media_events_installs_Nico.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.7/site-packages/IPython/core/interactiveshell.py:3049: DtypeWarning: Columns (12,18,19) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  interactivity=interactivity, compiler=compiler, result=result)\n"
     ]
    }
   ],
   "source": [
    "df_events = pd.read_csv(\"events.csv\", dtype={\"application_id\":\"int8\", \"event_id\":\"int8\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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       "      <th>date</th>\n",
       "      <th>event_id</th>\n",
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       "      <th>application_id</th>\n",
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       "      <th>user_agent</th>\n",
       "      <th>event_uuid</th>\n",
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       "      <th>device_os</th>\n",
       "      <th>wifi</th>\n",
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       "      <th>ip_address</th>\n",
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      "text/plain": [
       "                           date  event_id             ref_type  \\\n",
       "78094   2019-03-07 14:39:00.166       -94  1494519392962156891   \n",
       "76830   2019-03-07 14:38:21.082       -95  1494519392962156891   \n",
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       "714984  2019-03-10 15:13:13.086       -94  1494519392962156891   \n",
       "\n",
       "                   ref_hash  application_id  attributed   device_countrycode  \\\n",
       "78094   4897338357638817900             103       False  6333597102633388268   \n",
       "76830   4897338357638817900             103       False  6333597102633388268   \n",
       "713926    41614654414054753             103       False  6333597102633388268   \n",
       "714662  4872395157768010768             103       False  6333597102633388268   \n",
       "714984  4872395157768010768             103       False  6333597102633388268   \n",
       "\n",
       "        device_os_version  device_brand  device_model  ...  trans_id  \\\n",
       "78094        4.353750e+18           NaN  1.187661e+17  ...       NaN   \n",
       "76830        4.353750e+18           NaN  1.187661e+17  ...       NaN   \n",
       "713926       4.353750e+18           NaN  2.928262e+18  ...       NaN   \n",
       "714662       4.353750e+18           NaN  1.187661e+17  ...       NaN   \n",
       "714984       4.353750e+18           NaN  1.187661e+17  ...       NaN   \n",
       "\n",
       "        user_agent                            event_uuid       carrier  \\\n",
       "78094          NaN  0bf3717a-467b-4ee8-82c3-5e611deb6bbc  3.570805e+18   \n",
       "76830          NaN  92f559cf-cc70-4d0e-965c-4c3be5e09321  3.570805e+18   \n",
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       "\n",
       "                kind     device_os  wifi  connection_type      ip_address  \\\n",
       "78094   3.209078e+18  6.941825e+18   NaN        Cable/DSL   5287755497790   \n",
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       "714984  3.209078e+18  6.941825e+18   NaN        Cable/DSL  87345868419849   \n",
       "\n",
       "       device_language  \n",
       "78094     3.301378e+18  \n",
       "76830     3.301378e+18  \n",
       "713926    3.301378e+18  \n",
       "714662    3.301378e+18  \n",
       "714984    3.301378e+18  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_events.sort_values(by=[\"ip_address\"]).head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_events[\"cant_events\"] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "date                        0\n",
       "event_id                    0\n",
       "ref_type                    0\n",
       "ref_hash                    0\n",
       "application_id              0\n",
       "attributed                  0\n",
       "device_countrycode          0\n",
       "device_os_version     1472357\n",
       "device_brand          1329460\n",
       "device_model            87967\n",
       "device_city           1879725\n",
       "session_user_agent      11786\n",
       "trans_id              2494341\n",
       "user_agent            1102896\n",
       "event_uuid               5099\n",
       "carrier               1877989\n",
       "kind                     5099\n",
       "device_os             1836756\n",
       "wifi                  1115551\n",
       "connection_type       1881960\n",
       "ip_address                  0\n",
       "device_language         87819\n",
       "cant_events                 0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_events.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1891515180541284343, 1494519392962156891])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_events[\"ref_type\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_installs = pd.read_csv(\"installs.csv\")\n",
    "df_installs[\"cant_installs\"] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "                   created  application_id             ref_type  \\\n",
       "0  2019-03-13 01:43:33.445               0  1891515180541284343   \n",
       "1  2019-03-13 04:58:35.078               0  1891515180541284343   \n",
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       "4  2019-03-10 22:24:56.684               0  1891515180541284343   \n",
       "\n",
       "              ref_hash  click_hash  attributed  implicit   device_countrycode  \\\n",
       "0  8464844987297247076         NaN       False     False  6333597102633388268   \n",
       "1  3250564871270161533         NaN       False     False  6333597102633388268   \n",
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       "3  7953318831018100268         NaN       False     False  6333597102633388268   \n",
       "4  8355110941557237501         NaN       False      True  6333597102633388268   \n",
       "\n",
       "   device_brand  device_model                 session_user_agent user_agent  \\\n",
       "0  3.083059e+17  4.445252e+18                                NaN        NaN   \n",
       "1  3.083059e+17  4.445252e+18                                NaN        NaN   \n",
       "2  5.137992e+17  6.026543e+18  HasOffers Mobile AppTracking v1.0        NaN   \n",
       "3  5.137992e+17  6.026543e+18                                NaN        NaN   \n",
       "4  1.083369e+18  7.876612e+18  HasOffers Mobile AppTracking v1.0        NaN   \n",
       "\n",
       "                             event_uuid  kind wifi trans_id  \\\n",
       "0                                   NaN   NaN  NaN      NaN   \n",
       "1                                   NaN   NaN  NaN      NaN   \n",
       "2  0bfa9b4c-e07a-4522-b32d-138e3165ac98  Open  NaN      NaN   \n",
       "3                                   NaN   NaN  NaN      NaN   \n",
       "4  8f235a8c-41bf-4399-b33d-c41577c949b0  Open  NaN      NaN   \n",
       "\n",
       "            ip_address  device_language  cant_installs  \n",
       "0  5529284367937637301              NaN              1  \n",
       "1  6098022721363533304              NaN              1  \n",
       "2  4636407223847323867     3.301378e+18              1  \n",
       "3  4636407223847323867              NaN              1  \n",
       "4   685400811232710215     3.301378e+18              1  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_installs.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "installs_ip = df_installs[[\"ip_address\", \"cant_installs\"]].groupby(\"ip_address\").agg({\"cant_installs\":\"sum\"})\n",
    "events_ip = df_events[[\"ip_address\", \"cant_events\"]].groupby(\"ip_address\").agg({\"cant_events\":\"sum\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "                 ip_address  cant_events\n",
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       "28         1151615064267198           14\n",
       "29         1212888607375572            3\n",
       "...                     ...          ...\n",
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       "\n",
       "[285212 rows x 2 columns]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "installs_ip.reset_index()\n",
    "events_ip.reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
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      ],
      "text/plain": [
       "                     cant_events  cant_installs\n",
       "ip_address                                     \n",
       "5287755497790                2.0            0.0\n",
       "87345868419849               7.0            0.0\n",
       "167995586414012              1.0            0.0\n",
       "192556001908321              3.0            0.0\n",
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       "521945665648320             61.0            0.0\n",
       "559070282590318              3.0            0.0\n",
       "612975398150771              1.0            0.0\n",
       "683225025151763             12.0            0.0\n",
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       "791900554484110             17.0            0.0\n",
       "813406996989033             27.0            0.0\n",
       "846003162232794             24.0            0.0\n",
       "876214039257878             19.0            0.0\n",
       "894496323414241             30.0            0.0\n",
       "974917123101852              6.0            0.0\n",
       "1020491770477170             7.0            0.0\n",
       "1085588354075472            36.0            0.0\n",
       "1113548317003609             5.0            0.0\n",
       "1151615064267198            14.0            0.0\n",
       "1212888607375572             3.0            0.0\n",
       "...                          ...            ...\n",
       "7755192592474560600          NaN            1.0\n",
       "7758330896817653793          NaN            1.0\n",
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       "8230622630777650905          NaN            1.0\n",
       "8269428350309707258          NaN            1.0\n",
       "8301189279686418707          NaN            1.0\n",
       "8311977084031214056          NaN            1.0\n",
       "8426464419237930778          NaN            1.0\n",
       "8518222756719527152          NaN            1.0\n",
       "8583865643501804678          NaN            1.0\n",
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       "8608013793308321063          NaN            1.0\n",
       "8706369250388149903          NaN            1.0\n",
       "8846778001425047512          NaN            1.0\n",
       "8915609277685342555          NaN            1.0\n",
       "8940628648611040535          NaN            1.0\n",
       "8940809657798217129          NaN            1.0\n",
       "8950702799043022122          NaN            1.0\n",
       "8973020755901086044          NaN            1.0\n",
       "8993520643933861492          NaN            1.0\n",
       "9028250629266237437          NaN            1.0\n",
       "9130417606158582129          NaN            1.0\n",
       "\n",
       "[285372 rows x 2 columns]"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_ip = events_ip.merge(installs_ip, on=\"ip_address\", how=\"outer\")\n",
    "plot_ip[\"cant_installs\"][plot_ip[\"cant_installs\"].isnull()] = 0\n",
    "plot_ip"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### No me sirven las instalaciones de la gente que no sé qué eventos realizó."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "plot_ip_clean = plot_ip[~plot_ip[\"cant_events\"].isnull()]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cantidad de personas y cantidad de instalaciones"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.7/site-packages/ipykernel_launcher.py:1: 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",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    },
    {
     "data": {
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       "      <th></th>\n",
       "      <th>cantidad</th>\n",
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      ],
      "text/plain": [
       "               cantidad\n",
       "cant_installs          \n",
       "0.0              282655\n",
       "1.0                2151\n",
       "2.0                 325\n",
       "3.0                  34\n",
       "4.0                  21\n",
       "5.0                   8\n",
       "6.0                   1\n",
       "7.0                   5\n",
       "9.0                   2\n",
       "11.0                  2\n",
       "12.0                  2\n",
       "13.0                  1\n",
       "14.0                  1\n",
       "16.0                  1\n",
       "17.0                  1\n",
       "26.0                  1\n",
       "33.0                  1"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_ip_clean[\"cantidad\"] = 1\n",
    "plot_ip_clean.groupby(\"cant_installs\").agg({\"cantidad\":\"sum\"})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "cantidad_instalaciones = plot_ip_clean[\"cant_installs\"].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Media de eventos por cantidad de instalaciones ( Cada 51 eventos se hace 1 instalación )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
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       "      <th>33.0</th>\n",
       "      <td>22640.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                cant_events\n",
       "cant_installs              \n",
       "0.0                7.564752\n",
       "1.0               51.515574\n",
       "2.0              129.329231\n",
       "3.0              702.147059\n",
       "4.0             1523.047619\n",
       "5.0             2656.875000\n",
       "6.0              661.000000\n",
       "7.0             1957.800000\n",
       "9.0            12186.000000\n",
       "11.0            6481.500000\n",
       "12.0           10207.000000\n",
       "13.0            6241.000000\n",
       "14.0            4736.000000\n",
       "16.0            7561.000000\n",
       "17.0            9777.000000\n",
       "26.0            7100.000000\n",
       "33.0           22640.000000"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ploteo = plot_ip_clean.groupby(\"cant_installs\").agg({\"cant_events\":\"mean\"})\n",
    "ploteo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "ploteo.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 17 artists>"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(np.array(ploteo[\"cant_installs\"]), np.array(ploteo[\"cant_events\"]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.7.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}