Año de lanzamiento y heatmap de cantidad de compras por mes según el año de lanzamiento.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sb\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Martín-\\Anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py:2728: DtypeWarning: Columns (4) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  interactivity=interactivity, compiler=compiler, result=result)\n"
     ]
    }
   ],
   "source": [
    "left = pd.read_csv('events.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "right = pd.read_csv('phone_release_year.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>timestamp</th>\n",
       "      <th>event</th>\n",
       "      <th>person</th>\n",
       "      <th>url</th>\n",
       "      <th>sku</th>\n",
       "      <th>model</th>\n",
       "      <th>condition</th>\n",
       "      <th>storage</th>\n",
       "      <th>color</th>\n",
       "      <th>skus</th>\n",
       "      <th>...</th>\n",
       "      <th>city</th>\n",
       "      <th>region</th>\n",
       "      <th>country</th>\n",
       "      <th>device_type</th>\n",
       "      <th>screen_resolution</th>\n",
       "      <th>operating_system_version</th>\n",
       "      <th>browser_version</th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-05-31 23:38:05</td>\n",
       "      <td>ad campaign hit</td>\n",
       "      <td>0004b0a2</td>\n",
       "      <td>/comprar/iphone/iphone-5s</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-05-31 23:38:05</td>\n",
       "      <td>visited site</td>\n",
       "      <td>0004b0a2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>Camaragibe</td>\n",
       "      <td>Pernambuco</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>Smartphone</td>\n",
       "      <td>360x640</td>\n",
       "      <td>Android 6</td>\n",
       "      <td>Chrome Mobile 39</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-05-31 23:38:09</td>\n",
       "      <td>viewed product</td>\n",
       "      <td>0004b0a2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2694</td>\n",
       "      <td>iPhone 5s</td>\n",
       "      <td>Bom</td>\n",
       "      <td>32GB</td>\n",
       "      <td>Cinza espacial</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>191.0</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018-05-31 23:38:40</td>\n",
       "      <td>checkout</td>\n",
       "      <td>0004b0a2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2694</td>\n",
       "      <td>iPhone 5s</td>\n",
       "      <td>Bom</td>\n",
       "      <td>32GB</td>\n",
       "      <td>Cinza espacial</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>191.0</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018-05-29 13:29:25</td>\n",
       "      <td>viewed product</td>\n",
       "      <td>0006a21a</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15338</td>\n",
       "      <td>Samsung Galaxy S8</td>\n",
       "      <td>Bom</td>\n",
       "      <td>64GB</td>\n",
       "      <td>Dourado</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>135.0</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             timestamp            event    person                        url  \\\n",
       "0  2018-05-31 23:38:05  ad campaign hit  0004b0a2  /comprar/iphone/iphone-5s   \n",
       "1  2018-05-31 23:38:05     visited site  0004b0a2                        NaN   \n",
       "2  2018-05-31 23:38:09   viewed product  0004b0a2                        NaN   \n",
       "3  2018-05-31 23:38:40         checkout  0004b0a2                        NaN   \n",
       "4  2018-05-29 13:29:25   viewed product  0006a21a                        NaN   \n",
       "\n",
       "     sku              model condition storage           color skus  ...   \\\n",
       "0    NaN                NaN       NaN     NaN             NaN  NaN  ...    \n",
       "1    NaN                NaN       NaN     NaN             NaN  NaN  ...    \n",
       "2   2694          iPhone 5s       Bom    32GB  Cinza espacial  NaN  ...    \n",
       "3   2694          iPhone 5s       Bom    32GB  Cinza espacial  NaN  ...    \n",
       "4  15338  Samsung Galaxy S8       Bom    64GB         Dourado  NaN  ...    \n",
       "\n",
       "         city      region country device_type screen_resolution  \\\n",
       "0         NaN         NaN     NaN         NaN               NaN   \n",
       "1  Camaragibe  Pernambuco  Brazil  Smartphone           360x640   \n",
       "2         NaN         NaN     NaN         NaN               NaN   \n",
       "3         NaN         NaN     NaN         NaN               NaN   \n",
       "4         NaN         NaN     NaN         NaN               NaN   \n",
       "\n",
       "  operating_system_version   browser_version Unnamed: 0    year month  \n",
       "0                      NaN               NaN        NaN     NaN   NaN  \n",
       "1                Android 6  Chrome Mobile 39        NaN     NaN   NaN  \n",
       "2                      NaN               NaN      191.0  2013.0   9.0  \n",
       "3                      NaN               NaN      191.0  2013.0   9.0  \n",
       "4                      NaN               NaN      135.0  2017.0   4.0  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "datos = pd.merge(left, right, how='left', on='model')\n",
    "datos.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>timestamp</th>\n",
       "      <th>event</th>\n",
       "      <th>person</th>\n",
       "      <th>sku</th>\n",
       "      <th>model</th>\n",
       "      <th>condition</th>\n",
       "      <th>storage</th>\n",
       "      <th>color</th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>220</th>\n",
       "      <td>2018-03-20 17:46:12</td>\n",
       "      <td>conversion</td>\n",
       "      <td>00204059</td>\n",
       "      <td>3084</td>\n",
       "      <td>Motorola Moto X2</td>\n",
       "      <td>Muito Bom</td>\n",
       "      <td>32GB</td>\n",
       "      <td>Couro Vintage</td>\n",
       "      <td>57.0</td>\n",
       "      <td>2014.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2282</th>\n",
       "      <td>2018-04-26 22:28:53</td>\n",
       "      <td>conversion</td>\n",
       "      <td>00c13dee</td>\n",
       "      <td>6650</td>\n",
       "      <td>Samsung Galaxy Core Plus Duos TV</td>\n",
       "      <td>Muito Bom</td>\n",
       "      <td>4GB</td>\n",
       "      <td>Branco</td>\n",
       "      <td>80.0</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2547</th>\n",
       "      <td>2018-06-10 14:37:50</td>\n",
       "      <td>conversion</td>\n",
       "      <td>00fdbb4b</td>\n",
       "      <td>3348</td>\n",
       "      <td>Samsung Galaxy S6 Flat</td>\n",
       "      <td>Muito Bom</td>\n",
       "      <td>32GB</td>\n",
       "      <td>Branco</td>\n",
       "      <td>132.0</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4245</th>\n",
       "      <td>2018-03-16 13:50:25</td>\n",
       "      <td>conversion</td>\n",
       "      <td>0146a9df</td>\n",
       "      <td>2694</td>\n",
       "      <td>iPhone 5s</td>\n",
       "      <td>Bom</td>\n",
       "      <td>32GB</td>\n",
       "      <td>Cinza espacial</td>\n",
       "      <td>191.0</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6985</th>\n",
       "      <td>2018-02-09 22:07:07</td>\n",
       "      <td>conversion</td>\n",
       "      <td>01db2fe6</td>\n",
       "      <td>6357</td>\n",
       "      <td>Samsung Galaxy J5</td>\n",
       "      <td>Bom</td>\n",
       "      <td>16GB</td>\n",
       "      <td>Preto</td>\n",
       "      <td>96.0</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                timestamp       event    person   sku  \\\n",
       "220   2018-03-20 17:46:12  conversion  00204059  3084   \n",
       "2282  2018-04-26 22:28:53  conversion  00c13dee  6650   \n",
       "2547  2018-06-10 14:37:50  conversion  00fdbb4b  3348   \n",
       "4245  2018-03-16 13:50:25  conversion  0146a9df  2694   \n",
       "6985  2018-02-09 22:07:07  conversion  01db2fe6  6357   \n",
       "\n",
       "                                 model  condition storage           color  \\\n",
       "220                   Motorola Moto X2  Muito Bom    32GB   Couro Vintage   \n",
       "2282  Samsung Galaxy Core Plus Duos TV  Muito Bom     4GB          Branco   \n",
       "2547            Samsung Galaxy S6 Flat  Muito Bom    32GB          Branco   \n",
       "4245                         iPhone 5s        Bom    32GB  Cinza espacial   \n",
       "6985                 Samsung Galaxy J5        Bom    16GB           Preto   \n",
       "\n",
       "      Unnamed: 0    year  month  \n",
       "220         57.0  2014.0    9.0  \n",
       "2282        80.0  2013.0    6.0  \n",
       "2547       132.0  2015.0    4.0  \n",
       "4245       191.0  2013.0    9.0  \n",
       "6985        96.0  2015.0    6.0  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "datos_comprados_r = datos[datos[\"event\"] == \"conversion\"]\n",
    "datos_comprados = datos_comprados_r.drop([\"url\",\"skus\",\"search_term\",\"staticpage\",\"campaign_source\",\"search_engine\",\"channel\",\"new_vs_returning\",\"city\",\"region\",\"country\",\"device_type\",\"screen_resolution\",\"operating_system_version\",\"browser_version\"],axis='columns')\n",
    "datos_comprados.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x90c4a1048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cell = sns.countplot(data=datos_comprados, x = 'year',edgecolor=(0,0,0), linewidth=2)\n",
    "cell.set_title('Años de los celulares comprados')\n",
    "cell.grid(True, which='major', linestyle='-.', axis='y' )\n",
    "\n",
    "for i in cell.patches:\n",
    "    # get_x pulls left or right; get_height pushes up or down\n",
    "    cell.text(i.get_x()+.15, i.get_height()+.5, \\\n",
    "            str(round((i.get_height()), 2)), fontsize=13,\n",
    "                color='black')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(33,0.5,'Mes de Compra')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x90cff6278>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "datos_comprados['timestamp'] = pd.to_datetime(datos_comprados['timestamp'])\n",
    "datos_comprados['timestamp_month'] = datos_comprados['timestamp'].dt.month\n",
    "\n",
    "cross = pd.crosstab(datos_comprados.timestamp_month, datos_comprados.year)\n",
    "cross.head()\n",
    "\n",
    "g = sb.heatmap(cross,  cmap=\"BuPu\")\n",
    "g.set_title(\"Cantidad de compras por mes segun el año de lanzamiento\", fontsize=22)\n",
    "g.set_xlabel(\"Año de lanzamiento\",fontsize=16)\n",
    "g.set_ylabel(\"Mes de Compra\", fontsize=16)"
   ]
  }
 ],
 "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": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}