Extraccion_de_caracteristicas.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from scipy import stats\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import sklearn\n",
    "from sklearn.decomposition import PCA\n",
    "from mpl_toolkits.mplot3d import Axes3D"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>local</th>\n",
       "      <th>mac</th>\n",
       "      <th>ventanas</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1101049</td>\n",
       "      <td>00:00:06:AF:43:11</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1101049</td>\n",
       "      <td>00:02:C3:DF:7D:CA</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1101049</td>\n",
       "      <td>00:03:AA:FD:56:45</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1101049</td>\n",
       "      <td>00:08:22:04:29:44</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1101049</td>\n",
       "      <td>00:08:22:0A:5E:FC</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     local                mac  ventanas\n",
       "0  1101049  00:00:06:AF:43:11        19\n",
       "1  1101049  00:02:C3:DF:7D:CA         7\n",
       "2  1101049  00:03:AA:FD:56:45         6\n",
       "3  1101049  00:08:22:04:29:44         7\n",
       "4  1101049  00:08:22:0A:5E:FC        17"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aux = pd.read_csv('auxdiario_dia_junio.csv', header = None)\n",
    "aux.columns = ['local', 'mac', 'ventanas']\n",
    "aux.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\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>local</th>\n",
       "      <th>ventanas</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>3.399920e+05</td>\n",
       "      <td>339992.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>5.057247e+06</td>\n",
       "      <td>71.641918</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.143743e+07</td>\n",
       "      <td>234.181151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.101049e+06</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.108103e+06</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.201003e+06</td>\n",
       "      <td>4.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.210103e+07</td>\n",
       "      <td>29.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.301077e+08</td>\n",
       "      <td>8285.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              local       ventanas\n",
       "count  3.399920e+05  339992.000000\n",
       "mean   5.057247e+06      71.641918\n",
       "std    1.143743e+07     234.181151\n",
       "min    1.101049e+06       1.000000\n",
       "25%    1.108103e+06       2.000000\n",
       "50%    1.201003e+06       4.000000\n",
       "75%    1.210103e+07      29.000000\n",
       "max    1.301077e+08    8285.000000"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aux.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Filtrado de usuarios por cantidad de uso"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Se filtran los datos que no son de interés, esto es, nos quedamos con los dispositivos que estuvieron al menos 1 hora a lo largo del mes, y los que estuvieron a lo sumo 15 hs 22 dias en el mes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "\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>local</th>\n",
       "      <th>ventanas</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1.162380e+05</td>\n",
       "      <td>116238.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>5.846681e+06</td>\n",
       "      <td>192.508362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.042101e+07</td>\n",
       "      <td>268.571893</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.101049e+06</td>\n",
       "      <td>13.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.113120e+06</td>\n",
       "      <td>27.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.204409e+06</td>\n",
       "      <td>76.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.211111e+07</td>\n",
       "      <td>267.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.301077e+08</td>\n",
       "      <td>3957.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              local       ventanas\n",
       "count  1.162380e+05  116238.000000\n",
       "mean   5.846681e+06     192.508362\n",
       "std    1.042101e+07     268.571893\n",
       "min    1.101049e+06      13.000000\n",
       "25%    1.113120e+06      27.000000\n",
       "50%    1.204409e+06      76.000000\n",
       "75%    1.211111e+07     267.000000\n",
       "max    1.301077e+08    3957.000000"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aux = aux[aux.ventanas.between(13, 22*15*12)]\n",
    "aux.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = aux.ventanas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.xlabel('total time windows')\n",
    "plt.ylabel('devices in bin')\n",
    "plt.title('time windows histogram')\n",
    "plt.hist(x, bins=50)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Chequeo la existencia de outliers al realizar transformación logarítmica"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.log(aux.ventanas)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplot(1, 2, 1)\n",
    "plt.xlabel('total time windows')\n",
    "plt.ylabel('devices in bin')\n",
    "plt.title('time windows histogram')\n",
    "plt.hist(x, bins=50)\n",
    "\n",
    "plt.subplot(1, 2, 2)\n",
    "plt.title('time windows boxplot')\n",
    "plt.boxplot(x)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.295837 2.564949]\n",
      "[5.587249 8.283241]\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "B = plt.boxplot(x)\n",
    "for item in B['whiskers']:\n",
    "    print(np.round(item.get_ydata(), 6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "238469    8.283241\n",
       "Name: ventanas, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Series([], Name: ventanas, dtype: float64)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(x[x > 8.283241])\n",
    "display(x[x < 2.564949])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Chequeo la existencia de outliers al realizar transformación box-cox"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "x, _ = stats.boxcox(aux.ventanas)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplot(1, 2, 1)\n",
    "plt.xlabel('total time windows')\n",
    "plt.ylabel('devices in bin')\n",
    "plt.title('time windows histogram')\n",
    "plt.hist(x, bins=50)\n",
    "\n",
    "plt.subplot(1, 2, 2)\n",
    "plt.title('time windows boxplot')\n",
    "plt.boxplot(x)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2.73061798 2.21320761]\n",
      "[4.09157797 5.28609964]\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "B = plt.boxplot(x)\n",
    "for item in B['whiskers']:\n",
    "    print(item.get_ydata())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([], dtype=float64)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "array([], dtype=float64)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(x[x > 5.2861 ])\n",
    "display(x[x < 2.21320761])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Observaciones de outliers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Confirmamos que al realizar una transformación logarítmica no se ven outliers y al realizar una transformación box cox de los datos tampoco."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Aplico filtro al dataset original"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>local</th>\n",
       "      <th>mac</th>\n",
       "      <th>ventanas</th>\n",
       "      <th>concat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1101049</td>\n",
       "      <td>00:00:06:AF:43:11</td>\n",
       "      <td>19</td>\n",
       "      <td>1101049concat00:00:06:AF:43:11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1101049</td>\n",
       "      <td>00:08:22:0A:5E:FC</td>\n",
       "      <td>17</td>\n",
       "      <td>1101049concat00:08:22:0A:5E:FC</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     local                mac  ventanas                          concat\n",
       "0  1101049  00:00:06:AF:43:11        19  1101049concat00:00:06:AF:43:11\n",
       "4  1101049  00:08:22:0A:5E:FC        17  1101049concat00:08:22:0A:5E:FC"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aux['concat'] = aux['local'].astype('str') + 'concat' + aux['mac']\n",
    "aux.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "datos = pd.read_csv('auxdiario_fecha_junio.csv', names = ['local', 'mac', 'app', 'fecha', 'ventanas'])\n",
    "datos['concat'] = datos['local'].astype('str') + 'concat' + datos['mac']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# genero lista de macs aprobadas para su inclusión en el estudio\n",
    "macs_aprobadas = aux.concat.tolist()\n",
    "aux = None\n",
    "# guardo un dataset que contenga solamente las macs aprobadas\n",
    "datos[datos['concat'].isin(macs_aprobadas)][['local', 'mac', 'app', 'fecha', 'ventanas']].to_csv('junio_filtrado.csv', index=False)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Cuales son las apps mas importantes?\n",
    "Las aplicaciones a utilizar salen del dataset: para ver las apps mas relevantes se toman las observaciones de cada equipo por cada aplicacion y simplemente se suman dichas observaciones para cada aplicacion, de esta forma nos quedamos con la cantidad total de veces en las que hubo un registro de uso (individual) de dicha app.\n",
    "Se considero un umbral mínimo 2000 registros de uso individual en el mes para tomar en cuenta la aplicacion."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>local</th>\n",
       "      <th>mac</th>\n",
       "      <th>app</th>\n",
       "      <th>fecha</th>\n",
       "      <th>ventanas</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1101049</td>\n",
       "      <td>00:00:06:AF:43:11</td>\n",
       "      <td>DNS</td>\n",
       "      <td>2018-06-08</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1101049</td>\n",
       "      <td>00:00:06:AF:43:11</td>\n",
       "      <td>DNS</td>\n",
       "      <td>2018-06-20</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1101049</td>\n",
       "      <td>00:00:06:AF:43:11</td>\n",
       "      <td>DNS</td>\n",
       "      <td>2018-06-21</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1101049</td>\n",
       "      <td>00:00:06:AF:43:11</td>\n",
       "      <td>DNS</td>\n",
       "      <td>2018-06-22</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1101049</td>\n",
       "      <td>00:00:06:AF:43:11</td>\n",
       "      <td>Facebook</td>\n",
       "      <td>2018-06-08</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     local                mac       app       fecha  ventanas\n",
       "0  1101049  00:00:06:AF:43:11       DNS  2018-06-08         4\n",
       "1  1101049  00:00:06:AF:43:11       DNS  2018-06-20         2\n",
       "2  1101049  00:00:06:AF:43:11       DNS  2018-06-21         2\n",
       "3  1101049  00:00:06:AF:43:11       DNS  2018-06-22         4\n",
       "4  1101049  00:00:06:AF:43:11  Facebook  2018-06-08         5"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "datos = pd.read_csv('junio_filtrado.csv')\n",
    "datos.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>app</th>\n",
       "      <th>ventanas</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Google</td>\n",
       "      <td>18480573</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>Unknown</td>\n",
       "      <td>17544626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>DNS</td>\n",
       "      <td>14351017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>SSL</td>\n",
       "      <td>14014874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Facebook</td>\n",
       "      <td>11212664</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          app  ventanas\n",
       "27     Google  18480573\n",
       "132   Unknown  17544626\n",
       "15        DNS  14351017\n",
       "104       SSL  14014874\n",
       "22   Facebook  11212664"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "apps_importantes = datos.groupby(['app'])[['ventanas']].sum().reset_index().sort_values('ventanas', ascending=False)\n",
    "display(apps_importantes.head())\n",
    "\n",
    "categorizacion = ['Navegacion','drop','Navegacion','Navegacion','Red_social','Comunicacion','Navegacion',\n",
    "                  'Red_social','drop','drop','Navegacion','drop','Comunicacion','drop',\n",
    "                  'Navegacion_Ceibal','Multimedia_videos','drop','drop','Apple','Marketplace','drop','Microsoft',\n",
    "                  'Red_social','drop','correo','almacenamiento','Comunicacion','drop','Navegacion','Multimedia_musica',\n",
    "                  'Multimedia_videos','drop','drop','drop','drop','herramienta_educativa','Navegacion','drop',\n",
    "                  'Red_social','Multimedia_musica','drop','almacenamiento','Navegacion_Ceibal','drop',\n",
    "                  'herramienta_educativa','almacenamiento','Navegacion','Multimedia_videos','correo',\n",
    "                  'Educacion_Ceibal','drop','red','Navegacion_Ceibal','GoogleMaps','Red_social','Educacion_Ceibal',\n",
    "                  'drop','drop','ibirapita_Ceibal','Multimedia_videos','drop','drop','Educacion_Ceibal',\n",
    "                  'Comunicacion','drop','drop','Marketplace','herramienta_educativa','Educacion_Ceibal','Multimedia_musica',\n",
    "                  'Comunicacion','drop','Navegacion_Ceibal','Navegacion_Ceibal','drop','drop','drop','drop']\n",
    "drop_list = ['Microsoft', 'Apple', 'drop', 'red']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### apps relevantes cuya categorización no fue evidente\n",
    "- 'ingreso_Ceibal':lo puse como Educacion_Ceibal porque asumo que es lo que hay que hacer para loguearse en las plataformas de aprendizaje\n",
    "- 'ibirapita_Ceibal':lo dejé como categoría separada\n",
    "- 'portal_ceibal':lo pasé a Navegacion_ceibal\n",
    "- 'Schoology-Ceibal': lo pasé a Navegacion_ceibal\n",
    "- 'miespacio_Ceibal':  lo pasé a Navegacion_ceibal\n",
    "\n",
    "##### apps relevantes eliminadas:\n",
    "- 'PCA Ceibal', al igual que todas las etiquetas pertenecientes a protocolos de red (o a cualquier cosa cuya finalidad sea permitir la comunicación entre los dispositivos y la red) fue categorizado como 'drop' y desestimado.\n",
    "- 'Microsoft', al igual que las otras etiquetas que están vinculadas a la actualizacion de apps, software, etc fueron eliminadas.\n",
    "- 'Apple', fue eliminado bajo la sospecha de ser la tienda de apple o aplicaciones internas de apple. En caso de estar indicando cualquier aplicación de apple, tampoco nos serviría pues no es lo suficientemente específico."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Nos quedamos con 46 aps, de las cuales 13 son etiquetas unicas\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.5/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "    }\n",
       "\n",
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       "        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>Categorizacion</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>app</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Viber</th>\n",
       "      <td>Comunicacion</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WhatsApp</th>\n",
       "      <td>Comunicacion</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Telegram</th>\n",
       "      <td>Comunicacion</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Skype</th>\n",
       "      <td>Comunicacion</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>QQ</th>\n",
       "      <td>Comunicacion</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>aulas_Ceibal</th>\n",
       "      <td>Educacion_Ceibal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bibliotecadigital_Ceibal</th>\n",
       "      <td>Educacion_Ceibal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pam_Ceibal</th>\n",
       "      <td>Educacion_Ceibal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ingreso_Ceibal</th>\n",
       "      <td>Educacion_Ceibal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GoogleMaps</th>\n",
       "      <td>GoogleMaps</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>eBay</th>\n",
       "      <td>Marketplace</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Amazon</th>\n",
       "      <td>Marketplace</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Spotify</th>\n",
       "      <td>Multimedia_musica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Deezer</th>\n",
       "      <td>Multimedia_musica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AppleiTunes</th>\n",
       "      <td>Multimedia_musica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BitTorrent</th>\n",
       "      <td>Multimedia_videos</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mega</th>\n",
       "      <td>Multimedia_videos</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NetFlix</th>\n",
       "      <td>Multimedia_videos</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YouTube</th>\n",
       "      <td>Multimedia_videos</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tor</th>\n",
       "      <td>Navegacion</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Google</th>\n",
       "      <td>Navegacion</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DNS</th>\n",
       "      <td>Navegacion</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SSL</th>\n",
       "      <td>Navegacion</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HTTP</th>\n",
       "      <td>Navegacion</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yahoo</th>\n",
       "      <td>Navegacion</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SSL_No_Cert</th>\n",
       "      <td>Navegacion</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MSN</th>\n",
       "      <td>Navegacion</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>api_Ceibal</th>\n",
       "      <td>Navegacion_Ceibal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>google_Ceibal</th>\n",
       "      <td>Navegacion_Ceibal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Schoology-Ceibal</th>\n",
       "      <td>Navegacion_Ceibal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>miespacio_Ceibal</th>\n",
       "      <td>Navegacion_Ceibal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ceibal_Ceibal</th>\n",
       "      <td>Navegacion_Ceibal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Facebook</th>\n",
       "      <td>Red_social</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Instagram</th>\n",
       "      <td>Red_social</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Snapchat</th>\n",
       "      <td>Red_social</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Twitter</th>\n",
       "      <td>Red_social</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Twitch</th>\n",
       "      <td>Red_social</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AppleiCloud</th>\n",
       "      <td>almacenamiento</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dropbox</th>\n",
       "      <td>almacenamiento</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MS_OneDrive</th>\n",
       "      <td>almacenamiento</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GMail</th>\n",
       "      <td>correo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hotmail</th>\n",
       "      <td>correo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wikipedia</th>\n",
       "      <td>herramienta_educativa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TeamViewer</th>\n",
       "      <td>herramienta_educativa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Office365</th>\n",
       "      <td>herramienta_educativa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ibirapita_Ceibal</th>\n",
       "      <td>ibirapita_Ceibal</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 Categorizacion\n",
       "app                                            \n",
       "Viber                              Comunicacion\n",
       "WhatsApp                           Comunicacion\n",
       "Telegram                           Comunicacion\n",
       "Skype                              Comunicacion\n",
       "QQ                                 Comunicacion\n",
       "aulas_Ceibal                   Educacion_Ceibal\n",
       "bibliotecadigital_Ceibal       Educacion_Ceibal\n",
       "Pam_Ceibal                     Educacion_Ceibal\n",
       "ingreso_Ceibal                 Educacion_Ceibal\n",
       "GoogleMaps                           GoogleMaps\n",
       "eBay                                Marketplace\n",
       "Amazon                              Marketplace\n",
       "Spotify                       Multimedia_musica\n",
       "Deezer                        Multimedia_musica\n",
       "AppleiTunes                   Multimedia_musica\n",
       "BitTorrent                    Multimedia_videos\n",
       "Mega                          Multimedia_videos\n",
       "NetFlix                       Multimedia_videos\n",
       "YouTube                       Multimedia_videos\n",
       "Tor                                  Navegacion\n",
       "Google                               Navegacion\n",
       "DNS                                  Navegacion\n",
       "SSL                                  Navegacion\n",
       "HTTP                                 Navegacion\n",
       "Yahoo                                Navegacion\n",
       "SSL_No_Cert                          Navegacion\n",
       "MSN                                  Navegacion\n",
       "api_Ceibal                    Navegacion_Ceibal\n",
       "google_Ceibal                 Navegacion_Ceibal\n",
       "Schoology-Ceibal              Navegacion_Ceibal\n",
       "miespacio_Ceibal              Navegacion_Ceibal\n",
       "ceibal_Ceibal                 Navegacion_Ceibal\n",
       "Facebook                             Red_social\n",
       "Instagram                            Red_social\n",
       "Snapchat                             Red_social\n",
       "Twitter                              Red_social\n",
       "Twitch                               Red_social\n",
       "AppleiCloud                      almacenamiento\n",
       "Dropbox                          almacenamiento\n",
       "MS_OneDrive                      almacenamiento\n",
       "GMail                                    correo\n",
       "Hotmail                                  correo\n",
       "Wikipedia                 herramienta_educativa\n",
       "TeamViewer                herramienta_educativa\n",
       "Office365                 herramienta_educativa\n",
       "ibirapita_Ceibal               ibirapita_Ceibal"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "Etiquetas de aplicaciones:\n",
      "['Navegacion' 'Red_social' 'Comunicacion' 'Navegacion_Ceibal'\n",
      " 'Multimedia_videos' 'Marketplace' 'correo' 'almacenamiento'\n",
      " 'Multimedia_musica' 'herramienta_educativa' 'Educacion_Ceibal'\n",
      " 'GoogleMaps' 'ibirapita_Ceibal']\n"
     ]
    }
   ],
   "source": [
    "importantes = apps_importantes.head(78)\n",
    "importantes['Categorizacion'] = categorizacion\n",
    "importantes = importantes[importantes.Categorizacion.isin(drop_list)==False][['app', 'Categorizacion']].set_index('app')\n",
    "\n",
    "mapper_caracteristicas = importantes.to_dict()\n",
    "print('Nos quedamos con', len(importantes), 'aps, de las cuales', importantes.Categorizacion.nunique(), 'son etiquetas unicas')\n",
    "display(importantes.sort_values('Categorizacion', inplace=False))\n",
    "print()\n",
    "print('Etiquetas de aplicaciones:')\n",
    "print(importantes.Categorizacion.unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "datos['etiquetas'] = datos.app.map(mapper_caracteristicas['Categorizacion'])\n",
    "datos.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### verifico cantidad de usuarios en las etiquetas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "etiquetas\n",
       "ibirapita_Ceibal    242\n",
       "Name: mac, dtype: int64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "usuarios_por_app = datos.groupby('etiquetas')['mac'].nunique()\n",
    "display(usuarios_por_app[usuarios_por_app < 300])\n",
    "datos = datos[datos.etiquetas != 'ibirapita_Ceibal']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>mac</th>\n",
       "      <th>app</th>\n",
       "      <th>ventanas</th>\n",
       "      <th>fecha</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>00:00:06:AF:43:11</td>\n",
       "      <td>Navegacion</td>\n",
       "      <td>4</td>\n",
       "      <td>2018-06-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>00:00:06:AF:43:11</td>\n",
       "      <td>Navegacion</td>\n",
       "      <td>2</td>\n",
       "      <td>2018-06-20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>00:00:06:AF:43:11</td>\n",
       "      <td>Navegacion</td>\n",
       "      <td>2</td>\n",
       "      <td>2018-06-21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>00:00:06:AF:43:11</td>\n",
       "      <td>Navegacion</td>\n",
       "      <td>4</td>\n",
       "      <td>2018-06-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>00:00:06:AF:43:11</td>\n",
       "      <td>Red_social</td>\n",
       "      <td>5</td>\n",
       "      <td>2018-06-08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 mac         app  ventanas       fecha\n",
       "0  00:00:06:AF:43:11  Navegacion         4  2018-06-08\n",
       "1  00:00:06:AF:43:11  Navegacion         2  2018-06-20\n",
       "2  00:00:06:AF:43:11  Navegacion         2  2018-06-21\n",
       "3  00:00:06:AF:43:11  Navegacion         4  2018-06-22\n",
       "4  00:00:06:AF:43:11  Red_social         5  2018-06-08"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "datos.to_csv('junio_filtrado_apps_importantes.csv')\n",
    "datos['app'] = datos['etiquetas']\n",
    "datos = datos[['mac', 'app', 'ventanas', 'fecha']]\n",
    "datos.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Extraccion de caracteristicas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### i) Cantidad total de observaciones por aplicacion.\n",
    "\n",
    "Para esto agrupamos a nivel dispositivo y aplicación, y contamos la cantidad de ventanas donde se observó cada aplicación para cada individuo. Este subgrupo implica que habrá una característica por aplicación (por ejemplo, cantidad de observaciones del individuo en Facebook).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mac</th>\n",
       "      <th>app</th>\n",
       "      <th>ventanas</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>00:00:00:3F:2E:34</td>\n",
       "      <td>Multimedia_videos</td>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>00:00:00:3F:2E:34</td>\n",
       "      <td>Navegacion</td>\n",
       "      <td>563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>00:00:00:46:95:B4</td>\n",
       "      <td>Navegacion</td>\n",
       "      <td>878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>00:00:00:5C:64:DE</td>\n",
       "      <td>Multimedia_videos</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>00:00:00:5C:64:DE</td>\n",
       "      <td>Navegacion</td>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 mac                app  ventanas\n",
       "0  00:00:00:3F:2E:34  Multimedia_videos        81\n",
       "1  00:00:00:3F:2E:34         Navegacion       563\n",
       "2  00:00:00:46:95:B4         Navegacion       878\n",
       "3  00:00:00:5C:64:DE  Multimedia_videos         4\n",
       "4  00:00:00:5C:64:DE         Navegacion        69"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "uso_total_apps = datos[['mac', 'app', 'ventanas']].groupby(['mac', 'app'])[['ventanas']].sum().reset_index()\n",
    "uso_total_apps.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### ii) Media diaria de observaciones por aplicacion.\n",
    "Para esto agrupamos a nivel dispositivo y aplicación, y contamos la cantidad de ventanas donde se observó cada aplicación para cada individuo. Este subgrupo implica que habrá una característica por aplicación (por ejemplo, cantidad de observaciones del individuo en Facebook)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mac</th>\n",
       "      <th>app</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>00:00:00:3F:2E:34</td>\n",
       "      <td>Multimedia_videos</td>\n",
       "      <td>5.0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>00:00:00:3F:2E:34</td>\n",
       "      <td>Navegacion</td>\n",
       "      <td>5.0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>00:00:00:46:95:B4</td>\n",
       "      <td>Navegacion</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>00:00:00:5C:64:DE</td>\n",
       "      <td>Multimedia_videos</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>00:00:00:5C:64:DE</td>\n",
       "      <td>Navegacion</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 mac                app  ventanas\n",
       "0  00:00:00:3F:2E:34  Multimedia_videos       5.0\n",
       "1  00:00:00:3F:2E:34         Navegacion       5.0\n",
       "2  00:00:00:46:95:B4         Navegacion       6.0\n",
       "3  00:00:00:5C:64:DE  Multimedia_videos       1.0\n",
       "4  00:00:00:5C:64:DE         Navegacion       1.0"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mediana_uso_diario_apps = datos[['mac', 'app', 'ventanas']].groupby(['mac', 'app'])[['ventanas']].median().reset_index()\n",
    "mediana_uso_diario_apps.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### iii) Cantidad de dias por aplicacion. \n",
    "Estás características son similares al primer grupo con la diferencia de que se toman en cuenta los días."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
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       "      <td>10</td>\n",
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       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 mac                app  fecha\n",
       "0  00:00:00:3F:2E:34  Multimedia_videos     16\n",
       "1  00:00:00:3F:2E:34         Navegacion     20\n",
       "2  00:00:00:46:95:B4         Navegacion     27\n",
       "3  00:00:00:5C:64:DE  Multimedia_videos      3\n",
       "4  00:00:00:5C:64:DE         Navegacion     10"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "dias_uso_apps = datos[['mac', 'app', 'fecha']].groupby(['mac', 'app'])[['fecha']].nunique().reset_index()\n",
    "dias_uso_apps.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### iv) Porcentaje de dias donde se observo el individuo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
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      "text/plain": [
       "                 mac     fecha\n",
       "0  00:00:00:3F:2E:34  0.666667\n",
       "1  00:00:00:46:95:B4  0.900000\n",
       "2  00:00:00:5C:64:DE  0.333333\n",
       "3  00:00:00:75:5E:53  0.233333\n",
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   "source": [
    "dias_uso_dispositivo = datos[['mac', 'fecha']].groupby(['mac'])[['fecha']].nunique().reset_index()\n",
    "dias_uso_dispositivo['fecha'] = dias_uso_dispositivo['fecha'] / (np.max(dias_uso_dispositivo['fecha']))\n",
    "dias_uso_dispositivo.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Guardo las caracteristicas en datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
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       "app                Comunicacion  Educacion_Ceibal  GoogleMaps  Marketplace  \\\n",
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       "mac                                                                   \n",
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       "mac                                                                        \n",
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       "mac                                       \n",
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       "app                Comunicacion  Educacion_Ceibal  GoogleMaps  Marketplace  \\\n",
       "mac                                                                          \n",
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       "mac                                                                   \n",
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       "app                Navegacion_Ceibal  Red_social  almacenamiento  correo  \\\n",
       "mac                                                                        \n",
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       "mac                                       \n",
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       "      <td>0.0</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "app                Comunicacion  Educacion_Ceibal  GoogleMaps  Marketplace  \\\n",
       "mac                                                                          \n",
       "00:00:00:3F:2E:34           0.0               0.0         0.0          0.0   \n",
       "00:00:00:46:95:B4           0.0               0.0         0.0          0.0   \n",
       "\n",
       "app                Multimedia_musica  Multimedia_videos  Navegacion  \\\n",
       "mac                                                                   \n",
       "00:00:00:3F:2E:34                0.0               16.0        20.0   \n",
       "00:00:00:46:95:B4                0.0                0.0        27.0   \n",
       "\n",
       "app                Navegacion_Ceibal  Red_social  almacenamiento  correo  \\\n",
       "mac                                                                        \n",
       "00:00:00:3F:2E:34                0.0         0.0             0.0     0.0   \n",
       "00:00:00:46:95:B4                0.0         0.0             0.0     0.0   \n",
       "\n",
       "app                herramienta_educativa  \n",
       "mac                                       \n",
       "00:00:00:3F:2E:34                    0.0  \n",
       "00:00:00:46:95:B4                    0.0  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>app</th>\n",
       "      <th>Comunicacion</th>\n",
       "      <th>Educacion_Ceibal</th>\n",
       "      <th>GoogleMaps</th>\n",
       "      <th>Marketplace</th>\n",
       "      <th>Multimedia_musica</th>\n",
       "      <th>Multimedia_videos</th>\n",
       "      <th>Navegacion</th>\n",
       "      <th>Navegacion_Ceibal</th>\n",
       "      <th>Red_social</th>\n",
       "      <th>almacenamiento</th>\n",
       "      <th>correo</th>\n",
       "      <th>herramienta_educativa</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mac</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "      <th></th>\n",
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       "    </tr>\n",
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       "      <td>81.0</td>\n",
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      ],
      "text/plain": [
       "app                Comunicacion  Educacion_Ceibal  GoogleMaps  Marketplace  \\\n",
       "mac                                                                          \n",
       "00:00:00:3F:2E:34           0.0               0.0         0.0          0.0   \n",
       "00:00:00:46:95:B4           0.0               0.0         0.0          0.0   \n",
       "\n",
       "app                Multimedia_musica  Multimedia_videos  Navegacion  \\\n",
       "mac                                                                   \n",
       "00:00:00:3F:2E:34                0.0               81.0       563.0   \n",
       "00:00:00:46:95:B4                0.0                0.0       878.0   \n",
       "\n",
       "app                Navegacion_Ceibal  Red_social  almacenamiento  correo  \\\n",
       "mac                                                                        \n",
       "00:00:00:3F:2E:34                0.0         0.0             0.0     0.0   \n",
       "00:00:00:46:95:B4                0.0         0.0             0.0     0.0   \n",
       "\n",
       "app                herramienta_educativa  \n",
       "mac                                       \n",
       "00:00:00:3F:2E:34                    0.0  \n",
       "00:00:00:46:95:B4                    0.0  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# dias_uso_dispositivo\n",
    "dias_uso_dispositivo.to_csv('dias_uso_dispositivo.csv', index=False)\n",
    "dias_uso_dispositivo\n",
    "\n",
    "# uso_total_apps\n",
    "uso_total_apps = uso_total_apps.pivot(index='mac', columns='app', values='ventanas').fillna(value=0)\n",
    "uso_total_apps.to_csv('uso_total_apps.csv', index=False)\n",
    "display(uso_total_apps.head(2))\n",
    "\n",
    "# mediana\n",
    "mediana_uso_diario_apps = mediana_uso_diario_apps.pivot(index='mac', columns='app', values='ventanas').fillna(value=0)\n",
    "mediana_uso_diario_apps.to_csv('mediana_uso_diario_apps.csv', index=False)\n",
    "display(mediana_uso_diario_apps.head(2))\n",
    "\n",
    "# mediana + dias de uso de dispositivo\n",
    "mediana_uso_y_dias = pd.merge(mediana_uso_diario_apps, dias_uso_dispositivo, left_on='mac', right_on='mac')\n",
    "mediana_uso_y_dias.to_csv('mediana_uso_y_dias.csv', index=False)\n",
    "display(mediana_uso_y_dias.head(2))\n",
    "\n",
    "# dias_uso_apps\n",
    "dias_uso_apps = dias_uso_apps.pivot(index='mac', columns='app', values='fecha').fillna(value=0)\n",
    "dias_uso_apps.to_csv('dias_uso_apps.csv', index=False)\n",
    "display(dias_uso_apps.head(2))\n",
    "\n",
    "# uso_total_y_dias   \n",
    "uso_total_y_dias = pd.merge(uso_total_apps, dias_uso_apps, left_index=True, right_index=True, suffixes=('_total', '_dias'))\n",
    "uso_total_y_dias.to_csv('uso_total_y_dias.csv', index=False)\n",
    "display(uso_total_apps.head(2))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Analizo la estructura de datos con PCA para ver cual dataset es mas conveniente utilizar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "def ver_PCA(dataset):\n",
    "    \n",
    "    pca = PCA(n_components=len(dataset.columns))\n",
    "    datos_transformados = pca.fit_transform(dataset.reset_index(inplace=False).drop('mac',axis=1))\n",
    "    print('varianza explicada', pca.explained_variance_ratio_)\n",
    "\n",
    "    pca = PCA(n_components=1)\n",
    "    datos_transformados = pca.fit_transform(dataset.reset_index(inplace=False).drop('mac',axis=1))\n",
    "    sns.kdeplot(datos_transformados.reshape(-1))\n",
    "    plt.title('PCA 1 componente')\n",
    "    plt.show()\n",
    "    \n",
    "    pca = PCA(n_components=2)\n",
    "    datos_transformados = pca.fit_transform(dataset.reset_index(inplace=False).drop('mac',axis=1))\n",
    "    plt.scatter(datos_transformados[:,0], datos_transformados[:,1])\n",
    "    plt.title('PCA 2 componentes')\n",
    "    plt.show()\n",
    "\n",
    "    pca = PCA(n_components=3)\n",
    "    datos_transformados = pca.fit_transform(dataset.reset_index(inplace=False).drop('mac',axis=1))\n",
    "    fig = plt.figure()\n",
    "    ax = fig.add_subplot(111, projection='3d')\n",
    "    ax.scatter(datos_transformados[:,0], datos_transformados[:,1], datos_transformados[:,2])\n",
    "    plt.title('PCA 3 componentes')\n",
    "    plt.show()\n",
    "    return"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "varianza explicada [0.57928677 0.17546634 0.06414555 0.04663556 0.03879236 0.03532156\n",
      " 0.02320773 0.01900829 0.01053702 0.00407785 0.0022076  0.00131335]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.5/dist-packages/scipy/stats/stats.py:1706: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "image/png": 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1wDbgNGC+mX0daABSZtbh7tcfdsv7IT0NQ/ehX1Fhmn9HRMpePqH/ODDdzKaQDvcFwIdytlkKLAQeAeYD93j61NZzMhuY2dXA3lIFPmRq+t2Xd0BTMYhI+es19N09YWaLgOVABLjF3VeZ2TXACndfCtwMLDazFmA76S+GQafrEGfkgkJfRMpfPj193H0ZsCxn2VVZtzuAi3p5jqv70b6CiicU+iISbqE6I7erl/LOCE2vLCJlLlShn0ippy8i4Raa0Hf3oKffe+hremURKVehCf2uZDrIexu9k0g5+zW9soiUqRCFfgrgkD39sSOqAWjd1VGUNomIFFtoQj9xoKff8y5PGlUDwCvb9xWlTSIixRaa0I9nevo9zLIJMLkxCP1t+4vSJhGRYgtN6B8o7/Qwnz5AY22MmliE9dsV+iJSnsIX+oco75gZR46qYYNCX0TKVIhCP6jpH6K8A3DkqBrWq7wjImUqRKGf7unHDjFkE9J1/Ve279dYfREpS6EL/WhF7z39zkSK1/Z0FqNZIiJFFbrQ76288/qwTZV4RKT8hCj0ez8jF2ByYy2A6voiUpZCFPqZmv6hd3lCwzAqTD19ESlPoQv9nq6RmxGLVjCufhivbNNZuSJSfkIT+vFEfuUdSB/MVU9fRMpRaEI/kcqvvAOvD9sUESk3oQn9fM7IzZg0qoate+Ps60wMdLNERIoqPKEflHeieZR3Dky8pt6+iJSZ0IR+PM/RO5Cu6YNCX0TKT2hCP9GH8s7kUZmx+hrBIyLlJTShnzk5K5/yTn1NJWNHVPPcq7sHulkiIkUVmtCP96GnDzBrwgieVeiLSJnJKwHNbI6ZrTGzFjO7spv1VWZ2Z7D+MTNrDpafamZPBX9Pm9n7Ctv8/PVl9A7AzPH1vNS2l/1xjeARkfLRawKaWQS4AZgLzAAuMbMZOZtdBuxw92nAdcC1wfJngdnufiIwB/iBmUUL1fi+SCSdSIUROcSVs7IdP6Eed1jdqt6+iJSPfLq9pwIt7r7W3ePAHcC8nG3mAbcFt5cA55mZuft+d890lauBkk1S35VMEc0z8AFmTagH4NlNCn0RKR/5hP4EYEPW/Y3Bsm63CUJ+F9AIYGanmdkq4BngiqwvgQPM7HIzW2FmK9ra2vq+F3mIJ1N5DdfMOGJEFaPrYjy7adeAtEdEpBQG/ECuuz/m7jOBNwFfMLPqbra5yd1nu/vspqamAWlHIum9zqWfzcyYOb5eB3NFpKzkk4KbgElZ9ycGy7rdJqjZ1wPbsjdw99XAXmBWfxt7OLqSqbwmW8s2a8IIXtyyh46u5AC1SkSkuPIJ/ceB6WY2xcxiwAJgac42S4GFwe35wD3u7sFjogBmNhk4FlhXkJb3UTyZ6vVSiblmja8nkXLWbN4zQK0SESmuXlMwqMEvApYDq4G73H2VmV1jZu8JNrsZaDSzFuDzQGZY59nA02b2FPA/wGfcfWuhdyIfXUkn1ofyDmQdzH1VdX0RKQ95DZ9092XAspxlV2Xd7gAu6uZxi4HFh9nGgkj0o7wzceQw6odVagSPiJSN0JyRm67p9213zSx9Zq5G8IhImQhN6MeT3uulErtzwsQGVrfu1sFcESkLoQn9rkSKWB/LOwAnHzmSRMp5Rr19ESkDoQn9RKrv5R2Ak49sAGDl+h2FbpKISNGFJvTjSe9X6DfWVdHcWMMTCn0RKQOhCf2uRN9H72ScPHkkT7yyA/eSTR0kIlIQ4Qn9fozeyTj5yJFs3Rtnw/b2ArdKRKS4QhP6iVT/yjsAp0weCcDKV7YXskkiIkUXmtCPJ/rf0z/6iOHUVUV5Yv3OArdKRKS4QhP6/ZlwLSNSYZw4qUEjeERkyAtZ6Pd/d08+soHnN+9mX6cunygiQ1doQj/RzyGbGSdPHknK4clXVOIRkaErNKEfT6aojPavvAMwu3kU0Qrj4ZdKMkmoiEhBhCb0u5IpKvs4n362uqooJx3ZwEMtCn0RGbpCEfrJlJNyiPbzQG7GWdNG89dNu9i1v6tALRMRKa5QhH5nIj1DZnVl5LCe56xpo3GHR9aqty8iQ1MoQr+jKwVAdR+vnJXrxEkN1MYiPKgSj4gMUaEI/fZgLvxhscPr6VdGKjjtqEYebtnW+8YiIoNQKEI/cwGUwy3vQLrEs3brPjbt1Dw8IjL0hCL02+OFC/2zp40G0CgeERmSQhH6mQO5wwoQ+kcfUcfouir+/ELbYT+XiEixhSL02+PBgdwChL6Z8bZjm7h/TRvxROqwn09EpJhCEfqZmn4hevoA588cy57OhM7OFZEhJxSh337gQG5hdvesaaOpjUVYvmpLQZ5PRKRY8kpBM5tjZmvMrMXMruxmfZWZ3Rmsf8zMmoPl7zCzlWb2TPDv2wrb/PwUcvRO5nnOPWYMf3xuC6mULqEoIkNHr6FvZhHgBmAuMAO4xMxm5Gx2GbDD3acB1wHXBsu3Au929+OBhcDiQjW8Lwod+gDvnHkEW/d28uQGzbEvIkNHPj39U4EWd1/r7nHgDmBezjbzgNuC20uA88zM3P1Jd381WL4KGGZmVYVoeF8U6uSsbG89dgyVEVOJR0SGlHxCfwKwIev+xmBZt9u4ewLYBTTmbPMB4Al37+xfU/uvUNMwZBtRXckZU0ezfNVm3FXiEZGhoSgHcs1sJumSz6d6WH+5ma0wsxVtbYUf/97elaQyYkQP4yIq3Zk7ayzrt+3n2U27C/q8IiIDJZ8U3ARMyro/MVjW7TZmFgXqgW3B/YnA/wAfdfeXunsBd7/J3We7++ympqa+7UEeOrqSVEcLV9rJuGDWOGKRCn755MaCP7eIyEDIJ/QfB6ab2RQziwELgKU52ywlfaAWYD5wj7u7mTUAvwWudPeHCtXovuroSlJdwHp+Rn1NJW87dgy/efpVEkmdqCUig1+voR/U6BcBy4HVwF3uvsrMrjGz9wSb3Qw0mlkL8HkgM6xzETANuMrMngr+xhR8L3rR0ZUq2Bj9XO87eQJb98Z54EWdqCUig180n43cfRmwLGfZVVm3O4CLunncV4GvHmYbD1t7PFmws3FzvfWYMTTUVPLLJzfx1mOL/n0mItInoTgjtyORLOgY/WyxaAXvPmE8f1i1mT0duoyiiAxuoQj99vjAhT6kSzydiRS//WvrgL2GiEghhCL0OxKpAQ39kyY1cOzY4dz68DqN2ReRQS0coR9PMmyADuRCerrly86ewvOb9+j6uSIyqIUj9Aewpp/xnhPH0zS8ih898PKAvo6IyOEIRegP5OidjKpohIVnTOb+F9p4YcueAX0tEZH+CkXod3QNfE8f4EOnTaa6soIfPbB2wF9LRKQ/QhL6A3sgN2NUbYyLZ0/iF09souU19fZFZPAp+9BPppx4cuDOyM31ufOmU1MZ4Wu/XV2U1xMR6YuyD/1CXx+3N411VXzuvOncu6aN+9a8VpTXFBHJV2hCvxjlnYyFZzbT3FjDV3+7WhOxicigUvah317knj6kp2b44oUzaHltLz/7yytFe10Rkd6UfehnrppVVaSafsbbjxvDWdMa+dYfX2Dn/nhRX1tEpCchCP3i9/QhfZbuly6cwe72Lr7zpxeL+toiIj0JTegXs6afcdy4ESw49UgWP7Keltf2Fv31RURylX3oH6jpD8CVs/Lx+XcczbDKCF/61TOkUpqMTURKq+xDP1PTL3Z5J2N0XRVfftcMHl27nR/qTF0RKbGyD/32A+Wd0u3qRbMnMmfmWL7xhzU8u2lXydohIlL2oV/Kmn6GmfEf7z+eUbUx/v6OJ9mtK2yJSIko9ItkZG2M6y4+kfXb9vOZ25+gSydtiUgJhCb0S1XTz3bm1NH8x/uP58GWrXzhl8/oKlsiUnTRUjdgoLXH0z3qUvf0My6aPYmNO9r5zp9eZGpTHZ8+d2qpmyQiIVL+Pf1EklikgkiFlbopB/zD26dz4Qnj+M/lz/PIS9tK3RwRCZGyD/32eLLoUzD0xsy49gMn0Dy6lr/77yd5bXdHqZskIiExuNJwAHQmBv5Sif1RVxXlex8+hb2dXVy+eCXb92l+HhEZeHmFvpnNMbM1ZtZiZld2s77KzO4M1j9mZs3B8kYzu9fM9prZ9YVten7a48W5VGJ/HDN2ON9ZcBKrW3cz74YHeVHX1hWRAdZr6JtZBLgBmAvMAC4xsxk5m10G7HD3acB1wLXB8g7gy8A/F6zFfdTRlRqUPf2M82eO5Y7LT6c9nuL9Nz7M75/dXOomiUgZy6enfyrQ4u5r3T0O3AHMy9lmHnBbcHsJcJ6Zmbvvc/cHSYd/SbR3JUt6Nm4+TjpyJL9edBZTmmq54vaVXL10FZ2JZKmbJSJlKJ80nABsyLq/MVjW7TbungB2AY35NsLMLjezFWa2oq2tLd+H5aWja/CWd7JNaBjGkivO5G/PmsKtD69j/vce4ZVt+0vdLBEpM4OiC+zuN7n7bHef3dTUVNDnHiqhD+krbl317hncdOkprN+2jwu/+wC/e6a11M0SkTKST+hvAiZl3Z8YLOt2GzOLAvXAoBiAPthr+t1558yx/PZz5zB1TB2f/ukTfPvuF3T2rogURD6h/zgw3cymmFkMWAAszdlmKbAwuD0fuMcHSUoNhZp+dyaNquGuT53B/FMm8u27X+Qf73xKdX4ROWy9TsPg7gkzWwQsByLALe6+ysyuAVa4+1LgZmCxmbUA20l/MQBgZuuAEUDMzN4LvNPdnyv8rnSvoytZsguoHK5YtIL/nH8CU0bX8p/L17BpZzs/uHQ2o2pjpW6aiAxRec294+7LgGU5y67Kut0BXNTDY5sPo32Hrb0rSVV0aIY+pM/e/exbpzG5sYbP3/U0773hIW752JuYNqau1E0TkSFo6NU9+qizKzVke/rZ3nXCeO64/HT2dSaY//2HeXrDzlI3SUSGoLIO/WTKiSdTVA/hnn62k48cyS8/cybDq6N86IeParI2Eemzsg79A3Ppx8pnNyc31rLkijMZ3zCMhT/+C3c/t6XUTRKRIaR80rAb7YPkqlmFdsSIau761BkcN3Y4n7p9Jb96MncErYhI98o69AfLpRIHwsjaGD/95Om8qXkk/3jXU9z60MulbpKIDAEK/SGsrirKrR8/lbcfdwRX/+Y5rl66imRqUJweISKDVJmHfvpSiUPtjNy+qK6M8P2PnMInzk7P2fPJn6xgb2ei1M0SkUGqrEP/9Zp+We8mkQrjS++awVffO4v7X2jjou8/Quuu9lI3S0QGobJOwwOjd8q4p5/tI6dP5scfexMbt+9n3vUP8czGXaVukogMMmUd+u3x8q7pd+fNRzex5NNnUhmp4IM/eIQ/rNJFWUTkdeUd+mV+ILcnx4wdzq8+exbHBEM6v3ffS6R0gFdEKPPQ7wwO5JZ7Tb87TcOruOPy07nw+HFc+/vnWfjjv7Bld8kuYCYig0RZp+HO9jgAw6sqS9yS0qiujPBfl5zEv7/veB5ft53zv/1nfvjnteyPa3SPSFiVdeiv2byXMcOrqK8JZ+hDepbOD512JP/7d+cwa3w9X1u2mjd//V5ufehlEslUqZsnIkVW1qG/unU3x44bUepmDArTxtRx+ydOY8kVZzB9zHCu/s1zXPDdB3ioZWupmyYiRVS2od+VTNHy2l6OGzu81E0ZVGY3j+JnnzyNH1x6Cu1dST78o8e4YvFKNmzXRdhFwiCvi6gMRS9v3Uc8meLYcQr9XGbG+TPH8pajm/jRA2u54d6XuGfNa1zx5qO44typ1MTK9mMhEnpl29Nf3bobgONU3ulRdWWERW+bzj3//BbmzhrLd+9p4bxv3s8vVm5UvV+kTJVt6D+/eQ+VEeOo0bqsYG/G1Q/jOwtO4udXnMGo2hj/9POnOfcb97H4kXUHzmoWkfJQvqHfupupTXXEomW7iwX3puZR/GbR2fzwo7NpGl7Fl3+9irOvvZcb72thd0dXqZsnIgVQtsXb1a17OGNqY6mbMeRUVBjvmHEEbz9uDI+u3c6N97Xw9d+v4fp7Wnj/yRP4yOmTOXasSmYiQ1VZhv6OfXE27+7gWI3c6Tcz44ypjZwxtZFnN+3i1ofXcdeKjdz+6CtMbapl7qxxvOWYJv5mYoN+TYkMIWUZ+s9v3gOgMfoFMmtCPd+46G/4wtzDqfO5AAAGRUlEQVRjWfZMK8ue2cyN97Vw/b0tDKuMMLt5ZPoL4qhGZk2opzKiLwGRwapMQz8YuaOefkE11lVx6RnNXHpGMzv3x3l07XYeXbuNh1/aytd/vwZIz3N04qQGZk8exSnNIzlpUgMNNbESt1xEMvIKfTObA3wHiAA/cvf/l7O+CvgJcAqwDbjY3dcF674AXAYkgc+5+/KCtb4Hz7fuYVRtjKbhVQP9UqHVUBNjzqyxzJk1FoC2PZ385eXtrFi/nRXrdvC9+18ieW96Zs/G2hhTRtdyVFMtU0bXMb6hmuHVUYZXVzKiupLh1VFG1cZCNxuqSCn0GvpmFgFuAN4BbAQeN7Ol7v5c1maXATvcfZqZLQCuBS42sxnAAmAmMB6428yOdvcBGQe4a38Xtz+2nt8928oJExsws4F4GelG0/AqLjxhHBeeMA6AfZ0Jnt6wk2df3cXLW/fxUts+7nm+ja17N/b4HMOrooweXkVTXRWNdTFqq6IMq4wwLBahujKSvl1ZQXVlhGikAgOiEaMmFqUmlt6uJhY5qLyU+QRkPguv38+st4Puk7s+z8cdeHgv67M/kz0954F/enhsn/ehl7ZYd4/R/52ylU9P/1Sgxd3XApjZHcA8IDv05wFXB7eXANdb+lMzD7jD3TuBl82sJXi+RwrT/Nc9vm47C2/5C/vjSc6ZPpovv2tGoV9C+qC2KsqZ00Zz5rTRBy3f3dHF1j2d7O5IsKeji93tCXZ3dLF9X5y2PZ207e1k655OXtiyh/Z4kvau9F/mesdSGn39AuIN2w90Cw/NGBpfYnOPH8u3PnjigL5GPqE/AdiQdX8jcFpP27h7wsx2AY3B8kdzHjsh9wXM7HLg8uDuXjNbk1fre7AeuP1wnqDvRgOauSxN78XB9H68Tu/Fwd7wfjwPXHdxv59vcj4bDYoDue5+E3BTqdvRX2a2wt1nl7odg4Hei4Pp/Xid3ouDler9yGds3SZgUtb9icGybrcxsyhQT/qAbj6PFRGRIskn9B8HppvZFDOLkT4wuzRnm6XAwuD2fOAed/dg+QIzqzKzKcB04C+FabqIiPRVr+WdoEa/CFhOesjmLe6+ysyuAVa4+1LgZmBxcKB2O+kvBoLt7iJ90DcBfHagRu6U2JAtTQ0AvRcH0/vxOr0XByvJ+2HpDrmIiISBzpcXEQkRhb6ISIgo9A+Dmc0xszVm1mJmV5a6PaVgZuvM7Bkze8rMVgTLRpnZH83sxeDfkaVu50Aws1vM7DUzezZrWbf7bmnfDT4rfzWzk0vX8oHRw/txtZltCj4fT5nZBVnrvhC8H2vM7PzStHpgmNkkM7vXzJ4zs1Vm9vfB8pJ/PhT6/ZQ1PcVcYAZwSTDtRBi91d1PzBpzfCXwJ3efDvwpuF+ObgXm5Czrad/nkh69Np30iYjfK1Ibi+lW3vh+AFwXfD5OdPdlADlTtMwBbgz+T5WLBPBP7j4DOB34bLDPJf98KPT778D0FO4eBzLTU0j6fbgtuH0b8N4StmXAuPufSY9Wy9bTvs8DfuJpjwINZjauOC0tjh7ej54cmKLF3V8GMlO0lAV3b3X3J4Lbe4DVpGcjKPnnQ6Hff91NT/GGKSZCwIE/mNnKYDoNgCPcvTW4vRk4ojRNK4me9j3Mn5dFQcnilqxSX2jeDzNrBk4CHmMQfD4U+nK4znb3k0n/PP2smb05e2Vwkl4oxwWHed+zfA+YCpwItALfLG1zisvM6oBfAP/g7ruz15Xq86HQ7z9NMQG4+6bg39eA/yH9E31L5qdp8O9rpWth0fW076H8vLj7FndPunsK+CGvl3DK/v0ws0rSgf9Td/9lsLjknw+Ffv/lMz1FWTOzWjMbnrkNvBN4loOn5VgI/Lo0LSyJnvZ9KfDRYJTG6cCurJ/5ZSunLv0+0p8PKPMpWoKp5W8GVrv7t7JWlf7z4e766+cfcAHwAvAS8MVSt6cE+38U8HTwtyrzHpCeVvtPwIvA3cCoUrd1gPb/v0mXLLpI12Av62nfSU8tf0PwWXkGmF3q9hfp/Vgc7O9fSQfbuKztvxi8H2uAuaVuf4Hfi7NJl27+CjwV/F0wGD4fmoZBRCREVN4REQkRhb6ISIgo9EVEQkShLyISIgp9EZEQUeiLiISIQl9EJET+PyM4poy3ZcGvAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ver_PCA(mediana_uso_diario_apps)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "varianza explicada [9.31128747e-01 3.99195907e-02 1.26918324e-02 6.96644366e-03\n",
      " 3.53514301e-03 3.04678870e-03 1.24017392e-03 9.19639224e-04\n",
      " 3.41730174e-04 1.10385671e-04 8.63803301e-05 1.31449680e-05]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.5/dist-packages/scipy/stats/stats.py:1706: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ver_PCA(uso_total_apps)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "varianza explicada [0.64520461 0.10069911 0.0735894  0.04370359 0.03342611 0.02543744\n",
      " 0.02491617 0.01892931 0.01588057 0.00920985 0.00519029 0.00381355]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.5/dist-packages/scipy/stats/stats.py:1706: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ver_PCA(dias_uso_apps)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "varianza explicada [9.30985737e-01 3.99151445e-02 1.26902428e-02 6.96649929e-03\n",
      " 3.54392298e-03 3.05235534e-03 1.24489318e-03 9.22656611e-04\n",
      " 3.42230170e-04 1.13136918e-04 8.71138850e-05 7.19375950e-05\n",
      " 1.42278263e-05 1.32872384e-05 6.87454345e-06 6.08115034e-06\n",
      " 5.62653033e-06 5.08183417e-06 4.54388088e-06 3.72928928e-06\n",
      " 2.11394921e-06 1.44762923e-06 8.61278666e-07 2.54874089e-07]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.5/dist-packages/scipy/stats/stats.py:1706: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ver_PCA(uso_total_y_dias)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "varianza explicada [9.99999593e-01 2.36515350e-07 7.08557901e-08 2.61161853e-08\n",
      " 1.90420228e-08 1.58400659e-08 1.44226026e-08 9.47103659e-09\n",
      " 7.75252073e-09 4.30254958e-09 1.66531132e-09 9.01441090e-10\n",
      " 5.36464909e-10 3.01308456e-11]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.5/dist-packages/scipy/stats/stats.py:1706: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ver_PCA(mediana_uso_y_dias)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.7.3 64-bit ('.env': virtualenv)",
   "language": "python",
   "name": "python37364bitenvvirtualenvf0653046e8094d769f4d88cd292bb6e8"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}