BLE devices at QS15.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "% pylab inline\n",
    "import pandas as pd\n",
    "import sqlite3\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "db = sqlite3.connect(\"/Users/onyame/Dropbox/QuantifiedSelf/btle_backup_20062015_1241.sqlite\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df = pd.read_sql(\"SELECT * from devices\", db,index_col='id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>address</th>\n",
       "      <th>addresstype</th>\n",
       "      <th>devicename</th>\n",
       "      <th>devicetype</th>\n",
       "      <th>firstseen</th>\n",
       "      <th>lastseen</th>\n",
       "      <th>scanresp</th>\n",
       "      <th>manufacturerspecificdatakey</th>\n",
       "      <th>manufacturerspecificdatafield</th>\n",
       "      <th>servicesuuid16</th>\n",
       "      <th>servicesuuid32</th>\n",
       "      <th>servicesuuid128</th>\n",
       "      <th>solicitedservicesuuid16</th>\n",
       "      <th>solicitedservicesuuid128</th>\n",
       "      <th>servicedata</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td> E1:53:4A:3A:6F:82</td>\n",
       "      <td> None</td>\n",
       "      <td>      One</td>\n",
       "      <td>                     Fitbit One (from device name)</td>\n",
       "      <td> 22/05/2015 12:24:46</td>\n",
       "      <td> 22/05/2015 12:25:01</td>\n",
       "      <td> None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>                                           None</td>\n",
       "      <td> None</td>\n",
       "      <td> None</td>\n",
       "      <td> adab6bc46e7d4601bda2bffaa68956ba</td>\n",
       "      <td> None</td>\n",
       "      <td> None</td>\n",
       "      <td>                   Device Information (180a): 0504</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td> C6:69:71:3C:BB:91</td>\n",
       "      <td> None</td>\n",
       "      <td>      One</td>\n",
       "      <td> Fitbit One (from device name), Fitbit Charge H...</td>\n",
       "      <td> 22/05/2015 12:24:42</td>\n",
       "      <td> 20/06/2015 12:36:21</td>\n",
       "      <td> None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>                                           None</td>\n",
       "      <td> None</td>\n",
       "      <td> None</td>\n",
       "      <td> adabfb006e7d4601bda2bffaa68956ba</td>\n",
       "      <td> None</td>\n",
       "      <td> None</td>\n",
       "      <td>                   Device Information (180a): 0506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td> DD:3A:1E:C6:8A:A8</td>\n",
       "      <td> None</td>\n",
       "      <td> estimote</td>\n",
       "      <td>                        Apple device (from MSData)</td>\n",
       "      <td> 22/05/2015 14:53:16</td>\n",
       "      <td> 20/06/2015 12:36:19</td>\n",
       "      <td> None</td>\n",
       "      <td> 76</td>\n",
       "      <td> 0215b9407f30f5f8466eaff925556b57fe6d8aa81ec6af</td>\n",
       "      <td> None</td>\n",
       "      <td> None</td>\n",
       "      <td>                             None</td>\n",
       "      <td> None</td>\n",
       "      <td> None</td>\n",
       "      <td> Device Information (180a): a88ac61e3addafa88ac61e</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td> F6:19:23:5D:29:68</td>\n",
       "      <td> None</td>\n",
       "      <td> estimote</td>\n",
       "      <td>                        Apple device (from MSData)</td>\n",
       "      <td> 22/05/2015 22:42:13</td>\n",
       "      <td> 23/05/2015 10:31:10</td>\n",
       "      <td> None</td>\n",
       "      <td> 76</td>\n",
       "      <td> 0215b9407f30f5f8466eaff925556b57fe6d2968235db6</td>\n",
       "      <td> None</td>\n",
       "      <td> None</td>\n",
       "      <td>                             None</td>\n",
       "      <td> None</td>\n",
       "      <td> None</td>\n",
       "      <td> Device Information (180a): 68295d2319f6b668295d23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td> 14:99:E2:05:F8:BD</td>\n",
       "      <td> None</td>\n",
       "      <td>     None</td>\n",
       "      <td>                        Apple device (from MSData)</td>\n",
       "      <td> 23/05/2015 15:46:01</td>\n",
       "      <td> 23/05/2015 15:46:01</td>\n",
       "      <td> None</td>\n",
       "      <td> 76</td>\n",
       "      <td>                               09060357c0a8007a</td>\n",
       "      <td> None</td>\n",
       "      <td> None</td>\n",
       "      <td>                             None</td>\n",
       "      <td> None</td>\n",
       "      <td> None</td>\n",
       "      <td>                                              None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              address addresstype devicename  \\\n",
       "id                                             \n",
       "1   E1:53:4A:3A:6F:82        None        One   \n",
       "2   C6:69:71:3C:BB:91        None        One   \n",
       "3   DD:3A:1E:C6:8A:A8        None   estimote   \n",
       "4   F6:19:23:5D:29:68        None   estimote   \n",
       "5   14:99:E2:05:F8:BD        None       None   \n",
       "\n",
       "                                           devicetype            firstseen  \\\n",
       "id                                                                           \n",
       "1                       Fitbit One (from device name)  22/05/2015 12:24:46   \n",
       "2   Fitbit One (from device name), Fitbit Charge H...  22/05/2015 12:24:42   \n",
       "3                          Apple device (from MSData)  22/05/2015 14:53:16   \n",
       "4                          Apple device (from MSData)  22/05/2015 22:42:13   \n",
       "5                          Apple device (from MSData)  23/05/2015 15:46:01   \n",
       "\n",
       "               lastseen scanresp  manufacturerspecificdatakey  \\\n",
       "id                                                              \n",
       "1   22/05/2015 12:25:01     None                          NaN   \n",
       "2   20/06/2015 12:36:21     None                          NaN   \n",
       "3   20/06/2015 12:36:19     None                           76   \n",
       "4   23/05/2015 10:31:10     None                           76   \n",
       "5   23/05/2015 15:46:01     None                           76   \n",
       "\n",
       "                     manufacturerspecificdatafield servicesuuid16  \\\n",
       "id                                                                  \n",
       "1                                             None           None   \n",
       "2                                             None           None   \n",
       "3   0215b9407f30f5f8466eaff925556b57fe6d8aa81ec6af           None   \n",
       "4   0215b9407f30f5f8466eaff925556b57fe6d2968235db6           None   \n",
       "5                                 09060357c0a8007a           None   \n",
       "\n",
       "   servicesuuid32                   servicesuuid128 solicitedservicesuuid16  \\\n",
       "id                                                                            \n",
       "1            None  adab6bc46e7d4601bda2bffaa68956ba                    None   \n",
       "2            None  adabfb006e7d4601bda2bffaa68956ba                    None   \n",
       "3            None                              None                    None   \n",
       "4            None                              None                    None   \n",
       "5            None                              None                    None   \n",
       "\n",
       "   solicitedservicesuuid128                                        servicedata  \n",
       "id                                                                              \n",
       "1                      None                    Device Information (180a): 0504  \n",
       "2                      None                    Device Information (180a): 0506  \n",
       "3                      None  Device Information (180a): a88ac61e3addafa88ac61e  \n",
       "4                      None  Device Information (180a): 68295d2319f6b668295d23  \n",
       "5                      None                                               None  "
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df['devicetype'] = df['devicetype'].str.replace('\\(.*\\)', '', case=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "device_types = df.groupby('devicetype').size()\n",
    "device_names = df.groupby('devicename').size()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "devicetype\n",
       "Apple device              447\n",
       "Ericsson device             1\n",
       "Fitbit Charge               5\n",
       "Fitbit Charge HR           24\n",
       "Fitbit Flex                12\n",
       "Fitbit One                 27\n",
       "Garmin Device               1\n",
       "Garmin Vivosmart            1\n",
       "Google device               1\n",
       "Jawbone UP24                9\n",
       "MI                          2\n",
       "Misfit Wearables Corp       7\n",
       "Nike device                 5\n",
       "Nordic device               1\n",
       "Unknown device            107\n",
       "dtype: int64"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "device_types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x110559090>"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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RsaS4PTEinigh5vPpn5gyp6yysGXHlfQZ0pDmLODxxvaIWJQzbhG7qn/jyaQP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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1105c6f10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "device_types.plot(kind='bar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index([u'Apple device ', u'Ericsson device ', u'Fitbit Charge ', u'Fitbit Charge HR ', u'Fitbit Flex ', u'Fitbit One ', u'Garmin Device ', u'Garmin Vivosmart ', u'Google device ', u'Jawbone UP24 ', u'MI ', u'Misfit Wearables Corp ', u'Nike device ', u'Nordic device ', u'Unknown device'], dtype='object')"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "device_types.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "devices = device_types.drop([u'Apple device ',u'Unknown device'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "devicetype\n",
       "Ericsson device            1\n",
       "Fitbit Charge              5\n",
       "Fitbit Charge HR          24\n",
       "Fitbit Flex               12\n",
       "Fitbit One                27\n",
       "Garmin Device              1\n",
       "Garmin Vivosmart           1\n",
       "Google device              1\n",
       "Jawbone UP24               9\n",
       "MI                         2\n",
       "Misfit Wearables Corp      7\n",
       "Nike device                5\n",
       "Nordic device              1\n",
       "dtype: int64"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "devices"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x110c22fd0>"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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fRU1/7091JvMe0rKFf6WGpT3VusnTgTNIXwK+DOTuQtKIZZzUxj5XK45HJb21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\nMvv/3DLaffZtl3AAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1108cbfd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "devices.plot(kind='bar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
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