td>\n",
       "      <td>[[fire tv, 1.4170755643005697], [fire tv box, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>B00VINDBJK</td>\n",
       "      <td>[battery life, hold hand, page turn, page turn...</td>\n",
       "      <td>[[battery life, 5.296619432474642], [hold hand...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>B00X4WHP5E</td>\n",
       "      <td>[amazon echo, google home, set easy, purchase ...</td>\n",
       "      <td>[[amazon echo, 1.073465848064495], [google hom...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>B00ZV9PXP2</td>\n",
       "      <td>[great product, love kindle, easy use, great r...</td>\n",
       "      <td>[[great product, 7.456719338828389], [love kin...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>B0189XYY0Q</td>\n",
       "      <td>[kindle fire, easy use, love kindle, large scr...</td>\n",
       "      <td>[[kindle fire, 13.821488308778248], [easy use,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>B018SZT3BK</td>\n",
       "      <td>[kindle fire, easy use, great tablet, tablet p...</td>\n",
       "      <td>[[kindle fire, 10.234999412958555], [easy use,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>B018T075DC</td>\n",
       "      <td>[long battery life, long battery, love love ki...</td>\n",
       "      <td>[[long battery life, 0.8474299650541652], [lon...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>B018Y225IA</td>\n",
       "      <td>[great tablet, easy use, kindle fire, fire tab...</td>\n",
       "      <td>[[great tablet, 47.88488735433637], [easy use,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>B018Y229OU</td>\n",
       "      <td>[great tablet, great price, easy use, good tab...</td>\n",
       "      <td>[[great tablet, 482.007203683829], [great pric...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>B018Y22BI4</td>\n",
       "      <td>[kid love, love great price, love product, gre...</td>\n",
       "      <td>[[kid love, 0.9138614422843211], [love great p...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>B018Y22C2Y</td>\n",
       "      <td>[device kid, enjoy play, love kid, kid enjoy, ...</td>\n",
       "      <td>[[device kid, 0.8176573835935743], [enjoy play...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>B018Y23MNM</td>\n",
       "      <td>[year old, great kid, great tablet, tablet kid...</td>\n",
       "      <td>[[year old, 105.05134836599197], [great kid, 7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>B018Y23P7K</td>\n",
       "      <td>[yr old, good work good, good starter tablet, ...</td>\n",
       "      <td>[[yr old, 0.0], [good work good, 0.0], [good s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>B01AHB9C1E</td>\n",
       "      <td>[kindle fire, big screen, year ago, kindle fir...</td>\n",
       "      <td>[[kindle fire, 1.5189772269588158], [big scree...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>B01AHB9CN2</td>\n",
       "      <td>[great tablet, easy use, kindle fire, tablet p...</td>\n",
       "      <td>[[great tablet, 115.72402675529698], [easy use...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>B01AHB9CYG</td>\n",
       "      <td>[easy use, love kindle, kindle fire, great tab...</td>\n",
       "      <td>[[easy use, 5.748992762650797], [love kindle, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>B01BFIBRIE</td>\n",
       "      <td>[read book, read device, book read, device dev...</td>\n",
       "      <td>[[read book, 1.5789594036001897], [read device...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>B01BH83OOM</td>\n",
       "      <td>[amazon tap, great sound, bluetooth speaker, s...</td>\n",
       "      <td>[[amazon tap, 33.78157401903504], [great sound...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>B01J2G4VBG</td>\n",
       "      <td>[star work, work good, work fine, charge kindl...</td>\n",
       "      <td>[[star work, 37.481541555963716], [work good, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>B01J4ORNHU</td>\n",
       "      <td>[use echo, stop work, buy replacement, reasona...</td>\n",
       "      <td>[[use echo, 1.6830527907486768], [stop work, 1...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     asin                                         keyphrases  \\\n",
       "0              B002Y27P3M  [page turn, new kindle, kindle keyboard, use k...   \n",
       "1              B002Y27P6Y  [kindle read, kindle work, it easy, work great...   \n",
       "2              B005PB2T0S  [kindle keyboard, new kindle, feel like, kindl...   \n",
       "3              B005PB2T2Q  [kindle touch, kindle keyboard, doe it, look l...   \n",
       "4              B006GWO5NE  [kindle fire, need new, kindle fire hd, good k...   \n",
       "5              B006GWO5WK  [charge kindle, kindle fire, purchase kindle, ...   \n",
       "6              B0083Q04TA  [kindle fire, fire hd, year old, kindle keyboa...   \n",
       "7              B00BFJAHF8  [great doe, yr old, good work good, good start...   \n",
       "8              B00DU15MU4  [apple tv, easy find, prime movie, i try, amaz...   \n",
       "9              B00IOY8XWQ  [kindle voyage, page turn, great reader, turn ...   \n",
       "10             B00IOYAM4I  [kindle voyage, small size, read sunlight, eas...   \n",
       "11  B00L9EPT8O,B01E6AO69U  [amazon echo, play music, great product, love ...   \n",
       "12             B00LO29KXQ  [fire tv stick, tv stick, fire tv, amazon prim...   \n",
       "13             B00LW9XOJM  [kindle love, look good, protective case, it h...   \n",
       "14             B00OQVZDJM  [kindle paperwhite, easy read, great reader, l...   \n",
       "15             B00QFQRELG  [charge kindle, charger work, kindle fire, wor...   \n",
       "16             B00QJDU3KY  [new kindle, kindle paperwhite, book amazon, r...   \n",
       "17             B00QL1ZN3G  [kindle purchase, charge kindle, recommend kin...   \n",
       "18             B00REQKWGA  [like buy, love small, great travel, good gift...   \n",
       "19             B00TSUGXKE  [great tablet, good tablet, easy use, year old...   \n",
       "20             B00U3FPN4U  [fire tv, fire stick, great product, amazon fi...   \n",
       "21             B00UH4D8G2  [fire tv, fire tv box, tv box, apple tv, amazo...   \n",
       "22             B00VINDBJK  [battery life, hold hand, page turn, page turn...   \n",
       "23             B00X4WHP5E  [amazon echo, google home, set easy, purchase ...   \n",
       "24             B00ZV9PXP2  [great product, love kindle, easy use, great r...   \n",
       "25             B0189XYY0Q  [kindle fire, easy use, love kindle, large scr...   \n",
       "26             B018SZT3BK  [kindle fire, easy use, great tablet, tablet p...   \n",
       "27             B018T075DC  [long battery life, long battery, love love ki...   \n",
       "28             B018Y225IA  [great tablet, easy use, kindle fire, fire tab...   \n",
       "29             B018Y229OU  [great tablet, great price, easy use, good tab...   \n",
       "30             B018Y22BI4  [kid love, love great price, love product, gre...   \n",
       "31             B018Y22C2Y  [device kid, enjoy play, love kid, kid enjoy, ...   \n",
       "32             B018Y23MNM  [year old, great kid, great tablet, tablet kid...   \n",
       "33             B018Y23P7K  [yr old, good work good, good starter tablet, ...   \n",
       "34             B01AHB9C1E  [kindle fire, big screen, year ago, kindle fir...   \n",
       "35             B01AHB9CN2  [great tablet, easy use, kindle fire, tablet p...   \n",
       "36             B01AHB9CYG  [easy use, love kindle, kindle fire, great tab...   \n",
       "37             B01BFIBRIE  [read book, read device, book read, device dev...   \n",
       "38             B01BH83OOM  [amazon tap, great sound, bluetooth speaker, s...   \n",
       "39             B01J2G4VBG  [star work, work good, work fine, charge kindl...   \n",
       "40             B01J4ORNHU  [use echo, stop work, buy replacement, reasona...   \n",
       "\n",
       "                                       raw_keyphrases  \n",
       "0   [[page turn, 2.34234933075354], [new kindle, 1...  \n",
       "1   [[kindle read, 1.2621111430206566], [kindle wo...  \n",
       "2   [[kindle keyboard, 1.7086062596953622], [new k...  \n",
       "3   [[kindle touch, 1.1339104523521293], [kindle k...  \n",
       "4   [[kindle fire, 1.9297370597577206], [need new,...  \n",
       "5   [[charge kindle, 2.329915134188034], [kindle f...  \n",
       "6   [[kindle fire, 1.6981013491860775], [fire hd, ...  \n",
       "7   [[great doe, 1.0], [yr old, 0.0], [good work g...  \n",
       "8   [[apple tv, 1.6966821556118379], [easy find, 1...  \n",
       "9   [[kindle voyage, 33.678076383063065], [page tu...  \n",
       "10  [[kindle voyage, 2.5620479153303113], [small s...  \n",
       "11  [[amazon echo, 224.46499785606383], [play musi...  \n",
       "12  [[fire tv stick, 0.9408076339985175], [tv stic...  \n",
       "13  [[kindle love, 1.3771673715708075], [look good...  \n",
       "14  [[kindle paperwhite, 118.54757979138726], [eas...  \n",
       "15  [[charge kindle, 9.567602583436267], [charger ...  \n",
       "16  [[new kindle, 1.7620474903082095], [kindle pap...  \n",
       "17  [[kindle purchase, 1.8874901394146284], [charg...  \n",
       "18  [[like buy, 1.0886788044160025], [love small, ...  \n",
       "19  [[great tablet, 13.248887547665554], [good tab...  \n",
       "20  [[fire tv, 403.2804348717742], [fire stick, 21...  \n",
       "21  [[fire tv, 1.4170755643005697], [fire tv box, ...  \n",
       "22  [[battery life, 5.296619432474642], [hold hand...  \n",
       "23  [[amazon echo, 1.073465848064495], [google hom...  \n",
       "24  [[great product, 7.456719338828389], [love kin...  \n",
       "25  [[kindle fire, 13.821488308778248], [easy use,...  \n",
       "26  [[kindle fire, 10.234999412958555], [easy use,...  \n",
       "27  [[long battery life, 0.8474299650541652], [lon...  \n",
       "28  [[great tablet, 47.88488735433637], [easy use,...  \n",
       "29  [[great tablet, 482.007203683829], [great pric...  \n",
       "30  [[kid love, 0.9138614422843211], [love great p...  \n",
       "31  [[device kid, 0.8176573835935743], [enjoy play...  \n",
       "32  [[year old, 105.05134836599197], [great kid, 7...  \n",
       "33  [[yr old, 0.0], [good work good, 0.0], [good s...  \n",
       "34  [[kindle fire, 1.5189772269588158], [big scree...  \n",
       "35  [[great tablet, 115.72402675529698], [easy use...  \n",
       "36  [[easy use, 5.748992762650797], [love kindle, ...  \n",
       "37  [[read book, 1.5789594036001897], [read device...  \n",
       "38  [[amazon tap, 33.78157401903504], [great sound...  \n",
       "39  [[star work, 37.481541555963716], [work good, ...  \n",
       "40  [[use echo, 1.6830527907486768], [stop work, 1...  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "products_keyphrases_df = pd.DataFrame(products_keyphrases_df)\n",
    "products_keyphrases_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Product 0. Top tags ['page turn' 'new kindle' 'kindle keyboard' 'use kindle'\n",
      " 'page turn button' 'turn button' 'use battery' 'reader i' 'good device'\n",
      " 'book easy' 'great service' 'good light' 'kindle touch' 'touch screen'\n",
      " 'great love' 'it small' 'generation kindle' 'love great' 'connect home'\n",
      " 'perfect read']\n",
      "Product 1. Top tags ['kindle read' 'kindle work' 'it easy' 'work great' 'new kindle'\n",
      " 'hold hand' 'quality product' 'like product' 'purchase kindle'\n",
      " 'recommend product' 'kindle product' 'new amazon' 'device purchase'\n",
      " 'read like' 'read device' 'good kindle' 'especially price' 'start use'\n",
      " 'price pay' 'replace kindle']\n",
      "Product 2. Top tags ['kindle keyboard' 'new kindle' 'feel like' 'kindle light' 'size weight'\n",
      " 'high quality' 'everyday use' 'buy replacement' 'version kindle'\n",
      " 'new version' 'light great' 'kindle doe' 'kindle use' 'decide buy'\n",
      " 'light screen' 'money buy' 'save money' 'want use' 'kindle good'\n",
      " 'ease use']\n",
      "Product 3. Top tags ['kindle touch' 'kindle keyboard' 'doe it' 'look like' 'good it'\n",
      " 'price tag' 'overall it' 'i glad' 'read review' 'like read' 'i happy'\n",
      " 'it nice' 'big deal' 'love reader' 'kindle product' 'work amazon'\n",
      " 'especially price' 'it like' 'generation kindle' 'i sure']\n",
      "Product 4. Top tags ['kindle fire' 'need new' 'kindle fire hd' 'good kindle' 'kindle fire buy'\n",
      " 'fire buy' 'kindle purchase' 'fire hd' 'original kindle' 'good thing'\n",
      " 'work great love' 'use time' 'download book' 'worth price' 'great love'\n",
      " 'work good' 'charger work' 'good worth price' 'work great' 'read bed']\n"
     ]
    }
   ],
   "source": [
    "# pos analysis\n",
    "for i, (ind, product) in enumerate(products_keyphrases_df.iterrows()):\n",
    "    print(f'Product {ind}. Top tags {product.keyphrases}')\n",
    "    if i == 4:\n",
    "        break"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Grouping keyphrases"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### TF LDA method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "def display_topics(model, feature_names, no_top_words):\n",
    "    for topic_idx, topic in enumerate(model.components_):\n",
    "        print(f'Topic number {topic_idx + 1}:')\n",
    "        print(', '.join(\n",
    "            [feature_names[i] for i in topic.argsort()[:-no_top_words - 1:-1]])\n",
    "        )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(['year old mother',\n",
       "  'year old nephew',\n",
       "  'year old son',\n",
       "  'year old use',\n",
       "  'year warranty',\n",
       "  'you look',\n",
       "  'young child',\n",
       "  'young kid',\n",
       "  'youtube video',\n",
       "  'yr old'],\n",
       " ['10 year',\n",
       "  '10 year old',\n",
       "  '11 year',\n",
       "  '11 year old',\n",
       "  '12 year',\n",
       "  '12 year old',\n",
       "  '128 gb',\n",
       "  '16 gb',\n",
       "  '32 gb',\n",
       "  '3rd kindle'])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vectorizer = CountVectorizer(ngram_range=(2,3), max_features=2000, tokenizer=token_spacy_v2)\n",
    "transformed_texts = vectorizer.fit_transform(reviews_df.all_text);\n",
    "vectorizer.get_feature_names()[-10:], vectorizer.get_feature_names()[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "no_topics = 10\n",
    "lda = LatentDirichletAllocation(n_components=no_topics, max_iter=5, learning_method='online', learning_offset=50., random_state=0)\n",
    "lda.fit(transformed_texts);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Topic number 1:\n",
      "work good, amazon echo, work great, good product, great product\n",
      "Topic number 2:\n",
      "great gift, love alexa, excellent product, smart tv, great addition\n",
      "Topic number 3:\n",
      "amazon prime, easy set, easy use, highly recommend, apple tv\n",
      "Topic number 4:\n",
      "great stream, great buy, it great, great sound, work great\n",
      "Topic number 5:\n",
      "great product, fire stick, product great, easy use, easy read\n",
      "Topic number 6:\n",
      "easy use, great device, sound quality, great read, ask alexa\n",
      "Topic number 7:\n",
      "year old, stream device, good tablet, love easy, easy use\n",
      "Topic number 8:\n",
      "fire tv, amazon fire, amazon fire tv, play music, love echo\n",
      "Topic number 9:\n",
      "great tablet, great price, tablet great, kid love, tablet price\n",
      "Topic number 10:\n",
      "kindle fire, love kindle, love love, battery life, kindle paperwhite\n"
     ]
    }
   ],
   "source": [
    "# n=2,3\n",
    "no_top_words = 5\n",
    "display_topics(lda, vectorizer.get_feature_names(), no_top_words)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Topic 0:\n",
      "tv, fire, amazon, fire tv, -PRON-\n",
      "Topic 1:\n",
      "great, product, love, great product, use\n",
      "Topic 2:\n",
      "easy, use, great, easy use, light\n",
      "Topic 3:\n",
      "box, reader, question, charge, month\n",
      "Topic 4:\n",
      "tablet, great, price, good, great tablet\n",
      "Topic 5:\n",
      "kindle, love, gift, buy, read\n",
      "Topic 6:\n",
      "echo, device, -PRON-, amazon, home\n",
      "Topic 7:\n",
      "alexa, music, play, use, game\n",
      "Topic 8:\n",
      "love, great, tablet, buy, year\n",
      "Topic 9:\n",
      "good, work, app, product, great\n"
     ]
    }
   ],
   "source": [
    "# n=1,3\n",
    "no_top_words = 5\n",
    "display_topics(lda, vectorizer.get_feature_names(), no_top_words)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### TF-IDF NMF method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(['year old mother',\n",
       "  'year old nephew',\n",
       "  'year old son',\n",
       "  'year old use',\n",
       "  'year warranty',\n",
       "  'you look',\n",
       "  'young child',\n",
       "  'young kid',\n",
       "  'youtube video',\n",
       "  'yr old'],\n",
       " ['10 year',\n",
       "  '10 year old',\n",
       "  '11 year',\n",
       "  '11 year old',\n",
       "  '12 year',\n",
       "  '12 year old',\n",
       "  '128 gb',\n",
       "  '16 gb',\n",
       "  '32 gb',\n",
       "  '3rd kindle'])"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vectorizer = TfidfVectorizer(ngram_range=(2,3), max_features=2000, tokenizer=token_spacy_v2)\n",
    "transformed_texts = vectorizer.fit_transform(reviews_df.all_text);\n",
    "vectorizer.get_feature_names()[-10:], vectorizer.get_feature_names()[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "no_topics = 10\n",
    "nmf = NMF(n_components=no_topics, random_state=1, alpha=.1, l1_ratio=.5, init='nndsvd')\n",
    "nmf.fit(transformed_texts);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Topic number 1:\n",
      "great tablet, tablet price, tablet great, great tablet price, tablet kid\n",
      "Topic number 2:\n",
      "great product, product great, great product great, product great product, great product love\n",
      "Topic number 3:\n",
      "easy use, use great, love easy, easy use great, love easy use\n",
      "Topic number 4:\n",
      "fire tv, amazon fire, amazon fire tv, fire stick, tv box\n",
      "Topic number 5:\n",
      "work great, great work, great love, tablet work great, work great love\n",
      "Topic number 6:\n",
      "year old, old love, buy year, year old love, buy year old\n",
      "Topic number 7:\n",
      "work good, tablet work good, tablet work, product work good, product work\n",
      "Topic number 8:\n",
      "great price, tablet great, tablet great price, price great, great price great\n",
      "Topic number 9:\n",
      "kindle fire, love kindle, love kindle fire, read book, new kindle\n",
      "Topic number 10:\n",
      "good product, product good, good product good, product good product, good good\n"
     ]
    }
   ],
   "source": [
    "no_top_words = 5\n",
    "display_topics(nmf, vectorizer.get_feature_names(), no_top_words)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## TF-IDF NMF grouped by product"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(['young son',\n",
       "  'youtube app',\n",
       "  'youtube kid',\n",
       "  'youtube netflix',\n",
       "  'youtube video',\n",
       "  'yr old',\n",
       "  'yr old daughter',\n",
       "  'yr old grandson',\n",
       "  'yr old love',\n",
       "  'yr old son'],\n",
       " ['10 inch',\n",
       "  '10 year',\n",
       "  '10 year old',\n",
       "  '11 year',\n",
       "  '11 year old',\n",
       "  '12 year',\n",
       "  '12 year old',\n",
       "  '128 gb',\n",
       "  '16 gb',\n",
       "  '1st gen'])"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vectorizer = TfidfVectorizer(ngram_range=(2, 3), max_features=5000, tokenizer=token_spacy_v2)\n",
    "vectorizer.fit(reviews_df.all_text)\n",
    "vectorizer.get_feature_names()[-10:], vectorizer.get_feature_names()[:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Showing top 5 topics for each product"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(19, 22)\n",
      "\n",
      "Product asin: B002Y27P3M\n",
      "Topic number 1:\n",
      "page turn, power button, read thing, dedicate reader, compare apple\n",
      "Topic number 2:\n",
      "kindle keyboard, kindle touch, br br, touch screen, year old kindle\n",
      "Topic number 3:\n",
      "new kindle, it small, generation kindle, perfect read, br br\n",
      "Topic number 4:\n",
      "page turn, br br, kindle store, good light, iphone ipad\n",
      "Topic number 5:\n",
      "buy want, read time, book easy, fit purse, yr old son\n",
      "(10, 22)\n",
      "\n",
      "Product asin: B002Y27P6Y\n",
      "Topic number 1:\n",
      "kindle cover, new kindle, it big, kindle read, kindle work\n",
      "Topic number 2:\n",
      "good fit, product want, long period, hold long, kindle product\n",
      "Topic number 3:\n",
      "great happy, work great, use small, way use, good price\n",
      "Topic number 4:\n",
      "find helpful, hold hand, quality product, yr old son, good product good\n",
      "Topic number 5:\n",
      "nice simple, good think, it easy, yr old son, good product good\n",
      "(5, 22)\n",
      "\n",
      "Product asin: B005PB2T0S\n",
      "Topic number 1:\n",
      "kindle keyboard, feel like, kindle battery, previous generation, big improvement\n",
      "Topic number 2:\n",
      "high quality, dark room, actual book, comfortable hold, kindle price\n",
      "Topic number 3:\n",
      "kindle cover, light like, finally decide, sound like, main reason\n",
      "Topic number 4:\n",
      "kindle cover, plan use, kindle keyboard, everyday use, version kindle\n",
      "Topic number 5:\n",
      "new kindle, kindle keyboard, kindle battery, light screen, kindle good\n",
      "(6, 22)\n",
      "\n",
      "Product asin: B005PB2T2Q\n",
      "Topic number 1:\n",
      "kindle cover, kindle touch, good it, look like, job good\n",
      "Topic number 2:\n",
      "little disappoint, look nice, doe it suppose, case it, lot little\n",
      "Topic number 3:\n",
      "super light, price tag, i glad, read review, like read\n",
      "Topic number 4:\n",
      "big problem, kindle keyboard, yr old son, good product price, good problem\n",
      "Topic number 5:\n",
      "look cheap, review buy, reader work, perfect fit, kindle touch\n",
      "(8, 22)\n",
      "\n",
      "Product asin: B006GWO5NE\n",
      "Topic number 1:\n",
      "kindle fire, kindle fire hd, fire hd, worth price, music it\n",
      "Topic number 2:\n",
      "come kindle, charge fast, need new, wish come, work exactly\n",
      "Topic number 3:\n",
      "power cord, usb port, good thing, work great love, great love\n",
      "Topic number 4:\n",
      "need kindle, yr old son, good product great, good price great, good price tablet\n",
      "Topic number 5:\n",
      "charge cord, kindle model, kindle come, good kindle, original kindle\n",
      "(13, 22)\n",
      "\n",
      "Product asin: B006GWO5WK\n",
      "Topic number 1:\n",
      "charge kindle, charger kindle, kindle fire, micro usb, save money\n",
      "Topic number 2:\n",
      "charger work, charge fast, kindle fire, use wife, time time\n",
      "Topic number 3:\n",
      "fast charger, price device, kindle hd, purchase kindle, yr old son\n",
      "Topic number 4:\n",
      "good fire, good deal, work good, yr old son, good problem\n",
      "Topic number 5:\n",
      "kindle cover, quality excellent, doe work, high quality, great value\n",
      "(4, 22)\n",
      "(1, 22)\n",
      "(6, 22)\n",
      "\n",
      "Product asin: B00DU15MU4\n",
      "Topic number 1:\n",
      "br br, device read, yr old son, good product work, good problem\n",
      "Topic number 2:\n",
      "i try, amazon prime, work good, search feature, couple hour\n",
      "Topic number 3:\n",
      "prime movie, let know, prime content, easy find, like amazon\n",
      "Topic number 4:\n",
      "game i, screen saver, i amazon, free movie, exactly look\n",
      "Topic number 5:\n",
      "apple tv, stream content, game changer, content amazon, price device\n",
      "(580, 22)\n",
      "\n",
      "Product asin: B00IOY8XWQ\n",
      "Topic number 1:\n",
      "kindle voyage, love kindle, avid reader, touch screen, easy hold\n",
      "Topic number 2:\n",
      "page turn, turn button, page turn button, turn page, love new\n",
      "Topic number 3:\n",
      "great reader, good reader, battery life, reader good, great reader kindle\n",
      "Topic number 4:\n",
      "new kindle, love new, love new kindle, new feature, kindle love\n",
      "Topic number 5:\n",
      "light weight, light weight easy, weight easy, comfortable hold, small light\n",
      "(51, 22)\n",
      "\n",
      "Product asin: B00IOYAM4I\n",
      "Topic number 1:\n",
      "kindle voyage, easy read, read sunlight, upgrade kindle, original kindle\n",
      "Topic number 2:\n",
      "good battery life, good battery, battery life, use little, battery life great\n",
      "Topic number 3:\n",
      "kindle love, old kindle, great product, light small, light feature\n",
      "Topic number 4:\n",
      "small size, size fit, like small, light carry, great replacement\n",
      "Topic number 5:\n",
      "purchase wife, read purchase, good think, good small, good purchase\n"
     ]
    }
   ],
   "source": [
    "for i, (ind, product_group) in enumerate(reviews_df.groupby('asins')):\n",
    "    print(product_group.shape)\n",
    "    if product_group.shape[0] < 5:\n",
    "        continue\n",
    "    nmf = NMF(n_components=5, random_state=1, alpha=.1, l1_ratio=.5, init='nndsvd')\n",
    "    nmf.fit(vectorizer.transform(product_group.all_text));\n",
    "    \n",
    "    no_top_words = 5\n",
    "    print(f'\\nProduct asin: {ind}')\n",
    "    display_topics(nmf, vectorizer.get_feature_names(), no_top_words)\n",
    "\n",
    "    if i == 10:\n",
    "        break"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Showing top 5 topics for the most popular products"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Product asin: B00L9EPT8O,B01E6AO69U\n",
      "Topic number 1:\n",
      "amazon echo, love amazon echo, love amazon, echo great, amazon echo great\n",
      "Topic number 2:\n",
      "love alexa, alexa great, alexa love, love alexa love, love alexa great\n",
      "Topic number 3:\n",
      "great product, product great, great product great, product great product, product love\n",
      "Topic number 4:\n",
      "love echo, echo love, echo love echo, love echo love, echo great\n",
      "Topic number 5:\n",
      "play music, great sound, answer question, smart home, ask question\n",
      "\n",
      "Product asin: B00OQVZDJM\n",
      "Topic number 1:\n",
      "easy read, read light, light easy, easy read light, light easy read\n",
      "Topic number 2:\n",
      "kindle paperwhite, love kindle, love kindle paperwhite, paperwhite great, paperwhite love\n",
      "Topic number 3:\n",
      "great reader, reader great, great reader love, reader love, reader great reader\n",
      "Topic number 4:\n",
      "paper white, kindle paper white, kindle paper, paper white kindle, white kindle\n",
      "Topic number 5:\n",
      "great read, battery life, read book, easy eye, easy use\n",
      "\n",
      "Product asin: B00U3FPN4U\n",
      "Topic number 1:\n",
      "fire tv, amazon fire tv, amazon fire, tv box, fire tv box\n",
      "Topic number 2:\n",
      "fire stick, fast fire stick, fast fire, amazon fire stick, love fire stick\n",
      "Topic number 3:\n",
      "stream device, great stream, great stream device, device stream, stream device great\n",
      "Topic number 4:\n",
      "great product, product great, product great product, great product great, product easy\n",
      "Topic number 5:\n",
      "work great, tv work, tv work great, work great easy, great easy\n",
      "\n",
      "Product asin: B018Y229OU\n",
      "Topic number 1:\n",
      "great tablet, tablet great, great tablet great, tablet great tablet, tablet kid\n",
      "Topic number 2:\n",
      "great price, tablet great price, tablet great, price great, great price great\n",
      "Topic number 3:\n",
      "tablet price, great tablet price, great tablet, price great, tablet price great\n",
      "Topic number 4:\n",
      "easy use, tablet easy, tablet easy use, year old, fire tablet\n",
      "Topic number 5:\n",
      "good tablet, tablet good, tablet good tablet, good tablet price, good tablet good\n",
      "\n",
      "Product asin: B01AHB9CN2\n",
      "Topic number 1:\n",
      "great tablet, tablet price, great tablet price, tablet love, great tablet tablet\n",
      "Topic number 2:\n",
      "kindle fire, fire hd, kindle fire hd, love kindle, love kindle fire\n",
      "Topic number 3:\n",
      "easy use, tablet easy, tablet easy use, easy use great, easy use tablet\n",
      "Topic number 4:\n",
      "tablet great, great tablet great, great price, tablet great price, tablet great tablet\n",
      "Topic number 5:\n",
      "fire hd8, amazon fire hd8, amazon fire, fire hd8 tablet, hd8 tablet\n"
     ]
    }
   ],
   "source": [
    "for ind, product_group in reviews_df.groupby('asins'):\n",
    "    if product_group.shape[0] < 2000:\n",
    "        continue\n",
    "    \n",
    "    nmf = NMF(n_components=5, random_state=1, alpha=.1, l1_ratio=.5, init='nndsvd')\n",
    "    nmf.fit(vectorizer.transform(product_group.all_text));\n",
    "    \n",
    "    no_top_words = 5\n",
    "    print(f'\\nProduct asin: {ind}')\n",
    "    display_topics(nmf, vectorizer.get_feature_names(), no_top_words)"
   ]
  }
 ],
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