user_clustering_v1.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8730d427-c3c9-4082-96d3-3bd5d7d4d28c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import polars as ps\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.cluster import KMeans, AgglomerativeClustering\n",
    "from sklearn.mixture import GaussianMixture\n",
    "from hdbscan import HDBSCAN\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5f5841c3-436e-4d7e-b9a2-ff7c05c76859",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('user_ratings_pca_components.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "97e06d90-9d0f-41f0-89e8-fa154dee29a9",
   "metadata": {},
   "outputs": [
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     },
     "execution_count": 3,
     "metadata": {},
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    }
   ],
   "source": [
    "df.head()"
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  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "8caab2ee-29d8-4f63-9c09-29a217bffe1b",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.drop(columns=[str(x) for x in range(539, 1000)])"
   ]
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       "           0          1         2         3          4         5         6  \\\n",
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       "\n",
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       "\n",
       "[5 rows x 539 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "82d63c7c-e300-44e7-a51e-938bd16dc030",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model M_2 finished\n",
      "Model M_3 finished\n",
      "Model M_4 finished\n",
      "Model M_5 finished\n",
      "Model M_6 finished\n",
      "Model M_7 finished\n",
      "Model M_8 finished\n",
      "Model M_9 finished\n",
      "Model M_10 finished\n",
      "Model M_11 finished\n",
      "Model M_12 finished\n",
      "Model M_13 finished\n",
      "Model M_14 finished\n",
      "Model M_15 finished\n",
      "Model M_16 finished\n",
      "Model M_17 finished\n",
      "Model M_18 finished\n",
      "Model M_19 finished\n",
      "Model M_20 finished\n",
      "Model M_21 finished\n",
      "Model M_22 finished\n",
      "Model M_23 finished\n",
      "Model M_24 finished\n",
      "Model M_25 finished\n"
     ]
    }
   ],
   "source": [
    "labels = {}\n",
    "inertias = {}\n",
    "for k in range(2,26):\n",
    "    model = KMeans(n_clusters=k, random_state=41)\n",
    "    model.fit(df)\n",
    "    labels[k] = model.labels_\n",
    "    inertias[k] = model.inertia_\n",
    "    print(f'Model M_{k} finished')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "cbab0113-727b-43a9-b43f-e6cbfa960c22",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 12,
     "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": [
    "sns.lineplot(x=[x for x, y in inertias.items()], y=[y for x, y in inertias.items()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "569e842e-09ea-4ce5-995f-78e69822496b",
   "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>k</th>\n",
       "      <th>inertia</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "      <td>3.680771e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>3.586930e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4</td>\n",
       "      <td>3.541963e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5</td>\n",
       "      <td>3.503859e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6</td>\n",
       "      <td>3.469495e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>7</td>\n",
       "      <td>3.439646e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>8</td>\n",
       "      <td>3.411987e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>9</td>\n",
       "      <td>3.387845e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>10</td>\n",
       "      <td>3.361939e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>11</td>\n",
       "      <td>3.344588e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>12</td>\n",
       "      <td>3.328060e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>13</td>\n",
       "      <td>3.313119e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>14</td>\n",
       "      <td>3.298568e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>15</td>\n",
       "      <td>3.288069e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>16</td>\n",
       "      <td>3.272865e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>17</td>\n",
       "      <td>3.260002e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>18</td>\n",
       "      <td>3.248661e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>19</td>\n",
       "      <td>3.241724e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>20</td>\n",
       "      <td>3.229917e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>21</td>\n",
       "      <td>3.220393e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>22</td>\n",
       "      <td>3.215220e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>23</td>\n",
       "      <td>3.203240e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>24</td>\n",
       "      <td>3.196733e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>25</td>\n",
       "      <td>3.190091e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     k       inertia\n",
       "0    2  3.680771e+08\n",
       "1    3  3.586930e+08\n",
       "2    4  3.541963e+08\n",
       "3    5  3.503859e+08\n",
       "4    6  3.469495e+08\n",
       "5    7  3.439646e+08\n",
       "6    8  3.411987e+08\n",
       "7    9  3.387845e+08\n",
       "8   10  3.361939e+08\n",
       "9   11  3.344588e+08\n",
       "10  12  3.328060e+08\n",
       "11  13  3.313119e+08\n",
       "12  14  3.298568e+08\n",
       "13  15  3.288069e+08\n",
       "14  16  3.272865e+08\n",
       "15  17  3.260002e+08\n",
       "16  18  3.248661e+08\n",
       "17  19  3.241724e+08\n",
       "18  20  3.229917e+08\n",
       "19  21  3.220393e+08\n",
       "20  22  3.215220e+08\n",
       "21  23  3.203240e+08\n",
       "22  24  3.196733e+08\n",
       "23  25  3.190091e+08"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kmeans_inertias = pd.DataFrame({'k': [x for x in range(2, 26)], 'inertia': [y for x, y in inertias.items()]})\n",
    "kmeans_inertias"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "8f1abd53-67a7-4f9c-9867-4fbacf6037c8",
   "metadata": {},
   "outputs": [],
   "source": [
    "kmeans_inertias.to_csv('user_kmeans_inertias.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "d1d8bc84-c0f5-41e4-a06f-295e84a24d1e",
   "metadata": {},
   "outputs": [],
   "source": [
    "kmeans_labels = pd.DataFrame(labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "d63fc9e2-0ff0-4290-ab3d-32a30d778d73",
   "metadata": {},
   "outputs": [],
   "source": [
    "kmeans_labels.to_csv('user_kmeans_labels.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "78c03f31-db6b-44ed-b370-cca5bbcd7c04",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      ],
      "text/plain": [
       "        2   3   4   5   6   7   8   9   10  11  ...  16  17  18  19  20  21  \\\n",
       "0        1   2   1   3   2   1   2   5   2   4  ...   1   5  17   5  18  10   \n",
       "1        0   0   2   0   4   0   0   1   5   3  ...  12   2   0   0   0   1   \n",
       "2        0   0   2   0   4   0   0   1   5   3  ...  12   2   0   0   0   1   \n",
       "3        0   0   2   2   5   2   3   1   4   2  ...   2   3   7  18   2   4   \n",
       "4        1   2   1   3   2   1   2   5   2   4  ...   1   5  17   5  18  10   \n",
       "...     ..  ..  ..  ..  ..  ..  ..  ..  ..  ..  ...  ..  ..  ..  ..  ..  ..   \n",
       "478558   0   0   2   0   4   0   0   1   5   3  ...  12   2   0   0   0   1   \n",
       "478559   0   0   2   0   4   0   0   1   5   3  ...  12   2   0   0   0   1   \n",
       "478560   0   0   2   0   4   0   0   1   5   3  ...  12   2   0   0   0   1   \n",
       "478561   0   0   2   0   4   0   0   1   5   3  ...  13   1  11  12  17  20   \n",
       "478562   0   0   2   0   4   0   0   1   5   3  ...  12   2   0   0   0   1   \n",
       "\n",
       "        22  23  24  25  \n",
       "0        2  20  12   0  \n",
       "1       12  10   0  21  \n",
       "2       12  10   0  21  \n",
       "3       19   8  12  18  \n",
       "4        2  20   6   0  \n",
       "...     ..  ..  ..  ..  \n",
       "478558  12  10   0  21  \n",
       "478559  12  10   0  21  \n",
       "478560  12  10   0  21  \n",
       "478561  16   1  13  17  \n",
       "478562  12  10   0  21  \n",
       "\n",
       "[478563 rows x 24 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kmeans_labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "9b96e629-d68d-4546-9683-04a298f681d4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2     int32\n",
       "3     int32\n",
       "4     int32\n",
       "5     int32\n",
       "6     int32\n",
       "7     int32\n",
       "8     int32\n",
       "9     int32\n",
       "10    int32\n",
       "11    int32\n",
       "12    int32\n",
       "13    int32\n",
       "14    int32\n",
       "15    int32\n",
       "16    int32\n",
       "17    int32\n",
       "18    int32\n",
       "19    int32\n",
       "20    int32\n",
       "21    int32\n",
       "22    int32\n",
       "23    int32\n",
       "24    int32\n",
       "25    int32\n",
       "dtype: object"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kmeans_labels.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "8b78bb68-d94f-4b1e-aa9f-506ab7c08890",
   "metadata": {},
   "outputs": [
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       "</style>\n",
       "<small>shape: (797_605, 1_002)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th></th><th>user_id</th><th>19</th><th>43</th><th>49</th><th>51</th><th>66</th><th>80</th><th>100</th><th>126</th><th>134</th><th>138</th><th>150</th><th>174</th><th>176</th><th>182</th><th>197</th><th>229</th><th>236</th><th>255</th><th>257</th><th>259</th><th>260</th><th>290</th><th>297</th><th>301</th><th>307</th><th>317</th><th>325</th><th>332</th><th>370</th><th>383</th><th>384</th><th>387</th><th>400</th><th>407</th><th>410</th><th>&hellip;</th><th>21164</th><th>21193</th><th>21252</th><th>21272</th><th>21422</th><th>21489</th><th>21796</th><th>21897</th><th>21898</th><th>21926</th><th>21949</th><th>22321</th><th>22426</th><th>22530</th><th>23355</th><th>23476</th><th>23787</th><th>23801</th><th>23815</th><th>23824</th><th>24173</th><th>24366</th><th>24928</th><th>26420</th><th>26421</th><th>27983</th><th>29336</th><th>32624</th><th>38819</th><th>39042</th><th>42643</th><th>42701</th><th>42703</th><th>42704</th><th>42705</th><th>47273</th><th>51259</th></tr><tr><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>&hellip;</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td></tr></thead><tbody><tr><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>3</td><td>5</td><td>0</td><td>5</td><td>0</td><td>5</td><td>5</td><td>0</td><td>4</td><td>0</td><td>0</td><td>4</td><td>5</td><td>5</td><td>0</td><td>5</td><td>0</td><td>0</td><td>5</td><td>0</td><td>0</td><td>4</td><td>0</td><td>4</td><td>5</td><td>4</td><td>5</td><td>0</td><td>5</td><td>&hellip;</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>1</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>5</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>&hellip;</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>2</td><td>2</td><td>0</td><td>0</td><td>0</td><td>3</td><td>3</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>&hellip;</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>3</td><td>3</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>3</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>4</td><td>0</td><td>4</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>&hellip;</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>4</td><td>4</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>4</td><td>0</td><td>0</td><td>3</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>3</td><td>0</td><td>4</td><td>4</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>4</td><td>4</td><td>&hellip;</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td></tr><tr><td>797600</td><td>876140</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>&hellip;</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>797601</td><td>876141</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>5</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>&hellip;</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>797602</td><td>876142</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>&hellip;</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>797603</td><td>876143</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>&hellip;</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>797604</td><td>876144</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>&hellip;</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr></tbody></table></div>"
      ],
      "text/plain": [
       "shape: (797_605, 1_002)\n",
       "┌────────┬─────────┬─────┬─────┬───┬───────┬───────┬───────┬───────┐\n",
       "│        ┆ user_id ┆ 19  ┆ 43  ┆ … ┆ 42704 ┆ 42705 ┆ 47273 ┆ 51259 │\n",
       "│ ---    ┆ ---     ┆ --- ┆ --- ┆   ┆ ---   ┆ ---   ┆ ---   ┆ ---   │\n",
       "│ i64    ┆ i64     ┆ i64 ┆ i64 ┆   ┆ f64   ┆ f64   ┆ f64   ┆ f64   │\n",
       "╞════════╪═════════╪═════╪═════╪═══╪═══════╪═══════╪═══════╪═══════╡\n",
       "│ 0      ┆ 0       ┆ 0   ┆ 0   ┆ … ┆ 0.0   ┆ 0.0   ┆ 0.0   ┆ 0.0   │\n",
       "│ 1      ┆ 1       ┆ 0   ┆ 0   ┆ … ┆ 0.0   ┆ 0.0   ┆ 0.0   ┆ 0.0   │\n",
       "│ 2      ┆ 2       ┆ 0   ┆ 0   ┆ … ┆ 0.0   ┆ 0.0   ┆ 0.0   ┆ 0.0   │\n",
       "│ 3      ┆ 3       ┆ 0   ┆ 0   ┆ … ┆ 0.0   ┆ 0.0   ┆ 0.0   ┆ 0.0   │\n",
       "│ 4      ┆ 4       ┆ 0   ┆ 0   ┆ … ┆ 0.0   ┆ 0.0   ┆ 0.0   ┆ 0.0   │\n",
       "│ …      ┆ …       ┆ …   ┆ …   ┆ … ┆ …     ┆ …     ┆ …     ┆ …     │\n",
       "│ 797600 ┆ 876140  ┆ 0   ┆ 0   ┆ … ┆ 0.0   ┆ 0.0   ┆ 0.0   ┆ 0.0   │\n",
       "│ 797601 ┆ 876141  ┆ 0   ┆ 0   ┆ … ┆ 0.0   ┆ 0.0   ┆ 0.0   ┆ 0.0   │\n",
       "│ 797602 ┆ 876142  ┆ 0   ┆ 0   ┆ … ┆ 0.0   ┆ 0.0   ┆ 0.0   ┆ 0.0   │\n",
       "│ 797603 ┆ 876143  ┆ 0   ┆ 0   ┆ … ┆ 0.0   ┆ 0.0   ┆ 0.0   ┆ 0.0   │\n",
       "│ 797604 ┆ 876144  ┆ 0   ┆ 0   ┆ … ┆ 0.0   ┆ 0.0   ┆ 0.0   ┆ 0.0   │\n",
       "└────────┴─────────┴─────┴─────┴───┴───────┴───────┴───────┴───────┘"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "book_ids = ps.scan_csv('data/ratings.csv')\n",
    "book_ids.collect()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "ea354675-f451-4e34-972e-92aaa5a6430d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><style>\n",
       ".dataframe > thead > tr,\n",
       ".dataframe > tbody > tr {\n",
       "  text-align: right;\n",
       "  white-space: pre-wrap;\n",
       "}\n",
       "</style>\n",
       "<small>shape: (9, 1_003)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>statistic</th><th></th><th>user_id</th><th>19</th><th>43</th><th>49</th><th>51</th><th>66</th><th>80</th><th>100</th><th>126</th><th>134</th><th>138</th><th>150</th><th>174</th><th>176</th><th>182</th><th>197</th><th>229</th><th>236</th><th>255</th><th>257</th><th>259</th><th>260</th><th>290</th><th>297</th><th>301</th><th>307</th><th>317</th><th>325</th><th>332</th><th>370</th><th>383</th><th>384</th><th>387</th><th>400</th><th>407</th><th>&hellip;</th><th>21164</th><th>21193</th><th>21252</th><th>21272</th><th>21422</th><th>21489</th><th>21796</th><th>21897</th><th>21898</th><th>21926</th><th>21949</th><th>22321</th><th>22426</th><th>22530</th><th>23355</th><th>23476</th><th>23787</th><th>23801</th><th>23815</th><th>23824</th><th>24173</th><th>24366</th><th>24928</th><th>26420</th><th>26421</th><th>27983</th><th>29336</th><th>32624</th><th>38819</th><th>39042</th><th>42643</th><th>42701</th><th>42703</th><th>42704</th><th>42705</th><th>47273</th><th>51259</th></tr><tr><td>str</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>&hellip;</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td></tr></thead><tbody><tr><td>&quot;count&quot;</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>&hellip;</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td><td>797605.0</td></tr><tr><td>&quot;null_count&quot;</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>&hellip;</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>&quot;mean&quot;</td><td>398802.0</td><td>419342.791758</td><td>0.050339</td><td>0.146891</td><td>0.13115</td><td>0.157922</td><td>0.494105</td><td>0.114446</td><td>0.053203</td><td>0.204292</td><td>0.05457</td><td>0.071098</td><td>0.138097</td><td>0.103017</td><td>0.057987</td><td>0.093826</td><td>0.383051</td><td>0.093086</td><td>0.080976</td><td>0.136746</td><td>0.052921</td><td>0.054517</td><td>0.079564</td><td>0.099424</td><td>0.13597</td><td>0.13647</td><td>0.092494</td><td>0.058524</td><td>0.13775</td><td>0.051769</td><td>0.073225</td><td>0.057067</td><td>0.189964</td><td>0.047596</td><td>0.070213</td><td>0.128176</td><td>&hellip;</td><td>0.096909</td><td>0.063126</td><td>0.054664</td><td>0.049091</td><td>0.06861</td><td>0.043357</td><td>0.103234</td><td>0.065188</td><td>0.114878</td><td>0.135958</td><td>0.053692</td><td>0.064483</td><td>0.079132</td><td>0.061124</td><td>0.064309</td><td>0.045861</td><td>0.054215</td><td>0.059314</td><td>0.091678</td><td>0.061129</td><td>0.066586</td><td>0.054972</td><td>0.053656</td><td>0.053076</td><td>0.075781</td><td>0.062318</td><td>0.073856</td><td>0.061238</td><td>0.055832</td><td>0.062704</td><td>0.055171</td><td>0.049671</td><td>0.059936</td><td>0.052451</td><td>0.056418</td><td>0.05934</td><td>0.049977</td></tr><tr><td>&quot;std&quot;</td><td>230248.875066</td><td>252553.3963</td><td>0.47585</td><td>0.766962</td><td>0.723321</td><td>0.820841</td><td>1.312118</td><td>0.715409</td><td>0.466082</td><td>0.953499</td><td>0.473171</td><td>0.553999</td><td>0.7383</td><td>0.671676</td><td>0.477062</td><td>0.648243</td><td>1.180588</td><td>0.627655</td><td>0.579036</td><td>0.744249</td><td>0.476279</td><td>0.488534</td><td>0.571841</td><td>0.659327</td><td>0.743479</td><td>0.734304</td><td>0.609521</td><td>0.493966</td><td>0.726335</td><td>0.474147</td><td>0.537779</td><td>0.496048</td><td>0.902383</td><td>0.444177</td><td>0.547932</td><td>0.744488</td><td>&hellip;</td><td>0.639851</td><td>0.530254</td><td>0.480596</td><td>0.435427</td><td>0.525293</td><td>0.411278</td><td>0.662341</td><td>0.519887</td><td>0.675344</td><td>0.744378</td><td>0.473401</td><td>0.527428</td><td>0.56687</td><td>0.504145</td><td>0.500946</td><td>0.408042</td><td>0.475668</td><td>0.504496</td><td>0.620105</td><td>0.5069</td><td>0.521984</td><td>0.490249</td><td>0.483228</td><td>0.463843</td><td>0.551656</td><td>0.514979</td><td>0.529991</td><td>0.505179</td><td>0.465234</td><td>0.506421</td><td>0.480158</td><td>0.456601</td><td>0.500204</td><td>0.471045</td><td>0.487511</td><td>0.505683</td><td>0.436828</td></tr><tr><td>&quot;min&quot;</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>&hellip;</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>&quot;25%&quot;</td><td>199401.0</td><td>201585.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>&hellip;</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>&quot;50%&quot;</td><td>398802.0</td><td>403536.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>&hellip;</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>&quot;75%&quot;</td><td>598203.0</td><td>636348.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>&hellip;</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>&quot;max&quot;</td><td>797604.0</td><td>876144.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>&hellip;</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td><td>5.0</td></tr></tbody></table></div>"
      ],
      "text/plain": [
       "shape: (9, 1_003)\n",
       "┌────────────┬─────────────┬────────────┬──────────┬───┬──────────┬──────────┬──────────┬──────────┐\n",
       "│ statistic  ┆             ┆ user_id    ┆ 19       ┆ … ┆ 42704    ┆ 42705    ┆ 47273    ┆ 51259    │\n",
       "│ ---        ┆ ---         ┆ ---        ┆ ---      ┆   ┆ ---      ┆ ---      ┆ ---      ┆ ---      │\n",
       "│ str        ┆ f64         ┆ f64        ┆ f64      ┆   ┆ f64      ┆ f64      ┆ f64      ┆ f64      │\n",
       "╞════════════╪═════════════╪════════════╪══════════╪═══╪══════════╪══════════╪══════════╪══════════╡\n",
       "│ count      ┆ 797605.0    ┆ 797605.0   ┆ 797605.0 ┆ … ┆ 797605.0 ┆ 797605.0 ┆ 797605.0 ┆ 797605.0 │\n",
       "│ null_count ┆ 0.0         ┆ 0.0        ┆ 0.0      ┆ … ┆ 0.0      ┆ 0.0      ┆ 0.0      ┆ 0.0      │\n",
       "│ mean       ┆ 398802.0    ┆ 419342.791 ┆ 0.050339 ┆ … ┆ 0.052451 ┆ 0.056418 ┆ 0.05934  ┆ 0.049977 │\n",
       "│            ┆             ┆ 758        ┆          ┆   ┆          ┆          ┆          ┆          │\n",
       "│ std        ┆ 230248.8750 ┆ 252553.396 ┆ 0.47585  ┆ … ┆ 0.471045 ┆ 0.487511 ┆ 0.505683 ┆ 0.436828 │\n",
       "│            ┆ 66          ┆ 3          ┆          ┆   ┆          ┆          ┆          ┆          │\n",
       "│ min        ┆ 0.0         ┆ 0.0        ┆ 0.0      ┆ … ┆ 0.0      ┆ 0.0      ┆ 0.0      ┆ 0.0      │\n",
       "│ 25%        ┆ 199401.0    ┆ 201585.0   ┆ 0.0      ┆ … ┆ 0.0      ┆ 0.0      ┆ 0.0      ┆ 0.0      │\n",
       "│ 50%        ┆ 398802.0    ┆ 403536.0   ┆ 0.0      ┆ … ┆ 0.0      ┆ 0.0      ┆ 0.0      ┆ 0.0      │\n",
       "│ 75%        ┆ 598203.0    ┆ 636348.0   ┆ 0.0      ┆ … ┆ 0.0      ┆ 0.0      ┆ 0.0      ┆ 0.0      │\n",
       "│ max        ┆ 797604.0    ┆ 876144.0   ┆ 5.0      ┆ … ┆ 5.0      ┆ 5.0      ┆ 5.0      ┆ 5.0      │\n",
       "└────────────┴─────────────┴────────────┴──────────┴───┴──────────┴──────────┴──────────┴──────────┘"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "book_ids.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "e9000afb-f901-466d-996f-2534c6a4335e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[19,\n",
       " 43,\n",
       " 49,\n",
       " 51,\n",
       " 66,\n",
       " 80,\n",
       " 100,\n",
       " 126,\n",
       " 134,\n",
       " 138,\n",
       " 150,\n",
       " 174,\n",
       " 176,\n",
       " 182,\n",
       " 197,\n",
       " 229,\n",
       " 236,\n",
       " 255,\n",
       " 257,\n",
       " 259,\n",
       " 260,\n",
       " 290,\n",
       " 297,\n",
       " 301,\n",
       " 307,\n",
       " 317,\n",
       " 325,\n",
       " 332,\n",
       " 370,\n",
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       " 19893,\n",
       " 19905,\n",
       " 19958,\n",
       " 19959,\n",
       " 19962,\n",
       " 19964,\n",
       " 19965,\n",
       " 19996,\n",
       " 20003,\n",
       " 20064,\n",
       " 20512,\n",
       " 20513,\n",
       " 20536,\n",
       " 20552,\n",
       " 20612,\n",
       " 20664,\n",
       " 20766,\n",
       " 20789,\n",
       " 20978,\n",
       " 21047,\n",
       " 21049,\n",
       " 21080,\n",
       " 21164,\n",
       " 21193,\n",
       " 21252,\n",
       " 21272,\n",
       " 21422,\n",
       " 21489,\n",
       " 21796,\n",
       " 21897,\n",
       " 21898,\n",
       " 21926,\n",
       " 21949,\n",
       " 22321,\n",
       " 22426,\n",
       " 22530,\n",
       " 23355,\n",
       " 23476,\n",
       " 23787,\n",
       " 23801,\n",
       " 23815,\n",
       " 23824,\n",
       " 24173,\n",
       " 24366,\n",
       " 24928,\n",
       " 26420,\n",
       " 26421,\n",
       " 27983,\n",
       " 29336,\n",
       " 32624,\n",
       " 38819,\n",
       " 39042,\n",
       " 42643,\n",
       " 42701,\n",
       " 42703,\n",
       " 42704,\n",
       " 42705,\n",
       " 47273,\n",
       " 51259]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[int(x) for x in book_ids.columns[2:]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ae04e8d8-8840-4e91-b533-0c523eaae88a",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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