Analisis_clicks.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "clicks_dtypes = {'advertiser': np.int8, 'action_id': np.float16, 'source_id': np.int8, 'country_code': 'category',\n",
    "                 'latitude': np.float16, 'longitude': np.float16, 'carrier_id': np.float16, 'brand': np.float16,\n",
    "                 'touchX': np.float16, 'touchY': np.float16}\n",
    "\n",
    "clicks = pd.read_csv('clicks.csv', dtype = clicks_dtypes)\n",
    "\n",
    "clicks.drop('action_id', axis = 1, inplace = True) #todos NaN\n",
    "clicks.drop('wifi_connection', axis = 1, inplace = True) #todos False\n",
    "\n",
    "clicks[\"created\"] =  pd.to_datetime(clicks[\"created\"], errors = \"coerce\") #parseo de fechas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ¿Cuáles fueron los horarios y días de la semana en los cuales se registraron mayor cantidad de clicks?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>advertiser_id</th>\n",
       "      <th>source_id</th>\n",
       "      <th>created</th>\n",
       "      <th>country_code</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>carrier_id</th>\n",
       "      <th>trans_id</th>\n",
       "      <th>os_minor</th>\n",
       "      <th>agent_device</th>\n",
       "      <th>os_major</th>\n",
       "      <th>specs_brand</th>\n",
       "      <th>brand</th>\n",
       "      <th>timeToClick</th>\n",
       "      <th>touchX</th>\n",
       "      <th>touchY</th>\n",
       "      <th>ref_type</th>\n",
       "      <th>ref_hash</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>2019-03-06 22:42:12.755</td>\n",
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       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-03-08 10:24:30.641</td>\n",
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       "      <td>1.071289</td>\n",
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       "      <td>3.025219e+18</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.774085e+18</td>\n",
       "      <td>392184377613098015</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1891515180541284343</td>\n",
       "      <td>3086509764961796666</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "   advertiser_id  source_id                 created         country_code  \\\n",
       "0              2          4 2019-03-06 22:42:12.755  6333597102633388268   \n",
       "1              0          0 2019-03-08 10:24:30.641  6333597102633388268   \n",
       "\n",
       "   latitude  longitude  carrier_id                         trans_id  \\\n",
       "0  1.206055   1.070312         1.0  iGgClCM9exiHF4K31g94XmvHEBSLKIY   \n",
       "1  1.218750   1.071289         4.0  MMHTOJ6qKAOeIH_Eywh1KIcCaxtO9oM   \n",
       "\n",
       "       os_minor  agent_device      os_major          specs_brand  brand  \\\n",
       "0  6.768137e+18           NaN  3.072849e+18  2733035977666442898    NaN   \n",
       "1  3.025219e+18           NaN  1.774085e+18   392184377613098015    NaN   \n",
       "\n",
       "   timeToClick    touchX    touchY             ref_type             ref_hash  \n",
       "0        1.563  0.904785  0.078003  1891515180541284343  1904083516767779093  \n",
       "1          NaN       NaN       NaN  1891515180541284343  3086509764961796666  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clicks.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "clicks['hora'] = clicks['created'].dt.hour\n",
    "clicks['dia_de_la_semana'] = clicks['created'].dt.dayofweek\n",
    "clicks['cant_clicks'] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>advertiser_id</th>\n",
       "      <th>source_id</th>\n",
       "      <th>created</th>\n",
       "      <th>country_code</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>carrier_id</th>\n",
       "      <th>trans_id</th>\n",
       "      <th>os_minor</th>\n",
       "      <th>agent_device</th>\n",
       "      <th>...</th>\n",
       "      <th>specs_brand</th>\n",
       "      <th>brand</th>\n",
       "      <th>timeToClick</th>\n",
       "      <th>touchX</th>\n",
       "      <th>touchY</th>\n",
       "      <th>ref_type</th>\n",
       "      <th>ref_hash</th>\n",
       "      <th>hora</th>\n",
       "      <th>dia_de_la_semana</th>\n",
       "      <th>cant_clicks</th>\n",
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       "<p>1 rows × 21 columns</p>\n",
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      "text/plain": [
       "   advertiser_id  source_id                 created         country_code  \\\n",
       "0              2          4 2019-03-06 22:42:12.755  6333597102633388268   \n",
       "\n",
       "   latitude  longitude  carrier_id                         trans_id  \\\n",
       "0  1.206055   1.070312         1.0  iGgClCM9exiHF4K31g94XmvHEBSLKIY   \n",
       "\n",
       "       os_minor  agent_device     ...               specs_brand  brand  \\\n",
       "0  6.768137e+18           NaN     ...       2733035977666442898    NaN   \n",
       "\n",
       "   timeToClick    touchX    touchY             ref_type             ref_hash  \\\n",
       "0        1.563  0.904785  0.078003  1891515180541284343  1904083516767779093   \n",
       "\n",
       "   hora  dia_de_la_semana  cant_clicks  \n",
       "0    22                 2            1  \n",
       "\n",
       "[1 rows x 21 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clicks.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "agrupamiento_clicks = clicks.groupby(['hora', 'dia_de_la_semana']).agg({'cant_clicks': 'count'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "                       cant_clicks\n",
       "hora dia_de_la_semana             \n",
       "0    2                         256\n",
       "     4                         166\n",
       "     5                          16\n",
       "     6                           2\n",
       "1    0                         878\n",
       "     1                         411\n",
       "     2                         222\n",
       "     4                         988\n",
       "     5                        1154\n",
       "     6                         556"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agrupamiento_clicks.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "agrupamiento_clicks_desapilado = agrupamiento_clicks.unstack()['cant_clicks'] \n",
    "#completa con NaN si en un determinada hora y dia de la semana no hubo clicks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
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       "      <th>dia_de_la_semana</th>\n",
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       "      <th>hora</th>\n",
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       "      <td>988.0</td>\n",
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       "      <th>2</th>\n",
       "      <td>456.0</td>\n",
       "      <td>661.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>57.0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>233.0</td>\n",
       "      <td>258.0</td>\n",
       "      <td>169.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>9.0</td>\n",
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       "      <th>4</th>\n",
       "      <td>256.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>84.0</td>\n",
       "      <td>284.0</td>\n",
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       "      <td>66.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>154.0</td>\n",
       "      <td>236.0</td>\n",
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       "      <th>6</th>\n",
       "      <td>87.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>143.0</td>\n",
       "      <td>173.0</td>\n",
       "      <td>207.0</td>\n",
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       "      <th>7</th>\n",
       "      <td>57.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>147.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>151.0</td>\n",
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      ],
      "text/plain": [
       "dia_de_la_semana      0      1      2    3      4       5      6\n",
       "hora                                                            \n",
       "0                   NaN    NaN  256.0  NaN  166.0    16.0    2.0\n",
       "1                 878.0  411.0  222.0  NaN  988.0  1154.0  556.0\n",
       "2                 456.0  661.0  238.0  NaN   57.0    28.0  887.0\n",
       "3                 233.0  258.0  169.0  1.0   13.0    71.0    9.0\n",
       "4                 256.0  130.0   81.0  NaN   84.0   284.0  244.0\n",
       "5                 149.0   66.0   40.0  NaN  154.0   236.0  300.0\n",
       "6                  87.0   42.0   26.0  NaN  143.0   173.0  207.0\n",
       "7                  57.0   31.0    4.0  NaN  147.0   128.0  151.0"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agrupamiento_clicks_desapilado.head(8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "agrupamiento_clicks_desapilado = agrupamiento_clicks_desapilado.fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "agrupamiento_clicks_desapilado.columns = ['Lunes', 'Martes', 'Miercoles', 'Jueves','Viernes','Sabado', 'Domingo']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1360f8e4748>"
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     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1296x936 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(18,13))\n",
    "sns.heatmap(agrupamiento_clicks_desapilado.T, cmap='RdYlGn_r', linewidths=0.5)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}