{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 277,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.ticker import StrMethodFormatter\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from tabulate import tabulate\n",
    "from wmfdata import charting, hive\n",
    "from wmfdata.charting import comma_fmt, pct_fmt\n",
    "from wmfdata.utils import df_to_remarkup, pct_str"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "charting.set_mpl_style()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Reusable SQL chunks\n",
    "sql_chunks = {\n",
    "    \"is_experiment_participant\": \"\"\"\n",
    "    event.bucket in ('default-visual', 'default-source') and\n",
    "    year = 2019 and month = 7 and day < 10\n",
    "    \"\"\"\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Events by platform and registration status"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since 3 June, when we [fixed the problem](https://phabricator.wikimedia.org/T221197#5305239) that led to many invalid mobile events, the number of phone events has recovered *past* pre-bug levels to reach a higher level than before (because the A/B test resulted in some of these editors moving to the visual editor, where all rather than 1/16 of their sessions are sampled). \n",
    "\n",
    "**Verdict: all good!**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "events_r = hive.run(\"\"\"\n",
    "select\n",
    "    date_format(dt, \"yyyy-MM-dd\") as date,\n",
    "    sum(cast(event.platform = \"desktop\" and event.user_id != 0 as int)) as registered_desktop,\n",
    "    sum(cast(event.platform = \"desktop\" and event.user_id = 0 as int)) as anonymous_desktop,\n",
    "    sum(cast(event.platform = \"phone\" and event.user_id != 0 as int)) as registered_phone,\n",
    "    sum(cast(event.platform = \"phone\" and event.user_id = 0 as int)) as anonymous_phone\n",
    "from event.editattemptstep\n",
    "where\n",
    "    year = 2019 and (\n",
    "        (month = 6 and day > 17) or\n",
    "        (month = 7)\n",
    "    )\n",
    "group by date_format(dt, \"yyyy-MM-dd\")\n",
    "order by date\n",
    "limit 100\n",
    "\"\"\")"
   ]
  },
  {
   "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>date</th>\n",
       "      <th>registered desktop</th>\n",
       "      <th>anonymous desktop</th>\n",
       "      <th>registered phone</th>\n",
       "      <th>anonymous phone</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-06-18</td>\n",
       "      <td>103855</td>\n",
       "      <td>230523</td>\n",
       "      <td>35744</td>\n",
       "      <td>286838</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-06-19</td>\n",
       "      <td>104869</td>\n",
       "      <td>211305</td>\n",
       "      <td>32402</td>\n",
       "      <td>275964</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-06-20</td>\n",
       "      <td>105994</td>\n",
       "      <td>201908</td>\n",
       "      <td>36134</td>\n",
       "      <td>283812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-06-21</td>\n",
       "      <td>104346</td>\n",
       "      <td>194389</td>\n",
       "      <td>33829</td>\n",
       "      <td>282477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-06-22</td>\n",
       "      <td>97378</td>\n",
       "      <td>164189</td>\n",
       "      <td>39652</td>\n",
       "      <td>298071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2019-06-23</td>\n",
       "      <td>101349</td>\n",
       "      <td>172402</td>\n",
       "      <td>36825</td>\n",
       "      <td>330253</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2019-06-24</td>\n",
       "      <td>108487</td>\n",
       "      <td>234554</td>\n",
       "      <td>33555</td>\n",
       "      <td>299146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2019-06-25</td>\n",
       "      <td>111791</td>\n",
       "      <td>222482</td>\n",
       "      <td>26893</td>\n",
       "      <td>227859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2019-06-26</td>\n",
       "      <td>107107</td>\n",
       "      <td>232324</td>\n",
       "      <td>55</td>\n",
       "      <td>1410</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2019-06-27</td>\n",
       "      <td>101278</td>\n",
       "      <td>212925</td>\n",
       "      <td>11</td>\n",
       "      <td>480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2019-06-28</td>\n",
       "      <td>100611</td>\n",
       "      <td>211608</td>\n",
       "      <td>0</td>\n",
       "      <td>7600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2019-06-29</td>\n",
       "      <td>96483</td>\n",
       "      <td>179354</td>\n",
       "      <td>0</td>\n",
       "      <td>62548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2019-06-30</td>\n",
       "      <td>104681</td>\n",
       "      <td>189258</td>\n",
       "      <td>0</td>\n",
       "      <td>91495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2019-07-01</td>\n",
       "      <td>114615</td>\n",
       "      <td>227053</td>\n",
       "      <td>0</td>\n",
       "      <td>97624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2019-07-02</td>\n",
       "      <td>109774</td>\n",
       "      <td>227518</td>\n",
       "      <td>0</td>\n",
       "      <td>106471</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2019-07-03</td>\n",
       "      <td>108142</td>\n",
       "      <td>226114</td>\n",
       "      <td>1268</td>\n",
       "      <td>115234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2019-07-04</td>\n",
       "      <td>104736</td>\n",
       "      <td>216140</td>\n",
       "      <td>41472</td>\n",
       "      <td>379458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2019-07-05</td>\n",
       "      <td>107162</td>\n",
       "      <td>209073</td>\n",
       "      <td>39922</td>\n",
       "      <td>357049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2019-07-06</td>\n",
       "      <td>99635</td>\n",
       "      <td>176616</td>\n",
       "      <td>39666</td>\n",
       "      <td>382526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2019-07-07</td>\n",
       "      <td>110147</td>\n",
       "      <td>172083</td>\n",
       "      <td>48740</td>\n",
       "      <td>455994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2019-07-08</td>\n",
       "      <td>114360</td>\n",
       "      <td>223040</td>\n",
       "      <td>36422</td>\n",
       "      <td>389963</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         date  registered desktop  anonymous desktop  registered phone  \\\n",
       "0  2019-06-18              103855             230523             35744   \n",
       "1  2019-06-19              104869             211305             32402   \n",
       "2  2019-06-20              105994             201908             36134   \n",
       "3  2019-06-21              104346             194389             33829   \n",
       "4  2019-06-22               97378             164189             39652   \n",
       "5  2019-06-23              101349             172402             36825   \n",
       "6  2019-06-24              108487             234554             33555   \n",
       "7  2019-06-25              111791             222482             26893   \n",
       "8  2019-06-26              107107             232324                55   \n",
       "9  2019-06-27              101278             212925                11   \n",
       "10 2019-06-28              100611             211608                 0   \n",
       "11 2019-06-29               96483             179354                 0   \n",
       "12 2019-06-30              104681             189258                 0   \n",
       "13 2019-07-01              114615             227053                 0   \n",
       "14 2019-07-02              109774             227518                 0   \n",
       "15 2019-07-03              108142             226114              1268   \n",
       "16 2019-07-04              104736             216140             41472   \n",
       "17 2019-07-05              107162             209073             39922   \n",
       "18 2019-07-06               99635             176616             39666   \n",
       "19 2019-07-07              110147             172083             48740   \n",
       "20 2019-07-08              114360             223040             36422   \n",
       "\n",
       "    anonymous phone  \n",
       "0            286838  \n",
       "1            275964  \n",
       "2            283812  \n",
       "3            282477  \n",
       "4            298071  \n",
       "5            330253  \n",
       "6            299146  \n",
       "7            227859  \n",
       "8              1410  \n",
       "9               480  \n",
       "10             7600  \n",
       "11            62548  \n",
       "12            91495  \n",
       "13            97624  \n",
       "14           106471  \n",
       "15           115234  \n",
       "16           379458  \n",
       "17           357049  \n",
       "18           382526  \n",
       "19           455994  \n",
       "20           389963  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "events = (\n",
    "    events_r\n",
    "    .assign(date=lambda df: pd.to_datetime(df[\"date\"]))\n",
    "    .query(\"~(date == '2019-07-09')\")\n",
    "    .rename(lambda col: col.replace(\"_\", \" \"), axis=1)\n",
    ")\n",
    "\n",
    "events"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1008x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = events.set_index(\"date\").plot()\n",
    "plt.xlabel(None);\n",
    "ax.yaxis.set_major_formatter(comma_fmt)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Deployment on non-test wikis?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 333,
   "metadata": {},
   "outputs": [],
   "source": [
    "wrong_wiki_events_r = hive.run(\"\"\"\n",
    "select\n",
    "    date_format(dt, \"yyyy-MM-dd\") as date,\n",
    "    count(*) as wrong_wiki_events\n",
    "from event.editattemptstep\n",
    "where\n",
    "    event.platform = \"phone\" and\n",
    "    event.bucket in ('default-visual', 'default-source') and\n",
    "    wiki not in (\n",
    "        'azwiki', 'bgwiki', 'zh_yuewiki', 'cawiki', 'hrwiki',\n",
    "        'dawiki', 'etwiki', 'fiwiki', 'elwiki', 'huwiki',\n",
    "        'mswiki', 'mlwiki', 'nowiki', 'ptwiki', 'rowiki',\n",
    "        'srwiki', 'svwiki', 'tawiki', 'thwiki', 'urwiki'\n",
    "    ) and\n",
    "    year = 2019 and (\n",
    "        (month = 6 and day > 23) or\n",
    "        (month = 7) or (month = 8)\n",
    "    )\n",
    "group by date_format(dt, \"yyyy-MM-dd\")\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 332,
   "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>date</th>\n",
       "      <th>wrong_wiki_events</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [date, wrong_wiki_events]\n",
       "Index: []"
      ]
     },
     "execution_count": 332,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wrong_wiki_inits_r"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 335,
   "metadata": {},
   "outputs": [],
   "source": [
    "other_wiki_mobile_ve_events_r = hive.run(\"\"\"\n",
    "select\n",
    "    date_format(dt, \"yyyy-MM-dd\") as date,\n",
    "    count(*) as other_wiki_mobile_ve_events\n",
    "from event.editattemptstep\n",
    "where\n",
    "    event.platform = \"phone\" and\n",
    "    event.editor_interface = \"visualeditor\" and\n",
    "    wiki not in (\n",
    "        'azwiki', 'bgwiki', 'zh_yuewiki', 'cawiki', 'hrwiki',\n",
    "        'dawiki', 'etwiki', 'fiwiki', 'elwiki', 'huwiki',\n",
    "        'mswiki', 'mlwiki', 'nowiki', 'ptwiki', 'rowiki',\n",
    "        'srwiki', 'svwiki', 'tawiki', 'thwiki', 'urwiki'\n",
    "    ) and\n",
    "    year = 2019 and (\n",
    "        (month = 6 and day > 15) or\n",
    "        (month = 7) or (month = 8)\n",
    "    )\n",
    "group by date_format(dt, \"yyyy-MM-dd\")\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 340,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f9291fc1f60>"
      ]
     },
     "execution_count": 340,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1008x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "(\n",
    "    other_wiki_mobile_ve_events_r\n",
    "    .assign(date=lambda df: pd.to_datetime(df[\"date\"]))\n",
    "    .sort_values(\"date\")\n",
    "    .set_index(\"date\")\n",
    ").plot();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Inits per bucket in test population"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We are logging a reasonable amount of inits in each bucket among the expected experiment population (i.e. on the selected wikis and with fewer than 100 edits total). After data from registered edits returned, we started seeing a small number of users not bucketed, which makes sense since some users in the population will stay out of the buckets because they already had the sticky preference set.\n",
    "\n",
    "With oversampling, we see a lot more events in the visual editing bucket because only mobile VE data is oversampled. Without oversampling, the number of inits in each buckets in pretty close. However, the visual editing bucket consistently has only 90% of the inits of the source editing bucket.\n",
    "\n",
    "**Verdict: we should oversample mobile wikitext events at our test wikis and keep an eye on the imbalance in inits.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## With oversampling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 343,
   "metadata": {},
   "outputs": [],
   "source": [
    "oversampled_inits_r = hive.run(\"\"\"\n",
    "select\n",
    "    date_format(dt, \"yyyy-MM-dd\") as date,\n",
    "    event.bucket as bucket,\n",
    "    count(*) as events\n",
    "from event.editattemptstep\n",
    "where\n",
    "    event.platform = \"phone\" and\n",
    "    event.action = \"init\" and\n",
    "    event.user_editcount < 100 and\n",
    "    wiki in (\n",
    "        'azwiki', 'bgwiki', 'zh_yuewiki', 'cawiki', 'hrwiki',\n",
    "        'dawiki', 'etwiki', 'fiwiki', 'elwiki', 'huwiki',\n",
    "        'mswiki', 'mlwiki', 'nowiki', 'ptwiki', 'rowiki',\n",
    "        'srwiki', 'svwiki', 'tawiki', 'thwiki', 'urwiki'\n",
    "    ) and\n",
    "    year = 2019 and (\n",
    "        (month = 6 and day > 23) or\n",
    "        (month = 7) or (month = 8)\n",
    "    )\n",
    "group by date_format(dt, \"yyyy-MM-dd\"), event.bucket\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 347,
   "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>bucket</th>\n",
       "      <th>none</th>\n",
       "      <th>default-source</th>\n",
       "      <th>default-visual</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-06-24</th>\n",
       "      <td>6422</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-25</th>\n",
       "      <td>5107</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-26</th>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-27</th>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-28</th>\n",
       "      <td>2</td>\n",
       "      <td>220</td>\n",
       "      <td>2374</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-29</th>\n",
       "      <td>1</td>\n",
       "      <td>1785</td>\n",
       "      <td>20300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-30</th>\n",
       "      <td>1</td>\n",
       "      <td>2598</td>\n",
       "      <td>29779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-01</th>\n",
       "      <td>0</td>\n",
       "      <td>2788</td>\n",
       "      <td>32164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-02</th>\n",
       "      <td>0</td>\n",
       "      <td>2932</td>\n",
       "      <td>35256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-03</th>\n",
       "      <td>0</td>\n",
       "      <td>3034</td>\n",
       "      <td>35754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-04</th>\n",
       "      <td>18</td>\n",
       "      <td>3286</td>\n",
       "      <td>35548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-05</th>\n",
       "      <td>8</td>\n",
       "      <td>2862</td>\n",
       "      <td>31704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-06</th>\n",
       "      <td>1</td>\n",
       "      <td>2927</td>\n",
       "      <td>33671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-07</th>\n",
       "      <td>1</td>\n",
       "      <td>3773</td>\n",
       "      <td>41194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-08</th>\n",
       "      <td>0</td>\n",
       "      <td>3211</td>\n",
       "      <td>36495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-09</th>\n",
       "      <td>0</td>\n",
       "      <td>3239</td>\n",
       "      <td>36541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-10</th>\n",
       "      <td>0</td>\n",
       "      <td>3375</td>\n",
       "      <td>35601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-11</th>\n",
       "      <td>0</td>\n",
       "      <td>3806</td>\n",
       "      <td>33960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-12</th>\n",
       "      <td>0</td>\n",
       "      <td>36135</td>\n",
       "      <td>32979</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-13</th>\n",
       "      <td>0</td>\n",
       "      <td>38475</td>\n",
       "      <td>35003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-14</th>\n",
       "      <td>0</td>\n",
       "      <td>43589</td>\n",
       "      <td>41260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-15</th>\n",
       "      <td>0</td>\n",
       "      <td>38695</td>\n",
       "      <td>37274</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-16</th>\n",
       "      <td>0</td>\n",
       "      <td>40047</td>\n",
       "      <td>36951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-17</th>\n",
       "      <td>0</td>\n",
       "      <td>39637</td>\n",
       "      <td>37898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-18</th>\n",
       "      <td>0</td>\n",
       "      <td>39458</td>\n",
       "      <td>36419</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-19</th>\n",
       "      <td>0</td>\n",
       "      <td>37408</td>\n",
       "      <td>34295</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-20</th>\n",
       "      <td>0</td>\n",
       "      <td>38682</td>\n",
       "      <td>35783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-21</th>\n",
       "      <td>0</td>\n",
       "      <td>44171</td>\n",
       "      <td>41491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-22</th>\n",
       "      <td>0</td>\n",
       "      <td>41327</td>\n",
       "      <td>37781</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-23</th>\n",
       "      <td>0</td>\n",
       "      <td>40652</td>\n",
       "      <td>37746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-24</th>\n",
       "      <td>0</td>\n",
       "      <td>40577</td>\n",
       "      <td>37571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-25</th>\n",
       "      <td>0</td>\n",
       "      <td>38936</td>\n",
       "      <td>36948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-26</th>\n",
       "      <td>0</td>\n",
       "      <td>36375</td>\n",
       "      <td>34108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-27</th>\n",
       "      <td>0</td>\n",
       "      <td>38157</td>\n",
       "      <td>36710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-28</th>\n",
       "      <td>0</td>\n",
       "      <td>43843</td>\n",
       "      <td>41422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-29</th>\n",
       "      <td>0</td>\n",
       "      <td>40986</td>\n",
       "      <td>38838</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-30</th>\n",
       "      <td>0</td>\n",
       "      <td>41777</td>\n",
       "      <td>38796</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-31</th>\n",
       "      <td>0</td>\n",
       "      <td>40537</td>\n",
       "      <td>37992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-01</th>\n",
       "      <td>0</td>\n",
       "      <td>40235</td>\n",
       "      <td>36842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-02</th>\n",
       "      <td>0</td>\n",
       "      <td>37199</td>\n",
       "      <td>34757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-03</th>\n",
       "      <td>0</td>\n",
       "      <td>38876</td>\n",
       "      <td>36878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-04</th>\n",
       "      <td>0</td>\n",
       "      <td>44443</td>\n",
       "      <td>41661</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-05</th>\n",
       "      <td>0</td>\n",
       "      <td>41704</td>\n",
       "      <td>39635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-06</th>\n",
       "      <td>0</td>\n",
       "      <td>42364</td>\n",
       "      <td>39508</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "bucket      none  default-source  default-visual\n",
       "date                                            \n",
       "2019-06-24  6422               0               0\n",
       "2019-06-25  5107               0               0\n",
       "2019-06-26    23               0               0\n",
       "2019-06-27    10               0               0\n",
       "2019-06-28     2             220            2374\n",
       "2019-06-29     1            1785           20300\n",
       "2019-06-30     1            2598           29779\n",
       "2019-07-01     0            2788           32164\n",
       "2019-07-02     0            2932           35256\n",
       "2019-07-03     0            3034           35754\n",
       "2019-07-04    18            3286           35548\n",
       "2019-07-05     8            2862           31704\n",
       "2019-07-06     1            2927           33671\n",
       "2019-07-07     1            3773           41194\n",
       "2019-07-08     0            3211           36495\n",
       "2019-07-09     0            3239           36541\n",
       "2019-07-10     0            3375           35601\n",
       "2019-07-11     0            3806           33960\n",
       "2019-07-12     0           36135           32979\n",
       "2019-07-13     0           38475           35003\n",
       "2019-07-14     0           43589           41260\n",
       "2019-07-15     0           38695           37274\n",
       "2019-07-16     0           40047           36951\n",
       "2019-07-17     0           39637           37898\n",
       "2019-07-18     0           39458           36419\n",
       "2019-07-19     0           37408           34295\n",
       "2019-07-20     0           38682           35783\n",
       "2019-07-21     0           44171           41491\n",
       "2019-07-22     0           41327           37781\n",
       "2019-07-23     0           40652           37746\n",
       "2019-07-24     0           40577           37571\n",
       "2019-07-25     0           38936           36948\n",
       "2019-07-26     0           36375           34108\n",
       "2019-07-27     0           38157           36710\n",
       "2019-07-28     0           43843           41422\n",
       "2019-07-29     0           40986           38838\n",
       "2019-07-30     0           41777           38796\n",
       "2019-07-31     0           40537           37992\n",
       "2019-08-01     0           40235           36842\n",
       "2019-08-02     0           37199           34757\n",
       "2019-08-03     0           38876           36878\n",
       "2019-08-04     0           44443           41661\n",
       "2019-08-05     0           41704           39635\n",
       "2019-08-06     0           42364           39508"
      ]
     },
     "execution_count": 347,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "oversampled_inits = (\n",
    "    oversampled_inits_r\n",
    "    .pivot(index=\"date\", columns=\"bucket\")\n",
    "    .fillna(0)\n",
    "    .xs(\"events\", axis=1)\n",
    "    .applymap(int)\n",
    "    .rename({np.NaN: \"none\"}, axis=1)\n",
    "    .query(\"~(date == '2019-08-07')\")\n",
    ")\n",
    "\n",
    "oversampled_inits"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Overall ratio of visual bucket inits to source bucket inits:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 351,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "94.1%\n"
     ]
    }
   ],
   "source": [
    "comparable_inits = inits.query(\"date > '2019-07-13'\")\n",
    "\n",
    "print(pct_str(\n",
    "    comparable_inits[\"default-visual\"].sum() / comparable_inits[\"default-source\"].sum()\n",
    "))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Without oversampling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 345,
   "metadata": {},
   "outputs": [],
   "source": [
    "inits_r = hive.run(\"\"\"\n",
    "select\n",
    "    date_format(dt, \"yyyy-MM-dd\") as date,\n",
    "    event.bucket as bucket,\n",
    "    count(*) as init\n",
    "from event.editattemptstep\n",
    "where\n",
    "    event.platform = \"phone\" and\n",
    "    event.action = \"init\" and\n",
    "    event.user_editcount < 100 and\n",
    "    not event.is_oversample and\n",
    "    wiki in (\n",
    "        'azwiki', 'bgwiki', 'zh_yuewiki', 'cawiki', 'hrwiki',\n",
    "        'dawiki', 'etwiki', 'fiwiki', 'elwiki', 'huwiki',\n",
    "        'mswiki', 'mlwiki', 'nowiki', 'ptwiki', 'rowiki',\n",
    "        'srwiki', 'svwiki', 'tawiki', 'thwiki', 'urwiki'\n",
    "    ) and\n",
    "    year = 2019 and (\n",
    "        (month = 6 and day > 23) or\n",
    "        (month = 7)\n",
    "    )\n",
    "group by date_format(dt, \"yyyy-MM-dd\"), event.bucket\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 349,
   "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>bucket</th>\n",
       "      <th>none</th>\n",
       "      <th>default-source</th>\n",
       "      <th>default-visual</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-06-24</th>\n",
       "      <td>5252</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-25</th>\n",
       "      <td>4111</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-26</th>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-27</th>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-28</th>\n",
       "      <td>2</td>\n",
       "      <td>167</td>\n",
       "      <td>152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-29</th>\n",
       "      <td>0</td>\n",
       "      <td>1431</td>\n",
       "      <td>1309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-30</th>\n",
       "      <td>1</td>\n",
       "      <td>2134</td>\n",
       "      <td>1858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-01</th>\n",
       "      <td>0</td>\n",
       "      <td>2303</td>\n",
       "      <td>2132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-02</th>\n",
       "      <td>0</td>\n",
       "      <td>2489</td>\n",
       "      <td>2200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-03</th>\n",
       "      <td>0</td>\n",
       "      <td>2527</td>\n",
       "      <td>2259</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-04</th>\n",
       "      <td>18</td>\n",
       "      <td>2578</td>\n",
       "      <td>2233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-05</th>\n",
       "      <td>7</td>\n",
       "      <td>2256</td>\n",
       "      <td>2105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-06</th>\n",
       "      <td>1</td>\n",
       "      <td>2316</td>\n",
       "      <td>2152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-07</th>\n",
       "      <td>1</td>\n",
       "      <td>2937</td>\n",
       "      <td>2636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-08</th>\n",
       "      <td>0</td>\n",
       "      <td>2596</td>\n",
       "      <td>2386</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-09</th>\n",
       "      <td>0</td>\n",
       "      <td>2539</td>\n",
       "      <td>2254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-10</th>\n",
       "      <td>0</td>\n",
       "      <td>2573</td>\n",
       "      <td>2237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-11</th>\n",
       "      <td>0</td>\n",
       "      <td>2384</td>\n",
       "      <td>2211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-12</th>\n",
       "      <td>0</td>\n",
       "      <td>2340</td>\n",
       "      <td>2051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-13</th>\n",
       "      <td>0</td>\n",
       "      <td>2456</td>\n",
       "      <td>2122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-14</th>\n",
       "      <td>0</td>\n",
       "      <td>2807</td>\n",
       "      <td>2567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-15</th>\n",
       "      <td>0</td>\n",
       "      <td>2392</td>\n",
       "      <td>2377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-16</th>\n",
       "      <td>0</td>\n",
       "      <td>2509</td>\n",
       "      <td>2357</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-17</th>\n",
       "      <td>0</td>\n",
       "      <td>2395</td>\n",
       "      <td>2450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-18</th>\n",
       "      <td>0</td>\n",
       "      <td>2478</td>\n",
       "      <td>2212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-19</th>\n",
       "      <td>0</td>\n",
       "      <td>2374</td>\n",
       "      <td>2178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-20</th>\n",
       "      <td>0</td>\n",
       "      <td>2452</td>\n",
       "      <td>2267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-21</th>\n",
       "      <td>0</td>\n",
       "      <td>2770</td>\n",
       "      <td>2649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-22</th>\n",
       "      <td>0</td>\n",
       "      <td>2552</td>\n",
       "      <td>2406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-23</th>\n",
       "      <td>0</td>\n",
       "      <td>2536</td>\n",
       "      <td>2341</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-24</th>\n",
       "      <td>0</td>\n",
       "      <td>2545</td>\n",
       "      <td>2343</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-25</th>\n",
       "      <td>0</td>\n",
       "      <td>2472</td>\n",
       "      <td>2364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-26</th>\n",
       "      <td>0</td>\n",
       "      <td>2238</td>\n",
       "      <td>2156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-27</th>\n",
       "      <td>0</td>\n",
       "      <td>2410</td>\n",
       "      <td>2240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-28</th>\n",
       "      <td>0</td>\n",
       "      <td>2783</td>\n",
       "      <td>2660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-29</th>\n",
       "      <td>0</td>\n",
       "      <td>2507</td>\n",
       "      <td>2442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-30</th>\n",
       "      <td>0</td>\n",
       "      <td>2618</td>\n",
       "      <td>2421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-31</th>\n",
       "      <td>0</td>\n",
       "      <td>2533</td>\n",
       "      <td>2254</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "bucket      none  default-source  default-visual\n",
       "date                                            \n",
       "2019-06-24  5252               0               0\n",
       "2019-06-25  4111               0               0\n",
       "2019-06-26    21               0               0\n",
       "2019-06-27     6               0               0\n",
       "2019-06-28     2             167             152\n",
       "2019-06-29     0            1431            1309\n",
       "2019-06-30     1            2134            1858\n",
       "2019-07-01     0            2303            2132\n",
       "2019-07-02     0            2489            2200\n",
       "2019-07-03     0            2527            2259\n",
       "2019-07-04    18            2578            2233\n",
       "2019-07-05     7            2256            2105\n",
       "2019-07-06     1            2316            2152\n",
       "2019-07-07     1            2937            2636\n",
       "2019-07-08     0            2596            2386\n",
       "2019-07-09     0            2539            2254\n",
       "2019-07-10     0            2573            2237\n",
       "2019-07-11     0            2384            2211\n",
       "2019-07-12     0            2340            2051\n",
       "2019-07-13     0            2456            2122\n",
       "2019-07-14     0            2807            2567\n",
       "2019-07-15     0            2392            2377\n",
       "2019-07-16     0            2509            2357\n",
       "2019-07-17     0            2395            2450\n",
       "2019-07-18     0            2478            2212\n",
       "2019-07-19     0            2374            2178\n",
       "2019-07-20     0            2452            2267\n",
       "2019-07-21     0            2770            2649\n",
       "2019-07-22     0            2552            2406\n",
       "2019-07-23     0            2536            2341\n",
       "2019-07-24     0            2545            2343\n",
       "2019-07-25     0            2472            2364\n",
       "2019-07-26     0            2238            2156\n",
       "2019-07-27     0            2410            2240\n",
       "2019-07-28     0            2783            2660\n",
       "2019-07-29     0            2507            2442\n",
       "2019-07-30     0            2618            2421\n",
       "2019-07-31     0            2533            2254"
      ]
     },
     "execution_count": 349,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "inits = (\n",
    "    inits_r\n",
    "    .pivot(index=\"date\", columns=\"bucket\")\n",
    "    .fillna(0)\n",
    "    .xs(\"init\", axis=1)\n",
    "    .applymap(int)\n",
    "    .rename({np.NaN: \"none\"}, axis=1)\n",
    "    .query(\"~(date == '2019-08-07')\")\n",
    ")\n",
    "\n",
    "inits"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Inits per bucket among experienced editors at test wikis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Editors at test wikis with 100 edits or more should not be bucketed. Since the fix on 3 June, this seems to be happening (if the numbers seem low, consider that it's a small number of wikis and that these users are probably using wikitext, which is 1/16 sampled).\n",
    "\n",
    "The few inits from our experimental buckets make sense, since rarely editors might actually move into this edit count range after being bucketed.\n",
    "\n",
    "**Verdict: all good!**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "buckets_experienced_r = hive.run(\"\"\"\n",
    "select\n",
    "    date_format(dt, \"yyyy-MM-dd\") as date,\n",
    "    event.bucket as bucket,\n",
    "    count(*) as events\n",
    "from event.editattemptstep\n",
    "where\n",
    "    event.platform = \"phone\" and\n",
    "    event.action = \"init\" and\n",
    "    event.user_editcount >= 100 and\n",
    "    wiki in (\n",
    "        'azwiki', 'bgwiki', 'zh_yuewiki', 'cawiki', 'hrwiki',\n",
    "        'dawiki', 'etwiki', 'fiwiki', 'elwiki', 'huwiki',\n",
    "        'mswiki', 'mlwiki', 'nowiki', 'ptwiki', 'rowiki',\n",
    "        'srwiki', 'svwiki', 'tawiki', 'thwiki', 'urwiki'\n",
    "    ) and\n",
    "    year = 2019 and (\n",
    "        (month = 6 and day > 23) or\n",
    "        (month = 7)\n",
    "    )\n",
    "group by date_format(dt, \"yyyy-MM-dd\"), event.bucket\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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>date</th>\n",
       "      <th>default-source</th>\n",
       "      <th>default-visual</th>\n",
       "      <th>no bucket</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-06-26</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-06-27</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-06-28</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-06-29</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-06-30</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2019-07-01</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2019-07-02</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2019-07-03</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2019-07-04</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2019-07-05</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2019-07-06</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2019-07-07</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         date  default-source  default-visual  no bucket\n",
       "0  2019-06-26               0               0          1\n",
       "1  2019-06-27               0               0          0\n",
       "2  2019-06-28               0               0          0\n",
       "3  2019-06-29               0               0          0\n",
       "4  2019-06-30               0               0          0\n",
       "5  2019-07-01               0               0          0\n",
       "6  2019-07-02               0               0          0\n",
       "7  2019-07-03               0               0          5\n",
       "8  2019-07-04               1               0        153\n",
       "9  2019-07-05               0               0        135\n",
       "10 2019-07-06               0               0        182\n",
       "11 2019-07-07               0               2        200"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "index_without_gaps = pd.date_range(\n",
    "    buckets_experienced_r[\"date\"].iloc[0], \n",
    "    buckets_experienced_r[\"date\"].iloc[-1],\n",
    "    name=\"date\"\n",
    ")\n",
    "\n",
    "buckets_experienced= (\n",
    "    buckets_experienced_r\n",
    "    .assign(\n",
    "        date=lambda df: pd.to_datetime(df[\"date\"]),\n",
    "        bucket=lambda df: df[\"bucket\"].fillna(\"none\")\n",
    "    )\n",
    "    .pivot(index=\"date\", columns=\"bucket\")\n",
    "    .xs(\"events\", axis=1)\n",
    "    .fillna(0)\n",
    "    .applymap(int)\n",
    "    .rename(columns={\"none\": \"no bucket\"})\n",
    "    .rename_axis(None, axis=1)\n",
    "    .reindex(index_without_gaps, fill_value=0)\n",
    "    .reset_index()\n",
    ")\n",
    "\n",
    "buckets_experienced"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Readies per bucket"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In our test population, without oversampling, the `default-visual` bucket is seeing far fewer readies—only about 60% as many."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "readies_r = hive.run(\"\"\"\n",
    "select\n",
    "    date_format(dt, \"yyyy-MM-dd\") as date,\n",
    "    event.bucket as bucket,\n",
    "    count(*) as readies\n",
    "from event.editattemptstep\n",
    "where\n",
    "    event.action = \"ready\" and\n",
    "    not event.is_oversample and\n",
    "    event.bucket in ('default-visual', 'default-source') and\n",
    "    year = 2019 and (\n",
    "        (month = 6 and day > 20) or\n",
    "        (month = 7 and day < 9)\n",
    "    )\n",
    "group by date_format(dt, \"yyyy-MM-dd\"), event.bucket\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "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>bucket</th>\n",
       "      <th>default-source</th>\n",
       "      <th>default-visual</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-06-28</th>\n",
       "      <td>165</td>\n",
       "      <td>117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-29</th>\n",
       "      <td>1425</td>\n",
       "      <td>894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-30</th>\n",
       "      <td>2128</td>\n",
       "      <td>1192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-01</th>\n",
       "      <td>2292</td>\n",
       "      <td>1395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-02</th>\n",
       "      <td>2477</td>\n",
       "      <td>1387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-03</th>\n",
       "      <td>2512</td>\n",
       "      <td>1429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-04</th>\n",
       "      <td>2565</td>\n",
       "      <td>1464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-05</th>\n",
       "      <td>2243</td>\n",
       "      <td>1402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-06</th>\n",
       "      <td>2308</td>\n",
       "      <td>1419</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-07</th>\n",
       "      <td>2922</td>\n",
       "      <td>1754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-08</th>\n",
       "      <td>2584</td>\n",
       "      <td>1537</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "bucket      default-source  default-visual\n",
       "date                                      \n",
       "2019-06-28             165             117\n",
       "2019-06-29            1425             894\n",
       "2019-06-30            2128            1192\n",
       "2019-07-01            2292            1395\n",
       "2019-07-02            2477            1387\n",
       "2019-07-03            2512            1429\n",
       "2019-07-04            2565            1464\n",
       "2019-07-05            2243            1402\n",
       "2019-07-06            2308            1419\n",
       "2019-07-07            2922            1754\n",
       "2019-07-08            2584            1537"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "readies = (\n",
    "    readies_r\n",
    "    .pivot(index=\"date\", columns=\"bucket\")\n",
    "    .fillna(0)\n",
    "    .xs(\"readies\", axis=1)\n",
    "    .applymap(int)\n",
    ")\n",
    "\n",
    "readies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ratio of visual bucket readies to source bucket readies: 59.2%\n"
     ]
    }
   ],
   "source": [
    "print(\n",
    "    \"Ratio of visual bucket readies to source bucket readies:\",\n",
    "    pct_str(\n",
    "        readies[\"default-visual\"].sum() / readies[\"default-source\"].sum()\n",
    "    )\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Ready rate"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ...in test population"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6\" ><thead>    <tr>        <th class=\"index_name level0\" >bucket</th>        <th class=\"col_heading level0 col0\" >default-source</th>        <th class=\"col_heading level0 col1\" >default-visual</th>    </tr>    <tr>        <th class=\"index_name level0\" >date</th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6level0_row0\" class=\"row_heading level0 row0\" >2019-06-28</th>\n",
       "                        <td id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6row0_col0\" class=\"data row0 col0\" >98.8%</td>\n",
       "                        <td id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6row0_col1\" class=\"data row0 col1\" >77.0%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6level0_row1\" class=\"row_heading level0 row1\" >2019-06-29</th>\n",
       "                        <td id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6row1_col0\" class=\"data row1 col0\" >99.6%</td>\n",
       "                        <td id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6row1_col1\" class=\"data row1 col1\" >68.3%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6level0_row2\" class=\"row_heading level0 row2\" >2019-06-30</th>\n",
       "                        <td id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6row2_col0\" class=\"data row2 col0\" >99.7%</td>\n",
       "                        <td id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6row2_col1\" class=\"data row2 col1\" >64.2%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6level0_row3\" class=\"row_heading level0 row3\" >2019-07-01</th>\n",
       "                        <td id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6row3_col0\" class=\"data row3 col0\" >99.5%</td>\n",
       "                        <td id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6row3_col1\" class=\"data row3 col1\" >65.4%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6level0_row4\" class=\"row_heading level0 row4\" >2019-07-02</th>\n",
       "                        <td id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6row4_col0\" class=\"data row4 col0\" >99.5%</td>\n",
       "                        <td id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6row4_col1\" class=\"data row4 col1\" >63.0%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6level0_row5\" class=\"row_heading level0 row5\" >2019-07-03</th>\n",
       "                        <td id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6row5_col0\" class=\"data row5 col0\" >99.4%</td>\n",
       "                        <td id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6row5_col1\" class=\"data row5 col1\" >63.3%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6level0_row6\" class=\"row_heading level0 row6\" >2019-07-04</th>\n",
       "                        <td id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6row6_col0\" class=\"data row6 col0\" >99.5%</td>\n",
       "                        <td id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6row6_col1\" class=\"data row6 col1\" >65.6%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6level0_row7\" class=\"row_heading level0 row7\" >2019-07-05</th>\n",
       "                        <td id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6row7_col0\" class=\"data row7 col0\" >99.4%</td>\n",
       "                        <td id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6row7_col1\" class=\"data row7 col1\" >66.6%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6level0_row8\" class=\"row_heading level0 row8\" >2019-07-06</th>\n",
       "                        <td id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6row8_col0\" class=\"data row8 col0\" >99.7%</td>\n",
       "                        <td id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6row8_col1\" class=\"data row8 col1\" >65.9%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6level0_row9\" class=\"row_heading level0 row9\" >2019-07-07</th>\n",
       "                        <td id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6row9_col0\" class=\"data row9 col0\" >99.5%</td>\n",
       "                        <td id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6row9_col1\" class=\"data row9 col1\" >66.5%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6level0_row10\" class=\"row_heading level0 row10\" >2019-07-08</th>\n",
       "                        <td id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6row10_col0\" class=\"data row10 col0\" >99.5%</td>\n",
       "                        <td id=\"T_1fdeaa3c_a288_11e9_89aa_d094661b49a6row10_col1\" class=\"data row10 col1\" >64.4%</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f929818a0f0>"
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ready_rate = (readies / inits.drop(\"none\", axis=1).query(\"date >= '2019-06-28'\"))\n",
    "ready_rate.style.format(pct_str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "| date | default-source | default-visual\n",
      "| ----- | ----- | ----- \n",
      "| 2019-06-28 | 98.8% | 77.0%\n",
      "| 2019-06-29 | 99.6% | 68.3%\n",
      "| 2019-06-30 | 99.7% | 64.2%\n",
      "| 2019-07-01 | 99.5% | 65.4%\n",
      "| 2019-07-02 | 99.5% | 63.0%\n",
      "| 2019-07-03 | 99.4% | 63.3%\n",
      "| 2019-07-04 | 99.5% | 65.6%\n",
      "| 2019-07-05 | 99.4% | 66.6%\n",
      "| 2019-07-06 | 99.7% | 65.9%\n",
      "| 2019-07-07 | 99.5% | 66.5%\n",
      "| 2019-07-08 | 99.5% | 64.4%\n",
      "\n"
     ]
    }
   ],
   "source": [
    "ready_rate.applymap(pct_str).reset_index().pipe(df_to_remarkup)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ...globally"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [],
   "source": [
    "global_ready_rate_r = hive.run(\"\"\"\n",
    "with attempts as (\n",
    "    select\n",
    "        date_format(min(dt), \"yyyy-MM-dd\") as date,\n",
    "        event.editor_interface as editor,\n",
    "        sum(cast(event.action = \"ready\" as int)) >= 1 as ready\n",
    "    from event_sanitized.editattemptstep\n",
    "    where\n",
    "        event.action in (\"init\", \"ready\") and\n",
    "        event.platform = \"phone\" and\n",
    "        year > 0\n",
    "    group by event.editor_interface, event.editing_session_id\n",
    ")\n",
    "select\n",
    "    date,\n",
    "    editor,\n",
    "    sum(cast(ready as int)) / count(*) as ready_rate\n",
    "from attempts\n",
    "group by date, editor\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the earliest data in this stream, the visual editor ready rate is around 99%, but it has now dropped to around 65%."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_980bd2cc_a31a_11e9_89aa_d094661b49a6\" ><thead>    <tr>        <th class=\"index_name level0\" >editor</th>        <th class=\"col_heading level0 col0\" >wikitext</th>        <th class=\"col_heading level0 col1\" >visualeditor</th>    </tr>    <tr>        <th class=\"index_name level0\" >date</th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_980bd2cc_a31a_11e9_89aa_d094661b49a6level0_row0\" class=\"row_heading level0 row0\" >2018-11-27</th>\n",
       "                        <td id=\"T_980bd2cc_a31a_11e9_89aa_d094661b49a6row0_col0\" class=\"data row0 col0\" >100.0%</td>\n",
       "                        <td id=\"T_980bd2cc_a31a_11e9_89aa_d094661b49a6row0_col1\" class=\"data row0 col1\" >100.0%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_980bd2cc_a31a_11e9_89aa_d094661b49a6level0_row1\" class=\"row_heading level0 row1\" >2018-11-28</th>\n",
       "                        <td id=\"T_980bd2cc_a31a_11e9_89aa_d094661b49a6row1_col0\" class=\"data row1 col0\" >100.0%</td>\n",
       "                        <td id=\"T_980bd2cc_a31a_11e9_89aa_d094661b49a6row1_col1\" class=\"data row1 col1\" >99.9%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_980bd2cc_a31a_11e9_89aa_d094661b49a6level0_row2\" class=\"row_heading level0 row2\" >2018-11-29</th>\n",
       "                        <td id=\"T_980bd2cc_a31a_11e9_89aa_d094661b49a6row2_col0\" class=\"data row2 col0\" >100.0%</td>\n",
       "                        <td id=\"T_980bd2cc_a31a_11e9_89aa_d094661b49a6row2_col1\" class=\"data row2 col1\" >99.8%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_980bd2cc_a31a_11e9_89aa_d094661b49a6level0_row3\" class=\"row_heading level0 row3\" >2018-11-30</th>\n",
       "                        <td id=\"T_980bd2cc_a31a_11e9_89aa_d094661b49a6row3_col0\" class=\"data row3 col0\" >99.9%</td>\n",
       "                        <td id=\"T_980bd2cc_a31a_11e9_89aa_d094661b49a6row3_col1\" class=\"data row3 col1\" >99.6%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_980bd2cc_a31a_11e9_89aa_d094661b49a6level0_row4\" class=\"row_heading level0 row4\" >2018-12-01</th>\n",
       "                        <td id=\"T_980bd2cc_a31a_11e9_89aa_d094661b49a6row4_col0\" class=\"data row4 col0\" >99.9%</td>\n",
       "                        <td id=\"T_980bd2cc_a31a_11e9_89aa_d094661b49a6row4_col1\" class=\"data row4 col1\" >99.8%</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f929810e5f8>"
      ]
     },
     "execution_count": 168,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "global_ready_rate = (\n",
    "    global_ready_rate_r\n",
    "    .assign(date=lambda df: pd.to_datetime(df[\"date\"]).dt.to_period(freq=\"D\"))\n",
    "    .pivot(index=\"date\", columns=\"editor\")\n",
    "    .xs(\"ready_rate\", axis=1)\n",
    "    .reindex([\"wikitext\", \"visualeditor\"], axis=1)\n",
    ")\n",
    "\n",
    "global_ready_rate.head().style.format(pct_str)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The first drop happed from 1 May to 3 May 2019; this is essentially the deployment schedule of [MediaWiki 1.34/wmf.3](https://www.mediawiki.org/wiki/MediaWiki_1.34/wmf.3), which included a patch [fixing incorrectly low `ready` timings](https://phabricator.wikimedia.org/T217825)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6\" ><thead>    <tr>        <th class=\"index_name level0\" >editor</th>        <th class=\"col_heading level0 col0\" >wikitext</th>        <th class=\"col_heading level0 col1\" >visualeditor</th>    </tr>    <tr>        <th class=\"index_name level0\" >date</th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6level0_row0\" class=\"row_heading level0 row0\" >2019-04-27</th>\n",
       "                        <td id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6row0_col0\" class=\"data row0 col0\" >99.8%</td>\n",
       "                        <td id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6row0_col1\" class=\"data row0 col1\" >98.4%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6level0_row1\" class=\"row_heading level0 row1\" >2019-04-28</th>\n",
       "                        <td id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6row1_col0\" class=\"data row1 col0\" >99.8%</td>\n",
       "                        <td id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6row1_col1\" class=\"data row1 col1\" >98.6%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6level0_row2\" class=\"row_heading level0 row2\" >2019-04-29</th>\n",
       "                        <td id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6row2_col0\" class=\"data row2 col0\" >99.8%</td>\n",
       "                        <td id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6row2_col1\" class=\"data row2 col1\" >98.4%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6level0_row3\" class=\"row_heading level0 row3\" >2019-04-30</th>\n",
       "                        <td id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6row3_col0\" class=\"data row3 col0\" >99.9%</td>\n",
       "                        <td id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6row3_col1\" class=\"data row3 col1\" >98.7%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6level0_row4\" class=\"row_heading level0 row4\" >2019-05-01</th>\n",
       "                        <td id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6row4_col0\" class=\"data row4 col0\" >99.8%</td>\n",
       "                        <td id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6row4_col1\" class=\"data row4 col1\" >98.7%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6level0_row5\" class=\"row_heading level0 row5\" >2019-05-02</th>\n",
       "                        <td id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6row5_col0\" class=\"data row5 col0\" >99.8%</td>\n",
       "                        <td id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6row5_col1\" class=\"data row5 col1\" >95.3%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6level0_row6\" class=\"row_heading level0 row6\" >2019-05-03</th>\n",
       "                        <td id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6row6_col0\" class=\"data row6 col0\" >99.8%</td>\n",
       "                        <td id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6row6_col1\" class=\"data row6 col1\" >84.4%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6level0_row7\" class=\"row_heading level0 row7\" >2019-05-04</th>\n",
       "                        <td id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6row7_col0\" class=\"data row7 col0\" >99.8%</td>\n",
       "                        <td id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6row7_col1\" class=\"data row7 col1\" >84.0%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6level0_row8\" class=\"row_heading level0 row8\" >2019-05-05</th>\n",
       "                        <td id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6row8_col0\" class=\"data row8 col0\" >99.8%</td>\n",
       "                        <td id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6row8_col1\" class=\"data row8 col1\" >83.7%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6level0_row9\" class=\"row_heading level0 row9\" >2019-05-06</th>\n",
       "                        <td id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6row9_col0\" class=\"data row9 col0\" >99.9%</td>\n",
       "                        <td id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6row9_col1\" class=\"data row9 col1\" >83.5%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6level0_row10\" class=\"row_heading level0 row10\" >2019-05-07</th>\n",
       "                        <td id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6row10_col0\" class=\"data row10 col0\" >99.8%</td>\n",
       "                        <td id=\"T_ea7c9f54_a31b_11e9_89aa_d094661b49a6row10_col1\" class=\"data row10 col1\" >84.1%</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f9293dd9240>"
      ]
     },
     "execution_count": 188,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "global_ready_rate[\"2019-04-27\":\"2019-05-07\"].style.format(pct_str)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The second drop happened during the process of deploying the A/B test (so it almost certainly had to do with an influx of less-experienced users to VE rather than a regression in the software)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6\" ><thead>    <tr>        <th class=\"index_name level0\" >editor</th>        <th class=\"col_heading level0 col0\" >wikitext</th>        <th class=\"col_heading level0 col1\" >visualeditor</th>    </tr>    <tr>        <th class=\"index_name level0\" >date</th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6level0_row0\" class=\"row_heading level0 row0\" >2019-06-21</th>\n",
       "                        <td id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6row0_col0\" class=\"data row0 col0\" >99.8%</td>\n",
       "                        <td id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6row0_col1\" class=\"data row0 col1\" >83.4%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6level0_row1\" class=\"row_heading level0 row1\" >2019-06-22</th>\n",
       "                        <td id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6row1_col0\" class=\"data row1 col0\" >99.9%</td>\n",
       "                        <td id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6row1_col1\" class=\"data row1 col1\" >84.1%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6level0_row2\" class=\"row_heading level0 row2\" >2019-06-23</th>\n",
       "                        <td id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6row2_col0\" class=\"data row2 col0\" >99.9%</td>\n",
       "                        <td id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6row2_col1\" class=\"data row2 col1\" >82.9%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6level0_row3\" class=\"row_heading level0 row3\" >2019-06-24</th>\n",
       "                        <td id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6row3_col0\" class=\"data row3 col0\" >99.8%</td>\n",
       "                        <td id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6row3_col1\" class=\"data row3 col1\" >83.4%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6level0_row4\" class=\"row_heading level0 row4\" >2019-06-25</th>\n",
       "                        <td id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6row4_col0\" class=\"data row4 col0\" >99.9%</td>\n",
       "                        <td id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6row4_col1\" class=\"data row4 col1\" >83.5%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6level0_row5\" class=\"row_heading level0 row5\" >2019-06-26</th>\n",
       "                        <td id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6row5_col0\" class=\"data row5 col0\" >100.0%</td>\n",
       "                        <td id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6row5_col1\" class=\"data row5 col1\" >80.8%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6level0_row6\" class=\"row_heading level0 row6\" >2019-06-27</th>\n",
       "                        <td id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6row6_col0\" class=\"data row6 col0\" >100.0%</td>\n",
       "                        <td id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6row6_col1\" class=\"data row6 col1\" >80.6%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6level0_row7\" class=\"row_heading level0 row7\" >2019-06-28</th>\n",
       "                        <td id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6row7_col0\" class=\"data row7 col0\" >100.0%</td>\n",
       "                        <td id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6row7_col1\" class=\"data row7 col1\" >71.6%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6level0_row8\" class=\"row_heading level0 row8\" >2019-06-29</th>\n",
       "                        <td id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6row8_col0\" class=\"data row8 col0\" >99.9%</td>\n",
       "                        <td id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6row8_col1\" class=\"data row8 col1\" >67.7%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6level0_row9\" class=\"row_heading level0 row9\" >2019-06-30</th>\n",
       "                        <td id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6row9_col0\" class=\"data row9 col0\" >99.9%</td>\n",
       "                        <td id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6row9_col1\" class=\"data row9 col1\" >66.0%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6level0_row10\" class=\"row_heading level0 row10\" >2019-07-01</th>\n",
       "                        <td id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6row10_col0\" class=\"data row10 col0\" >99.8%</td>\n",
       "                        <td id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6row10_col1\" class=\"data row10 col1\" >64.3%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6level0_row11\" class=\"row_heading level0 row11\" >2019-07-02</th>\n",
       "                        <td id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6row11_col0\" class=\"data row11 col0\" >99.9%</td>\n",
       "                        <td id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6row11_col1\" class=\"data row11 col1\" >63.9%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6level0_row12\" class=\"row_heading level0 row12\" >2019-07-03</th>\n",
       "                        <td id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6row12_col0\" class=\"data row12 col0\" >99.8%</td>\n",
       "                        <td id=\"T_bd278a10_a31f_11e9_89aa_d094661b49a6row12_col1\" class=\"data row12 col1\" >63.3%</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f9293b24cc0>"
      ]
     },
     "execution_count": 213,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "global_ready_rate[\"2019-06-21\":\"2019-07-03\"].style.format(pct_str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA2YAAAHHCAYAAADUCkucAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvnQurowAAIABJREFUeJzsnWeYVEXWgN/T05MZBIacQXAIChJUclZQFNeEAVAU1DWsYV3Tpy7DmtigsitrDqy6qKisruIquAR1HRMogiJBRXLOzDAz3V3fj3N7pqenJ8owhPM+z31ud926VXWr6nbXqXPqlDjnMAzDMAzDMAzDMKoPX3UXwDAMwzAMwzAM42jHBDPDMAzDMAzDMIxqxgQzwzAMwzAMwzCMasYEM8MwDMMwDMMwjGrGBDPDMAzDMAzDMIxqxgQzwzAMwzAMwzCMasYEM8MwjCMUEZkqIk5EWlZ3WQ4VRKS9iLwjIpu9uvm6ustUGiIyT0RsX5sSEJGWXjtOjQq3ejMM47DDBDPDMIxyEjEIjDzyRGS1iLwgIhnVXcbDkZIG11WQTxzwL2AI8CYwEXiiKvM0Dh1EJNPrZwOquyyGYRix8Fd3AQzDMA5DVgDTvM81gV7AGOBXInKKc25ptZXMKI3WQAbwpHPu19VdGKNKuRRIqe5CGIZhVAQTzAzDMCrOcudcZmSAiPwduBa4Ex0UGocejbzzxmothVHlOOdWV3cZDMMwKoqZMhqGYRwYpnrnbrEuikgXEXlNRDaJSK6I/CAiD4pIjah4CSJyg4jMFpF1nqnkBhGZJiJtS0i7lYi8LiI7RWS3iLwvIp1ixLvcM+W6tYR0LvGu/19ZDysiq7yjtog8JiJrRSQoIr/yrg8SkedFZLmI7BORPSLyiYhcGJXOWOAn7+tlUWaiAyLiJYrIrSKySESyRWSXiHwgIv3LKmu4vMB87+uEiDzGRsTpLCJviMgWr41WiMj9MdqowPRSRDqKyFsist0Lq1VGOZy3/qmF1x+2e/UzR0ROLuW+eM8U7yevbMtF5NoS4tYXkSki8nNE//mHiLSKVS/eUUNE/ioi6730vxGR80tIv6aI3Cci34vIfhHZJiJvikjn0p49RjoNReRvIvKjl+cmEXkpVjm9+NeKyFIvzx9F5C4groS4RdaYicg8YIL3dW5E+6+Kuq+/9/7sEJEcEVkiIreJSHxUvAHe/Zki0sfri7tEZEdEnAtE5COvP+0XfZ/fFZFTK1JPhmEcPZjGzDAM48CSHx0gIucArwB56NqmjUBX4A5goIj0c87ledHrAA8DHwJvA7tQ87uRwDAR6eac+yki7SbA/1Bt0NvAt0AX4CNgUVRRXgUmA1cAf45R9nFAkEIhsywSgTmoydibXth273wbajr4GbDOe64RwCsi0sg5N9mL9zXwV+BGr7zhdABWec+YBMwC+gJfAE8BqcDZwH9FZKRzbkYZZZ0MnAhchgpo8yLyxxPw/oMO9Kd7ZR4I/B8wVET6OudyotJsA2R5aTwHNEDrryxqo+2zHngSaApcCMwXkcHOuU9i3PMycLJXxiDaH/4uIvnOuafDkUSkPlrnLYHZqMltBmpqO1xE+jjnvo9KOx6t39rAG2h7XgRMF5FhzrlZEenXRftme2AuMBNIB84DThWRIc65rLIqQHSSYR7QEHjXy7eZ91xDRaSHc+6HiPh/AO5B2+UJdGL5BqBnWXl5TPXO/YF/4PUtYGdEHhcB/wT2oe/KDmA48Eegr4iMcM5FOxTpjfaR/6JtWc9L6zpgCvCDl9YeoLEXfyjaNoZhGEVxztlhhx122FGOAx3sOuCdGNce865NiQqvC+wGfgQaR1271bvndxFhidHxvPD+QAB4Jir8BS+N30aF/8ELd0DLGOXsFRW/FRAC/l3OuljlpfMukBSrrmKEpaLC1y4gJUa9Ti0hrwe963dEhdfzyrEFSC5HmQd46WRGhcehA+gQ0D8iXNABvQMmxCivA35fwT4Uvu8fUeGDvfBvosLneeGfAjUjwjPQSYDvo+JPjVUuVBh3wNwS2vFNICFGed6Liv+yF35xVHgbr10Xl7MesoBcoF9UeE/vud6JCGvr9f2fgDoR4Y2ATbH6TrjeosIyvbgDYpTnGK/8+4D2EeHxwAfefZfF6EsOuDRGegtRITIlxrX0ivQZO+yw4+g5zJTRMAyj4hznmTBlishDIvIpcA3qFOS+qLiXAmmoULE+6tpDqFBxUTjAOZcbIx7OufnAd6hHQUDN+4ALgA3Ao1G3/BGd8Y/mKe98RVT4Fagg8myMe0rjNufc/hjlXRUjbB+qraiJan/KRER8wK+B75xzk6LS2wL8BRV+B1ew3JH0QbV7b3v1HE7fodqQPFTTFs0GVGisKEHg7sgA59x/US3KCSLSJcY9dzrndkfEX4ZqSjNEJA0K+sOFwGbgT1H3Pw8sAQaISPMY6d/sCrW24fL8DJwUDvO0ZSOB/zjnXo4q/0rgaeB4ETm+lGdHRLoCPYBnnXMfRqWTBbwFnC4ix3jBF6PC80POue0RcTeg2tYDwa/QfvmMi3De45zLRzXbELsPLHDOvVBCmnnE0KA657b9wrIahnGEYqaMhmEYFacthetVwqwE+jjnNkeFn+Kde4tIhxhp5QPtIgNEpBtqCtgbqI/O2ofJi/h8HJAEfO4NIAtwzu0T3aNrYFT41yLyBXChiNzknNvrCT9jURPLmTHKWBL7nXNLYl0QkZreM5yNCj3RHvIaFbspNhlALWC1iGTGuB5ed9cOeKecaUYTXhs1P/qCc269iKwAOopImnNuT8Tlb6LrvZz87JxbEyP8Y+BUrzxfRV1bECP+Wu9cCzWVy0D7w+xoYdk550RkPnC8l36kc4ydLsI8Nir9SFPBk1ATwtQS2qK9d26HCoElEX4nmpSQTiMvn7bAlxS2z8cx4sYKqwyl9YEvRWRvRJxIviwhvVeBScASEXkF1eBlOeeyD0BZDcM4QjHBzDAMo+LMdM6dCSAiDVCNTibwuogMcs4FIuLW8c43lCdhEemDrlcJAe+jAt8+1GRqLNAiInpYo7ClhOQ2lRD+FKrdGImujRqKrnP6Y1TZyyJaCAXUgQk6wD0RFSimomvPgl7Y2ajJZnkI118n7yiJ1HKmF4ua3rmk+toIdPTiRQpmJcUvi5j1FpHeMdEXIrVlEYTbKuwAozzPERkvzK4S4gco6iQs3Bb9vKMkymqLcDojvKOsdErr55Vtg2jKqrtNFH33ysr/T2if/zWqHb0byBWR14FbnHMHqtyGYRxBmGBmGIbxC/AGWBNFpCE6CPsN8EhElPCAur0r7nQhFncCCUBvF+UEQqI8GlI4oK5XQloNSgh/GXUwcgUqmI3zwitqxhjtCCHM2agA9rRz7qrICyJyu3e9vITr71Xn3EWlxqw84TxKqq8GUfHClPT8ZVG/jHxKEpTKorLPUdH0/+icu6PUmOVL5xrnXHk2+I7s5+uirpX0rJUtU2l1F6veYvYBzwz2aeBpEamHrhG9FBiFOjkplzdRwzCOLmyNmWEYxoHhHmAvcFd4zY/H5965RznTORbYFkMoa+Bdi2Q5sB84OYY771RUOCqGt9ZrGmpe2RfVWsx3zq0oZxnLIlzOf8e41jtGWHgdTizX50tRLVV3EYnpGv0A8LV3LqYFEpFGqMnoj1FmjL+EFiLSLEZ4H+8c7U2zvCyjsD/E0kiGn6+y6X+BCiLl7cslUdF3IlzePjGuxQoridL6WWl9oCtQIyJOhXDObXHOve6cG+Gl0S9i/ZxhGEYBJpgZhmEcAJxzW4G/o67DI80Wn0cFtgdFJCP6PhE5JsrZw2qgjoi0j4iTgLreLiJ8OedygdfQNTm/iUr6dtT9eUmEnYC84qVbUW1ZaYTXLxURwkTkXOCsGPF3oAP+YsKKZ1r5BCrsPRhLOBORU0Qkeg1bRfgY9Zo5wjMljeR+VINZkoOHyhBHlJMYERmMri9b4pyLXl9WLrz+8Cqq3bklKv3LUFPQea6Smy875zYCrwP9RSS6vyFKmZog59xnqHA2Rrx976LSiY9qh1dQoeoWEakTEa8Rus1CeQk7DoklFL+FasTGi8hxEXn40bViUIE+EKseRCQZNcsMUL5tFQzDOMowU0bDMIwDx0PA9egA8lHn3G7n3GYRGYUOmBeLyLuo98ZU1EX9ANRT4a+9NKagA/T/icir6CBuCCo8LaK4A4I7vfgPiW7IvATdI60nuldW31gFdc4tFJGFXtxd6ID7QPE2KpzdLiIdge/RNVrDgH8B50SVZa/nkKSfiLyI1k8IeNE59zPwe6A7ur3ACBH5CB1kN0U39M5AhdNKOVZwzoVE5ArgPeADEQnvYzYA1eosoLiXw1/CN+j+dVmoU4im6Hq//cDVvzDt21AzuftFpB/qtj0DrfNtqPfQX8I1qHOPv4nI5eieaXuB5mhdNUAdkJTFJeg+aP8SkY9RZycBdB1XX7R92wE455aLyAOoVvobEXkNFW4vRLV4w8tZ9rnoBMADXr/chTo+meKc2yUivwZeAr7w3r3wPmYdUccyFRHO3xKRnWj9/IzWyenoOz/FObe3AmkZhnG0UN3++u2www47DpeDUvYxi4jzZ6L2vfLCO6BOMNagnhW3ooPmSUC7qLgj0YFqNuqwYSo64J1H1N5MXvzW6Aa9u9BZ//dR7chUovYxi7rvBu/6Y5Woi1XAqlKuH4sKYVtQU8SPUCcjY708x0bFPw71CLkDFcqK7DeFTiReh+7ntRvIQbVcb6Jrd/zlKPMAYuxjFnH9RGAGKsDkoY5XHgBqlNAPplai3pzXji1QYXi7185zgFNixI/Z5t61mO2LrmGbggrHeV4fegFoVZF2LKW/paLbCHyFOqbZiwrTLwPnVqAu0tHtBr7z2nM3arr6LDA4RvxrUSE/F93T7C6vn5VrHzMv/DJUMN7v3bcq6voA9P3Z6cX5FtU+x1ewL12DmvKu8tLZgmpmxwBS0X5jhx12HB2HOFfZtcuVQ0Saej9y3dGZ32T0z2JVVLwk4F5gNOoK+Gvgdhe154nn5vl2dJaxIWpj/wfn3BtR8W4BbkZnnZ8D7nLOhSKun4JuInlCdFkMwzCORETkWdQBSDfn3MLqLs/RgIg4dD3fgOoui2EYhnFoUR1rzNqgs8E70BnUkngWuBI1YTkT3cjzfRGJXsx+L+qmegpqJvAp8JqInBGOICKD0FnpPwA3obOul0ZcjwMeBx4wocwwjKMBb33OxcAXJpQZhmEYRvVTHRozX1hTJSLjUXeyRTRmItIZ1ZBd4Zx73gvzoyYFy5x6NkJE6qNmQZOccxMi7v8vUM8518n7/mego3PuDO/740Ad59yF3vfrUWGtk6vcZqGGYRiHBSIyHF2XdQG62fBZzrnKbsxsVBDTmBmGYRglcdA1ZpHmg6UwAshHF8uH7wugnpmGRrgBHop6y3op6v6XgBNEpJX3PQG1Xw+Tjbc42XNBfS9wrQllhmEcBVwATERNxG82ocwwDMMwDg0OVXf5HYGfnHPRHra+RYWsNhHxctEF2tHxQBfbg3pFGiIiXUWkDTow+dS79hdgpnNu7gEsv2EYxiGJc26sc06cc82cc5OruzxHG17dD6juchiGYRiHHoequ/w66Bq0aLZHXA+fd7ri9pjR8V4FfoW6PAZ1mfs3b5+RM/Fc8hqGYRiGYRiGYVQHh6pgdkBxzgWBkSLSGHWpvFpE4tHNYO92zm0SkRvRjSproO6Sb3bO5USnJSJXAVcBHJPs79a0dgJxBPG7AEKhfJhPPPtJIMfFk4+fRPJJkjwSyGeXq8FGT2YUIFKqFBwp5JJKDj4cWzmGAEX3U/UTJIX9OASHEELIIRGHFHv2OEIEK6kYFcDvA79PiqdQPKsy06pKflH6pd3sHIhUefnLKgZoPwk6CDkIOm1tn2jbiIBPvDMaR+PpfeE44f7mvHDn5Rudd6yVp+KlESteZBmcU1/n4TKEnCv47BPtT3Fe3HAZQ97ciuZRmIkrCBctvxSWI3x2zsvTq5fw84W8hwunJhR+Lwjz8vKh5Yk8wnkkxAnxFXyFws8VdBAKucLP3rmg4gueU4NCzhW2jVePRLRVLAraxRXG+aUrh8Pt6bxniZlfNK58eVfFquboNg6fIvt6JL6IdyFcqOg4v6SckelH19+hQIpfSE/W9zAUChHCx7b9jpzAIVhYowgnbFzJ4oZtyo54AND/mKLvfPi33EXECWO9xzjQxIk3DhWJ/b8DbA+soIa0IT90aPfBvI0rtzrn6pUV71AVzHage7xEE9aAbY+IV0tEJEprFh0PAOfc+oivN6F7izwuIqei68z6oZuKvo/u0XJPdAGcc08BTwFkZGS4JcuW6YVQEHasgs1LveNb2LwUt3UF4vYT8icTTD8eSayJf/VHuJ4XIqfdW/BrF9y+Ct69Fd9P85FgrgpZvjhc3H42n3g9G9tfTmLuVhotfpJjvn8VCeUVKVcovS3BU+/DtTlNk9y1lrh59yPfvAqJadD0ZFzznkjNhsju9bBrDezbBs1OgnZnQd027Nmfz7qdOazdnqPnHdms3ZHD2h057MsNFNZB0fooITzic8SVIuElvEG/KM0S4lOu+MXzzc/Px++PL7NslCPN0spXnueJ9wl1aiTQO34Ft+x9iPkpp/FiwoXszQuyLzfI3twA+/ICOKfCT62UBOqkxpPg97E/P0ROXpDcQIiEOCEpPo4Evw+fCCHnCIQcwZArEEZ8Ivi8H8I2wR+5JGcajydezirXgNx8XSYaH+fDH6dC6768IHv3B8jJD+ITqJkcT82keNKS/NRMiqdmsp8aifHszc1n4+5cNu7KYXdOgNop8dSpkUDtlAQAcgMhcvOD5Acd8XFCnE/w+3zkBUPszw96R4j9Af2cGwiRHB9HaqKftEQ/Li+HRvVqk5roJzUhDgcEQo5AMEQw5MgP6nMGQiECQX3uQChEdl6Qndn57MzOKzaQDgG9Mupxee9W9G1bl0DI8fO2fazYtJeft2cXvCcbdu5n275cdmTnEwwVCppx3gGQluindmoC/jjBOQrqPDk+jqT4OFIS4vSzd070+0jw+0jw6jo+zkd8nH53OLLzguTkB9mfF0REvDrzFdRdfJyvoB1L6m9+n97j9wn5wRC7c/LZvT/AvtwAKQlat6mJ+leR4+WXGwh6zycRQrJ+Xrd2Lc2aNSsUoMMTGxIdv+j38ASICvhS5H4i4oMKsMFQxOF9DwSd15+1veN8QlpSPDUS/STFx7E/P8i+3AB7cwMEQs4TwqXgiPN5eUd8LjzA54sRzwsXEXLyAuzKyWdXTj45eSHSkvzUSPRTI8lf0EdrJPpJ8PvIC4S0vweCxPmkoK1FhNx8Dc/ND4FXxjiftmH4vrxAqKCufBFl8EWESYznWrl5L0/O/wG/T7j51ONYsmwl764K0sQnXNmvNY1rJXuCatFJgsjvOIfPJwV9p/BdLexL4e8IhEIUtEn4tyYQcoS8/h+moK29fpmcEEdKgp+keB/5QVdQJ/vzg95vgP5exPkEn0+IE803fPhECIYcecEQ+cEQcaJpJnnvli8i8+hBX+R0XPFrJX0p330OCAQdeUF9Hgcke+98crz3uxUMkR90LPjqazoefwL5wRCBkOOMTo154525BEIhfCKkeX0rJcGvk6hSOIkV7rsh59iXG2DP/gC79+fjHAW/N/FxPvYHguTk6buRkx8kO887cgNk5xdeS/D7Cn7bk+PjCIZC5AUd+cEQfq8PJ8bHabsTFuC8fuNNOvl8Qo1Ef8FvS8FkXrE+5wr6XSgUEVbkWvRklk5YpnrvWVpSPEnxPu8dkIJz+H0IOee9g/p/UDAhF/nOe/UZ+Z/oKyXOp59m0btXryL3hONHvq/BkCPHq9uc/GCx8VCR9yKqk5UkoJQQXGL8ku4oKC+FzxbGeROgIee8SUdtn/Bvcsi7FvTCQiEHov0tyR9HYryv4L8vEAoV+W0IhhwpCfp7WSPRzzHJOn4pC5ko7JmwAuccW/bkkhsIef9bccT7fOzMyWfr3ly27sll0aJF9O3RnbQkP8nxcezPD5GdHyA7L0hCnK9g7JCUEFfwvPoh6jeQyP7o/adGTE6Gw/y+wv/wlET/z2U+DIeuYPYtcI6IpEStM+tA4aaf4XiJ6AaTK6PigW5aWQxvL7W7gSHOuZCIDANmO+e+9q4/j7rTLyaYlYgvDtKP1aP9mYV5BXJh31Z8aY3w+fSfde0zo2ia9SjEJ8Ogu+Cb6cTNvEVvOPlKaNkHad4Dsrcjs+6h4Rd/pOH3L8C+LSA+6DIKuozWty2QC7vX45v7AL5XLoS2Q6F+O/jsSe0Zp1ytcVZnIXPvLSxvan1IqgnLZsIHmVA3g7SO59Cuy2jadWhW7sc+0pk3bx4DBgw4cAnuXg/Z26Hh8ZW7//t34fXfgz+B8/e8yPmd8mHEo+BXwSYU0j+apHhfEc1TpcneDk9eB4HV9KqxAa54H2o2LjF6IBgizhsgVgfaXj0qfX8o5NiXp4OT3PwQ+/ICvLdkIy99uppLn/ucujUS2ZmdRyBCequVEk/T2sk0T0+ha4vapKcmUCc1gfQaeq6TmkB6aiK1U+NJ9MeVkvuRwbx5WxgwoEPZESPZ9gPsXgct+5Y2ijAOEOd3bcqEfy/hvplLATirc2PuOqM9DY9JquaSGdHkroljQLv6RcLO69a0mkpjlEWdJB8NapbvPUpLii87klFuRIT6Meo+/D98XIM08tbGcXyTY6qhdOXnUBXM3ka9hl0A/AMK3OVfCMxyzuV68d5DvTeO8uKHGQ0scc79VEL6k4F/Oue+iAhLjfhcgwNlfedPhGOaFH4XYWWb8TRtkA4f/gl++C+sWwDNesC5T0HtCEVhcm24eBr8MAc+ngwdzoZeNxRNL0z7EfDZEzD/T7DifThhJAy+B2o1L4yzbxvs36kD6/hkDdu5Bpa9C0vfhvl/1KPNYOh6GRw3VMt/NOCcaj1DAQjle+cgCbnbtI5CgeJHMPJ7fsT9AQhGfA/mwoZv4KcPYdsKza/NqTD0Aah3XNEy7F6vGtctS2HrCjimGTQ/BZp0g8Wvwzs3QeMucMl0+PJ5mHufDmgvfBGSa+PzZplLJC8bfv4frPwv/DgXGnXWfheLUAj+dTXs2QBnPgKz7oEXz4HL/wMpdWLe4o+LMbsVDMCGr2F1FrQZAvXbl7NRqgDn4JvpkDVFn6lp9yKXfZ6GJfIPs13Dmlwz4FjeWbSB+cu30LR2Mm0b1KBNvTRa1k35ZX+ugTydcIn1TkeX+6cPoUlX1YAfKWz+Hj76Cyx5A1wIWvSGM/4MDTpWd8mOaJqnp/Dc2JOYt2wLy79bzNXndvllCXom34ZhGMYvo1oEMxE53/vYzTufLiJbgC3OufnOua9E5FVgsrcW7CfgGqAVKoQB4JzbLCIPA3eKyB5gISq8DUJd7sfKeyjQF8iICP4AuFFErgXWA78Bph6Qh41ZCB+cOVk1WYtfh4F3Q5+bIa6E5jh2kB6l4U+A3jfAiaMgdzfUaVU8Tmq6HpHUaqZatVOuhh0/w9f/hK9eguljIOkYFfhOOB8anVhU8ChNECkQbKKFl2jBJr/kNIOFwlGR9ELBiGvRRynXysrLBWNWay+ArDJbtGwSakCLXtDtMs3zo4fh8Z5w0nio0QDWfglrP9dBepjk2pDj+cCROC1jmyEw8gVISIX+t6og/9Z1MLmTCjx1j4P6HaDzRcWFp6+nwcxbID8b/ElQpzV88yqceAm0HlC8zB89BCtmwfCHoPsVkN4GXjof/nkBXPoWJNYoGn/vFlg8XQXZYK4KHXs3wepPIW+Pxvn0Cbh6PqTWPQCVWkGyt8M7N8N3b2p9Tr8Mfv1RiUJmJIn+OM7r1vTAzlTn7oGXzoMNi+CaT1TbHou8bHj7Blj8GjQ4XoXySEFu42KdUGl/tr6rxRYCOtj4DSx9B5b9BxJSoM9vdeIlHHfTt/DFM5C/H1r2VgGpdsuKD7Z3rqbR+vfgu12Q1gjSGkKNhgUaXQB2b9DJpmXvwvczIT7Fm3BqCnPvhyf6quVAt7FQNwN8h5Dz4Pz9EBevFhLVTX6OvscVaaOcHfqe1m2LiDCwXX1kY9SzBAOwb7NOyIgPUutBSl2Ij6EF2LMJ3rtd+1WjE6FVX2jZB+q1U6uMX9J2oSBsWgI/Z8GmxWoN0u7Mg98fAnmwczVs+V4nzPZu1gmzOq31HcndrZNo21bq54addAKlfsei/T6YD1uX6yTdlqVaPw06QsMTtE+t/QJWf6YTtft3afvmZ5OR2BoOpNWGYRiHNAd9g2ko2GAzFgWbbopIMnA/cAm6384i4Hbn3LyotOKAO4ErgYbAMuAPzrnXY+SbCCwB7nXOvRB17TbgBiAFeBO4Poa7/iJkZGS4ZeE1ZhWgwDzOOf2jLMfA8KASCsIPc2HJ66pJy9t7cPMXH/j8sY+4EsJ9/sIBk88PvnjvHBdxLfw9PuK+uIhrxdNbtvIHMtp1iEizkumlNdTwMHu3qLZr4QuqKUhvA01PgsZd9c+6fnvtFzk7VGhb/akOwvrcVDQdgDVfqEC9dTlsWQbZWyElHU67XwW0YD68f6cOvFv21UmAFr0AgSknQXItuGp+0QHPD3PgxXOh00g458nCwd/SdzyhvZYOwlr110HKope1r4TyIbEmxCWotjWxJrToqfkm14ZpF0LzHjDmX1UyuC3R9HTlB/DmdZC9Tc2HW/aD54dp+S+ZfvAHe2GhbO2XWk+t+sElrxaPt3MNvHKJCl/dL4dvXlON2ajXtI988ijMuQ9wKvA3OwWGTVJN6OpP4ft39Ni5Wt+r5j1h11rY+bMOpLuM1nb7aT74k1Voy96meddqrn2ly5jifS6a/P1alo8egkAxn0k6sK/ZSAf9W9R8jhoNdCKp5/WFE0bZ2/V5vnxOnynxGF0H26wHNDtZNcfREwIlEciDrctg03e65nf7T9ofa9RTYcM5FUD2btbJiowzdCIqIaVoOjt+huXvw/L3YNVHWv8Zp2vc1gMqZlWwewP8bzL89JFaLSSk6gRY9yvg2IFRdZoDC6aqgJSfo0f2dm3Lnashd5e+5/U76FG7pZqnJ6apsLtvi2rTd29QoWHLMti7UdNu1U/U6CdqAAAgAElEQVT7SYOO+s6cdDx8+hgsehX2rNffpGhS6qow3/4sfe5vpsPse7RcJ1yggsv6rwsnuXx+Fc6PaQYNOujvWt0M7Xs/f6L9c+9mnZColwF1jtUJnJ1rtI9u+V4FHdCJrby9KuwMuF1/T9Z+oWlsXKx9OyFFnzu1rgpNYcHJn6z/GxKn9bDqI63/DYu0X8cn6+HQvpu/P+K8v/ikXUJa4URTJHEJmv/+nYXfI7XbuXt1wgr0PyMUY9tU8ekz1qivZdq1BrdhMXL7j/r7CYUej4xDkgO+/MEoE5kouAnleyeqs31EZIFzrnuZ8apDMDtS+MWC2eFAfo5qTXatLSroRAo+JQk2xQSpSMGpNOHm0Jkhr/K22rVO/4APpHC+cYlqhtZ+rgOYYB6s+Qx6/QYGZxbVzH4zHWZcCec8BZ0v1LANi2DqWaqVGf+BDh4j+XGe3vfjPB34gQpqJ16iWo56GZTIwhfh39erxmbIBB1gLPuPDgo7jYSul/6iRy/WXnnZ8MEE+PwpqNdezTYbddJrXzyjGsRB90C/3xVPLBjQgWd6GzhpXPHrlTXfyt2jmse1X8AFz+vAf/Y9cPGrkDGsMN7qT+GVUdp+5z2jg+KNS1RjmbtH15Ku/UIHysMfUcHhvxN1QB7WtsYlQOuBuu414wwdtAbzVVP64Z/VYVHNJqqh6nqZ3rfle1j1sWro1nymzz94gmrtc7Zrujk7ddCan6Nh//sb7PgJOpzN56lDOLlbFxUI9myAPRu98wad9GnVF44drAP1kupvhzd4X/MprPlczXtxOnBtcLwKmC16QvNeOojN3q7p71ytdbLG0zwE9mt6vngdpOft0/oJD4rjElRz4UIqkCSkwfHnapobFql2IyzMpLeBtqfp/cvfV6EhoYYKOW2GaP3kZ2v+a7/Q52/QARp2hrpt9J358jmt/2MHap65e7XMezdBv1thwB36e7hhEcy4StvCn6RHfIoKcbWa61GjAexa7QmeSyF/X+y6TK6tz16vfeG7+fEjWv7u41izYQvNNs3Stsw4XdslrZGavLuQPu++LbBluffcuwoFixa94ay/Qt22mu7+3fq7s/0nbY/d6/Xz5u8KhSzQ34vmPbTvbVupGqc967U9ajZRS470Ntq+LXpqeZa8oZrhbRHLySVOJyh8cfqu52drWYNFnWMVo+5x0PRk/Zzv3YeoVtCfXPxcs7FqAesdp8JW9nbt7ztW6eRB+rHaJuLT9ly3QM238yLaJCEVGpygvz/pbfQ92rRE3+n8bJ2Ya9q9qDD3c5ZOII18ETp4RkAmmB3SHFbjuyMEE8yMAo4Kwewo57Btq1AIFk6F2ZmqSTl7ig44Y8V7eoAONK7/UgcVz5+uA8Er3tMBUkk4p04bdvyk5kvhdYtl8e8bYOE/YMD/wfL/wPqvID5VB5ZnTlbNUCTbf1St4IZFapKXn6OD+9YDdXAXobEooo1et1DXyG1boVqZQfcUNcdyDt4YD9/OUA1e6wFF6+XNa+CbV7RsNy8pKjyHgvDsaTogrlFfB8mJaTrYyt6q9VmjQeFgq3YLHaBuXaHaqa0r4PxnoeM5qtl5orcO2K/9VMv4/bvw+uU6SL34laJrEXetg2kjVXg540/Q+eJCAWf/btXI7FoLxw2DtqeWvCYtmK8mjA06xtaIOafmhh9kqja2NNLbalmOHVQ170zOTtUurvlMhbW1X3qDaYprH3x+NSdr3kM1bA066kA4/IxhSwURFRDCA92fP1Ez7u/eVDPzehmaTuMTdU1o3QgX5YFc1bosmwkrPlABKZLk2lCzqWrswkKC+LSt+v1OtTlh8vbBu7fB1y/pRErLvio0p9aFXz1Wthk7aH/N3aXtn7tbhZTUukXXE0eSvV3NRr98TucXOo2Evr8tfVIFtK+u+hBWzFYTvM6XlG8izTn1BLxlmZqsxjJRzfNMrEtLLxTU9tnxs75bTboWnzgKBbX/b/9Rf8+CeYUm6zUb629VWsOyy3woEMwn8EBT/F1GwZkPa5gJZoc0h+2Y4TDGBDOjgPIIZrt372bz5s3k5xcOHPbv309Sknm/Ohw4FNsqPj6e+vXrU7NmzbIjZ29XrUEpnhT5cT68MAJOuQaW/lsHMpe/V3QgeiDJ36+zwOu/0lnm/rergPLa5eq4JiycbV2hZm3fvan3+ZNUW+Lzw7ovdbDlT9JBVnIdSKnD9m3bqBOXrQOz/H0q2PzqcWjdP3ZZcvfC04Ng+w8qvPW/XQeyM3+r2o0uY+CrF1WIHHB74X1fT1PB7Xhvuey+zTooTq6tA+LkOoXam+ythfcl1FDtQt9bVNMV5oc56lhl0N26JuvtGzwnL68VXxcKOkDOz1Yz1KomGFDhdfd6FU6T62i+8cmF2pxaLQo0sQfljy+Yr9qs1Z/Avq2F69lqNlZBLHqwXhHyPVPM8k40OKdanB/neVuTnKSCl4iWc8syFeCbdC15HSEUXQPafoRqoqrazH3HKrI++4Kewy6o2nyMSrPtb4NJZwfcsFADTDA7pDHB7OBzpAlmh6pXxiOC3bt3s2nTJpo0aUJycnKBC/E9e/aQlnYEeVY7gjnU2so5R05ODuvWqQlhmcJZeQZ2rfurRuCzx9VUauy7VSeUgWqELnlNB9XHnV64QP7CF+HV0ep5ctm76jnSn6QmXsefp1qZsBlm7h41t1v1sZrK5WyHfVvxB/ZCw/bqWbR2S+h0YenCS2IN1QzOvkc1Td/+S9cyLX5N11cNnqCmUZ89Ab2u1wF/IBfmPqhrtM57pnRzRufU3Gn3Oh2spzWKHf/YQToYn/dH1f4cO1idvJS0nsqfUNSxQFUS51cz00OJuHho2k2PA015BbIwIipsh835IomL160xyrM9xomXqHnd9h/UZPJgeDms3ZLcpFVVn49RabbXOZH0lc/oRE+kl2XDMI5ITDCrQjZv3kyTJk1ISUkpO7JhlAMRISUlhSZNmrB+/fryac3Kw9AHdKZ+yMTK77FWEWrU0+0fIvEn6lqK6WNU+3DK1boWrUa94veHHTBknF4keGFlZsNS6sDZf1czs3duVqHs5KtVKBNRAe25obo+rsevYcE/1HTtrEfKHjyLqIfUWF5Soxn6gLrEP24ojJhy8AQv49ChbpuqnRQxDjt21O6sH36c94vX4BqGcehjglkVkp+fT3JyBWdfDaMcJCcnFzGP/cXUOw4uf/fApVdZ4pPUCUbeHtXeHUxa9oFff6zrl5r3LBS6mvdQJwSfPKpeLj/8M7Too1qtA0mtZvC7FSaQGYZRQHZKM12vaoKZYRwVHDru745Q5GCYoxhHHUd0v/L5Dr5QFsafqPt4RTsg6HMz7F4LL52r68mGTKgaUzMTygzDiEREHRP9OE+dvBiGcURjgplhGEZZtD1V9xdat0DXxTU7ubpLZBjG0ULrgbq/4KYl1V0SwzCqGBPMDMMwykJE95jyJ6vnRMMwjINF2Kvsj/OqtRiGYVQ9JpgZB5WWLVsyduzYgu9Tp05FRFi1alVBWGZmJnPmzDn4hTOM0ugwAu74+eA4RzEMwwhTs7Hu/WaCmWEc8ZhgZlQrw4cPJysri0aNGhWETZw40QQz49AkYjNrwzCMg0brAboJumEYRzQmmBnVSr169ejRoweJiVU34HXOkZeXV2XpG4ZhGEaVcuxACORUdykMw6hiTDAzKsWiRYsYMWIEtWvXJjk5md69e/PRRx8VifPXv/6Vli1bkpSURPfu3Ytdh+KmjGFvg/fffz8igoiQmZlZEP+ll16ic+fOJCUlUbduXcaMGcOGDRuKpNmyZUtGjx7Nc889R7t27UhISGDmzJkHtgIMwzAM42BRv0N1l8AwjIOACWZGhVm4cCG9evVi+/btPP3007zxxhukp6czZMgQFixYAMCzzz7LTTfdxMCBA3nzzTcZO3YsF198MTt27Cg17aysLADGjh1LVlYWWVlZjB8/HoCnnnqKMWPG0L59e2bMmMGkSZN4//336d+/P3v37i2Szty5c3n44YeZMGEC7733Hp06daqCmjAMwzCMg0Bq3eougWEYBwHbYNqoMLfeeivNmzdnzpw5JCTovktDhw7l+OOP595772XGjBlkZmYydOhQnn/++YL76tWrx0UXXVRq2j169ACgSZMmBZ8BgsEg99xzDwMGDOCVV14pCG/Xrh19+/blueee44YbbigI37FjBwsWLKBhw4YH5JkNwzAMo9pISIX4FGB3dZfEMIwqxDRmRoXIyclh/vz5XHDBBfh8PgKBAIFAAOccQ4YM4cMPP2Tt2rWsXbuWkSNHFrn3vPPOw++v3FzAsmXL2Lx5M6NGjSoS3qdPH1q0aMH8+fOLhPfo0cOEMsMwDOPIwbRmhnHEYxozo0Js376dYDDIvffey7333hszTnjNV4MGDYqE+/1+0tPTK50vUMR7Y5iGDRsWXA8TK55hGIZhHLakmGBmGEc6JpgZFaJWrVr4fD6uu+46Lr300phx6tevD8CmTZuKhAcCAbZt21apfOvUqQPAxo0bi13buHEj3bp1KxIWdiJiGIZhGEcEpjEzjCMeE8yMCpGamkrfvn1ZtGgRXbt2xecrbg0bCoVo1qwZ06dP54orrigIf+ONNwgEAmXmkZCQQE5OUbfAGRkZNGjQgFdeeYVx48YVhH/yySf8/PPP3HLLLb/gqQzDMAzjECe1XnWXwDCMKsYEM6PCPPzww/Tr14+hQ4cybtw4GjVqxNatW1m4cCHBYJBJkyYxYcIExo8fz+WXX85FF13EypUrmTRpEjVr1iwz/Q4dOjBz5kyGDRtG7dq1ady4MY0bN+YPf/gDV199NaNHj2b06NGsW7eOu+66i7Zt2xYRAA3DMAzjiCPFWwrgHJhViGEckZjzD6PCdO3alS+++IL09HRuuOEGTjvtNG688UYWL15Mv379ABg3bhyTJ09mzpw5nH322Tz//PO8/PLL1K5du8z0p0yZQmpqKmeddRYnnXQSTz31FABXXXUVL774IosXL+bss8/mtttu49RTT2X+/PmkpqZW6TMbhmEYRrUS1pjl7S09nmEYhy2mMTMqRfv27Yu4rY/FjTfeyI033lgkLLyRdJixY8cyduzYImG9e/cu2A8tmrC2rDSi8zAMwzCMw57wGrN9WyAxrXrLYhhGlWAaM8MwDMMwjEOdsMZsX+WcaBmGcehjgplhGIZhGMahTniN2b4t1VsOwzCqDBPMDMMwDMMwDnXCpozZW6u3HIZhVBkmmBmGYRiGYRzqpESsMTMM44jEBDPDMAzDMIxDnYQUPdsaM8M4YjHBzDAMwzAM43DBTBkN44jFBDPDMAzDMIzDBTNlNIwjFhPMDMMwDMMwDhf2mcbMMI5UTDAzDMMwDMM4XDDBzDCOWEwwMwzDMAzDOFzI3grOVXcpDMOoAkwwM6qUqVOnIiKsWrWqIKxly5aMHj261PsyMzMRkYLvO3fuJDMzk4ULF1ZVUQGYN28emZmZhEKhKs3HMAzDMCpFMA9y91R3KQzDqAJMMDOqlOHDh5OVlUWjRo0qdN/48ePJysoq+L5z504mTpx4UASziRMnmmBmGIZhHLqYAxDDOCLxV3cBjCObevXqUa9evQrf17RpU5o2bVoFJTIMwzCMw5zsbZB+bHWXwjCMA4xpzIxys2DBAkSEjz/+uCDs0UcfRUS4++67C8JWrFiBiDBz5syYpozRBINBrrrqKmrWrMkHH3wAFDVlXLVqFa1atQLgyiuvREQQEaZOnVqQxowZM+jRowcpKSnUqlWLCy64gNWrVxdcnz17Nj6fj8mTJxfJe9SoUdSpU4c1a9aQmZnJxIkTAYiPj0dEqFmzZuUqyzAMwzCqCtOYGcYRiQlmRrnp0qULtWrVYs6cOQVhc+bMITk5uViY3++nX79+ZaaZk5PDeeedx1tvvcW8efMYMmRIsTiNGjVixowZANx5551kZWWRlZXF8OHDAXjiiSc477zz6NChA6+//jpPPvkkS5YsoX///uzZo3b4p556Kr/73e+44447WLRoEaDr36ZNm8bTTz9Ns2bNGD9+POPGjQPg448/Jisrq0BQNAzDMIxDBvPMaBhHJGbKeJCZ+Pa3LF6zg7i4uGorQ4fGNZlwVscK3+fz+ejXrx9z587l97//PaFQiPnz53PNNdfwt7/9jb1791KjRg3mzp1Lt27dSEtLKzW9HTt2cNZZZ7FhwwY++eQTjj02tllGYmIiXbp0AaB169b06NGj4NrevXu5/fbbufzyy3nuuecKwk8++WQyMjJ49tlnuemmmwC4//77mTt3LhdffDHTpk3jN7/5DVdddRXnnXceUNR88pRTTsHv9xcIdoZhGIZxyGAaM8M4IjGNmVEhBg0aRFZWFvv37+frr79m586d3HbbbSQmJvLRRx8BMHfuXAYOHFhqOuvXr6dPnz5kZ2eXKpSVRVZWFrt372bUqFEEAoGCo1mzZrRr144PP/ywIG58fDzTpk1jzZo19OjRg2bNmvHII49UKl/DMAzDqBYSaugaM8MwjjhMY3aQmXBWR/bs2VOmNulQZeDAgeTm5vLJJ5/w1Vdf0blzZxo0aECfPn2YO3cuzZs3Z/PmzQwaNKjUdL755hu2bdvGpEmTaNCgQaXLs3nzZoCYJpAAtWvXLvK9bdu29OrVi1mzZnHVVVeRkpJS6bwNwzAM46CTkm6mjIZxhGKCmVEhTjjhBOrWrcucOXP46quvCgSwQYMGMX36dJo1a0ZCQgK9e/cuNZ1hw4bRuXNnbr/9dpKSkrjxxhsrVZ709HRA14t17FjcPDNaAH7uueeYNWsW3bp1Y+LEiZx77rk0b968UnkbhmEYxkEntZ6ZMhrGEYoJZkaFEBEGDBjA7NmzWbp0Kddeey2ggtmdd95JzZo1Ofnkk8ulibr11luJi4vjpptuIhQKcfPNN5cYNzExEVBnIZH06tWLtLQ0Vq5cyWWXXVZqfsuXL+eGG27g2muv5cEHH6Rz586MGjWKefPmFaz5i8zncNVqGoZhGEcwqXVh97rqLoVhGFWACWZGhRk4cCDXXXcdcXFx9O3bF1CPjWlpaQWOQcrLb3/7W+Li4rj55psJhULccsstMeM1aNCA9PR0XnnlFTp16kRqaiqtWrUiPT2dP//5z1x33XVs2bKF008/nWOOOYZ169Yxf/58BgwYwCWXXEJeXh4XX3wxrVq14qGHHiIpKYlp06bRr18/7rvvPiZMmABAhw4dAHjooYc4/fTT2b9/P/379/+FNWYYhmEYB4jUurBhUXWXwjCMKsCcfxgVJuzYo3v37gX7fMXFxRUIMGU5/ojmxhtv5NFHH+XWW2/lT3/6U8w4Pp+PZ555hh07djBkyBBOOukk3n77bQCuvvpq/v3vf7Ns2TLGjBnDGWecQWZmJoFAgBNPPBGA//u//+O7777j5ZdfJikpCYCePXsyYcIE7r33Xj755BMAzjzzTK699loee+wxevbsyYABAypWOYZhGIZRlaTU1TVmzlV3SQzDOMCIsxe70mRkZLhly5aVeH3p0qW0b9++WPjh7PzjaONQbquS+tfRzLx580yYrmasDQ4vrL0ObYq1jwj871GYdRfcsRqSjqm2shnFsffp4CMTBTehfLJMdbaPiCxwznUvK55pzAzDMAzDMA4XUuvq2TwzGsYRhwlmhmEYhmEYhwspJpgZxpGKCWaGYRiGYRiHCwUaM3OZbxhHGiaYGYZhGIZhHC6EBbPso0hjFgrCyv/CjKvhr53hy+eru0SHD8veg7VfVncpjHJi7vINwzAMwzAOF1IOgsYsbx+s/wpa9FaHI5UhkAurs6B+R6hRr+i1XWvh48mQcTq0GVx6Ol88A/P/DHs3qrOTWi3gnZtgyzI47T6I+wVD2WAAPvoLfPaEern0J+rR41rocU3l0w2zdzMsfh2+nwnpraH9CGjVT/M4GPzvrzD795BUC67NgpqND06+RqUxwcwwDMMwDONwIT4JEtJg37aqSX/bD/DKKNiyFNqfBSOmQHKtwutrPocVsyExDVLqQHKdouc9G+Grl+CbVyFnu5a1/21wyq8hLh6+ehHevwtyd8MXT0Oni2DYg3pvJM7B/D/BvAegZV8448/Q9jTw+WH2PfDpY7BtJZz/bHHvlDt+hp8/gfrtoHGX2M+5czW8cSWs+RQyzoBjmqowuWUZvHcnpLeFtkMqXn/5+2H5f+Drl2HlB+CCUL8DLFkEC1/Q+uh0gQqVCaklp7N/F3z/LmxdBtt/1KN2KzjjL5DWoPQyOAdz7lOh87hh8NOH8Nb1MPqNygvaxkHBBDPDMAzDMIzDidT0qjFlXPYezLgKfHGqNfr8KXiyH1wwVcPm3A8r3i87HV88tBsOHc6GRS+rILXgeRV+fvpQBa3hD8Hi1+DjR1SAGXS3xk+po4LFBxNU49P5Ejh7iuYfZtiDULctvHsr/LGVplunFaSkw9ovVOgKl+Pcp+D4cwvvdU61WDNvAReCc5+GTiMLr+dlw7OnwozxcPVHUKtZ+epu7QKOW/YYZF0KubsgrTH0vkEFz/rtVOj7cT5896aaYq75HC76J9RuWbRs6xbCgudgyQzIz1ZBtHZL1RSumA2P94Kz/w4ZwyCQp3X46eOQvQ2adNVjx8+w8B/Q9VI4czJ8+Ry8+zs9nzRO88rdq5rChFQ4cRQk1SzfcxpViglmhmEYhmEYhxOp9WD3Bh3IV1YD4pxqt7athO0/qECw8B/QsBNc+BLUbgEdz4HXLldBJRRQk7jBE+Dkq1SoydkO2du98w49xyWoyV5quuZz/LkqULz/f7B2gWp8uo8Dn0+FsY7nwL9/o+aJM38LzXrovUvf1nhn/EXjRtP9CmjYWbVT23+CHT+ptq9RZ+h5PTTtrpq5169Q7VP3y2HnGhXIVrwPTbrDec+oQBdJQgqMfAGe7A+vXQaXv6dar0WvaP3Uaq7pNztZ429ZBh9kwrJ3aeBLhOPPgc4XqclipDDpT4TjTtOj47nwxhXw1AA471kVjpa9qxqybSsgPhVOOB+6jtXnCZtrblkGr4+Dly/UOl77BezZoOaiLXtrG37/jsbteb1q5UTgpPGw7D8w625oPQC2LoeZv4PdazXunPtViDvhfNi7SfPZtkK1hp0vgrSGhc+xcYmaZrY/Cxp0qFzfM0rEBDPDMAzDMIzDiTqt1VTwiT6qATlhJCTWKPu+Lctg+Xs6oF/zha7bChOXAF1GqyAUn6xhzU6GX3+kGq+aTaHntUXNBpNqFtX4lETbU6H1QNUARWtmGnSEcR/Ahq9UY7fsP7o2rddv4NR7Sxc8m3bToyRGz1Dh6p2bYNXHmjYOhj4AJ19d8vq09GPhV4/B9DHw0rmwealqKBscDz/Og+/egqYnQd3jVGBLSIXBE/gktx19h5xRjvoYAlfOVZPRlzxtni8eWvbRtW0nXBBbg1UvA678L/z3D5D1dxX+zp4Cxw4urKfs7br+sO5xhWEiGu+xHvD0INi/E+q1hyve13b/9DH4/En49O+FeaWkQ/ZLmlfbU6HRibD037D5O72+YhaM/6B4+2z6ToXX6P7onLZr4y6F/csohglmhmEYhmEYhxNn/VUH8Z8/De/cDLN+r4402p+lzjSi1y7l74f5f1TTQBfUtUqt+kGTblDvOKhzrJoDRmp4wqTUUdO5X0qcH+JKMJfz+bQsTbrBoLvU7O9AOMhISIGLpsGb16jJX5tT1YSydouy7+0wQoXDTx7VdVq9fqPOUPL2wdfTVJhZ/xWcfCX0uxVS6xKcN6/8ZUs/FsbPhi+eVXPJNkOKr5WLhT8Rht4Pp/6h5PaKXq8H6vjjrL9qfxk8QTVq/gS9dt4zMGSirsur3VLNRJNrwdYV8PU/db3c8veg2SkquOdnq1ORFbPguKGFeaz+DJ4bqlrIkS9AwxM0PHePakW//ZdqSM9/3ta6lYAJZsYBR0SYMGECmZmZ1ZL/qlWraNWqFc8//zxjx449IGlGP1NmZiYTJ07EOQfAzp07mTx5MiNGjKBr164HJE/DMAzDiEl8spqedRmjrtAXTlUzuMXTwZ+sZm1Nuqs5ny8O3r1NTdNOHA2D7ylqmnYociC9FsbFwzlPQd/fqcapIgLBqfdC75sLzTJBNUGnXKWaykCuCn+VJTEN+txUuXtjCWVl0fEc6PCr2HVwTBN1ShJJ3bYwJBMG3q1atvBWDcF8Xa825z51yCKi693evhHSGkF+Djw9GM74EzQ9GaZfquayxw5W4axlHzWvLAlvbHU0Cm8mmBkHnKysLJo2bVrdxahSxo8fz7Bhwwq+79y5k4kTJ9K0aVMTzAzDMIyDgwg0O0mPMwOw+hNdm7XqY1j5R8Ab4B7TXM36ynJNf6Ti86kDjooiUlQoK5Jm3C8TyqqLygg7cf5CoQxU2O1/B7z5a+1vHUaoNnbLUrjkNTVXnHGlCmoSp2aRl70NzXvBtJHq9bLpSbp+DmDDIvjf33Sd4J5Nus6tVV8Y868D88yHESaYGQecHj16VHcRqpymTZtWufAZDAZxzuH322tqGIZhlEGcX80TW/XT77l71NRu11p1FFGeNWiGUV46jYSPHoK5D6gm8sM/qVOT407T66PfUI+bG7+B0/9UqKU950ldGzn9Mhj1mu5n9/U/1XSy0YlQNwP2bVZPnTt+Lp/Z6RFEDDc3hhGb1157DRHhm2++KXbtjDPOoHNnnfkQkSJmjMuXL+ecc86hfv36JCUl0bx5cy644AICgQAAU6dORURYtWpVkTQzMzORqJmdKVOm0LNnT+rUqUOtWrXo0aMHM2fOLFf558+fz+DBg0lLSyM1NZWhQ4eyZMmSInGCwSB33303jRo1IiUlhTPOOINvv/22WFqRZQubTgJceeWViAgiwtSpUwFwzvHII4+QkZFBQkICjRo14vrrr2f37t1F0hQR7rrrLiZNmkSrVq1ISEhg8eLF5Xo2wzAMwyhCYpoKaSdeYkKZcXpDXUoAACAASURBVODxxcHAO1VL9o+z1Lx22KSi1/v9TteaRZrOpqbD+c/plgZTuqsTm17Xww1fw6VvwjmP6zpA0K0FjjJMMDPKzVlnncUxxxzDSy+9VCR806ZNzJo1i0svvTTmfcOHD2fdunU8/vjjvP/++0yaNInExERCoVCFy7Bq1SrGjx/Pa6+9xquvvkr37t0588wzee+990q9b+bMmQwePJgaNWrw0ksvMW3aNPbs2UPfvn1Zs2ZNQbzMzEweeOABRo0axZtvvsmgQYMYMWJEqWk3atSIGTNmAHDnnXeSlZVFVlYWw4cPB+Cuu+7it7/9Laeeeipvv/02t912G1OnTmX48OHF6mDq1KnMnDmTv/zlL8ycOZPGjRtXuI4MwzAMwzCqnA7nqKv+vZt0PV5ZG1+HadETznxE93i77jN16x+5iXntltC4q65HO8owG6mDzX/uIHndVyW7aD0YNDwBTp9UdrwokpKSuOCCC5g2bRqTJk3C5+0r8vLLLwNwySWXFLtn69atrFy5krfeequIgBMrbnn4y1/+UvA5FAoxePBgli9fzuOPP15kzVc0N954I/379+ett94qCBs4cCCtW7fmoYceYvLkyezYsYNHHnmEq666qiCfnj17kpKSwh133FFi2omJiXTp0gWA1q1bFzHl3L59Ow899BCXXXYZU6ZMAWDo0KHUq1ePMWPG8M477xSpF+ccs2bNIjnZXMkahmEYhnEI4/PptgIrZqkjmorQ7TI9SqLjObpNw/afiu81dwRjGjOjQlx66aWsW7eOOXPmFIS9+OKLDB48mEaNGhWLn56eTuvWrbnjjjt4+umnWbFixS/Kf8GCBZx55pk0aNAAv99PfHw8s2fPZtmyZSXes2LFCn744QdGjRpFIBAoOFJSUujZsycffvghAIsXL2bfvn2MHDmyyP0XXXRRpcv76aefkpeXx+jRo4ul6ff7mT9/fpHwYcOGmVBmGIZhGMbhQeMTof9tsTcB/yV0/JWejzJzRtOYHWxOn0TOnj2kpaVVd0kqRZ8+fWjZsiUvvvgiQ4YMYenSpSxcuLCYeWMYEWH27NlkZmZy5513sm3bNlq1asWtt97KNddcU6G816xZw+DBg+nQoQOPPvoozZs3x+/3c88997B06dIS79u8eTMA48aNY9y4ccWuN2/eHIANGzYA0KBBUVV89PeKsH37doBiQqvf7yc9Pb3gephYwq1hGIZhGMZRRa3muuXDt/+CPjdXd2kOGiaYGRVCRBg9ejSTJ0/m8ccf58UXX6RGjRqcc845Jd7TunVrXnjhBZxzLFq0iClTpnDttdfSsmVLTj/9dJKSkgDIy8srct+2bduKfH/vvffYtWsX06dPL+IRMTs7u9Qyp6erq9sHH3yQIUOGFLuekKAbLIaFok2bNtGxY8eC65s2bSo1/dKoU0c3edy4cWORNAOBANu2bSu4Hiba2YlhGIZhGMZRScdzYNZdsO0H3ZD7KOCQNWUUkd4iMktENovIHhFZKCJXRMVJEpE/i8gGEckRkSwR6RcVJ05E/uils0ZEiu3kJyIjRWS9iJSwJb0RyZgxY9i7dy8zZszgn//8J+eeey4pKWXv5SEinHjiiTz88MMABR4RW7RoUeQ7qOAya9asIveHBbD4+PiCsOXLl/O///2v1HwzMjJo2bIl3377Ld27dy92dOrUCYBOnTqRmprK9OnTi9z/yiuvlPlsiYm6GWZOTk6R8B49epCQkFAsjVdffZVAIMCAAQPKTNswDMMwDOOoo8PZej6KzBkPSY2ZiHQCPgA+Ba4EsoHzgWdFJNE597gX9f/Zu/Nwu8az8ePfO0IGiQwEEWIKQSit+TUlqigadDDWVF4/LUWrNFWtqYZSQ19DVdU862Sq1phQU7VmIuaIxBAZSIghyf37Y+2TnHNyzslKsndOkvP9XNe+9t7P86y17rWX43J7pj8COwPHAq8DhwP/jIjNM/PpSpsDgP8HHAZ0By6MiKczc2jlWl2Ac4FjMrPh+uVq0pprrsmmm27KkCFDGD16dLOrMQI8++yzHHXUUey5557069ePadOmceWVV9K+fXu23XZbADbeeGNWX311jj32WKZPn06HDh24+OKL+eyzzxqca7vttqN9+/bsv//+HHPMMbzzzjuceOKJ9O3bt8UVHiOCiy66iF133ZXPP/+cPfbYg2WWWYb33nuPRx55hL59+/LjH/+Y7t2786Mf/YjTTjuNrl27sv322/Ovf/2r2WGa9S233HIsvfTS3HjjjTMSvFVXXZWll16aY445hjPOOIMll1ySnXbaieHDh3PCCSew5ZZbzli5UZIkSfV0XwlW3KQYzrjVMa0dzXyxoPaY7QUsBnwjM2/NzHsy8/9RJGr7A0TE+sA+wI8y8w+ZeR+wB/AWcEq9c30duD4zb8zMS4B7KmV1TgJeyswban1Ti5L99tuP0aNH06dPHwYNGtRsu+WXX56+ffty7rnnMnjwYPbee2/GjBnDHXfcwYYbbggU861uvfVWVlppJQ488EAOP/xwvva1r3HggQc2ONeAAQO47rrrGDlyJIMHD+ass87izDPPZOutt27iyg3ttNNOPPjgg3z88ccccsgh7LDDDhx33HG8++67bL755jPanXTSSRx//PFcc801DB48mPvvv5/bb799tudv164dl112GRMmTGC77bZj4403nnHcaaedxrnnnstdd93FLrvswplnnsn+++/PnXfeOWNlS0mSJDUyYHd49zm440fw6MUw4i74ZPzsj1tIRWa2dgyziIjfAN8HlsrMafXK/wH0yMxNI+IXwC+A7pn5Sb02JwNDKsd+FhG3Aq9m5jGV+j8Db2fmURGxLkWyt2FmNr+sXzP69++fLa0GOHz4cNZee+1ZyictxIt/tDUL8rNq7p+vtmzo0KEOD21lPoOFi89rwTbL84mABfC/21Tw76kGJo+FG/eG91+CzycVZasNhP2L7Y/i5CBPLPc30ZrPJyL+m5kbza5dqf9dHxGnR0TfeQ+rtCsr7/8XEStERPeI+F/gq8B5lboBwBv1k7KKF4AlgH6V748D34qIfhGxIbA9RTIGcDFw/twkZZIkSZJqqEsvOORe+NkoOPZ1WHPHYm+zRVTZcVQ/BF6PiL9HxOCIqOn4q8x8HhgI7AqMBiYAFwGHZWbdKgo9K+WNja9XD3AB8CbwCvAf4A7gpojYH1gROK36dyBJkiSpKiJgyaVhmTVg8nuLbM9x2cU/egP7AocCfwNGR8RlwGWZObraQUXEGsCfKXq/DgOmUCRpl0TEp5l5XdlzZeYkYGBErAx8npnvRER34Gzge8BnEXEaxSIhQdFb94vMbHI1iYg4lOJ3oFevXgwdOrTZa3fr1o1JkybNUj5t2rQmy7XgWZCf1aefftriP39t0eTJk/1NWpnPYOHi81qwNX4+A8HntQDz76n2VnzvY/pN/ZR/3XsnUxfvApT/m1gYns8czzGLiI0pkqU9KYYM3gn8PjP/UbWgIm4BvgKslZlf1Cu/DtgBWBa4AdggM/s3OnYP4CZg3cx8oZnzXwSskJm7V4ZInkDx7zuAYcDJmfnH2cXpHLNF34L8rJxjNivH97c+n8HCxee1YHOO2cLFv6f54Pk/w5++Bz94DJZdu23OMasvM5/IzIOBVYFHKHqy7oyI1yPi8CoNc1wPeKZ+Ulbxb2BpisTsBWDViGi8gdY6wOfAq02duDLPbD/gqErRjsCfMvONzHwDuKVSVhUL4uIqWvj5z5UkSWpzuvYu3ie907px1MgcJ1ERsXpEnEWRGG0B/JVimOOjwPnAJVWI611gg4hYolH5psCnFPPIbgcWB75TL7b2FD15d2fmZ42OpZI0Xgz8KjPfqle1ZL3PXSiGNM6z9u3bM3Xq1GqcSmpg6tSptG+/QG5DKEmSVBtdly/eJ73bunHUSKn/souIxYDdKTZqHgS8B/yOYgjjmEqzGyPiIeDXVOZgzYMLKXqubo+IiynmmA0G9gbOy8zPgaci4ibg/IhYHHiDYon9VSkSxab8L0USdl69snuBX1dih2JvtKrsYtexY0cmT55Mjx49qnE6aYZJkybRsWPH1g5DkiRp/ulSl5gtmj1mZf+X+2igF/AgRXL018xsqivoKWCeJ+Rk5p8iYifgp8BlQEfgNeBw4Pf1mh5Esarir4DuwDPAjpn5ZONzRsQywOnA7o2GSF4KrA6cS9FTdgkw2/llZfTq1Yu33nqLDh060KlTJyKq0hGnNiwzmTJlCh988AF9+87PHSwkSZJa2RKdoUM3mPRea0dSE2UTs5uB32Xm8JYaZebjzMXwyGbOdRdw12zaTAF+XHnN7nwfUMxPa1w+DfhJ5VVVHTt2ZLnlluPdd9/ls89mjqz89NNP7e1YSCyIz6pDhw4st9xyC1xckiRJNdd1+bbdY5aZR9Y6kEVVt27d6NatW4OyoUOH8uUvf7mVItKc8FlJkiQtQLou3/bmmEXE1nNyosx8cN7DkSRJkqRmdO0NIx9p7ShqoqUes6FA3ZrcUe9zcxarRkCSJEmS1KS6oYyL4NZBLSVmg+p97g5cADwP3EixKuNyFAuBDKBYlEOSJEmSaqfr8jD9C/hkfGtHUnXNJmaZOazuc0RcSbE32CGNml0dEX8Evkmxr5gkSZIk1UbdXmaTF715ZmVXUNwVuKmZupsq9ZIkSZJUO117F++L4MqMZROzdkC/ZurWwPllkiRJkmqtrsdsEVyZsWxididwRkR8JyIWA4iIxSJiD4rNne+oVYCSJEmSBECXusRs0esxK7vB9JHAShTDFqdGxASgR+X4f1XqJUmSJKl2Fu8InXoskj1mZTeY/gDYKiK+BmwG9AbeAR7NzHtrGJ8kSZIkzdRl0dxkumyPGQCZeQ9wT41ikSRJkqSW1e1ltogpO8dMkiRJklpf194w6b3WjqLqSidmEXFoRDwVEZ9ExLTGr1oGKUmSJElA0WPWVvcxi4j9gQuAJ4COwBXAtcBHwGvAKbUKUJIkSZJm6Nobpk9t7SiqrmyP2dHAGcD3K98vzswDgNWAKcC4GsQmSZIkSQ3V7WW2iCmbmK0BPAhMr7yWAMjMCcBpwFE1iU6SJEmS6mvjidkUoF1mJvAuRU9ZncnACtUOTJIkSZJmsYgmZmWXy38O6AfcCzwEHB8RbwBTgZOAl2oSnSRJkiTV12W51o6gJsomZpcys5fsFxQJ2r8q3ycBu1U5LkmSJEmaVfsO0HlpmPJRa0dSVaUSs8y8qd7nVyNiALA50Bl4JDM/qFF8kiRJktRQ194w5Y3WjqKqyvaYNZCZH1P0mkmSJEnS/NV1eXi/tYOorjnZYHrJiDgyIv4UEQ9ExBqV8r0iYq3ahShJkiRJ9XRZ9BYAKdVjFhErAUOBFSkW+lgX6FqpHgRsBxxSg/gkSZIkqaG6lRmnT4N2i7VuLFVStsfsHOAzYE1gQyDq1Q0DtqpyXJIkSZLUtLrE7ONFZ6mLsonZ14ATM3MkkI3qRgN9qhqVJEmSJDWna+/i/aPRrRtHFZVNzJagWBa/Kd0o9jOTJEmSpNrr1b94f/e51o2jisomZs8C32qm7uvAf6sTjiRJkiTNxtL9ive3HmvdOKqo7HL5ZwN/igiA6ytl60TErsDBwOAaxCZJkiRJs4rKkhejapiYTR4Li3eEDl1n37YKym4w/ZeI+AFwJvC9SvHVFMMbj8jMf9QoPkmSJElq2vjXYdJ70HW56p53ygS4cEP4/BNYaVPoty2sNhCWWxfad6jutSpKbzCdmZdExDXA5sCywDjgkcxsbu6ZJEmSJNXWqMdgnV2re84nLoNPP4SND4FRj8N9pxSvdu1h2bWh9/qw1U+g56pVu+RsE7OIWAK4CTgvMx8E7q3a1SVJkiRpbrXvCG89Xt3E7Isp8Ngl0G872PmcomzSezDyYXj3WXjnWXj+LzB2BHzvbmhXdtmOls32LJn5OcUG0tW5oiRJkiRVQ58N4a1Hq3vOp6+DTz6ALY6eWdZ1OVj3m7DdSbDfX4qE7e0n4Nkbq3bZssnWw8BmVbuqJEmSJM2rvpsVvViff1yd802bCo9cAH02glW2bL7dl/aCFTeGe06ETz9qWPfZZPhsEmTj7Z9bVjYxOwY4OCKOiIgVI2KxiGhX/zVHV5UkSZKkebXSZjB9Koyu0u5dw2+FCW/ClkfPXPmxKe3awdfPgo/HwrBfF2XTp8OjF8FZq8EZK8KvloXfrFn60mUX/6jbue23lVdjOQfnkiRJkqR5t9LGQBT7ma269bydKxP+dT4svQb033n27ft8Bb6yHzxemY/2r/PgjWGw5tdh5c3hk/EwZTzwSqnLl02mTqFIviRJkiRpwdCpR7FKYjU2mn5jWDEscvAF5Rf0+OqJ8MKtcM1usHhn+Mb/wVf2b9TbdmGpU5Xdx+ykcpFJkiRJ0nzUdzN49haYPg3aLTb353l9KLRbHNbbo/wxSy4Du5wLz94MO54BS68+15d3bpgkSZKkhVffzeHzSfD+i/N2nvdfgqX7weId5+y49b4N+948T0kZmJhJkiRJWpittGnxPq/DGccOh2XXmvd45pKJmSRJkqSFV/e+0HWFYiji3Pr8Y5gwEpZdp2phzSkTM0mSJEkLrwhYf0946U5455m5O8fYEUBCL3vMJEmSJGnubHE0dOpebPg8N8a+VLwvu3b1YppDJmaSJEmSFm6dusPWx8HrD8Cr98358e8Ph8WWgB6rVj+2kkotlx8R+7dQPR34EHgqM9+uSlSSJEmSNCc2PrjY7PmeE2G1QeX3IoOix2yZNWGxsts8V1/ZK1/JzA2m6++WVr9sekTcBByUmZ9XJzxJkiRJKqF9B/jqL+HPB8NzN8P6e5U/9v2XYKVNahdbCWXTyC2AkRTbVm8DrFV5vxh4C9gZGALsDpxU9SglSZIkaXYGfBN6bwD3nQpffFrumM8mwYdvter8MiifmP0EuDEzj8rMhzLz5cr7D4EbgEMz8zfAOcAcpKaSJEmSVCXt2sH2p8JHb8O/f1/umLEjiveFJDHbHmhuFt39wFcrnx8E+sxrUJIkSZI0V1bdGtbYHh48Bz4ZP/v27w8v3ltxqXwon5h9BmzYTN2GQN2csnbAx/MalCRJkiTNte1Ohs8nwUPnzL7t2JegfUfosUrNw2pJ2cTsFuDkiDgmIlaOiE6V959QzCm7qdJuA2BEDeKUJEmSpHKWWwfW3wf+fSlMGNly2/eHFysytlts/sTWjLKJ2Y+BPwNnAa8Dkyvvvwb+BBxTafc88NMqxyhJkiRJc2bQ8RDt4P5ftdzu/eGtPr8MSi6Xn5lTgO9GxCnApkBv4B3g35k5ol67O2sSpSRJkiTNiW59YLMfwL/OpcuGmwIDZ20zZSJMGrPwJGZ1MvNl4OUaxSJJkiRJ1bPl0fDkVWzw9C+g85giUVtymZn1dSsy9mr9xGwOtsOGiFg+IjaJiK0bv2oVoCRJkiTNlY7d4KC7GN/zy/DQuXD+enD3CcXeZQBjKysyLtu6KzJCyR6ziOgDXEOxqTRAANnoc+vOlpMkSZKkxnr158UBx7HsgN7FKo2PXAgv3ga7XwLvvwSLd4ZufVs7ytJDGX8HrAccBzxHsXy+JEmSJC0cevWHb14KGx4EfzsMrtip6FHr1b/YmLqVlU3MtgKOzMxrahmMJEmSJNXUypvDYQ/DPb+A/1wOy3+ptSMCyidmU4D3axmIJEmSJM0XHbrALufBRgfDUiu0djRA+cU//gDsV8tAJEmSJGm+Wn5d6NyztaMAyveYjQb2i4j7gLuA8Y0bZObl1QxMkiRJktqKsonZJZX3VYBBTdQnYGImSZIkSXOhbGK2ak2jkCRJkqQ2rFRilpkjax2IJEmSJLVVrb9g/2xExE4R8WBETI6IjyLiPxGxbb36HhFxWUR8EBEfR8S9EbFeo3N0jog/RsT4iHgtIvZs4jrHRcQzEVG2F1GSJEmSqqLZJCQiXgd2z8xnIuINinlkzcnMXL3awUXE/wMurLxOpUgkNwA6V+oDuJ1i7tsPgQnAz4AHImKDzHy7cqohwNeAA4EvAddExJOZ+UrlPCsCJwA7ZubUat+HJEmSJLWkpd6hYcBH9T63lJhVXUSsApwPHJuZ59er+me9z4OBLYBtM/OBynGPAm8AxwFHVtp9HbgwM28DbouIfYHtgFcq9ecDt2TmI7W5G0mSJElqXrOJWWYeVO/zgfMlmoa+B0xn5oqQTRkMjKlLygAy88OIuB3YlZmJ2RIUm2TX+QToCBAROwIDgf5Vi1ySJEmS5sCCPMdsS+AlYK/KvLCpEfFqRBxer80A4Pkmjn0B6BsRXSrfHwcOiIjeEbEDxXDIxyKiA3ABMCQzx9XuViRJkiSpeaUXuoiIpYCdgL5Uepvqycw8tZqBAStUXmcDxwOvAd8BLoyI9pn5W6An8GYTx9ZtgN0DmAycTLEx9phK+dmZ+WhE/BIYC/yxyrFLkiRJUmmROfupYxGxBcUiG92baZKZuVhVA4t4GVgD+FZm/qVe+V3Al4HewAjgyczcq9GxhwB/APpm5qhKWQCrARMzc1xErAY8Q9Ez9wpwLrA7xTDHczPzgmbiOhQ4FKBXr14b3nzzzXN8b5MnT6ZLly6zb6hW57NauPi8Wp/PYOHi81qwNX4+AwcNYugDD7RwhFqTf0/z36Bhg3hgm3J/E635fAYNGvTfzNxodu3K9pidT9Ez9b/Ac5n5+TzEVtY4isTsnkbldwM7UiRmEyh6xRrrWXmfUFeQRQb6Wr02FwCXVVadPA3YCFgX6AM8FBEvZuZ9jU+cmZcClwL0798/Bw4cOMc3NnToUObmOM1/PquFi8+r9fkMFi4+rwVbU8/H57Xg8u+pFQwr/zexMDyfsnPM1gZOyMz/zqekDIp5Yi2ZXmkzoIm6dYC3MnNyUwdGxG4U88x+WSnaEbgqM8dm5tPMTP4kSZIkqebKJmZvAR1qGUgT/lp536FR+Y7A25n5LnAb0CcitqmrrMyF+0albhYR0Rn4LfCjzJxUr2rJep+7ADFv4UuSJElSOWWHMp4MDImI+zLzo9m2ro6/Aw8Av4+IZYDXKRb/2B6oW8r/NuBR4NqIOJaZG0wHcFYz5/0FMCIz608Ouxc4IiJeolhw5KvAOdW9HUmSJElqWrOJWURc3ahoOeCNygbO4xvVZWYeUM3AMjMrQw7PoEgMe1Asn79vZl5faTM9InYBfgNcTLFa5KPAoLpFPxrd01rA4cCGjapOBZYFLqfY72xIZt5dzfuRJEmSpOa01GO2NVB/ycYEPqLpOV2zX9pxLlR65w6vvJprM55iM+rvlTjfS8BSTZRPZmYvnCRJkiTNV80mZpm5ynyMQ5IkSZLarLKLf0iSJEmSaqRUYhYRB0XESc3UnRQRVZ1fJkmSJEltSdkes6MoNnxuyvvA0dUJR5IkSZLanrKJWT+a3/B5OLB6dcKRJEmSpLanbGI2FVimmbpeVYpFkiRJktqksonZv4HDmqk7DHiiOuFIkiRJUtvT0j5m9Z0G3BsRjwOXAaOBPsAhwFeAr9UmPEmSJEla9JVKzDJzWER8Gzgf+H29qjeBb2Xm0OqHJkmSJEltQ9keMzLzVuDWiOgPLA18kJkv1ywySZIkSWojSidmdTJzRC0CkSRJkqS2ao4Ss4hYH+gPdGxcl5lXVysoSZIkSWpLSiVmEdEduBPYrK6o8p71mpmYSZIkSdJcKLtc/ukU88q2pkjKdge2Ba4DXgc2qUl0kiRJktQGlE3MdqBIzh6rfH87M4dm5v7AvcBRtQhOkiRJktqCsolZb+D1zJwGfAp0rVf3F2DnagcmSZIkSW1F2cTsXaB75fNIYPN6df2qGpEkSZIktTFlV2X8F8XCH3cA1wAnRsQqwFTgAOC2WgQnSZIkSW1B2cTsZGCFyuezKRYC2RPoTJGU/bD6oUmSJElS21AqMcvM14DXKp+/AI6pvCRJkiRJ86jsHLMZIqJLRKwcEYvXIiBJkiRJamtKJ2YRsUtEPAl8SLF32XqV8ssiYp8axSdJkiRJi7xSiVlE7AbcCnwA/JRik+k6b1AsACJJkiRJmgtle8xOBK7IzO2B8xvVPQ+sW9WoJEmSJKkNKZuYrQ3cVPmcjeomUKzSKEmSJEmaC2UTs4+AZZqpWwUYW5VoJEmSJKkNKpuY3QP8LCK61yvLiOgAHAHcVfXIJEmSJKmNKLvB9M+BfwMjgL9TDGccAnwJ6AbsVpPoJEmSJKkNKNVjlplvAl8B7gC+BkwDtgYeAzbNzDG1ClCSJEmSFnWleswiohswNjMPrnE8kiRJktTmzLbHLCLaA+OA7WsfjiRJkiS1PbNNzDJzKvAexfBFSZIkSVKVlV2V8VrgkFoGIkmSJEltVdlVGd8E9omIJ4BbgXdotNF0Zl5e3dAkSZIkqW0om5hdVHnvA2zYRH0CJmaSJEmSNBfKJmar1jQKSZIkSWrDSiVmmTmy1oFIkiRJUltVdvEPSZIkSVKNmJhJkiRJUiszMZMkSZKkVmZiJkmSJEmtzMRMkiRJklpZqVUZI6Id0C4zp9Yr2wFYF7g/M5+qUXySJEmStMgru4/ZDcBnwP4AEXEYcHGl7ouI2Dkz761BfJIkSZK0yCs7lHEz4O/1vh8LXAZ0A/4C/LzKcUmSJElSm1E2MVsWGA0QEf2AVYELM3MScAWwXm3CkyRJkqRFX9nE7CNg6crngcAHmfls5fs0oGOV45IkSZKkNqPsHLNHgCERMRU4mobDGvsBb1c7MEmSJElqK8r2mB1H0WN2G0Xv2En16vYEHq1uWJIkSZLUdpTqMcvMV4A1ImLpzBzXqPoo4N2qRyZJkiRJbUTZoYwANJGUkZnPVS8cSZIkSWp7SidmEbEasAfQl1kX+8jMPLiagUmSJElSW1EqMYuI3YCbKeakvU+x2XR9WeW4JEmSJKnNKNtjdiowFNg3M8fWLhxJkiRJanvKJmarW60UeAAAIABJREFUAceYlEmSJElS9ZVdLv8lZm4wLUmSJEmqojnZx+z4ygIgkiRJkqQqKjuU8SSKHrPhEfEKML5RfWbmNtUMTJIkSZLairKJ2TRgRC0DkSRJkqS2qlRilpkDaxyHJEmSJLVZZeeYSZIkSZJqpHRiFhG9I+I3EfFERLxWeT8rIpavZYCSJEmStKgrlZhFxJrA08CRwGTg35X3o4CnI2KNmkUoSZIkSYu4sot//Br4CNg0M9+sK4yIlYG7K/XfrHp0kiRJktQGlB3KOAj4Rf2kDCAzR1IspT+oumHNKiL+EREZEb9qVN4jIi6LiA8i4uOIuDci1mvUpnNE/DEixleGYe7ZxPmPi4hnIqJssipJkiRJVVE2MVsCmNRM3aRKfc1ExN7A+k2UB3A7sCPwQ+BbwOLAAxGxYr2mQ4CvAQcCVwDX1B9+WWl7AvD9zJxao9uQJEmSpCaVTcyeBn4YEQ3aVxKjH1TqayIiegDnAT9uonowsAWwX2bekJn/qJS1A46r1+7rwIWZeVtm/gp4DdiuXv35wC2Z+Ugt7kGSJEmSWlJ22N4pwB3A8Ii4CXgHWB74DrAGsHNtwgOK+WvPZ+YNEXF9o7rBwJjMfKCuIDM/jIjbgV0pFiuBokdvSr3jPgE6AkTEjsBAoH9twpckSZKklpXqMav0RO1CMWzx58BFFEP/JgO7ZObdtQguIrYE9gcOb6bJAOD5JspfAPpGRJfK98eBAypL/u8AbAA8FhEdgAuAIZk5rrrRS5IkSVI5kZlzdkBEZ6AHMCEzP6lJVMV1lgCeAv6amSdUyhI4rd73l4EnM3OvRsceAvwB6JuZoyKiD3AXULcoyNmZeVxE/JJiftoWWfKHiIhDgUMBevXqteHNN988x/c2efJkunTpMvuGanU+q4WLz6v1+QwWLj6vBVvj5zNw0CCGPvBAC0eoNfn3NP8NGjaIB7Yp9zfRms9n0KBB/83MjWbXbo5XIKwkYzVLyOo5DugEnDavJ8rM0RGxPrAaMDEzx0XEasCxwJZAp4g4F9id4t7OzcwLmjnXpcClAP3798+BAwfOcTxDhw5lbo7T/OezWrj4vFqfz2Dh4vNasDX1fHxeCy7/nlrBsPJ/EwvD82k2Mav0Jl2WmWMqn1uSmXlqtYKKiL4UQyYPATpUhhzW6RAR3SmGVU6g6L1rrGflfUL9ACkW/ahzAcX9PRMRpwEbAesCfYCHIuLFzLyvWvckSZIkSc1pqcfsJOAfwJjK55YkULXEjKJnqyNwbRN1P6m8vkwxl2z7JtqsA7yVmZObOnlE7EYxz6xuCOSOwJWZORYYGxF3V8pMzCRJkiTVXLOJWWa2a+rzfPI0TW9a/QBFsvZH4FXgNuCgiNgmM4cBRMRSwDeAxis4UqnvDPwW+FFm1t+bbcl6n7sAMa83IUmSJEllzPEcs/khMycCQxuXF9umMTIzh1a+3wY8ClwbEcdSDF38GUVSdVYzp/8FMCIz66/acS9wRES8BKwAfBU4pxr3IkmSJEmzUyoxi4g1ge6Z+e/K907ALynmZP0zMy+sXYjNy8zpEbEL8BvgYorhj48CgzJzVOP2EbEWxdL7GzaqOhVYFricYr+zIbXaAkCSJEmSGivbY3YhxfDCf1e+nwYcATwHnBcRmZkX1SC+BjJzluGFmTke+F7lNbvjXwKWaqJ8MnBQNWKUJEmSpDlVdu7Y+sDDABHRjmLT559m5obAr6js6yVJkiRJmnNlE7NuwLjK5y9TLFH/p8r3oRSrKEqSJEmS5kLZxOw9oF/l8/bAa/XmcHUBplY7MEmSJElqK8rOMbsNOCMi1gUOBH5fr2494PUqxyVJkiRJbUbZxGwIxYqHO1AkaafVqxsMuIKhJEmSJM2lUolZZn4M/G8zdf9T1YgkSZIkqY0pu49ZO6BdZk6tV7YDxT5m92Xm0zWKT5IkSZIWeWWHMt4AfEaxTD4RcRjFhs4AX0TEzpl5bw3ikyRJkqRFXtlVGTcD/l7v+7HAZRTL6P8F+HmV45IkSZKkNqNsYrYsMBogIvoBqwIXZuYk4AqKlRklSZIkSXOhbGL2EbB05fNA4IPMfLbyfRrFio2SJEmSpLlQdo7ZI8CQiJgKHE3DYY39gLerHZgkSZIktRVle8yOo+gxu42id+ykenV7Ao9WNyxJkiRJajvK7mP2CrBGRCydmeMaVR8FvFv1yCRJkiSpjSg7lBGAzBwXEV0oes/GZOYXmflcbUKTJEmSpLah7FBGImKXiHgS+BB4jcpKjBFxWUTsU6P4JEmSJGmRVyoxi4jdgFuBD4CfNjruDeCA6ocmSZIkSW1D2R6zE4ErMnN74PxGdc8D61Y1KkmSJElqQ8omZmsDN1U+Z6O6Cczc40ySJEmSNIfmZIPpZZqpWwUYW5VoJEmSJKkNKpuY3QP8LCK61yvLiOgAHAHcVfXIJEmSJKmNKJuY/RxYHhgBXEYxnHEI8DSwIg03nJYkSdVy0knw3e+2dhStZ+xYWGstmDKltSOpnWOOgd/9rrWjkNTKSiVmmfkm8BXgDuBrwDRga+AxYNPMHFOrACVJWqR16TLz1a4ddOo08/t119X00ivdeCOsuy507Qqrrgpnn9184zffhAj48pcbln/wASyxBKyySm2CPPNMOPDA4ncZMGDmb7PYYtCx48zvp58Od94JW24J3bvD8svDIYfApEkzz3XzzfA//wOdO8PAgQ2v89BDDZ9Fly7F/f75z0V9JpxwAvTpA926Fce/8MLM43/yE1hjjeK3XGstuPrqhuePgCWXnHnuQw5peOzpp8Pnn1fxh5O0sCm9j1lmvp2ZB2fmipm5RGb2zsyDMnNULQOUJGmRNnnyzFffvnD77TO/77tvba+dWSQQEybAP/4BF14IN97Y8jGffALPPz/z+/XXF0ldLXz2GVx11cwewxdemPnbbLVVEW/d9+OPhw8/LJKnMWNg+HAYPRqOPXbm+Xr2hKOPhiFDZr3WVls1fBZ33FEkUDvuWNTfcgtcfnmRwI0fD5tvDvvtN/P4JZcsnt2HHxYxH3UUPPJIw2s888zM81922czy3r2LZO6226rzu0laKJVOzBqLiHUi4lsRsUI1A5IkSY18/jnsv3/RGzNgAPznPzPrIuDVV2d+P/DAIjkpYdTee8NXvgLt20P//rDrrvDwwy0ftN9+ReJR5+qri9jqO/NMWH31It511oG//nXmffTsCc89N7Pt++8XPVhjm1hH7PHHi96vFVcsdT/ss0+RSHXuDD16wP/+b8P72W472GMPWKHEf7pcdRV8+9tFwgXwxhtFb9xqqxW9dd/9Lrz44sz2J59cJFft2sGmmxaJ3qOPlosbih64O+8s317SIqfsBtMXRsQl9b5/E3gWuAV4MSI2rlF8kiTptttgr71g4kQYPBiOOKL618gseoMGDGi53Xe/W/SqTZtWJCaTJxeJSH2rr16c68MP4cQTi2PeeacY8rjXXnDttTPb3nADfPWr0KvXrNd67rkiYZxbDz44+/tpyscfw5/+BAccMLNsr73gtdfg5Zfhiy+KxK2uN62xKVPgiSdmvfbWWxdDLL/5zWJoaH1rr130qElqs8r2mH0dqN8ffzJwO7A+8G+KDaglSVItbLkl7LRT0VOz3361+Q/4k06C6dPhoINabrfiikWydO+9RW9Z/eF8db7znaJXql072HPPYu7Vv/9d1B1wQJGMZWVb1GuuafocUCSiXbvO3f3cc0+RPJ1yypwf+5e/wDLLwDbbzCzr3bt4Dv37F/PdbrkFzjuv6eMPOwzWXx922GFm2bBhRTL20kvFb7PLLjB16sz6rl2L+5XUZpVNzHoDbwJExIrAAOCMzHwO+D/AHjNJkmpl+eVnfu7cGT79tOF/1M+rCy8skqw774QOHWbffv/94coriwSrqaTq6qthgw2KYYjduxdz0j74oKjbdNPiHoYOLZKUV18tegGb0qNHw8U7ynrssWJY45/+BGuuOefHX3VVcY8RM8tOOaXoBRs1qvj9TzwRtt22mHNX37HHFvd7880Nj99666LHsHt3+O1vi6GRw4fPrJ80qaiT1GaVTcw+AbpUPm9DseF03QD3ycBc/u8sSZI0Tzp3bpgcvPvunB1/+eXFnLD77is/l+tb3yqSuNVWKxYsqW/kyGJu14UXwrhxRS/QuuvO7CGDotfs2muL3rJvf7tYXbEpX/pSMXRwTjz1VJHoXX55MURyTo0aVSSNjefNPf100fu34orFnLwDDywWTak/z+zEE+Guu+Duu2GppVq+TkTD32T48KKXTVKbVTYxexI4PCLWBQ4H7snM6ZW6VYF3ahGcJEmajQ02KFZGnDatWFlx2LCG9RFFotGEZe+5p1jN8J57iiSrrCWXhPvvb7iyYJ2PPy6uWTdn7IorGq7iCMWcs7/+tUjOGidA9W2ySZHYjR5dLq7nny/mfV1wAXzjG7PWT5s2s7dx+vTi8xdfNGxzzTXFkvqrr96wfOONi+GL771XHHvNNcWx/foV9WecUTyHe++FpZdueOwLLxSJ3bRpxZy8Y44plt1fe+2ZbYYNg69/vdx9SlokzckG05sBzwD9gVPr1e1GMc9MkiTNb7/9bbFMe/fuxb5nu+02s27UqGLu0nrrNXnoqpdfXvRqbbzxzP21Djus3HU32mjW5AWKVRiPOaZYTn655YoFPLbYomGblVYqVoOMKFYvbM4SSxQ9U/UXC2nJOecUqzsefPDM+6m/AMc11xTzw77//WJxkk6dit69+q6+uuGiH3V++tOiR6tuiOZ55xV7nNUNPzz+eHjrrSJRq7+3GhTJ3J57Fr1oq61WzDW74w5YfPGi/p13ip63+s9OUpvTvkyjzHwiIvoCawGvZOZH9aovBV6pRXCSJLUpjVfqg2JRjvpWWaXhELiNNmq40XF9w4bB4YfP2oNT8fgNNzCw8UbLzWl83fq2265h7KedVrxa0rcvbLZZw3lYTTnuuCJ5O/LIIpGq01Qv4BVXFK/mHHhg8WrJSy81Xd6xI1x0UfFqSnO/DRRz0UaMaL7+N78pErsllmg5NkmLtFKJGUBmfgz8t4lyN92QJGlBVLcx84LmzTeLlQ+femr2bXv1aj5ZWlScc05rRyBpATDXG0xLkiTNsV/8olgM5NhjYdVVWzsaSVpglO4xkyRJmmennlq8JEkN2GMmSZIkSa2s2cQsIpaKmN2MXEmSJEnSvGqpx2wCsDFARNwfEWvNn5AkSZIkqW1pKTH7HKhssMFAYDZb2EuSJEmS5kZLi3+8AhwfEbdUvu/UUq9ZZl5d1cgkSZIkqY1oKTH7OXAt8HUggV+20DYBEzNJkiRJmgvNJmaZeXtE9ARWBN4Avg08M78CkyRJkqS2osV9zDJzGjAyIk4GHsvMMfMnLEmSJElqO0ptMJ2ZJwNUls9fB+gJjAdezMysXXiSJEmStOgrvcF0RBwCvAM8CwytvI+JiINrE5okSZIktQ2leswiYl/gUuA+igVB3gWWB/YFLo2ITzLzhppFKUmSJEmLsFKJGXAccF1m7teo/KqIuAb4KWBiJkmSJElzoexQxv4UPWVNubZSL0mSJEmaC2UTs0kUy+Y3ZcVKvSRJkiRpLpRNzO4CTo+IreoXRsTmwK8q9ZIkSZKkuTAnc8w2A4ZGxGiK1RmXp+gte7VSL0mSJEmaC2X3MXs3IjYAvgdsRbGP2ZvAMODKzPykZhFKkiRJ0iKubI8ZleTrwspLkiRJklQlpTeYliRJkiTVhomZJEmSJLUyEzNJkiRJamUmZpIkSZLUykzMJEmSJKmVlV6Vsb6I6EGxr1kAj2Xm+KpGJUmSJEltyBwnZhGxDfBXYDrQAZgaEd/OzPuqHZwkSZIktQVzM5TxPODHmbkM0AO4ATi/qlFJkiRJUhvSbGIWERdERNcmqlYBbgTIzKnAX4CVaxKdJEmSJLUBLfWYrQaMiIh9GpU/DpwXEetExCbA8ZUySZIkSdJcaDYxy8ydgcOB0yPivohYs1J1GPAl4HngMaAz8P+qHVhEfDsi/hwRIyNiSkSMiIgzGvfiRUSPiLgsIj6IiI8j4t6IWK9Rm84R8ceIGB8Rr0XEnk1c77iIeCYi5mpBFEmSJEmaWy3OMcvMvwJrA08A/4mI04D3MnMLYCmgW2Zulpmv1yC2nwDTKHrkdgR+B3wfuCci2gFERAC3V+p/CHwLWBx4ICJWrHeuIcDXgAOBK4BrImKNuspK2xOA71eGZ0qSJEnSfDPb3qHMnAIMiYirgAuAFyPiyMy8o8axfSMzx9b7PiwixgNXAQOB+4HBwBbAtpn5AEBEPAq8ARwHHFk59uvAhZl5G3BbROwLbAe8Uqk/H7glMx+p7S1JkiRJ0qxa7DGLiHYR0T8i1gfeyMztKHqWfh8Rt0bESrUKrFFSVueJynufyvtgYExdUlY57kOKXrRd6x23BDCl3vdPgI4AEbEjRaJ3XFUClyRJkqQ51NKqjF8CXgKGA08Bb0fE7pl5PbAWRa/UcxHx0/k4L2ubyvvwyvsAirlujb0A9I2ILpXvjwMHRETviNgB2AB4LCI6UPQCDsnMcTWMW5IkSZKaFZnZdEXEY8BIirlbU4BjKq9lMvOzSpv1gYuAHpk5oKaBRvShSBCfycyvVcpeBp7MzL0atT0E+APQNzNHVY69C6hbFOTszDwuIn5JMT9ti2zuh5g1jkOBQwF69eq14c033zzH9zJ58mS6dOky+4ZqdT6rhYvPq/X5DBYuPq8FW+PnM3DQIIY+8EALR6g1+fc0/w0aNogHtin3N9Gaz2fQoEH/zcyNZteupcTsI2D3zLyv8r07MB5YKzNfbtT2oMy8Yt7DbibIoudrKLACsElmvl0pL5WYVcqCYguAiZk5LiJWA54BtqSYa3YusDvFMMdzM/OC2cXVv3//HDFixBzfz9ChQxk4cOAcH6f5z2e1cPF5tT6fwcLF57Vgm+X5REC5/4+sVuDf0/wXJwd5Yrm/idZ8PhFRKjFraQjiExSLfkwEPgWOAMYBs6zAWOOkrBPFnLHVgG3qkrKKCUCPJg7rWa++LsYEXqvX5gLgssx8prLa5EbAuhTz1x6KiBfrklJJkiRJqqWWFv84GOhAkaA9B2wLfHt+LicfEYsDf6JImnbKzOcaNXmBYp5ZY+sAb2Xm5GbOuxvFPLNfVop2BK7KzLGZ+TRwd6VMkiRJkmqupQ2m38zMrYEuQM/M7J+Zw+ZXYJW9yq6jSAh3y8zHmmh2G9AnIrapd9xSwDcqdU2dtzPwW+BHmTmpXtWS9T53AWLe7kCSJEmSyimzj9knFPOu5reLgO8ApwEfR8Rm9erergxpvA14FLg2Io6lGLr4M4qk6qxmzvsLYERm1l+1417giIh4iWIe21eBc6p5M5IkSZLUnPm1zP3c+Hrl/eeVV30nAydl5vSI2AX4DXAxxd5kjwKD6hb9qC8i1gIOBzZsVHUqsCxwOcUKlEMy8+5q3YgkSZIktWSBTcwyc5WS7cYD36u8Ztf2JWCpJsonAwfNYYiSJEmSVBUtLf4hSZIkSZoPTMwkSZIkqZWZmEmSJElSKzMxkyRJkqRWZmImSZIkSa3MxEySJEmSWpmJmSRJkiS1MhMzSZIkSWplJmaSJEmS1MpMzCRJkiSplZmYSZIkSVIrMzGTJEmSpFZmYiZJkiRJrczETJIkSZJamYmZJEmSJLUyEzNJkiRJamUmZpIkSZLUykzMJEmSJKmVmZhJkiRJUiszMZMkSZKkVmZiJkmSJEmtzMRMkiRJALz14Vt0Ob0L06ZPa+1Qqm6Ly7fgqXeeau0w5ouBVw7ksicvm+fzXPn0lWx5+ZZViGjOxMnBq+NfBeCYfx7D75743XyPoTWYmEmSJC3CVjl/FTqd1okup3eZ8RozaUyTbft268vk4yezWLvFZnvel8e9zK437kqvs3vR89c92eHaHRjxwYgZ9ZnJCfefQJ9z+9DtzG4MvHIgL7z/QrPnq1Yy0ZTbR9xO1yW68uXeX25QfuXTVxInBzc9f1OTx53x0Bkcf9/xDH1zKO1Objfj9+tzbh9OfODEZq/35sQ3iZODqdOnznPsB/7tQE64/4R5Ps/C6if/8xNO/9fpfD7t89YOpeZMzCRJkhZxt+99O5OPnzzjtULXFWZpM6dJxMRPJzJ4zcGMOGIE7/3kPTZZYRN2vXHXGfW3vHgLlz91OQ8d9BDjjxvP5ituzn5/3W+e72VuXPLfS9jvS7Ne+6pnrqJnp55c/ezVTR535yt3stMaOwGwQtcVZvx+/zroX/zxqT/yt5f+VtO4Bb279matZdbithG3tXYoNWdiJkmS1AbV9er88ck/0ve8vmx71bZz1NOzSZ9NOPgrB9OzU08WX2xxfrT5jxgxbgTjPhkHwBsT3mDLvluyWo/VWKzdYnz3S9/lxbEvloqtqSF09Ye3Hfi3Azn8zsPZ+fqd6XpGVza9bFNeG/9ak+f6fNrn3P/G/WyzyjYNykdOHMmwN4dx6S6X8s9X/8m7k99tUD9hygReHvcym6+4+SznXLXHqvzPSv/T7P1sfcXWAHQ/sztdTu/Co6MeBeDypy5n7YvWpseve7DDtTswcuJIoOhd/NE/fsSyZy/LUmcsxXq/W4/n33+eS/97Kdc9dx1nPXwWXU7vwjdu+EaT17vntXtY68K16HZmN474+xEk2aC+uevW/a7/9/j/sdpvV2OZs5bh2LuPZXpOb/I6j4x6hI3/sDHdzuzGxn/YmEdGPQLALS/cwoaXbtig7bmPnjsjUf9s6mf85O6f0Pe8viz3m+U47I7DmPLFlBltz374bHqf05sVzlmBy5+6fJbrDlx5IHe+cmeTMS1KTMwkSZLasGEjhzH88OH887v/nKfzPDjyQZbvsjxLd14agL3W3YvXJrzGy+Ne5otpX3DVM1exY78dqxEyADe+cCMnbnMiE346gX49+/Hz+3/eZLtXxr1Cu2jHikut2KD86meuZqMVNuJb63yLtXutzXXPXteg/p+v/ZOvrvbVJod1vjLuFR4e9TCbrbhZk9d88KAHAZg4ZCKTj5/M5ittzq0v3crpD53OX/b4C2OPHctWfbdi7z/vDcDdr93Ng289yMs/fJkPh3zIzd++maU7Lc2hGx7Kvuvty3FbHMfk4ydz+963z3KtDz75gG/e/E1+te2v+ODYD1i9x+o8/NbDM+pbum6dv770V/5z6H948v89ya0jbm0yORo/ZTw7X78zR25yJOOOG8ePN/sxO1+/M+M+Gcfg/oN5Y8IbDB87fEb7a569hv2/tD8AQ+4dwsvjXubpw57m1R++yuhJozll2CkA/OPVf/CbR3/DPfvdwys/fIV7X793lmuv3Wttnnn3mSZ/60WJiZkkSdIibrcbd6P7md3pfmZ3drtxtwZ1Jw08iSWXWJJOi3ea6/O//dHbHP73wzl3+3NnlPXu2pstV9qS/hf2p9NpnbjlxVs4b4fz5voaje2+1u5s0mcT2rdrz77r7cvT7z7dZLuJn06k6xJdZym/+tmr2We9fQDYZ919ZhnOeOcrd7JTv51mfB8zaQzdz+zOUmcsxZoXrsmmfTZly77lF8a45L+X8LMtf8bavdamfbv2HL/V8Tz97tOMnDiSxRdbnEmfTeKlD14iSdbutTa9u/Yudd6/v/J3BvQawLfX+TaLL7Y4R292NMt3Wb7Udev8dIuf0rNTT/p268vRmx3NDc/fMMt17nz5TtbouQb7rb8f7du1Z+/19matZdbi9pdvp0P7Duw5YE+uffZaAF54/wXenPgmu6y5C5nJpU9eynk7nEfPTj3p2qErx295PDe+cCMAN79wMwdtcBDrLrsuSy6xJCcNPGmWa3ddoisTP51Y+rdeWJmYSZIkLeL+ttffmDhkIhOHTORvezWcF7XSUivN07nHfjyW7a/Znh9s9AP2Xm9mT8wpw07hiTFPMOpHo/j0hE85cZsT2fbqbfnki0/m6Xp16icfnRfvzOTPJzfZrkenHkz6fFKDsoffepg3JrzBXuvuBcA+6+3Dc+89NyO5m57Tuee1exr08K3QdQUmDpnIRz/7iIk/nUinxTtxwN8OKB3vyIkjOeofR81IkHv+uidJMnrSaLZddVuO2OQIDv/74Sx79rIcevuhfPTZR6XOO2bSGFbqNvMZRkSD7y1dt079fwZW7rZyk4vDjJk0hpW7r9ygbOVuKzP6o+I8B2xwANc/fz2ZyTXPXsMe6+xBh/YdGPvJWD754hM2vHTDGTHseN2OjP147Mz4G12/sUmfT6J7x+6lfo+FWfvWDkCSJEmtJyLm+tgJUyaw/bXbM7j/YH6+dcOhhE+/+zR7DthzxhDCAzc4kKP/cTQvjn2RjVbYqMXzLrn4kg0SuMbzv+ZEv579yExGfzSaPkv1AYpFP5Jkg0s2aND2qqevYoMdN+CJ0U+wcveV6bVkrybP2a1jN/ZZdx/2/NOeTdYHs/6mK3VbiZ9v9XP2/dK+TR5z5KZHcuSmR/L+x++zxy17cPbDZ3PqtqfO9vn07tKbUR+OmvE9Mxt8n911AUZ9NIoByw4Aii0TmlocZoWuKzBy+MgGZW99+NaM5HWzFTdjicWW4KG3HuL6567n+m9dD8AynZehU/tOvPCDF2b8/g3i79qbUR+NanDOxoaPHc76y6/fbPyLCnvMJEmS1KSThp7EwCsHNln30WcfscO1O7DFSltw5nZnzlK/8Qobc8uLt/De5PeYntO55plr+GL6F/z/9u49bqqq3uP456tiiogXNG9HMAMsb0hqByOPxcESUdFKRFM0DbXS8pIHPVpSeQMjvBwkL0dNxbuCYqZgIuUFw4oS8IIpXgCPiIgIiiK/88faDw7DAA8PM89+Zub7fr3mNc/sy1prP+u1ZvZvr7XX7rh5x9Xm22XrLkydM5XJb07mwyUfMuixQU0+hvXXXZ+eO/ZkwqsTAPhwyYfcOfVOrjnoGiafPHnZ68peV3LUnUrGAAAT4klEQVTrlFtZsnQJD05/kN6deq80zfc/ep/bp96+LJgptuVGW7KO1uHleS8vW3bynidz8eMXL3tkwPwP53PX1LsAmDRzEk+/8TQff/IxG7XaiA3W24B1lE7Tt9poq+XSKda7c2+mzpnKvc/dy5KlS7ji6SuWC2RXlW+DS5+8lHkfzOP1+a9z+dOXc8QuKwacB3Y6kBfnvsitz6b/0R1T7mDanGkc1PmgZdv0370/pzx4Cq3WbbVsmOc6WocBXxrA6Q+fzlsL3wJg5nszefildE9j3537cuPkG5k2ZxqLPl7ELyb8YoW8J7w6gV4de630f1ArHJiZmZmZWUmvz3+d7tt3L7lu1HOjmDRrEjdMvmG5Z6Q19HgM/OpAumzVhT2u3oNNL9mUYROHcU/fe1Y5JK2hp6lzu878/D9+Ts+betLpyk5rdC9XKSfteRI3//NmAEY/P5oNW21I/y792brN1stex3c9niVLl/DQSw8tN01+g1kLZi07xg6XdeCdD95h5LdGlsqO1q1ac+6+59L9+u5sesmmTHxjIod98TAGdh9Iv3v60fbituw6Ylf+8NIfgBTkDhgzgM0Gb0aHyzrQrnU7zup+FgAndD2BaXOmlbw/EFKP1F2H38XZj5xNuyHtmP7OdLq3/7TOVpVvgz479WHPa/Zkj6v3oHen3pzQ9YQV8mnXuh0PHPUAQ58aSrsh7Rjy5BAeOOoBtmi9xbJtjulyDFPemsLRux293L6D9x9Mx8070u26brS9uC09b+7JC3PTM+96derFad1Oo8fvetDxio70+FyP5fadvWA20+ZM49AvrHjsNSci/Griq3PnztEU48ePb9J+1vxcV9XF9ZU/10F1cX21bCvUDzR7GbqM6BJvL3y7WfLq+tuuMeq5URVL/yv/+5X426y/rXa7Nxe8Gdv8eptYunTpGqVfre2JQcT0udPLktaijxZFm4vaxItvv1iW9CIiznjojBj+l+El1zGo8W0iz/oBnolGxBa+x8zMzMzMSpp8cumZDstt6ltTee7t5+i6ddeK5fHE8U+sfiNg/uL5DP3G0LW6965ejXhmBHtvuzed2nUqW5pDvzm0bGm1dA7MzMzMzCw3A8cN5JZnb2Fwz8ErzPqXh87tOtO5Xee8i1F1drhsB4Jg9BGjV7+xleTAzMzMzMxyM3j/wQzef3DexahbcX6UJZ0Zp80oSzr1zJN/mJmZmZmZ5cyBmZmZmZmZWc4cmJmZmZmZmeXMgZmZmZmZmVnOHJiZmZmZmZnlzIGZmZmZmZlZzhyYmZmZmZmZ5cyBmZmZmZmZWc4cmJmZmZmZmeXMgZmZmZmZmVnOHJiZmZmZmZnlzIGZmZmZmZlZzhyYmZmZmZmZ5cyBmZmZmZmZWc4cmJmZmZmZmeXMgZmZmZmZmVnOHJiZmZmZmZnlzIGZmZmZmZlZzhyYmZmZmZmZ5cyBmZmZmZmZWc4cmJmZmZmZmeXMgZmZmZmZmVnOHJiZmZmZmZnlzIGZmZmZmZlZzhyYmZmZmZmZ5cyBmZmZmZmZWc4cmJmZmZmZmeXMgZmZmZmZmVnOaiIwk7S9pLslzZf0nqR7JbUv2maLbPl8SVMk9SiRzlWSft98JTczMzMzM4P18i7A2pLUGngUWAwcCwRwATBe0u4RsTDb9DfA54G+wEHA3ZI+HxHzsnT2BPoDuzfzIZiZmZmZWZ2rhR6zAcCOwKERMToi7gMOAToAJxVs1wu4MCIeBk4HWgHdACStA4wABkfEy81ZeDMzMzMzs1oIzA4BJkbESw0LIuIV4AmgT8F26wMfZOuXAB8BG2TrTgQ2AYY0R4HNzMzMzMwK1UJgtgswpcTyqcDOBZ+fBk6S1E7SCcDGwF8lbQlcCPwoIhZXvLRmZmZmZmZFqv4eM2BzYF6J5e8AmxV8PgP4PfA2sAQ4MyJek3Q9MC4iHmlMZpJOJPWwASyWVCooXJ0tsnKUsgkwvwlpNla1p98ceRSmv6q6Kkf6lVLt9dzU9NekvlrqMVR7+q6D6sqjEt9xhWrhf5Rn+ivWj1TO9MullutgTfj8Loc8NKjRbSLP77udGpVCRFT1izQk8ZISyy8AlhQtWw/oDLTNPncH3gW2IVXWHcBc4Hng8Ebk/UwTy7zS/YBrKvz/qur0m/sYmlrH9fQ/aknpr0l9tdRjqPb0XQfVlUclvuNq8H+UW/rlqB/XQfOl7/O7lp1Hnt93jc27FnrM5rF8z1iDFXrSIt1b9iKApHWBq4DzI2K2pJFAG+BzwL8DYyT9MyJeqGThSxjj9HPPo9rTb448qj395sjD6eefR7Wn31x5VFIt/I+cfv55VHv6zZFHtaffXHlU0lqXX1kUV7UkPQqsHxFfLVr+GOn49lvJfqeRptffKyI+kTQXOC4ixmTr/wpcHxHDV5H3MxGxVxPK3KT9rPm5rqqL6yt/roPq4vpq2Vw/1cX11bLlWT+NzbsWJv+4H+gmaceGBZJ2IA1TvL/UDpK2AQYBP4iITwpWbVTwdxtgdYNWr1nz4q7Vftb8XFfVxfWVP9dBdXF9tWyun+ri+mrZ8qyfRuVdCz1mGwH/IE2Ffx7pAdO/Is26uHtEvF9in9uABRFxYsGyO0gzPJ4FfBn4Wbb/tIofhJmZmZmZ1bWqD8wAJLUHhgH7k3q5/gicFhEzSmzbgzTJx04R8U7B8q2A3wI9SBOA/CwiRla+9GZmZmZmVu9qIjAzMzMzMzOrZrVwj1luJB0nKQpeCyXNkDRKUl9pzR82YpUnaVBWX7UwK2nNKtG+Cl89m5BOx0qWtxYV1UHnEuv3a0qdWOVJujarl2F5l6XeuR1VL58vVI+m1pWkGyXNqFCx1pgDs/I4HNgHOJB0b9pi4DZgnKQN8yyYWQ1oaF+Fr7/kWqL6swA4psTyY7N11oJkvzt9s49H+aSyxXA7MrNVcmBWHpMjYmJETIiImyOiH+lHsQcwJOeymVW7hvZV+Hov70LVmXuBowtHAWQn/98B7ilXJpI+U6606tyhQFvgQeCzwAHlSth1tFaapR2ZWfVyYFYhEXEPcB8wQFJrAEmtJQ2W9Iqkj7L3cyUtVw+StpR0laTXJS3O3m/2D2JlSOon6VFJcyS9L+nvko4tsV1IukDSj7O6WyBpgqRd8ii3LWsrv5U0M2srz0s6cSWbbytpdFbHcyUNd492o90MdAAKnxd5GOk3ZLkTSkl7S7pb0huSPpD0gqSLiv/Xkh6T9Likg7M2txj4YaUPpE4cC8wDjiPNWLzc91nBkJ/dJI2XtEjSbEm/LPw9kvS1bLtvZUMj5wD/15wHUmPK2o4kXSnp/yS1Ktp34+z36ZIKHktdytrDoKJlO2TLjytYdmNWd10l/TlrY9MlndzcZa5Xja2rlsaBWWU9CHwG2CsbSvIw8H3gcqAXcB1p6OOlDTtI2gx4EjgC+A1peOR/Aa2A9Zuz8HVkR+Bu4LukK81jgOtW8gV6NNAb+AnwPaA9cJ+HClXUupLWK3itCyCpLfA4qY0MItXLGGCEpFNLpHML8BLwLdIsrgOAEc1Q/lrwKvAnlh+G1R8YBRQ/kqQ9MBk4mdRTczlwPHBDiXQ7A1cAVwLfJM2oa2tB0rZAT+COiJgDjAYOzn5bio0GHiF9791K+j36eYntriTNeHwMKdizpil3OxpB6hE9rGjfo0jPZb26XAW3JmlLale3AH2ASaTfp6/nWipr0XwyWVmvZe/bAEeSrpLtFxF/ypb/MRvRcL6kwRHxFnA6KVDYKyL+XpDWbc1U5roTERc1/J1dLX6MVGc/ID1CodDHwEER8XG2PcBdpGffPdkMxa1Hzxd9foLUln5Cuvq8W0RMz9Y9ImlTUpsaERFLCvZ7MCJ+mv09VlIAv5R0UUS8WMkDqBE3AUMl/RjYjHTy36t4o2y0AADZkK0ngPeAmyT9KCLmFmy+BfCNiJhc0ZLXl6OBdUn1BfA70u/PEaz4fXZtRDT0qozNLnacKemyiHi3YLu/RMT3K1noOlK2dhQR0yRNAE4C7izY/SRgbES8UsHjsNXbGPhhRIwHkPQn0gWoI4HxeRbMWi73mFVWwzjyIF3xehV4svDqPzCW1BvWLdv2G8CkoqDMKkhSJ0m3SZpJCrw+JvVs7lRi83ENQVnm2ey9fYWLWc8OA/YueJ2QLT8AeBp4pahNPQy0A3YuSufOos+3k74Dv1ypgteYu0gjAA4m9S6/SYkeLkltlYZs/4s0EdLHpCFcAjoVbT7DQVnZHQtMj4inss+PALMoGs6YKdUm2gC7Fi0fVdYS1rdyt6OrgK9L6pTttzfQFfeWtQSLGoIygIhYDLyIzxdsFdxjVlnbZ++zScMNOpC+XEtpV/D+jwqXyzKS2gDjgEXA2cC/gI9IvWXHl9jlnaLPi7P3DSpVRmNKRLxUYvlngY6svk01KL43puHzdmtRtroREQskjSYNw9oBGBkRS7XiU0FuIPUC/Jw0FGshKfgdzortZHYly1xvJO1FuiAxOOs5bnAvcIqkzkW9w41tE66nMqlAOxpFCu5OAn5KGvo4izSs2/I1r8Syxfh8wVbBgVll9QY+BP4KzAVe4dMpjIvNyN7fxieKzWkfUsC8b0Q83rDQ94xVhbnAW6QhjaW8UPR5K2Bq0WeAmWUuVy27Cfg9qafxyOKVkjYg3UsxKCIuL1i+20rSi0oUso419IoNzF7F+gPnFXzeCni56DOs2CZcT+VVtnYUER9Lug74oaQhQD9gaNEwbiufxax4v3/xRUBrGaqyrnzyWSGSvg0cAlweEYskPQR8G3g/IorvmSk0FjhPUpeIcM9Z5bXO3pf1umQ3yffJpzi2Bh4CTgVey+7PXJ2+wKMFn/sBS0nDIa1xxpGGv70bEVNLrP8M6f6m4l7M4ypcrronaX3SSf7TpN7/YsOAYyT9rGBZX6Bw5r5+pEkonsUqqdzt6Grgv/l0mOS15SmmlfAqKw717Z1HQWy1qrKuHJiVxx6StiBF5u2Bg0gPxR0HnJNtM5I0i98fJQ0lDVdcH/g8KYA7NCIWkX48jyJNYnAB6QdyC1KgcHJE+CGU5ROkCTveA4ZLOp80k9V5pJ7LTXIsm63eMNKEBn+WNIzUQ7YR8AVSD2hxcH2gpEtJFz++DJwP3FQwcYitRkR8Qokr/AXr50uaSJpAYjapHR2PRwE0h96kq8FnRsRjxSslXU2axe9rBYsHZBMeTSJNSvB9Ui/N/IqXto6Vux1FxExJ95Puxx0TEa9XoNj1rqHX+HbSxfNzgYnAvqyiLi0XVV1XnvyjPO4CniJNOnAh6YpVP+CAiPgQ0nAD0g/ftcCJpKn0R5KGnjxJuq+JbCas7qRx42eTegWGAksatrG1tiHwSUR8kk0nfRjp6uTdwMWkxxjckmP5rBGyk8evkNrSQFL7u550EaPUjFdHk6ZnHwWcSWqLfm5W+R1JGr49HLiRdP/LyoabWvkcCywg/R6VchsrPtOsD7A/cD+pfVwA/KqCZbTGW9N21FDvnvSjvJadL2SfLwb+BziF9LiJL7L84w8sPzVRV4rw0HGrL5LuBXaPiI55l8XMrLllD109H2jle5Fqg6SRpIu6O0bE0rzLUyt8vlA9aqWuPJTR6kY2Y9m+pCE/v8m5OGZmZmtFUjdgD9Kw7jMclJWHzxeqR63VlQMzqyd3kobvXk66WmxmZlbNniJN2PI70jPNrDx8vlA9aqquPJTRzMzMzMwsZ578w8zMzMzMLGcOzKzmSPqOpHskvSrpA0kvSLpY0sZF220m6TpJb0taKOmRUg/wlHSRpLGS5koKScetJN/WkoZJmilpsaRnJX23QodpZmZmZjXEgZnVop8Cn5AeuHkA6dk9PwDGZc/sQZKAMdn6U0kP/24FjJf0b0XpnUqahvWB1eR7L+lZM5cABwNPALdIOroMx2RmZmZmNcz3mFnNkbRl9nyywmX9STdH/2dEPCqpD+m5Fj0iYny2zSbAK8AtEfHjgn3XiYilkjoC04HvRcSNRel/Ffhz8TpJDwBfArYveLaGmZmZmdly3GNmNac4KMtMyt63y94PAWY1BGXZfvNJvWh9itJrzPTD3bL3PxQtfwjYpmC9mZmZmdkKHJhZvdgve38ue98FmFJiu6lAe0lt1jD9ht6wj4qWL87ed13D9MzMzMysjjgws5onaTvgl8AjEfFMtnhzYF6Jzd/J3jdbw2xeyN6Le8b2KcjPzMzMzKwkB2ZW07Ker/uAJcD3KpjVWFJv3BWS9slmfDwBODJb35jhkGZmZmZWpxyYWc2StCHpnrEdgW9GxBsFq+dRulds84L1jRYRS4DvAAuBJ0k9bxcC52SbzF6T9MzMzMysvjgws5okqRVwN7AXcGBEPFu0yVTSfWbFdgZei4j31zTPiJgWEXsAnyPdU7Y9nwZkT6xpemZmZmZWPxyYWc3JnlU2EugBHBoRE0tsdj+wnaT9CvZrS3r+2P1rk39EzIiIqdnHU4CxEfGvtUnTzMzMzGrbenkXwKwChgOHk4YSLpRUOCHHG9mQxvuBp0gPgD6LNHTxHEDAkMLEsuBtS2DrbNFekt4HiIi7C7Y7B3gVmAW0B36UvXcv9wGamZmZWW3xA6at5kiaAXRYyepfRMSgbLvNgV8DhwIbkAK1MyLiH0XpPcan0+0vJyJUsN0FwHeBbYF3Sc8wOy8iXm/60ZiZmZlZPXBgZmZmZmZmljPfY2ZmZmZmZpYzB2ZmZmZmZmY5c2BmZmZmZmaWMwdmZmZmZmZmOXNgZmZmZmZmljMHZmZmZmZmZjlzYGZmZmZmZpYzB2ZmZmZmZmY5c2BmZmZmZmaWs/8HBrHu1M9cqFUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1008x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = global_ready_rate.plot(ylim=0)\n",
    "ax.yaxis.set_major_formatter(pct_fmt)\n",
    "plt.axvline(\"2019-05-02\", color=\"red\", linewidth=1)\n",
    "plt.text(\"2019-03-23\", 0.3, \"Thu, 2 May (T217825)\", size=12, color=\"red\")\n",
    "plt.axvline(\"2019-06-28\", color=\"green\", linewidth=1)\n",
    "plt.text(\"2019-05-06\", 0.1, \"Fri, 28 Jun (A/B test deployed)\", size=12, color=\"green\")\n",
    "plt.ylabel(\"% of sessions reaching ready\")\n",
    "plt.xlabel(None)\n",
    "plt.title(\"Ready rate for phone editors\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Distinct sessions reporting readies"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The imbalance in ready events isn't caused by wikitext editor sessions mistakenly logging multiple events, since the imbalance is almost exactly the same when we count the number of distinct sessions which logged readies in each bucket.\n",
    "\n",
    "Number of distinct sessions:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "ready_sessions_r = hive.run(\"\"\"\n",
    "select\n",
    "    date_format(dt, \"yyyy-MM-dd\") as date,\n",
    "    event.bucket as bucket,\n",
    "    count(distinct event.editing_session_id) as distinct_sessions\n",
    "from event.editattemptstep\n",
    "where\n",
    "    event.action = \"ready\" and\n",
    "    not event.is_oversample and\n",
    "    event.bucket in ('default-visual', 'default-source') and\n",
    "    year = 2019 and (\n",
    "        (month = 6 and day > 20) or\n",
    "        (month = 7 and day < 9)\n",
    "    )\n",
    "group by date_format(dt, \"yyyy-MM-dd\"), event.bucket\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "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>bucket</th>\n",
       "      <th>default-source</th>\n",
       "      <th>default-visual</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-06-28</th>\n",
       "      <td>165</td>\n",
       "      <td>117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-29</th>\n",
       "      <td>1424</td>\n",
       "      <td>894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-30</th>\n",
       "      <td>2128</td>\n",
       "      <td>1191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-01</th>\n",
       "      <td>2292</td>\n",
       "      <td>1395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-02</th>\n",
       "      <td>2477</td>\n",
       "      <td>1387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-03</th>\n",
       "      <td>2511</td>\n",
       "      <td>1429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-04</th>\n",
       "      <td>2565</td>\n",
       "      <td>1464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-05</th>\n",
       "      <td>2240</td>\n",
       "      <td>1402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-06</th>\n",
       "      <td>2308</td>\n",
       "      <td>1419</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-07</th>\n",
       "      <td>2920</td>\n",
       "      <td>1754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-08</th>\n",
       "      <td>2584</td>\n",
       "      <td>1537</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "bucket      default-source  default-visual\n",
       "date                                      \n",
       "2019-06-28             165             117\n",
       "2019-06-29            1424             894\n",
       "2019-06-30            2128            1191\n",
       "2019-07-01            2292            1395\n",
       "2019-07-02            2477            1387\n",
       "2019-07-03            2511            1429\n",
       "2019-07-04            2565            1464\n",
       "2019-07-05            2240            1402\n",
       "2019-07-06            2308            1419\n",
       "2019-07-07            2920            1754\n",
       "2019-07-08            2584            1537"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ready_sessions = (\n",
    "    ready_sessions_r\n",
    "    .pivot(index=\"date\", columns=\"bucket\")\n",
    "    .fillna(0)\n",
    "    .xs(\"distinct_sessions\", axis=1)\n",
    "    .applymap(int)\n",
    ")\n",
    "\n",
    "ready_sessions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There is almost exactly one ready per ready-logging session, so almost no duplication."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "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>bucket</th>\n",
       "      <th>default-source</th>\n",
       "      <th>default-visual</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-06-28</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-29</th>\n",
       "      <td>1.000702</td>\n",
       "      <td>1.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-30</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00084</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-01</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-02</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-03</th>\n",
       "      <td>1.000398</td>\n",
       "      <td>1.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-04</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-05</th>\n",
       "      <td>1.001339</td>\n",
       "      <td>1.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-06</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-07</th>\n",
       "      <td>1.000685</td>\n",
       "      <td>1.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-08</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "bucket      default-source  default-visual\n",
       "date                                      \n",
       "2019-06-28        1.000000         1.00000\n",
       "2019-06-29        1.000702         1.00000\n",
       "2019-06-30        1.000000         1.00084\n",
       "2019-07-01        1.000000         1.00000\n",
       "2019-07-02        1.000000         1.00000\n",
       "2019-07-03        1.000398         1.00000\n",
       "2019-07-04        1.000000         1.00000\n",
       "2019-07-05        1.001339         1.00000\n",
       "2019-07-06        1.000000         1.00000\n",
       "2019-07-07        1.000685         1.00000\n",
       "2019-07-08        1.000000         1.00000"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "readies / ready_sessions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Ready timings by editor in test population"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Among people in our test (which is important because it mostly removes the possibility that users are choosing editors *because* of their device or connection), the mobile visual editor takes *much* longer to load than the mobile wikitext editor."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "ready_times_r = hive.run(\"\"\"\n",
    "select\n",
    "    event.editor_interface as editor,\n",
    "    percentile_approx(event.ready_timing, 0.1) as 10th_percentile,\n",
    "    percentile_approx(event.ready_timing, 0.5) as median,\n",
    "    percentile_approx(event.ready_timing, 0.9) as 90th_percentile\n",
    "from event.editattemptstep\n",
    "where\n",
    "    event.bufcket in (\"default-source\", \"default-visual\") and\n",
    "    event.action = \"ready\" and\n",
    "    year = 2019 and (\n",
    "        (month = 6 and day > 28) or\n",
    "        (month = 7 and day < 9)\n",
    "    )\n",
    "group by event.editor_interface\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "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>editor</th>\n",
       "      <th>visualeditor</th>\n",
       "      <th>wikitext</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>10th_percentile</th>\n",
       "      <td>1136</td>\n",
       "      <td>218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>median</th>\n",
       "      <td>2868</td>\n",
       "      <td>560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90th_percentile</th>\n",
       "      <td>7917</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "editor           visualeditor  wikitext\n",
       "10th_percentile          1136       218\n",
       "median                   2868       560\n",
       "90th_percentile          7917      2020"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ready_times = (\n",
    "    ready_times_r\n",
    "    .set_index(\"editor\")\n",
    "    .transpose()\n",
    "    .applymap(int)\n",
    ")\n",
    "\n",
    "ready_times"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "| index | visualeditor | wikitext\n",
      "| ----- | ----- | ----- \n",
      "| 10th_percentile | 1136 | 218\n",
      "| median | 2868 | 560\n",
      "| 90th_percentile | 7917 | 2020\n",
      "\n"
     ]
    }
   ],
   "source": [
    "ready_times.reset_index().pipe(df_to_remarkup)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Ready timings by editor globally"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "But this isn't limited to our test population—the story is pretty much identical when you look at all users."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "global_ready_times_r = hive.run(\"\"\"\n",
    "select\n",
    "    event.editor_interface as editor,\n",
    "    percentile_approx(event.ready_timing, 0.1) as 10th_percentile,\n",
    "    percentile_approx(event.ready_timing, 0.5) as median,\n",
    "    percentile_approx(event.ready_timing, 0.9) as 90th_percentile\n",
    "from event.editattemptstep\n",
    "where\n",
    "    event.platform = \"phone\" and\n",
    "    event.action = \"ready\" and\n",
    "    year = 2019 and (\n",
    "        (month = 6 and day > 28) or\n",
    "        (month = 7 and day < 9)\n",
    "    )\n",
    "group by event.editor_interface\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "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>editor</th>\n",
       "      <th>visualeditor</th>\n",
       "      <th>wikitext</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>10th_percentile</th>\n",
       "      <td>1111</td>\n",
       "      <td>184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>median</th>\n",
       "      <td>2840</td>\n",
       "      <td>513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90th_percentile</th>\n",
       "      <td>8184</td>\n",
       "      <td>1912</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "editor           visualeditor  wikitext\n",
       "10th_percentile          1111       184\n",
       "median                   2840       513\n",
       "90th_percentile          8184      1912"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "global_ready_times = (\n",
    "    global_ready_times_r\n",
    "    .set_index(\"editor\")\n",
    "    .transpose()\n",
    "    .applymap(int)\n",
    ")\n",
    "\n",
    "global_ready_times"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "metadata": {},
   "outputs": [],
   "source": [
    "hist_ready_times_r = hive.run(\"\"\"\n",
    "select\n",
    "    date_format(dt, \"yyyy-MM-dd\"),\n",
    "    percentile_approx(event.ready_timing, 0.1) as 10th_percentile,\n",
    "    percentile_approx(event.ready_timing, 0.5) as median,\n",
    "    percentile_approx(event.ready_timing, 0.9) as 90th_percentile\n",
    "from event_sanitized.editattemptstep\n",
    "where\n",
    "    event.platform = \"phone\" and\n",
    "    event.editor_interface = \"visualeditor\" and\n",
    "    event.action = \"ready\" and\n",
    "    year > 0\n",
    "group by date_format(dt, \"yyyy-MM-dd\")\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 296,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1008x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "hist_ready_times = (\n",
    "    hist_ready_times_r\n",
    "    .rename({\"_c0\": \"date\"}, axis=1)\n",
    "    .assign(date=lambda df: pd.to_datetime(df[\"date\"]).dt.to_period(freq=\"D\"))\n",
    "    .sort_values(\"date\")\n",
    "    .set_index(\"date\")\n",
    "    .loc[\"2019-01-06\":]\n",
    ")\n",
    "\n",
    "hist_ready_times.plot(ylim=0)\n",
    "plt.axvline(\"2019-05-02\", color=\"red\", linewidth=1)\n",
    "plt.text(\"2019-03-31\", 3000, \"Thu, 2 May (T217825)\", size=12, color=\"red\")\n",
    "plt.axvline(\"2019-06-28\", color=\"green\", linewidth=1)\n",
    "plt.text(\"2019-05-15\", 5000, \"Fri, 28 Jun (A/B test deployed)\", size=12, color=\"green\")\n",
    "plt.ylabel(\"milliseconds\")\n",
    "plt.xlabel(None)\n",
    "plt.title(\"Ready timings for the mobile visual editor\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Saves per bucket"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "saves_r = hive.run(\"\"\"\n",
    "select\n",
    "    date_format(dt, \"yyyy-MM-dd\") as date,\n",
    "    event.bucket as bucket,\n",
    "    count(*) as saves\n",
    "from event.editattemptstep\n",
    "where\n",
    "    event.action = \"saveSuccess\" and\n",
    "    not event.is_oversample and\n",
    "    event.bucket in ('default-visual', 'default-source') and\n",
    "    year = 2019 and (\n",
    "        (month = 6 and day > 20) or\n",
    "        (month = 7 and day < 9)\n",
    "    )\n",
    "group by date_format(dt, \"yyyy-MM-dd\"), event.bucket\n",
    "\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "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>bucket</th>\n",
       "      <th>default-source</th>\n",
       "      <th>default-visual</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-06-28</th>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-29</th>\n",
       "      <td>56</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-30</th>\n",
       "      <td>58</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-01</th>\n",
       "      <td>50</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-02</th>\n",
       "      <td>72</td>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-03</th>\n",
       "      <td>69</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-04</th>\n",
       "      <td>78</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-05</th>\n",
       "      <td>66</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-06</th>\n",
       "      <td>75</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-07</th>\n",
       "      <td>105</td>\n",
       "      <td>71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-08</th>\n",
       "      <td>65</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "bucket      default-source  default-visual\n",
       "date                                      \n",
       "2019-06-28               4               3\n",
       "2019-06-29              56              41\n",
       "2019-06-30              58              39\n",
       "2019-07-01              50              43\n",
       "2019-07-02              72              44\n",
       "2019-07-03              69              55\n",
       "2019-07-04              78              60\n",
       "2019-07-05              66              59\n",
       "2019-07-06              75              48\n",
       "2019-07-07             105              71\n",
       "2019-07-08              65              65"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "saves = (\n",
    "    saves_r\n",
    "    .pivot(index=\"date\", columns=\"bucket\")\n",
    "    .fillna(0)\n",
    "    .xs(\"saves\", axis=1)\n",
    "    .applymap(int)\n",
    ")\n",
    "\n",
    "saves"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ratio of visual bucket saves to source bucket saves: 75.6%\n"
     ]
    }
   ],
   "source": [
    "print(\n",
    "    \"Ratio of visual bucket saves to source bucket saves:\",\n",
    "    pct_str(\n",
    "        saves[\"default-visual\"].sum() / saves[\"default-source\"].sum()\n",
    "    )\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Edit completion rate"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Edit completion based on actually reconstructing sessions:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 360,
   "metadata": {},
   "outputs": [],
   "source": [
    "completion_r = hive.run(\"\"\"\n",
    "with attempts as (\n",
    "    select\n",
    "        date_format(min(dt), \"yyyy-MM-dd\") as date,\n",
    "        event.bucket as bucket,\n",
    "        sum(cast(event.action = \"saveSuccess\" as int)) >= 1 as completed\n",
    "    from event.editattemptstep\n",
    "    where\n",
    "        event.action in (\"ready\", \"saveSuccess\") and\n",
    "        event.bucket in (\"default-source\", \"default-visual\") and\n",
    "        year = 2019 and ((month = 6 and day >= 15) or month = 7 or month = 8 )\n",
    "    group by event.bucket, event.editing_session_id\n",
    ")\n",
    "select\n",
    "    date,\n",
    "    bucket,\n",
    "    sum(cast(completed as int)) / count(*) as edit_completion_rate\n",
    "from attempts\n",
    "group by date, bucket\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 363,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 82 entries, 0 to 81\n",
      "Data columns (total 3 columns):\n",
      "date                    82 non-null object\n",
      "bucket                  82 non-null object\n",
      "edit_completion_rate    82 non-null float64\n",
      "dtypes: float64(1), object(2)\n",
      "memory usage: 2.0+ KB\n"
     ]
    }
   ],
   "source": [
    "completion_r.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 361,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" colspan=2>edit_completion_rate</th>    </tr>    <tr>        <th class=\"index_name level1\" >bucket</th>        <th class=\"col_heading level1 col0\" >default-source</th>        <th class=\"col_heading level1 col1\" >default-visual</th>    </tr>    <tr>        <th class=\"index_name level0\" >date</th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row0\" class=\"row_heading level0 row0\" >2019-06-28 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row0_col0\" class=\"data row0 col0\" >5.2%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row0_col1\" class=\"data row0 col1\" >4.3%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row1\" class=\"row_heading level0 row1\" >2019-06-29 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row1_col0\" class=\"data row1 col0\" >8.6%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row1_col1\" class=\"data row1 col1\" >2.9%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row2\" class=\"row_heading level0 row2\" >2019-06-30 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row2_col0\" class=\"data row2 col0\" >6.9%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row2_col1\" class=\"data row2 col1\" >2.4%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row3\" class=\"row_heading level0 row3\" >2019-07-01 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row3_col0\" class=\"data row3 col0\" >6.1%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row3_col1\" class=\"data row3 col1\" >2.1%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row4\" class=\"row_heading level0 row4\" >2019-07-02 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row4_col0\" class=\"data row4 col0\" >5.3%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row4_col1\" class=\"data row4 col1\" >2.2%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row5\" class=\"row_heading level0 row5\" >2019-07-03 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row5_col0\" class=\"data row5 col0\" >6.4%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row5_col1\" class=\"data row5 col1\" >2.3%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row6\" class=\"row_heading level0 row6\" >2019-07-04 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row6_col0\" class=\"data row6 col0\" >8.6%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row6_col1\" class=\"data row6 col1\" >2.8%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row7\" class=\"row_heading level0 row7\" >2019-07-05 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row7_col0\" class=\"data row7 col0\" >8.3%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row7_col1\" class=\"data row7 col1\" >2.6%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row8\" class=\"row_heading level0 row8\" >2019-07-06 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row8_col0\" class=\"data row8 col0\" >7.1%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row8_col1\" class=\"data row8 col1\" >2.6%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row9\" class=\"row_heading level0 row9\" >2019-07-07 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row9_col0\" class=\"data row9 col0\" >8.5%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row9_col1\" class=\"data row9 col1\" >2.7%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row10\" class=\"row_heading level0 row10\" >2019-07-08 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row10_col0\" class=\"data row10 col0\" >7.1%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row10_col1\" class=\"data row10 col1\" >2.7%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row11\" class=\"row_heading level0 row11\" >2019-07-09 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row11_col0\" class=\"data row11 col0\" >8.5%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row11_col1\" class=\"data row11 col1\" >2.5%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row12\" class=\"row_heading level0 row12\" >2019-07-10 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row12_col0\" class=\"data row12 col0\" >8.9%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row12_col1\" class=\"data row12 col1\" >3.1%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row13\" class=\"row_heading level0 row13\" >2019-07-11 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row13_col0\" class=\"data row13 col0\" >7.2%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row13_col1\" class=\"data row13 col1\" >3.1%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row14\" class=\"row_heading level0 row14\" >2019-07-12 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row14_col0\" class=\"data row14 col0\" >3.3%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row14_col1\" class=\"data row14 col1\" >4.8%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row15\" class=\"row_heading level0 row15\" >2019-07-13 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row15_col0\" class=\"data row15 col0\" >3.3%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row15_col1\" class=\"data row15 col1\" >5.4%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row16\" class=\"row_heading level0 row16\" >2019-07-14 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row16_col0\" class=\"data row16 col0\" >2.9%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row16_col1\" class=\"data row16 col1\" >4.5%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row17\" class=\"row_heading level0 row17\" >2019-07-15 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row17_col0\" class=\"data row17 col0\" >2.8%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row17_col1\" class=\"data row17 col1\" >4.1%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row18\" class=\"row_heading level0 row18\" >2019-07-16 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row18_col0\" class=\"data row18 col0\" >3.1%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row18_col1\" class=\"data row18 col1\" >3.4%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row19\" class=\"row_heading level0 row19\" >2019-07-17 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row19_col0\" class=\"data row19 col0\" >2.6%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row19_col1\" class=\"data row19 col1\" >4.2%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row20\" class=\"row_heading level0 row20\" >2019-07-18 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row20_col0\" class=\"data row20 col0\" >3.1%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row20_col1\" class=\"data row20 col1\" >3.9%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row21\" class=\"row_heading level0 row21\" >2019-07-19 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row21_col0\" class=\"data row21 col0\" >3.3%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row21_col1\" class=\"data row21 col1\" >3.7%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row22\" class=\"row_heading level0 row22\" >2019-07-20 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row22_col0\" class=\"data row22 col0\" >2.9%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row22_col1\" class=\"data row22 col1\" >4.2%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row23\" class=\"row_heading level0 row23\" >2019-07-21 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row23_col0\" class=\"data row23 col0\" >2.4%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row23_col1\" class=\"data row23 col1\" >3.8%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row24\" class=\"row_heading level0 row24\" >2019-07-22 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row24_col0\" class=\"data row24 col0\" >2.9%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row24_col1\" class=\"data row24 col1\" >3.7%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row25\" class=\"row_heading level0 row25\" >2019-07-23 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row25_col0\" class=\"data row25 col0\" >2.9%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row25_col1\" class=\"data row25 col1\" >3.2%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row26\" class=\"row_heading level0 row26\" >2019-07-24 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row26_col0\" class=\"data row26 col0\" >3.0%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row26_col1\" class=\"data row26 col1\" >3.7%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row27\" class=\"row_heading level0 row27\" >2019-07-25 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row27_col0\" class=\"data row27 col0\" >2.6%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row27_col1\" class=\"data row27 col1\" >4.0%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row28\" class=\"row_heading level0 row28\" >2019-07-26 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row28_col0\" class=\"data row28 col0\" >2.9%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row28_col1\" class=\"data row28 col1\" >4.5%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row29\" class=\"row_heading level0 row29\" >2019-07-27 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row29_col0\" class=\"data row29 col0\" >2.9%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row29_col1\" class=\"data row29 col1\" >3.7%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row30\" class=\"row_heading level0 row30\" >2019-07-28 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row30_col0\" class=\"data row30 col0\" >3.2%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row30_col1\" class=\"data row30 col1\" >3.9%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row31\" class=\"row_heading level0 row31\" >2019-07-29 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row31_col0\" class=\"data row31 col0\" >3.0%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row31_col1\" class=\"data row31 col1\" >3.4%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row32\" class=\"row_heading level0 row32\" >2019-07-30 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row32_col0\" class=\"data row32 col0\" >2.8%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row32_col1\" class=\"data row32 col1\" >3.8%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row33\" class=\"row_heading level0 row33\" >2019-07-31 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row33_col0\" class=\"data row33 col0\" >2.8%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row33_col1\" class=\"data row33 col1\" >4.5%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row34\" class=\"row_heading level0 row34\" >2019-08-01 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row34_col0\" class=\"data row34 col0\" >3.1%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row34_col1\" class=\"data row34 col1\" >3.4%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row35\" class=\"row_heading level0 row35\" >2019-08-02 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row35_col0\" class=\"data row35 col0\" >3.2%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row35_col1\" class=\"data row35 col1\" >4.2%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row36\" class=\"row_heading level0 row36\" >2019-08-03 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row36_col0\" class=\"data row36 col0\" >3.1%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row36_col1\" class=\"data row36 col1\" >3.9%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row37\" class=\"row_heading level0 row37\" >2019-08-04 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row37_col0\" class=\"data row37 col0\" >2.7%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row37_col1\" class=\"data row37 col1\" >3.9%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row38\" class=\"row_heading level0 row38\" >2019-08-05 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row38_col0\" class=\"data row38 col0\" >3.0%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row38_col1\" class=\"data row38 col1\" >3.9%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row39\" class=\"row_heading level0 row39\" >2019-08-06 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row39_col0\" class=\"data row39 col0\" >2.8%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row39_col1\" class=\"data row39 col1\" >3.9%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6level0_row40\" class=\"row_heading level0 row40\" >2019-08-07 00:00:00</th>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row40_col0\" class=\"data row40 col0\" >2.7%</td>\n",
       "                        <td id=\"T_1c66be94_b935_11e9_89aa_d094661b49a6row40_col1\" class=\"data row40 col1\" >4.4%</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f9291fc0160>"
      ]
     },
     "execution_count": 361,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(\n",
    "    completion_r\n",
    "    .assign(date=lambda df: pd.to_datetime(df[\"date\"]))\n",
    "    .sort_values(\"date\")\n",
    "    .pivot(index=\"date\", columns=\"bucket\")\n",
    "    .style.format(pct_str)\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Same method, but removing oversampled sessions (a big chunk of the VE sessions). It's very different, but that doesn't make sense, since the remaining VE sessions should just be a random 1/16 sample."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 358,
   "metadata": {},
   "outputs": [],
   "source": [
    "non_oversampled_completion_r = hive.run(\"\"\"\n",
    "with attempts as (\n",
    "    select\n",
    "        date_format(min(dt), \"yyyy-MM-dd\") as date,\n",
    "        event.bucket as bucket,\n",
    "        sum(cast(event.action = \"saveSuccess\" as int)) >= 1 as completed\n",
    "    from event.editattemptstep\n",
    "    where\n",
    "        not event.is_oversample and\n",
    "        event.action in (\"ready\", \"saveSuccess\") and\n",
    "        event.bucket in (\"default-source\", \"default-visual\") and\n",
    "        year = 2019 and ((month = 6 and day >= 15) or month = 7 or month = 8 )\n",
    "    group by event.bucket, event.editing_session_id\n",
    ")\n",
    "select\n",
    "    date,\n",
    "    bucket,\n",
    "    sum(cast(completed as int)) / count(*) as edit_completion_rate\n",
    "from attempts\n",
    "group by date, bucket\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 359,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_6469302a_b933_11e9_89aa_d094661b49a6\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" colspan=2>edit_completion_rate</th>    </tr>    <tr>        <th class=\"index_name level1\" >bucket</th>        <th class=\"col_heading level1 col0\" >default-source</th>        <th class=\"col_heading level1 col1\" >default-visual</th>    </tr>    <tr>        <th class=\"index_name level0\" >date</th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row0\" class=\"row_heading level0 row0\" >2019-06-28 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row0_col0\" class=\"data row0 col0\" >2.4%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row0_col1\" class=\"data row0 col1\" >2.6%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row1\" class=\"row_heading level0 row1\" >2019-06-29 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row1_col0\" class=\"data row1 col0\" >3.9%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row1_col1\" class=\"data row1 col1\" >4.6%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row2\" class=\"row_heading level0 row2\" >2019-06-30 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row2_col0\" class=\"data row2 col0\" >2.7%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row2_col1\" class=\"data row2 col1\" >3.3%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row3\" class=\"row_heading level0 row3\" >2019-07-01 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row3_col0\" class=\"data row3 col0\" >2.2%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row3_col1\" class=\"data row3 col1\" >3.1%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row4\" class=\"row_heading level0 row4\" >2019-07-02 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row4_col0\" class=\"data row4 col0\" >2.9%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row4_col1\" class=\"data row4 col1\" >3.2%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row5\" class=\"row_heading level0 row5\" >2019-07-03 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row5_col0\" class=\"data row5 col0\" >2.7%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row5_col1\" class=\"data row5 col1\" >3.8%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row6\" class=\"row_heading level0 row6\" >2019-07-04 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row6_col0\" class=\"data row6 col0\" >3.0%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row6_col1\" class=\"data row6 col1\" >4.1%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row7\" class=\"row_heading level0 row7\" >2019-07-05 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row7_col0\" class=\"data row7 col0\" >2.9%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row7_col1\" class=\"data row7 col1\" >4.2%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row8\" class=\"row_heading level0 row8\" >2019-07-06 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row8_col0\" class=\"data row8 col0\" >3.3%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row8_col1\" class=\"data row8 col1\" >3.4%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row9\" class=\"row_heading level0 row9\" >2019-07-07 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row9_col0\" class=\"data row9 col0\" >3.6%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row9_col1\" class=\"data row9 col1\" >4.0%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row10\" class=\"row_heading level0 row10\" >2019-07-08 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row10_col0\" class=\"data row10 col0\" >2.5%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row10_col1\" class=\"data row10 col1\" >4.2%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row11\" class=\"row_heading level0 row11\" >2019-07-09 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row11_col0\" class=\"data row11 col0\" >3.2%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row11_col1\" class=\"data row11 col1\" >4.2%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row12\" class=\"row_heading level0 row12\" >2019-07-10 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row12_col0\" class=\"data row12 col0\" >3.2%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row12_col1\" class=\"data row12 col1\" >3.8%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row13\" class=\"row_heading level0 row13\" >2019-07-11 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row13_col0\" class=\"data row13 col0\" >2.9%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row13_col1\" class=\"data row13 col1\" >4.5%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row14\" class=\"row_heading level0 row14\" >2019-07-12 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row14_col0\" class=\"data row14 col0\" >3.8%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row14_col1\" class=\"data row14 col1\" >5.3%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row15\" class=\"row_heading level0 row15\" >2019-07-13 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row15_col0\" class=\"data row15 col0\" >2.6%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row15_col1\" class=\"data row15 col1\" >5.5%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row16\" class=\"row_heading level0 row16\" >2019-07-14 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row16_col0\" class=\"data row16 col0\" >2.5%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row16_col1\" class=\"data row16 col1\" >4.4%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row17\" class=\"row_heading level0 row17\" >2019-07-15 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row17_col0\" class=\"data row17 col0\" >2.8%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row17_col1\" class=\"data row17 col1\" >4.1%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row18\" class=\"row_heading level0 row18\" >2019-07-16 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row18_col0\" class=\"data row18 col0\" >2.4%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row18_col1\" class=\"data row18 col1\" >3.1%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row19\" class=\"row_heading level0 row19\" >2019-07-17 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row19_col0\" class=\"data row19 col0\" >2.3%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row19_col1\" class=\"data row19 col1\" >4.5%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row20\" class=\"row_heading level0 row20\" >2019-07-18 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row20_col0\" class=\"data row20 col0\" >2.8%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row20_col1\" class=\"data row20 col1\" >4.5%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row21\" class=\"row_heading level0 row21\" >2019-07-19 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row21_col0\" class=\"data row21 col0\" >3.0%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row21_col1\" class=\"data row21 col1\" >3.7%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row22\" class=\"row_heading level0 row22\" >2019-07-20 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row22_col0\" class=\"data row22 col0\" >2.7%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row22_col1\" class=\"data row22 col1\" >5.1%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row23\" class=\"row_heading level0 row23\" >2019-07-21 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row23_col0\" class=\"data row23 col0\" >2.2%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row23_col1\" class=\"data row23 col1\" >3.1%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row24\" class=\"row_heading level0 row24\" >2019-07-22 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row24_col0\" class=\"data row24 col0\" >2.6%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row24_col1\" class=\"data row24 col1\" >2.9%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row25\" class=\"row_heading level0 row25\" >2019-07-23 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row25_col0\" class=\"data row25 col0\" >2.8%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row25_col1\" class=\"data row25 col1\" >3.5%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row26\" class=\"row_heading level0 row26\" >2019-07-24 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row26_col0\" class=\"data row26 col0\" >2.9%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row26_col1\" class=\"data row26 col1\" >3.4%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row27\" class=\"row_heading level0 row27\" >2019-07-25 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row27_col0\" class=\"data row27 col0\" >2.9%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row27_col1\" class=\"data row27 col1\" >3.8%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row28\" class=\"row_heading level0 row28\" >2019-07-26 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row28_col0\" class=\"data row28 col0\" >2.7%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row28_col1\" class=\"data row28 col1\" >3.6%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row29\" class=\"row_heading level0 row29\" >2019-07-27 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row29_col0\" class=\"data row29 col0\" >2.4%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row29_col1\" class=\"data row29 col1\" >4.1%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row30\" class=\"row_heading level0 row30\" >2019-07-28 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row30_col0\" class=\"data row30 col0\" >3.3%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row30_col1\" class=\"data row30 col1\" >3.6%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row31\" class=\"row_heading level0 row31\" >2019-07-29 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row31_col0\" class=\"data row31 col0\" >3.2%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row31_col1\" class=\"data row31 col1\" >3.4%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row32\" class=\"row_heading level0 row32\" >2019-07-30 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row32_col0\" class=\"data row32 col0\" >3.0%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row32_col1\" class=\"data row32 col1\" >4.6%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row33\" class=\"row_heading level0 row33\" >2019-07-31 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row33_col0\" class=\"data row33 col0\" >2.8%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row33_col1\" class=\"data row33 col1\" >4.8%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row34\" class=\"row_heading level0 row34\" >2019-08-01 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row34_col0\" class=\"data row34 col0\" >2.9%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row34_col1\" class=\"data row34 col1\" >2.7%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row35\" class=\"row_heading level0 row35\" >2019-08-02 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row35_col0\" class=\"data row35 col0\" >3.1%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row35_col1\" class=\"data row35 col1\" >4.3%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row36\" class=\"row_heading level0 row36\" >2019-08-03 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row36_col0\" class=\"data row36 col0\" >3.9%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row36_col1\" class=\"data row36 col1\" >4.1%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row37\" class=\"row_heading level0 row37\" >2019-08-04 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row37_col0\" class=\"data row37 col0\" >2.7%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row37_col1\" class=\"data row37 col1\" >4.2%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row38\" class=\"row_heading level0 row38\" >2019-08-05 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row38_col0\" class=\"data row38 col0\" >3.0%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row38_col1\" class=\"data row38 col1\" >3.1%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row39\" class=\"row_heading level0 row39\" >2019-08-06 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row39_col0\" class=\"data row39 col0\" >2.8%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row39_col1\" class=\"data row39 col1\" >3.0%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_6469302a_b933_11e9_89aa_d094661b49a6level0_row40\" class=\"row_heading level0 row40\" >2019-08-07 00:00:00</th>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row40_col0\" class=\"data row40 col0\" >2.3%</td>\n",
       "                        <td id=\"T_6469302a_b933_11e9_89aa_d094661b49a6row40_col1\" class=\"data row40 col1\" >4.4%</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f9291fcba20>"
      ]
     },
     "execution_count": 359,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(\n",
    "    non_oversampled_completion_r\n",
    "    .assign(date=lambda df: pd.to_datetime(df[\"date\"]))\n",
    "    .sort_values(\"date\")\n",
    "    .pivot(index=\"date\", columns=\"bucket\")\n",
    "    .style.format(pct_str)\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Early edit completion rate"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before we started oversampling"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Correspondence between buckets and editors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "metadata": {},
   "outputs": [],
   "source": [
    "default_editor_inits_r = hive.run(\"\"\"\n",
    "select\n",
    "    date_format(dt, \"yyyy-MM-dd\") as date,\n",
    "    sum(cast(\n",
    "        array(event.bucket, event.editor_interface) in (\n",
    "            array(\"default-source\", \"wikitext\"),\n",
    "            array(\"default-visual\", \"visualeditor\")\n",
    "        )\n",
    "    as int)) / count(*) as default_editor_inits\n",
    "from event.editattemptstep\n",
    "where\n",
    "    event.platform = \"phone\" and\n",
    "    event.action = \"init\" and\n",
    "    event.bucket in (\"default-source\", \"default-visual\") and\n",
    "    wiki in (\n",
    "        'azwiki', 'bgwiki', 'zh_yuewiki', 'cawiki', 'hrwiki',\n",
    "        'dawiki', 'etwiki', 'fiwiki', 'elwiki', 'huwiki',\n",
    "        'mswiki', 'mlwiki', 'nowiki', 'ptwiki', 'rowiki',\n",
    "        'srwiki', 'svwiki', 'tawiki', 'thwiki', 'urwiki'\n",
    "    ) and\n",
    "    year = 2019 and (\n",
    "        (month = 6 and day >= 28) or\n",
    "        (month = 7)\n",
    "    )\n",
    "group by date_format(dt, \"yyyy-MM-dd\")\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "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>date</th>\n",
       "      <th>default_editor_inits</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-06-28</td>\n",
       "      <td>97.6%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-06-29</td>\n",
       "      <td>98.1%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-06-30</td>\n",
       "      <td>98.4%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-07-01</td>\n",
       "      <td>98.4%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2019-07-02</td>\n",
       "      <td>98.6%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-07-03</td>\n",
       "      <td>98.5%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2019-07-04</td>\n",
       "      <td>97.9%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         date default_editor_inits\n",
       "0  2019-06-28                97.6%\n",
       "3  2019-06-29                98.1%\n",
       "4  2019-06-30                98.4%\n",
       "1  2019-07-01                98.4%\n",
       "5  2019-07-02                98.6%\n",
       "2  2019-07-03                98.5%\n",
       "6  2019-07-04                97.9%"
      ]
     },
     "execution_count": 236,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "default_editor_inits = (\n",
    "    default_editor_inits_r\n",
    "    .assign(\n",
    "        default_editor_inits=lambda df: df[\"default_editor_inits\"].map(pct_str)\n",
    "    ).sort_values(\"date\")\n",
    ")\n",
    "\n",
    "default_editor_inits"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Buckets per user"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 252,
   "metadata": {},
   "outputs": [],
   "source": [
    "multiple_buckets_r = hive.run(\"\"\"\n",
    "select\n",
    "    user_type,\n",
    "    sum(cast(distinct_buckets > 1 as int)) / count(*) as multiple_buckets\n",
    "from (\n",
    "    select\n",
    "        if(event.user_id = 0, \"anonymous\", \"registered\") as user_type,\n",
    "        count(distinct event.bucket) as distinct_buckets\n",
    "    from event.editattemptstep\n",
    "    where\n",
    "        event.platform = \"phone\" and\n",
    "        wiki in (\n",
    "            'azwiki', 'bgwiki', 'zh_yuewiki', 'cawiki', 'hrwiki',\n",
    "            'dawiki', 'etwiki', 'fiwiki', 'elwiki', 'huwiki',\n",
    "            'mswiki', 'mlwiki', 'nowiki', 'ptwiki', 'rowiki',\n",
    "            'srwiki', 'svwiki', 'tawiki', 'thwiki', 'urwiki'\n",
    "        ) and\n",
    "        year = 2019 and (\n",
    "            (month = 6 and day > 23) or\n",
    "            (month = 7)\n",
    "        )\n",
    "    group by\n",
    "        wiki,\n",
    "        if(event.user_id = 0, event.anonymous_user_token, event.user_id),\n",
    "        if(event.user_id = 0, \"anonymous\", \"registered\")\n",
    ") buckets_per_user\n",
    "group by user_type\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 253,
   "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>user_type</th>\n",
       "      <th>multiple_buckets</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>anonymous</td>\n",
       "      <td>0.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>registered</td>\n",
       "      <td>0.0%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    user_type multiple_buckets\n",
       "0   anonymous             0.0%\n",
       "1  registered             0.0%"
      ]
     },
     "execution_count": 253,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "multiple_buckets = multiple_buckets_r.assign(\n",
    "    multiple_buckets=lambda df: df[\"multiple_buckets\"].map(pct_str)\n",
    ")\n",
    "\n",
    "multiple_buckets"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Anonymous editors with tokens"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "metadata": {},
   "outputs": [],
   "source": [
    "anons_with_tokens_r = hive.run(\"\"\"\n",
    "select\n",
    "    date_format(dt, \"yyyy-MM-dd\") as date,\n",
    "    sum(cast(event.anonymous_user_token is not null as int)) / count(*) as anonymous_users_with_tokens\n",
    "from event.editattemptstep\n",
    "where\n",
    "    event.platform = \"phone\" and\n",
    "    event.user_id = 0 and\n",
    "    wiki in (\n",
    "        'azwiki', 'bgwiki', 'zh_yuewiki', 'cawiki', 'hrwiki',\n",
    "        'dawiki', 'etwiki', 'fiwiki', 'elwiki', 'huwiki',\n",
    "        'mswiki', 'mlwiki', 'nowiki', 'ptwiki', 'rowiki',\n",
    "        'srwiki', 'svwiki', 'tawiki', 'thwiki', 'urwiki'\n",
    "    ) and\n",
    "    year = 2019 and (\n",
    "        (month = 6 and day > 23) or\n",
    "        (month = 7)\n",
    "    )\n",
    "group by date_format(dt, \"yyyy-MM-dd\")\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 216,
   "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>date</th>\n",
       "      <th>anonymous_users_with_tokens</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-06-24</td>\n",
       "      <td>0.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-06-25</td>\n",
       "      <td>0.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2019-06-26</td>\n",
       "      <td>0.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-06-27</td>\n",
       "      <td>0.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2019-06-28</td>\n",
       "      <td>99.9%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2019-06-29</td>\n",
       "      <td>100.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-06-30</td>\n",
       "      <td>100.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2019-07-01</td>\n",
       "      <td>100.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-07-02</td>\n",
       "      <td>100.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2019-07-03</td>\n",
       "      <td>100.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2019-07-04</td>\n",
       "      <td>99.9%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          date anonymous_users_with_tokens\n",
       "0   2019-06-24                        0.0%\n",
       "4   2019-06-25                        0.0%\n",
       "7   2019-06-26                        0.0%\n",
       "1   2019-06-27                        0.0%\n",
       "5   2019-06-28                       99.9%\n",
       "8   2019-06-29                      100.0%\n",
       "2   2019-06-30                      100.0%\n",
       "9   2019-07-01                      100.0%\n",
       "3   2019-07-02                      100.0%\n",
       "6   2019-07-03                      100.0%\n",
       "10  2019-07-04                       99.9%"
      ]
     },
     "execution_count": 216,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "anons_with_tokens_r.sort_values(\"date\").assign(\n",
    "    anonymous_users_with_tokens=lambda df: df[\"anonymous_users_with_tokens\"].map(pct_str)\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# New revision IDs in saveSuccess events"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are a lot of edits with a revision ID of 0."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 325,
   "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>platform</th>\n",
       "      <th>editor</th>\n",
       "      <th>null_revid_events</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>desktop</td>\n",
       "      <td>visualeditor</td>\n",
       "      <td>60485</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>desktop</td>\n",
       "      <td>wikitext</td>\n",
       "      <td>134565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>desktop</td>\n",
       "      <td>wikitext-2017</td>\n",
       "      <td>304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>phone</td>\n",
       "      <td>visualeditor</td>\n",
       "      <td>24403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>phone</td>\n",
       "      <td>wikitext</td>\n",
       "      <td>46817</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  platform         editor  null_revid_events\n",
       "0  desktop   visualeditor              60485\n",
       "1  desktop       wikitext             134565\n",
       "2  desktop  wikitext-2017                304\n",
       "3    phone   visualeditor              24403\n",
       "4    phone       wikitext              46817"
      ]
     },
     "execution_count": 325,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hive.run(\"\"\"\n",
    "select \n",
    "    event.platform as platform,\n",
    "    event.editor_interface as editor,\n",
    "    count(*) as null_revid_events\n",
    "from event.editattemptstep\n",
    "where\n",
    "    event.revision_id = 0 and\n",
    "    year = 2019 and month = 8 and day = 6\n",
    "group by event.platform, event.editor_interface\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The ones which also have a page ID of 0 seem to be trying to create pages which don't exist, but there are plenty of others which do have a page ID."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 370,
   "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>wiki</th>\n",
       "      <th>action</th>\n",
       "      <th>page_title</th>\n",
       "      <th>page_id</th>\n",
       "      <th>page_ns</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>eswiki</td>\n",
       "      <td>loaded</td>\n",
       "      <td>After:_En_Mil_Pedazos</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>itwiki</td>\n",
       "      <td>init</td>\n",
       "      <td>Lista_di_compagnie_aeree_di_bandiera</td>\n",
       "      <td>1988047</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>dewiktionary</td>\n",
       "      <td>init</td>\n",
       "      <td>Mielert</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>enwiki</td>\n",
       "      <td>ready</td>\n",
       "      <td>Mask_(Fanatic_Crisis_album)</td>\n",
       "      <td>55479138</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>eswiki</td>\n",
       "      <td>loaded</td>\n",
       "      <td>Edgewall_Software</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>thwiki</td>\n",
       "      <td>init</td>\n",
       "      <td>ทะไลลามะ_องค์ที่แปด</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>enwiki</td>\n",
       "      <td>loaded</td>\n",
       "      <td>User:Kawnhr/sandbox</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>ptwiki</td>\n",
       "      <td>ready</td>\n",
       "      <td>História_da_Nova_Zelândia</td>\n",
       "      <td>15487</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>eswiki</td>\n",
       "      <td>init</td>\n",
       "      <td>Microscopio</td>\n",
       "      <td>3273</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>kowiki</td>\n",
       "      <td>ready</td>\n",
       "      <td>팔자명리</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>ptwiki</td>\n",
       "      <td>loaded</td>\n",
       "      <td>Brittany_Howard</td>\n",
       "      <td>5004967</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>ptwiki</td>\n",
       "      <td>loaded</td>\n",
       "      <td>Dominic_Brown</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>enwiki</td>\n",
       "      <td>loaded</td>\n",
       "      <td>Zha_(surname)</td>\n",
       "      <td>44250652</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>ptwiki</td>\n",
       "      <td>init</td>\n",
       "      <td>Copa_Suruga_Bank_de_2019</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>hiwikiquote</td>\n",
       "      <td>init</td>\n",
       "      <td>वार्ता:Testdata:</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>mswiki</td>\n",
       "      <td>loaded</td>\n",
       "      <td>Senarai_perkataan_Inggeris_dari_asalan_Parsi</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>jawiki</td>\n",
       "      <td>ready</td>\n",
       "      <td>シュコダ15T</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>svwiki</td>\n",
       "      <td>init</td>\n",
       "      <td>Ingrid_Arthur</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>arwiki</td>\n",
       "      <td>abort</td>\n",
       "      <td>مستخدم:حسام_سينا</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>fiwiki</td>\n",
       "      <td>init</td>\n",
       "      <td>Glyseryylifosforyylikoliini</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>enwiki</td>\n",
       "      <td>init</td>\n",
       "      <td>Christian_Ramirez_(soccer,_born_1991)</td>\n",
       "      <td>39202377</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>eswiki</td>\n",
       "      <td>ready</td>\n",
       "      <td>Emel_Rojas_Castillo</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>ptwiki</td>\n",
       "      <td>init</td>\n",
       "      <td>Predefinição:QMPan2019</td>\n",
       "      <td>6049569</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>hrwiki</td>\n",
       "      <td>loaded</td>\n",
       "      <td>Atol</td>\n",
       "      <td>51236</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>ptwiki</td>\n",
       "      <td>loaded</td>\n",
       "      <td>Bad_for_You_Baby</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>enwiki</td>\n",
       "      <td>abort</td>\n",
       "      <td>Wikipedia:Articles_for_deletion/Adam_Everett_L...</td>\n",
       "      <td>61414598</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>viwiki</td>\n",
       "      <td>ready</td>\n",
       "      <td>Người_từ_chối_nhập_ngũ_có_chủ_đích</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>ptwiki</td>\n",
       "      <td>loaded</td>\n",
       "      <td>Balaenoptera_rostratella</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>ptwiki</td>\n",
       "      <td>loaded</td>\n",
       "      <td>Fajã_de_São_João</td>\n",
       "      <td>354472</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>cswiki</td>\n",
       "      <td>init</td>\n",
       "      <td>Lidský_sexuální_reakční_cyklus</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>cawiki</td>\n",
       "      <td>init</td>\n",
       "      <td>Anna_Andersen</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>mswiki</td>\n",
       "      <td>init</td>\n",
       "      <td>Sana_Ay_Ikaw_Na_Nga</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>ptwiki</td>\n",
       "      <td>ready</td>\n",
       "      <td>Óptica_geométrica</td>\n",
       "      <td>110840</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>dewiki</td>\n",
       "      <td>loaded</td>\n",
       "      <td>The_Orville</td>\n",
       "      <td>10042512</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>jawiki</td>\n",
       "      <td>init</td>\n",
       "      <td>ルイ・ベルソン</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>enwiki</td>\n",
       "      <td>loaded</td>\n",
       "      <td>Peace_Corps</td>\n",
       "      <td>23488900</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>ruwiki</td>\n",
       "      <td>ready</td>\n",
       "      <td>Крысы_(фильм,_2015)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>dewiktionary</td>\n",
       "      <td>init</td>\n",
       "      <td>Glasperlenspiel</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>eswiki</td>\n",
       "      <td>ready</td>\n",
       "      <td>Silvana_Prince</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>jawiki</td>\n",
       "      <td>loaded</td>\n",
       "      <td>アスマーン</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>enwiki</td>\n",
       "      <td>ready</td>\n",
       "      <td>A_World_to_Believe_In</td>\n",
       "      <td>14481669</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>zhwiki</td>\n",
       "      <td>loaded</td>\n",
       "      <td>維多利亞國立美術館</td>\n",
       "      <td>4520217</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>enwiki</td>\n",
       "      <td>ready</td>\n",
       "      <td>Boulevard_Haussmann</td>\n",
       "      <td>1888629</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>svwiki</td>\n",
       "      <td>loaded</td>\n",
       "      <td>Potatisskalare</td>\n",
       "      <td>162541</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>ptwiki</td>\n",
       "      <td>loaded</td>\n",
       "      <td>Manoel_Quinídio_Sobral</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>enwiki</td>\n",
       "      <td>abort</td>\n",
       "      <td>Foodpanda</td>\n",
       "      <td>42399763</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>enwiki</td>\n",
       "      <td>loaded</td>\n",
       "      <td>Metro-Goldwyn-Mayer</td>\n",
       "      <td>58819</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>eswiki</td>\n",
       "      <td>loaded</td>\n",
       "      <td>Applied_optics</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>ptwiki</td>\n",
       "      <td>init</td>\n",
       "      <td>Navega</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>ptwiki</td>\n",
       "      <td>init</td>\n",
       "      <td>Festival_do_Novo_Cinema_Latino-Americano</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            wiki  action                                         page_title  \\\n",
       "0         eswiki  loaded                              After:_En_Mil_Pedazos   \n",
       "1         itwiki    init               Lista_di_compagnie_aeree_di_bandiera   \n",
       "2   dewiktionary    init                                            Mielert   \n",
       "3         enwiki   ready                        Mask_(Fanatic_Crisis_album)   \n",
       "4         eswiki  loaded                                  Edgewall_Software   \n",
       "5         thwiki    init                                ทะไลลามะ_องค์ที่แปด   \n",
       "6         enwiki  loaded                                User:Kawnhr/sandbox   \n",
       "7         ptwiki   ready                          História_da_Nova_Zelândia   \n",
       "8         eswiki    init                                        Microscopio   \n",
       "9         kowiki   ready                                               팔자명리   \n",
       "10        ptwiki  loaded                                    Brittany_Howard   \n",
       "11        ptwiki  loaded                                      Dominic_Brown   \n",
       "12        enwiki  loaded                                      Zha_(surname)   \n",
       "13        ptwiki    init                           Copa_Suruga_Bank_de_2019   \n",
       "14   hiwikiquote    init                                   वार्ता:Testdata:   \n",
       "15        mswiki  loaded       Senarai_perkataan_Inggeris_dari_asalan_Parsi   \n",
       "16        jawiki   ready                                            シュコダ15T   \n",
       "17        svwiki    init                                      Ingrid_Arthur   \n",
       "18        arwiki   abort                                   مستخدم:حسام_سينا   \n",
       "19        fiwiki    init                        Glyseryylifosforyylikoliini   \n",
       "20        enwiki    init              Christian_Ramirez_(soccer,_born_1991)   \n",
       "21        eswiki   ready                                Emel_Rojas_Castillo   \n",
       "22        ptwiki    init                             Predefinição:QMPan2019   \n",
       "23        hrwiki  loaded                                               Atol   \n",
       "24        ptwiki  loaded                                   Bad_for_You_Baby   \n",
       "25        enwiki   abort  Wikipedia:Articles_for_deletion/Adam_Everett_L...   \n",
       "26        viwiki   ready                 Người_từ_chối_nhập_ngũ_có_chủ_đích   \n",
       "27        ptwiki  loaded                           Balaenoptera_rostratella   \n",
       "28        ptwiki  loaded                                   Fajã_de_São_João   \n",
       "29        cswiki    init                     Lidský_sexuální_reakční_cyklus   \n",
       "30        cawiki    init                                      Anna_Andersen   \n",
       "31        mswiki    init                                Sana_Ay_Ikaw_Na_Nga   \n",
       "32        ptwiki   ready                                  Óptica_geométrica   \n",
       "33        dewiki  loaded                                        The_Orville   \n",
       "34        jawiki    init                                            ルイ・ベルソン   \n",
       "35        enwiki  loaded                                        Peace_Corps   \n",
       "36        ruwiki   ready                                Крысы_(фильм,_2015)   \n",
       "37  dewiktionary    init                                    Glasperlenspiel   \n",
       "38        eswiki   ready                                     Silvana_Prince   \n",
       "39        jawiki  loaded                                              アスマーン   \n",
       "40        enwiki   ready                              A_World_to_Believe_In   \n",
       "41        zhwiki  loaded                                          維多利亞國立美術館   \n",
       "42        enwiki   ready                                Boulevard_Haussmann   \n",
       "43        svwiki  loaded                                     Potatisskalare   \n",
       "44        ptwiki  loaded                             Manoel_Quinídio_Sobral   \n",
       "45        enwiki   abort                                          Foodpanda   \n",
       "46        enwiki  loaded                                Metro-Goldwyn-Mayer   \n",
       "47        eswiki  loaded                                     Applied_optics   \n",
       "48        ptwiki    init                                             Navega   \n",
       "49        ptwiki    init           Festival_do_Novo_Cinema_Latino-Americano   \n",
       "\n",
       "     page_id  page_ns  \n",
       "0          0        0  \n",
       "1    1988047        0  \n",
       "2          0        0  \n",
       "3   55479138        0  \n",
       "4          0        0  \n",
       "5          0        0  \n",
       "6          0        2  \n",
       "7      15487        0  \n",
       "8       3273        0  \n",
       "9          0        0  \n",
       "10   5004967        0  \n",
       "11         0        0  \n",
       "12  44250652        0  \n",
       "13         0        0  \n",
       "14         0        1  \n",
       "15         0        0  \n",
       "16         0        0  \n",
       "17         0        0  \n",
       "18         0        2  \n",
       "19         0        0  \n",
       "20  39202377        0  \n",
       "21         0        0  \n",
       "22   6049569       10  \n",
       "23     51236        0  \n",
       "24         0        0  \n",
       "25  61414598        4  \n",
       "26         0        0  \n",
       "27         0        0  \n",
       "28    354472        0  \n",
       "29         0        0  \n",
       "30         0        0  \n",
       "31         0        0  \n",
       "32    110840        0  \n",
       "33  10042512        0  \n",
       "34         0        0  \n",
       "35  23488900        0  \n",
       "36         0        0  \n",
       "37         0        0  \n",
       "38         0        0  \n",
       "39         0        0  \n",
       "40  14481669        0  \n",
       "41   4520217        0  \n",
       "42   1888629        0  \n",
       "43    162541        0  \n",
       "44         0        0  \n",
       "45  42399763        0  \n",
       "46     58819        0  \n",
       "47         0        0  \n",
       "48         0        0  \n",
       "49         0        0  "
      ]
     },
     "execution_count": 370,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hive.run(\"\"\"\n",
    "select\n",
    "    wiki,\n",
    "    event.action,\n",
    "    event.page_title,\n",
    "    event.page_id,\n",
    "    event.page_ns\n",
    "from event.editattemptstep\n",
    "where\n",
    "    event.revision_id = 0 and\n",
    "    year = 2019 and month = 8 and day = 8\n",
    "limit 50\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 378,
   "metadata": {},
   "outputs": [],
   "source": [
    "missing_rev_id_events_r = hive.run(\"\"\"\n",
    "select\n",
    "    event.platform,\n",
    "    event.editor_interface,\n",
    "    event.action,\n",
    "    count(*) as events\n",
    "from event.editattemptstep\n",
    "where\n",
    "    event.revision_id = 0 and\n",
    "    event.page_id != 0 and\n",
    "    year = 2019 and month = 8 and day = 7\n",
    "group by\n",
    "    event.platform,\n",
    "    event.editor_interface,\n",
    "    event.action\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These events with \"missing\" revision IDs are concentrated among the earlier events, and essentially none are save success events, which means they aren't very severe for our problems here."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 381,
   "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>action</th>\n",
       "      <th>abort</th>\n",
       "      <th>init</th>\n",
       "      <th>loaded</th>\n",
       "      <th>ready</th>\n",
       "      <th>saveAttempt</th>\n",
       "      <th>saveFailure</th>\n",
       "      <th>saveIntent</th>\n",
       "      <th>saveSuccess</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>platform</th>\n",
       "      <th>editor_interface</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 rowspan=\"2\" valign=\"top\">desktop</th>\n",
       "      <th>visualeditor</th>\n",
       "      <td>518</td>\n",
       "      <td>778</td>\n",
       "      <td>711</td>\n",
       "      <td>711</td>\n",
       "      <td>207</td>\n",
       "      <td>56</td>\n",
       "      <td>199</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>wikitext</th>\n",
       "      <td>8862</td>\n",
       "      <td>0</td>\n",
       "      <td>26543</td>\n",
       "      <td>26625</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">phone</th>\n",
       "      <th>visualeditor</th>\n",
       "      <td>4</td>\n",
       "      <td>1678</td>\n",
       "      <td>1377</td>\n",
       "      <td>1380</td>\n",
       "      <td>235</td>\n",
       "      <td>81</td>\n",
       "      <td>196</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>wikitext</th>\n",
       "      <td>941</td>\n",
       "      <td>5342</td>\n",
       "      <td>5311</td>\n",
       "      <td>5315</td>\n",
       "      <td>183</td>\n",
       "      <td>35</td>\n",
       "      <td>253</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "action                     abort  init  loaded  ready  saveAttempt  \\\n",
       "platform editor_interface                                            \n",
       "desktop  visualeditor        518   778     711    711          207   \n",
       "         wikitext           8862     0   26543  26625            0   \n",
       "phone    visualeditor          4  1678    1377   1380          235   \n",
       "         wikitext            941  5342    5311   5315          183   \n",
       "\n",
       "action                     saveFailure  saveIntent  saveSuccess  \n",
       "platform editor_interface                                        \n",
       "desktop  visualeditor               56         199            1  \n",
       "         wikitext                    0           0            0  \n",
       "phone    visualeditor               81         196            3  \n",
       "         wikitext                   35         253            2  "
      ]
     },
     "execution_count": 381,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "missing_rev_id_events = (\n",
    "    missing_rev_id_events_r\n",
    "    .pivot_table(index=[\"platform\", \"editor_interface\"], columns=\"action\")\n",
    "    .xs(\"events\", axis=1)\n",
    "    .fillna(0)\n",
    "    .applymap(int)\n",
    ")\n",
    "\n",
    "missing_rev_id_events"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 384,
   "metadata": {},
   "outputs": [],
   "source": [
    "missing_rev_id_prop_r = hive.run(\"\"\"\n",
    "select\n",
    "    event.platform,\n",
    "    event.editor_interface,\n",
    "    event.action,\n",
    "    sum(cast(event.revision_id = 0 and event.page_id != 0 as int)) / count(*) as missing_rev_id\n",
    "from event.editattemptstep\n",
    "where\n",
    "    year = 2019 and month = 8 and day = 7\n",
    "group by\n",
    "    event.platform,\n",
    "    event.editor_interface,\n",
    "    event.action\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 388,
   "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>action</th>\n",
       "      <th>abort</th>\n",
       "      <th>init</th>\n",
       "      <th>loaded</th>\n",
       "      <th>ready</th>\n",
       "      <th>saveAttempt</th>\n",
       "      <th>saveFailure</th>\n",
       "      <th>saveIntent</th>\n",
       "      <th>saveSuccess</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>platform</th>\n",
       "      <th>editor_interface</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 rowspan=\"3\" valign=\"top\">desktop</th>\n",
       "      <th>visualeditor</th>\n",
       "      <td>3.0%</td>\n",
       "      <td>3.8%</td>\n",
       "      <td>3.7%</td>\n",
       "      <td>3.7%</td>\n",
       "      <td>11.6%</td>\n",
       "      <td>12.9%</td>\n",
       "      <td>11.9%</td>\n",
       "      <td>0.1%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>wikitext</th>\n",
       "      <td>48.0%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>68.7%</td>\n",
       "      <td>68.5%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>wikitext-2017</th>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">phone</th>\n",
       "      <th>visualeditor</th>\n",
       "      <td>0.0%</td>\n",
       "      <td>3.1%</td>\n",
       "      <td>3.6%</td>\n",
       "      <td>3.6%</td>\n",
       "      <td>3.7%</td>\n",
       "      <td>6.1%</td>\n",
       "      <td>3.1%</td>\n",
       "      <td>0.1%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>wikitext</th>\n",
       "      <td>1.2%</td>\n",
       "      <td>4.8%</td>\n",
       "      <td>4.8%</td>\n",
       "      <td>4.8%</td>\n",
       "      <td>3.6%</td>\n",
       "      <td>4.9%</td>\n",
       "      <td>3.4%</td>\n",
       "      <td>0.0%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "action                     abort  init loaded  ready saveAttempt saveFailure  \\\n",
       "platform editor_interface                                                      \n",
       "desktop  visualeditor       3.0%  3.8%   3.7%   3.7%       11.6%       12.9%   \n",
       "         wikitext          48.0%  0.0%  68.7%  68.5%        0.0%        0.0%   \n",
       "         wikitext-2017      0.0%  0.0%   0.0%   0.0%        0.0%        0.0%   \n",
       "phone    visualeditor       0.0%  3.1%   3.6%   3.6%        3.7%        6.1%   \n",
       "         wikitext           1.2%  4.8%   4.8%   4.8%        3.6%        4.9%   \n",
       "\n",
       "action                    saveIntent saveSuccess  \n",
       "platform editor_interface                         \n",
       "desktop  visualeditor          11.9%        0.1%  \n",
       "         wikitext               0.0%        0.0%  \n",
       "         wikitext-2017          0.0%        0.0%  \n",
       "phone    visualeditor           3.1%        0.1%  \n",
       "         wikitext               3.4%        0.0%  "
      ]
     },
     "execution_count": 388,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "missing_rev_id_prop = (\n",
    "    missing_rev_id_prop_r\n",
    "    .pivot_table(index=[\"platform\", \"editor_interface\"], columns=\"action\")\n",
    "    .xs(\"missing_rev_id\", axis=1)\n",
    "    .fillna(0)\n",
    "    .applymap(pct_str)\n",
    ")\n",
    "\n",
    "missing_rev_id_prop"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With that out of the way, do the non-zero revision IDs that are being logged in `saveSuccess` events represent the newly saved edits, as they should?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 320,
   "metadata": {},
   "outputs": [],
   "source": [
    "rev_ids_r = hive.run(\"\"\"\n",
    "with saves as (\n",
    "    select\n",
    "        dt,\n",
    "        event.editing_session_id as attempt_id,\n",
    "        event.revision_id as revision_id,\n",
    "        event.platform as platform,\n",
    "        event.editor_interface as editor\n",
    "    from event.editattemptstep\n",
    "    where\n",
    "        event.action = \"saveSuccess\" and\n",
    "        year = 2019 and (\n",
    "            (month = 6 and day > 23) or\n",
    "            (month = 7)\n",
    "        ) and\n",
    "        -- Remove Flow and other non-standard edits\n",
    "        event.integration = \"page\"\n",
    "),\n",
    "pre_saves as (\n",
    "    select\n",
    "        event.editing_session_id as attempt_id,\n",
    "        max(event.revision_id) as max_revision_id\n",
    "    from event.editattemptstep\n",
    "    where\n",
    "        event.action != \"saveSuccess\" and\n",
    "        year = 2019 and (\n",
    "            (month = 6 and day > 23) or\n",
    "            (month = 7)\n",
    "        ) and\n",
    "        -- Remove Flow and other non-standard edits\n",
    "        event.integration = \"page\"\n",
    "    group by event.editing_session_id\n",
    ")\n",
    "select\n",
    "    date_format(dt, \"yyyy-MM-dd\") as date,\n",
    "    platform,\n",
    "    editor,\n",
    "    sum(cast(saves.revision_id > pre_saves.max_revision_id as int)) / count(*) as save_has_greater_revision_id\n",
    "from saves \n",
    "left join pre_saves\n",
    "on saves.attempt_id = pre_saves.attempt_id\n",
    "group by\n",
    "    date_format(dt, \"yyyy-MM-dd\"),\n",
    "    platform,\n",
    "    editor\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 321,
   "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>editor</th>\n",
       "      <th>date</th>\n",
       "      <th>desktop visualeditor</th>\n",
       "      <th>desktop wikitext</th>\n",
       "      <th>desktop wikitext-2017</th>\n",
       "      <th>phone visualeditor</th>\n",
       "      <th>phone wikitext</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-06-24</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>96.4%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-06-25</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>95.6%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-06-26</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>95.9%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-06-27</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>95.9%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-06-28</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>96.1%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2019-06-29</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>96.7%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2019-06-30</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>96.8%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2019-07-01</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>96.2%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2019-07-02</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>96.1%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2019-07-03</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>96.4%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2019-07-04</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>96.3%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2019-07-05</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>96.1%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2019-07-06</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>96.8%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2019-07-07</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>96.3%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2019-07-08</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>96.6%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2019-07-09</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>96.7%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>0.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2019-07-10</td>\n",
       "      <td>0.2%</td>\n",
       "      <td>96.7%</td>\n",
       "      <td>0.3%</td>\n",
       "      <td>0.1%</td>\n",
       "      <td>0.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2019-07-11</td>\n",
       "      <td>16.4%</td>\n",
       "      <td>96.2%</td>\n",
       "      <td>18.1%</td>\n",
       "      <td>19.5%</td>\n",
       "      <td>21.8%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2019-07-12</td>\n",
       "      <td>95.8%</td>\n",
       "      <td>96.3%</td>\n",
       "      <td>96.5%</td>\n",
       "      <td>97.5%</td>\n",
       "      <td>98.9%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2019-07-13</td>\n",
       "      <td>96.8%</td>\n",
       "      <td>96.9%</td>\n",
       "      <td>96.9%</td>\n",
       "      <td>98.2%</td>\n",
       "      <td>99.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2019-07-14</td>\n",
       "      <td>96.2%</td>\n",
       "      <td>97.0%</td>\n",
       "      <td>98.3%</td>\n",
       "      <td>97.6%</td>\n",
       "      <td>99.2%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2019-07-15</td>\n",
       "      <td>96.6%</td>\n",
       "      <td>96.6%</td>\n",
       "      <td>98.9%</td>\n",
       "      <td>97.7%</td>\n",
       "      <td>99.3%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2019-07-16</td>\n",
       "      <td>96.9%</td>\n",
       "      <td>96.6%</td>\n",
       "      <td>97.0%</td>\n",
       "      <td>98.1%</td>\n",
       "      <td>99.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2019-07-17</td>\n",
       "      <td>96.5%</td>\n",
       "      <td>97.4%</td>\n",
       "      <td>98.2%</td>\n",
       "      <td>98.1%</td>\n",
       "      <td>99.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2019-07-18</td>\n",
       "      <td>96.9%</td>\n",
       "      <td>96.4%</td>\n",
       "      <td>98.9%</td>\n",
       "      <td>98.0%</td>\n",
       "      <td>99.1%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2019-07-19</td>\n",
       "      <td>97.1%</td>\n",
       "      <td>97.2%</td>\n",
       "      <td>98.6%</td>\n",
       "      <td>98.0%</td>\n",
       "      <td>99.1%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2019-07-20</td>\n",
       "      <td>96.7%</td>\n",
       "      <td>97.1%</td>\n",
       "      <td>94.6%</td>\n",
       "      <td>98.2%</td>\n",
       "      <td>98.9%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2019-07-21</td>\n",
       "      <td>97.5%</td>\n",
       "      <td>97.0%</td>\n",
       "      <td>98.3%</td>\n",
       "      <td>97.8%</td>\n",
       "      <td>99.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2019-07-22</td>\n",
       "      <td>96.8%</td>\n",
       "      <td>96.6%</td>\n",
       "      <td>97.6%</td>\n",
       "      <td>98.1%</td>\n",
       "      <td>99.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2019-07-23</td>\n",
       "      <td>97.2%</td>\n",
       "      <td>97.0%</td>\n",
       "      <td>98.0%</td>\n",
       "      <td>98.0%</td>\n",
       "      <td>98.7%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>2019-07-24</td>\n",
       "      <td>96.6%</td>\n",
       "      <td>96.7%</td>\n",
       "      <td>98.9%</td>\n",
       "      <td>97.9%</td>\n",
       "      <td>98.8%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>2019-07-25</td>\n",
       "      <td>97.4%</td>\n",
       "      <td>96.6%</td>\n",
       "      <td>97.7%</td>\n",
       "      <td>97.8%</td>\n",
       "      <td>98.8%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>2019-07-26</td>\n",
       "      <td>97.4%</td>\n",
       "      <td>97.6%</td>\n",
       "      <td>98.9%</td>\n",
       "      <td>98.3%</td>\n",
       "      <td>99.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2019-07-27</td>\n",
       "      <td>97.0%</td>\n",
       "      <td>97.4%</td>\n",
       "      <td>95.0%</td>\n",
       "      <td>97.7%</td>\n",
       "      <td>98.7%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>2019-07-28</td>\n",
       "      <td>97.4%</td>\n",
       "      <td>97.1%</td>\n",
       "      <td>97.5%</td>\n",
       "      <td>98.0%</td>\n",
       "      <td>98.9%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>2019-07-29</td>\n",
       "      <td>95.8%</td>\n",
       "      <td>97.5%</td>\n",
       "      <td>98.0%</td>\n",
       "      <td>97.9%</td>\n",
       "      <td>99.1%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>2019-07-30</td>\n",
       "      <td>96.8%</td>\n",
       "      <td>97.2%</td>\n",
       "      <td>96.2%</td>\n",
       "      <td>97.7%</td>\n",
       "      <td>98.5%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>2019-07-31</td>\n",
       "      <td>97.6%</td>\n",
       "      <td>97.5%</td>\n",
       "      <td>98.6%</td>\n",
       "      <td>97.7%</td>\n",
       "      <td>99.2%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "editor        date desktop visualeditor desktop wikitext  \\\n",
       "0       2019-06-24                 0.0%            96.4%   \n",
       "1       2019-06-25                 0.0%            95.6%   \n",
       "2       2019-06-26                 0.0%            95.9%   \n",
       "3       2019-06-27                 0.0%            95.9%   \n",
       "4       2019-06-28                 0.0%            96.1%   \n",
       "5       2019-06-29                 0.0%            96.7%   \n",
       "6       2019-06-30                 0.0%            96.8%   \n",
       "7       2019-07-01                 0.0%            96.2%   \n",
       "8       2019-07-02                 0.0%            96.1%   \n",
       "9       2019-07-03                 0.0%            96.4%   \n",
       "10      2019-07-04                 0.0%            96.3%   \n",
       "11      2019-07-05                 0.0%            96.1%   \n",
       "12      2019-07-06                 0.0%            96.8%   \n",
       "13      2019-07-07                 0.0%            96.3%   \n",
       "14      2019-07-08                 0.0%            96.6%   \n",
       "15      2019-07-09                 0.0%            96.7%   \n",
       "16      2019-07-10                 0.2%            96.7%   \n",
       "17      2019-07-11                16.4%            96.2%   \n",
       "18      2019-07-12                95.8%            96.3%   \n",
       "19      2019-07-13                96.8%            96.9%   \n",
       "20      2019-07-14                96.2%            97.0%   \n",
       "21      2019-07-15                96.6%            96.6%   \n",
       "22      2019-07-16                96.9%            96.6%   \n",
       "23      2019-07-17                96.5%            97.4%   \n",
       "24      2019-07-18                96.9%            96.4%   \n",
       "25      2019-07-19                97.1%            97.2%   \n",
       "26      2019-07-20                96.7%            97.1%   \n",
       "27      2019-07-21                97.5%            97.0%   \n",
       "28      2019-07-22                96.8%            96.6%   \n",
       "29      2019-07-23                97.2%            97.0%   \n",
       "30      2019-07-24                96.6%            96.7%   \n",
       "31      2019-07-25                97.4%            96.6%   \n",
       "32      2019-07-26                97.4%            97.6%   \n",
       "33      2019-07-27                97.0%            97.4%   \n",
       "34      2019-07-28                97.4%            97.1%   \n",
       "35      2019-07-29                95.8%            97.5%   \n",
       "36      2019-07-30                96.8%            97.2%   \n",
       "37      2019-07-31                97.6%            97.5%   \n",
       "\n",
       "editor desktop wikitext-2017 phone visualeditor phone wikitext  \n",
       "0                       0.0%               0.0%           0.0%  \n",
       "1                       0.0%               0.0%           0.0%  \n",
       "2                       0.0%               0.0%           0.0%  \n",
       "3                       0.0%               0.0%           0.0%  \n",
       "4                       0.0%               0.0%           0.0%  \n",
       "5                       0.0%               0.0%           0.0%  \n",
       "6                       0.0%               0.0%           0.0%  \n",
       "7                       0.0%               0.0%           0.0%  \n",
       "8                       0.0%               0.0%           0.0%  \n",
       "9                       0.0%               0.0%           0.0%  \n",
       "10                      0.0%               0.0%           0.0%  \n",
       "11                      0.0%               0.0%           0.0%  \n",
       "12                      0.0%               0.0%           0.0%  \n",
       "13                      0.0%               0.0%           0.0%  \n",
       "14                      0.0%               0.0%           0.0%  \n",
       "15                      0.0%               0.0%           0.0%  \n",
       "16                      0.3%               0.1%           0.0%  \n",
       "17                     18.1%              19.5%          21.8%  \n",
       "18                     96.5%              97.5%          98.9%  \n",
       "19                     96.9%              98.2%          99.0%  \n",
       "20                     98.3%              97.6%          99.2%  \n",
       "21                     98.9%              97.7%          99.3%  \n",
       "22                     97.0%              98.1%          99.0%  \n",
       "23                     98.2%              98.1%          99.0%  \n",
       "24                     98.9%              98.0%          99.1%  \n",
       "25                     98.6%              98.0%          99.1%  \n",
       "26                     94.6%              98.2%          98.9%  \n",
       "27                     98.3%              97.8%          99.0%  \n",
       "28                     97.6%              98.1%          99.0%  \n",
       "29                     98.0%              98.0%          98.7%  \n",
       "30                     98.9%              97.9%          98.8%  \n",
       "31                     97.7%              97.8%          98.8%  \n",
       "32                     98.9%              98.3%          99.0%  \n",
       "33                     95.0%              97.7%          98.7%  \n",
       "34                     97.5%              98.0%          98.9%  \n",
       "35                     98.0%              97.9%          99.1%  \n",
       "36                     96.2%              97.7%          98.5%  \n",
       "37                     98.6%              97.7%          99.2%  "
      ]
     },
     "execution_count": 321,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rev_ids = (\n",
    "    rev_ids_r\n",
    "    .assign(\n",
    "        editor=lambda df: df[\"platform\"] + \" \" + df[\"editor\"]\n",
    "    )\n",
    "    .drop(\"platform\", axis=1)\n",
    "    .pivot(index=\"date\", columns=\"editor\")\n",
    "    .fillna(0)\n",
    "    .xs(\"save_has_greater_revision_id\", axis=1)\n",
    "    .applymap(pct_str)\n",
    "    .reset_index()\n",
    ")\n",
    "\n",
    "rev_ids"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's get a sample of those remaining ~3% that don't properly log the new ID."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 392,
   "metadata": {},
   "outputs": [],
   "source": [
    "old_rev_ids_r = hive.run(\"\"\"\n",
    "with saves as (\n",
    "    select\n",
    "        dt,\n",
    "        event.editing_session_id as attempt_id,\n",
    "        event.revision_id as saved_revision_id,\n",
    "        event.platform as platform,\n",
    "        event.editor_interface as editor,\n",
    "        event.user_id as user_id,\n",
    "        wiki,\n",
    "        event.page_title as page_title,\n",
    "    from event.editattemptstep\n",
    "    where\n",
    "        event.action = \"saveSuccess\" and\n",
    "        year = 2019 and month = 8 and day = 8 and\n",
    "        -- Remove Flow and other non-standard edits\n",
    "        event.integration = \"page\"\n",
    "),\n",
    "pre_saves as (\n",
    "    select\n",
    "        event.editing_session_id as attempt_id,\n",
    "        max(event.revision_id) as base_revision_id\n",
    "    from event.editattemptstep\n",
    "    where\n",
    "        event.action != \"saveSuccess\" and\n",
    "        year = 2019 and month = 8 and day = 8 and\n",
    "        -- Remove Flow and other non-standard edits\n",
    "        event.integration = \"page\"\n",
    "    group by event.editing_session_id\n",
    ")\n",
    "select\n",
    "    wiki,\n",
    "    user_id,\n",
    "    page_title,\n",
    "    base_revision_id,\n",
    "    saved_revision_id,\n",
    "    dt,\n",
    "    \n",
    "\n",
    "from saves \n",
    "left join pre_saves\n",
    "on saves.attempt_id = pre_saves.attempt_id\n",
    "where saved_revision_id <= base_revision_id\n",
    "limit 1000\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 395,
   "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>dt</th>\n",
       "      <th>attempt_id</th>\n",
       "      <th>saved_revision_id</th>\n",
       "      <th>platform</th>\n",
       "      <th>editor</th>\n",
       "      <th>wiki</th>\n",
       "      <th>page_ns</th>\n",
       "      <th>page_id</th>\n",
       "      <th>page_title</th>\n",
       "      <th>useragent</th>\n",
       "      <th>attempt_id</th>\n",
       "      <th>base_revision_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>533</th>\n",
       "      <td>2019-08-08T19:58:31Z</td>\n",
       "      <td>e9e3ea503b2e38615a36f68b323a49db</td>\n",
       "      <td>909966419</td>\n",
       "      <td>desktop</td>\n",
       "      <td>wikitext</td>\n",
       "      <td>enwiki</td>\n",
       "      <td>0</td>\n",
       "      <td>60646188</td>\n",
       "      <td>2004 Alor earthquake</td>\n",
       "      <td>{\"browser_family\":\"Chrome\",\"browser_major\":\"49...</td>\n",
       "      <td>e9e3ea503b2e38615a36f68b323a49db</td>\n",
       "      <td>909966419</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-08-08T00:10:54Z</td>\n",
       "      <td>0163f490440fffd24b9187f15ace687c</td>\n",
       "      <td>892063186</td>\n",
       "      <td>desktop</td>\n",
       "      <td>wikitext</td>\n",
       "      <td>enwiki</td>\n",
       "      <td>100</td>\n",
       "      <td>57321777</td>\n",
       "      <td>Portal:Alpine Rhine Valley</td>\n",
       "      <td>{\"browser_family\":\"Chrome\",\"browser_major\":\"75...</td>\n",
       "      <td>0163f490440fffd24b9187f15ace687c</td>\n",
       "      <td>892063186</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>269</th>\n",
       "      <td>2019-08-08T19:27:36Z</td>\n",
       "      <td>70da7d8a5ca469968f23</td>\n",
       "      <td>909961371</td>\n",
       "      <td>phone</td>\n",
       "      <td>visualeditor</td>\n",
       "      <td>enwiki</td>\n",
       "      <td>0</td>\n",
       "      <td>1325666</td>\n",
       "      <td>Thovalai</td>\n",
       "      <td>{\"browser_family\":\"Chrome Mobile\",\"browser_maj...</td>\n",
       "      <td>70da7d8a5ca469968f23</td>\n",
       "      <td>909961371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>507</th>\n",
       "      <td>2019-08-08T16:49:27Z</td>\n",
       "      <td>dc5806a0bef703f39241c939abb234e3</td>\n",
       "      <td>3869485</td>\n",
       "      <td>desktop</td>\n",
       "      <td>wikitext</td>\n",
       "      <td>mkwiki</td>\n",
       "      <td>0</td>\n",
       "      <td>11257</td>\n",
       "      <td>Луковица (Македонска Каменица)</td>\n",
       "      <td>{\"browser_family\":\"Mobile Safari\",\"browser_maj...</td>\n",
       "      <td>dc5806a0bef703f39241c939abb234e3</td>\n",
       "      <td>3869485</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>453</th>\n",
       "      <td>2019-08-08T00:30:50Z</td>\n",
       "      <td>c11e7e5025fa419429d18465ff91892a</td>\n",
       "      <td>118080628</td>\n",
       "      <td>desktop</td>\n",
       "      <td>wikitext</td>\n",
       "      <td>eswiki</td>\n",
       "      <td>0</td>\n",
       "      <td>7085655</td>\n",
       "      <td>Quintino (DJ)</td>\n",
       "      <td>{\"browser_family\":\"Chrome\",\"browser_major\":\"75...</td>\n",
       "      <td>c11e7e5025fa419429d18465ff91892a</td>\n",
       "      <td>118080628</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202</th>\n",
       "      <td>2019-08-08T01:51:29Z</td>\n",
       "      <td>578ed5d07a883a22346b379eeafb321e</td>\n",
       "      <td>909856158</td>\n",
       "      <td>desktop</td>\n",
       "      <td>wikitext</td>\n",
       "      <td>enwiki</td>\n",
       "      <td>0</td>\n",
       "      <td>1072260</td>\n",
       "      <td>Ha*Ash</td>\n",
       "      <td>{\"browser_family\":\"Opera\",\"browser_major\":\"62\"...</td>\n",
       "      <td>578ed5d07a883a22346b379eeafb321e</td>\n",
       "      <td>909856158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>311</th>\n",
       "      <td>2019-08-08T11:43:27Z</td>\n",
       "      <td>7f301040aae12b7a9d0a8d313c507578</td>\n",
       "      <td>909906264</td>\n",
       "      <td>desktop</td>\n",
       "      <td>wikitext</td>\n",
       "      <td>enwiki</td>\n",
       "      <td>2</td>\n",
       "      <td>47513516</td>\n",
       "      <td>User:M00036/sandbox</td>\n",
       "      <td>{\"browser_family\":\"Chrome\",\"browser_major\":\"75...</td>\n",
       "      <td>7f301040aae12b7a9d0a8d313c507578</td>\n",
       "      <td>909906264</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>506</th>\n",
       "      <td>2019-08-08T16:49:27Z</td>\n",
       "      <td>dc5806a0bef703f39241c939abb234e3</td>\n",
       "      <td>3869485</td>\n",
       "      <td>desktop</td>\n",
       "      <td>wikitext</td>\n",
       "      <td>mkwiki</td>\n",
       "      <td>0</td>\n",
       "      <td>11257</td>\n",
       "      <td>Луковица (Македонска Каменица)</td>\n",
       "      <td>{\"browser_family\":\"Mobile Safari\",\"browser_maj...</td>\n",
       "      <td>dc5806a0bef703f39241c939abb234e3</td>\n",
       "      <td>3869485</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>530</th>\n",
       "      <td>2019-08-08T01:34:36Z</td>\n",
       "      <td>e8ac551443886886ff01</td>\n",
       "      <td>8439683</td>\n",
       "      <td>phone</td>\n",
       "      <td>wikitext</td>\n",
       "      <td>thwiki</td>\n",
       "      <td>0</td>\n",
       "      <td>42096</td>\n",
       "      <td>ศาสนาฮินดู</td>\n",
       "      <td>{\"browser_family\":\"Mobile Safari\",\"browser_maj...</td>\n",
       "      <td>e8ac551443886886ff01</td>\n",
       "      <td>8439683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>595</th>\n",
       "      <td>2019-08-08T13:48:15Z</td>\n",
       "      <td>fde3bb8214f5becd988a</td>\n",
       "      <td>15425021</td>\n",
       "      <td>phone</td>\n",
       "      <td>visualeditor</td>\n",
       "      <td>idwiki</td>\n",
       "      <td>0</td>\n",
       "      <td>2661028</td>\n",
       "      <td>Cinta_Suci</td>\n",
       "      <td>{\"browser_family\":\"Mobile Safari\",\"browser_maj...</td>\n",
       "      <td>fde3bb8214f5becd988a</td>\n",
       "      <td>15425021</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       dt                        attempt_id  \\\n",
       "533  2019-08-08T19:58:31Z  e9e3ea503b2e38615a36f68b323a49db   \n",
       "3    2019-08-08T00:10:54Z  0163f490440fffd24b9187f15ace687c   \n",
       "269  2019-08-08T19:27:36Z              70da7d8a5ca469968f23   \n",
       "507  2019-08-08T16:49:27Z  dc5806a0bef703f39241c939abb234e3   \n",
       "453  2019-08-08T00:30:50Z  c11e7e5025fa419429d18465ff91892a   \n",
       "202  2019-08-08T01:51:29Z  578ed5d07a883a22346b379eeafb321e   \n",
       "311  2019-08-08T11:43:27Z  7f301040aae12b7a9d0a8d313c507578   \n",
       "506  2019-08-08T16:49:27Z  dc5806a0bef703f39241c939abb234e3   \n",
       "530  2019-08-08T01:34:36Z              e8ac551443886886ff01   \n",
       "595  2019-08-08T13:48:15Z              fde3bb8214f5becd988a   \n",
       "\n",
       "     saved_revision_id platform        editor    wiki  page_ns   page_id  \\\n",
       "533          909966419  desktop      wikitext  enwiki        0  60646188   \n",
       "3            892063186  desktop      wikitext  enwiki      100  57321777   \n",
       "269          909961371    phone  visualeditor  enwiki        0   1325666   \n",
       "507            3869485  desktop      wikitext  mkwiki        0     11257   \n",
       "453          118080628  desktop      wikitext  eswiki        0   7085655   \n",
       "202          909856158  desktop      wikitext  enwiki        0   1072260   \n",
       "311          909906264  desktop      wikitext  enwiki        2  47513516   \n",
       "506            3869485  desktop      wikitext  mkwiki        0     11257   \n",
       "530            8439683    phone      wikitext  thwiki        0     42096   \n",
       "595           15425021    phone  visualeditor  idwiki        0   2661028   \n",
       "\n",
       "                         page_title  \\\n",
       "533            2004 Alor earthquake   \n",
       "3        Portal:Alpine Rhine Valley   \n",
       "269                        Thovalai   \n",
       "507  Луковица (Македонска Каменица)   \n",
       "453                   Quintino (DJ)   \n",
       "202                          Ha*Ash   \n",
       "311             User:M00036/sandbox   \n",
       "506  Луковица (Македонска Каменица)   \n",
       "530                      ศาสนาฮินดู   \n",
       "595                      Cinta_Suci   \n",
       "\n",
       "                                             useragent  \\\n",
       "533  {\"browser_family\":\"Chrome\",\"browser_major\":\"49...   \n",
       "3    {\"browser_family\":\"Chrome\",\"browser_major\":\"75...   \n",
       "269  {\"browser_family\":\"Chrome Mobile\",\"browser_maj...   \n",
       "507  {\"browser_family\":\"Mobile Safari\",\"browser_maj...   \n",
       "453  {\"browser_family\":\"Chrome\",\"browser_major\":\"75...   \n",
       "202  {\"browser_family\":\"Opera\",\"browser_major\":\"62\"...   \n",
       "311  {\"browser_family\":\"Chrome\",\"browser_major\":\"75...   \n",
       "506  {\"browser_family\":\"Mobile Safari\",\"browser_maj...   \n",
       "530  {\"browser_family\":\"Mobile Safari\",\"browser_maj...   \n",
       "595  {\"browser_family\":\"Mobile Safari\",\"browser_maj...   \n",
       "\n",
       "                           attempt_id  base_revision_id  \n",
       "533  e9e3ea503b2e38615a36f68b323a49db         909966419  \n",
       "3    0163f490440fffd24b9187f15ace687c         892063186  \n",
       "269              70da7d8a5ca469968f23         909961371  \n",
       "507  dc5806a0bef703f39241c939abb234e3           3869485  \n",
       "453  c11e7e5025fa419429d18465ff91892a         118080628  \n",
       "202  578ed5d07a883a22346b379eeafb321e         909856158  \n",
       "311  7f301040aae12b7a9d0a8d313c507578         909906264  \n",
       "506  dc5806a0bef703f39241c939abb234e3           3869485  \n",
       "530              e8ac551443886886ff01           8439683  \n",
       "595              fde3bb8214f5becd988a          15425021  "
      ]
     },
     "execution_count": 395,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "old_rev_ids_r.sample(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Editor switching"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 308,
   "metadata": {},
   "outputs": [],
   "source": [
    "switches_r = hive.run(\"\"\"\n",
    "select\n",
    "    date,\n",
    "    editor,\n",
    "    sum(cast(switches >= 1 as int)) / count(*) as sessions_with_switches\n",
    "from (\n",
    "    select\n",
    "        date_format(dt, \"yyyy-MM-dd\") as date,\n",
    "        event.editing_session_id as editingsessionid,\n",
    "        concat(event.platform, \" \", event.editor_interface) as editor\n",
    "    from event.editattemptstep\n",
    "    where\n",
    "        event.action = \"ready\" and\n",
    "        year = 2019 and (\n",
    "            (month = 6 and day > 23) or\n",
    "            (month = 7)\n",
    "        )\n",
    ") readies\n",
    "left join (\n",
    "    select\n",
    "        event.editingsessionid as editingsessionid,\n",
    "        count(*) as switches\n",
    "    from event.visualeditorfeatureuse\n",
    "    where\n",
    "        event.feature = \"editor-switch\" and\n",
    "        year = 2019 and (\n",
    "            (month = 6 and day > 23) or\n",
    "            (month = 7)\n",
    "        )\n",
    "    group by event.editingsessionid\n",
    ") switches\n",
    "on readies.editingsessionid = switches.editingsessionid\n",
    "group by date, editor\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 313,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6\" ><thead>    <tr>        <th class=\"index_name level0\" >editor</th>        <th class=\"col_heading level0 col0\" >desktop visualeditor</th>        <th class=\"col_heading level0 col1\" >desktop wikitext</th>        <th class=\"col_heading level0 col2\" >desktop wikitext-2017</th>        <th class=\"col_heading level0 col3\" >phone visualeditor</th>        <th class=\"col_heading level0 col4\" >phone wikitext</th>    </tr>    <tr>        <th class=\"index_name level0\" >date</th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6level0_row0\" class=\"row_heading level0 row0\" >2019-06-24 00:00:00</th>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row0_col0\" class=\"data row0 col0\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row0_col1\" class=\"data row0 col1\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row0_col2\" class=\"data row0 col2\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row0_col3\" class=\"data row0 col3\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row0_col4\" class=\"data row0 col4\" >0.0%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6level0_row1\" class=\"row_heading level0 row1\" >2019-06-25 00:00:00</th>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row1_col0\" class=\"data row1 col0\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row1_col1\" class=\"data row1 col1\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row1_col2\" class=\"data row1 col2\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row1_col3\" class=\"data row1 col3\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row1_col4\" class=\"data row1 col4\" >0.0%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6level0_row2\" class=\"row_heading level0 row2\" >2019-06-26 00:00:00</th>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row2_col0\" class=\"data row2 col0\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row2_col1\" class=\"data row2 col1\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row2_col2\" class=\"data row2 col2\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row2_col3\" class=\"data row2 col3\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row2_col4\" class=\"data row2 col4\" >0.0%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6level0_row3\" class=\"row_heading level0 row3\" >2019-06-27 00:00:00</th>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row3_col0\" class=\"data row3 col0\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row3_col1\" class=\"data row3 col1\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row3_col2\" class=\"data row3 col2\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row3_col3\" class=\"data row3 col3\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row3_col4\" class=\"data row3 col4\" >0.0%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6level0_row4\" class=\"row_heading level0 row4\" >2019-06-28 00:00:00</th>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row4_col0\" class=\"data row4 col0\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row4_col1\" class=\"data row4 col1\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row4_col2\" class=\"data row4 col2\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row4_col3\" class=\"data row4 col3\" >1.5%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row4_col4\" class=\"data row4 col4\" >0.0%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6level0_row5\" class=\"row_heading level0 row5\" >2019-06-29 00:00:00</th>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row5_col0\" class=\"data row5 col0\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row5_col1\" class=\"data row5 col1\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row5_col2\" class=\"data row5 col2\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row5_col3\" class=\"data row5 col3\" >1.1%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row5_col4\" class=\"data row5 col4\" >0.9%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6level0_row6\" class=\"row_heading level0 row6\" >2019-06-30 00:00:00</th>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row6_col0\" class=\"data row6 col0\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row6_col1\" class=\"data row6 col1\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row6_col2\" class=\"data row6 col2\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row6_col3\" class=\"data row6 col3\" >0.9%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row6_col4\" class=\"data row6 col4\" >0.6%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6level0_row7\" class=\"row_heading level0 row7\" >2019-07-01 00:00:00</th>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row7_col0\" class=\"data row7 col0\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row7_col1\" class=\"data row7 col1\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row7_col2\" class=\"data row7 col2\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row7_col3\" class=\"data row7 col3\" >1.1%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row7_col4\" class=\"data row7 col4\" >0.8%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6level0_row8\" class=\"row_heading level0 row8\" >2019-07-02 00:00:00</th>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row8_col0\" class=\"data row8 col0\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row8_col1\" class=\"data row8 col1\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row8_col2\" class=\"data row8 col2\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row8_col3\" class=\"data row8 col3\" >1.2%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row8_col4\" class=\"data row8 col4\" >0.8%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6level0_row9\" class=\"row_heading level0 row9\" >2019-07-03 00:00:00</th>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row9_col0\" class=\"data row9 col0\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row9_col1\" class=\"data row9 col1\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row9_col2\" class=\"data row9 col2\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row9_col3\" class=\"data row9 col3\" >1.1%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row9_col4\" class=\"data row9 col4\" >0.7%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6level0_row10\" class=\"row_heading level0 row10\" >2019-07-04 00:00:00</th>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row10_col0\" class=\"data row10 col0\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row10_col1\" class=\"data row10 col1\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row10_col2\" class=\"data row10 col2\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row10_col3\" class=\"data row10 col3\" >4.5%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row10_col4\" class=\"data row10 col4\" >0.8%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6level0_row11\" class=\"row_heading level0 row11\" >2019-07-05 00:00:00</th>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row11_col0\" class=\"data row11 col0\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row11_col1\" class=\"data row11 col1\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row11_col2\" class=\"data row11 col2\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row11_col3\" class=\"data row11 col3\" >4.4%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row11_col4\" class=\"data row11 col4\" >0.7%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6level0_row12\" class=\"row_heading level0 row12\" >2019-07-06 00:00:00</th>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row12_col0\" class=\"data row12 col0\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row12_col1\" class=\"data row12 col1\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row12_col2\" class=\"data row12 col2\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row12_col3\" class=\"data row12 col3\" >4.6%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row12_col4\" class=\"data row12 col4\" >0.7%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6level0_row13\" class=\"row_heading level0 row13\" >2019-07-07 00:00:00</th>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row13_col0\" class=\"data row13 col0\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row13_col1\" class=\"data row13 col1\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row13_col2\" class=\"data row13 col2\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row13_col3\" class=\"data row13 col3\" >4.4%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row13_col4\" class=\"data row13 col4\" >0.7%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6level0_row14\" class=\"row_heading level0 row14\" >2019-07-08 00:00:00</th>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row14_col0\" class=\"data row14 col0\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row14_col1\" class=\"data row14 col1\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row14_col2\" class=\"data row14 col2\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row14_col3\" class=\"data row14 col3\" >4.1%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row14_col4\" class=\"data row14 col4\" >0.7%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6level0_row15\" class=\"row_heading level0 row15\" >2019-07-09 00:00:00</th>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row15_col0\" class=\"data row15 col0\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row15_col1\" class=\"data row15 col1\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row15_col2\" class=\"data row15 col2\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row15_col3\" class=\"data row15 col3\" >4.1%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row15_col4\" class=\"data row15 col4\" >0.7%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6level0_row16\" class=\"row_heading level0 row16\" >2019-07-10 00:00:00</th>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row16_col0\" class=\"data row16 col0\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row16_col1\" class=\"data row16 col1\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row16_col2\" class=\"data row16 col2\" >0.0%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row16_col3\" class=\"data row16 col3\" >4.3%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row16_col4\" class=\"data row16 col4\" >0.8%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6level0_row17\" class=\"row_heading level0 row17\" >2019-07-11 00:00:00</th>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row17_col0\" class=\"data row17 col0\" >0.9%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row17_col1\" class=\"data row17 col1\" >0.2%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row17_col2\" class=\"data row17 col2\" >0.9%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row17_col3\" class=\"data row17 col3\" >4.5%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row17_col4\" class=\"data row17 col4\" >0.7%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6level0_row18\" class=\"row_heading level0 row18\" >2019-07-12 00:00:00</th>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row18_col0\" class=\"data row18 col0\" >6.8%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row18_col1\" class=\"data row18 col1\" >0.9%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row18_col2\" class=\"data row18 col2\" >5.8%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row18_col3\" class=\"data row18 col3\" >4.5%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row18_col4\" class=\"data row18 col4\" >0.8%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6level0_row19\" class=\"row_heading level0 row19\" >2019-07-13 00:00:00</th>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row19_col0\" class=\"data row19 col0\" >6.8%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row19_col1\" class=\"data row19 col1\" >1.1%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row19_col2\" class=\"data row19 col2\" >3.9%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row19_col3\" class=\"data row19 col3\" >4.2%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row19_col4\" class=\"data row19 col4\" >0.7%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6level0_row20\" class=\"row_heading level0 row20\" >2019-07-14 00:00:00</th>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row20_col0\" class=\"data row20 col0\" >6.8%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row20_col1\" class=\"data row20 col1\" >0.8%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row20_col2\" class=\"data row20 col2\" >2.5%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row20_col3\" class=\"data row20 col3\" >4.2%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row20_col4\" class=\"data row20 col4\" >0.7%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6level0_row21\" class=\"row_heading level0 row21\" >2019-07-15 00:00:00</th>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row21_col0\" class=\"data row21 col0\" >7.6%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row21_col1\" class=\"data row21 col1\" >0.9%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row21_col2\" class=\"data row21 col2\" >6.9%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row21_col3\" class=\"data row21 col3\" >4.3%</td>\n",
       "                        <td id=\"T_b335be8e_a714_11e9_89aa_d094661b49a6row21_col4\" class=\"data row21 col4\" >0.7%</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f9293074a58>"
      ]
     },
     "execution_count": 313,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "switches = (\n",
    "    switches_r\n",
    "    .assign(date=lambda df: pd.to_datetime(df[\"date\"]))\n",
    "    .pivot(index=\"date\", columns=\"editor\")\n",
    "    .fillna(0)\n",
    "    .xs(\"sessions_with_switches\", axis=1)\n",
    ")\n",
    "\n",
    "switches.style.format(pct_str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 318,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1008x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = (\n",
    "    switches\n",
    "    .plot(ylim=(0, 0.1))\n",
    ")\n",
    "\n",
    "ax.yaxis.set_major_formatter(pct_fmt)\n",
    "plt.ylabel(\"% of ready-reaching sessions with switches\")\n",
    "plt.xlabel(None);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Impact of loading screen improvements"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "While I'm looking at ready rates and ready times, let me check the impact of [the mobile visual editor's improved loading screen](https://phabricator.wikimedia.org/T210626), which was deployed as part of [Mediawiki 1.33-wmf.21](https://www.mediawiki.org/wiki/MediaWiki_1.33/wmf.21#MobileFrontend) (Tue, 12 Mar–Thu, 14 Mar 2019)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 282,
   "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>10th_percentile</th>\n",
       "      <th>median</th>\n",
       "      <th>90th_percentile</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-03-04</th>\n",
       "      <td>122</td>\n",
       "      <td>1384</td>\n",
       "      <td>5543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-05</th>\n",
       "      <td>139</td>\n",
       "      <td>1433</td>\n",
       "      <td>5010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-06</th>\n",
       "      <td>125</td>\n",
       "      <td>1308</td>\n",
       "      <td>4364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-07</th>\n",
       "      <td>136</td>\n",
       "      <td>1468</td>\n",
       "      <td>5384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-08</th>\n",
       "      <td>127</td>\n",
       "      <td>1444</td>\n",
       "      <td>5320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-09</th>\n",
       "      <td>140</td>\n",
       "      <td>1452</td>\n",
       "      <td>5410</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-10</th>\n",
       "      <td>130</td>\n",
       "      <td>1422</td>\n",
       "      <td>5351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-11</th>\n",
       "      <td>126</td>\n",
       "      <td>1395</td>\n",
       "      <td>5226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-12</th>\n",
       "      <td>130</td>\n",
       "      <td>1387</td>\n",
       "      <td>5236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-13</th>\n",
       "      <td>128</td>\n",
       "      <td>1437</td>\n",
       "      <td>5750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-14</th>\n",
       "      <td>148</td>\n",
       "      <td>1501</td>\n",
       "      <td>5561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-15</th>\n",
       "      <td>180</td>\n",
       "      <td>1620</td>\n",
       "      <td>5932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-16</th>\n",
       "      <td>189</td>\n",
       "      <td>1597</td>\n",
       "      <td>5848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-17</th>\n",
       "      <td>185</td>\n",
       "      <td>1572</td>\n",
       "      <td>5615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-18</th>\n",
       "      <td>164</td>\n",
       "      <td>1567</td>\n",
       "      <td>5537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-19</th>\n",
       "      <td>173</td>\n",
       "      <td>1599</td>\n",
       "      <td>5768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-20</th>\n",
       "      <td>181</td>\n",
       "      <td>1544</td>\n",
       "      <td>5741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-21</th>\n",
       "      <td>172</td>\n",
       "      <td>1585</td>\n",
       "      <td>5785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-22</th>\n",
       "      <td>197</td>\n",
       "      <td>1578</td>\n",
       "      <td>6100</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            10th_percentile  median  90th_percentile\n",
       "date                                                \n",
       "2019-03-04              122    1384             5543\n",
       "2019-03-05              139    1433             5010\n",
       "2019-03-06              125    1308             4364\n",
       "2019-03-07              136    1468             5384\n",
       "2019-03-08              127    1444             5320\n",
       "2019-03-09              140    1452             5410\n",
       "2019-03-10              130    1422             5351\n",
       "2019-03-11              126    1395             5226\n",
       "2019-03-12              130    1387             5236\n",
       "2019-03-13              128    1437             5750\n",
       "2019-03-14              148    1501             5561\n",
       "2019-03-15              180    1620             5932\n",
       "2019-03-16              189    1597             5848\n",
       "2019-03-17              185    1572             5615\n",
       "2019-03-18              164    1567             5537\n",
       "2019-03-19              173    1599             5768\n",
       "2019-03-20              181    1544             5741\n",
       "2019-03-21              172    1585             5785\n",
       "2019-03-22              197    1578             6100"
      ]
     },
     "execution_count": 282,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hist_ready_times[\"2019-03-04\":\"2019-03-22\"].applymap(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 304,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Before-to-after change\n",
    "before = hist_ready_times[\"2019-03-04\": \"2019-03-11\"].mean()\n",
    "after = hist_ready_times[\"2019-03-15\": \"2019-03-22\"].mean()\n",
    "timing_change = (\n",
    "    ((after / before ) - 1)\n",
    "    .apply(pct_str)\n",
    "    .to_frame()\n",
    "    .rename({0: \"change after deploy\"}, axis=1)\n",
    "    .rename(lambda x: x.replace(\"_\", \" \"))\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 305,
   "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>change after deploy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>10th percentile</th>\n",
       "      <td>37.7%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>median</th>\n",
       "      <td>12.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90th percentile</th>\n",
       "      <td>11.3%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                change after deploy\n",
       "10th percentile               37.7%\n",
       "median                        12.0%\n",
       "90th percentile               11.3%"
      ]
     },
     "execution_count": 305,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "timing_change"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 307,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "| index | change after deploy\n",
      "| ----- | ----- \n",
      "| 10th percentile | 37.7%\n",
      "| median | 12.0%\n",
      "| 90th percentile | 11.3%\n",
      "\n"
     ]
    }
   ],
   "source": [
    "timing_change.reset_index().pipe(df_to_remarkup)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 297,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1008x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = hist_ready_times[\"2019-03-04\": \"2019-03-22\"].plot(ylim=0)\n",
    "ax.yaxis.set_major_formatter(FuncFormatter(\n",
    "    lambda x, pos: str(int(x/1000)) + \" s\"\n",
    "))   \n",
    "plt.axvline(\"2019-03-12\", color=\"red\", linewidth=1.25)\n",
    "plt.text(\"2019-03-05\", 3500, \"Load screen improvements deployed\", size=16, color=\"red\")\n",
    "plt.ylabel(\"time until interface is ready for user input\")\n",
    "plt.xlabel(None)\n",
    "plt.title(\"Ready timings for the mobile visual editor\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 252,
   "metadata": {},
   "outputs": [],
   "source": [
    "load_screen_ready_rates = global_ready_rate[\"visualeditor\"][\"2019-03-04\": \"2019-03-22\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 298,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1008x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = load_screen_ready_rates.plot(ylim=(0.86, 1))\n",
    "ax.yaxis.set_major_formatter(pct_fmt)\n",
    "plt.axvline(\"2019-03-12\", color=\"red\", linewidth=1.25)\n",
    "plt.text(\"2019-03-05\", 0.95, \"Load screen improvements deployed\", size=16, color=\"red\")\n",
    "plt.xlabel(None)\n",
    "plt.ylabel(\"% of sessions reaching ready\")\n",
    "plt.title(\"Mobile visual editor ready rate\");"
   ]
  }
 ],
 "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": "3.5.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}