exploring_imessage.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Exploring iMessage Data\n",
    "\n",
    "Using Jupyter, Pandas and NLTK to explore iMessage data on MacOS"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "notes"
    }
   },
   "source": [
    "Run slides with:\n",
    "\n",
    "jupyter nbconvert exploring_imessage.ipynb --to slides --post serve"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "notes"
    }
   },
   "source": [
    "Requirements: this notebook is running on MacOS, in order to view iMessage data.\n",
    "\n",
    "This is a notebook for people to see the conversational patterns in their digital communications. This notebook currently includes\n",
    "\n",
    "#### Important Notes:\n",
    "This notebook was constructed with the following tools:\n",
    "\n",
    "Python 3.6\n",
    "\n",
    "Dates\n",
    "I ran into an issue converting iMessage dates in the SQLite query language. They are stored in Mac Absolute Time, (number of seconds since 01/01/2001 00:00:00 UTC), not Unix Time!\n",
    "\n",
    "Since I am running this notebook on High Sierra, it's worth mentioning that the date formats have changed since previous versions (they are now padded with 9 0's!) and I will use this for converting the dates:\n",
    "\n",
    "datetime(message.date/1000000000 + strftime(\"%s\", \"2001-01-01\"),\"unixepoch\",\"localtime\")\n",
    "\n",
    "If your version of MacOS is lower than 10.13, you should replace line with this:\n",
    "\n",
    "datetime(date + strftime('%s','2001-01-01'), 'unixepoch')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Introduction\n",
    "\n",
    "Why would you do this?\n",
    "\n",
    "A data-driven journey of self-discovery! We all generate a lot of textual data, messaging each other each day. What kinds of language do we choose to use, and what does it say about us?\n",
    "\n",
    "iMessage data is synced across your Apple devices, so it's fairly easy to get to on your Mac."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Extract iMessage Data\n",
    "\n",
    "iMessage data is stored in **chat.db**, an SQLite database located in the user's Library directory.\n",
    "\n",
    "My iMessage data only goes back until 2016, as that's when I moved to Australia and everything changed. You may have a lot more, or a lot less data than I do!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Organise Imports\n",
    "\n",
    "The first thing I like to do is grab all the imports that I'll use throughout the Notebook."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import sys\n",
    "import sqlite3\n",
    "from datetime import date, datetime\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import nltk\n",
    "import json"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Grab your chat.db database path"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "We locate our username in order to navigate to the correct path where our chat.db file is stored.\n",
    "Once we have this, we can make the connection. Let's see what tables we have access to in the database!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'pauline'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "USERNAME = os.popen('whoami').read().strip()\n",
    "USERNAME"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
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      "text/plain": [
       "                         name\n",
       "0   _SqliteDatabaseProperties\n",
       "1                     message\n",
       "2             sqlite_sequence\n",
       "3                        chat\n",
       "4                  attachment\n",
       "5                      handle\n",
       "6     message_attachment_join\n",
       "7            chat_handle_join\n",
       "8           chat_message_join\n",
       "9            deleted_messages\n",
       "10      sync_deleted_messages\n",
       "11    message_processing_task\n",
       "12         sync_deleted_chats\n",
       "13   sync_deleted_attachments\n",
       "14                    kvtable\n",
       "15               sqlite_stat1"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chat_db = '/Users/'+USERNAME+'/Library/Messages/chat.db'\n",
    "\n",
    "conn = sqlite3.connect(chat_db, check_same_thread=False)\n",
    "query = '''\n",
    "        SELECT name \n",
    "        FROM sqlite_master \n",
    "        WHERE type='table';\n",
    "        '''\n",
    "df = pd.read_sql_query(query, conn)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Turns out we have 15 different tables here! Let's look to see what ones might be interesting to us.\n",
    "\n",
    "The **message** table looks useful, as does **chat**. I'm guessing **handle** is like a user handle.\n",
    "\n",
    "Let's check out the **message** schema."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
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       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>36</td>\n",
       "      <td>was_data_detected</td>\n",
       "      <td>INTEGER</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>37</td>\n",
       "      <td>was_deduplicated</td>\n",
       "      <td>INTEGER</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>38</td>\n",
       "      <td>is_audio_message</td>\n",
       "      <td>INTEGER</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>39</td>\n",
       "      <td>is_played</td>\n",
       "      <td>INTEGER</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>40</td>\n",
       "      <td>date_played</td>\n",
       "      <td>INTEGER</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>41</td>\n",
       "      <td>item_type</td>\n",
       "      <td>INTEGER</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>42</td>\n",
       "      <td>other_handle</td>\n",
       "      <td>INTEGER</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>43</td>\n",
       "      <td>group_title</td>\n",
       "      <td>TEXT</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>44</td>\n",
       "      <td>group_action_type</td>\n",
       "      <td>INTEGER</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>45</td>\n",
       "      <td>share_status</td>\n",
       "      <td>INTEGER</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>46</td>\n",
       "      <td>share_direction</td>\n",
       "      <td>INTEGER</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>47</td>\n",
       "      <td>is_expirable</td>\n",
       "      <td>INTEGER</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>48</td>\n",
       "      <td>expire_state</td>\n",
       "      <td>INTEGER</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>49</td>\n",
       "      <td>message_action_type</td>\n",
       "      <td>INTEGER</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>50</td>\n",
       "      <td>message_source</td>\n",
       "      <td>INTEGER</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>51</td>\n",
       "      <td>associated_message_guid</td>\n",
       "      <td>STRING</td>\n",
       "      <td>0</td>\n",
       "      <td>NULL</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>52</td>\n",
       "      <td>balloon_bundle_id</td>\n",
       "      <td>STRING</td>\n",
       "      <td>0</td>\n",
       "      <td>NULL</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>53</td>\n",
       "      <td>payload_data</td>\n",
       "      <td>BLOB</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>54</td>\n",
       "      <td>associated_message_type</td>\n",
       "      <td>INTEGER</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>55</td>\n",
       "      <td>expressive_send_style_id</td>\n",
       "      <td>STRING</td>\n",
       "      <td>0</td>\n",
       "      <td>NULL</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>56</td>\n",
       "      <td>associated_message_range_location</td>\n",
       "      <td>INTEGER</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>57</td>\n",
       "      <td>associated_message_range_length</td>\n",
       "      <td>INTEGER</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>58</td>\n",
       "      <td>time_expressive_send_played</td>\n",
       "      <td>INTEGER</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>59</td>\n",
       "      <td>message_summary_info</td>\n",
       "      <td>BLOB</td>\n",
       "      <td>0</td>\n",
       "      <td>NULL</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>60</td>\n",
       "      <td>ck_sync_state</td>\n",
       "      <td>INTEGER</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>61</td>\n",
       "      <td>ck_record_id</td>\n",
       "      <td>TEXT</td>\n",
       "      <td>0</td>\n",
       "      <td>NULL</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>62</td>\n",
       "      <td>ck_record_change_tag</td>\n",
       "      <td>TEXT</td>\n",
       "      <td>0</td>\n",
       "      <td>NULL</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>63</td>\n",
       "      <td>destination_caller_id</td>\n",
       "      <td>TEXT</td>\n",
       "      <td>0</td>\n",
       "      <td>NULL</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>64</td>\n",
       "      <td>sr_ck_sync_state</td>\n",
       "      <td>INTEGER</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>65</td>\n",
       "      <td>sr_ck_record_id</td>\n",
       "      <td>TEXT</td>\n",
       "      <td>0</td>\n",
       "      <td>NULL</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>66</td>\n",
       "      <td>sr_ck_record_change_tag</td>\n",
       "      <td>TEXT</td>\n",
       "      <td>0</td>\n",
       "      <td>NULL</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    cid                               name     type  notnull dflt_value  pk\n",
       "0     0                              ROWID  INTEGER        0       None   1\n",
       "1     1                               guid     TEXT        1       None   0\n",
       "2     2                               text     TEXT        0       None   0\n",
       "3     3                            replace  INTEGER        0          0   0\n",
       "4     4                     service_center     TEXT        0       None   0\n",
       "5     5                          handle_id  INTEGER        0          0   0\n",
       "6     6                            subject     TEXT        0       None   0\n",
       "7     7                            country     TEXT        0       None   0\n",
       "8     8                     attributedBody     BLOB        0       None   0\n",
       "9     9                            version  INTEGER        0          0   0\n",
       "10   10                               type  INTEGER        0          0   0\n",
       "11   11                            service     TEXT        0       None   0\n",
       "12   12                            account     TEXT        0       None   0\n",
       "13   13                       account_guid     TEXT        0       None   0\n",
       "14   14                              error  INTEGER        0          0   0\n",
       "15   15                               date  INTEGER        0       None   0\n",
       "16   16                          date_read  INTEGER        0       None   0\n",
       "17   17                     date_delivered  INTEGER        0       None   0\n",
       "18   18                       is_delivered  INTEGER        0          0   0\n",
       "19   19                        is_finished  INTEGER        0          0   0\n",
       "20   20                           is_emote  INTEGER        0          0   0\n",
       "21   21                         is_from_me  INTEGER        0          0   0\n",
       "22   22                           is_empty  INTEGER        0          0   0\n",
       "23   23                         is_delayed  INTEGER        0          0   0\n",
       "24   24                      is_auto_reply  INTEGER        0          0   0\n",
       "25   25                        is_prepared  INTEGER        0          0   0\n",
       "26   26                            is_read  INTEGER        0          0   0\n",
       "27   27                  is_system_message  INTEGER        0          0   0\n",
       "28   28                            is_sent  INTEGER        0          0   0\n",
       "29   29                     has_dd_results  INTEGER        0          0   0\n",
       "30   30                 is_service_message  INTEGER        0          0   0\n",
       "31   31                         is_forward  INTEGER        0          0   0\n",
       "32   32                     was_downgraded  INTEGER        0          0   0\n",
       "33   33                         is_archive  INTEGER        0          0   0\n",
       "34   34              cache_has_attachments  INTEGER        0          0   0\n",
       "35   35                    cache_roomnames     TEXT        0       None   0\n",
       "36   36                  was_data_detected  INTEGER        0          0   0\n",
       "37   37                   was_deduplicated  INTEGER        0          0   0\n",
       "38   38                   is_audio_message  INTEGER        0          0   0\n",
       "39   39                          is_played  INTEGER        0          0   0\n",
       "40   40                        date_played  INTEGER        0       None   0\n",
       "41   41                          item_type  INTEGER        0          0   0\n",
       "42   42                       other_handle  INTEGER        0          0   0\n",
       "43   43                        group_title     TEXT        0       None   0\n",
       "44   44                  group_action_type  INTEGER        0          0   0\n",
       "45   45                       share_status  INTEGER        0          0   0\n",
       "46   46                    share_direction  INTEGER        0          0   0\n",
       "47   47                       is_expirable  INTEGER        0          0   0\n",
       "48   48                       expire_state  INTEGER        0          0   0\n",
       "49   49                message_action_type  INTEGER        0          0   0\n",
       "50   50                     message_source  INTEGER        0          0   0\n",
       "51   51            associated_message_guid   STRING        0       NULL   0\n",
       "52   52                  balloon_bundle_id   STRING        0       NULL   0\n",
       "53   53                       payload_data     BLOB        0       None   0\n",
       "54   54            associated_message_type  INTEGER        0          0   0\n",
       "55   55           expressive_send_style_id   STRING        0       NULL   0\n",
       "56   56  associated_message_range_location  INTEGER        0          0   0\n",
       "57   57    associated_message_range_length  INTEGER        0          0   0\n",
       "58   58        time_expressive_send_played  INTEGER        0          0   0\n",
       "59   59               message_summary_info     BLOB        0       NULL   0\n",
       "60   60                      ck_sync_state  INTEGER        0          0   0\n",
       "61   61                       ck_record_id     TEXT        0       NULL   0\n",
       "62   62               ck_record_change_tag     TEXT        0       NULL   0\n",
       "63   63              destination_caller_id     TEXT        0       NULL   0\n",
       "64   64                   sr_ck_sync_state  INTEGER        0          0   0\n",
       "65   65                    sr_ck_record_id     TEXT        0       NULL   0\n",
       "66   66            sr_ck_record_change_tag     TEXT        0       NULL   0"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "conn = sqlite3.connect(chat_db, check_same_thread=False)\n",
    "query = '''\n",
    "        PRAGMA table_info (message);\n",
    "        '''\n",
    "df = pd.read_sql_query(query, conn)\n",
    "\n",
    "pd.set_option('display.max_rows', 1000) # Display all columns\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Ok, that's all our data that we want to look at! The **text** column looks promising, that should be our messages.\n",
    "\n",
    "Let's get a small slice of our dataframe and see what we get."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ROWID</th>\n",
       "      <th>date</th>\n",
       "      <th>text</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>218</td>\n",
       "      <td>477363211000000000</td>\n",
       "      <td>2degrees alert: Just a reminder that your bala...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>219</td>\n",
       "      <td>477363211000000000</td>\n",
       "      <td>2degrees alert: You don't have enough credit t...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>220</td>\n",
       "      <td>477368362000000000</td>\n",
       "      <td>How's Australia? Settling in?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>296</td>\n",
       "      <td>477532796000000000</td>\n",
       "      <td>2degrees alert: Just a reminder that your bala...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>298</td>\n",
       "      <td>477532796000000000</td>\n",
       "      <td>2degrees alert: You don't have enough credit t...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "   ROWID                date  \\\n",
       "0    218  477363211000000000   \n",
       "1    219  477363211000000000   \n",
       "2    220  477368362000000000   \n",
       "3    296  477532796000000000   \n",
       "4    298  477532796000000000   \n",
       "\n",
       "                                                text  \n",
       "0  2degrees alert: Just a reminder that your bala...  \n",
       "1  2degrees alert: You don't have enough credit t...  \n",
       "2                      How's Australia? Settling in?  \n",
       "3  2degrees alert: Just a reminder that your bala...  \n",
       "4  2degrees alert: You don't have enough credit t...  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "conn = sqlite3.connect(chat_db, check_same_thread=False)\n",
    "query = '''\n",
    "        SELECT ROWID, date, text \n",
    "        FROM message;\n",
    "        '''\n",
    "df = pd.read_sql_query(query, conn)\n",
    "df[:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "However, those dates look pretty funky. I wonder why that is? \n",
    "It doesn't *look* like Unix time - there's too many digits."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Time Conversions\n",
    "\n",
    "### Unix Time\n",
    "- Number of seconds that have elapsed since **Midnight, January 1 1970 GMT**\n",
    "\n",
    "### Core Foundation (CF) Absolute Time\n",
    "- Number of seconds elapsed since **Midnight, January 1 2001 UTC**\n",
    "- Prior to High Sierra: `datetime(message.date + strftime(\"%s\", \"2001-01-01\") ,\"unixepoch\",\"localtime\"`\n",
    "- Release of High Sierra (macOS 10.13) means this is now padded with extra 0's\n",
    "- Now use `datetime(message.date/1000000000 + strftime(\"%s\", \"2001-01-01\") ,\"unixepoch\",\"localtime\"`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "notes"
    }
   },
   "source": [
    "### Unix Time\n",
    "\n",
    "If you aren't familiar with **Unix time**, it's the number of seconds that have elapsed since Midnight, January 1 1970 GMT. In computer systems, it is stored as a signed 32 bit integer, which is a value up to 2<sup>31-1</sup>, or up to 2,147,483,647 seconds after 1 January 1970. [1]\n",
    "\n",
    "Aside: this means it's going to run into issues on the January 19, 2038 due to a 32-bit overflow! Time will be meaningless! It'll be the Y2K thing all over again.\n",
    "\n",
    "Why wasn't unix time stored as an unsigned integer? I don't know!  `¯\\_(ツ)_/¯ `\n",
    "\n",
    "### CF Absolute Time (Mac)\n",
    "\n",
    "But this date has 18 digits, which is too many! Turns out, this is actually **Core Foundation (CF) Absolute Time**.\n",
    "\n",
    "This is how iMessage time data is stored on your Mac, and is the number of seconds elapsed since Midnight, January 1 2001 UTC. Like Unix time, it is also represented as a 32 bit integer (unsigned or signed?)\n",
    "\n",
    "However, that changed since the release of High Sierra (macOS 10.13). I'm trying to find the reference for this but I can't remember where I saw it, so you'll need to convert the time.\n",
    "\n",
    "`datetime(message.date/1000000000 + strftime(\"%s\", \"2001-01-01\") ,\"unixepoch\",\"localtime\"`\n",
    "\n",
    "(so, you'll need to adjust the date conversion expression if you're running a version of macOS below this).\n",
    "\n",
    "`datetime(message.date + strftime(\"%s\", \"2001-01-01\") ,\"unixepoch\",\"localtime\"`\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
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       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ROWID</th>\n",
       "      <th>text</th>\n",
       "      <th>date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>218</td>\n",
       "      <td>2degrees alert: Just a reminder that your bala...</td>\n",
       "      <td>2016-02-16 19:53:31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>219</td>\n",
       "      <td>2degrees alert: You don't have enough credit t...</td>\n",
       "      <td>2016-02-16 19:53:31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>220</td>\n",
       "      <td>How's Australia? Settling in?</td>\n",
       "      <td>2016-02-16 21:19:22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>296</td>\n",
       "      <td>2degrees alert: Just a reminder that your bala...</td>\n",
       "      <td>2016-02-18 18:59:56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>298</td>\n",
       "      <td>2degrees alert: You don't have enough credit t...</td>\n",
       "      <td>2016-02-18 18:59:56</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ROWID                                               text  \\\n",
       "0    218  2degrees alert: Just a reminder that your bala...   \n",
       "1    219  2degrees alert: You don't have enough credit t...   \n",
       "2    220                      How's Australia? Settling in?   \n",
       "3    296  2degrees alert: Just a reminder that your bala...   \n",
       "4    298  2degrees alert: You don't have enough credit t...   \n",
       "\n",
       "                  date  \n",
       "0  2016-02-16 19:53:31  \n",
       "1  2016-02-16 19:53:31  \n",
       "2  2016-02-16 21:19:22  \n",
       "3  2016-02-18 18:59:56  \n",
       "4  2016-02-18 18:59:56  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "conn = sqlite3.connect(chat_db, check_same_thread=False)\n",
    "query = '''\n",
    "        SELECT ROWID, text,\n",
    "        datetime(message.date/1000000000 + strftime(\"%s\", \"2001-01-01\") ,\"unixepoch\",\"localtime\") as date\n",
    "        FROM `message`;\n",
    "        '''\n",
    "df = pd.read_sql_query(query, conn)\n",
    "df[:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "That is a much more reasonable date to deal with!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# iMessage Stats\n",
    "\n",
    "Great! Now that we have our content, we should deep dive into it.\n",
    "\n",
    "DataFrames have a neat **describe** function which looks at the numerical data in your dataframe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
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       "        text-align: right;\n",
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       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ROWID</th>\n",
       "      <th>replace</th>\n",
       "      <th>handle_id</th>\n",
       "      <th>version</th>\n",
       "      <th>type</th>\n",
       "      <th>error</th>\n",
       "      <th>date</th>\n",
       "      <th>date_read</th>\n",
       "      <th>date_delivered</th>\n",
       "      <th>is_delivered</th>\n",
       "      <th>...</th>\n",
       "      <th>is_expirable</th>\n",
       "      <th>expire_state</th>\n",
       "      <th>message_action_type</th>\n",
       "      <th>message_source</th>\n",
       "      <th>associated_message_type</th>\n",
       "      <th>associated_message_range_location</th>\n",
       "      <th>associated_message_range_length</th>\n",
       "      <th>time_expressive_send_played</th>\n",
       "      <th>ck_sync_state</th>\n",
       "      <th>sr_ck_sync_state</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>15236.000000</td>\n",
       "      <td>15236.000000</td>\n",
       "      <td>15236.000000</td>\n",
       "      <td>15236.0</td>\n",
       "      <td>15236.000000</td>\n",
       "      <td>15236.000000</td>\n",
       "      <td>1.523600e+04</td>\n",
       "      <td>1.523600e+04</td>\n",
       "      <td>1.523600e+04</td>\n",
       "      <td>15236.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>15236.0</td>\n",
       "      <td>15236.000000</td>\n",
       "      <td>15236.0</td>\n",
       "      <td>15236.0</td>\n",
       "      <td>15236.000000</td>\n",
       "      <td>15236.000000</td>\n",
       "      <td>15236.000000</td>\n",
       "      <td>15236.0</td>\n",
       "      <td>15236.0</td>\n",
       "      <td>15236.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>14682.998884</td>\n",
       "      <td>0.000328</td>\n",
       "      <td>46.923865</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.019296</td>\n",
       "      <td>0.009911</td>\n",
       "      <td>5.257533e+17</td>\n",
       "      <td>2.271642e+16</td>\n",
       "      <td>4.708073e+16</td>\n",
       "      <td>0.968233</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.001181</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.444342</td>\n",
       "      <td>0.002166</td>\n",
       "      <td>0.028813</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>4482.125912</td>\n",
       "      <td>0.018113</td>\n",
       "      <td>14.681128</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.137569</td>\n",
       "      <td>0.393373</td>\n",
       "      <td>1.819170e+16</td>\n",
       "      <td>1.090301e+17</td>\n",
       "      <td>1.533933e+17</td>\n",
       "      <td>0.175385</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.059524</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>53.736171</td>\n",
       "      <td>0.267349</td>\n",
       "      <td>1.635798</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>218.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.773632e+17</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>10911.750000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.107401e+17</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>14720.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.255981e+17</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>18533.250000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.418992e+17</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>5.135253e+08</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>22346.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>144.000000</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>39.000000</td>\n",
       "      <td>5.561534e+17</td>\n",
       "      <td>5.561426e+17</td>\n",
       "      <td>5.561426e+17</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2001.000000</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>145.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 46 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              ROWID       replace     handle_id  version          type  \\\n",
       "count  15236.000000  15236.000000  15236.000000  15236.0  15236.000000   \n",
       "mean   14682.998884      0.000328     46.923865     10.0      0.019296   \n",
       "std     4482.125912      0.018113     14.681128      0.0      0.137569   \n",
       "min      218.000000      0.000000      0.000000     10.0      0.000000   \n",
       "25%    10911.750000      0.000000     41.000000     10.0      0.000000   \n",
       "50%    14720.500000      0.000000     47.000000     10.0      0.000000   \n",
       "75%    18533.250000      0.000000     47.000000     10.0      0.000000   \n",
       "max    22346.000000      1.000000    144.000000     10.0      1.000000   \n",
       "\n",
       "              error          date     date_read  date_delivered  is_delivered  \\\n",
       "count  15236.000000  1.523600e+04  1.523600e+04    1.523600e+04  15236.000000   \n",
       "mean       0.009911  5.257533e+17  2.271642e+16    4.708073e+16      0.968233   \n",
       "std        0.393373  1.819170e+16  1.090301e+17    1.533933e+17      0.175385   \n",
       "min        0.000000  4.773632e+17  0.000000e+00    0.000000e+00      0.000000   \n",
       "25%        0.000000  5.107401e+17  0.000000e+00    0.000000e+00      1.000000   \n",
       "50%        0.000000  5.255981e+17  0.000000e+00    0.000000e+00      1.000000   \n",
       "75%        0.000000  5.418992e+17  0.000000e+00    5.135253e+08      1.000000   \n",
       "max       39.000000  5.561534e+17  5.561426e+17    5.561426e+17      1.000000   \n",
       "\n",
       "             ...         is_expirable  expire_state  message_action_type  \\\n",
       "count        ...              15236.0  15236.000000              15236.0   \n",
       "mean         ...                  0.0      0.001181                  0.0   \n",
       "std          ...                  0.0      0.059524                  0.0   \n",
       "min          ...                  0.0      0.000000                  0.0   \n",
       "25%          ...                  0.0      0.000000                  0.0   \n",
       "50%          ...                  0.0      0.000000                  0.0   \n",
       "75%          ...                  0.0      0.000000                  0.0   \n",
       "max          ...                  0.0      3.000000                  0.0   \n",
       "\n",
       "       message_source  associated_message_type  \\\n",
       "count         15236.0             15236.000000   \n",
       "mean              0.0                 1.444342   \n",
       "std               0.0                53.736171   \n",
       "min               0.0                 0.000000   \n",
       "25%               0.0                 0.000000   \n",
       "50%               0.0                 0.000000   \n",
       "75%               0.0                 0.000000   \n",
       "max               0.0              2001.000000   \n",
       "\n",
       "       associated_message_range_location  associated_message_range_length  \\\n",
       "count                       15236.000000                     15236.000000   \n",
       "mean                            0.002166                         0.028813   \n",
       "std                             0.267349                         1.635798   \n",
       "min                             0.000000                         0.000000   \n",
       "25%                             0.000000                         0.000000   \n",
       "50%                             0.000000                         0.000000   \n",
       "75%                             0.000000                         0.000000   \n",
       "max                            33.000000                       145.000000   \n",
       "\n",
       "       time_expressive_send_played  ck_sync_state  sr_ck_sync_state  \n",
       "count                      15236.0        15236.0           15236.0  \n",
       "mean                           0.0            0.0               0.0  \n",
       "std                            0.0            0.0               0.0  \n",
       "min                            0.0            0.0               0.0  \n",
       "25%                            0.0            0.0               0.0  \n",
       "50%                            0.0            0.0               0.0  \n",
       "75%                            0.0            0.0               0.0  \n",
       "max                            0.0            0.0               0.0  \n",
       "\n",
       "[8 rows x 46 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "conn = sqlite3.connect(chat_db, check_same_thread=False)        \n",
    "query = '''\n",
    "        SELECT * \n",
    "        FROM `message`;\n",
    "        '''\n",
    "df = pd.read_sql_query(query, conn)\n",
    "\n",
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Number of Messages\n",
    "As of right now, how many messages do I have in total?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15236"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "conn = sqlite3.connect(chat_db, check_same_thread=False)        \n",
    "query = '''\n",
    "        SELECT count(ROWID) as count \n",
    "        FROM `message`;\n",
    "        '''\n",
    "df = pd.read_sql_query(query, conn)\n",
    "number_of_messages = df['count'][0]\n",
    "number_of_messages"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Message Breakdown\n",
    "\n",
    "How many of them are from me, and how many are from everyone else?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>from_me</th>\n",
       "      <th>from_others</th>\n",
       "      <th>total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7980</td>\n",
       "      <td>7256</td>\n",
       "      <td>15236</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   from_me  from_others  total\n",
       "0     7980         7256  15236"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "conn = sqlite3.connect(chat_db, check_same_thread=False)        \n",
    "\n",
    "query = '''\n",
    "        SELECT\n",
    "        sum(case when is_from_me = 1 then 1 else 0 end) as from_me,\n",
    "        sum(case when is_from_me = 0 then 1 else 0 end) as from_others,\n",
    "        count(ROWID) as total\n",
    "        FROM `message`\n",
    "        '''\n",
    "\n",
    "df = pd.read_sql_query(query, conn)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Average Number of Messages Exchanged Per Day\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>min_date</th>\n",
       "      <th>max_date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2016-02-16 19:53:31</td>\n",
       "      <td>2018-08-16 19:02:37</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              min_date             max_date\n",
       "0  2016-02-16 19:53:31  2018-08-16 19:02:37"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "conn = sqlite3.connect(chat_db, check_same_thread=False)\n",
    "date_time_conversion = 'datetime(message.date/1000000000 + strftime(\"%s\", \"2001-01-01\") ,\"unixepoch\",\"localtime\")'\n",
    "query = '''\n",
    "        SELECT min({}) as min_date, max({}) as max_date\n",
    "        FROM `message`;\n",
    "        '''.format(date_time_conversion, date_time_conversion)\n",
    "        \n",
    "df = pd.read_sql_query(query, conn)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I exchange 16.724 messages on average per day.\n"
     ]
    }
   ],
   "source": [
    "min_date_string = df['min_date'][0]\n",
    "min_date = datetime.strptime(min_date_string, \"%Y-%m-%d %H:%M:%S\")\n",
    "\n",
    "max_date_string = df['max_date'][0]\n",
    "max_date = datetime.strptime(max_date_string, \"%Y-%m-%d %H:%M:%S\")\n",
    "\n",
    "delta = (max_date - min_date).days\n",
    "\n",
    "average = number_of_messages / delta\n",
    "print('I exchange {:.3f} messages on average per day.'.format(average))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## How many did I actually exchange per day?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "conn = sqlite3.connect(chat_db, check_same_thread=False)\n",
    "query = '''\n",
    "        SELECT ROWID, text,\n",
    "        datetime(message.date/1000000000 + strftime(\"%s\", \"2001-01-01\"), \"unixepoch\",\"localtime\") as date\n",
    "        FROM `message`;\n",
    "        '''\n",
    "df = pd.read_sql_query(query, conn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
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MTI2BLmxuEbTQ3dlVjpsnHq1xcro+M9GqLXQoLA5WjVTWqlPDKSyeEg834Zg5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\njAxrWgqOhW4OgY6ZnyOip5RSf7r56u1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HNilK+cqGi31Fz7x6a1Ib5l6l3xPbWrZpa5zK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ARPAJy/trEtraH7mwDwRfb39wPAB5xzfwQAPjD9/VUFWftwBc4RkYafpdrk0nlCGBOL34s+dP5w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dZoME+tDpvWWJiX7gXZ+gp0ri+1PQBWv0WKBzCCFB+4UtFEcEj3LZapLsmtkrKd8IdKZMFhKs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RhHpnomVAzdVGnjccxs2oJAGJueFSOMW1ZjtVJ0Cpl2vsQQqiLlPc/GD7tswfxceBdEDBV1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\n2r/xDwKff2YAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114cca4e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['Dates'] = df['date'].apply(lambda x: x[:10])\n",
    "\n",
    "frequencies = df.groupby('Dates')['ROWID'].count()\n",
    "frequencies.plot(kind='line', figsize=(15, 10))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Who have I messaged the most? "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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57HLbJ7chhslU/+t/vJ/PDrd9a6tjKOfa1fYL/dTvA0y0vaodcfQ594eAw23/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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1163bc860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "conn = sqlite3.connect(chat_db, check_same_thread=False)\n",
    "query = '''\n",
    "        SELECT count(handle.ROWID) as total, handle.id, message.text \n",
    "        FROM `handle` JOIN `message` \n",
    "        ON handle.ROWID = message.handle_id \n",
    "        GROUP BY handle.id \n",
    "        ORDER BY total DESC \n",
    "        LIMIT 10;\n",
    "        '''\n",
    "df = pd.read_sql_query(query, conn)\n",
    "#my_plot = df.plot(kind='bar', x=df['id']) # display who they are\n",
    "\n",
    "my_plot = df.plot(kind='bar')\n",
    "my_plot.set_xlabel(\"Contacts\")\n",
    "my_plot.set_ylabel(\"Exchanged messages\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Using NLTK\n",
    "\n",
    "First, let's get every message that I've ever sent."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>text</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>All done, heading back now</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>What gate did you arrive at? I'm at arrivals B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Did you fly air nz?</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                             text\n",
       "0                     All done, heading back now \n",
       "1  What gate did you arrive at? I'm at arrivals B\n",
       "2                             Did you fly air nz?"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "conn = sqlite3.connect(chat_db, check_same_thread=False)        \n",
    "\n",
    "query = '''\n",
    "        SELECT\n",
    "        text\n",
    "        FROM `message`\n",
    "        WHERE is_from_me = 1\n",
    "        '''\n",
    "\n",
    "my_imessage_df = pd.read_sql_query(query, conn)\n",
    "my_imessage_df[:3]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Let's create an NLTK Text object that we can perform operations on.\n",
    "\n",
    "We tokenize every message we've sent, and combine them all together to make a novel."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Text: All done , heading back now What gate...>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# we need to account for empty messages\n",
    "messages = [msg for msg in my_imessage_df[\"text\"] if msg]\n",
    "\n",
    "msg_tokens = []\n",
    "for msg in messages:\n",
    "    new_set = nltk.word_tokenize(msg)\n",
    "    msg_tokens.extend(new_set)\n",
    "    \n",
    "msg_tokens\n",
    "\n",
    "text = nltk.Text(msg_tokens)\n",
    "text"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## How do I feel?\n",
    "\n",
    "Let's use **dispersion plots** to see how the mentioning of certain words are distributed over all the messages that I've sent."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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S8iOHqsaBmD690RXYcFHL91qzfJ82Sx05WqnWoTJkV0lJfIQiKF4HXgU+BxwMHAE8CtwD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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11a8aac18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "text.dispersion_plot([\n",
    "    \"hungry\", \"happy\", \"sad\", \"sleepy\", \"jealous\", \"angry\", \"gutted\"\n",
    "])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Looks like I'm much more happy than I am sad, and don't get angry very often. I thought I'd be sleepier though!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## What's my favourite meal to talk about?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x11a898fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "text.dispersion_plot([\n",
    "    \"breakfast\", \"brunch\", \"lunch\", \"dinner\", \"snack\", \"dessert\"\n",
    "])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Dinner! This is usually a correspondance between my partner and I each day trying to organise our evening meal."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Thanks!\n",
    "\n",
    "If you're like to use this for your own data, I'll be putting it up on Github soon :)\n",
    "\n",
    "Next steps: Sentiment Analysis!\n",
    "\n",
    "http://www.nltk.org/howto/sentiment.html\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "# References\n",
    "\n",
    "[1] https://en.wikipedia.org/wiki/Year_2038_problem"
   ]
  }
 ],
 "metadata": {
  "celltoolbar": "Slideshow",
  "kernelspec": {
   "display_name": "Python [default]",
   "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": "3.6.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}