spotify_dummy_sparse.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10000\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(10000, 3)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import scipy as sp\n",
    "\n",
    "df = pd.read_csv(r'F:\\AppliedDataScience\\data\\ratingdf_likescore.csv')\n",
    "print(len(df))\n",
    "\n",
    "df2 = df[['session_id','track_id','rating']]\n",
    "\n",
    "display(df2.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>session_id</th>\n",
       "      <th>track_id</th>\n",
       "      <th>rating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0_00006f66-33e5-4de7-a324-2d18e439fc1e</td>\n",
       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>4.0</td>\n",
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       "      <td>0.9</td>\n",
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       "      <td>t_0479f24c-27d2-46d6-a00c-7ec928f2b539</td>\n",
       "      <td>3.0</td>\n",
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       "      <th>3</th>\n",
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       "      <td>2.3</td>\n",
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      ],
      "text/plain": [
       "                               session_id  \\\n",
       "0  0_00006f66-33e5-4de7-a324-2d18e439fc1e   \n",
       "1  0_00079a23-1600-486a-91bd-5208be0c745a   \n",
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       "3  0_013cc010-c476-4ad2-8972-73449e0b2ef4   \n",
       "4  0_01a5f0dc-9938-48c9-92f1-c7e51f34d290   \n",
       "\n",
       "                                 track_id  rating  \n",
       "0  t_0479f24c-27d2-46d6-a00c-7ec928f2b539     4.0  \n",
       "1  t_0479f24c-27d2-46d6-a00c-7ec928f2b539     0.9  \n",
       "2  t_0479f24c-27d2-46d6-a00c-7ec928f2b539     3.0  \n",
       "3  t_0479f24c-27d2-46d6-a00c-7ec928f2b539     2.3  \n",
       "4  t_0479f24c-27d2-46d6-a00c-7ec928f2b539     2.5  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Memory usage is 1.12 MB\n"
     ]
    }
   ],
   "source": [
    "BYTES_TO_MB_DIV = 0.000001\n",
    "def print_memory_usage_of_data_frame(df2):\n",
    "    mem = round(df.memory_usage().sum() * BYTES_TO_MB_DIV, 3) \n",
    "    print(\"Memory usage is \" + str(mem) + \" MB\")\n",
    "    \n",
    "print_memory_usage_of_data_frame(df2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "<p>5 rows × 13226 columns</p>\n",
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      "text/plain": [
       "   rating  session_id_0_00006f66-33e5-4de7-a324-2d18e439fc1e  \\\n",
       "0     4.0                                                  1   \n",
       "1     0.9                                                  0   \n",
       "2     3.0                                                  0   \n",
       "3     2.3                                                  0   \n",
       "4     2.5                                                  0   \n",
       "\n",
       "   session_id_0_0000a72b-09ac-412f-b452-9b9e79bded8f  \\\n",
       "0                                                  0   \n",
       "1                                                  0   \n",
       "2                                                  0   \n",
       "3                                                  0   \n",
       "4                                                  0   \n",
       "\n",
       "   session_id_0_00010fc5-b79e-4cdf-bc4c-f140d0f99a3a  \\\n",
       "0                                                  0   \n",
       "1                                                  0   \n",
       "2                                                  0   \n",
       "3                                                  0   \n",
       "4                                                  0   \n",
       "\n",
       "   session_id_0_00016a3d-9076-4f67-918f-f29e3ce160dc  \\\n",
       "0                                                  0   \n",
       "1                                                  0   \n",
       "2                                                  0   \n",
       "3                                                  0   \n",
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       "\n",
       "   session_id_0_00018b58-deb8-4f98-ac5e-d7e01b346130  \\\n",
       "0                                                  0   \n",
       "1                                                  0   \n",
       "2                                                  0   \n",
       "3                                                  0   \n",
       "4                                                  0   \n",
       "\n",
       "   session_id_0_00027db1-ffe5-4b00-8eeb-8d8188451298  \\\n",
       "0                                                  0   \n",
       "1                                                  0   \n",
       "2                                                  0   \n",
       "3                                                  0   \n",
       "4                                                  0   \n",
       "\n",
       "   session_id_0_00029482-6542-4d3e-bb9e-ffc988f58bd6  \\\n",
       "0                                                  0   \n",
       "1                                                  0   \n",
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       "3                                                  0   \n",
       "4                                                  0   \n",
       "\n",
       "   session_id_0_0002fbb5-29c2-4d54-9636-e6d15e77b58c  \\\n",
       "0                                                  0   \n",
       "1                                                  0   \n",
       "2                                                  0   \n",
       "3                                                  0   \n",
       "4                                                  0   \n",
       "\n",
       "   session_id_0_00030fe3-298d-4930-8534-fc5a9b82971b  \\\n",
       "0                                                  0   \n",
       "1                                                  0   \n",
       "2                                                  0   \n",
       "3                                                  0   \n",
       "4                                                  0   \n",
       "\n",
       "                        ...                         \\\n",
       "0                       ...                          \n",
       "1                       ...                          \n",
       "2                       ...                          \n",
       "3                       ...                          \n",
       "4                       ...                          \n",
       "\n",
       "   track_id_t_ffb7ca71-83d3-46f3-a579-d2630476ab74  \\\n",
       "0                                                0   \n",
       "1                                                0   \n",
       "2                                                0   \n",
       "3                                                0   \n",
       "4                                                0   \n",
       "\n",
       "   track_id_t_ffc37789-d3ce-4aa6-8e89-067ab0f18b21  \\\n",
       "0                                                0   \n",
       "1                                                0   \n",
       "2                                                0   \n",
       "3                                                0   \n",
       "4                                                0   \n",
       "\n",
       "   track_id_t_ffc47bd8-2feb-4f10-8f33-d9b2a9916a24  \\\n",
       "0                                                0   \n",
       "1                                                0   \n",
       "2                                                0   \n",
       "3                                                0   \n",
       "4                                                0   \n",
       "\n",
       "   track_id_t_ffc7e0ca-abdd-41e4-849d-9c4077e5fc0a  \\\n",
       "0                                                0   \n",
       "1                                                0   \n",
       "2                                                0   \n",
       "3                                                0   \n",
       "4                                                0   \n",
       "\n",
       "   track_id_t_ffc9bec7-76fb-43e2-8b82-1bcdeb7ff3de  \\\n",
       "0                                                0   \n",
       "1                                                0   \n",
       "2                                                0   \n",
       "3                                                0   \n",
       "4                                                0   \n",
       "\n",
       "   track_id_t_ffcb69c4-ff37-4715-8b74-0d8ba7a62054  \\\n",
       "0                                                0   \n",
       "1                                                0   \n",
       "2                                                0   \n",
       "3                                                0   \n",
       "4                                                0   \n",
       "\n",
       "   track_id_t_ffce5f0c-85f8-48e9-8d19-476b13ced5b2  \\\n",
       "0                                                0   \n",
       "1                                                0   \n",
       "2                                                0   \n",
       "3                                                0   \n",
       "4                                                0   \n",
       "\n",
       "   track_id_t_ffd25283-d868-4ace-a8e4-6c210bf56fe0  \\\n",
       "0                                                0   \n",
       "1                                                0   \n",
       "2                                                0   \n",
       "3                                                0   \n",
       "4                                                0   \n",
       "\n",
       "   track_id_t_ffd5b4a5-60c7-43b1-9a5c-bf43491dc7d2  \\\n",
       "0                                                0   \n",
       "1                                                0   \n",
       "2                                                0   \n",
       "3                                                0   \n",
       "4                                                0   \n",
       "\n",
       "   track_id_t_ffe8cf3c-0862-4d08-bf52-1ba574bf7593  \n",
       "0                                                0  \n",
       "1                                                0  \n",
       "2                                                0  \n",
       "3                                                0  \n",
       "4                                                0  \n",
       "\n",
       "[5 rows x 13226 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(10000, 13226)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Memory usage is 1.12 MB\n"
     ]
    }
   ],
   "source": [
    "data_one_hot = pd.get_dummies(df2, columns=['session_id', 'track_id'])\n",
    "display(data_one_hot.head())\n",
    "display(data_one_hot.shape)\n",
    "print_memory_usage_of_data_frame(data_one_hot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10000, 13226)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_one_hot.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data_one_hot2 = data_one_hot.drop('rating',axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
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       "    .dataframe thead th {\n",
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       "      <th>track_id_t_ffb7ca71-83d3-46f3-a579-d2630476ab74</th>\n",
       "      <th>track_id_t_ffc37789-d3ce-4aa6-8e89-067ab0f18b21</th>\n",
       "      <th>track_id_t_ffc47bd8-2feb-4f10-8f33-d9b2a9916a24</th>\n",
       "      <th>track_id_t_ffc7e0ca-abdd-41e4-849d-9c4077e5fc0a</th>\n",
       "      <th>track_id_t_ffc9bec7-76fb-43e2-8b82-1bcdeb7ff3de</th>\n",
       "      <th>track_id_t_ffcb69c4-ff37-4715-8b74-0d8ba7a62054</th>\n",
       "      <th>track_id_t_ffce5f0c-85f8-48e9-8d19-476b13ced5b2</th>\n",
       "      <th>track_id_t_ffd25283-d868-4ace-a8e4-6c210bf56fe0</th>\n",
       "      <th>track_id_t_ffd5b4a5-60c7-43b1-9a5c-bf43491dc7d2</th>\n",
       "      <th>track_id_t_ffe8cf3c-0862-4d08-bf52-1ba574bf7593</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "    </tr>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 13225 columns</p>\n",
       "</div>"
      ],
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       "   session_id_0_00006f66-33e5-4de7-a324-2d18e439fc1e  \\\n",
       "0                                                  1   \n",
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       "   session_id_0_00010fc5-b79e-4cdf-bc4c-f140d0f99a3a  \\\n",
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       "   session_id_0_00027db1-ffe5-4b00-8eeb-8d8188451298  \\\n",
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       "   session_id_0_0003ac37-c70a-47a6-b9dc-b8b163826082  \\\n",
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       "\n",
       "                        ...                         \\\n",
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       "1                       ...                          \n",
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       "3                       ...                          \n",
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       "\n",
       "   track_id_t_ffb7ca71-83d3-46f3-a579-d2630476ab74  \\\n",
       "0                                                0   \n",
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       "2                                                0   \n",
       "3                                                0   \n",
       "4                                                0   \n",
       "\n",
       "   track_id_t_ffc37789-d3ce-4aa6-8e89-067ab0f18b21  \\\n",
       "0                                                0   \n",
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       "3                                                0   \n",
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       "\n",
       "   track_id_t_ffc47bd8-2feb-4f10-8f33-d9b2a9916a24  \\\n",
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       "3                                                0   \n",
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       "\n",
       "   track_id_t_ffc7e0ca-abdd-41e4-849d-9c4077e5fc0a  \\\n",
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       "3                                                0   \n",
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       "\n",
       "   track_id_t_ffc9bec7-76fb-43e2-8b82-1bcdeb7ff3de  \\\n",
       "0                                                0   \n",
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       "3                                                0   \n",
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       "\n",
       "   track_id_t_ffcb69c4-ff37-4715-8b74-0d8ba7a62054  \\\n",
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       "1                                                0   \n",
       "2                                                0   \n",
       "3                                                0   \n",
       "4                                                0   \n",
       "\n",
       "   track_id_t_ffce5f0c-85f8-48e9-8d19-476b13ced5b2  \\\n",
       "0                                                0   \n",
       "1                                                0   \n",
       "2                                                0   \n",
       "3                                                0   \n",
       "4                                                0   \n",
       "\n",
       "   track_id_t_ffd25283-d868-4ace-a8e4-6c210bf56fe0  \\\n",
       "0                                                0   \n",
       "1                                                0   \n",
       "2                                                0   \n",
       "3                                                0   \n",
       "4                                                0   \n",
       "\n",
       "   track_id_t_ffd5b4a5-60c7-43b1-9a5c-bf43491dc7d2  \\\n",
       "0                                                0   \n",
       "1                                                0   \n",
       "2                                                0   \n",
       "3                                                0   \n",
       "4                                                0   \n",
       "\n",
       "   track_id_t_ffe8cf3c-0862-4d08-bf52-1ba574bf7593  \n",
       "0                                                0  \n",
       "1                                                0  \n",
       "2                                                0  \n",
       "3                                                0  \n",
       "4                                                0  \n",
       "\n",
       "[5 rows x 13225 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_one_hot2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10000, 13225)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_one_hot2.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data_one_hot2_arr = data_one_hot2.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "cannot reshape array of size 132250000 into shape (4,3306250)",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-10-a4c59b7f2cea>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mdata_one_hot2_new\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdata_one_hot2_arr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m4\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m3306250\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m: cannot reshape array of size 132250000 into shape (4,3306250)"
     ]
    }
   ],
   "source": [
    "data_one_hot2_new = data_one_hot2_arr.reshape(4,3306250)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\n",
    "data_one_hot_sparse = data_one_hot2.to_sparse()\n",
    "#display(data_one_hot_sparse.dtypes)\n",
    "#print_memory_usage_of_sparse_data_frame(data_one_hot_sparse)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
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       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 13225 columns</p>\n",
       "</div>"
      ],
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       "   track_id_t_ffd25283-d868-4ace-a8e4-6c210bf56fe0  \\\n",
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       "[5 rows x 13225 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_one_hot_sparse.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "session_id_0_00006f66-33e5-4de7-a324-2d18e439fc1e    uint8\n",
       "session_id_0_0000a72b-09ac-412f-b452-9b9e79bded8f    uint8\n",
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       "session_id_0_0003ac37-c70a-47a6-b9dc-b8b163826082    uint8\n",
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       "session_id_0_00054512-7872-45c0-aaec-7b790f698a4f    uint8\n",
       "session_id_0_0005a7a1-196e-4e08-8928-39b9a3ca2e1a    uint8\n",
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       "session_id_0_0009367d-0072-4f19-8458-e291ddbbbd25    uint8\n",
       "                                                     ...  \n",
       "track_id_t_fe8fdb29-4cf3-4e87-acb0-9fa76ff5d874      uint8\n",
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       "track_id_t_ffb7ca71-83d3-46f3-a579-d2630476ab74      uint8\n",
       "track_id_t_ffc37789-d3ce-4aa6-8e89-067ab0f18b21      uint8\n",
       "track_id_t_ffc47bd8-2feb-4f10-8f33-d9b2a9916a24      uint8\n",
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       "track_id_t_ffcb69c4-ff37-4715-8b74-0d8ba7a62054      uint8\n",
       "track_id_t_ffce5f0c-85f8-48e9-8d19-476b13ced5b2      uint8\n",
       "track_id_t_ffd25283-d868-4ace-a8e4-6c210bf56fe0      uint8\n",
       "track_id_t_ffd5b4a5-60c7-43b1-9a5c-bf43491dc7d2      uint8\n",
       "track_id_t_ffe8cf3c-0862-4d08-bf52-1ba574bf7593      uint8\n",
       "Length: 13225, dtype: object"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "ename": "NameError",
     "evalue": "name 'print_memory_usage_of_sparse_data_frame' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-12-b08b060b67be>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0mdisplay\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata_one_hot_sparse\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdtypes\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mprint_memory_usage_of_sparse_data_frame\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata_one_hot_sparse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m: name 'print_memory_usage_of_sparse_data_frame' is not defined"
     ]
    }
   ],
   "source": [
    "display(data_one_hot_sparse.dtypes)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Memory usage is 1.12 MB\n"
     ]
    }
   ],
   "source": [
    "print_memory_usage_of_data_frame(data_one_hot_sparse)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "rating_df = data_one_hot[['rating']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Memory usage is 1.12 MB\n",
      "Memory usage is 1.12 MB\n"
     ]
    }
   ],
   "source": [
    "y = data_one_hot['rating']\n",
    "X = data_one_hot[data_one_hot.columns.difference(['rating'])]\n",
    "y_sparse = data_one_hot['rating']\n",
    "X_sparse = data_one_hot[data_one_hot.columns.difference(['rating'])]\n",
    "print_memory_usage_of_data_frame(X)\n",
    "print_memory_usage_of_data_frame(X_sparse)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "vector_dict_df = pd.DataFrame(vector_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th>Pandas dataframe</th>\n",
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      "text/plain": [
       "                                    Pandas dataframe  \\\n",
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       "\n",
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       "1  0       4.0\n",
       "1       0.9\n",
       "2       3.0\n",
       "3       2....  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
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    }
   ],
   "source": [
    "vector_dict_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn import metrics\n",
    "for key, item in vector_dict.items():\n",
    "    \n",
    "    #print(key)\n",
    "    \n",
    "    start = time.time()\n",
    "    X_train, X_test, y_train, y_test = train_test_split(item[0], item[1], test_size=0.3, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
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       "</table>\n",
       "<p>5 rows × 13225 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      session_id_0_00006f66-33e5-4de7-a324-2d18e439fc1e  \\\n",
       "9069                                                  0   \n",
       "2603                                                  0   \n",
       "7738                                                  0   \n",
       "1579                                                  0   \n",
       "5058                                                  0   \n",
       "\n",
       "      session_id_0_0000a72b-09ac-412f-b452-9b9e79bded8f  \\\n",
       "9069                                                  0   \n",
       "2603                                                  0   \n",
       "7738                                                  0   \n",
       "1579                                                  0   \n",
       "5058                                                  0   \n",
       "\n",
       "      session_id_0_00010fc5-b79e-4cdf-bc4c-f140d0f99a3a  \\\n",
       "9069                                                  0   \n",
       "2603                                                  0   \n",
       "7738                                                  0   \n",
       "1579                                                  0   \n",
       "5058                                                  0   \n",
       "\n",
       "      session_id_0_00016a3d-9076-4f67-918f-f29e3ce160dc  \\\n",
       "9069                                                  0   \n",
       "2603                                                  0   \n",
       "7738                                                  0   \n",
       "1579                                                  0   \n",
       "5058                                                  0   \n",
       "\n",
       "      session_id_0_00018b58-deb8-4f98-ac5e-d7e01b346130  \\\n",
       "9069                                                  0   \n",
       "2603                                                  0   \n",
       "7738                                                  0   \n",
       "1579                                                  0   \n",
       "5058                                                  0   \n",
       "\n",
       "      session_id_0_00027db1-ffe5-4b00-8eeb-8d8188451298  \\\n",
       "9069                                                  0   \n",
       "2603                                                  0   \n",
       "7738                                                  0   \n",
       "1579                                                  0   \n",
       "5058                                                  0   \n",
       "\n",
       "      session_id_0_00029482-6542-4d3e-bb9e-ffc988f58bd6  \\\n",
       "9069                                                  0   \n",
       "2603                                                  0   \n",
       "7738                                                  0   \n",
       "1579                                                  0   \n",
       "5058                                                  0   \n",
       "\n",
       "      session_id_0_0002fbb5-29c2-4d54-9636-e6d15e77b58c  \\\n",
       "9069                                                  0   \n",
       "2603                                                  0   \n",
       "7738                                                  0   \n",
       "1579                                                  0   \n",
       "5058                                                  0   \n",
       "\n",
       "      session_id_0_00030fe3-298d-4930-8534-fc5a9b82971b  \\\n",
       "9069                                                  0   \n",
       "2603                                                  0   \n",
       "7738                                                  0   \n",
       "1579                                                  0   \n",
       "5058                                                  0   \n",
       "\n",
       "      session_id_0_0003ac37-c70a-47a6-b9dc-b8b163826082  \\\n",
       "9069                                                  0   \n",
       "2603                                                  0   \n",
       "7738                                                  0   \n",
       "1579                                                  0   \n",
       "5058                                                  0   \n",
       "\n",
       "                           ...                         \\\n",
       "9069                       ...                          \n",
       "2603                       ...                          \n",
       "7738                       ...                          \n",
       "1579                       ...                          \n",
       "5058                       ...                          \n",
       "\n",
       "      track_id_t_ffb7ca71-83d3-46f3-a579-d2630476ab74  \\\n",
       "9069                                                0   \n",
       "2603                                                0   \n",
       "7738                                                0   \n",
       "1579                                                0   \n",
       "5058                                                0   \n",
       "\n",
       "      track_id_t_ffc37789-d3ce-4aa6-8e89-067ab0f18b21  \\\n",
       "9069                                                0   \n",
       "2603                                                0   \n",
       "7738                                                0   \n",
       "1579                                                0   \n",
       "5058                                                0   \n",
       "\n",
       "      track_id_t_ffc47bd8-2feb-4f10-8f33-d9b2a9916a24  \\\n",
       "9069                                                0   \n",
       "2603                                                0   \n",
       "7738                                                0   \n",
       "1579                                                0   \n",
       "5058                                                0   \n",
       "\n",
       "      track_id_t_ffc7e0ca-abdd-41e4-849d-9c4077e5fc0a  \\\n",
       "9069                                                0   \n",
       "2603                                                0   \n",
       "7738                                                0   \n",
       "1579                                                0   \n",
       "5058                                                0   \n",
       "\n",
       "      track_id_t_ffc9bec7-76fb-43e2-8b82-1bcdeb7ff3de  \\\n",
       "9069                                                0   \n",
       "2603                                                0   \n",
       "7738                                                0   \n",
       "1579                                                0   \n",
       "5058                                                0   \n",
       "\n",
       "      track_id_t_ffcb69c4-ff37-4715-8b74-0d8ba7a62054  \\\n",
       "9069                                                0   \n",
       "2603                                                0   \n",
       "7738                                                0   \n",
       "1579                                                0   \n",
       "5058                                                0   \n",
       "\n",
       "      track_id_t_ffce5f0c-85f8-48e9-8d19-476b13ced5b2  \\\n",
       "9069                                                0   \n",
       "2603                                                0   \n",
       "7738                                                0   \n",
       "1579                                                0   \n",
       "5058                                                0   \n",
       "\n",
       "      track_id_t_ffd25283-d868-4ace-a8e4-6c210bf56fe0  \\\n",
       "9069                                                0   \n",
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       "7738                                                0   \n",
       "1579                                                0   \n",
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       "\n",
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       "9069                                                0   \n",
       "2603                                                0   \n",
       "7738                                                0   \n",
       "1579                                                0   \n",
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       "\n",
       "      track_id_t_ffe8cf3c-0862-4d08-bf52-1ba574bf7593  \n",
       "9069                                                0  \n",
       "2603                                                0  \n",
       "7738                                                0  \n",
       "1579                                                0  \n",
       "5058                                                0  \n",
       "\n",
       "[5 rows x 13225 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9069    0.3\n",
       "2603    0.5\n",
       "7738    0.8\n",
       "1579   -0.7\n",
       "5058    2.8\n",
       "Name: rating, dtype: float64"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DecisionTreeClassifier(class_weight=None, criterion='gini', max_depth=None,\n",
       "            max_features=None, max_leaf_nodes=20,\n",
       "            min_impurity_decrease=0.0, min_impurity_split=None,\n",
       "            min_samples_leaf=1, min_samples_split=2,\n",
       "            min_weight_fraction_leaf=0.0, presort=False, random_state=None,\n",
       "            splitter='best')"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf = DecisionTreeClassifier(max_depth=None, max_leaf_nodes=20)\n",
    "\n",
    "from sklearn import tree\n",
    "clf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "Unknown label type: 'continuous'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-42-48a2aac41443>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mclf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mX_train\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my_train\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\sklearn\\tree\\tree.py\u001b[0m in \u001b[0;36mfit\u001b[1;34m(self, X, y, sample_weight, check_input, X_idx_sorted)\u001b[0m\n\u001b[0;32m    788\u001b[0m             \u001b[0msample_weight\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msample_weight\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    789\u001b[0m             \u001b[0mcheck_input\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mcheck_input\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 790\u001b[1;33m             X_idx_sorted=X_idx_sorted)\n\u001b[0m\u001b[0;32m    791\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    792\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\sklearn\\tree\\tree.py\u001b[0m in \u001b[0;36mfit\u001b[1;34m(self, X, y, sample_weight, check_input, X_idx_sorted)\u001b[0m\n\u001b[0;32m    138\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    139\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mis_classification\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 140\u001b[1;33m             \u001b[0mcheck_classification_targets\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    141\u001b[0m             \u001b[0my\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcopy\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    142\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\sklearn\\utils\\multiclass.py\u001b[0m in \u001b[0;36mcheck_classification_targets\u001b[1;34m(y)\u001b[0m\n\u001b[0;32m    170\u001b[0m     if y_type not in ['binary', 'multiclass', 'multiclass-multioutput',\n\u001b[0;32m    171\u001b[0m                       'multilabel-indicator', 'multilabel-sequences']:\n\u001b[1;32m--> 172\u001b[1;33m         \u001b[1;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Unknown label type: %r\"\u001b[0m \u001b[1;33m%\u001b[0m \u001b[0my_type\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    173\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    174\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mValueError\u001b[0m: Unknown label type: 'continuous'"
     ]
    }
   ],
   "source": [
    "clf.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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