Main notebook.ipynb

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    "# Project GEVPRO (H&M) - MAIN\n",
    "\n",
    "We will work with the following dataset: \n",
    "Source: https://www.kaggle.com/competitions/h-and-m-personalized-fashion-recommendations/overview\n",
    "This dataset has been reduced to use less memory. Only sales data from > 08-01-2020 is selected. "
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   "source": [
    "# Used libaries:\n",
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "\n",
    "from matplotlib import pyplot as plt\n",
    "import matplotlib.image as mpimg\n",
    "\n",
    "from sklearn.metrics.pairwise import cosine_similarity\n",
    "from tqdm.notebook import tqdm"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "## 0.  Research questions:\n",
    "We try to answer the following main research question:“Can we use the H&M dataset to explore data about its latest fashion trends and customer base?” This main research question is devided into 3 sub categories“: \n",
    "1. Sales --> What is popular\n",
    "2. Customer base --> Who is our customer?\n",
    "3. Personalised Fashion reccomendation --> Can we reccomend products based on other customers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.  Reducing the dataset: \n",
    "This is only ran on the default dataset (transactions_train.csv) found on kaggle to reduce the memory size to 91.3mb (instead of 3+gb)."
   ]
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   "source": [
    "# df = pd.read_csv('data/transactions_train.csv', low_memory=False)\n",
    "# df['t_dat'] = pd.to_datetime(df['t_dat'])\n",
    "# mask = df['t_dat'] > '08-01-2020'\n",
    "# df_reduced = df.loc[mask]\n",
    "# df_reduced.to_csv('C:\\\\Users\\\\Nils\\\\Jupyter Notebooks\\\\Project_gevpro\\\\transactions_reduced.csv')"
   ]
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   "cell_type": "code",
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   "metadata": {
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    "id": "tt1B9_GsBNQ1",
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   "source": [
    "# This loads the reduced transaction (sales) dataset.\n",
    "customers = pd.read_csv('data/customers.csv', low_memory=False)\n",
    "articles = pd.read_csv('data/articles.csv', low_memory=False)\n",
    "transactions = pd.read_csv('data/transactions_reduced.csv', low_memory=False)"
   ]
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  {
   "cell_type": "markdown",
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   "source": [
    "## 2. Exploring the data"
   ]
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   "source": [
    "#### 2.1 Exploring customers.csv\n",
    "\n",
    "The following table will describe information contained in customers.csv:\n",
    "\n",
    "| Column | Description |\n",
    "| --- | --- |\n",
    "| customer_id | A unique customer id |\n",
    "| FN | ? |\n",
    "| Active | Whether an account is active or not |\n",
    "| club_member_status | Is member of H&M club |\n",
    "| Fashion_news_frequency | If customers get notified about H&M news |\n",
    "| age | The age of customers |"
   ]
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       "      <td>NaN</td>\n",
       "      <td>ACTIVE</td>\n",
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       "      <td>54.0</td>\n",
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       "      <td>52.0</td>\n",
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       "                                         customer_id   FN  Active  \\\n",
       "0  00000dbacae5abe5e23885899a1fa44253a17956c6d1c3...  NaN     NaN   \n",
       "1  0000423b00ade91418cceaf3b26c6af3dd342b51fd051e...  NaN     NaN   \n",
       "2  000058a12d5b43e67d225668fa1f8d618c13dc232df0ca...  NaN     NaN   \n",
       "3  00005ca1c9ed5f5146b52ac8639a40ca9d57aeff4d1bd2...  NaN     NaN   \n",
       "4  00006413d8573cd20ed7128e53b7b13819fe5cfc2d801f...  1.0     1.0   \n",
       "\n",
       "  club_member_status fashion_news_frequency   age  \\\n",
       "0             ACTIVE                   NONE  49.0   \n",
       "1             ACTIVE                   NONE  25.0   \n",
       "2             ACTIVE                   NONE  24.0   \n",
       "3             ACTIVE                   NONE  54.0   \n",
       "4             ACTIVE              Regularly  52.0   \n",
       "\n",
       "                                         postal_code  \n",
       "0  52043ee2162cf5aa7ee79974281641c6f11a68d276429a...  \n",
       "1  2973abc54daa8a5f8ccfe9362140c63247c5eee03f1d93...  \n",
       "2  64f17e6a330a85798e4998f62d0930d14db8db1c054af6...  \n",
       "3  5d36574f52495e81f019b680c843c443bd343d5ca5b1c2...  \n",
       "4  25fa5ddee9aac01b35208d01736e57942317d756b32ddd...  "
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   "source": [
    "customers.head()"
   ]
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       "      <th></th>\n",
       "      <th>FN</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>476930.0</td>\n",
       "      <td>464404.0</td>\n",
       "      <td>1.356119e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.638696e+01</td>\n",
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       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.431363e+01</td>\n",
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       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.600000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.400000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.200000e+01</td>\n",
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       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.900000e+01</td>\n",
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       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.900000e+01</td>\n",
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      "text/plain": [
       "             FN    Active           age\n",
       "count  476930.0  464404.0  1.356119e+06\n",
       "mean        1.0       1.0  3.638696e+01\n",
       "std         0.0       0.0  1.431363e+01\n",
       "min         1.0       1.0  1.600000e+01\n",
       "25%         1.0       1.0  2.400000e+01\n",
       "50%         1.0       1.0  3.200000e+01\n",
       "75%         1.0       1.0  4.900000e+01\n",
       "max         1.0       1.0  9.900000e+01"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "customers.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.2 Exploring articles.csv\n",
    "This section will show the information contained in the articles.csv file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
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       "      <td>Ladieswear</td>\n",
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       "      <td>Womens Everyday Basics</td>\n",
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       "      <td>Jersey Basic</td>\n",
       "      <td>Jersey top with narrow shoulder straps.</td>\n",
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       "      <th>3</th>\n",
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       "      <td>306</td>\n",
       "      <td>Bra</td>\n",
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       "      <td>1010016</td>\n",
       "      <td>Solid</td>\n",
       "      <td>9</td>\n",
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       "      <td>...</td>\n",
       "      <td>Clean Lingerie</td>\n",
       "      <td>B</td>\n",
       "      <td>Lingeries/Tights</td>\n",
       "      <td>1</td>\n",
       "      <td>Ladieswear</td>\n",
       "      <td>61</td>\n",
       "      <td>Womens Lingerie</td>\n",
       "      <td>1017</td>\n",
       "      <td>Under-, Nightwear</td>\n",
       "      <td>Microfibre T-shirt bra with underwired, moulde...</td>\n",
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       "      <td>1010016</td>\n",
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       "      <td>1017</td>\n",
       "      <td>Under-, Nightwear</td>\n",
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       "   article_id  product_code          prod_name  product_type_no  \\\n",
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       "1   108775044        108775          Strap top              253   \n",
       "2   108775051        108775      Strap top (1)              253   \n",
       "3   110065001        110065  OP T-shirt (Idro)              306   \n",
       "4   110065002        110065  OP T-shirt (Idro)              306   \n",
       "\n",
       "  product_type_name  product_group_name  graphical_appearance_no  \\\n",
       "0          Vest top  Garment Upper body                  1010016   \n",
       "1          Vest top  Garment Upper body                  1010016   \n",
       "2          Vest top  Garment Upper body                  1010017   \n",
       "3               Bra           Underwear                  1010016   \n",
       "4               Bra           Underwear                  1010016   \n",
       "\n",
       "  graphical_appearance_name  colour_group_code colour_group_name  ...  \\\n",
       "0                     Solid                  9             Black  ...   \n",
       "1                     Solid                 10             White  ...   \n",
       "2                    Stripe                 11         Off White  ...   \n",
       "3                     Solid                  9             Black  ...   \n",
       "4                     Solid                 10             White  ...   \n",
       "\n",
       "   department_name index_code        index_name index_group_no  \\\n",
       "0     Jersey Basic          A        Ladieswear              1   \n",
       "1     Jersey Basic          A        Ladieswear              1   \n",
       "2     Jersey Basic          A        Ladieswear              1   \n",
       "3   Clean Lingerie          B  Lingeries/Tights              1   \n",
       "4   Clean Lingerie          B  Lingeries/Tights              1   \n",
       "\n",
       "   index_group_name section_no            section_name garment_group_no  \\\n",
       "0        Ladieswear         16  Womens Everyday Basics             1002   \n",
       "1        Ladieswear         16  Womens Everyday Basics             1002   \n",
       "2        Ladieswear         16  Womens Everyday Basics             1002   \n",
       "3        Ladieswear         61         Womens Lingerie             1017   \n",
       "4        Ladieswear         61         Womens Lingerie             1017   \n",
       "\n",
       "   garment_group_name                                        detail_desc  \n",
       "0        Jersey Basic            Jersey top with narrow shoulder straps.  \n",
       "1        Jersey Basic            Jersey top with narrow shoulder straps.  \n",
       "2        Jersey Basic            Jersey top with narrow shoulder straps.  \n",
       "3   Under-, Nightwear  Microfibre T-shirt bra with underwired, moulde...  \n",
       "4   Under-, Nightwear  Microfibre T-shirt bra with underwired, moulde...  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "articles.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>article_id</th>\n",
       "      <th>product_code</th>\n",
       "      <th>product_type_no</th>\n",
       "      <th>graphical_appearance_no</th>\n",
       "      <th>colour_group_code</th>\n",
       "      <th>perceived_colour_value_id</th>\n",
       "      <th>perceived_colour_master_id</th>\n",
       "      <th>department_no</th>\n",
       "      <th>index_group_no</th>\n",
       "      <th>section_no</th>\n",
       "      <th>garment_group_no</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1.055420e+05</td>\n",
       "      <td>105542.000000</td>\n",
       "      <td>105542.000000</td>\n",
       "      <td>1.055420e+05</td>\n",
       "      <td>105542.000000</td>\n",
       "      <td>105542.000000</td>\n",
       "      <td>105542.000000</td>\n",
       "      <td>105542.000000</td>\n",
       "      <td>105542.000000</td>\n",
       "      <td>105542.000000</td>\n",
       "      <td>105542.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>6.984246e+08</td>\n",
       "      <td>698424.563378</td>\n",
       "      <td>234.861875</td>\n",
       "      <td>1.009515e+06</td>\n",
       "      <td>32.233822</td>\n",
       "      <td>3.206183</td>\n",
       "      <td>7.807972</td>\n",
       "      <td>4532.777833</td>\n",
       "      <td>3.171534</td>\n",
       "      <td>42.664219</td>\n",
       "      <td>1010.438290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.284624e+08</td>\n",
       "      <td>128462.384432</td>\n",
       "      <td>75.049308</td>\n",
       "      <td>2.241359e+04</td>\n",
       "      <td>28.086154</td>\n",
       "      <td>1.563839</td>\n",
       "      <td>5.376727</td>\n",
       "      <td>2712.692011</td>\n",
       "      <td>4.353234</td>\n",
       "      <td>23.260105</td>\n",
       "      <td>6.731023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.087750e+08</td>\n",
       "      <td>108775.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000e+00</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>1201.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1001.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>6.169925e+08</td>\n",
       "      <td>616992.500000</td>\n",
       "      <td>252.000000</td>\n",
       "      <td>1.010008e+06</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1676.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>1005.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>7.022130e+08</td>\n",
       "      <td>702213.000000</td>\n",
       "      <td>259.000000</td>\n",
       "      <td>1.010016e+06</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>4222.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>46.000000</td>\n",
       "      <td>1009.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>7.967030e+08</td>\n",
       "      <td>796703.000000</td>\n",
       "      <td>272.000000</td>\n",
       "      <td>1.010016e+06</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>7389.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>1017.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>9.594610e+08</td>\n",
       "      <td>959461.000000</td>\n",
       "      <td>762.000000</td>\n",
       "      <td>1.010029e+06</td>\n",
       "      <td>93.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>9989.000000</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>1025.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         article_id   product_code  product_type_no  graphical_appearance_no  \\\n",
       "count  1.055420e+05  105542.000000    105542.000000             1.055420e+05   \n",
       "mean   6.984246e+08  698424.563378       234.861875             1.009515e+06   \n",
       "std    1.284624e+08  128462.384432        75.049308             2.241359e+04   \n",
       "min    1.087750e+08  108775.000000        -1.000000            -1.000000e+00   \n",
       "25%    6.169925e+08  616992.500000       252.000000             1.010008e+06   \n",
       "50%    7.022130e+08  702213.000000       259.000000             1.010016e+06   \n",
       "75%    7.967030e+08  796703.000000       272.000000             1.010016e+06   \n",
       "max    9.594610e+08  959461.000000       762.000000             1.010029e+06   \n",
       "\n",
       "       colour_group_code  perceived_colour_value_id  \\\n",
       "count      105542.000000              105542.000000   \n",
       "mean           32.233822                   3.206183   \n",
       "std            28.086154                   1.563839   \n",
       "min            -1.000000                  -1.000000   \n",
       "25%             9.000000                   2.000000   \n",
       "50%            14.000000                   4.000000   \n",
       "75%            52.000000                   4.000000   \n",
       "max            93.000000                   7.000000   \n",
       "\n",
       "       perceived_colour_master_id  department_no  index_group_no  \\\n",
       "count               105542.000000  105542.000000   105542.000000   \n",
       "mean                     7.807972    4532.777833        3.171534   \n",
       "std                      5.376727    2712.692011        4.353234   \n",
       "min                     -1.000000    1201.000000        1.000000   \n",
       "25%                      4.000000    1676.000000        1.000000   \n",
       "50%                      5.000000    4222.000000        2.000000   \n",
       "75%                     11.000000    7389.000000        4.000000   \n",
       "max                     20.000000    9989.000000       26.000000   \n",
       "\n",
       "          section_no  garment_group_no  \n",
       "count  105542.000000     105542.000000  \n",
       "mean       42.664219       1010.438290  \n",
       "std        23.260105          6.731023  \n",
       "min         2.000000       1001.000000  \n",
       "25%        20.000000       1005.000000  \n",
       "50%        46.000000       1009.000000  \n",
       "75%        61.000000       1017.000000  \n",
       "max        97.000000       1025.000000  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "articles.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.3 Exploring transactions.csv\n",
    "This section will show the information contained in the transactions.csv file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>t_dat</th>\n",
       "      <th>customer_id</th>\n",
       "      <th>article_id</th>\n",
       "      <th>price</th>\n",
       "      <th>sales_channel_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-08-02</td>\n",
       "      <td>0001d44dbe7f6c4b35200abdb052c77a87596fe1bdcc37...</td>\n",
       "      <td>853474004</td>\n",
       "      <td>0.033881</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-08-02</td>\n",
       "      <td>0001d44dbe7f6c4b35200abdb052c77a87596fe1bdcc37...</td>\n",
       "      <td>865594003</td>\n",
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       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-08-02</td>\n",
       "      <td>0001d44dbe7f6c4b35200abdb052c77a87596fe1bdcc37...</td>\n",
       "      <td>865699001</td>\n",
       "      <td>0.025407</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-08-02</td>\n",
       "      <td>0001d44dbe7f6c4b35200abdb052c77a87596fe1bdcc37...</td>\n",
       "      <td>822959001</td>\n",
       "      <td>0.050831</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-08-02</td>\n",
       "      <td>0001d44dbe7f6c4b35200abdb052c77a87596fe1bdcc37...</td>\n",
       "      <td>888024005</td>\n",
       "      <td>0.084729</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        t_dat                                        customer_id  article_id  \\\n",
       "0  2020-08-02  0001d44dbe7f6c4b35200abdb052c77a87596fe1bdcc37...   853474004   \n",
       "1  2020-08-02  0001d44dbe7f6c4b35200abdb052c77a87596fe1bdcc37...   865594003   \n",
       "2  2020-08-02  0001d44dbe7f6c4b35200abdb052c77a87596fe1bdcc37...   865699001   \n",
       "3  2020-08-02  0001d44dbe7f6c4b35200abdb052c77a87596fe1bdcc37...   822959001   \n",
       "4  2020-08-02  0001d44dbe7f6c4b35200abdb052c77a87596fe1bdcc37...   888024005   \n",
       "\n",
       "      price  sales_channel_id  \n",
       "0  0.033881                 2  \n",
       "1  0.013542                 2  \n",
       "2  0.025407                 2  \n",
       "3  0.050831                 2  \n",
       "4  0.084729                 2  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "transactions.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>article_id</th>\n",
       "      <th>price</th>\n",
       "      <th>sales_channel_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1.993503e+06</td>\n",
       "      <td>1.993503e+06</td>\n",
       "      <td>1.993503e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>8.011889e+08</td>\n",
       "      <td>2.957675e-02</td>\n",
       "      <td>1.675810e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.305485e+08</td>\n",
       "      <td>2.038062e-02</td>\n",
       "      <td>4.680714e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.087750e+08</td>\n",
       "      <td>3.220339e-04</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>7.542380e+08</td>\n",
       "      <td>1.693220e-02</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>8.457900e+08</td>\n",
       "      <td>2.540678e-02</td>\n",
       "      <td>2.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>8.895500e+08</td>\n",
       "      <td>3.388136e-02</td>\n",
       "      <td>2.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>9.562170e+08</td>\n",
       "      <td>5.067797e-01</td>\n",
       "      <td>2.000000e+00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         article_id         price  sales_channel_id\n",
       "count  1.993503e+06  1.993503e+06      1.993503e+06\n",
       "mean   8.011889e+08  2.957675e-02      1.675810e+00\n",
       "std    1.305485e+08  2.038062e-02      4.680714e-01\n",
       "min    1.087750e+08  3.220339e-04      1.000000e+00\n",
       "25%    7.542380e+08  1.693220e-02      1.000000e+00\n",
       "50%    8.457900e+08  2.540678e-02      2.000000e+00\n",
       "75%    8.895500e+08  3.388136e-02      2.000000e+00\n",
       "max    9.562170e+08  5.067797e-01      2.000000e+00"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "transactions.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. Exploring H&M's customer base\n",
    "\n",
    "In the customer section of this project we have explored the following research questions: \n",
    "* What is the most frequent age of H&M customers? \n",
    "* What is the distribution of the ages of H&M customers? W\n",
    "* What is the most frequent postal code? \n",
    "* How many customers have a club membership?\n",
    "* What kind of fashion news frequency is most popular with what club membership?\n",
    "* How many people receive fashion news? \n",
    "* What is the spread of fashion news in contrast to club member status? \n",
    "* What is the relation between receiving fashion news and the customers age?\n",
    "\n",
    "We have expressed the data in different ways, varying from plots to tables. With this research, we try to create a better overview of the customers shopping at H&M."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1356119, 7)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('data/customers.csv', low_memory=False)\n",
    "df = df.dropna(subset=['age', 'postal_code'])  # drop rows with missing values in this column\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 3.1 What is the most frequent age of H&M customers?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "21.0    67530\n",
       "24.0    56124\n",
       "20.0    55196\n",
       "25.0    54989\n",
       "23.0    54867\n",
       "26.0    53658\n",
       "22.0    51869\n",
       "27.0    49134\n",
       "28.0    44294\n",
       "29.0    40697\n",
       "Name: age, dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#What are the 10 most frequent ages?\n",
    "df[\"age\"].value_counts().head(10)\n",
    "\n",
    "#The most frequent age is 21, and the most people shopping at H&M are between 20 and 30"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 3.2 What is the distribution of the ages of H&M customers? "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#What is the distribution of age?\n",
    "sns.set_theme(style='darkgrid')\n",
    "ax = sns.histplot(x=\"age\", data=df, color='green', bins=40)\n",
    "\n",
    "#the distribution of age centers around 20/30 and 45/55."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 3.3 What is the most frequent postal code? "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2c29ae653a9282cce4151bd87643c907644e09541abc28ae87dea0d1f6603b1c    118002\n",
       "cc4ed85e30f4977dae47662ddc468cd2eec11472de6fac5ec985080fd92243c8       260\n",
       "714976379549eb90aae4a71bca6c7402cc646ae7c40f6c1cb91d4b5a18623fc1       158\n",
       "7c1fa3b0ec1d37ce2c3f34f63bd792f3b4494f324b6be5d1e4ba6a75456b96a7       156\n",
       "5b7eb31eabebd3277de632b82267286d847fd5d44287ee150bb4206b48439145       155\n",
       "1f5bd429acc88fbbf24de844a59e438704aa8761bc7b99fd977cad297c50b74c       154\n",
       "a1959a16bf167858c93a66ec2a330644512b25fb10f97eee2058549885af4dbd       138\n",
       "9d5787501bf1c77592156ba51eab13f4a2670c807686431a9e22a69090b02358       138\n",
       "087a46b65170845b4a55226ff1eb748ce7843d4b637cbe17f6bfbd1e645d2ffb       134\n",
       "4d22901a97bd952bb92cdd31b38c39b41dd3250a735cabdfac1503eb405b807d       131\n",
       "Name: postal_code, dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#what are the 10 most frequent postal codes\n",
    "df['postal_code'].value_counts().head(10)\n",
    "\n",
    "#the most frequent postal code appears to be a value that gives 120303"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 3.4 How many customers have a club membership?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#how many customers have a club_membership?\n",
    "sns.set_theme(style='darkgrid')\n",
    "ax = sns.histplot(x=\"club_member_status\", data=df, color='green', bins=40)\n",
    "\n",
    "#The biggest part of the customers have a club membership"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 3.5 What kind of fashion news frequency is most popular with what club membership?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "#uniting the values that all mean none but have different named values for this \n",
    "df.loc[~df['fashion_news_frequency'].isin(['Regularly', 'Monthly']), 'fashion_news_frequency'] = 'None'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['None', 'Regularly', 'Monthly'], dtype=object)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#showing the new values for fashion news frequency\n",
    "df['fashion_news_frequency'].unique()"
   ]
  },
  {
   "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>fashion_news_frequency</th>\n",
       "      <th>Monthly</th>\n",
       "      <th>None</th>\n",
       "      <th>Regularly</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>club_member_status</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ACTIVE</th>\n",
       "      <td>777</td>\n",
       "      <td>795295</td>\n",
       "      <td>470183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LEFT CLUB</th>\n",
       "      <td>0</td>\n",
       "      <td>457</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PRE-CREATE</th>\n",
       "      <td>59</td>\n",
       "      <td>79861</td>\n",
       "      <td>5704</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "fashion_news_frequency  Monthly    None  Regularly\n",
       "club_member_status                                \n",
       "ACTIVE                      777  795295     470183\n",
       "LEFT CLUB                     0     457          7\n",
       "PRE-CREATE                   59   79861       5704"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#the club_member_status against the fashion news frequency\n",
    "pd.crosstab(df['club_member_status'], df['fashion_news_frequency'])\n",
    "\n",
    "#There are no people that leave the club that have monthly news updates. \n",
    "#The people that have no news updates, which are the most people that leave the club, dont receive fashion news. \n",
    "#The most people have an active status but do not receive news updates. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# division of fashion_news_frequency\n",
    "sns.set_theme(style='darkgrid')\n",
    "ax = sns.histplot(x=\"fashion_news_frequency\", data=df, color='green', bins=40)\n",
    "\n",
    "#most people don't like to receive fashion news"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# A visual representation of the fashion news frequency and the club member status\n",
    "fashion_status = sns.countplot(y='fashion_news_frequency', hue='club_member_status', data=df, palette=\"Set3\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 3.6 What is the relation between receiving fashion news and the customers age?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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>age</th>\n",
       "      <th>16.0</th>\n",
       "      <th>17.0</th>\n",
       "      <th>18.0</th>\n",
       "      <th>19.0</th>\n",
       "      <th>20.0</th>\n",
       "      <th>21.0</th>\n",
       "      <th>22.0</th>\n",
       "      <th>23.0</th>\n",
       "      <th>24.0</th>\n",
       "      <th>25.0</th>\n",
       "      <th>...</th>\n",
       "      <th>91.0</th>\n",
       "      <th>92.0</th>\n",
       "      <th>93.0</th>\n",
       "      <th>94.0</th>\n",
       "      <th>95.0</th>\n",
       "      <th>96.0</th>\n",
       "      <th>97.0</th>\n",
       "      <th>98.0</th>\n",
       "      <th>99.0</th>\n",
       "      <th>All</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fashion_news_frequency</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Monthly</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>26</td>\n",
       "      <td>22</td>\n",
       "      <td>31</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>841</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>None</th>\n",
       "      <td>86</td>\n",
       "      <td>6405</td>\n",
       "      <td>16216</td>\n",
       "      <td>22646</td>\n",
       "      <td>33292</td>\n",
       "      <td>40891</td>\n",
       "      <td>31905</td>\n",
       "      <td>35318</td>\n",
       "      <td>37744</td>\n",
       "      <td>37778</td>\n",
       "      <td>...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>879067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Regularly</th>\n",
       "      <td>75</td>\n",
       "      <td>2987</td>\n",
       "      <td>8107</td>\n",
       "      <td>15055</td>\n",
       "      <td>21894</td>\n",
       "      <td>26623</td>\n",
       "      <td>19948</td>\n",
       "      <td>19523</td>\n",
       "      <td>18358</td>\n",
       "      <td>17180</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>476211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>All</th>\n",
       "      <td>161</td>\n",
       "      <td>9392</td>\n",
       "      <td>24323</td>\n",
       "      <td>37707</td>\n",
       "      <td>55196</td>\n",
       "      <td>67530</td>\n",
       "      <td>51869</td>\n",
       "      <td>54867</td>\n",
       "      <td>56124</td>\n",
       "      <td>54989</td>\n",
       "      <td>...</td>\n",
       "      <td>16</td>\n",
       "      <td>17</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>13</td>\n",
       "      <td>1356119</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4 rows × 85 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "age                     16.0  17.0   18.0   19.0   20.0   21.0   22.0   23.0  \\\n",
       "fashion_news_frequency                                                         \n",
       "Monthly                    0     0      0      6     10     16     16     26   \n",
       "None                      86  6405  16216  22646  33292  40891  31905  35318   \n",
       "Regularly                 75  2987   8107  15055  21894  26623  19948  19523   \n",
       "All                      161  9392  24323  37707  55196  67530  51869  54867   \n",
       "\n",
       "age                      24.0   25.0  ...  91.0  92.0  93.0  94.0  95.0  96.0  \\\n",
       "fashion_news_frequency                ...                                       \n",
       "Monthly                    22     31  ...     0     0     0     0     0     0   \n",
       "None                    37744  37778  ...    12    10     4     2     8     3   \n",
       "Regularly               18358  17180  ...     4     7     0     1     2     0   \n",
       "All                     56124  54989  ...    16    17     4     3    10     3   \n",
       "\n",
       "age                     97.0  98.0  99.0      All  \n",
       "fashion_news_frequency                             \n",
       "Monthly                    0     0     0      841  \n",
       "None                       3     5     8   879067  \n",
       "Regularly                  1     2     5   476211  \n",
       "All                        4     7    13  1356119  \n",
       "\n",
       "[4 rows x 85 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#fashion news in relation to age \n",
    "pd.crosstab(df['fashion_news_frequency'], df['age'], margins=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x18105b2da60>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1221.42x360 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#fashion news frequency in relation to age \n",
    "sns.displot(data=df, x=\"age\", hue=\"fashion_news_frequency\", col=\"fashion_news_frequency\")\n",
    "\n",
    "#the highest amount of customers don't receive fashion news\n",
    "#There are almost no people that receive fashion news monthly"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4. Exploring H&M's dataset sales to figure out the latest trends\n",
    "This section will try to answer the following questions:\n",
    "1. What are the most sold articles?\n",
    "   - What is the most sold article?\n",
    "2. What are the most sold types of articles?\n",
    "3. What are the worst selling articles?\n",
    "   - What is the least sold article?\n",
    "4. What are the worst selling types of articles?\n",
    "5. What color is the most popular?\n",
    "6. What was the most succesful week in sales?\n",
    "7. Do expensive (categories) sell better than cheaper articles? "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This loads the reduced transaction (sales) dataset.\n",
    "customers = pd.read_csv('data/customers.csv', low_memory=False)\n",
    "articles = pd.read_csv('data/articles.csv', low_memory=False)\n",
    "transactions = pd.read_csv('data/transactions_reduced.csv', low_memory=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 4.1 What are the most sold articles?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "751471001    4037\n",
       "918292001    3552\n",
       "706016001    3471\n",
       "448509014    2948\n",
       "751471043    2939\n",
       "915526001    2936\n",
       "916468003    2769\n",
       "896152002    2728\n",
       "915529003    2697\n",
       "866731001    2561\n",
       "Name: article_id, dtype: int64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# What are the most sold articles?\n",
    "transactions[\"article_id\"].value_counts().head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 4.2 What is the most sold article?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# The most sold article\n",
    "import os\n",
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "from matplotlib import pyplot as plt\n",
    "import matplotlib.image as mpimg\n",
    "\n",
    "img = mpimg.imread(os.getcwd()+'/photos/'+str(751471001).zfill(10)+'.jpg')\n",
    "imgplot = plt.imshow(img)\n",
    "plt.show()\n",
    "\n",
    "# The most sold article is a pair of black trousers."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 4.3 What are the most sold types of articles?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Amount of sales')"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# What are the most sold types of articles?\n",
    "df = pd.merge(transactions,articles, on=\"article_id\", how=\"inner\")\n",
    "df[\"product_type_name\"].value_counts().head(10).plot.bar(color=\"lightblue\")\n",
    "\n",
    "plt.title(\"Top 10 most sold types of items\")\n",
    "plt.xlabel(\"Type of product\")\n",
    "plt.ylabel(\"Amount of sales\")\n",
    "\n",
    "# The most sold type of item appear to be trousers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "738675001    1\n",
       "786101003    1\n",
       "733753001    1\n",
       "738572002    1\n",
       "549914003    1\n",
       "642230006    1\n",
       "778833003    1\n",
       "689389052    1\n",
       "679687028    1\n",
       "865792012    1\n",
       "Name: article_id, dtype: int64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# What are the worst selling articles?\n",
    "transactions['article_id'].value_counts().tail(10)\n",
    "\n",
    "# These are 10 of the worst selling items in the transactions file.\n",
    "# Of course there will also be items that aren't sold at all.\n",
    "# These articles understandably don't appear in the transaction file.\n",
    "# The amount of articles without sales will most likely be far too many to give as a reasonable output.\n",
    "# Therefore we have decided to not consider items with 0 sales."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 4.4 What are the least sold articles?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Object `article` not found.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# One of the least sold articles\n",
    "import os\n",
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "from matplotlib import pyplot as plt\n",
    "import matplotlib.image as mpimg\n",
    "\n",
    "img = mpimg.imread(os.getcwd()+'/photos/'+str(865792012).zfill(10)+'.jpg')\n",
    "imgplot = plt.imshow(img)\n",
    "plt.show()What is the least sold article?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 4.5 What are the worst selling types of articles?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Amount of sales')"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# What are the least sold types of articles?\n",
    "df = pd.merge(transactions,articles, on=\"article_id\", how=\"inner\")\n",
    "df[\"product_type_name\"].value_counts().tail(10).plot.bar(color=\"orange\")\n",
    "\n",
    "plt.title(\"Top 10 least sold types of items\")\n",
    "plt.xlabel(\"Type of product\")\n",
    "plt.ylabel(\"Amount of sales\")\n",
    "\n",
    "# The least sold types of item appear to be the zipper head, sewing kit and bumbag."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 4.6 What color is the most popular?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Amount of sales')"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# What color is the most popular?\n",
    "df = pd.merge(transactions,articles, on=\"article_id\", how=\"inner\")\n",
    "df[\"colour_group_name\"].value_counts().head(5).plot.bar(color=\"lightpink\")\n",
    "\n",
    "plt.title(\"Top 5 most popular colors according to sales\")\n",
    "plt.xlabel(\"Product color\")\n",
    "plt.ylabel(\"Amount of sales\")\n",
    "\n",
    "# It turns out that black is by far the most popular color."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 4.7 What was the most succesful week in sales?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\ADMINI~1\\AppData\\Local\\Temp/ipykernel_4844/1624348371.py:3: FutureWarning: Series.dt.weekofyear and Series.dt.week have been deprecated.  Please use Series.dt.isocalendar().week instead.\n",
      "  week = transactions['t_dat'].dt.week\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Amount of sales')"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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UbtjtyeMZY1o2SzJR5kDRAfbv2E/GUG+STI2MoV2YnDeN0X8cz85PtvPc2KdYdt9HVB22iQHGmK9ZkokyNcv7H8vMsmDFxMZw3PdPYPqSq8g8uy//+eNi/n3Gv9j24RbPH7s1KV5RxHNjn+IfJ/yD5Y98Svmug+EOyZigWZKJMkU1SWZI/cvJNLd2XZM5+9HzOPfZi6gsr+SVC//NuzfPsw/DZrD2FeWlc2dxaPdBYuJi+OB/3mfm0H8y7+o32PzuRltrzkQ8z5eVMaFVnF9I+96pJKYmhfyx+0zI5jsLe7Hsr0v54u+fsPGtDZx+xxhk6iBPVgyIZtVV1Xz0h8V89sDHdD2lO+c8fj59hnRl9XsbWPPcCvSF1ax/9UuSe6QwYOog5DuDSc3sEO6wjfkWa8lEmeL8QtI9Ho9pSHzbeE67fTSXvjODDtkdefemebx6yQvsXrsrbDG1NOV7ynlz+st89sDHDLpiKBe+fCltu7QDnBbqqLvGc9Xya5j46Hl0kjSW3fcRzwx/nFcveQF9YRWVB20zOhM5LMlEkUNlhygt2BOS8ZjGpA3K4OLXpzL2ngmUrCji+XFP8Z8/LaayvLLxg1uxXWuKeXHiM2z94CvG3jOBcfdMIDYh9lv1YhPjyLmgP+c9dwmXf3o1w39xOnu/KmP+9XOZedw/WfCzd9j52Q6bXm7CzrrLokjJyiKg4eX9Q8kX42PwFUPJOqcvi+9YwLJ7P2Lty8qYv5xJr7F9wh1exFn/xlrm3zCXhOQELnz5MroND25VhZQeKZz8kxGcdMupbPtwC6ufXYH+exUrn1xOp4HpDJw+hP5TBtImrY3Hz8CYb7OWTBQpCuHMsqZo27kdZ/19Eue/MBmA1y+dzds/msP+wv1hjiwy+Kv9fPSnxcz7r9fpNCCNKW9PDzrBBPLF+OgxshcT/i+XK/N/yNi7JxCXFMvi29/nyaH/YN73X2fT/AKbLGBCyloyUaQ4v5C2ndvRrsux7YnjlV5j+zB1wRV8+r8f8ekDH/Pguw8y4tejGTh9SKudGHCo7BDvXJfHprc2MGD6YMb86Uziko79zzKxfSKDrxzK4CuHUrKqiDWzVqIvrmb962tp1y0ZmTqIgd8ZTGp2x2Z4FsbUz1oyUaRoeSHpEdJVVp+4pDiG/2IkU9+/gi7HdeH9H7/Nqxf9u1VODNi9dhezz3mWr97dyOg/nsH4+yY2S4KpLW1QBiN/N44rv7iGsx87j7TBGXx2/8c8M+IJXrno36x5fhUV+22ygPGGtWSiRGV5Jbu/LCHz7OxwhxKUjv06ceV7V7Lw/g/58M6FPD/+X5x40ymcdPNwYhOj/9dy47z1vP2jPOKSYjn/xcn0OL2X548ZmxBL3/P70/f8/uzbvhd9fhWrn13BuzfOZdEv36XfxcLA6UPofGLXFtey9Ff72b9jH6Ub91C2qZS9m0rpP6EvHU7uGu7QWr3o/2tuJXatKcZf5ScjwsZjGuKL8TFoxnFknpXN4l8vYNk9S1n3ijL2ngkh+dANB3+1n0/u+4j//HkJGcd34ZwnzielZ/uQx5HcLYWTbjmVE28ezvalW1n97Aq+nL2aVf/Kp6OkMXDaYPpfOoi2GW1DHlt9KssrKdtcStmmUso27qF0o/N/2aZSyjaXUlX+zSWNlt37ESf9+FSG//fp+GJaVtKMJpZkokQol5Npbm07t+Oshychlw1i4c/n8+pFLzBg+mBOv2MMSR2jZ0bU4X2HmX99HgV56+k/ZSDj/jqh2VfKbiqfz0f303rS/bSejP7DeNa9oqx+diVLfrOQpXd9QJ+J2QycPoTeZ2QSE+dt77rf7+fQ7vIjrZEjSWTjHko3lbJ/+z4ImJEd1zae1MxUOuR0os+ELNr36UD7zFRSMzvQtnM7lt31AZ/c9xHFK4uY8FAuie0TPY3f1M2STJQoWl5IQvtE2vdJDXcoR633GZlMXXgFy/66lM8fWsamtzYw8rfj6Dd5QIvrvqltz4bd5F35GnvW7WLk78Yx9JoTIu45JaQkMujyoQy6fCi7tMRp3bywioI562jbpZ0zWWDaEDr0PfrJAtVV1ezburfO1kjpxlIOlx36Rv22ndvRPjOVnqN6075P6pEk0j6zA23S2zT4Gp7/yPkk53Rk8e3vMzt3FpOeuvCYYjdHx3bG/FomLXhnzNm5zxKbGMdFr1z2rfta4k58xSuKeP/Wtyn8dAe9xvVhzJ/PJDWrQ9jjOhqb5hfw9g/nEBPnY+I/z6PnmN4REVcwqiqq2PR2AaufXcHmdwrwV/vpdmoPBkwfTM75/YlPTvhWXBX7KyjbVKs1sqmU0o172PtVGdUVX0+hjomPIaVXeydx9EmlfWYHUjOd/9v3TiW+3dG39Gri2rr4K+b94A2qK6o56x+T6HNm1jG9JseqJf49NqSxnTEtyXwtkxaaZKqrqnk0+0EGXzGUkb8bFzFxNaaxuKqrqlk58wuW/n4x1ZVVnHLraRz/o5OIjf/2FfChjCtYfr+fzx74mKW//4C0QRnkzrzgmFqa4X4f9+/Yh/57FWtmrWTP+t3Et4sn5yKhc780tq8sdFsnpRyodf1TQkrCN5JHambqka6t5B4pxMR60w0X+Hrt/aqMvCtfpXhlESP+ZxQn3HhK2FqS4X4f6+NVkrHusiiwZ91uKg9WtsjxmIbUbCWQNSmHRb98j6V3fcCXs9cw7q8T6Hpy0y9WDKWK/RW8e/M81r/2JTkXCePvm3hM38ojQbuuyZx403BOuPEUdny0jdWzVrD2ZWX1gQradUsmNTOV3mdmOokkoGsrsWNS2LsGU3q15+I3vsN7t7zF0rs+oHhlkfOetG3Z70lLYEkmChQt3wm0zEH/YCR3SyF35gUU5K1j4S/f5aVzn2PIVcdz6v+MisjB3NKNe8i78jV2awmn/Xo0w64/Oewfss3J5/PRbUQPuo3owZg/n0lGRgq790b+tg7xbeM56x+TSB+SwdLff8CedbvJnXkBKb1CP7uvNbGLMaNAcX4RsUmxdOzXKdyheCorN4dpH1zFcT84gRUzv+C5UTNZ//qXEbUI5FcLNvHi2c+yf9tezn32Yk64IXzdMqEQlxTnyQWkXvH5fJx403DOfeYiyjaV8sLEZ9i65KtwhxXVLMlEgeIVhaQNyvB8imkkSEhOYPTvxzN57nTapLdl3vffIO+KV9m7Nbx93H6/n88fWsYbU1+iXZd2TJk3nd5nZIY1JlO/PhOymTx3Gkkdk3h9ymxWPP55RH1ZiSbR/6kU5fx+v7OHzJDo7CqrT5cTujLlrRmcdscYtizazKyRM/niH5+GZfHHigMVvPOjPJb8ZiFZuX2ZPGearQnWAnTM6cTkudPpNb4PC3/xLu//9G2qDtlWFM3NkkwLt3dzGYdKD7WoK/2bS0xcDCdcfzLfWXgl3U/r4VwPcc6sI6tRh8Ler8p4+fznWfvyGob/ciRnP34+8ckJIXt8c2wS2yeS+9SFnHjLcFY/vYJXL3mRAzttdfDmZEmmhTuyvH8Yd8MMt/a9Uzn32Ys565/nsm/bXl486xkW/3oBFfsOe/q4Wxd/xQsTn6Fs4x4mPX0RJ//41Kgef4lWMbExjPjVKCY+eh7FKwt5YeIz7PxsR7jDihqWZFq44hWF+GJ9pA1MD3coYeXz+eh3kTBt8VUMnDGELx7+hFljnmTj2xua/bH8fj/LH/2M16a8SFKnNkyeN53Ms1rGwqSmfjkX9OeSN6YRExfDKxc8z5rnV4U7pKhgSaaFK1peSMf+nVrUDB8vJXVIYtxfz+Li16YS3y6BOTNeYd4P3mD/zn3Ncv7K8krevWkeH/zqPfqclc2UudPomBPds/pak/QhGUx5awZdT+nOuzfOZfGvF1BdaZu8HQtPP5lE5A6gZp2TN1X15yLyBDAKqOn4vFNVXxaRYcCjQHtgIXCtqlaKSG/gaaAzoMAMVd0nIh2AZ4BsoAi4TFV3iEgC8BhwMnAQmK6qa7x8nuFUnF941MuURLNuI3pw2fzv8tmDH/PJfR/x1fubGHHbKAZfMfSoV+Tdt20vc7/3GoWf7eTkW0dwyq2n2eq+UahNWhvOe/4SltyxgC8e/oSS1cVM/OekqFqsNZQ8a8mIyARgInACMAw4SUQuxvnwH6Oqw9x/L7uHPA3coKr9AR9wtVv+EPCQqg4AlgG3u+V3AYtUdSDwCPA3t/wmYL9bfgsw06vnGG4HCvdzYOd+MoZ2CXcoESk2IZaTfzKCqe9fQcbQziz8+XxePv95dq0pbvK5ti/dygsTnmH3l7s4Z+YFDP+5LR8fzWLjYxn9hzMY/7eJbPtwCy9OfJaS1U3/vTHedpdtB36qqodVtQJYDfR2/z0uIstF5E4RiRGRPkAbVV3qHjsTuFRE4oExwIuB5e7P5+K0ZABmAblu/SPlqroQyHBbQ1GneEXN8v6RvRtmuHXo25ELZk/hjPvPZs/6Xfz7zKf56I+LqTwY3G6QK2Z+wauXvEBC+wQmz51O9qQcjyM2kWLgtCFc9MqlVJZXMjt3FhveXBvukFocz7rLVHVlzc8i0g+n22w0MA64DigF3gC+D6zASUo1tgM9gXSgTFUra5UDdK85xu1WKwMyAstrHbM5mLjdhd6OWkZGyjEd3xRr1pcCMGBcNkmpSQ3WDWVcTRHKuDrfOIKTpg3lrZ++xSf3fUTB62s57x/nkXXGt1flzchIofJQJXk35vHpI5+Sk5vD5Gcnk9Sh4dfZa/Y+Nk1zxJWRK2R+2p3nL3meud97nbF3jGXsr8ceU0s2ml+v2jwfLRaRwcCbwM9UVYGLA+57ALgCWMU3tiPCB1TjtLRqX4ZbHVAnUH3H+AKOaVRLWoV509KvaN8nlb2HK9hbVP+38mhb9fVYjbznTPpc0I8FP3uHp858CrlsEKffOZY2aW2OxLVxxXbmfu91di7bzom3DGf4f5/O3oqGX2ev2fvYNM0aVzyc+8JkFv58PgvuXMDm/2zhzP/LJeEoromKttcrYBXmuu8/lqAaIyIjgfnAL1T1SRE5TkQmB1TxARXAFqBbQHlXYBtQCKSKSM3a7t3ccoCtbj1EJA5IAUoaOFfUKcovJKMVXx9zLHqO6c3U9y/npB+fytqX1jBr5BOseW4lfr+fLUu38MKEZyhZVcTER89jxK9GebYcvWk54pLiGP+3iYz6/Tg2vrWBlybNonTD7nCHFfG8HPjvBbyCM7vrObfYB/yviHR0x0+uAV5W1U1AuZuUAC4H8tyxnEXAVLf8CiDP/XmOexv3/kVu/SPlIjIKKFfVoLrKWpJDZYco21gatSsvh0Jcm3hO/eVILnv3u3To24l3b5rH7NxZzBw7k7jEOCbPmUbOBf3DHaaJID6fj6FXn8j5/57M/p37efHsZ9n83sZwhxXRvPx6diuQBNwrIp+LyOfA6cAfgcU4XWSfq+ost/4M4D4RWQMkA/e75dcB14jIKpwxndvc8tuBESKy0q1zvVv+AJDolt+Pk7CizteD/pZkjlWnAelc/PpUxt49gT3rdpM5LpMpb08nbZBNqDB16zm6N5e+NYPkHim8Oe1lPn9omS2wWQ/bGfNrmbSgnTG/+MenLL79fa7K/yFtu7SLmLiaIhLjqjpcRZfuqRQXN8/Fm80pEl8vaN1xVew77GxO9/pa+k8ZyLi/TiCuTcMboUXb69XYzpjW0dxCFecX0rZLu0YTjGma2IRYW3/MBC0+OYGJj57H8F+O5MvZq3n5gn+HfduJSGNJpoUqyt9pXWXGRACfz8fJPz6VSU9dyJ71u3nxrGfYvnRruMOKGJZkWqDKgxXs/nJXq1ze35hIlXl2XybPnUZC+wRenfwCK59aHu6QIoIlmRaoZE0J/iq/tWSMiTCd+qcxZd50eo7uzYJb32HBz96h6nBVuMMKK0syLVCxu4eMtWSMiTyJqUlMeuYiTrjhZFY+uZzXprzIgaID4Q4rbCzJtEBFywtJTE0kpXf7cIdijKlDTGwMp/16DGc9PInCz3fw4sRnKFq+M9xhhYUlmRaoeEUhaUMybBaUMRGu3yUDuOSN7wDw0nnPsfalqN11pF6WZFqY6spqSlYVkXGcLe9vTEuQMbQLU96aQedhXXn72jks+euScIcUUo0mGRFpKyIj3J+vFZHHonXp/JZgz7pdVJVX2fL+xrQgbTPacsGLU+g1rg+L/7yY6qrWs9tmMC2ZJ4ALReQU4OfAVzibhJkwKFpug/7GtESxCbEMnDGEA0UH2PFxVK7ZW6dgkky2qv4SOB+Yqaq/AWxT8zApzi8kNimWDravvDEtTu8zs4hNiKVgzvpwhxIywSSZmoV4zgbedZfdP7advcxRK1pRSPrgDGLibDjNmJYmITmB7AnZFMxZ12oW1Azmk2qJuwJyG2AJ8I77z4SY3++nOL+I9CHWVWZMSyUXCWWbSylZVRzuUEIimCRzI86+L6NVtRq4B7jZ06hMnco2lXK47JBd6W9MCyYXCPigIG9duEMJiUaTjKpW4ewu+TMRaQu0d5ONCbGaK/0tyRjTciV3SabrKd0pyGsd4zLBTGH+BfAj4DKcLrM7ROR2rwMz31a8oghfrI+0genhDsUYcwyycnMozi+kbHNpuEPxXDDdZd8BJgH7VbUEGAFM9zQqU6ei5Tvp2D+NuKS4cIdijDkG2bl9ASiYG/2tmWCSTIWqHqq5oap7gArPIjL1Ks4vsutjjIkCqdkd6TQwrVWMywSTZL4SkXMBv4gkisj/AJs8jsvUcmDnfg4U7id9qCUZY6JBVm4O2z/cysGSg+EOxVPBJJkbgJ8AQ4H9QK5bZkKoaIVd6W9MNMnKzcFf7WfT2xvCHYqnGu3cV9VtwJnuzLJYVbUNrMOgZjmZ9CG2Zpkx0SBjaGeSe6RQMGcdA74zONzheKbeJCMi99dTDoCq3uRRTKYOxfmFtM9MJSElMdyhGGOagc/nIyu3L6ufWUHFgQri28Y3flAL1FB3WUkj/0wIFecXkjHUlvc3Jppk5eZQebCSr97bGO5QPFNvS0ZV76zvPhFp5004pi6HSssp21TKwO8eF+5QjDHNqNuIHiR2SKQgbz3Z5/YLdzieaHRMRkQuBH6LsyimD4jFWYU5xdvQTI3iFUUAZNgeMsZEldj4WDIn9mXjW+uprqyOyoVvg3lG9wB/ADYD1wFzgYe9DMp805HlZGxhTGOiTlZuXw7tOcS2D7eEOxRPBJNk9qvq88BSoBxniZnzPI3KfENRfiHturajbWfrpTQm2vQal0lsUmzUXpgZzPok5SKSCKwDhqnq+yIS1EYIInIHzppnAG+q6s9FZAJwL846aM+r6m1u3WHAo0B7YCFwrapWuls9Pw10BhSYoar7RKQD8AyQDRQBl6nqDhFJAB4DTgYOAtNVdU0w8Uaq4vxCWxTTmCgV3y6e3uMyKchbz6jfj8fn84U7pGYVTEvmNeBNnG6yn4jIbKDRjRDcZDIROAEYBpwkItOAx4ELgYHAKSKS6x7yNHCDqvbHGfu52i1/CHhIVQcAy4CaxTnvAhap6kCc7aD/5pbfhNP6GgjcAswM4jlGrMqDFexeu8uSjDFRLGtSDvu27j3SNR5Nglnq/w/Af6nqVpzksBCYEsS5twM/VdXDqloBrAb6A2tVtUBVK3ESy6Ui0gdoo6pL3WNnuuXxwBjgxcBy9+dzcVoyALOAXLf+kXJVXQhkuK2hFqlkdTH+Kr+NxxgTxfqclY0vxseGOdHXZRbMUv9tge7uzVNxlpdJauw4VV1ZkzREpB9Ot1k1TvKpsR3o6Z6/rvJ0oMxNSIHlBB7j3l8GZDRwrhapON+dWWZrlhkTtdqktaHbaT2iclwmmDGZJ4ANIlIF/Bx4Cqd76uxgHkBEBuN0t/0MqMRpzdTw4SSeGMAfRDlueU2dQI2dKyhpacnBVq1TRkbzzuzeu3YXSR2TyD6xxzH11TZ3XM3F4moai6tpWlJcx106mHm3zCO2tIJOOZ3CEJU3r1cwSSZbVaeKyG+Bmar6WxH5OJiTi8hIYDZwi6o+JyJjgW4BVboC24At9ZQXAqkiEuvu0NnNLQfY6tbbIiJxONftlASca32tcwWlpGQf1dVBzWv4loyMFIqKmndpty0fbyVtcAbFxfuO+hxexNUcLK6msbiapqXFlTHK6XBZ9vQXnHD9yaEO66hfr5gYX4NfzoMZ+K9ZUOds4F0RicW5MLNBItILeAVndtdzbvFHzl2S455nOpCnqptwZrGNdOtd7pZXAIuAqW75FUCe+/Mc9zbu/Yvc+kfKRWQUUK6qm4N4nhGnurKaktXFNuhvTCvQvncq6UMyoq7LLJiWzBIRWYXT1bUEmA+8E8Rxt+KM3dxbs6gmzkWcV+G0bpJwEkLNoP4M4BERaQ98CtQs0Hkd8KSI3IZzQeg0t/x2YKaIrAT2uMcDPAD8wy0/hJOwWqTda3dRVV5ly/sb00pkTcrh47s/5EDh/qi5Li6YJHMjcBqQr6rVInIPX7cm6qWqNwM313P38XXU/wIYXkf5JmBcHeW7gAvqKC8HrmwsvpbgyPL+lmSMaRWycnP4+C8fsnHeegZdPjTc4TSLYPaTqQI+CLj9pqcRmSOKVxQS1yaODjkdwx2KMSYE0gal0753KhvyoifJRN9qbFGkOL+QtEEZxMTa22RMa+Dz+cialMOWhZs5vO9wuMNpFvV+erlLyZgw8Vf7bTkZY1qhrEl9qT5cxeZ3N4Y7lGbR0FfkBQAi8ucQxWIClG0q5fDew7a8vzGtTNdTupOU1oaCOWvDHUqzaGhMpquI/AqYLiI7a9+pqvd6F5YpXmGD/sa0RjGxMWSenc2G19dSdbiK2ITYcId0TBpqyVwN9AXaAsfV+jfE+9Bat6L8QmLiYug0ID3coRhjQix7Uj8O7z3M1sVfhTuUY9bQ9stvA2+LyGpVvSeEMRmgeHkhHft3Ii4pmFnmxpho0nN0L+LaxlMwZx29x2eGO5xjEsy0pYdF5CERKRCRLSLyuHvBpPFQkQ36G9NqxbWJp/cZmRTMXY//KJe5ihTBJJl7gUTgYpyl/v04V9Ubj+zfuY+DRQcsyRjTimVPyuHAzv0UfrYj3KEck2D6Yk5V1SNX6IvI1cBK70IyNRsX2fL+xrRevSdkERMXw4a8dXQ5qVvjB0SoYFoycSISWC8GqPIoHkPAcjKDbfqyMa1VUockup/ek4IWvpFZMElmPvC8iJwpImfg7EL5nrdhtW7F+YWkZnUgIcWuhzWmNcvKzWHPut3sXrsr3KEctWCSzE9wusf+APwFUJwNyIxHivOLSLeuMmNavazcvgAtevn/YBbIrAR+4/4zHivfU07Z5lIGXXFcuEMxxoRZcvcUOp/QhQ1z1nHiTd9apL5FsJUXI0xJzZX+Q6wlY4xxuswKP93Bvu2Rt8tnMCzJRJii/CLAlpMxxjiyJuUAsHHuhjBHcnQaTTIi0qOOskHehGOK8wtp1y2Zthltwx2KMSYCdOzXiQ59O7bYcZl6x2REpJP74xwRGQf43NvxwEvAAG9Da53sSn9jTCCfz0dWbl++ePhTDpWWk5iaFO6QmqShlswsoBhnQcwS9+di4CvgU+9Da30qDlSwZ+0uMobY9THGmK9l5eZQXVnNpncKwh1KkzW0QObZACLyuKr+V+hCar12rS7GX+23lowx5hu6nNSNtp3bUZC3nv6TB4Y7nCYJZgrzf4lIH6ATX3eZoarWmmlmRUeWk+kS5kiMMZHEF+Mj85y+rJ29msryyha1OnswA/93AquBl4HZ7r8XPY6rVSrOLySxQyLJPVPCHYoxJsJkT+pLxf4KtizaHO5QmiSYdHgFkKOq27wOprWrGfT3+XyNVzbGtCo9RvUmISWBgrx1ZJ6VHe5wghbMdTJfWYLxXlVFFbtWF9tFmMaYOsUmxNJ7QhYb526guqo63OEELZiWzHwR+QvwKnCwptDGZJrXnrW7qDpUZcv7G2PqlZWbw7qXlZ0fb6fbiG9dwhiRgkkyV7n/XxpQ5gdaTnutBTiyvL/NLDPG1KPPmZnEJMSyIW9d9CQZVc0KRSCtXfGKQuLaxtGhb8dwh2KMiVAJKYn0HN2Lgrx1nP6bMS1i/LbRJCMiP6mrXFXvbf5wWq/i/ELSBmUQE2vLyRlj6peVm8OCW99h1+pi0gZF/oXbwXSXBa45nwCMxdnIrFEi0h5YApynqhtF5AlgFLDfrXKnqr4sIsOAR4H2wELgWlWtFJHewNNAZ5x9bGao6j4R6QA8g9NlVwRcpqo7RCQBeAw4GWf8aLqqrgkm1nDyV/spXlFE/ykt6yIrY0zoZZ3dlwU/e4eCvPUtIsk0+rVZVb8X8G8GMBznQ79BInIq8AHQP6D4ZGCMqg5z/73slj8N3KCq/XEu+LzaLX8IeEhVBwDLgNvd8ruARao6EHgE+JtbfhOw3y2/BZjZWJyRoGzjHg7vPWzjMcaYRrXt0o6uJ3dvMQtmNrlvxp3OnBlE1auB64FtACLSFugNPC4iy0XkThGJcVcTaKOqS93jZgKXikg8MIavL/ycydeTD87FacmAs8Zarlv/SLmqLgQy3NZQRCtaYcv7G2OCl5Xbl6LlhezdUhbuUBrV1DEZH05rpLCx41T1B+7xNUVdgXeB64BS4A3g+8AKYHvAoduBnkA6UObuzBlYDtC95hi3W60MyAgsr3VM0JfIpqUlB1u1ThkZTb9af/n6PcTExSCjM4lL9Ga5iKOJKxQsrqaxuJomWuM66bvH8+FvF1G0aAvZN53aTFF583o1dUzGj/OB/bOmPpCqbgAurrktIg/grCawyj1vDR9QjdPKCizHLa+pE6i+Y3wBxwSlpGQf1dW1HzY4GRkpFBU1ffe6TUu/oqOksbvsYOOVj8LRxuU1i6tpLK6mieq4OiTQaUAa+S+sJHta82zvdbRxxcT4GvxyHswU5u8BuN1a8ap6VB2BInIc0F9VZ7tFPqAC2AJ0C6jaFaeLrRBIFZFYVa1y69SsPLDVrbdFROKAFJztCGrOtb7WuSKW3++nOL+IPhNsprgxJnhZuTl8ev9/KN91kKRObcIdTr2CWSAzR0RWAp8Dn4jIehE5mmlQPuB/RaSjO35yDfCyqm4CykVkpFvvciBPVSuARcBUt/wKIM/9eY57G/f+RW79I+UiMgooV9WIXk3uwM79HCw+QPpxkT9LxBgTObJy++Kv8rPxrcjeljmYgf8Hgb+oakdVTcWZ2fV/TX0gVV0O/BFYjNNF9rmqznLvngHcJyJrgGTgfrf8OuAaEVkFjAZuc8tvB0a4ye86nAkGAA8AiW75/TgJK6IdWd7/OFve3xgTvIzju9Cue3LEzzILZkymi6o+WXNDVZ+o7wLNuqhqZsDPD+FMS65d5wucqdG1yzcB4+oo3wVcUEd5OXBlsLFFguLlheCDNNsN0xjTBD6fj+zcHFY/u4KKAxXEt40Pd0h1CqYlEycinWpuiEg63x6QN0epKL+Q1KwOJCQnhDsUY0wLk5WbQ+XBSrYs2BTuUOoVTEvmAWCpiDyPk1y+A9znaVStSPGKQjqf0DXcYRhjWqBup/UgsUMiG+asIys3J9zh1CmYK/7/CVyLs6RMW+A6Vf2714G1BuV7ytm7uYwMuwjTGHMUYuNj6XNWNhvf2kB1ZWTuMRPsFf+rgCeBx4FtItI8E7NbueJ8W97fGHNssnJzOLS7nO0fbQ13KHUK5or/e3Fmb5W6RT6cbjP7ZDxGxUdmltlLaYw5Or3HZxKbFMuGOevoMbJXuMP5lmDGZC4BuqtqidfBtDZF+YW0655Mm/S24Q7FGNNCxbeLp9fYPhTkrWPUXeMibo+ZYLrLvgT2eBxHq1ScX2itGGPMMcualMO+LXspdhfbjSTBtGTuBxaIyHs4y8AAoKq/9SyqVqDiQAV71u2m7/n9G69sjDENyDwrG1+Mj4I56yLui2swLZlfAGVAB5yVjmv+mWNQsqoIf7XfBv2NMcesTXpbup3anQ1zIu/q/2BaMu1UdZTnkbQyxflOszZjqCUZY8yxy5rUj8W3v09pwR5SszqEO5wjgmnJqIgM9TySVqYofyeJHZNI7hGZ+10YY1qWrHP6AlAwd30jNUMrmJZMb2CZiBQAh9wyv6oe711Y0a84v4iMIZ0jbiaIMaZlat8nlbTBGRTMWcewH50U7nCOCCbJ/DLg53ic8ZgfexNO61BVUUXJ6mKG/mBYuEMxxkSRrNy+LPvrUg4UHaBtRmRcGhHMsjILgOXACOAJnFWU8xo8yDRo95e7qD5cRcZQW97fGNN8sif1Az9sfCtyuswabMmIiAC34OzLshFoA2SqamkDh5lG2HIyxhgvpA1OJ6V3ewry1jNoxnHhDgdooCUjIm8CC3GujRmnqkOAvZZgjl1RfiFxbeNIze4Q7lCMMVHE5/ORlZvDlgWbOLzvcLjDARruLjsR+ARYAdRMvrZ9ZJpBcX4haYMyiIkNdn1SY4wJTvakHKoOVfHVexvDHQrQcJLpBcwEpgHbReQFnO4ycwz81X6KVxTZ9THGGE90PaU7SWltIubCzHqTjKpWquq/VXU8cBKwHUgSkbUicm3IIowypRv3ULHvsI3HGGM8ERMXQ+bEbDa9XUDV4apwhxPcfjKqukpVbwJ6AHcD13gaVRSz5f2NMV7Lys3hcNkhti3ZEu5QgrpO5ghVPQD80/1njkJRfiEx8TF0krRwh2KMiVK9xvYmrm0cBXnr6DWuT1hjsZHnECteXkgnSSM2sUn53RhjghbXJp7e4zMpmLsef3V452tZkgkhv99P8YpCG48xxnguKzeH/dv3Ufj5jrDGYUkmhPbv2MfB4oOWZIwxnuszMRtfrI+CvPBe/W9JJoSOLO9vScYY47GkDkn0OL0XBXnhncpsSSaEipbvBB+kD7Y934wx3sua1JfdX+5i97pdYYvBkkwIFecX0iG7I/HJCeEOxRjTCmSekwNAQRgvzPR0ipOItAeWAOep6kYRmQDci7NywPOqeptbbxjwKNAeZ720a1W1UkR6A08DnQEFZqjqPhHpADwDZANFwGWqukNEEoDHgJOBg8B0VV3j5XNsiuIVRXQ5qVu4wzDGtBIpPVLIGNaFgrz1nHjT8LDE4FlLRkROBT4A+ru32wCPAxcCA4FTRCTXrf40cIOq9gd8wNVu+UPAQ6o6AFgG3O6W3wUsUtWBwCPA39zym4D9bvktOMviRITy3QfZ+1WZjccYY0IqKzeHnZ9sZ/+OfWF5fC+7y64Grge2ubeHA2tVtUBVK3ESy6Ui0gdoo6pL3Xoz3fJ4YAzwYmC5+/O5OC0ZgFlArlv/SLmqLgQy3NZQ2NUM+tvMMmNMKGXnhndbZs+SjKr+QFUXBRR1x1n/rMZ2oGcD5elAmZuQAsu/cS73/jKcHTvrO1fYFdkeMsaYMOgoaaRmdwjbLLNQXnYewze3CvAB1U0oxy2vqROosXMFLS0tuSnVvyUjI6XO8n1rd9O+Z3t6DwhPkqkvrnCzuJrG4moai8sxePIglv7vUlIS4klKTaq3nhdxhTLJbAECR7274nSl1VdeCKSKSKyqVrl1arretrr1tohIHJAClASca32tcwWtpGQf1Ue5DENGRgpFRXvrvG/Lsq10GpJR7/1eaiiucLK4msbiahqL62tdxvam+u4lfPpcPv0uGdCsccXE+Br8ch7KKcwf4ezonCMiscB0IE9VNwHlIjLSrXe5W14BLAKmuuVXAHnuz3Pc27j3L3LrHykXkVFAuapu9vh5NapifwW71+4ifYhdH2OMCb2uJ3ejTUZbNoShyyxkSUZVy4GrgNnAKmANXw/qzwDuE5E1QDJwv1t+HXCNiKwCRgO3ueW3AyNEZKVb53q3/AEg0S2/HydhhV3JqiLw25X+xpjw8MX4yDqnL5vfKaDqUGXjBzQjz7vLVDUz4Of5wPF11PkCZ/ZZ7fJNwLg6yncBF9RRXg5ceUwBe6BmD5n0oV3CHIkxprXKmpTDqn/ls2XRZvpMyA7Z49oV/yFQlF9IUqckkrsf26QCY4w5Wj1H9SI+OSHkC2ZakgmB4vxC0od0xuerPSnOGGNCIzYxjj4TsijIW091VZMm3R4TSzIeq6qoomRNiV0fY4wJu6zcvhwsPsDOT0K3x4wlGY/t1l1UH64iY6glGWNMePU+M4uY+BgK5qwN2WNakvFYUf5OwK70N8aEX2L7RHqO7s2GOevw+0OzLbMlGY8V5xcS1zaeDtkdwx2KMcaQlZtD2cZSdmtJSB7PkozHivOLSB+cgS/GBv2NMeGXeY4zfXlDiPaYsSTjIX+1n+IVhTYeY4yJGO26JNPlpG4hm8psScZDpQV7qNhfYeMxxpiIkj0ph6IvdrJ3q/drqFmS8ZAt72+MiURZk5xtmTfO9b7LzJKMh4rzC4mJj6GTpIU7FGOMOaJD34507N8pJOMylmQ8VLS8kE4D0olNiA13KMYY8w1Zk3LYtmQL5bsPevo4lmQ84vc7g/7px9ny/saYyJOVm4O/ys+mtws8fRxLMh7Zv30f5SUHbXl/Y0xE6nx8F9p1S/a8y8ySjEeOLO9/nC3vb4yJPDV7zHz13kYqDlR49jiWZDxStLwQfJA+KD3coRhjTJ2yJuVQebCSLQu920DYkoxHivML6dC3I/HJCeEOxRhj6tT99J4ktE+kwMNtmS3JeKRoRaFdH2OMiWix8bH0OSuLjfPWU13pzR4zlmQ8UL7rIPu27LVBf2NMxMuelEP5rnI2L/amy8ySjAfsSn9jTEvRe3wmsYmxrHlljSfntyTjgZqZZdaSMcZEuvjkBPpdMoDDew97cv44T87ayhWvKCS5RwpJndqEOxRjjGnU+PsmktE5heLifc1+bmvJeKAov8haMcaYFsMX48Pn82bPK0syzaxi32H2rNtl4zHGGIMlmWZXvKoY/Dbob4wxYEmm2R0Z9LfdMI0xxpJMcyvK30lSWhvadUsOdyjGGBN2lmSaWXF+EelDOns2iGaMMS1JWKYwi8h7QGegZunPHwIpwL1AG+B5Vb3NrTsMeBRoDywErlXVShHpDTztnkeBGaq6T0Q6AM8A2UARcJmq7gjF86o6XMWuNcUc/8MTQ/FwxhgT8ULekhERH9AfOF5Vh6nqMGA58DhwITAQOEVEct1DngZuUNX+gA+42i1/CHhIVQcAy4Db3fK7gEWqOhB4BPib98/KUbSqiOqKatKH2vL+xhgD4ekuE/f/t0TkCxG5ARgOrFXVAlWtxEksl4pIH6CNqi51j5nplscDY4AXA8vdn8/FackAzAJy3fqe2/7pdsCu9DfGmBrh6C7rCMwHbgTigfeBPwPbA+psB3oC3espTwfK3IQUWE7gMW63WhmQAWwLJri0tKMfsP/4s+0kJCeQM7wXvpjIGpPJyEgJdwh1sriaxuJqGourabyIK+RJRlU/BD6suS0ijwG/BT4IqOYDqnFaWv4gynHLa+oE8gXc16iSkn1UV9c+dXB2fLaDToPSKS5p/qUZjkVGRgpFRXvDHca3WFxNY3E1jcXVNEcbV0yMr8Ev5+EYkxklImcGFPmAjUC3gLKuOC2PLfWUFwKpIhLrlnfj65bKVrceIhKHM6GgpHmfxbf5q/3s+HyHXR9jjDEBwjEm0wG4W0SSRCQFuBL4FSAikuMmjulAnqpuAspFZKR77OVueQWwCJjqll8B5Lk/z3Fv496/yK3vqT0bdlOxv8Ku9DfGmAAhTzKq+gbwJvAZ8AnwuNuFdhUwG1gFrOHrQf0ZwH0isgZIBu53y68DrhGRVcBo4Da3/HZghIisdOtc7/VzgoAr/YdYkjHGmBphuU5GVW/n6ynHNWXzgePrqPsFzuyz2uWbgHF1lO8CLmiuWINVnF9ITHwMHSUt1A9tjDERy674byZF+UV0Oa4LsQmxjVc2xphWwpJMM/D7/RTn76TrCV3DHYoxxkQUSzLNoLqymsryKrLOyAp3KMYYE1Fs++VmEBsfy1Urfkj3zE6ebF9qjDEtlbVkmklCcoKtvGyMMbVYkjHGGOMZSzLGGGM8Y0nGGGOMZyzJGGOM8YwlGWOMMZ6xJGOMMcYzdp3M12LB2RvhWBzr8V6xuJrG4moai6tpoimugGPqXFPL5/cf3QZdUWgUzvYBxhhjmm4039x8ErAkEygROAVn6+aqMMdijDEtRSzOxpEfA4dq32lJxhhjjGds4N8YY4xnLMkYY4zxjCUZY4wxnrEkY4wxxjOWZIwxxnjGkowxxhjPWJIxxhjjGVtW5iiJyG+BKYAfeExV73XL44G5wO9U9f1IiEtErgFucsuWAT9U1cMRENePgBsAH/Am8HNVDemFW/W9j+59NwBTVHVcKGOqLy4ReQJnZYr9brU7VfXlCIjrNOA+IAVYDlwZ7t8vYA3wh4AqPYCPVPW8cMblvl4TgbtxLmL8FPhBuF8vN66rgJ/jXIz+LvBTVa081seyJHMURGQscAYwFIgHVonIm+7djwMnRlhcPwNOAvYCM4HrcT4Uwh3XT4BhQDmwEDgLeCvccamqisgg4BfAulDF01hcwMnAGFXdHuqYGohrPvAScLaqLheRWcD3gb+HMy7gHFUd5t7fFVgM/DhUMdUXl/s+PgZMVNXVIvIicAXwaATEdRdwiqpuF5GHcL6Y3lv/mYJj3WVHQVUXAOPdLN8ZJ1nvx/njuhv4KILiKgeuU9Uyt5WQD/SOgLj2A4NUdT/QAUgF9kRCXCKSCPwD+HUo42kkroM479vjIrJcRO4UkZD+/dYT1zDgQ1Vd7la7EQhp66qB368adwMPq+raCIkrFmgvIrFAEs57G+64huO8jzVfYN4ALmqOx7Mkc5RUtUJE7sT51jQf2KqqP1fVVyIsrs2q+jaAiGTgdE+9GgFxbXXLrgY24KwZ93kkxAX8EadFuiHU8TQQVzxOF8Z/ASNwFiP8fgTE1RXYJyLPicjnwJ2E+MtCPXFtBRCRfsA44P5Qx9RAXNcB7wPbgHTgxQiI6z/ACBHp5Sa/KTjv7TGzJHMMVPUOIAPoBVwd5nCOqCsuEemB88v0WDjGiuqLS1UfAdKAHcBvIiCua4DeqvpEOGIJVCuuM1X1YlXdrqoHgAeASREQVxJwNvBLnC7ZdjjdjOGOq+bv8RrgIVX91sKNYYrrduBPwBCcRSWX0gxdUs0Q11ic9+01nNXolwPNMk5kSeYoiMgAERkG4P7Bv4TTvxlW9cUlIgOAJcCTqvq7CInrVBEZ6ZZVAs8R4tewvriAwe638keBk0Xk+QiIa6qITA6o5gMqIiCuXwBLVbVAVauAf+N0vYQ7rprfpYtwfrdCrr73EVihqutVtRp4BKelFe64hgP/UdUTVPV0nBbX+uZ4PEsyRycbeEREEkUkAbiQOvZRCIO64voIZzD9NlX9awTFVQA8IyIdRMSH0zwP9WtYV1xvqepAd9D4B8AyVZ0aAXEtAP5XRDq6MxivIcRjH/XEdQ1wkoj0cuucB3wSAXF9ICLpQBtVLQhxPA3F9TQwXES6uHUuxFkiP9xxvQfMF5EUt+xGoFm+XFmSOQqqOgdnyu1nOH9QS1Q1LN+WAtUVF06fbxfgpyLyufvvt+GOS1Xvwhn7WAJ8ARwAQpoEW9L7qKq/xXm9FuP0o3+uqrMiIK5/AT8EXheRNUAnN85wx/UczofpllDGEkRcf8TpMntPRJbjzBi8NQLiegZnPG0psAJ4V1WfbY7Hs/1kjDHGeMZaMsYYYzxjScYYY4xnLMkYY4zxjCUZY4wxnrEkY4wxxjOWZIwJIRGZKyI3B9zuLyJ+EflDQFlnETkkIqlHcf6ZIhLSKbHGNMSSjDGhlQeMD7h9PvA6zgVxNc4AFqtqaSgDM8YLttS/MaGVB9whIjHusiLnA78CnhORvqq6HjgTeFNETgf+jLMeWBXO/jFvAIjI93EWWowBSoAbVHVN4AOJyH04y6tcqKr7QvP0jPkma8kYE0Kq+iWwG2dNuY6A4FxlPQe4wK12Js5KCE8Al6vqiTgtnb+LSG93P5ArgdGqegLwF765xIxPRB4E+gCTLMGYcLKWjDGhl4ezKGIh8LaqVovIG8D1IvIyzm6FHXFW6X1FRGqO8+O0TMYAOcCSgPs6ikgn9+ef4OwTMiycqw8bA5ZkjAmHPJy9YMqBV9yy+TirPk/AWVcqFlitqqfWHCQi3YEinDGdf6nqf7vlMUB3nBYSOItpLgZmisgIVQ3pas3GBLLuMmNC7z2cHSXHAvMAVPUgzmKFN+AkmaVAPxEZA+Auzb4WZ6/6ecA0Eenmnu9anCRVYxnwIM7mYb/x8okY0xhLMsaEmLuHx1rnx2/MIHsT6Ae8r6pFwGTgbhH5AvgXzvjMRlV9C2dCwNvuSr7TgUvc7bVrHsOPs4vmde4EAmPCwlZhNsYY4xlryRhjjPGMJRljjDGesSRjjDHGM5ZkjDHGeMaSjDHGGM9YkjHGGOMZSzLGGGM8Y0nGGGOMZ/4fUqOSN1ZfFK4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# How do the weekly sales compare?\n",
    "transactions['t_dat'] = pd.to_datetime(transactions['t_dat'], errors ='coerce') \n",
    "week = transactions['t_dat'].dt.week\n",
    "week.value_counts(sort=False).plot(color=\"purple\")\n",
    "\n",
    "plt.title(\"Comparison of sales per week in 2020\")\n",
    "plt.xlabel(\"Week\")\n",
    "plt.ylabel(\"Amount of sales\")\n",
    "\n",
    "# Week 32 was the most succesful in sales.\n",
    "# This week lasted from the 3rd until the 9th of August 2020."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5. Exploring H&M's dataset to build a reccomendation system\n",
    "#### Building a item based reccomendation system (using cosine similarity)\n",
    "In this chapter we will be using an item based collaborative filtering approach to reccomending items to users. The item reccomendations can be used to reccomend other items to users when they are shopping for products. The main idea is to find products that are frequently bought together.\n",
    "\n",
    "We first start by reducing the dataset even more. The current appoach of using cosine similarity could not be used on the intire dataset since the matrix would become to large to fit into memory. We reduced the dataset to only contain data after 09/01/2020 and selected the first 20 000 items that users bought in h&m stores. This does probably impact accuracy, since a lot of previous transactional data is not taken into account.  \n",
    "\n",
    "Used sources for this chapter:\n",
    "* https://heartbeat.comet.ml/recommender-systems-with-python-part-i-content-based-filtering-5df4940bd831\n",
    "* https://scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.cosine_similarity.html\n",
    "* https://en.wikipedia.org/wiki/Cosine_similarity\n",
    "* https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.transpose.html\n",
    "* https://www.datasource.ai/uploads/6b86b1630562b323a26143f90d97fe08.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "customers = pd.read_csv('data/customers.csv', low_memory=False)\n",
    "articles = pd.read_csv('data/articles.csv', low_memory=False)\n",
    "transactions = pd.read_csv('data/transactions_reduced.csv', low_memory=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>t_dat</th>\n",
       "      <th>customer_id</th>\n",
       "      <th>article_id</th>\n",
       "      <th>price</th>\n",
       "      <th>sales_channel_id</th>\n",
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       "      <td>2020-09-02</td>\n",
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       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "             t_dat                                        customer_id  \\\n",
       "1233294 2020-09-02  0001f8cef6b9702d54abf66fd89eb21014bf98567065a9...   \n",
       "1233295 2020-09-02  0006bfcec82c6c132276c0a5549ae13645c9ab77b0243f...   \n",
       "1233296 2020-09-02  0006bfcec82c6c132276c0a5549ae13645c9ab77b0243f...   \n",
       "1233297 2020-09-02  0006bfcec82c6c132276c0a5549ae13645c9ab77b0243f...   \n",
       "1233298 2020-09-02  000ed4cabda96069b547ae531c66de5f1bf6a7e5b83aa8...   \n",
       "\n",
       "         article_id     price  sales_channel_id  \n",
       "1233294   820671001  0.016932                 1  \n",
       "1233295   882354001  0.015237                 2  \n",
       "1233296   817354001  0.025407                 2  \n",
       "1233297   817354001  0.025407                 2  \n",
       "1233298   899002003  0.010153                 1  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Reducing the dataset even further\n",
    "articles = pd.read_csv('data/articles.csv', low_memory=False)\n",
    "transactions = pd.read_csv('data/transactions_reduced.csv', low_memory=False)\n",
    "transactions['t_dat'] = pd.to_datetime(transactions['t_dat'])\n",
    "mask = transactions['t_dat'] > '09-01-2020'\n",
    "transactions = transactions.loc[mask]\n",
    "transactions.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
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       "        article_id                                        customer_id  \\\n",
       "41916    568601043  00000dbacae5abe5e23885899a1fa44253a17956c6d1c3...   \n",
       "213512   794321007  000058a12d5b43e67d225668fa1f8d618c13dc232df0ca...   \n",
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       "87922    685814001  000172a9c322560c849754ffbdfdb2180d408aa7176b94...   \n",
       "\n",
       "        quantity  \n",
       "41916          1  \n",
       "213512         1  \n",
       "15137          1  \n",
       "123249         1  \n",
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      ]
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     "execution_count": 36,
     "metadata": {},
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   ],
   "source": [
    "# Selecting only relevant data and count how many articles customers have bought\n",
    "collaborative_filtering_df = transactions[['customer_id', 'article_id']]\n",
    "collaborative_filtering_df = collaborative_filtering_df.groupby(['article_id', 'customer_id']).size().reset_index()\n",
    "collaborative_filtering_df = collaborative_filtering_df.set_axis(['article_id', 'customer_id', 'quantity'], axis=1, inplace=False).sort_values(by=['customer_id'])\n",
    "collaborative_filtering_df.head()"
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  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
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       "article_id                                          111565001  111586001  \\\n",
       "customer_id                                                                \n",
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       "\n",
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       "customer_id                                                                \n",
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       "customer_id                                                                \n",
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       "...                                                       ...        ...   \n",
       "075083cf54e37abbfb4fc5be69b8556acc14008318f0537...        NaN        NaN   \n",
       "0751425041cd8f0f5975e8594d99eff7e7cbb8ad639de18...        NaN        NaN   \n",
       "0751a0dcf7a097889c6086860067230972601507675e1d7...        NaN        NaN   \n",
       "0751e6551ef6b6ca840db0e4a86d2a9227f1494963ca9d9...        NaN        NaN   \n",
       "0751f18cafeb100efb2c6d16f300a49c75befd79fc10bff...        NaN        NaN   \n",
       "\n",
       "article_id                                          146730001  148033001  \\\n",
       "customer_id                                                                \n",
       "00000dbacae5abe5e23885899a1fa44253a17956c6d1c3d...        NaN        NaN   \n",
       "000058a12d5b43e67d225668fa1f8d618c13dc232df0cad...        NaN        NaN   \n",
       "0000757967448a6cb83efb3ea7a3fb9d418ac7adf2379d8...        NaN        NaN   \n",
       "000172a9c322560c849754ffbdfdb2180d408aa7176b943...        NaN        NaN   \n",
       "0001d44dbe7f6c4b35200abdb052c77a87596fe1bdcc37e...        NaN        NaN   \n",
       "...                                                       ...        ...   \n",
       "075083cf54e37abbfb4fc5be69b8556acc14008318f0537...        NaN        NaN   \n",
       "0751425041cd8f0f5975e8594d99eff7e7cbb8ad639de18...        NaN        NaN   \n",
       "0751a0dcf7a097889c6086860067230972601507675e1d7...        NaN        NaN   \n",
       "0751e6551ef6b6ca840db0e4a86d2a9227f1494963ca9d9...        NaN        NaN   \n",
       "0751f18cafeb100efb2c6d16f300a49c75befd79fc10bff...        NaN        NaN   \n",
       "\n",
       "article_id                                          153115020  153115043  ...  \\\n",
       "customer_id                                                               ...   \n",
       "00000dbacae5abe5e23885899a1fa44253a17956c6d1c3d...        NaN        NaN  ...   \n",
       "000058a12d5b43e67d225668fa1f8d618c13dc232df0cad...        NaN        NaN  ...   \n",
       "0000757967448a6cb83efb3ea7a3fb9d418ac7adf2379d8...        NaN        NaN  ...   \n",
       "000172a9c322560c849754ffbdfdb2180d408aa7176b943...        NaN        NaN  ...   \n",
       "0001d44dbe7f6c4b35200abdb052c77a87596fe1bdcc37e...        NaN        NaN  ...   \n",
       "...                                                       ...        ...  ...   \n",
       "075083cf54e37abbfb4fc5be69b8556acc14008318f0537...        NaN        NaN  ...   \n",
       "0751425041cd8f0f5975e8594d99eff7e7cbb8ad639de18...        NaN        NaN  ...   \n",
       "0751a0dcf7a097889c6086860067230972601507675e1d7...        NaN        NaN  ...   \n",
       "0751e6551ef6b6ca840db0e4a86d2a9227f1494963ca9d9...        NaN        NaN  ...   \n",
       "0751f18cafeb100efb2c6d16f300a49c75befd79fc10bff...        NaN        NaN  ...   \n",
       "\n",
       "article_id                                          946748003  946764002  \\\n",
       "customer_id                                                                \n",
       "00000dbacae5abe5e23885899a1fa44253a17956c6d1c3d...        NaN        NaN   \n",
       "000058a12d5b43e67d225668fa1f8d618c13dc232df0cad...        NaN        NaN   \n",
       "0000757967448a6cb83efb3ea7a3fb9d418ac7adf2379d8...        NaN        NaN   \n",
       "000172a9c322560c849754ffbdfdb2180d408aa7176b943...        NaN        NaN   \n",
       "0001d44dbe7f6c4b35200abdb052c77a87596fe1bdcc37e...        NaN        NaN   \n",
       "...                                                       ...        ...   \n",
       "075083cf54e37abbfb4fc5be69b8556acc14008318f0537...        NaN        NaN   \n",
       "0751425041cd8f0f5975e8594d99eff7e7cbb8ad639de18...        NaN        NaN   \n",
       "0751a0dcf7a097889c6086860067230972601507675e1d7...        NaN        NaN   \n",
       "0751e6551ef6b6ca840db0e4a86d2a9227f1494963ca9d9...        NaN        NaN   \n",
       "0751f18cafeb100efb2c6d16f300a49c75befd79fc10bff...        NaN        NaN   \n",
       "\n",
       "article_id                                          946764003  946827001  \\\n",
       "customer_id                                                                \n",
       "00000dbacae5abe5e23885899a1fa44253a17956c6d1c3d...        NaN        NaN   \n",
       "000058a12d5b43e67d225668fa1f8d618c13dc232df0cad...        NaN        NaN   \n",
       "0000757967448a6cb83efb3ea7a3fb9d418ac7adf2379d8...        NaN        NaN   \n",
       "000172a9c322560c849754ffbdfdb2180d408aa7176b943...        NaN        NaN   \n",
       "0001d44dbe7f6c4b35200abdb052c77a87596fe1bdcc37e...        NaN        NaN   \n",
       "...                                                       ...        ...   \n",
       "075083cf54e37abbfb4fc5be69b8556acc14008318f0537...        NaN        NaN   \n",
       "0751425041cd8f0f5975e8594d99eff7e7cbb8ad639de18...        NaN        NaN   \n",
       "0751a0dcf7a097889c6086860067230972601507675e1d7...        NaN        NaN   \n",
       "0751e6551ef6b6ca840db0e4a86d2a9227f1494963ca9d9...        NaN        NaN   \n",
       "0751f18cafeb100efb2c6d16f300a49c75befd79fc10bff...        NaN        NaN   \n",
       "\n",
       "article_id                                          947168001  947509001  \\\n",
       "customer_id                                                                \n",
       "00000dbacae5abe5e23885899a1fa44253a17956c6d1c3d...        NaN        NaN   \n",
       "000058a12d5b43e67d225668fa1f8d618c13dc232df0cad...        NaN        NaN   \n",
       "0000757967448a6cb83efb3ea7a3fb9d418ac7adf2379d8...        NaN        NaN   \n",
       "000172a9c322560c849754ffbdfdb2180d408aa7176b943...        NaN        NaN   \n",
       "0001d44dbe7f6c4b35200abdb052c77a87596fe1bdcc37e...        NaN        NaN   \n",
       "...                                                       ...        ...   \n",
       "075083cf54e37abbfb4fc5be69b8556acc14008318f0537...        NaN        NaN   \n",
       "0751425041cd8f0f5975e8594d99eff7e7cbb8ad639de18...        NaN        NaN   \n",
       "0751a0dcf7a097889c6086860067230972601507675e1d7...        NaN        NaN   \n",
       "0751e6551ef6b6ca840db0e4a86d2a9227f1494963ca9d9...        NaN        NaN   \n",
       "0751f18cafeb100efb2c6d16f300a49c75befd79fc10bff...        NaN        NaN   \n",
       "\n",
       "article_id                                          947934001  949198001  \\\n",
       "customer_id                                                                \n",
       "00000dbacae5abe5e23885899a1fa44253a17956c6d1c3d...        NaN        NaN   \n",
       "000058a12d5b43e67d225668fa1f8d618c13dc232df0cad...        NaN        NaN   \n",
       "0000757967448a6cb83efb3ea7a3fb9d418ac7adf2379d8...        NaN        NaN   \n",
       "000172a9c322560c849754ffbdfdb2180d408aa7176b943...        NaN        NaN   \n",
       "0001d44dbe7f6c4b35200abdb052c77a87596fe1bdcc37e...        NaN        NaN   \n",
       "...                                                       ...        ...   \n",
       "075083cf54e37abbfb4fc5be69b8556acc14008318f0537...        NaN        NaN   \n",
       "0751425041cd8f0f5975e8594d99eff7e7cbb8ad639de18...        NaN        NaN   \n",
       "0751a0dcf7a097889c6086860067230972601507675e1d7...        NaN        NaN   \n",
       "0751e6551ef6b6ca840db0e4a86d2a9227f1494963ca9d9...        NaN        NaN   \n",
       "0751f18cafeb100efb2c6d16f300a49c75befd79fc10bff...        NaN        NaN   \n",
       "\n",
       "article_id                                          949551001  949551002  \n",
       "customer_id                                                               \n",
       "00000dbacae5abe5e23885899a1fa44253a17956c6d1c3d...        NaN        NaN  \n",
       "000058a12d5b43e67d225668fa1f8d618c13dc232df0cad...        NaN        NaN  \n",
       "0000757967448a6cb83efb3ea7a3fb9d418ac7adf2379d8...        NaN        NaN  \n",
       "000172a9c322560c849754ffbdfdb2180d408aa7176b943...        NaN        NaN  \n",
       "0001d44dbe7f6c4b35200abdb052c77a87596fe1bdcc37e...        NaN        NaN  \n",
       "...                                                       ...        ...  \n",
       "075083cf54e37abbfb4fc5be69b8556acc14008318f0537...        NaN        NaN  \n",
       "0751425041cd8f0f5975e8594d99eff7e7cbb8ad639de18...        NaN        NaN  \n",
       "0751a0dcf7a097889c6086860067230972601507675e1d7...        NaN        NaN  \n",
       "0751e6551ef6b6ca840db0e4a86d2a9227f1494963ca9d9...        NaN        NaN  \n",
       "0751f18cafeb100efb2c6d16f300a49c75befd79fc10bff...        NaN        NaN  \n",
       "\n",
       "[5248 rows x 7062 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Select only first 20 000 rows of data and represent previously reduced data as a matrix\n",
    "customer_article_matrix = collaborative_filtering_df[:20000].pivot_table(\n",
    "    index='customer_id',\n",
    "    columns='article_id',\n",
    "    values='quantity',\n",
    "    aggfunc='sum')\n",
    "\n",
    "customer_article_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Replacing the nan's with 0's and values >1 with 1's\n",
    "customer_article_matrix = customer_article_matrix.fillna(0)\n",
    "customer_article_matrix.where(customer_article_matrix > 0, 0, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7062 rows × 7062 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          0         1         2     3     4     5     6     7     8     9     \\\n",
       "0     1.000000  0.000000  0.000000   0.0   0.0   0.0   0.0   0.0   0.0   0.0   \n",
       "1     0.000000  1.000000  0.109109   0.0   0.0   0.0   0.0   0.0   0.0   0.0   \n",
       "2     0.000000  0.109109  1.000000   0.0   0.0   0.0   0.0   0.0   0.0   0.0   \n",
       "3     0.000000  0.000000  0.000000   1.0   0.0   0.0   0.0   0.0   0.0   0.0   \n",
       "4     0.000000  0.000000  0.000000   0.0   1.0   0.0   0.0   0.0   0.0   0.0   \n",
       "...        ...       ...       ...   ...   ...   ...   ...   ...   ...   ...   \n",
       "7057  0.000000  0.000000  0.000000   0.0   0.0   0.0   0.0   0.0   0.0   0.0   \n",
       "7058  0.707107  0.000000  0.000000   0.0   0.0   0.0   0.0   0.0   0.0   0.0   \n",
       "7059  0.000000  0.000000  0.000000   0.0   0.0   0.0   0.0   0.0   0.0   0.0   \n",
       "7060  0.500000  0.000000  0.000000   0.0   0.0   0.0   0.0   0.0   0.0   0.0   \n",
       "7061  0.000000  0.000000  0.000000   0.0   0.0   0.0   0.0   0.0   0.0   0.0   \n",
       "\n",
       "      ...  7052  7053      7054  7055  7056  7057      7058  7059      7060  \\\n",
       "0     ...   0.0   0.0  0.000000   0.0   0.0   0.0  0.707107   0.0  0.500000   \n",
       "1     ...   0.0   0.0  0.000000   0.0   0.0   0.0  0.000000   0.0  0.000000   \n",
       "2     ...   0.0   0.0  0.000000   0.0   0.0   0.0  0.000000   0.0  0.000000   \n",
       "3     ...   0.0   0.0  0.000000   0.0   0.0   0.0  0.000000   0.0  0.000000   \n",
       "4     ...   0.0   0.0  0.000000   0.0   0.0   0.0  0.000000   0.0  0.000000   \n",
       "...   ...   ...   ...       ...   ...   ...   ...       ...   ...       ...   \n",
       "7057  ...   0.0   0.0  0.149071   0.0   0.0   1.0  0.000000   0.0  0.000000   \n",
       "7058  ...   0.0   0.0  0.000000   0.0   0.0   0.0  1.000000   0.0  0.707107   \n",
       "7059  ...   0.0   0.0  0.000000   0.0   0.0   0.0  0.000000   1.0  0.000000   \n",
       "7060  ...   0.0   0.0  0.000000   0.0   0.0   0.0  0.707107   0.0  1.000000   \n",
       "7061  ...   0.0   0.0  0.000000   0.0   0.0   0.0  0.000000   0.0  0.000000   \n",
       "\n",
       "      7061  \n",
       "0      0.0  \n",
       "1      0.0  \n",
       "2      0.0  \n",
       "3      0.0  \n",
       "4      0.0  \n",
       "...    ...  \n",
       "7057   0.0  \n",
       "7058   0.0  \n",
       "7059   0.0  \n",
       "7060   0.0  \n",
       "7061   1.0  \n",
       "\n",
       "[7062 rows x 7062 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"\n",
    "We transpose (T) in order to rotate dataframe 90 degrees to left.\n",
    "We do this so that index now represents articles and columns customers.\n",
    "Afterwards we apply cosine similarity to the dataset. \n",
    "https://scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.cosine_similarity.html\n",
    "\"\"\"\n",
    "\n",
    "article_similarity_matrix = pd.DataFrame(cosine_similarity(customer_article_matrix.T))\n",
    "article_similarity_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Since column names and index names are not yet set, we set index and column names to belonging article id.\n",
    "article_similarity_matrix.columns = customer_article_matrix.T.index\n",
    "article_similarity_matrix['article_id'] = customer_article_matrix.T.index\n",
    "article_similarity_matrix = article_similarity_matrix.set_index('article_id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "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>article_id</th>\n",
       "      <th>882759003</th>\n",
       "      <th>product_code</th>\n",
       "      <th>prod_name</th>\n",
       "      <th>product_type_no</th>\n",
       "      <th>product_type_name</th>\n",
       "      <th>product_group_name</th>\n",
       "      <th>graphical_appearance_no</th>\n",
       "      <th>graphical_appearance_name</th>\n",
       "      <th>colour_group_code</th>\n",
       "      <th>...</th>\n",
       "      <th>department_name</th>\n",
       "      <th>index_code</th>\n",
       "      <th>index_name</th>\n",
       "      <th>index_group_no</th>\n",
       "      <th>index_group_name</th>\n",
       "      <th>section_no</th>\n",
       "      <th>section_name</th>\n",
       "      <th>garment_group_no</th>\n",
       "      <th>garment_group_name</th>\n",
       "      <th>detail_desc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>882757003</td>\n",
       "      <td>0.816497</td>\n",
       "      <td>882757</td>\n",
       "      <td>Price Timeless Triangle Top</td>\n",
       "      <td>298</td>\n",
       "      <td>Bikini top</td>\n",
       "      <td>Swimwear</td>\n",
       "      <td>1010001</td>\n",
       "      <td>All over pattern</td>\n",
       "      <td>9</td>\n",
       "      <td>...</td>\n",
       "      <td>Swimwear</td>\n",
       "      <td>B</td>\n",
       "      <td>Lingeries/Tights</td>\n",
       "      <td>1</td>\n",
       "      <td>Ladieswear</td>\n",
       "      <td>60</td>\n",
       "      <td>Womens Swimwear, beachwear</td>\n",
       "      <td>1018</td>\n",
       "      <td>Swimwear</td>\n",
       "      <td>Lined, non-wired triangle bikini top with narr...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>699080001</td>\n",
       "      <td>0.577350</td>\n",
       "      <td>699080</td>\n",
       "      <td>Lazer Razer Padded Wire</td>\n",
       "      <td>298</td>\n",
       "      <td>Bikini top</td>\n",
       "      <td>Swimwear</td>\n",
       "      <td>1010016</td>\n",
       "      <td>Solid</td>\n",
       "      <td>9</td>\n",
       "      <td>...</td>\n",
       "      <td>Swimwear</td>\n",
       "      <td>B</td>\n",
       "      <td>Lingeries/Tights</td>\n",
       "      <td>1</td>\n",
       "      <td>Ladieswear</td>\n",
       "      <td>60</td>\n",
       "      <td>Womens Swimwear, beachwear</td>\n",
       "      <td>1018</td>\n",
       "      <td>Swimwear</td>\n",
       "      <td>Fully lined bikini top with laser-cut edges an...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>776237008</td>\n",
       "      <td>0.577350</td>\n",
       "      <td>776237</td>\n",
       "      <td>Shake it in Balconette</td>\n",
       "      <td>298</td>\n",
       "      <td>Bikini top</td>\n",
       "      <td>Swimwear</td>\n",
       "      <td>1010026</td>\n",
       "      <td>Other structure</td>\n",
       "      <td>9</td>\n",
       "      <td>...</td>\n",
       "      <td>Swimwear</td>\n",
       "      <td>B</td>\n",
       "      <td>Lingeries/Tights</td>\n",
       "      <td>1</td>\n",
       "      <td>Ladieswear</td>\n",
       "      <td>60</td>\n",
       "      <td>Womens Swimwear, beachwear</td>\n",
       "      <td>1018</td>\n",
       "      <td>Swimwear</td>\n",
       "      <td>Lined balconette bikini top with underwired, p...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>186262001</td>\n",
       "      <td>0.408248</td>\n",
       "      <td>186262</td>\n",
       "      <td>4p Claw</td>\n",
       "      <td>72</td>\n",
       "      <td>Hair clip</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>1010016</td>\n",
       "      <td>Solid</td>\n",
       "      <td>9</td>\n",
       "      <td>...</td>\n",
       "      <td>Hair Accessories</td>\n",
       "      <td>C</td>\n",
       "      <td>Ladies Accessories</td>\n",
       "      <td>1</td>\n",
       "      <td>Ladieswear</td>\n",
       "      <td>66</td>\n",
       "      <td>Womens Small accessories</td>\n",
       "      <td>1019</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Plastic hair claws. Width 2.5 cm.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>821152002</td>\n",
       "      <td>0.408248</td>\n",
       "      <td>821152</td>\n",
       "      <td>Danderyd polo</td>\n",
       "      <td>252</td>\n",
       "      <td>Sweater</td>\n",
       "      <td>Garment Upper body</td>\n",
       "      <td>1010016</td>\n",
       "      <td>Solid</td>\n",
       "      <td>22</td>\n",
       "      <td>...</td>\n",
       "      <td>Knitwear</td>\n",
       "      <td>A</td>\n",
       "      <td>Ladieswear</td>\n",
       "      <td>1</td>\n",
       "      <td>Ladieswear</td>\n",
       "      <td>11</td>\n",
       "      <td>Womens Tailoring</td>\n",
       "      <td>1003</td>\n",
       "      <td>Knitwear</td>\n",
       "      <td>Jumper in a soft, fine-knit viscose blend with...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   article_id  882759003  product_code                    prod_name  \\\n",
       "0   882757003   0.816497        882757  Price Timeless Triangle Top   \n",
       "1   699080001   0.577350        699080      Lazer Razer Padded Wire   \n",
       "2   776237008   0.577350        776237       Shake it in Balconette   \n",
       "3   186262001   0.408248        186262                      4p Claw   \n",
       "4   821152002   0.408248        821152                Danderyd polo   \n",
       "\n",
       "   product_type_no product_type_name  product_group_name  \\\n",
       "0              298        Bikini top            Swimwear   \n",
       "1              298        Bikini top            Swimwear   \n",
       "2              298        Bikini top            Swimwear   \n",
       "3               72         Hair clip         Accessories   \n",
       "4              252           Sweater  Garment Upper body   \n",
       "\n",
       "   graphical_appearance_no graphical_appearance_name  colour_group_code  ...  \\\n",
       "0                  1010001          All over pattern                  9  ...   \n",
       "1                  1010016                     Solid                  9  ...   \n",
       "2                  1010026           Other structure                  9  ...   \n",
       "3                  1010016                     Solid                  9  ...   \n",
       "4                  1010016                     Solid                 22  ...   \n",
       "\n",
       "    department_name  index_code          index_name  index_group_no  \\\n",
       "0          Swimwear           B    Lingeries/Tights               1   \n",
       "1          Swimwear           B    Lingeries/Tights               1   \n",
       "2          Swimwear           B    Lingeries/Tights               1   \n",
       "3  Hair Accessories           C  Ladies Accessories               1   \n",
       "4          Knitwear           A          Ladieswear               1   \n",
       "\n",
       "  index_group_name  section_no                section_name garment_group_no  \\\n",
       "0       Ladieswear          60  Womens Swimwear, beachwear             1018   \n",
       "1       Ladieswear          60  Womens Swimwear, beachwear             1018   \n",
       "2       Ladieswear          60  Womens Swimwear, beachwear             1018   \n",
       "3       Ladieswear          66    Womens Small accessories             1019   \n",
       "4       Ladieswear          11            Womens Tailoring             1003   \n",
       "\n",
       "  garment_group_name                                        detail_desc  \n",
       "0           Swimwear  Lined, non-wired triangle bikini top with narr...  \n",
       "1           Swimwear  Fully lined bikini top with laser-cut edges an...  \n",
       "2           Swimwear  Lined balconette bikini top with underwired, p...  \n",
       "3        Accessories                  Plastic hair claws. Width 2.5 cm.  \n",
       "4           Knitwear  Jumper in a soft, fine-knit viscose blend with...  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"\n",
    "This code only selects top 5 results and merges information from the arcticles csv to get additional information on products.\n",
    "I decided to use a bikini bottom (882759003), because looking at other kaggle notebooks, I saw that bikini tops are usually bought\n",
    "with a matching top. So I thought it was a good strategy to test our model.\n",
    "\"\"\" \n",
    "bikini_bottom_id = int(882759003)\n",
    "similar_items = article_similarity_matrix.loc[bikini_bottom_id].sort_values(ascending=False).reset_index()[1:6]\n",
    "similar_items.set_axis(['article_id', 'similarity'], axis=1, inplace=False)\n",
    "similar_items_detailed = pd.merge(similar_items, articles, how='inner')\n",
    "similar_items_detailed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# This code displays the article (bikini bottom) that is used to for prediction \n",
    "import os\n",
    "img = mpimg.imread(os.getcwd()+'\\\\photos\\\\'+str(bikini_bottom_id).zfill(10)+'.jpg')\n",
    "imgplot = plt.imshow(img)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# These are the results for the prediction visualized.\n",
    "article_ids = similar_items_detailed['article_id'].to_list()\n",
    "\n",
    "fig = plt.figure(figsize=(20, 5))\n",
    "columns = 5\n",
    "rows = 1\n",
    "for i in range(1, columns*rows +1):\n",
    "    img = mpimg.imread(os.getcwd()+'\\\\photos\\\\'+str(article_ids[i-1]).zfill(10)+'.jpg')\n",
    "    fig.add_subplot(rows, columns, i)\n",
    "    plt.imshow(img)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we can see, the method shows promising results for this clothing item. It reccomends the matching bikini top and shows alternative tops that are usually bought. It also reccomends hair clips which surprisingly people buy as well while shopping for bikini bottoms. This method needs to be further investigated and evaluated before it can be implemented. It also needs more thinking on how it can be implented efficiently, but I think this is out of scope for this assingment."
   ]
  }
 ],
 "metadata": {
  "colab": {
   "collapsed_sections": [],
   "name": "assignment3.ipynb",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}