Untitled.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import gzip\n",
    "import urllib\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Download dataset helper functions\n",
    "def _download(url, filename):\n",
    "    # This has no exception handling at the moment xD. \n",
    "    # Be double check the URL before you use this. \n",
    "    print('Downloading dataset from '+url)\n",
    "    resp = urllib.request.urlretrieve(url, \"data/\"+filename)\n",
    "    print(\"Done.\")\n",
    "    print()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Download the Amazon sample [beauty dataset](http://snap.stanford.edu/data/amazon/productGraph/categoryFiles/reviews_Beauty_5.json.gz)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading dataset from http://snap.stanford.edu/data/amazon/productGraph/categoryFiles/meta_Beauty.json.gz\n",
      "Done.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "REVIEWS_URL = \"http://snap.stanford.edu/data/amazon/productGraph/categoryFiles/reviews_Beauty.json.gz\"\n",
    "METADATA_URL = \"http://snap.stanford.edu/data/amazon/productGraph/categoryFiles/meta_Beauty.json.gz\"\n",
    "\n",
    "#_download(REVIEWS_URL, \"amazon_beauty_reviews.json.gz\") # Download reviews\n",
    "_download(METADATA_URL, \"amazon_beauty_ratings.json.gz\") # Download reviews"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.7/site-packages/IPython/core/interactiveshell.py:3063: DtypeWarning: Columns (14,15) have mixed types.Specify dtype option on import or set low_memory=False.\n",
      "  interactivity=interactivity, compiler=compiler, result=result)\n",
      "/opt/anaconda3/lib/python3.7/site-packages/IPython/core/interactiveshell.py:3063: DtypeWarning: Columns (10) have mixed types.Specify dtype option on import or set low_memory=False.\n",
      "  interactivity=interactivity, compiler=compiler, result=result)\n"
     ]
    }
   ],
   "source": [
    "amazon_meta_df = pd.read_csv('datasets/amazon_beauty_metadata.csv')\n",
    "amazon_reviews_df = pd.read_csv('datasets/amazon_beauty_reviews.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 371345 entries, 0 to 371344\n",
      "Data columns (total 13 columns):\n",
      " #   Column          Non-Null Count   Dtype  \n",
      "---  ------          --------------   -----  \n",
      " 0   Unnamed: 0      371345 non-null  int64  \n",
      " 1   overall         371345 non-null  float64\n",
      " 2   verified        371345 non-null  bool   \n",
      " 3   reviewTime      371345 non-null  object \n",
      " 4   reviewerID      371345 non-null  object \n",
      " 5   asin            371345 non-null  object \n",
      " 6   reviewerName    371293 non-null  object \n",
      " 7   reviewText      370946 non-null  object \n",
      " 8   summary         371134 non-null  object \n",
      " 9   unixReviewTime  371345 non-null  int64  \n",
      " 10  vote            51899 non-null   object \n",
      " 11  style           125958 non-null  object \n",
      " 12  image           8391 non-null    object \n",
      "dtypes: bool(1), float64(1), int64(2), object(9)\n",
      "memory usage: 34.4+ MB\n"
     ]
    }
   ],
   "source": [
    "amazon_reviews_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 32992 entries, 0 to 32991\n",
      "Data columns (total 16 columns):\n",
      " #   Column        Non-Null Count  Dtype \n",
      "---  ------        --------------  ----- \n",
      " 0   Unnamed: 0    32992 non-null  int64 \n",
      " 1   title         32991 non-null  object\n",
      " 2   image         16609 non-null  object\n",
      " 3   brand         17301 non-null  object\n",
      " 4   rank          32615 non-null  object\n",
      " 5   main_cat      32992 non-null  object\n",
      " 6   asin          32992 non-null  object\n",
      " 7   description   15191 non-null  object\n",
      " 8   also_view     8155 non-null   object\n",
      " 9   also_buy      6613 non-null   object\n",
      " 10  price         11288 non-null  object\n",
      " 11  similar_item  1305 non-null   object\n",
      " 12  details       32836 non-null  object\n",
      " 13  feature       269 non-null    object\n",
      " 14  tech1         10 non-null     object\n",
      " 15  date          19 non-null     object\n",
      "dtypes: int64(1), object(15)\n",
      "memory usage: 4.0+ MB\n"
     ]
    }
   ],
   "source": [
    "amazon_meta_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "amazon_meta_df = amazon_meta_df.drop('details', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "brand\n",
      "#Flashmob                                              1\n",
      "#Healthy                                               2\n",
      "#R5                                                    1\n",
      "(3 Pack) NYC Ultra Moist Lipwear - Violet Shine ...    1\n",
      "(Black Opal)                                           1\n",
      "                                                      ..\n",
      "younique                                               1\n",
      "youthwaters                                            1\n",
      "yoyomax                                                1\n",
      "zila                                                   1\n",
      "zonman                                                 1\n",
      "Name: title, Length: 7893, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "brands = amazon_meta_df.groupby('brand')['title'].nunique()\n",
    "print(brands)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>title</th>\n",
       "      <th>description</th>\n",
       "      <th>brand</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>workout headphones by arena essentials</td>\n",
       "      <td>nan</td>\n",
       "      <td>harpercollins</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>black diamond</td>\n",
       "      <td>['this is the new purple bottle that just came...</td>\n",
       "      <td>swedish beauty</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12 pc blue heaven kajal\"herbal kajal with vita...</td>\n",
       "      <td>['a brand-new, unused, unopened, undamaged ite...</td>\n",
       "      <td>blue heave</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>the inheritance</td>\n",
       "      <td>[\"you have to wonder why there isn't a word in...</td>\n",
       "      <td>sunatoria</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>the listening cards</td>\n",
       "      <td>['the listening cards are an eloquent primer i...</td>\n",
       "      <td>listening planet</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               title  \\\n",
       "0             workout headphones by arena essentials   \n",
       "1                                      black diamond   \n",
       "2  12 pc blue heaven kajal\"herbal kajal with vita...   \n",
       "3                                    the inheritance   \n",
       "4                                the listening cards   \n",
       "\n",
       "                                         description             brand  \n",
       "0                                                nan     harpercollins  \n",
       "1  ['this is the new purple bottle that just came...    swedish beauty  \n",
       "2  ['a brand-new, unused, unopened, undamaged ite...        blue heave  \n",
       "3  [\"you have to wonder why there isn't a word in...         sunatoria  \n",
       "4  ['the listening cards are an eloquent primer i...  listening planet  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "keywords = ['cleanser', 'moisturizer', 'oil', 'lotion', 'mask', 'aftershave', 'wash', 'scrub', 'shaving cream', 'deoderant', 'spf', 'face',\n",
    "           'moisture', 'dry', 'oily', 'skincare', 'facial']\n",
    "\n",
    "lowercase_cols = amazon_meta_df[['title','description', 'brand']]\n",
    "lowercase_cols = lowercase_cols.apply(lambda x: x.astype(str).str.lower())\n",
    "lowercase_cols.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "import string\n",
    "table = str.maketrans(\"\", \"\", string.punctuation)\n",
    "indices = []\n",
    "products = []\n",
    "i=0\n",
    "while i < len(keywords):\n",
    "    for idx, j in lowercase_cols.iterrows():\n",
    "        for val in j:\n",
    "            val = val.translate(table)\n",
    "            check = val.find(keywords[i])\n",
    "            if check != -1:\n",
    "                indices.append(idx)\n",
    "                products.append(val)\n",
    "    i+=1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "17328\n"
     ]
    }
   ],
   "source": [
    "print(len(indices))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>title</th>\n",
       "      <th>description</th>\n",
       "      <th>brand</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>dove nutrium nutrient beads nourishing body wa...</td>\n",
       "      <td>[\"nutrient beads with vitamin e lotion for sof...</td>\n",
       "      <td>nan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>lever 2000 antibacterial moisturizing wipes, t...</td>\n",
       "      <td>['5.5 x 7.5-inch. with vitamin e. alcohol-free...</td>\n",
       "      <td>nan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>neutrogena clean for color - color defending s...</td>\n",
       "      <td>['&lt;p&gt;color defending shampoo&lt;/p&gt; &lt;p&gt;&lt;strong&gt;pr...</td>\n",
       "      <td>nan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>phisoderm deep cleaning cleanser, sensitive sk...</td>\n",
       "      <td>['deep cleaning cleanser cleans revitalizes nu...</td>\n",
       "      <td>nan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>phisoderm deep cleaning cleanser, sensitive sk...</td>\n",
       "      <td>['deep cleaning cleanser cleans revitalizes nu...</td>\n",
       "      <td>nan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32786</th>\n",
       "      <td>facial cleanser for acne prone skin, oily skin...</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32796</th>\n",
       "      <td>cosmetic, makeup and beauty blender and facial...</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32875</th>\n",
       "      <td>derma roller 0.25mm - facial skin care tool fo...</td>\n",
       "      <td>['stop spending thousands of dollars! forget a...</td>\n",
       "      <td>new body life</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32875</th>\n",
       "      <td>derma roller 0.25mm - facial skin care tool fo...</td>\n",
       "      <td>['stop spending thousands of dollars! forget a...</td>\n",
       "      <td>new body life</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32974</th>\n",
       "      <td>bial 24k golden beauty bar facial massager wat...</td>\n",
       "      <td>['1. power supply : d.c1.5v (one aa dry batter...</td>\n",
       "      <td>bial ex</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>17328 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   title  \\\n",
       "141    dove nutrium nutrient beads nourishing body wa...   \n",
       "163    lever 2000 antibacterial moisturizing wipes, t...   \n",
       "164    neutrogena clean for color - color defending s...   \n",
       "170    phisoderm deep cleaning cleanser, sensitive sk...   \n",
       "170    phisoderm deep cleaning cleanser, sensitive sk...   \n",
       "...                                                  ...   \n",
       "32786  facial cleanser for acne prone skin, oily skin...   \n",
       "32796  cosmetic, makeup and beauty blender and facial...   \n",
       "32875  derma roller 0.25mm - facial skin care tool fo...   \n",
       "32875  derma roller 0.25mm - facial skin care tool fo...   \n",
       "32974  bial 24k golden beauty bar facial massager wat...   \n",
       "\n",
       "                                             description          brand  \n",
       "141    [\"nutrient beads with vitamin e lotion for sof...            nan  \n",
       "163    ['5.5 x 7.5-inch. with vitamin e. alcohol-free...            nan  \n",
       "164    ['<p>color defending shampoo</p> <p><strong>pr...            nan  \n",
       "170    ['deep cleaning cleanser cleans revitalizes nu...            nan  \n",
       "170    ['deep cleaning cleanser cleans revitalizes nu...            nan  \n",
       "...                                                  ...            ...  \n",
       "32786                                                nan            nan  \n",
       "32796                                                nan            nan  \n",
       "32875  ['stop spending thousands of dollars! forget a...  new body life  \n",
       "32875  ['stop spending thousands of dollars! forget a...  new body life  \n",
       "32974  ['1. power supply : d.c1.5v (one aa dry batter...        bial ex  \n",
       "\n",
       "[17328 rows x 3 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "products = lowercase_cols.iloc[indices, :]\n",
    "products"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "filtered_df = amazon_meta_df.merge(products, left_index=True, right_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>image</th>\n",
       "      <th>rank</th>\n",
       "      <th>main_cat</th>\n",
       "      <th>asin</th>\n",
       "      <th>also_view</th>\n",
       "      <th>also_buy</th>\n",
       "      <th>price</th>\n",
       "      <th>similar_item</th>\n",
       "      <th>feature</th>\n",
       "      <th>tech1</th>\n",
       "      <th>date</th>\n",
       "      <th>title</th>\n",
       "      <th>description</th>\n",
       "      <th>brand</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1,462,563inBeautyamp;PersonalCare(</td>\n",
       "      <td>All Beauty</td>\n",
       "      <td>0143026860</td>\n",
       "      <td>['B000LXTNMW']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>black diamond</td>\n",
       "      <td>['this is the new purple bottle that just came...</td>\n",
       "      <td>swedish beauty</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>['https://images-na.ssl-images-amazon.com/imag...</td>\n",
       "      <td>1,885,596inBeautyamp;PersonalCare(</td>\n",
       "      <td>All Beauty</td>\n",
       "      <td>0721917704</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>control of outdoor advertising and graffiti</td>\n",
       "      <td>['product description product: sunatoria teeth...</td>\n",
       "      <td>sunatoria</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>['https://images-na.ssl-images-amazon.com/imag...</td>\n",
       "      <td>1,162,704inBeautyamp;PersonalCare(</td>\n",
       "      <td>All Beauty</td>\n",
       "      <td>0957664613</td>\n",
       "      <td>['0634039245', '0757978134', '1458424219', '15...</td>\n",
       "      <td>['153717309X']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>xylophone for beginners 2015</td>\n",
       "      <td>['product description product: sunatoria teeth...</td>\n",
       "      <td>sunatoria</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>['https://images-na.ssl-images-amazon.com/imag...</td>\n",
       "      <td>3,473,391inBeautyamp;PersonalCare(</td>\n",
       "      <td>All Beauty</td>\n",
       "      <td>0977689565</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>podcasting 101: the multimedia university that...</td>\n",
       "      <td>['product description product: sunatoria teeth...</td>\n",
       "      <td>sunatoria</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>['https://images-na.ssl-images-amazon.com/imag...</td>\n",
       "      <td>459,527inBeautyamp;PersonalCare(</td>\n",
       "      <td>All Beauty</td>\n",
       "      <td>140717455X</td>\n",
       "      <td>['0545947898', '0142403873', '1407132326', 'B0...</td>\n",
       "      <td>['0142402753', '0142407542', '0142411388', 'B0...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>stick man tenth anniversary edition</td>\n",
       "      <td>['looking for a natural and effective way of r...</td>\n",
       "      <td>larivia essential</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32978</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1,222,808inBeautyPersonalCare(</td>\n",
       "      <td>All Beauty</td>\n",
       "      <td>B01HIGWNF8</td>\n",
       "      <td>['B07H4XCH7M', 'B073VRHNC5', 'B07H5ZQG68']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>$15.54</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>australian gold 8 oz. lotion with kona bronzer...</td>\n",
       "      <td>['australian gold 8 oz. lotion with kona bronz...</td>\n",
       "      <td>australian gold</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32978</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1,222,808inBeautyPersonalCare(</td>\n",
       "      <td>All Beauty</td>\n",
       "      <td>B01HIGWNF8</td>\n",
       "      <td>['B07H4XCH7M', 'B073VRHNC5', 'B07H5ZQG68']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>$15.54</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>australian gold 8 oz. lotion with kona bronzer...</td>\n",
       "      <td>['australian gold 8 oz. lotion with kona bronz...</td>\n",
       "      <td>australian gold</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32979</th>\n",
       "      <td>['https://images-na.ssl-images-amazon.com/imag...</td>\n",
       "      <td>748,822inBeautyPersonalCare(</td>\n",
       "      <td>All Beauty</td>\n",
       "      <td>B01HIH2QTU</td>\n",
       "      <td>['B01B6K6MRC', 'B075F9VTZM', 'B01MY6ZNNQ', 'B0...</td>\n",
       "      <td>['B01HMGQ48G', 'B01D6JFM04', 'B01B6K6MRC']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>gentlemen's hardware apothecary shaving cream</td>\n",
       "      <td>[\"theres no finer way for a chap to get ready ...</td>\n",
       "      <td>gentlemen's hardware</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32979</th>\n",
       "      <td>['https://images-na.ssl-images-amazon.com/imag...</td>\n",
       "      <td>748,822inBeautyPersonalCare(</td>\n",
       "      <td>All Beauty</td>\n",
       "      <td>B01HIH2QTU</td>\n",
       "      <td>['B01B6K6MRC', 'B075F9VTZM', 'B01MY6ZNNQ', 'B0...</td>\n",
       "      <td>['B01HMGQ48G', 'B01D6JFM04', 'B01B6K6MRC']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>gentlemen's hardware apothecary shaving cream</td>\n",
       "      <td>[\"theres no finer way for a chap to get ready ...</td>\n",
       "      <td>gentlemen's hardware</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32988</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1,639,713inBeautyPersonalCare(</td>\n",
       "      <td>All Beauty</td>\n",
       "      <td>B01HJ1K3YK</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>(buy 3 get 1 free) salon perfect eye makeup co...</td>\n",
       "      <td>nan</td>\n",
       "      <td>salon perfect</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>17328 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   image  \\\n",
       "1                                                    NaN   \n",
       "5      ['https://images-na.ssl-images-amazon.com/imag...   \n",
       "7      ['https://images-na.ssl-images-amazon.com/imag...   \n",
       "16     ['https://images-na.ssl-images-amazon.com/imag...   \n",
       "27     ['https://images-na.ssl-images-amazon.com/imag...   \n",
       "...                                                  ...   \n",
       "32978                                                NaN   \n",
       "32978                                                NaN   \n",
       "32979  ['https://images-na.ssl-images-amazon.com/imag...   \n",
       "32979  ['https://images-na.ssl-images-amazon.com/imag...   \n",
       "32988                                                NaN   \n",
       "\n",
       "                                     rank    main_cat        asin  \\\n",
       "1      1,462,563inBeautyamp;PersonalCare(  All Beauty  0143026860   \n",
       "5      1,885,596inBeautyamp;PersonalCare(  All Beauty  0721917704   \n",
       "7      1,162,704inBeautyamp;PersonalCare(  All Beauty  0957664613   \n",
       "16     3,473,391inBeautyamp;PersonalCare(  All Beauty  0977689565   \n",
       "27       459,527inBeautyamp;PersonalCare(  All Beauty  140717455X   \n",
       "...                                   ...         ...         ...   \n",
       "32978      1,222,808inBeautyPersonalCare(  All Beauty  B01HIGWNF8   \n",
       "32978      1,222,808inBeautyPersonalCare(  All Beauty  B01HIGWNF8   \n",
       "32979        748,822inBeautyPersonalCare(  All Beauty  B01HIH2QTU   \n",
       "32979        748,822inBeautyPersonalCare(  All Beauty  B01HIH2QTU   \n",
       "32988      1,639,713inBeautyPersonalCare(  All Beauty  B01HJ1K3YK   \n",
       "\n",
       "                                               also_view  \\\n",
       "1                                         ['B000LXTNMW']   \n",
       "5                                                    NaN   \n",
       "7      ['0634039245', '0757978134', '1458424219', '15...   \n",
       "16                                                   NaN   \n",
       "27     ['0545947898', '0142403873', '1407132326', 'B0...   \n",
       "...                                                  ...   \n",
       "32978         ['B07H4XCH7M', 'B073VRHNC5', 'B07H5ZQG68']   \n",
       "32978         ['B07H4XCH7M', 'B073VRHNC5', 'B07H5ZQG68']   \n",
       "32979  ['B01B6K6MRC', 'B075F9VTZM', 'B01MY6ZNNQ', 'B0...   \n",
       "32979  ['B01B6K6MRC', 'B075F9VTZM', 'B01MY6ZNNQ', 'B0...   \n",
       "32988                                                NaN   \n",
       "\n",
       "                                                also_buy   price similar_item  \\\n",
       "1                                                    NaN     NaN          NaN   \n",
       "5                                                    NaN     NaN          NaN   \n",
       "7                                         ['153717309X']     NaN          NaN   \n",
       "16                                                   NaN     NaN          NaN   \n",
       "27     ['0142402753', '0142407542', '0142411388', 'B0...     NaN          NaN   \n",
       "...                                                  ...     ...          ...   \n",
       "32978                                                NaN  $15.54          NaN   \n",
       "32978                                                NaN  $15.54          NaN   \n",
       "32979         ['B01HMGQ48G', 'B01D6JFM04', 'B01B6K6MRC']     NaN          NaN   \n",
       "32979         ['B01HMGQ48G', 'B01D6JFM04', 'B01B6K6MRC']     NaN          NaN   \n",
       "32988                                                NaN     NaN          NaN   \n",
       "\n",
       "      feature tech1 date                                              title  \\\n",
       "1         NaN   NaN  NaN                                      black diamond   \n",
       "5         NaN   NaN  NaN        control of outdoor advertising and graffiti   \n",
       "7         NaN   NaN  NaN                       xylophone for beginners 2015   \n",
       "16        NaN   NaN  NaN  podcasting 101: the multimedia university that...   \n",
       "27        NaN   NaN  NaN                stick man tenth anniversary edition   \n",
       "...       ...   ...  ...                                                ...   \n",
       "32978     NaN   NaN  NaN  australian gold 8 oz. lotion with kona bronzer...   \n",
       "32978     NaN   NaN  NaN  australian gold 8 oz. lotion with kona bronzer...   \n",
       "32979     NaN   NaN  NaN      gentlemen's hardware apothecary shaving cream   \n",
       "32979     NaN   NaN  NaN      gentlemen's hardware apothecary shaving cream   \n",
       "32988     NaN   NaN  NaN  (buy 3 get 1 free) salon perfect eye makeup co...   \n",
       "\n",
       "                                             description                 brand  \n",
       "1      ['this is the new purple bottle that just came...        swedish beauty  \n",
       "5      ['product description product: sunatoria teeth...             sunatoria  \n",
       "7      ['product description product: sunatoria teeth...             sunatoria  \n",
       "16     ['product description product: sunatoria teeth...             sunatoria  \n",
       "27     ['looking for a natural and effective way of r...     larivia essential  \n",
       "...                                                  ...                   ...  \n",
       "32978  ['australian gold 8 oz. lotion with kona bronz...       australian gold  \n",
       "32978  ['australian gold 8 oz. lotion with kona bronz...       australian gold  \n",
       "32979  [\"theres no finer way for a chap to get ready ...  gentlemen's hardware  \n",
       "32979  [\"theres no finer way for a chap to get ready ...  gentlemen's hardware  \n",
       "32988                                                nan         salon perfect  \n",
       "\n",
       "[17328 rows x 14 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filtered_df = filtered_df.drop(['brand_x', 'description_x', 'Unnamed: 0', 'title_x'], axis=1)\n",
    "filtered_df = filtered_df.rename(columns = {\n",
    "    'brand_y': 'brand', 'title_y': 'title', 'description_y': 'description'\n",
    "})\n",
    "filtered_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['brands', 'acqua di parma', 'adwoa beauty', 'aerin', 'aether beauty', 'algenist', 'alphah', 'alpyn beauty', 'alterna haircare', 'amika', 'amorepacific', 'anastasia beverly hills', 'anthony ', 'antonym', 'aquis', 'armani beauty', 'the art of shaving', 'artis', 'artist couture', 'atelier cologne', 'balenciaga', 'bareminerals', 'beachwaver', 'the beauty chef', 'beautybio', 'beautyblender', 'becca cosmetics', 'belif', 'benefit cosmetics', 'berdoues', 'bsame cosmetics', 'better not younger', 'bio ionic', 'biossance', 'bite beauty', 'bkr', 'black up', 'blinc', 'bobbi brown', 'boscia', 'briogeo', 'bumble and bumble', 'burberry', 'buxom', 'bvlgari', 'by rosie jane', 'calvin klein', 'capri blue', 'carolina herrera', 'caudalie', 'cellucup', 'chanel', 'charlotte tilbury', 'chlo', 'christian louboutin', 'christophe robin', 'ciat london', 'cinema secrets', 'clarins', 'clarisonic skincare', 'clean', 'clinique', 'coal and canary', 'cocofloss', 'comme des garcons ', 'commodity', 'comptoir sud pacifique', 'conture', 'coola', 'cover fx', 'crushed tonic', 'dae', 'deborah lippmann', 'derek lam  crosby', 'dermadoctor', 'dermaflash', 'dermalogica', 'devacurl', 'diamancel', 'dior', 'dolcegabbana', 'dominique cosmetics', 'donna karan', 'dphue', 'dr roebucks', 'dr barbara sturm', 'dr brandt skincare', 'dr dennis gross', 'dr jart', 'drunk elephant', 'drybar', 'dtrt', 'duo', 'dyson', 'earths nectar', 'edible beauty', 'eight  bob', 'elizabeth and james ', 'ellis brooklyn', 'erborian', 'erno laszlo', 'este lauder', 'etat libre dorange', 'eve lom', 'evian', 'fable  mane', 'farmacy', 'farsli', 'fenty beauty by rihanna', 'first aid beauty', 'flora  bast', 'floral street', 'foreo', 'form', 'four sigmatic', 'fresh', 'ghd', 'givenchy', 'glamglow', 'glo science', 'glow recipe', 'golde', 'good dye young', 'google', 'goop', 'grande cosmetics', 'gucci', 'guerlain', 'herbivore', 'herms', 'high beauty', 'hourglass', 'huda beauty', 'hum nutrition', 'hush', 'igk', 'ilia', 'incredible', 'indie lee', 'the inkey list', 'innisfree', 'invisibobble', 'isle of paradise', 'issey miyake', 'it cosmetics', 'its skin', 'jack black', 'jimmy choo', 'jo malone london', 'john varvatos', 'josie maran', 'jouer cosmetics', 'juicy couture', 'juliette has a gun', 'kaja', 'kate somerville', 'kate spade new york', 'kenzo', 'kenzoki', 'krastase', 'kevyn aucoin', 'kiehls since ', 'kilian', 'klorane', 'knc beauty', 'koh gen do', 'kopari', 'kora organics', 'korres', 'kosas', 'kvd vegan beauty', 'loccitane', 'la mer', 'lab series for men', 'lancer skincare', 'lancme', 'laneige', 'lashfood', 'laura mercier', 'lavanila', 'lawless', 'lightstim', 'lilah b', 'lilly lashes', 'living proof', 'lord jones', 'lunar beauty', 'lxmi', 'madam cj walker beauty culture', 'maelys cosmetics', 'maison louis marie', 'maison margiela', 'make up for ever', 'marc jacobs beauty', 'marc jacobs fragrances', 'mario badescu', 'marvis', 'mdsolarsciences', 'melt cosmetics', 'michael kors', 'milk makeup', 'miu miu', 'mizani', 'montblanc', 'moon juice', 'moroccanoil', 'moschino', 'mount lai', 'mugler', 'murad', 'nails inc', 'narciso rodriguez', 'nars', 'natasha denona', 'naturally serious', 'neogen dermalogy', 'nest new york', 'no mostache', 'nudestix', 'nuface', 'nurse jamie', 'om', 'obagi clinical', 'olaplex', 'olehenriksen', 'omorovicza', 'the ordinary', 'the original makeup eraser', 'origins', 'ouai', 'ouidad', 'overose', 'paco rabanne', 'pat mcgrath labs', 'patrick ta', 'peace out', 'perricone md', 'peter thomas roth', 'philosophy', 'phlur', 'pink sugar', 'pinrose', 'playa', 'pmd', 'prada', 'pretty vulgar', 'prima', 'proactiv', 'qhemet biologics', 'rag  bone', 'rahua', 'ralph lauren', 'refa', 'ren clean skincare', 'reverie', 'rita hazan', 'rms beauty', 'rodin olio lusso', 'roen beauty', 'rosebud perfume co', 'rossano ferretti parma', 'sachajuan', 'saint jane', 'sakara life', 'sand  sky', 'saturday skin', 'seed phytonutrients', 'sephora collection', 'sephora favorites', 'shani darden skin care', 'shaveworks', 'shhhowercap', 'shiseido', 'shu uemura', 'skii', 'skin inc supplement bar', 'skin laundry', 'skinfix', 'slip', 'smashbox', 'sobel skin rx', 'sol de janeiro', 'st tropez', 'stackedskincare', 'stellar', 'stila', 'sulwhasoo', 'summer fridays', 'sunday riley', 'supergoop', 'surratt beauty', 't', 'tanluxe', 'tarte', 'taste beauty', 'tata harper', 'tatcha', 'tocca', 'together beauty', 'tokyomilk', 'tom ford', 'too cool for school', 'too faced', 'tory burch', 'touch in sol', 'tower  beauty', 'trstique', 'tweezerman', 'urban decay', 'valentino', 'velour lashes', 'verb', 'versace', 'viktorrolf', 'violet voss', 'virtue', 'viseart', 'vital proteins', 'vitruvi', 'volition beauty', 'voluspa', 'wander beauty', 'welleco', 'wishful', 'youth to the people', 'yuni', 'yves saint laurent', 'the  virtues', 'greens']\n",
      "329\n"
     ]
    }
   ],
   "source": [
    "with open('brands.txt') as f:\n",
    "    brands = [line.rstrip('\\n') for line in f]\n",
    "    \n",
    "brand_names = []\n",
    "for brand in brands:\n",
    "    b = brand.lower()\n",
    "    brand_names.append(b)\n",
    "    \n",
    "print(brand_names)\n",
    "print(len(brand_names))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>brand</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>swedish beauty</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>sunatoria</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>sunatoria</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>sunatoria</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>larivia essential</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32978</th>\n",
       "      <td>australian gold</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32978</th>\n",
       "      <td>australian gold</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32979</th>\n",
       "      <td>gentlemen's hardware</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32979</th>\n",
       "      <td>gentlemen's hardware</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32988</th>\n",
       "      <td>salon perfect</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>17328 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      brand\n",
       "1            swedish beauty\n",
       "5                 sunatoria\n",
       "7                 sunatoria\n",
       "16                sunatoria\n",
       "27        larivia essential\n",
       "...                     ...\n",
       "32978       australian gold\n",
       "32978       australian gold\n",
       "32979  gentlemen's hardware\n",
       "32979  gentlemen's hardware\n",
       "32988         salon perfect\n",
       "\n",
       "[17328 rows x 1 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "brand_col = filtered_df[['brand']]\n",
    "brand_col"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "import unicodedata\n",
    "from unicodedata import normalize\n",
    "import re\n",
    "\n",
    "def remove_punct(word):    \n",
    "    table = str.maketrans(\"\", \"\", string.punctuation)\n",
    "    word = word.translate(table)\n",
    "    return word\n",
    "\n",
    "def norma_uni(word):\n",
    "    word = normalize(\"NFD\", word).encode(\"ascii\", \"ignore\")\n",
    "    word = word.decode('UTF-8')\n",
    "    return word\n",
    "\n",
    "def non_print(word):\n",
    "    re_print = re.compile(\"[^%s]\" % re.escape(string.printable))\n",
    "    word = re_print.sub(\"\", word)\n",
    "    return word\n",
    "\n",
    "def clean_txt(lst):\n",
    "    cleaned = []\n",
    "    for word in lst:\n",
    "        w = norma_uni(word)\n",
    "        w = remove_punct(w)\n",
    "        w = non_print(w)\n",
    "        cleaned.append(w)\n",
    "    return cleaned"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['healthy', 'black opal', 'wonderfulbreast', '', '', '417', '14 oz dabon', '100 pure', '111skin nac y2', '1979 collection', '2 pack sexy hair soy renewal crme oil 42 ounce', '2013newestseller', '21 drops', '21transdermal', '2n', '320 oz can', '3m', '40 carrots', '47krate', '4everstore', '50 shades of grey', '6th sense styling technology', '7 miracles', '759shop', '7felicity', '7th heaven', '80 acres', 'a size above', 'a wild soap bar llc', 'aaa de aromas artesanales de antigua', 'aaa shea butter', 'aaatssox', 'aaronatherapy', 'ab', 'abba', 'abbey st clare', 'abcstore99', 'ableware', 'abra', 'absolute', 'absolute new york', 'absolutely fabulous', 'absolutely natural', 'academie', 'acca kappa', 'acid mantle', 'acneorg', 'acnefree', 'acqua dellelba', 'act']\n"
     ]
    }
   ],
   "source": [
    "unique_brands = sorted(brand_col.brand.unique().tolist())\n",
    "clean_amazon_b = clean_txt(unique_brands)\n",
    "clean_sephora_b = clean_txt(brand_names)\n",
    "print(clean_amazon_b[:50])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['aerin', 'algenist', 'aquis', 'bareminerals', 'becca cosmetics', 'bite beauty', 'bobbi brown', 'briogeo', 'bumble and bumble', 'bvlgari', 'carolina herrera', 'caudalie', 'chanel', 'charlotte tilbury', 'clarins', 'clean', 'clinique', 'deborah lippmann', 'dermalogica', 'dior', 'donna karan', 'dr jart', 'erborian', 'fresh', 'givenchy', 'glamglow', 'gucci', 'guerlain', 'herms', 'innisfree', 'invisibobble', 'issey miyake', 'it cosmetics', 'its skin', 'josie maran', 'kate somerville', 'kenzo', 'kevyn aucoin', 'kiehls', 'koh gen do', 'la mer', 'lancme', 'laneige', 'laura mercier', 'living proof', 'make up for ever', 'michael kors', 'moroccanoil', 'murad', 'nars', 'neogen dermalogy', 'nickel skincare for men', 'omorovicza', 'origins', 'origins', 'ouai', 'paco rabanne', 'perricone md', 'peter thomas roth', 'philosophy', 'prada', 'ralph lauren', 'rms beauty', 'shiseido', 'shu uemura', 'skinfood', 'smashbox', 'st tropez', 'tarte', 'tata harper', 'tocca', 'too cool for school', 'too faced', 'urban decay', 'valentino', 'versace', 'yves saint laurent']\n",
      "77\n"
     ]
    }
   ],
   "source": [
    "amazon_set = set(clean_amazon_b)\n",
    "sephora_set = set(clean_sephora_b)\n",
    "\n",
    "intersection = amazon_set.intersection(brand_names)\n",
    "brands_list = list(intersection)\n",
    "missing_brands = ['kiehls', 'nickel skincare for men', 'origins', 'skinfood']\n",
    "brands_list.extend(missing_brands)\n",
    "print(sorted(brands_list))\n",
    "print(len(brands_list))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "327\n",
      "[4957, 27848, 27848, 17286, 17286, 2420, 2420, 2420, 3021, 3021, 4445, 4445, 5073, 5584, 5932, 5932, 9532, 12920, 12921, 13520, 13520, 13520, 13520, 19206, 21571, 23877, 25814, 27033, 27033, 27033, 27514, 2343, 2343, 2343, 4898, 13519, 13519, 13519, 26181, 26181, 21254, 21254, 22188, 23336, 27453, 27631, 8499, 8499, 8499, 25754, 25754, 3071, 6960, 6960, 6960, 6960, 13633, 13633, 13633, 13633, 13633, 19084, 19084, 19084, 19084, 23047, 23047, 23047, 23047, 23047, 32005, 19077, 19078, 10925, 10925, 13306, 9632, 9632, 9632, 9632, 9632, 9632, 11382, 11382, 11382, 11382, 17100, 3670, 3821, 3821, 3821, 3892, 4291, 4291, 4291, 4291, 4291, 4291, 7843, 7843, 17519, 17519, 17519, 17519, 2591, 10076, 10210, 10210, 10210, 5807, 5807, 6434, 7147, 23538, 23538, 23539, 23539, 27877, 17637, 17637, 17637, 17637, 17637, 30200, 29496, 32370, 1641, 4301, 5206, 1000, 26710, 12021, 12021, 12021, 22444, 22444, 22444, 28321, 28321, 28321, 1250, 1847, 1847, 1984, 2016, 2016, 2016, 2016, 3548, 3548, 3548, 3548, 4102, 4102, 4102, 4102, 4102, 4102, 6770, 6770, 7042, 7042, 7042, 7042, 7042, 7142, 7142, 10587, 10587, 10587, 10587, 25669, 32176, 4379, 4379, 4379, 4379, 4379, 6853, 1501, 1501, 3465, 3465, 3465, 7892, 18097, 20602, 20602, 20602, 32713, 3495, 5339, 6576, 6576, 2422, 2422, 4178, 10220, 25823, 25823, 27556, 32209, 32209, 996, 996, 996, 996, 2824, 2824, 5622, 5622, 5622, 5948, 6677, 6677, 6677, 7415, 7634, 7634, 7634, 13515, 13628, 17184, 17184, 24376, 28035, 28035, 28035, 28207, 28207, 28207, 28207, 28300, 1871, 2965, 3683, 3683, 3683, 7523, 7707, 7707, 7707, 1191, 1191, 1191, 1193, 1193, 1193, 1451, 1451, 1451, 1462, 1462, 1462, 2852, 29662, 276, 276, 494, 494, 680, 680, 898, 898, 1479, 1479, 2540, 2540, 2540, 3692, 3870, 3870, 5166, 8356, 8356, 8356, 8356, 8356, 12855, 12855, 12855, 12855, 13160, 18226, 18226, 18226, 18226, 18226, 21382, 21382, 21382, 4621, 4621, 7382, 7382, 7382, 7382, 19798, 19798, 19798, 28744, 28744, 13114, 32933, 9385, 7608, 7608, 15893, 15893, 278, 278, 278, 278, 682, 682, 682, 682, 1244, 1244, 3058, 4677, 4677, 5507, 19531, 30945, 32734, 32734]\n"
     ]
    }
   ],
   "source": [
    "makeup_brands = ['kevyn aucoin', 'bareminerals', 'smashbox', 'bobbi brown', 'nars', 'urban decay', \n",
    "                 'too faced', 'tocca', 'tarte', 'becca cosmetics', 'laura mercier', 'make up for everyone', 'it cosmetics', 'paco rabanne']\n",
    "prod_lst_final = np.setdiff1d(brands_list, makeup_brands)\n",
    "\n",
    "indxs = []\n",
    "prod_lst = []\n",
    "while i < len(prod_lst_final):\n",
    "    for idx, j in brand_col.iterrows():\n",
    "        for val in j:\n",
    "            check = val.find(prod_lst_final[i])\n",
    "            if check != -1:\n",
    "                indxs.append(idx)\n",
    "                prod_lst.append(val)\n",
    "    i+=1\n",
    "print(len(indxs))\n",
    "print(indxs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['aerin' 'algenist' 'aquis' 'bite beauty' 'briogeo' 'bumble and bumble'\n",
      " 'bvlgari' 'carolina herrera' 'caudalie' 'chanel' 'charlotte tilbury'\n",
      " 'clarins' 'clean' 'clinique' 'deborah lippmann' 'dermalogica' 'dior'\n",
      " 'donna karan' 'dr jart' 'erborian' 'fresh' 'givenchy' 'glamglow' 'gucci'\n",
      " 'guerlain' 'herms' 'innisfree' 'invisibobble' 'issey miyake' 'its skin'\n",
      " 'josie maran' 'kate somerville' 'kenzo' 'kiehls' 'koh gen do' 'la mer'\n",
      " 'lancme' 'laneige' 'living proof' 'make up for ever' 'michael kors'\n",
      " 'moroccanoil' 'murad' 'neogen dermalogy' 'nickel skincare for men'\n",
      " 'omorovicza' 'origins' 'ouai' 'perricone md' 'peter thomas roth'\n",
      " 'philosophy' 'prada' 'ralph lauren' 'rms beauty' 'shiseido' 'shu uemura'\n",
      " 'skinfood' 'st tropez' 'tata harper' 'too cool for school' 'valentino'\n",
      " 'versace' 'yves saint laurent']\n",
      "63\n"
     ]
    }
   ],
   "source": [
    "print(prod_lst_final)\n",
    "print(len(prod_lst_final))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
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       "                                  brand\n",
       "4957                        donna karan\n",
       "27848                       donna karan\n",
       "27848                       donna karan\n",
       "27848                       donna karan\n",
       "27848                       donna karan\n",
       "...                                 ...\n",
       "30945                yves saint laurent\n",
       "32734  yves saint laurent & beauty-buyz\n",
       "32734  yves saint laurent & beauty-buyz\n",
       "32734  yves saint laurent & beauty-buyz\n",
       "32734  yves saint laurent & beauty-buyz\n",
       "\n",
       "[947 rows x 1 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prods = brand_col.loc[indxs, :]\n",
    "prods"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
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       "      <td>All Beauty</td>\n",
       "      <td>B01H4K03CS</td>\n",
       "      <td>[\"Listing includes Bonus 5 Purse-Sized 4inch E...</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>Parisienne Body Lotion Plus Bonus 5 Emery Boards</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>All Beauty</td>\n",
       "      <td>B01H4K03CS</td>\n",
       "      <td>[\"Listing includes Bonus 5 Purse-Sized 4inch E...</td>\n",
       "      <td>NaN</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>32734</th>\n",
       "      <td>Parisienne Body Lotion Plus Bonus 5 Emery Boards</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2,252,486inBeautyPersonalCare(</td>\n",
       "      <td>All Beauty</td>\n",
       "      <td>B01H4K03CS</td>\n",
       "      <td>[\"Listing includes Bonus 5 Purse-Sized 4inch E...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>yves saint laurent &amp; beauty-buyz</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32933</th>\n",
       "      <td>Too Cool For School Egg Cream Firming Mask Pac...</td>\n",
       "      <td>['https://images-na.ssl-images-amazon.com/imag...</td>\n",
       "      <td>164,907inBeautyPersonalCare(</td>\n",
       "      <td>All Beauty</td>\n",
       "      <td>B01HFUTUBC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>['B01HFUQ0TM', 'B00KR3H0NK', 'B0177ECA8Q', 'B0...</td>\n",
       "      <td>$14.73</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>too cool for school</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>947 rows × 14 columns</p>\n",
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      ],
      "text/plain": [
       "                                                   title  \\\n",
       "276    Shiseido THE SKINCARE Night Essential Moisturi...   \n",
       "276    Shiseido THE SKINCARE Night Essential Moisturi...   \n",
       "276    Shiseido THE SKINCARE Night Essential Moisturi...   \n",
       "276    Shiseido THE SKINCARE Night Essential Moisturi...   \n",
       "278    Yves Saint Laurent Instant Pur Natural Action ...   \n",
       "...                                                  ...   \n",
       "32734   Parisienne Body Lotion Plus Bonus 5 Emery Boards   \n",
       "32734   Parisienne Body Lotion Plus Bonus 5 Emery Boards   \n",
       "32734   Parisienne Body Lotion Plus Bonus 5 Emery Boards   \n",
       "32734   Parisienne Body Lotion Plus Bonus 5 Emery Boards   \n",
       "32933  Too Cool For School Egg Cream Firming Mask Pac...   \n",
       "\n",
       "                                                   image  \\\n",
       "276    ['https://images-na.ssl-images-amazon.com/imag...   \n",
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       "276    ['https://images-na.ssl-images-amazon.com/imag...   \n",
       "278    ['https://images-na.ssl-images-amazon.com/imag...   \n",
       "...                                                  ...   \n",
       "32734                                                NaN   \n",
       "32734                                                NaN   \n",
       "32734                                                NaN   \n",
       "32734                                                NaN   \n",
       "32933  ['https://images-na.ssl-images-amazon.com/imag...   \n",
       "\n",
       "                                     rank    main_cat        asin  \\\n",
       "276    3,208,315inBeautyamp;PersonalCare(  All Beauty  B000142SG4   \n",
       "276    3,208,315inBeautyamp;PersonalCare(  All Beauty  B000142SG4   \n",
       "276    3,208,315inBeautyamp;PersonalCare(  All Beauty  B000142SG4   \n",
       "276    3,208,315inBeautyamp;PersonalCare(  All Beauty  B000142SG4   \n",
       "278    3,408,887inBeautyamp;PersonalCare(  All Beauty  B000142QMA   \n",
       "...                                   ...         ...         ...   \n",
       "32734      2,252,486inBeautyPersonalCare(  All Beauty  B01H4K03CS   \n",
       "32734      2,252,486inBeautyPersonalCare(  All Beauty  B01H4K03CS   \n",
       "32734      2,252,486inBeautyPersonalCare(  All Beauty  B01H4K03CS   \n",
       "32734      2,252,486inBeautyPersonalCare(  All Beauty  B01H4K03CS   \n",
       "32933        164,907inBeautyPersonalCare(  All Beauty  B01HFUTUBC   \n",
       "\n",
       "                                             description also_view  \\\n",
       "276    [\"A multi-action emulsion Provides instant and...       NaN   \n",
       "276    [\"A multi-action emulsion Provides instant and...       NaN   \n",
       "276    [\"A multi-action emulsion Provides instant and...       NaN   \n",
       "276    [\"A multi-action emulsion Provides instant and...       NaN   \n",
       "278    [\"A gentle exfoliating facial scrub  Eases awa...       NaN   \n",
       "...                                                  ...       ...   \n",
       "32734  [\"Listing includes Bonus 5 Purse-Sized 4inch E...       NaN   \n",
       "32734  [\"Listing includes Bonus 5 Purse-Sized 4inch E...       NaN   \n",
       "32734  [\"Listing includes Bonus 5 Purse-Sized 4inch E...       NaN   \n",
       "32734  [\"Listing includes Bonus 5 Purse-Sized 4inch E...       NaN   \n",
       "32933                                                NaN       NaN   \n",
       "\n",
       "                                                also_buy   price similar_item  \\\n",
       "276                                                  NaN     NaN          NaN   \n",
       "276                                                  NaN     NaN          NaN   \n",
       "276                                                  NaN     NaN          NaN   \n",
       "276                                                  NaN     NaN          NaN   \n",
       "278                                                  NaN     NaN          NaN   \n",
       "...                                                  ...     ...          ...   \n",
       "32734                                                NaN     NaN          NaN   \n",
       "32734                                                NaN     NaN          NaN   \n",
       "32734                                                NaN     NaN          NaN   \n",
       "32734                                                NaN     NaN          NaN   \n",
       "32933  ['B01HFUQ0TM', 'B00KR3H0NK', 'B0177ECA8Q', 'B0...  $14.73          NaN   \n",
       "\n",
       "      feature tech1 date                             brand  \n",
       "276       NaN   NaN  NaN                          shiseido  \n",
       "276       NaN   NaN  NaN                          shiseido  \n",
       "276       NaN   NaN  NaN                          shiseido  \n",
       "276       NaN   NaN  NaN                          shiseido  \n",
       "278       NaN   NaN  NaN                yves saint laurent  \n",
       "...       ...   ...  ...                               ...  \n",
       "32734     NaN   NaN  NaN  yves saint laurent & beauty-buyz  \n",
       "32734     NaN   NaN  NaN  yves saint laurent & beauty-buyz  \n",
       "32734     NaN   NaN  NaN  yves saint laurent & beauty-buyz  \n",
       "32734     NaN   NaN  NaN  yves saint laurent & beauty-buyz  \n",
       "32933     NaN   NaN  NaN               too cool for school  \n",
       "\n",
       "[947 rows x 14 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filtered_brand_df = amazon_meta_df.merge(prods, left_index=True, right_index=True)\n",
    "filtered_brand_df = filtered_brand_df.drop(['brand_x', 'Unnamed: 0'], axis=1)\n",
    "filtered_brand_df = filtered_brand_df.rename(columns = {\n",
    "    'brand_y': 'brand'})\n",
    "filtered_brand_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "filtered_brand_df.to_csv('filtered_amazon_meta.csv')"
   ]
  }
 ],
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