{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from collections import OrderedDict\n",
    "from datetime import timedelta\n",
    "from functools import partial\n",
    "import re\n",
    "\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.ticker import FuncFormatter, FixedLocator\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import requests\n",
    "from wmfdata import hive, mariadb, charting\n",
    "from wmfdata.utils import pct_str\n",
    "\n",
    "charting.set_mpl_style()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "null_prop = lambda s: len(s[s.isnull()]) / len(s)\n",
    "pos_prop = lambda s: len(s[s > 0]) / len(s)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data loading"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Mobile edit proportion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-19-fae70611ab4b>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     18\u001b[0m     \u001b[0msnapshot\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"2018-09\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     19\u001b[0m \u001b[0mgroup\u001b[0m \u001b[0mby\u001b[0m \u001b[0mcoalesce\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mevent_user_text\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mevent_user_text_historical\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mevent_user_is_anonymous\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 20\u001b[0;31m \"\"\")\n\u001b[0m",
      "\u001b[0;32m/srv/home/neilpquinn-wmf/pkg/wmfdata/wmfdata/hive.py\u001b[0m in \u001b[0;36mrun\u001b[0;34m(cmds, fmt)\u001b[0m\n\u001b[1;32m     27\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     28\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mcmd\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mcmds\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 29\u001b[0;31m             \u001b[0mhive_cursor\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcmd\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     30\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mfmt\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"pandas\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     31\u001b[0m                 \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/venv/lib/python3.5/site-packages/impala/hiveserver2.py\u001b[0m in \u001b[0;36mexecute\u001b[0;34m(self, operation, parameters, configuration)\u001b[0m\n\u001b[1;32m    302\u001b[0m                            configuration=configuration)\n\u001b[1;32m    303\u001b[0m         \u001b[0mlog\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdebug\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Waiting for query to finish'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 304\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_wait_to_finish\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# make execute synchronous\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    305\u001b[0m         \u001b[0mlog\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdebug\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Query finished'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    306\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/venv/lib/python3.5/site-packages/impala/hiveserver2.py\u001b[0m in \u001b[0;36m_wait_to_finish\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    371\u001b[0m         \u001b[0;32mwhile\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    372\u001b[0m             \u001b[0mreq\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTGetOperationStatusReq\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0moperationHandle\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_last_operation\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhandle\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 373\u001b[0;31m             \u001b[0mresp\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_last_operation\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_rpc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'GetOperationStatus'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreq\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    374\u001b[0m             \u001b[0moperation_state\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTOperationState\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_VALUES_TO_NAMES\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mresp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moperationState\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    375\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/venv/lib/python3.5/site-packages/impala/hiveserver2.py\u001b[0m in \u001b[0;36m_rpc\u001b[0;34m(self, func_name, request)\u001b[0m\n\u001b[1;32m    921\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_rpc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfunc_name\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrequest\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    922\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_log_request\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfunc_name\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrequest\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 923\u001b[0;31m         \u001b[0mresponse\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_execute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfunc_name\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrequest\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    924\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_log_response\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfunc_name\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    925\u001b[0m         \u001b[0merr_if_rpc_not_ok\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresponse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/venv/lib/python3.5/site-packages/impala/hiveserver2.py\u001b[0m in \u001b[0;36m_execute\u001b[0;34m(self, func_name, request)\u001b[0m\n\u001b[1;32m    938\u001b[0m                 \u001b[0mlog\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdebug\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Transport opened'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    939\u001b[0m                 \u001b[0mfunc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclient\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfunc_name\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 940\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrequest\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    941\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0msocket\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0merror\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    942\u001b[0m                 log.exception('Failed to open transport (tries_left=%s)',\n",
      "\u001b[0;32m~/venv/lib/python3.5/site-packages/thriftpy/thrift.py\u001b[0m in \u001b[0;36m_req\u001b[0;34m(self, _api, *args, **kwargs)\u001b[0m\n\u001b[1;32m    196\u001b[0m         \u001b[0;31m# wait result only if non-oneway\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    197\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresult_cls\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"oneway\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 198\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_recv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0m_api\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    199\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    200\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_send\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0m_api\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/venv/lib/python3.5/site-packages/thriftpy/thrift.py\u001b[0m in \u001b[0;36m_recv\u001b[0;34m(self, _api)\u001b[0m\n\u001b[1;32m    208\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    209\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_recv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0m_api\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 210\u001b[0;31m         \u001b[0mfname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrseqid\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_iprot\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_message_begin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    211\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mmtype\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mTMessageType\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mEXCEPTION\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    212\u001b[0m             \u001b[0mx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTApplicationException\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/venv/lib/python3.5/site-packages/thriftpy/protocol/binary.py\u001b[0m in \u001b[0;36mread_message_begin\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    370\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mread_message_begin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    371\u001b[0m         api, ttype, seqid = read_message_begin(\n\u001b[0;32m--> 372\u001b[0;31m             self.trans, strict=self.strict_read)\n\u001b[0m\u001b[1;32m    373\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mapi\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mttype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mseqid\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    374\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/venv/lib/python3.5/site-packages/thriftpy/protocol/binary.py\u001b[0m in \u001b[0;36mread_message_begin\u001b[0;34m(inbuf, strict)\u001b[0m\n\u001b[1;32m    162\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    163\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mread_message_begin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minbuf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstrict\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 164\u001b[0;31m     \u001b[0msz\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0munpack_i32\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minbuf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m4\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    165\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0msz\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    166\u001b[0m         \u001b[0mversion\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msz\u001b[0m \u001b[0;34m&\u001b[0m \u001b[0mVERSION_MASK\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/venv/lib/python3.5/site-packages/thrift_sasl/__init__.py\u001b[0m in \u001b[0;36mread\u001b[0;34m(self, sz)\u001b[0m\n\u001b[1;32m    157\u001b[0m       \u001b[0;32mreturn\u001b[0m \u001b[0mret\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    158\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 159\u001b[0;31m     \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_read_frame\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    160\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mret\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__rbuf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msz\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mret\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    161\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/venv/lib/python3.5/site-packages/thrift_sasl/__init__.py\u001b[0m in \u001b[0;36m_read_frame\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    161\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    162\u001b[0m   \u001b[0;32mdef\u001b[0m \u001b[0m_read_frame\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 163\u001b[0;31m     \u001b[0mheader\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mread_all_compat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_trans\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m4\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    164\u001b[0m     \u001b[0;34m(\u001b[0m\u001b[0mlength\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mstruct\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munpack\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\">I\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheader\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    165\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mencode\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/venv/lib/python3.5/site-packages/thrift_sasl/six.py\u001b[0m in \u001b[0;36m<lambda>\u001b[0;34m(trans, sz)\u001b[0m\n\u001b[1;32m     52\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mis_open\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     53\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 54\u001b[0;31m   \u001b[0mread_all_compat\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mlambda\u001b[0m \u001b[0mtrans\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msz\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mreadall\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtrans\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msz\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m~/venv/lib/python3.5/site-packages/thriftpy/transport/__init__.py\u001b[0m in \u001b[0;36mreadall\u001b[0;34m(read_fn, sz)\u001b[0m\n\u001b[1;32m     12\u001b[0m     \u001b[0mhave\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     13\u001b[0m     \u001b[0;32mwhile\u001b[0m \u001b[0mhave\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0msz\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 14\u001b[0;31m         \u001b[0mchunk\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mread_fn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msz\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mhave\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     15\u001b[0m         \u001b[0mhave\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mchunk\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     16\u001b[0m         \u001b[0mbuff\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0mchunk\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/venv/lib/python3.5/site-packages/thriftpy/transport/socket.py\u001b[0m in \u001b[0;36mread\u001b[0;34m(self, sz)\u001b[0m\n\u001b[1;32m    106\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msz\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    107\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 108\u001b[0;31m             \u001b[0mbuff\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msock\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrecv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msz\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    109\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0msocket\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0merror\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    110\u001b[0m             if (e.args[0] == errno.ECONNRESET and\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "editors_r = hive.run(\"\"\"\n",
    "select\n",
    "    coalesce(event_user_text, event_user_text_historical) as user_name,\n",
    "    not event_user_is_anonymous as registered,\n",
    "    count(*) as yearly_edits,\n",
    "    sum(cast(\n",
    "        coalesce(mve.editor, \"desktop wikitext editor\") in (\"mobile visual editor\", \"mobile wikitext editor\")\n",
    "    as int)) / count(*) as mobile_edit_proportion\n",
    "from wmf.mediawiki_history mh\n",
    "left join neilpquinn.mob_or_ve_edits mve\n",
    "on \n",
    "    mve.wiki = mh.wiki_db and\n",
    "    mve.rev_id = mh.revision_id\n",
    "where\n",
    "    mh.event_timestamp >= \"2017-10\" and\n",
    "    event_entity = \"revision\" and\n",
    "    event_type = \"create\" and\n",
    "    snapshot = \"2018-09\"\n",
    "group by coalesce(event_user_text, event_user_text_historical), event_user_is_anonymous\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 302,
   "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_name</th>\n",
       "      <th>registered</th>\n",
       "      <th>yearly_edits</th>\n",
       "      <th>mobile_edit_proportion</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>! Bikkit !</td>\n",
       "      <td>True</td>\n",
       "      <td>583</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>!Alla17</td>\n",
       "      <td>True</td>\n",
       "      <td>45</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>!Ann07</td>\n",
       "      <td>True</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>!Maciek!Wawa</td>\n",
       "      <td>True</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>!Puce456</td>\n",
       "      <td>True</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      user_name  registered  yearly_edits  mobile_edit_proportion\n",
       "0    ! Bikkit !        True           583                     0.0\n",
       "1       !Alla17        True            45                     0.0\n",
       "2        !Ann07        True             1                     0.0\n",
       "3  !Maciek!Wawa        True             2                     0.0\n",
       "4      !Puce456        True             1                     1.0"
      ]
     },
     "execution_count": 302,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "editors = editors_r.copy()\n",
    "editors.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 303,
   "metadata": {},
   "outputs": [],
   "source": [
    "def bin_platform(x):\n",
    "    if x == 0:\n",
    "        return \"desktop only\"\n",
    "    elif x == 1:\n",
    "        return \"mobile only\"\n",
    "    else:\n",
    "        return \"mixed\"\n",
    "    \n",
    "editors[\"platform\"] = pd.Categorical(editors[\"mobile_edit_proportion\"].apply(bin_platform))\n",
    "\n",
    "editors[\"activity_level\"] = pd.cut(\n",
    "    editors[\"yearly_edits\"], \n",
    "    bins=ec_bins[1:], \n",
    "    labels=ec_labels[1:],\n",
    "    right=False\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 304,
   "metadata": {},
   "outputs": [],
   "source": [
    "reg_editors = editors.query(\"registered == True\")\n",
    "ip_editors = editors.query(\"registered == False\")"
   ]
  },
  {
   "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>platform</th>\n",
       "      <th>desktop only</th>\n",
       "      <th>mixed</th>\n",
       "      <th>mobile only</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>user_name</th>\n",
       "      <td>74.9%</td>\n",
       "      <td>6.2%</td>\n",
       "      <td>18.9%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "platform  desktop only mixed mobile only\n",
       "user_name        74.9%  6.2%       18.9%"
      ]
     },
     "execution_count": 305,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "platform_prop = reg_editors.groupby(\"platform\")[\"user_name\"].agg(len) / len(reg_editors)\n",
    "pd.DataFrame(platform_prop).applymap(pct_str).T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 306,
   "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>platform</th>\n",
       "      <th>desktop only</th>\n",
       "      <th>mixed</th>\n",
       "      <th>mobile only</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>activity_level</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1-9 edits</th>\n",
       "      <td>74.5%</td>\n",
       "      <td>3.4%</td>\n",
       "      <td>22.1%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10-99 edits</th>\n",
       "      <td>78.5%</td>\n",
       "      <td>15.5%</td>\n",
       "      <td>6.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100-999 edits</th>\n",
       "      <td>69.6%</td>\n",
       "      <td>28.6%</td>\n",
       "      <td>1.9%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000+ edits</th>\n",
       "      <td>66.7%</td>\n",
       "      <td>33.1%</td>\n",
       "      <td>0.1%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "platform       desktop only  mixed mobile only\n",
       "activity_level                                \n",
       "1-9 edits             74.5%   3.4%       22.1%\n",
       "10-99 edits           78.5%  15.5%        6.0%\n",
       "100-999 edits         69.6%  28.6%        1.9%\n",
       "1000+ edits           66.7%  33.1%        0.1%"
      ]
     },
     "execution_count": 306,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "by_act = reg_editors.groupby([\"activity_level\", \"platform\"])[\"user_name\"].agg(len).unstack()\n",
    "by_act.apply(lambda row: row / row.sum(), axis=1).applymap(pct_str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 323,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.hist(reg_editors[\"mobile_edit_proportion\"])\n",
    "ax.margins(y=0.1, tight=True)\n",
    "ax.yaxis.set_major_formatter(charting.comma_fmt)\n",
    "ax.xaxis.set_major_formatter(charting.pct_fmt)\n",
    "ax.set_ylabel(\"editors\")\n",
    "ax.set_xlabel(\"mobile edit proportion\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 361,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.hist(reg_editors.query(\"0 < mobile_edit_proportion < 1.0\")[\"mobile_edit_proportion\"])\n",
    "ax.margins(y=0.1, tight=True)\n",
    "ax.yaxis.set_major_formatter(charting.comma_fmt)\n",
    "ax.xaxis.set_major_formatter(charting.pct_fmt)\n",
    "ax.set_ylabel(\"editors\")\n",
    "ax.set_xlabel(\"mobile edit proportion\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Interface retention"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# For all the people who edited Oct 2017–March 2018, find their first edit with each interface \n",
    "# and join it to all their edits from Oct 2017-Sep 2018 with the same interface\n",
    "\n",
    "# WARNING: Initial edit count is unreliable because the database has a separate edit count for each wiki\n",
    "edits_r = hive.run(\"\"\"\n",
    "with first_edits as (\n",
    "    select\n",
    "        event_user_text,\n",
    "        coalesce(editor, \"desktop wikitext editor\") as editor,\n",
    "        min(event_timestamp) as first_edit_time,\n",
    "        min(event_user_revision_count) as initial_edit_count\n",
    "    from wmf.mediawiki_history mh\n",
    "    left join neilpquinn.mob_or_ve_edits mve\n",
    "    on \n",
    "        mve.wiki = mh.wiki_db and\n",
    "        mve.rev_id = mh.revision_id\n",
    "    where\n",
    "        event_timestamp >= \"2017-10\" and\n",
    "        event_timestamp < \"2018-04\" and\n",
    "        not event_user_is_anonymous and\n",
    "        event_entity = \"revision\" and\n",
    "        event_type = \"create\" and\n",
    "        mh.snapshot = \"2018-09\"\n",
    "    group by event_user_text, editor\n",
    ")\n",
    "select\n",
    "user_name,\n",
    "interface,\n",
    "week_number,\n",
    "min(initial_edit_count) as initial_edit_count,\n",
    "count(*) as edits\n",
    "from (\n",
    "    select\n",
    "        fe.event_user_text as user_name,\n",
    "        fe.editor as interface,\n",
    "        fe.initial_edit_count as initial_edit_count,\n",
    "        event_timestamp,\n",
    "        (fe.first_edit_time = mh.event_timestamp) as first_edit,\n",
    "        -- If datediff is 0-7, week 1; if 8-14, week 2; etc.\n",
    "        if(\n",
    "            ceil(datediff(event_timestamp, first_edit_time) / 7) != 0,\n",
    "            ceil(datediff(event_timestamp, first_edit_time) / 7),\n",
    "            1\n",
    "        ) as week_number\n",
    "    from first_edits fe\n",
    "    left join wmf.mediawiki_history mh on\n",
    "        fe.event_user_text = mh.event_user_text and\n",
    "        mh.snapshot = \"2018-09\"\n",
    "    left join neilpquinn.mob_or_ve_edits mve on \n",
    "        mve.wiki = mh.wiki_db and\n",
    "        mve.rev_id = mh.revision_id\n",
    "    where\n",
    "        fe.editor = coalesce(mve.editor, \"desktop wikitext editor\") and\n",
    "        -- Limit to events with 182 days (26 full weeks) after starting to avoid censoring\n",
    "        datediff(event_timestamp, first_edit_time) <= 182 and\n",
    "        event_timestamp >= \"2017-10\" and\n",
    "        event_timestamp < \"2018-10\" and\n",
    "        event_entity = \"revision\" and\n",
    "        event_type = \"create\"\n",
    ") edits\n",
    "group by user_name, interface, week_number\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "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_name</th>\n",
       "      <th>interface</th>\n",
       "      <th>week_number</th>\n",
       "      <th>edits</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>! Bikkit !</td>\n",
       "      <td>desktop wikitext editor</td>\n",
       "      <td>14</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>! Bikkit !</td>\n",
       "      <td>desktop wikitext editor</td>\n",
       "      <td>26</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>!!Ethereal!!</td>\n",
       "      <td>desktop wikitext editor</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>!!Priyanshu Patel!!</td>\n",
       "      <td>desktop wikitext editor</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>!0Clarke</td>\n",
       "      <td>desktop wikitext editor</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             user_name                interface  week_number  edits\n",
       "0           ! Bikkit !  desktop wikitext editor           14     24\n",
       "1           ! Bikkit !  desktop wikitext editor           26      6\n",
       "2         !!Ethereal!!  desktop wikitext editor            2      1\n",
       "3  !!Priyanshu Patel!!  desktop wikitext editor            1      2\n",
       "4             !0Clarke  desktop wikitext editor            1      4"
      ]
     },
     "execution_count": 226,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weekly_edits = edits_r.drop([\"initial_edit_count\"], axis=1)\n",
    "weekly_edits.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "        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></th>\n",
       "      <th>week 1</th>\n",
       "      <th>week 2</th>\n",
       "      <th>week 3</th>\n",
       "      <th>week 4</th>\n",
       "      <th>week 5</th>\n",
       "      <th>week 6</th>\n",
       "      <th>week 7</th>\n",
       "      <th>week 8</th>\n",
       "      <th>week 9</th>\n",
       "      <th>week 10</th>\n",
       "      <th>...</th>\n",
       "      <th>week 17</th>\n",
       "      <th>week 18</th>\n",
       "      <th>week 19</th>\n",
       "      <th>week 20</th>\n",
       "      <th>week 21</th>\n",
       "      <th>week 22</th>\n",
       "      <th>week 23</th>\n",
       "      <th>week 24</th>\n",
       "      <th>week 25</th>\n",
       "      <th>week 26</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user_name</th>\n",
       "      <th>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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>! Bikkit !</th>\n",
       "      <th>desktop wikitext editor</th>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "      <td>31</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>46</td>\n",
       "      <td>47</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>!! !!ПОМОГИТЕ СЕСТРЕ НА ОПЕРАЦИЮ!! !!</th>\n",
       "      <th>desktop wikitext editor</th>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>!!7597JOBV++!</th>\n",
       "      <th>desktop wikitext editor</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>!!Ethereal!!</th>\n",
       "      <th>desktop wikitext editor</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>!!Priyanshu Patel!!</th>\n",
       "      <th>desktop wikitext editor</th>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                               week 1  week 2  \\\n",
       "user_name                             interface                                 \n",
       "! Bikkit !                            desktop wikitext editor       4       0   \n",
       "!! !!ПОМОГИТЕ СЕСТРЕ НА ОПЕРАЦИЮ!! !! desktop wikitext editor      11       0   \n",
       "!!7597JOBV++!                         desktop wikitext editor       5       0   \n",
       "!!Ethereal!!                          desktop wikitext editor       1       1   \n",
       "!!Priyanshu Patel!!                   desktop wikitext editor       2       0   \n",
       "\n",
       "                                                               week 3  week 4  \\\n",
       "user_name                             interface                                 \n",
       "! Bikkit !                            desktop wikitext editor      15       0   \n",
       "!! !!ПОМОГИТЕ СЕСТРЕ НА ОПЕРАЦИЮ!! !! desktop wikitext editor       0       0   \n",
       "!!7597JOBV++!                         desktop wikitext editor       0       0   \n",
       "!!Ethereal!!                          desktop wikitext editor       0       0   \n",
       "!!Priyanshu Patel!!                   desktop wikitext editor       0       0   \n",
       "\n",
       "                                                               week 5  week 6  \\\n",
       "user_name                             interface                                 \n",
       "! Bikkit !                            desktop wikitext editor       2      14   \n",
       "!! !!ПОМОГИТЕ СЕСТРЕ НА ОПЕРАЦИЮ!! !! desktop wikitext editor       0       0   \n",
       "!!7597JOBV++!                         desktop wikitext editor       0       0   \n",
       "!!Ethereal!!                          desktop wikitext editor       0       0   \n",
       "!!Priyanshu Patel!!                   desktop wikitext editor       0       0   \n",
       "\n",
       "                                                               week 7  week 8  \\\n",
       "user_name                             interface                                 \n",
       "! Bikkit !                            desktop wikitext editor      31       6   \n",
       "!! !!ПОМОГИТЕ СЕСТРЕ НА ОПЕРАЦИЮ!! !! desktop wikitext editor       0       0   \n",
       "!!7597JOBV++!                         desktop wikitext editor       0       0   \n",
       "!!Ethereal!!                          desktop wikitext editor       0       0   \n",
       "!!Priyanshu Patel!!                   desktop wikitext editor       0       0   \n",
       "\n",
       "                                                               week 9  \\\n",
       "user_name                             interface                         \n",
       "! Bikkit !                            desktop wikitext editor       0   \n",
       "!! !!ПОМОГИТЕ СЕСТРЕ НА ОПЕРАЦИЮ!! !! desktop wikitext editor       0   \n",
       "!!7597JOBV++!                         desktop wikitext editor       0   \n",
       "!!Ethereal!!                          desktop wikitext editor       0   \n",
       "!!Priyanshu Patel!!                   desktop wikitext editor       0   \n",
       "\n",
       "                                                               week 10  \\\n",
       "user_name                             interface                          \n",
       "! Bikkit !                            desktop wikitext editor        0   \n",
       "!! !!ПОМОГИТЕ СЕСТРЕ НА ОПЕРАЦИЮ!! !! desktop wikitext editor        0   \n",
       "!!7597JOBV++!                         desktop wikitext editor        0   \n",
       "!!Ethereal!!                          desktop wikitext editor        0   \n",
       "!!Priyanshu Patel!!                   desktop wikitext editor        0   \n",
       "\n",
       "                                                                ...     \\\n",
       "user_name                             interface                 ...      \n",
       "! Bikkit !                            desktop wikitext editor   ...      \n",
       "!! !!ПОМОГИТЕ СЕСТРЕ НА ОПЕРАЦИЮ!! !! desktop wikitext editor   ...      \n",
       "!!7597JOBV++!                         desktop wikitext editor   ...      \n",
       "!!Ethereal!!                          desktop wikitext editor   ...      \n",
       "!!Priyanshu Patel!!                   desktop wikitext editor   ...      \n",
       "\n",
       "                                                               week 17  \\\n",
       "user_name                             interface                          \n",
       "! Bikkit !                            desktop wikitext editor        9   \n",
       "!! !!ПОМОГИТЕ СЕСТРЕ НА ОПЕРАЦИЮ!! !! desktop wikitext editor        0   \n",
       "!!7597JOBV++!                         desktop wikitext editor        0   \n",
       "!!Ethereal!!                          desktop wikitext editor        0   \n",
       "!!Priyanshu Patel!!                   desktop wikitext editor        0   \n",
       "\n",
       "                                                               week 18  \\\n",
       "user_name                             interface                          \n",
       "! Bikkit !                            desktop wikitext editor        0   \n",
       "!! !!ПОМОГИТЕ СЕСТРЕ НА ОПЕРАЦИЮ!! !! desktop wikitext editor        0   \n",
       "!!7597JOBV++!                         desktop wikitext editor        0   \n",
       "!!Ethereal!!                          desktop wikitext editor        0   \n",
       "!!Priyanshu Patel!!                   desktop wikitext editor        0   \n",
       "\n",
       "                                                               week 19  \\\n",
       "user_name                             interface                          \n",
       "! Bikkit !                            desktop wikitext editor        0   \n",
       "!! !!ПОМОГИТЕ СЕСТРЕ НА ОПЕРАЦИЮ!! !! desktop wikitext editor        0   \n",
       "!!7597JOBV++!                         desktop wikitext editor        0   \n",
       "!!Ethereal!!                          desktop wikitext editor        0   \n",
       "!!Priyanshu Patel!!                   desktop wikitext editor        0   \n",
       "\n",
       "                                                               week 20  \\\n",
       "user_name                             interface                          \n",
       "! Bikkit !                            desktop wikitext editor        0   \n",
       "!! !!ПОМОГИТЕ СЕСТРЕ НА ОПЕРАЦИЮ!! !! desktop wikitext editor        0   \n",
       "!!7597JOBV++!                         desktop wikitext editor        0   \n",
       "!!Ethereal!!                          desktop wikitext editor        0   \n",
       "!!Priyanshu Patel!!                   desktop wikitext editor        0   \n",
       "\n",
       "                                                               week 21  \\\n",
       "user_name                             interface                          \n",
       "! Bikkit !                            desktop wikitext editor        0   \n",
       "!! !!ПОМОГИТЕ СЕСТРЕ НА ОПЕРАЦИЮ!! !! desktop wikitext editor        0   \n",
       "!!7597JOBV++!                         desktop wikitext editor        0   \n",
       "!!Ethereal!!                          desktop wikitext editor        0   \n",
       "!!Priyanshu Patel!!                   desktop wikitext editor        0   \n",
       "\n",
       "                                                               week 22  \\\n",
       "user_name                             interface                          \n",
       "! Bikkit !                            desktop wikitext editor       46   \n",
       "!! !!ПОМОГИТЕ СЕСТРЕ НА ОПЕРАЦИЮ!! !! desktop wikitext editor        0   \n",
       "!!7597JOBV++!                         desktop wikitext editor        0   \n",
       "!!Ethereal!!                          desktop wikitext editor        0   \n",
       "!!Priyanshu Patel!!                   desktop wikitext editor        0   \n",
       "\n",
       "                                                               week 23  \\\n",
       "user_name                             interface                          \n",
       "! Bikkit !                            desktop wikitext editor       47   \n",
       "!! !!ПОМОГИТЕ СЕСТРЕ НА ОПЕРАЦИЮ!! !! desktop wikitext editor        0   \n",
       "!!7597JOBV++!                         desktop wikitext editor        0   \n",
       "!!Ethereal!!                          desktop wikitext editor        0   \n",
       "!!Priyanshu Patel!!                   desktop wikitext editor        0   \n",
       "\n",
       "                                                               week 24  \\\n",
       "user_name                             interface                          \n",
       "! Bikkit !                            desktop wikitext editor       16   \n",
       "!! !!ПОМОГИТЕ СЕСТРЕ НА ОПЕРАЦИЮ!! !! desktop wikitext editor        0   \n",
       "!!7597JOBV++!                         desktop wikitext editor        0   \n",
       "!!Ethereal!!                          desktop wikitext editor        0   \n",
       "!!Priyanshu Patel!!                   desktop wikitext editor        0   \n",
       "\n",
       "                                                               week 25  \\\n",
       "user_name                             interface                          \n",
       "! Bikkit !                            desktop wikitext editor        0   \n",
       "!! !!ПОМОГИТЕ СЕСТРЕ НА ОПЕРАЦИЮ!! !! desktop wikitext editor        0   \n",
       "!!7597JOBV++!                         desktop wikitext editor        0   \n",
       "!!Ethereal!!                          desktop wikitext editor        0   \n",
       "!!Priyanshu Patel!!                   desktop wikitext editor        0   \n",
       "\n",
       "                                                               week 26  \n",
       "user_name                             interface                         \n",
       "! Bikkit !                            desktop wikitext editor        6  \n",
       "!! !!ПОМОГИТЕ СЕСТРЕ НА ОПЕРАЦИЮ!! !! desktop wikitext editor        0  \n",
       "!!7597JOBV++!                         desktop wikitext editor        0  \n",
       "!!Ethereal!!                          desktop wikitext editor        0  \n",
       "!!Priyanshu Patel!!                   desktop wikitext editor        0  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 227,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weekly_edits = weekly_edits.set_index([\"user_name\", \"interface\", \"week_number\"]).unstack()\n",
    "weekly_edits = weekly_edits.fillna(0).apply(np.uint32)\n",
    "weekly_edits.columns = weekly_edits.columns.droplevel(0)\n",
    "weekly_edits.columns.name = None\n",
    "weekly_edits = weekly_edits.rename(columns = lambda x: \"week {!s}\".format(x))\n",
    "weekly_edits.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 258,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>week 1</th>\n",
       "      <th>week 2</th>\n",
       "      <th>week 3</th>\n",
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       "      <th>week 8</th>\n",
       "      <th>week 9</th>\n",
       "      <th>week 10</th>\n",
       "      <th>...</th>\n",
       "      <th>week 17</th>\n",
       "      <th>week 18</th>\n",
       "      <th>week 19</th>\n",
       "      <th>week 20</th>\n",
       "      <th>week 21</th>\n",
       "      <th>week 22</th>\n",
       "      <th>week 23</th>\n",
       "      <th>week 24</th>\n",
       "      <th>week 25</th>\n",
       "      <th>week 26</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>desktop visual editor</th>\n",
       "      <td>100.0%</td>\n",
       "      <td>8.6%</td>\n",
       "      <td>7.0%</td>\n",
       "      <td>6.1%</td>\n",
       "      <td>5.5%</td>\n",
       "      <td>5.1%</td>\n",
       "      <td>4.7%</td>\n",
       "      <td>4.4%</td>\n",
       "      <td>4.1%</td>\n",
       "      <td>3.9%</td>\n",
       "      <td>...</td>\n",
       "      <td>3.1%</td>\n",
       "      <td>3.0%</td>\n",
       "      <td>3.0%</td>\n",
       "      <td>2.9%</td>\n",
       "      <td>2.8%</td>\n",
       "      <td>2.8%</td>\n",
       "      <td>2.7%</td>\n",
       "      <td>2.7%</td>\n",
       "      <td>2.7%</td>\n",
       "      <td>2.7%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>desktop wikitext editor</th>\n",
       "      <td>100.0%</td>\n",
       "      <td>12.4%</td>\n",
       "      <td>10.6%</td>\n",
       "      <td>9.7%</td>\n",
       "      <td>9.2%</td>\n",
       "      <td>8.7%</td>\n",
       "      <td>8.3%</td>\n",
       "      <td>8.0%</td>\n",
       "      <td>7.8%</td>\n",
       "      <td>7.5%</td>\n",
       "      <td>...</td>\n",
       "      <td>6.8%</td>\n",
       "      <td>6.8%</td>\n",
       "      <td>6.7%</td>\n",
       "      <td>6.6%</td>\n",
       "      <td>6.6%</td>\n",
       "      <td>6.5%</td>\n",
       "      <td>6.5%</td>\n",
       "      <td>6.4%</td>\n",
       "      <td>6.3%</td>\n",
       "      <td>6.3%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mobile visual editor</th>\n",
       "      <td>100.0%</td>\n",
       "      <td>4.4%</td>\n",
       "      <td>3.4%</td>\n",
       "      <td>3.0%</td>\n",
       "      <td>2.6%</td>\n",
       "      <td>2.3%</td>\n",
       "      <td>2.1%</td>\n",
       "      <td>2.0%</td>\n",
       "      <td>1.9%</td>\n",
       "      <td>1.8%</td>\n",
       "      <td>...</td>\n",
       "      <td>1.3%</td>\n",
       "      <td>1.3%</td>\n",
       "      <td>1.3%</td>\n",
       "      <td>1.1%</td>\n",
       "      <td>1.0%</td>\n",
       "      <td>1.1%</td>\n",
       "      <td>1.1%</td>\n",
       "      <td>1.1%</td>\n",
       "      <td>1.1%</td>\n",
       "      <td>1.1%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mobile wikitext editor</th>\n",
       "      <td>100.0%</td>\n",
       "      <td>5.9%</td>\n",
       "      <td>4.9%</td>\n",
       "      <td>4.4%</td>\n",
       "      <td>4.1%</td>\n",
       "      <td>3.8%</td>\n",
       "      <td>3.6%</td>\n",
       "      <td>3.5%</td>\n",
       "      <td>3.4%</td>\n",
       "      <td>3.3%</td>\n",
       "      <td>...</td>\n",
       "      <td>2.8%</td>\n",
       "      <td>2.7%</td>\n",
       "      <td>2.7%</td>\n",
       "      <td>2.7%</td>\n",
       "      <td>2.6%</td>\n",
       "      <td>2.6%</td>\n",
       "      <td>2.6%</td>\n",
       "      <td>2.5%</td>\n",
       "      <td>2.5%</td>\n",
       "      <td>2.4%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                         week 1 week 2 week 3 week 4 week 5 week 6 week 7  \\\n",
       "interface                                                                   \n",
       "desktop visual editor    100.0%   8.6%   7.0%   6.1%   5.5%   5.1%   4.7%   \n",
       "desktop wikitext editor  100.0%  12.4%  10.6%   9.7%   9.2%   8.7%   8.3%   \n",
       "mobile visual editor     100.0%   4.4%   3.4%   3.0%   2.6%   2.3%   2.1%   \n",
       "mobile wikitext editor   100.0%   5.9%   4.9%   4.4%   4.1%   3.8%   3.6%   \n",
       "\n",
       "                        week 8 week 9 week 10   ...   week 17 week 18 week 19  \\\n",
       "interface                                       ...                             \n",
       "desktop visual editor     4.4%   4.1%    3.9%   ...      3.1%    3.0%    3.0%   \n",
       "desktop wikitext editor   8.0%   7.8%    7.5%   ...      6.8%    6.8%    6.7%   \n",
       "mobile visual editor      2.0%   1.9%    1.8%   ...      1.3%    1.3%    1.3%   \n",
       "mobile wikitext editor    3.5%   3.4%    3.3%   ...      2.8%    2.7%    2.7%   \n",
       "\n",
       "                        week 20 week 21 week 22 week 23 week 24 week 25  \\\n",
       "interface                                                                 \n",
       "desktop visual editor      2.9%    2.8%    2.8%    2.7%    2.7%    2.7%   \n",
       "desktop wikitext editor    6.6%    6.6%    6.5%    6.5%    6.4%    6.3%   \n",
       "mobile visual editor       1.1%    1.0%    1.1%    1.1%    1.1%    1.1%   \n",
       "mobile wikitext editor     2.7%    2.6%    2.6%    2.6%    2.5%    2.5%   \n",
       "\n",
       "                        week 26  \n",
       "interface                        \n",
       "desktop visual editor      2.7%  \n",
       "desktop wikitext editor    6.3%  \n",
       "mobile visual editor       1.1%  \n",
       "mobile wikitext editor     2.4%  \n",
       "\n",
       "[4 rows x 26 columns]"
      ]
     },
     "execution_count": 258,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weekly_retention = weekly_edits.groupby(\"interface\").agg(pos_prop)\n",
    "weekly_retention.applymap(pct_str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 268,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f47c4df5f98>"
      ]
     },
     "execution_count": 268,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "retention_for_graph = weekly_retention.iloc[:, 1:].T\n",
    "retention_for_graph.index = range(2, 27)\n",
    "retention_for_graph.plot()\n",
    "plt.gca().yaxis.set_major_formatter(charting.pct_fmt)\n",
    "plt.ylim(ymin=0)\n",
    "plt.ylabel(\"percent retained as editors in the given interface\")\n",
    "plt.xlabel(\"week after first edit with the interface in the past year\")\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['week 1', 'week 2', 'week 3', 'week 4', 'week 5', 'week 6', 'week 7',\n",
       "       'week 8', 'week 9', 'week 10', 'week 11', 'week 12', 'week 13',\n",
       "       'week 14', 'week 15', 'week 16', 'week 17', 'week 18', 'week 19',\n",
       "       'week 20', 'week 21', 'week 22', 'week 23', 'week 24', 'week 25',\n",
       "       'week 26'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 237,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_229.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 246,
   "metadata": {},
   "outputs": [],
   "source": [
    "second_week = _229[\"week 2\"]\n",
    "second_week.name = \"second week\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 249,
   "metadata": {},
   "outputs": [],
   "source": [
    "second_month_edits = weekly_edits.loc[:, \"week 5\":\"week 8\"].sum(axis=1)\n",
    "second_month = second_month_edits.groupby(\"interface\").agg(pos_prop).map(pct_str)\n",
    "second_month.name = \"second month\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 251,
   "metadata": {},
   "outputs": [],
   "source": [
    "sixth_month_edits = weekly_edits.loc[:, \"week 23\":\"week 26\"].sum(axis=1)\n",
    "sixth_month = sixth_month_edits.groupby(\"interface\").agg(pos_prop).map(pct_str)\n",
    "sixth_month.name = \"sixth month\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 252,
   "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>second week</th>\n",
       "      <th>second month</th>\n",
       "      <th>sixth month</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>interface</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>desktop visual editor</th>\n",
       "      <td>8.6%</td>\n",
       "      <td>11.9%</td>\n",
       "      <td>6.4%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>desktop wikitext editor</th>\n",
       "      <td>12.4%</td>\n",
       "      <td>16.7%</td>\n",
       "      <td>11.6%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mobile visual editor</th>\n",
       "      <td>4.4%</td>\n",
       "      <td>6.0%</td>\n",
       "      <td>2.8%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mobile wikitext editor</th>\n",
       "      <td>5.9%</td>\n",
       "      <td>8.7%</td>\n",
       "      <td>5.5%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        second week second month sixth month\n",
       "interface                                                   \n",
       "desktop visual editor          8.6%        11.9%        6.4%\n",
       "desktop wikitext editor       12.4%        16.7%       11.6%\n",
       "mobile visual editor           4.4%         6.0%        2.8%\n",
       "mobile wikitext editor         5.9%         8.7%        5.5%"
      ]
     },
     "execution_count": 252,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.concat([second_week, second_month, sixth_month], axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## By experience"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "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></th>\n",
       "      <th>initial_experience</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user_name</th>\n",
       "      <th>interface</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>! Bikkit !</th>\n",
       "      <th>desktop wikitext editor</th>\n",
       "      <td>1-9 edits</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>!! !!ПОМОГИТЕ СЕСТРЕ НА ОПЕРАЦИЮ!! !!</th>\n",
       "      <th>desktop wikitext editor</th>\n",
       "      <td>1-9 edits</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>!!7597JOBV++!</th>\n",
       "      <th>desktop wikitext editor</th>\n",
       "      <td>1-9 edits</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>!!Ethereal!!</th>\n",
       "      <th>desktop wikitext editor</th>\n",
       "      <td>1-9 edits</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>!!Priyanshu Patel!!</th>\n",
       "      <th>desktop wikitext editor</th>\n",
       "      <td>1-9 edits</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                              initial_experience\n",
       "user_name                             interface                                 \n",
       "! Bikkit !                            desktop wikitext editor          1-9 edits\n",
       "!! !!ПОМОГИТЕ СЕСТРЕ НА ОПЕРАЦИЮ!! !! desktop wikitext editor          1-9 edits\n",
       "!!7597JOBV++!                         desktop wikitext editor          1-9 edits\n",
       "!!Ethereal!!                          desktop wikitext editor          1-9 edits\n",
       "!!Priyanshu Patel!!                   desktop wikitext editor          1-9 edits"
      ]
     },
     "execution_count": 230,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "experience = edits_r[[\"user_name\", \"interface\", \"initial_edit_count\"]].copy()\n",
    "experience = experience.groupby([\"user_name\", \"interface\"]).first()\n",
    "experience[\"initial_experience\"] = pd.cut(\n",
    "    experience[\"initial_edit_count\"], \n",
    "    bins=ec_bins[1:], \n",
    "    labels=ec_labels[1:],\n",
    "    right=False\n",
    ")\n",
    "experience = experience.drop([\"initial_edit_count\"], axis=1)\n",
    "experience.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 328,
   "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></th>\n",
       "      <th>week 1</th>\n",
       "      <th>week 2</th>\n",
       "      <th>week 3</th>\n",
       "      <th>week 4</th>\n",
       "      <th>week 5</th>\n",
       "      <th>week 6</th>\n",
       "      <th>week 7</th>\n",
       "      <th>week 8</th>\n",
       "      <th>week 9</th>\n",
       "      <th>week 10</th>\n",
       "      <th>...</th>\n",
       "      <th>week 17</th>\n",
       "      <th>week 18</th>\n",
       "      <th>week 19</th>\n",
       "      <th>week 20</th>\n",
       "      <th>week 21</th>\n",
       "      <th>week 22</th>\n",
       "      <th>week 23</th>\n",
       "      <th>week 24</th>\n",
       "      <th>week 25</th>\n",
       "      <th>week 26</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>interface</th>\n",
       "      <th>initial_experience</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <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=\"4\" valign=\"top\">desktop visual editor</th>\n",
       "      <th>1-9 edits</th>\n",
       "      <td>100.0%</td>\n",
       "      <td>6.9%</td>\n",
       "      <td>5.3%</td>\n",
       "      <td>4.5%</td>\n",
       "      <td>4.0%</td>\n",
       "      <td>3.5%</td>\n",
       "      <td>3.1%</td>\n",
       "      <td>2.9%</td>\n",
       "      <td>2.7%</td>\n",
       "      <td>2.5%</td>\n",
       "      <td>...</td>\n",
       "      <td>1.6%</td>\n",
       "      <td>1.6%</td>\n",
       "      <td>1.6%</td>\n",
       "      <td>1.5%</td>\n",
       "      <td>1.5%</td>\n",
       "      <td>1.4%</td>\n",
       "      <td>1.4%</td>\n",
       "      <td>1.4%</td>\n",
       "      <td>1.3%</td>\n",
       "      <td>1.4%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10-99 edits</th>\n",
       "      <td>100.0%</td>\n",
       "      <td>11.1%</td>\n",
       "      <td>9.2%</td>\n",
       "      <td>8.3%</td>\n",
       "      <td>7.6%</td>\n",
       "      <td>7.1%</td>\n",
       "      <td>6.5%</td>\n",
       "      <td>6.1%</td>\n",
       "      <td>5.9%</td>\n",
       "      <td>5.5%</td>\n",
       "      <td>...</td>\n",
       "      <td>4.6%</td>\n",
       "      <td>4.5%</td>\n",
       "      <td>4.5%</td>\n",
       "      <td>4.3%</td>\n",
       "      <td>4.3%</td>\n",
       "      <td>4.3%</td>\n",
       "      <td>4.1%</td>\n",
       "      <td>4.2%</td>\n",
       "      <td>4.1%</td>\n",
       "      <td>4.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100-999 edits</th>\n",
       "      <td>100.0%</td>\n",
       "      <td>16.8%</td>\n",
       "      <td>15.4%</td>\n",
       "      <td>13.9%</td>\n",
       "      <td>13.5%</td>\n",
       "      <td>13.1%</td>\n",
       "      <td>12.9%</td>\n",
       "      <td>12.4%</td>\n",
       "      <td>11.7%</td>\n",
       "      <td>11.6%</td>\n",
       "      <td>...</td>\n",
       "      <td>10.8%</td>\n",
       "      <td>10.7%</td>\n",
       "      <td>10.9%</td>\n",
       "      <td>10.4%</td>\n",
       "      <td>10.2%</td>\n",
       "      <td>10.2%</td>\n",
       "      <td>10.3%</td>\n",
       "      <td>10.3%</td>\n",
       "      <td>10.0%</td>\n",
       "      <td>10.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000+ edits</th>\n",
       "      <td>100.0%</td>\n",
       "      <td>25.0%</td>\n",
       "      <td>23.0%</td>\n",
       "      <td>22.4%</td>\n",
       "      <td>21.7%</td>\n",
       "      <td>21.3%</td>\n",
       "      <td>21.2%</td>\n",
       "      <td>20.0%</td>\n",
       "      <td>20.0%</td>\n",
       "      <td>19.6%</td>\n",
       "      <td>...</td>\n",
       "      <td>18.8%</td>\n",
       "      <td>18.9%</td>\n",
       "      <td>19.1%</td>\n",
       "      <td>18.1%</td>\n",
       "      <td>17.9%</td>\n",
       "      <td>18.1%</td>\n",
       "      <td>18.1%</td>\n",
       "      <td>18.2%</td>\n",
       "      <td>17.6%</td>\n",
       "      <td>17.5%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">desktop wikitext editor</th>\n",
       "      <th>1-9 edits</th>\n",
       "      <td>100.0%</td>\n",
       "      <td>9.8%</td>\n",
       "      <td>8.0%</td>\n",
       "      <td>7.1%</td>\n",
       "      <td>6.5%</td>\n",
       "      <td>6.1%</td>\n",
       "      <td>5.7%</td>\n",
       "      <td>5.4%</td>\n",
       "      <td>5.2%</td>\n",
       "      <td>5.0%</td>\n",
       "      <td>...</td>\n",
       "      <td>4.2%</td>\n",
       "      <td>4.1%</td>\n",
       "      <td>4.1%</td>\n",
       "      <td>4.0%</td>\n",
       "      <td>4.0%</td>\n",
       "      <td>3.9%</td>\n",
       "      <td>3.9%</td>\n",
       "      <td>3.8%</td>\n",
       "      <td>3.8%</td>\n",
       "      <td>3.7%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10-99 edits</th>\n",
       "      <td>100.0%</td>\n",
       "      <td>16.3%</td>\n",
       "      <td>14.8%</td>\n",
       "      <td>13.8%</td>\n",
       "      <td>13.3%</td>\n",
       "      <td>12.7%</td>\n",
       "      <td>12.3%</td>\n",
       "      <td>11.9%</td>\n",
       "      <td>11.8%</td>\n",
       "      <td>11.5%</td>\n",
       "      <td>...</td>\n",
       "      <td>10.9%</td>\n",
       "      <td>10.8%</td>\n",
       "      <td>10.6%</td>\n",
       "      <td>10.5%</td>\n",
       "      <td>10.5%</td>\n",
       "      <td>10.5%</td>\n",
       "      <td>10.5%</td>\n",
       "      <td>10.4%</td>\n",
       "      <td>10.2%</td>\n",
       "      <td>10.2%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100-999 edits</th>\n",
       "      <td>100.0%</td>\n",
       "      <td>22.4%</td>\n",
       "      <td>20.5%</td>\n",
       "      <td>19.7%</td>\n",
       "      <td>19.4%</td>\n",
       "      <td>18.6%</td>\n",
       "      <td>18.1%</td>\n",
       "      <td>17.6%</td>\n",
       "      <td>17.4%</td>\n",
       "      <td>17.0%</td>\n",
       "      <td>...</td>\n",
       "      <td>16.4%</td>\n",
       "      <td>16.5%</td>\n",
       "      <td>16.6%</td>\n",
       "      <td>16.3%</td>\n",
       "      <td>16.3%</td>\n",
       "      <td>16.2%</td>\n",
       "      <td>16.0%</td>\n",
       "      <td>16.1%</td>\n",
       "      <td>15.8%</td>\n",
       "      <td>15.8%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000+ edits</th>\n",
       "      <td>100.0%</td>\n",
       "      <td>35.7%</td>\n",
       "      <td>34.1%</td>\n",
       "      <td>33.2%</td>\n",
       "      <td>32.3%</td>\n",
       "      <td>32.1%</td>\n",
       "      <td>31.3%</td>\n",
       "      <td>31.1%</td>\n",
       "      <td>31.1%</td>\n",
       "      <td>31.0%</td>\n",
       "      <td>...</td>\n",
       "      <td>30.2%</td>\n",
       "      <td>29.7%</td>\n",
       "      <td>29.9%</td>\n",
       "      <td>29.4%</td>\n",
       "      <td>29.5%</td>\n",
       "      <td>29.7%</td>\n",
       "      <td>29.6%</td>\n",
       "      <td>28.9%</td>\n",
       "      <td>29.3%</td>\n",
       "      <td>29.6%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">mobile visual editor</th>\n",
       "      <th>1-9 edits</th>\n",
       "      <td>100.0%</td>\n",
       "      <td>2.8%</td>\n",
       "      <td>2.0%</td>\n",
       "      <td>1.9%</td>\n",
       "      <td>1.5%</td>\n",
       "      <td>1.4%</td>\n",
       "      <td>1.3%</td>\n",
       "      <td>1.1%</td>\n",
       "      <td>1.1%</td>\n",
       "      <td>1.0%</td>\n",
       "      <td>...</td>\n",
       "      <td>0.7%</td>\n",
       "      <td>0.7%</td>\n",
       "      <td>0.7%</td>\n",
       "      <td>0.5%</td>\n",
       "      <td>0.5%</td>\n",
       "      <td>0.5%</td>\n",
       "      <td>0.5%</td>\n",
       "      <td>0.5%</td>\n",
       "      <td>0.6%</td>\n",
       "      <td>0.5%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10-99 edits</th>\n",
       "      <td>100.0%</td>\n",
       "      <td>9.8%</td>\n",
       "      <td>7.6%</td>\n",
       "      <td>6.5%</td>\n",
       "      <td>6.1%</td>\n",
       "      <td>4.9%</td>\n",
       "      <td>4.7%</td>\n",
       "      <td>5.4%</td>\n",
       "      <td>4.8%</td>\n",
       "      <td>4.2%</td>\n",
       "      <td>...</td>\n",
       "      <td>3.1%</td>\n",
       "      <td>3.0%</td>\n",
       "      <td>3.1%</td>\n",
       "      <td>3.1%</td>\n",
       "      <td>2.8%</td>\n",
       "      <td>2.9%</td>\n",
       "      <td>2.9%</td>\n",
       "      <td>2.9%</td>\n",
       "      <td>2.6%</td>\n",
       "      <td>3.1%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100-999 edits</th>\n",
       "      <td>100.0%</td>\n",
       "      <td>15.1%</td>\n",
       "      <td>13.7%</td>\n",
       "      <td>12.9%</td>\n",
       "      <td>11.5%</td>\n",
       "      <td>10.4%</td>\n",
       "      <td>9.0%</td>\n",
       "      <td>7.5%</td>\n",
       "      <td>7.2%</td>\n",
       "      <td>8.6%</td>\n",
       "      <td>...</td>\n",
       "      <td>5.9%</td>\n",
       "      <td>6.0%</td>\n",
       "      <td>6.4%</td>\n",
       "      <td>5.1%</td>\n",
       "      <td>4.9%</td>\n",
       "      <td>4.6%</td>\n",
       "      <td>4.3%</td>\n",
       "      <td>5.3%</td>\n",
       "      <td>5.0%</td>\n",
       "      <td>5.2%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000+ edits</th>\n",
       "      <td>100.0%</td>\n",
       "      <td>16.6%</td>\n",
       "      <td>16.8%</td>\n",
       "      <td>13.6%</td>\n",
       "      <td>11.6%</td>\n",
       "      <td>11.8%</td>\n",
       "      <td>9.9%</td>\n",
       "      <td>9.9%</td>\n",
       "      <td>9.1%</td>\n",
       "      <td>8.3%</td>\n",
       "      <td>...</td>\n",
       "      <td>6.5%</td>\n",
       "      <td>9.1%</td>\n",
       "      <td>7.1%</td>\n",
       "      <td>6.5%</td>\n",
       "      <td>7.5%</td>\n",
       "      <td>6.1%</td>\n",
       "      <td>6.9%</td>\n",
       "      <td>6.5%</td>\n",
       "      <td>8.1%</td>\n",
       "      <td>6.5%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">mobile wikitext editor</th>\n",
       "      <th>1-9 edits</th>\n",
       "      <td>100.0%</td>\n",
       "      <td>4.1%</td>\n",
       "      <td>3.2%</td>\n",
       "      <td>2.8%</td>\n",
       "      <td>2.5%</td>\n",
       "      <td>2.3%</td>\n",
       "      <td>2.1%</td>\n",
       "      <td>2.0%</td>\n",
       "      <td>1.9%</td>\n",
       "      <td>1.8%</td>\n",
       "      <td>...</td>\n",
       "      <td>1.5%</td>\n",
       "      <td>1.4%</td>\n",
       "      <td>1.3%</td>\n",
       "      <td>1.3%</td>\n",
       "      <td>1.3%</td>\n",
       "      <td>1.3%</td>\n",
       "      <td>1.3%</td>\n",
       "      <td>1.2%</td>\n",
       "      <td>1.2%</td>\n",
       "      <td>1.2%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10-99 edits</th>\n",
       "      <td>100.0%</td>\n",
       "      <td>10.9%</td>\n",
       "      <td>9.4%</td>\n",
       "      <td>8.8%</td>\n",
       "      <td>8.5%</td>\n",
       "      <td>7.9%</td>\n",
       "      <td>7.5%</td>\n",
       "      <td>7.5%</td>\n",
       "      <td>7.2%</td>\n",
       "      <td>7.1%</td>\n",
       "      <td>...</td>\n",
       "      <td>5.9%</td>\n",
       "      <td>5.8%</td>\n",
       "      <td>5.7%</td>\n",
       "      <td>5.6%</td>\n",
       "      <td>5.5%</td>\n",
       "      <td>5.6%</td>\n",
       "      <td>5.5%</td>\n",
       "      <td>5.5%</td>\n",
       "      <td>5.5%</td>\n",
       "      <td>5.1%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100-999 edits</th>\n",
       "      <td>100.0%</td>\n",
       "      <td>16.7%</td>\n",
       "      <td>15.1%</td>\n",
       "      <td>15.0%</td>\n",
       "      <td>14.2%</td>\n",
       "      <td>13.4%</td>\n",
       "      <td>13.3%</td>\n",
       "      <td>12.9%</td>\n",
       "      <td>12.8%</td>\n",
       "      <td>12.8%</td>\n",
       "      <td>...</td>\n",
       "      <td>11.9%</td>\n",
       "      <td>11.4%</td>\n",
       "      <td>11.5%</td>\n",
       "      <td>11.4%</td>\n",
       "      <td>10.9%</td>\n",
       "      <td>10.9%</td>\n",
       "      <td>11.4%</td>\n",
       "      <td>11.5%</td>\n",
       "      <td>10.8%</td>\n",
       "      <td>10.9%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000+ edits</th>\n",
       "      <td>100.0%</td>\n",
       "      <td>20.0%</td>\n",
       "      <td>18.4%</td>\n",
       "      <td>17.6%</td>\n",
       "      <td>17.1%</td>\n",
       "      <td>16.5%</td>\n",
       "      <td>16.7%</td>\n",
       "      <td>16.1%</td>\n",
       "      <td>16.3%</td>\n",
       "      <td>16.1%</td>\n",
       "      <td>...</td>\n",
       "      <td>15.1%</td>\n",
       "      <td>14.7%</td>\n",
       "      <td>14.1%</td>\n",
       "      <td>14.9%</td>\n",
       "      <td>14.4%</td>\n",
       "      <td>15.0%</td>\n",
       "      <td>14.6%</td>\n",
       "      <td>14.5%</td>\n",
       "      <td>14.7%</td>\n",
       "      <td>14.1%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            week 1 week 2 week 3 week 4  \\\n",
       "interface               initial_experience                                \n",
       "desktop visual editor   1-9 edits           100.0%   6.9%   5.3%   4.5%   \n",
       "                        10-99 edits         100.0%  11.1%   9.2%   8.3%   \n",
       "                        100-999 edits       100.0%  16.8%  15.4%  13.9%   \n",
       "                        1000+ edits         100.0%  25.0%  23.0%  22.4%   \n",
       "desktop wikitext editor 1-9 edits           100.0%   9.8%   8.0%   7.1%   \n",
       "                        10-99 edits         100.0%  16.3%  14.8%  13.8%   \n",
       "                        100-999 edits       100.0%  22.4%  20.5%  19.7%   \n",
       "                        1000+ edits         100.0%  35.7%  34.1%  33.2%   \n",
       "mobile visual editor    1-9 edits           100.0%   2.8%   2.0%   1.9%   \n",
       "                        10-99 edits         100.0%   9.8%   7.6%   6.5%   \n",
       "                        100-999 edits       100.0%  15.1%  13.7%  12.9%   \n",
       "                        1000+ edits         100.0%  16.6%  16.8%  13.6%   \n",
       "mobile wikitext editor  1-9 edits           100.0%   4.1%   3.2%   2.8%   \n",
       "                        10-99 edits         100.0%  10.9%   9.4%   8.8%   \n",
       "                        100-999 edits       100.0%  16.7%  15.1%  15.0%   \n",
       "                        1000+ edits         100.0%  20.0%  18.4%  17.6%   \n",
       "\n",
       "                                           week 5 week 6 week 7 week 8 week 9  \\\n",
       "interface               initial_experience                                      \n",
       "desktop visual editor   1-9 edits            4.0%   3.5%   3.1%   2.9%   2.7%   \n",
       "                        10-99 edits          7.6%   7.1%   6.5%   6.1%   5.9%   \n",
       "                        100-999 edits       13.5%  13.1%  12.9%  12.4%  11.7%   \n",
       "                        1000+ edits         21.7%  21.3%  21.2%  20.0%  20.0%   \n",
       "desktop wikitext editor 1-9 edits            6.5%   6.1%   5.7%   5.4%   5.2%   \n",
       "                        10-99 edits         13.3%  12.7%  12.3%  11.9%  11.8%   \n",
       "                        100-999 edits       19.4%  18.6%  18.1%  17.6%  17.4%   \n",
       "                        1000+ edits         32.3%  32.1%  31.3%  31.1%  31.1%   \n",
       "mobile visual editor    1-9 edits            1.5%   1.4%   1.3%   1.1%   1.1%   \n",
       "                        10-99 edits          6.1%   4.9%   4.7%   5.4%   4.8%   \n",
       "                        100-999 edits       11.5%  10.4%   9.0%   7.5%   7.2%   \n",
       "                        1000+ edits         11.6%  11.8%   9.9%   9.9%   9.1%   \n",
       "mobile wikitext editor  1-9 edits            2.5%   2.3%   2.1%   2.0%   1.9%   \n",
       "                        10-99 edits          8.5%   7.9%   7.5%   7.5%   7.2%   \n",
       "                        100-999 edits       14.2%  13.4%  13.3%  12.9%  12.8%   \n",
       "                        1000+ edits         17.1%  16.5%  16.7%  16.1%  16.3%   \n",
       "\n",
       "                                           week 10   ...   week 17 week 18  \\\n",
       "interface               initial_experience           ...                     \n",
       "desktop visual editor   1-9 edits             2.5%   ...      1.6%    1.6%   \n",
       "                        10-99 edits           5.5%   ...      4.6%    4.5%   \n",
       "                        100-999 edits        11.6%   ...     10.8%   10.7%   \n",
       "                        1000+ edits          19.6%   ...     18.8%   18.9%   \n",
       "desktop wikitext editor 1-9 edits             5.0%   ...      4.2%    4.1%   \n",
       "                        10-99 edits          11.5%   ...     10.9%   10.8%   \n",
       "                        100-999 edits        17.0%   ...     16.4%   16.5%   \n",
       "                        1000+ edits          31.0%   ...     30.2%   29.7%   \n",
       "mobile visual editor    1-9 edits             1.0%   ...      0.7%    0.7%   \n",
       "                        10-99 edits           4.2%   ...      3.1%    3.0%   \n",
       "                        100-999 edits         8.6%   ...      5.9%    6.0%   \n",
       "                        1000+ edits           8.3%   ...      6.5%    9.1%   \n",
       "mobile wikitext editor  1-9 edits             1.8%   ...      1.5%    1.4%   \n",
       "                        10-99 edits           7.1%   ...      5.9%    5.8%   \n",
       "                        100-999 edits        12.8%   ...     11.9%   11.4%   \n",
       "                        1000+ edits          16.1%   ...     15.1%   14.7%   \n",
       "\n",
       "                                           week 19 week 20 week 21 week 22  \\\n",
       "interface               initial_experience                                   \n",
       "desktop visual editor   1-9 edits             1.6%    1.5%    1.5%    1.4%   \n",
       "                        10-99 edits           4.5%    4.3%    4.3%    4.3%   \n",
       "                        100-999 edits        10.9%   10.4%   10.2%   10.2%   \n",
       "                        1000+ edits          19.1%   18.1%   17.9%   18.1%   \n",
       "desktop wikitext editor 1-9 edits             4.1%    4.0%    4.0%    3.9%   \n",
       "                        10-99 edits          10.6%   10.5%   10.5%   10.5%   \n",
       "                        100-999 edits        16.6%   16.3%   16.3%   16.2%   \n",
       "                        1000+ edits          29.9%   29.4%   29.5%   29.7%   \n",
       "mobile visual editor    1-9 edits             0.7%    0.5%    0.5%    0.5%   \n",
       "                        10-99 edits           3.1%    3.1%    2.8%    2.9%   \n",
       "                        100-999 edits         6.4%    5.1%    4.9%    4.6%   \n",
       "                        1000+ edits           7.1%    6.5%    7.5%    6.1%   \n",
       "mobile wikitext editor  1-9 edits             1.3%    1.3%    1.3%    1.3%   \n",
       "                        10-99 edits           5.7%    5.6%    5.5%    5.6%   \n",
       "                        100-999 edits        11.5%   11.4%   10.9%   10.9%   \n",
       "                        1000+ edits          14.1%   14.9%   14.4%   15.0%   \n",
       "\n",
       "                                           week 23 week 24 week 25 week 26  \n",
       "interface               initial_experience                                  \n",
       "desktop visual editor   1-9 edits             1.4%    1.4%    1.3%    1.4%  \n",
       "                        10-99 edits           4.1%    4.2%    4.1%    4.0%  \n",
       "                        100-999 edits        10.3%   10.3%   10.0%   10.0%  \n",
       "                        1000+ edits          18.1%   18.2%   17.6%   17.5%  \n",
       "desktop wikitext editor 1-9 edits             3.9%    3.8%    3.8%    3.7%  \n",
       "                        10-99 edits          10.5%   10.4%   10.2%   10.2%  \n",
       "                        100-999 edits        16.0%   16.1%   15.8%   15.8%  \n",
       "                        1000+ edits          29.6%   28.9%   29.3%   29.6%  \n",
       "mobile visual editor    1-9 edits             0.5%    0.5%    0.6%    0.5%  \n",
       "                        10-99 edits           2.9%    2.9%    2.6%    3.1%  \n",
       "                        100-999 edits         4.3%    5.3%    5.0%    5.2%  \n",
       "                        1000+ edits           6.9%    6.5%    8.1%    6.5%  \n",
       "mobile wikitext editor  1-9 edits             1.3%    1.2%    1.2%    1.2%  \n",
       "                        10-99 edits           5.5%    5.5%    5.5%    5.1%  \n",
       "                        100-999 edits        11.4%   11.5%   10.8%   10.9%  \n",
       "                        1000+ edits          14.6%   14.5%   14.7%   14.1%  \n",
       "\n",
       "[16 rows x 26 columns]"
      ]
     },
     "execution_count": 328,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "retention_by_experience = weekly_edits.join(experience).groupby(\n",
    "    [\"interface\", \"initial_experience\"]\n",
    ").agg(pos_prop)\n",
    "\n",
    "retention_by_experience.applymap(pct_str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 330,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "newbie_retention = retention_by_experience.xs(\"1-9 edits\", level=1)\n",
    "\n",
    "for_graph = newbie_retention.iloc[:, 1:].T\n",
    "for_graph.index = range(2, 27)\n",
    "\n",
    "for_graph.plot()\n",
    "plt.gca().yaxis.set_major_formatter(charting.pct_fmt)\n",
    "plt.ylim(ymin=0)\n",
    "plt.ylabel(\"percent retained as editors in the given interface\")\n",
    "plt.xlabel(\"week after first edit with the interface in the past year\")\n",
    "plt.title(\"Interface retention among inexperienced editors\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 331,
   "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></th>\n",
       "      <th>week 1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>interface</th>\n",
       "      <th>initial_experience</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">desktop visual editor</th>\n",
       "      <th>1-9 edits</th>\n",
       "      <td>256058</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10-99 edits</th>\n",
       "      <td>55906</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100-999 edits</th>\n",
       "      <td>19627</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000+ edits</th>\n",
       "      <td>7967</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">desktop wikitext editor</th>\n",
       "      <th>1-9 edits</th>\n",
       "      <td>589884</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10-99 edits</th>\n",
       "      <td>114853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100-999 edits</th>\n",
       "      <td>57749</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000+ edits</th>\n",
       "      <td>22566</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">mobile visual editor</th>\n",
       "      <th>1-9 edits</th>\n",
       "      <td>31681</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10-99 edits</th>\n",
       "      <td>5255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100-999 edits</th>\n",
       "      <td>1361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000+ edits</th>\n",
       "      <td>493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">mobile wikitext editor</th>\n",
       "      <th>1-9 edits</th>\n",
       "      <td>194749</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10-99 edits</th>\n",
       "      <td>24287</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100-999 edits</th>\n",
       "      <td>11885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000+ edits</th>\n",
       "      <td>6942</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            week 1\n",
       "interface               initial_experience        \n",
       "desktop visual editor   1-9 edits           256058\n",
       "                        10-99 edits          55906\n",
       "                        100-999 edits        19627\n",
       "                        1000+ edits           7967\n",
       "desktop wikitext editor 1-9 edits           589884\n",
       "                        10-99 edits         114853\n",
       "                        100-999 edits        57749\n",
       "                        1000+ edits          22566\n",
       "mobile visual editor    1-9 edits            31681\n",
       "                        10-99 edits           5255\n",
       "                        100-999 edits         1361\n",
       "                        1000+ edits            493\n",
       "mobile wikitext editor  1-9 edits           194749\n",
       "                        10-99 edits          24287\n",
       "                        100-999 edits        11885\n",
       "                        1000+ edits           6942"
      ]
     },
     "execution_count": 331,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# How many people are contributing to these statistics?\n",
    "pd.DataFrame(weekly_edits[\"week 1\"]).join(experience).groupby([\"interface\", \"initial_experience\"]).count()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Editor proportion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 332,
   "metadata": {},
   "outputs": [],
   "source": [
    "started = may_sessions.query(\"ready_count >= 1\")\n",
    "completed = started.query(\"save_success_count >=1 \")\n",
    "mobile_edits = completed.query(\"platform == 'phone'\")\n",
    "desktop_edits = completed.query(\"platform == 'desktop'\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 333,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "editor\n",
       "visualeditor     9.9%\n",
       "wikitext        90.1%\n",
       "Name: actions, dtype: object"
      ]
     },
     "execution_count": 333,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "desktop_edits.groupby(\"editor\")[\"actions\"].agg(lambda grp: len(grp) / len(desktop_edits)).map(pct_str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 334,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "editor\n",
       "visualeditor     6.1%\n",
       "wikitext        93.9%\n",
       "Name: actions, dtype: object"
      ]
     },
     "execution_count": 334,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mobile_edits.groupby(\"editor\")[\"actions\"].agg(lambda grp: len(grp) / len(mobile_edits)).map(pct_str)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## VE-default wikis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "However, on desktop this isn't the fairest of comparisons, since the visual editor isn't available on many wikis and many wikis and many namespaces. How does the picture look when we limit it to VE-default wikis?\n",
    "\n",
    "To get the list of VE-default wikis, we start with the [\"visualeditor-nondefault\" database list](https://phabricator.wikimedia.org/source/mediawiki-config/browse/master/dblists/visualeditor-nondefault.dblist?as=source&blame=off). On top of that, we need to add the wikis where visual editor is demoted using settings in [InitialiseSettings.php](https://phabricator.wikimedia.org/source/mediawiki-config/browse/master/wmf-config/InitialiseSettings.php):  wmgVisualEditorSingleEditTabSecondaryEditor (enwiki and frwiktionary) and wmgVisualEditorDisableForAnons (enwiki and eswiki)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 338,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get raw dblist file\n",
    "r = requests.get(\"https://raw.githubusercontent.com/wikimedia/operations-mediawiki-config/master/dblists/visualeditor-nondefault.dblist\")\n",
    "\n",
    "# Strip comments\n",
    "no_comments = re.sub(r\"#.*\\n\", \"\", r.text)\n",
    "\n",
    "# Split by line\n",
    "nonve_dbs = re.split(\"\\n\", no_comments)\n",
    "\n",
    "# Remove the trailing empty line\n",
    "nonve_dbs.remove(\"\")\n",
    "\n",
    "# Add our extras\n",
    "nonve_dbs.extend([\"enwiki\", \"eswiki\", \"frwiktionary\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 340,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "editor\n",
       "visualeditor    14.8%\n",
       "wikitext        85.2%\n",
       "Name: actions, dtype: object"
      ]
     },
     "execution_count": 340,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ve_def_edits = desktop_edits.query('wiki not in @nonve_dbs')\n",
    "\n",
    "ve_def_edits.groupby(\"editor\")[\"actions\"].agg(lambda grp: len(grp) / len(ve_def_edits)).map(pct_str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 341,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "editor\n",
       "visualeditor     5.7%\n",
       "wikitext        94.3%\n",
       "Name: actions, dtype: object"
      ]
     },
     "execution_count": 341,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ve_nondef_edits = desktop_edits.query('wiki in @nonve_dbs')\n",
    "ve_nondef_edits.groupby(\"editor\")[\"actions\"].agg(lambda grp: len(grp) / len(ve_nondef_edits)).map(pct_str)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Funnel chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "def calc_funnel(df, omitloaded=False, omitsaveintent=False):\n",
    "    results = OrderedDict()\n",
    "    \n",
    "    with_inits = df.query(\"init_count >= 1\") \n",
    "    total = len(with_inits)\n",
    "    results[\"init\"] = len(with_inits) / total\n",
    "    \n",
    "    with_readies = with_inits.query(\"ready_count >= 1\")\n",
    "    results[\"ready\"] = len(with_readies) / total\n",
    "    \n",
    "    with_loaded = with_readies.query(\"loaded_count >= 1\")\n",
    "    if not omitloaded and len(with_loaded) > 0:\n",
    "        results[\"loaded\"] = len(with_loaded) / total\n",
    "        with_readies = with_loaded\n",
    "    \n",
    "    with_saveintents = with_readies.query(\"save_intent_count >= 1\")\n",
    "    if not omitsaveintent and len(with_saveintents) > 0:\n",
    "        results[\"saveIntent\"] = len(with_saveintents) / total\n",
    "        with_readies = with_saveintents\n",
    "    \n",
    "    with_saveattempts = with_readies.query(\"save_attempt_count >= 1\")\n",
    "    results[\"saveAttempt\"] = len(with_saveattempts) / total\n",
    "    \n",
    "    with_savesuccesses = with_saveattempts.query(\"save_success_count >= 1\")\n",
    "    results[\"saveSuccess\"] = len(with_savesuccesses) / total\n",
    "    \n",
    "    return pd.DataFrame(results, index = [\"percentage_reaching\"]).T.applymap(pct_str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>percentage_reaching</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>init</th>\n",
       "      <td>100.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ready</th>\n",
       "      <td>63.9%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>saveAttempt</th>\n",
       "      <td>7.9%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>saveSuccess</th>\n",
       "      <td>7.7%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            percentage_reaching\n",
       "init                     100.0%\n",
       "ready                     63.9%\n",
       "saveAttempt                7.9%\n",
       "saveSuccess                7.7%"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "calc_funnel(may_sessions, omitloaded=True, omitsaveintent=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"4\" halign=\"left\">percentage_reaching</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>platform</th>\n",
       "      <th colspan=\"2\" halign=\"left\">desktop</th>\n",
       "      <th colspan=\"2\" halign=\"left\">phone</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>editor</th>\n",
       "      <th>visualeditor</th>\n",
       "      <th>wikitext</th>\n",
       "      <th>visualeditor</th>\n",
       "      <th>wikitext</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>init</th>\n",
       "      <td>100.0%</td>\n",
       "      <td>100.0%</td>\n",
       "      <td>100.0%</td>\n",
       "      <td>100.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>loaded</th>\n",
       "      <td>92.3%</td>\n",
       "      <td>41.7%</td>\n",
       "      <td>—</td>\n",
       "      <td>—</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ready</th>\n",
       "      <td>92.3%</td>\n",
       "      <td>42.0%</td>\n",
       "      <td>95.4%</td>\n",
       "      <td>97.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>saveAttempt</th>\n",
       "      <td>12.6%</td>\n",
       "      <td>10.4%</td>\n",
       "      <td>17.1%</td>\n",
       "      <td>2.7%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>saveIntent</th>\n",
       "      <td>13.2%</td>\n",
       "      <td>—</td>\n",
       "      <td>18.8%</td>\n",
       "      <td>3.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>saveSuccess</th>\n",
       "      <td>11.6%</td>\n",
       "      <td>10.2%</td>\n",
       "      <td>15.1%</td>\n",
       "      <td>2.5%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            percentage_reaching                               \n",
       "platform                desktop                 phone         \n",
       "editor             visualeditor wikitext visualeditor wikitext\n",
       "init                     100.0%   100.0%       100.0%   100.0%\n",
       "loaded                    92.3%    41.7%            —        —\n",
       "ready                     92.3%    42.0%        95.4%    97.0%\n",
       "saveAttempt               12.6%    10.4%        17.1%     2.7%\n",
       "saveIntent                13.2%        —        18.8%     3.0%\n",
       "saveSuccess               11.6%    10.2%        15.1%     2.5%"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "may_sessions.groupby([\"platform\", \"editor\"]).apply(calc_funnel).unstack([0, 1]).fillna(\"—\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Low ready rate on the desktop wikitext editor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3340351"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "with_inits = may_sessions.query(\"platform == 'desktop' & editor == 'wikitext' & init_count >= 1\")\n",
    "len(with_inits)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It's not because a lot of sessions skip the loaded event."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9938517826194514"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(with_inits.query(\"loaded_count >= 1 & ready_count >= 1\")) / len(with_inits.query(\"ready_count >= 1\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The desktop wikitext editor has more sessions that drop after init (because there's no ready) but that still have other later events. However, it's not enough to explain the dramatically lower ready rate."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "87.4%\n"
     ]
    }
   ],
   "source": [
    "wt_init_no_ready = with_inits.query(\"ready_count == 0\")\n",
    "wt_init_only = wt_init_no_ready.query(\"ready_count == 0 & save_intent_count == 0 & save_attempt_count == 0 & save_success_count == 0\")\n",
    "\n",
    "print(pct_str(len(wt_init_only) / len(wt_init_no_ready)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "97.6%\n"
     ]
    }
   ],
   "source": [
    "ve_init_no_ready = may_sessions.query(\"platform == 'desktop' & editor == 'visualeditor' & init_count >= 1 & ready_count == 0\")\n",
    "ve_init_only = ve_init_no_ready.query(\"ready_count == 0 & save_intent_count == 0 & save_attempt_count == 0 & save_success_count == 0\")\n",
    "\n",
    "print(pct_str(len(ve_init_only) / len(ve_init_no_ready)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Edit completion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "platform\n",
       "desktop    22.5%\n",
       "phone       2.7%\n",
       "dtype: object"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def completion_rate(df):\n",
    "    started = df.query(\"ready_count >= 1\")\n",
    "    completed = started.query(\"save_success_count >= 1\")\n",
    "    if len(started) > 0:\n",
    "        return len(completed) / len(started)\n",
    "    else:\n",
    "        return None\n",
    "\n",
    "may_sessions.groupby([\"platform\"]).apply(completion_rate).map(pct_str)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Desktop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "editor\n",
       "visualeditor    12.6%\n",
       "wikitext        24.6%\n",
       "dtype: object"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "desktop = may_sessions.query(\"platform == 'desktop'\")\n",
    "desktop.groupby([\"editor\"]).apply(completion_rate).map(pct_str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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",
       "    <tr>\n",
       "      <th>experience</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>IP</th>\n",
       "      <td>5.2%</td>\n",
       "      <td>6.4%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0 edits (new editor)</th>\n",
       "      <td>27.8%</td>\n",
       "      <td>18.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1-9 edits</th>\n",
       "      <td>45.3%</td>\n",
       "      <td>35.5%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10-99 edits</th>\n",
       "      <td>57.6%</td>\n",
       "      <td>48.8%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100-999 edits</th>\n",
       "      <td>65.3%</td>\n",
       "      <td>58.4%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000+ edits</th>\n",
       "      <td>73.3%</td>\n",
       "      <td>71.7%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "editor               visualeditor wikitext\n",
       "experience                                \n",
       "IP                           5.2%     6.4%\n",
       "0 edits (new editor)        27.8%    18.0%\n",
       "1-9 edits                   45.3%    35.5%\n",
       "10-99 edits                 57.6%    48.8%\n",
       "100-999 edits               65.3%    58.4%\n",
       "1000+ edits                 73.3%    71.7%"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "desktop.groupby([\"experience\", \"editor\"]).apply(completion_rate).unstack().applymap(pct_str)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Phone"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 349,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "editor\n",
       "visualeditor    15.8%\n",
       "wikitext         2.6%\n",
       "dtype: object"
      ]
     },
     "execution_count": 349,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "phone = may_sessions.query(\"platform == 'phone'\")\n",
    "phone.groupby([\"editor\"]).apply(completion_rate).map(pct_str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 350,
   "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",
       "    <tr>\n",
       "      <th>experience</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>IP</th>\n",
       "      <td>11.4%</td>\n",
       "      <td>1.5%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0 edits (new editor)</th>\n",
       "      <td>17.4%</td>\n",
       "      <td>21.9%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1-9 edits</th>\n",
       "      <td>28.0%</td>\n",
       "      <td>38.7%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10-99 edits</th>\n",
       "      <td>38.1%</td>\n",
       "      <td>45.8%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100-999 edits</th>\n",
       "      <td>52.1%</td>\n",
       "      <td>55.9%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000+ edits</th>\n",
       "      <td>58.1%</td>\n",
       "      <td>62.9%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "editor               visualeditor wikitext\n",
       "experience                                \n",
       "IP                          11.4%     1.5%\n",
       "0 edits (new editor)        17.4%    21.9%\n",
       "1-9 edits                   28.0%    38.7%\n",
       "10-99 edits                 38.1%    45.8%\n",
       "100-999 edits               52.1%    55.9%\n",
       "1000+ edits                 58.1%    62.9%"
      ]
     },
     "execution_count": 350,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "phone.groupby([\"experience\", \"editor\"]).apply(completion_rate).unstack().applymap(pct_str)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Time to save"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 351,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "114   00:07:54\n",
       "130   00:00:46\n",
       "137   00:01:55\n",
       "144   00:28:50\n",
       "158   00:00:12\n",
       "Name: duration, dtype: timedelta64[ns]"
      ]
     },
     "execution_count": 351,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "completed[\"duration\"].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 352,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "editor        platform\n",
       "visualeditor  desktop    00:01:40\n",
       "              phone      00:01:43\n",
       "wikitext      desktop    00:00:38\n",
       "              phone      00:00:48\n",
       "Name: duration, dtype: timedelta64[ns]"
      ]
     },
     "execution_count": 352,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "completed.groupby([\"editor\", \"platform\"])[\"duration\"].apply(np.median)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 357,
   "metadata": {},
   "outputs": [],
   "source": [
    "def duration_hist(ax, td_ser):\n",
    "    hist_vals = (\n",
    "        td_ser\n",
    "        .astype(\"timedelta64[s]\")\n",
    "        .replace(0, 1)\n",
    "    )\n",
    "\n",
    "    bins = np.floor(\n",
    "        np.logspace(0, 4, num=40, dtype=int)\n",
    "    )\n",
    "\n",
    "    ax.hist(hist_vals, bins=bins, label=None)\n",
    "    ax.set_xscale(\"log\")\n",
    "\n",
    "    s_ticks = [1, 10, 60, 10*60, 60*60, 150*60]\n",
    "    duration_ticks = FixedLocator(s_ticks)\n",
    "    \n",
    "    def to_td(s):\n",
    "        return str(timedelta(seconds=int(s)))\n",
    "    \n",
    "    duration_fmt = FuncFormatter(lambda x, pos: to_td(x))\n",
    "    \n",
    "    lines = [\n",
    "        (\"10th percentile ({})\", hist_vals.quantile(0.1), \"xkcd:pink\"),\n",
    "        (\"50th percentile ({})\", hist_vals.median(), \"xkcd:red\"),\n",
    "        (\"90th percentile ({})\", hist_vals.quantile(0.9), \"xkcd:dark red\")\n",
    "        \n",
    "    ]\n",
    "    \n",
    "    for label, pos, color in lines:\n",
    "        ax.axvline(x=pos, color=color, label=label.format(to_td(pos)))\n",
    "    \n",
    "    ax.legend()\n",
    "\n",
    "    ax.yaxis.set_major_formatter(charting.comma_fmt)\n",
    "    ax.set_ylabel(\"number of sampled, completed edit sessions\")\n",
    "\n",
    "    ax.xaxis.set_major_locator(duration_ticks)\n",
    "    ax.xaxis.set_major_formatter(duration_fmt)\n",
    "    ax.set_xlabel(\"time to save as %H:%M:%S (log scale)\")\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 358,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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E/H650C7vmp0NDg75B1V2g9BahdaGxMRE/P39KVWqlEV5QEAAmZmZnDhxgkaNGjFv3jyGDh3K7NmzadLEsCZh/fr1zfG7d+/m+PHjTJkyBRcXF1599VW6du1KUlKSRUKQlx49evB///d/jB8/ni1btjBlyhRKlChhHuKYnp5OixYtuHr1KjExMfj7+7NlyxZefPFFrl27xvDhwy2u169fP55++mlWr17N9evXAfjss88IDw/n8ccf5/3336d8+fIkJiZy+vRp83njxo3jrbfeYsSIEcyYMYPk5GQmTJjAkSNH2Lt3Lw45Pq9ly5ZRp04dZs2aRWZmJlFRUYSFhfHTTz9RsmRJ1q5dS+fOnQkMDDTfR4UKFez+bA4ePEjLli0JCgrigw8+oFSpUrz33nu0b9+evXv38uijj+Z57v79+0lLS7MaImzP5x0QEABA69atSUpKMs81/eWXX8jIyKBBgwYW57q4uFCzZk2OHj0KwNWrVzl16hSDBw+2aldAQIA5DgzDj/39/Zk0adJNz5c0Jd6522O6v5z1gCEZTU9PZ9++fbRt2/am6ipqdieDSqkyQGcMPYQuuQ5rrfWUO9kwIYQQQghx77pw4QJeXl5W5WXLljUfDwgIMCd+9erVo1mzZlbx6enpJCQkmK9VuXJlmjRpwueff27VO2XLv/71L8aNGwdAx44dSU9P56233mLkyJF4enoya9YsTp8+zY8//shDDz0EQPv27UlLS2Py5Mm8+OKLlCz5z6/MvXr14o033jC/1loTGRlJw4YN2b59u7nnqX379uaYpKQkZsyYwaRJk5g4caK5vHbt2rRo0YINGzZYzGFzdHQkPj7eopesd+/efPPNNzRv3pygoCCcnZ0pX768zfesIFFRUfj6+vLVV1/h5OQEQGhoKA0aNGDKlCmsW7cuz3P379+PUopHHnnEotyez9vEwcHB4j01HcvrfNPx1NRUtNZ5xh0/ftz8WimFg4OD3T3Zue8lr/Z4eXlZ9eYGBgZSokQJ9u/ff38mg0qpx4ENQF5/ftGAJINCCCGEEPYoxB45gKuXLuHufn8s9h4cHGzxS/nDDz8MwK+//mrX+X369LF43bdvXxYsWMCRI0do0aIFmzdv5rHHHsPf39/c0weG5GjBggUcPXrUIvHp2bOnxfWOHz/O6dOnGTduXJ6Jx7Zt27hx4wb9+vWzqOOxxx7D3d2dXbt2WSSDHTp0sEgEc95z8+bN7brvvFy9epWdO3cSHR1tnjtn0r59ez766KN8zz937hxlypQxJ5G34ssvv7zlc+1VvXp1i3srTI6Ojnh4eHDu3Lm7Ut+dZG/P4EwM+wz+C/hRa51ZaC0SQgghhBD3PC8vL4thkiamXhVTj1FBcseZFmzJyMiw6/xKlSrZfJ2cnAxASkoKJ06csEi+cvrrr78sXnt7e9s8nt+iLSkpKQDUqmX7jwC567jde87PhQsXyM7OZsqUKUyZYrsv58aNG3kmthkZGTYTwdv5vE3Jfmpqqs3zTcNLPT09UUrlGWfvd6og+bUnNTXVZj2urq739ZzBekAfrbXVnEEhhBBCCCFyCwgIYO3atVy5csViHtnRo0dxcnLKMzG6086fP0+NGjUsXgP4+PgAUK5cOSpWrMisWbNsnl+nTh2L17kXZylfvjzwT3JpS7ly5QDYunWrzaGHpuN3g6enJyVKlGDo0KE899xzNmPyG1pZrlw5Ll68aFV+O593zZo1cXZ2tlgkBwyJ58mTJ+nduzcApUqVws/PzyrOVE9ISEieddwMU/KZmJhIcHCwuTwpKYkrV65YzGk1uXDhgvm7cC+xdxDtr0DxWjdXCCGEEEIUW926dSMrK4tVq1aZy65fv86KFSvo2LGjubfL9FxYvSorV660eL18+XLc3NzMQy87derETz/9hK+vL40bN7Z6FDTctnbt2vj5+bFgwQK01jZjOnToQIkSJfj1119t1uHv73/T9+Xs7HxL71np0qVp2bIlP/zwA40aNbLZnvzUrVuXzMxMzp49a1Fu7+dti5OTE506dWLlypUWQztXr17NtWvX6N69u7mse/fubNy40SIh3bNnD6dPn7aIux2+vr4EBgZaDZldtmwZjo6OPPHEExblv//+OxkZGVZ/OLgX2NszOBkYp5T6UmudfjsVKqVCgbFAfcAL+APYC8RorY/miKsGvAN0ABTwBTBSa13gAHGllAuGOYwRGOY5JgBjtda7csWVMLZlCFAZOA68prVeY+Oa/wJGA/4Yhsy+o7XOe3MSIcRd5TeucBY2TprWpVCuK4QQ97LVq1cD8P33hkFjmzZtokKFClSoUMHcOxMUFMRTTz3FyJEjycrKwt/fn//85z+cOnXK4pfs2rVrU7JkSRYuXEjZsmVxdnamTp06d2zO4wcffMCNGzdo0qQJW7ZsYcGCBcTExODh4QHAyy+/zIoVK2jZsiUvv/wyderU4e+//+ann35i9+7dBW5XoJRi5syZPPnkk7Rt25YXXniBChUqcOzYMVJSUpg8eTI1a9Zk7NixDBs2jOPHjxMSEoKLiwtnzpxh27ZtDB482LzFhr3q16/P7t27iY+Pp3LlypQvXx4/Pz+7zn377bdp1aoVoaGhDBo0CG9vb/78808OHjxIdnY206ZNy/PcVq1aAfDNN99YDI219/MGaNeuHadPn+bEiRPmspiYGJo1a0afPn0YOnQoSUlJREVF0atXL4vVTaOioli2bBndu3dn/PjxXLx4kTFjxvDYY49ZzOc8ffo0NWvWZOLEiRaL9nz33XckJSWZtxc5evSo+fvcuXNnc6/m1KlT6dq1K0OGDOHpp5/m0KFDxMbGEhkZad5j0OTAgQMW7829xN5ksCtQCTillNoHXMh1XGut+9t5rbIYtqh4F0Mi6AuMA/YrpR7WWp9WSpUCvgKuAf0xLFATC2xXSj1i3OYiP/8FugBRwElgKLBFKRWstU7IETcF+DfwirFNfYFVSqmuWuvPTUHGRPB9IA5DUtoOeFcppbTW/7HzvoUQQggh7gumYXsmL730EmDYZDznHoGLFi3ilVdeYcKECaSlpREYGMjmzZvNG4iDYdjh3LlzmT59OiEhIWRnZ7N9+3Zat259R9r62WefMXz4cKZMmYKHhwcTJkzg1VdfNR/38PBg7969vPbaa0yfPp3k5GQ8PT2pU6cO4eHhdtURFhbGtm3bmDJlCoMGDQIMQx9Hjhxpjpk6dSr16tVj3rx5zJs3D6UU1apVo127duZVTG9GXFwc//rXv+jTpw9Xr16lf//+LF682K5zGzVqxLfffsvkyZMZMWIEFy9epEKFCjRq1IgXXngh33P9/Px49NFH2bBhg9UG7/Z83gDZ2dlWi7s0bNiQrVu3MnbsWLp06YKHhwfPPfccU6dOtYjz8fFh+/btjBo1ivDwcJycnAgLC+Ott96yGN6qtSY7O9tqT8m5c+eyZMkS8+tVq1aZezNPnTplTqg7d+7M6tWrmTx5MosXL6ZSpUpER0fzyiuvWL0n8fHxPProo3dt6POdpPLqzrYIUupUASFaa12jgJj8rl8H+An4t9b6LaVUJPA2UEdrfcIY4w/8DIzRWr+dz7UCMfQE/p/WepGxrCSQCBzXWnc3llUEzgDTtNaTcpz/JVBBa/1IjnPPAZtyJrxKqYVAd8Bba52V3/3VqVNH51zqVogH0pIE0tLS8IxsXSiXL+49g8W9fYXlT+Mvc+VzbSBdGHbs2HHHfnkU4nYsNX4PnzV+748dO0a9evXuahsu3Uerid6qmJgYJk+eTFZWlsU2BuL2vffee4wdO5bffvvNal/BB01GRgbe3t68+eab5j8E2HLp0iXOnj2b738LlFLfa63zH6d7h9k1Z1Br7V/A45YTQSPTEkqmPxF0B/abEkFjG04BXwNhBVyrO5AFrMhx7nVgORCqlDINWA4FnIBluc5fBjxsTD4BgoEKNuKWAuWAFgW0RwghhBBCiPvGU089RZUqVXj33XeLuilF7v3336dixYr072/vIMni5eZ3YbxDlFIOSiknpdRDGIZg/g58YjwcAByxcVoihrmG+QkATmmtr9g41wmolSPuGnDCRhw56gkwPuduT+44IYQQQggh7nslS5Zk0aJFD3yvIBgW8lm8ePE92/tsd6uN8/j+DwjBMO/vArAdWKS1vpXlnw4AptmgJ4C2WusU4+uygPXGHoY6rdfjtZTfuabjpuc0bT1O1lYcNq6ZO86CUup54HmAChUqWIyfF+JB1DDNMEegsP4tjH64cDaWvVPtLe7tKyxV09IAOHIX2nn58uVi/36IB0Oa8Xtv+j56eHhw6dKlu9qG7Ozsu15ncTN69GhGjx59T+79VtxlZ2cTEBBAQEDAA/8969evH0CB70N2djYZGRnF7v9TdiWDSqnKwA6gNnAaQy9eDSAcGK6Uaq21Pn+TdT8LlDFe59/ANqVUC6110k1ep1jSWs8H5oNhzqDMYxEPvNOGOYOF9W9hQGHNyevX+o5cp7i3r7D86ekJQK278N9AmTMoioszxu+96ft47Nixuz5/T+YMisIk36+bd+nSJVxcXAgKCirqpliwd5joGxh65Foa5wgGa639McyX8wSm32zFWutjWusDWutPMKzO6YZhVVEw9MLZ6gHMq9cvp/zOhX969FIBT5V751Dbcdi4Zu44IYQQQgghhLhn2JsMPgGM11p/nbNQa70XmIBhG4dbprVOwzBU1DSfL5F/5urlVB84aqM8p0TA3zisNfe5mfwzRzARcAZq2ogjRz2muYG525M7TgghhBBCCCHuGfYmg24Ytlew5azx+C1TSlUC6gK/GIvWA82UUjVyxPgBjxuP5WcD4AiYN8Axbg/xFLBVa33NWLwZw6qj/XKdHwEcMa5eCrAP+DOPuAsYVjgVQgghhBBCiHuKvQvIHMcwx2+zjWMRGPYItItSai1wEDgMpGOYh/gyhm0l3jKGfQAMAz5TSk3AsOn8FAz7Ar6f63oaWKK1HgCgtT6klFoBzFRKOQKngBcBf3IkdFrrFKXU28B4pdQlY5ueAtpi2J7CFJellHoVwybzyRg2nW+LYTGd4VrrTHvvXQghhBBCCCGKC3uTwTeBD409eB8DvwGVgb5AewyJor32A32A0Ri2ejiDYXGaONPiMVrrv5VSbYF3MOznp4AvgZFa68umCymlSht//D1XHQOB14FYDHMafwA6aa0P5op7BbgMRBrv5zjQR2sdnzNIa/2eMekcDUQBvwLDtNayuYoQQgghhBDinmRXMqi1Xmacg/casCDHofPAC1rrj+2tUGs9HTsWnNFa/4phtdL8PI5hHuDcXOdeBUYZH/nVkY0hYYy1oz3vk6tXUgghhBBCCCHuVXZvOm/cKqEKhoVUWhqffbTWHxRS2+wRgmGI6NkibIMQQhQZv3Eb79hDCCHssWPHDpRSVg9P45YaOaWmpjJ48GDKly9P6dKlad++PT/++KNFTEJCAjExMVy4YL1Au1KKCRMmFNq93MtiYmL46quvrMoHDBiAn5+f+XVSUhJKKRYvXnxH6+/evTvDhg2zKLPn887PunXrCAoKwsXFherVqxMbG0t2drZV3J49e2jevDmurq5UrlyZUaNG3dJ+ktOmTUMpRYsWLfKNW758OUopqlatalF+9epVvL29Wbly5U3XXVzYnQwCaK1vGLeE+Nr4fKOwGmZne17RWj9flG0QQgghhHgQzZ49m3379pkfX3zxhcVxrTXdunVj8+bNzJkzhzVr1pCVlUWbNm04e/afv+MnJCQwefJkm8mgyNvkyZNtJoOvvvoqa9euLdS6v/76a7Zu3cr48ePNZfZ+3nnZsmUL4eHhNGnShE2bNhEZGUlsbCzR0dEWcYcPH6ZDhw5UrFiR+Ph4YmNjWbRoEQMGDLipezh58iSxsbFUrFgx37i0tDRGjhxJ5cqVrY65uroyZswYoqOjycrKuqn6i4s8h4kqpZ4DNmqt/zL+nC+t9Yd3tGVCCCGEEKLYqlevHs2aNcvz+Pr16/n666/56quvaNOmDQDBwcH4+/vzxhtvMHv27LvV1EJz7do1nJ2di7oZFmrWzL1r2p03a9YsunXrho+Pj7nsdj/vcePG0aJFC+bPnw9AmzZtuHz5MrGxsbydCxDYAAAgAElEQVT88svmZGzSpElUrVqVVatW4ejoCICTkxP9+/dn7NixNGrUyK57ePHFF+nXrx/Hjx/n+vXrecaNGTOGwMBAvL29rf7gAYae2HHjxrF27Vr69OljV93FSX49g4v5Zw++xQU8Ft35pgkhhBBCiHvV+vXrqVKlijkxAPDw8KBbt2589tlnACxevJiBAwcC8NBDD5mHnCYlJVlca/bs2fj7++Pu7k5ISAiJiYkUZMCAAVStWpW9e/fSpEkTXFxc8PPzY86cOVaxp06dol+/flSoUAFnZ2caNmxo1bsWExODUoojR44QGhqKm5ubxS//a9eu5fHHH8fNzY0yZcrQtGlT1q//Z0e069evExcXR926dXF2dqZKlSqMHj2ajIwMc4xpSOf777/PxIkT8fb2xtPTk27duln0rimlAHj99dfN71lMTIz5vnMOE83Lzp07adeuHe7u7pQuXZrQ0FCOHDlS4Hnnzp1j27ZtPPPMMxbl9nzeeTlz5gwJCQlERERYlD/77LNkZWWxadMmALKysti8eTN9+vQxJ4IAffr0wcnJqcB6TD7++GMOHjxIXFxcvnFff/01y5YtY968eXnGeHl5ERoayoIFC/KMKc7yW0DGH8OqoaafhRBC3Mfu9LzBpGld7uj1hLifXBw5kqyEhEK7fnZ2NtccHPKNcWzYEI+ZM2+5jn79+vHnn3/i6elJaGgo06ZNw9fX13w8MTGRBg0aWJ0XEBDAhx9+yOXLl+nSpQsTJkwgNjaWVatWmedkeXt7m+OXLVtGnTp1mDVrFpmZmURFRREWFsZPP/1EyZL5r4WYnp7OU089xdixY6lVqxbLly9nxIgRuLu7m4cVnjlzhscee4yKFSvyzjvvUKFCBVasWEF4eDjr1q2je/fuFtcMCwtj0KBBjB07lhIlDP0qc+bMYcSIEfTo0YMlS5bg5ubGwYMHLZLaiIgINmzYwNixY2nevDnHjh3j1VdfJSkpiTVr1ljUERcXR/PmzVm4cCEpKSmMHj2aiIgIduzYAcC+ffsIDg5mwIABDBkyBMBqPlt+Nm7cSFhYGF26dGHZsmUATJ8+nZYtW3L48GGqVauW57nbtm0jOzubli1bWpTb83m7uRm2Jvfz88PPz898P6bkPvf5/v7+lCpViqNHjwLwyy+/kJGRYRXn4uJCzZo1zXFgmNvapk0bqyGkqampvPzyy7zxxhuULVs2z/vMysri+eefJyoqilq1auUZB9CqVSteeeUVMjIycHFxyTe2uMnzX5DW+rStn4UQQgghxIPLw8OD0aNHExISQpkyZTh06BBTp04lODiYQ4cOmedgXbhwwWYPlekX8NTUVKpVq2Ye1tiwYUObv3Q7OjoSHx9v0RPUu3dvvvnmG5o3b55vWy9dusT8+fPp27cvAJ06dSI5OZlJkybRv39/c4+a1pqdO3dSrlw5AEJDQzlz5gwTJ060SgZHjBhBZGSk+XV6ejrR0dH07NmTTz/91FweGhpq/nn37t2sWLGCJUuW8NxzhtlX7du3p2zZskRERJCQkEDDhg3N8X5+fnz88T+L9f/xxx9ERUVx7tw5qlSpYh6e6+Pjk+9Q3bxERkYSEhJi0ZPWpk0batSowVtvvcXMfP5IsH//fry9vSlfvrxFuT2ftykZLFmyJA45/lhhmi/q5eVldb6Xl5f5eH5xZcuWtZh3qpTCwcHBnLCbREVFUbt27QLnGE6fPp1r165ZzIvMS1BQEJmZmRw8eLDA72RxY9fWEkqp8kAp43YPprIhQANgS+59+YQQQgghRN5up0fOHpcuXcLd3b1Qrh0UFERQUJD5dUhICK1ataJp06bMnj2b2NgCd+y6KR06dLBIBB9++GEAfv311wJ/8XZwcCA83HKnsr59+zJ48GCSk5OpWrUqmzdvpnPnznh4eFjMHQsNDSUqKor09HTKlCljLu/Zs6fF9fbu3cvly5d5/vm81zTcvHkzTk5O9OrVy6KOjh07ArBr1y6LZLBz584W5+e85ypVquR7zwX5+eef+eWXX4iOjrZoS6lSpQgODmbXrl35nn/u3DmrRPBmnThx4rbOt0dISIjVXMDdu3fz4YcfcvDgQfNQW1tOnDjB66+/ztq1a+3q6atQoQJgeG/uNfZuOr8QOAu8BKCUehWYDKQCLymlntFaryicJgohhLgX+Y3byNyTfwEw7A4NQZWhp0IUT40aNaJ27dp8++235jIvLy9SU1OtYvPr3bEl91A+04ItOefa5cXLy8sikQSoVKkSgDkZTElJ4cMPP+TDD22vhfjXX39ZJIM5h7CajkP+wzRTUlLIzMykdOnSedaR0+3cc0FSUlIAGDRoEIMGDbI6nnOory0ZGRk4OTlZld/O5206Zuv81NRU8/uRX9yFCxcICAjIt+1Dhgxh0KBBVK1albS0NMAwlzM7O5u0tDRcXV1xdnZmxIgRtG3blmbNmpnjMjMz0VqTlpaGs7Mzrq6u5uuafr6V7S2Kmr3JYGNgSY7XLwBTtdYTlFKzMWzuLsmgEEIIIcQDLGdvS0BAAFu3brWKOXr0KL6+vuYhg4UpNTWVrKwsi4Tw/PnzAOaVMMuVK0fLli0ZO3aszWvk7onL3aNk6iVLTk62OWfOVIeLiwu7d++2q47CZBoKGxcXR/v27a2O20r0cp//yy+/WJXfzudtSuISExMJDg42lyclJXHlyhXq168PGFZKdXZ2tlpAKCMjg5MnT9K7d+98237s2DGOHTvGe++9Z3XMy8uLd955h5EjR3L06FFOnz6d57DVyMhIi6G0poT3dntMi4K9yWBZ4DyAUqoBUJl/ksN1QIFbTwghhBBCiPvTd999x/Hjx+nVq5e5rHv37ixatIidO3cSEhICGObXbdiwwWIlSlOvV2H0qmRnZ7NmzRrznEEwbCDu6+trTgY7derEvn37CAgIsOjtsVfz5s1xc3Nj/vz5FvMEc+rUqRPTp0/n4sWLtGvX7tZuJhcnJ6dbes/q1KmDn58fiYmJjBs37qbPr1u3LmvXruX69esWC/jY+3nb4uvrS2BgIB999BGDBw82ly9btgxHR0eeeOIJwHDPnTp1YuXKlcTExJjrX716NdeuXbOa35nb9u3brcpGjhxJdnY2c+bMMc9ZXb58uVUv7LRp0/j+++8tFjoyOXXqFGB4b+819iaDfwGmu24LnNNa/2x87chNbl4vhBBCCCHuTf369cPf359GjRrh6enJoUOHiIuLw8fHhxEjRpjjunfvTnBwMBEREcyYMQMvLy/i4uLQWjNmzBhznKnXZ968efTv3x9HR0ceeeSRAnuo7OHu7s6YMWP4888/eeihh/jkk0/44osvWLx4sbmH77XXXqNp06a0atWKYcOG4efnR2pqKkeOHOHkyZMsXLiwwDri4uIYPnw44eHh9OvXD3d3dxISEnBxcWH48OG0bt2ap59+ml69ejFq1CiaNm1KiRIlSEpK4vPPP2f69OnUrl37pu6tfv36bNy4kU6dOuHl5UWVKlXs6mFUSjFv3jzCwsLIzMykT58+lC9fnvPnz7N37158fX0ZNWpUnue3atWKSZMmcfjwYYs9/ez9vAFq1apF9erV+fLLL81lU6dOpWvXrgwZMoSnn36aQ4cOERsbS2RkpMWG7zExMTRr1ow+ffowdOhQkpKSiIqKolevXjz66KPmONPWGQsXLjQv2tO6dWur+/H09OT69esWx2wtyrN48WKcnZ1tXuPAgQP4+PhQo0aNPN+34sreJO4LIEYpNQwYjaE30KQuIKuNCiGEEEI8ABo0aMD69esZOHAgoaGhzJw5kyeffJIDBw5YDJMrUaIE8fHxdOjQgZdeeomePXvi4ODA9u3bLbYuCAwMJCYmhg0bNtCiRQuaNGlyxxbiKFOmDMuXL2fJkiWEhYWxfft2Zs2aRf/+/c0xvr6+fPfddwQGBhIdHU2HDh148cUX2blzJ23btrWrnmHDhrFq1SrOnj1Lv379CA8PZ/Xq1fj7/7M727Jly4iJiWH16tWEhYXRq1cv5s6dy0MPPWSex3gz5s6dS+nSpenWrRtNmjQxb9Zuj86dO7Nr1y7+/vtvBg8eTGhoKGPGjOH333+3GKZpS8uWLfH29mbDhg0W5fZ+3vDPPL3cbVq9ejX79+8nNDSUd955h+joaKZNm2YR17BhQ7Zu3cpvv/1Gly5diI6O5rnnnmPJkiUWcVprsrOzuXHjht3vy62Kj4+36H2+lyitdcFBSlUClgHNgG+BPlrrP43HvgG+11q/WJgNvZfVqVNHHz9+vKibIUTRWpJAWloanpGtC+Xyd3qPPJM7tWBJYbWvuJv7sWEI0rBnphUQaZ/8Po8dO3bY/IutEHfbUuP38FnjHmrHjh2jXr16d7UNhbma6L1iwIABfPHFFxabtYs7Y/z48axevZr//e9/+a7K+SA4cOCAed/I/Hp3L126xNmzZ/P9b4FS6nutdePCaGde7OoZ1Fqf11p30Fq7a63bmhJBo/ZAZF7nCiGEEEIIIe4fQ4cOJS0tjTVr1hR1U4rctGnT6N+//00P8y0u7J0zaEUpVR+oB+zTWqffuSYJIYQQQgghiisPDw+WLl1qscn7g+jq1as0bNgw3z0mizt7N52fC5TUWr9gfP0khq0kHIB0pVQHrfW3+V1DCCGEEEKIu2Xx4sVF3YT7WqdOnYq6CUXO1dWVSZMmFXUzbou9C8g8AezN8XoyEA8EAt8A9/a7IIQQQgghhBAPGHuTQW8gCUApVRUIAOK01j8Cs4EmhdI6IYQQQgghhBCFwt5k8ArgZvw5BEgHvjO+vgw82MtVCSGEEEIIIcQ9xt4FZA4CQ5VSvwJDgW1aa9OmHf7Ab4XROCGEEEIIIYQQhcPeZPAVYDPwA5AGvJDjWA8M8waFEEIIIYQQQtwj7EoGtdbfKqV8gbrAz7m2kpgP/FwYjRNCCCGEEEIIUTjs3mdQa/038L2N8o13tEVCCCGEEEIIIQqdvQvIoJQKUkp9qpT6Uyl1XSnVyFg+VSklG40IIYQQQjwgtm/fTosWLXB1daVs2bI8++yznD9/3iouNTWVwYMHU758eUqXLk379u358ccfLWISEhKIiYmxuYG5UooJEyYU2n3cy2JiYvjqq6+sygcMGICfn5/5dVJSEkqpO77vYvfu3Rk2bJhFmT2fd37WrVtHUFAQLi4uVK9endjYWLKzs63isrOzmTlzJg0aNMDFxYVy5crRvn17fvut4GVMlFI2HwkJCRZxfn5+NuPWrVtnjrl69Sre3t6sXLnS7nssbuxKBpVSLYB9GIaJfpzrvBtYziEUQgghhBD3qd27d9OxY0c8PT1Zs2YNs2bNYteuXbRr145r166Z47TWdOvWjc2bNzNnzhzWrFlDVlYWbdq04ezZs+a4hIQEJk+ebDMZFHmbPHmyzWTw1VdfZe3atYVa99dff83WrVsZP368uczezzsvW7ZsITw8nCZNmrBp0yYiIyOJjY0lOjraKvbZZ59lypQpDBw4kC1btrBo0SICAwPJyMiwq/0DBgxg3759Fo/atWtbxYWGhlrFhYSEmI+7uroyZswYoqOjycrKsqvu4sbeYaLTgC0YFotxAHL+GeAg8NwdbpcQQgghhCiGJk+eTPXq1Vm3bh0lSxp+laxXrx5NmjThv//9Ly+99BIA69ev5+uvv+arr76iTZs2AAQHB+Pv788bb7zB7Nmzi+we7pRr167h7Oxc1M2wULNmzUKvY9asWXTr1g0fHx9z2e1+3uPGjaNFixbMnz8fgDZt2nD58mViY2N5+eWXqVy5MgDLly9n5cqVHDhwgEcffdR8fvfu3e1uv4+PD82aNSswrnz58gXGDRgwgHHjxrF27Vr69OljdxuKC3uHiTYC/qO11oDOdexPoMIdbZUQQgghhCiW9u/fT4cOHcyJIEDjxo0pV66cRY/U+vXrqVKlijkxAPDw8KBbt2589tlnACxevJiBAwcC8NBDD5mH4iUlJVnUOXv2bPz9/XF3dyckJITExMQC2zlgwACqVq3K3r17adKkCS4uLvj5+TFnzhyr2FOnTtGvXz8qVKiAs7MzDRs2tOpdi4mJQSnFkSNHCA0Nxc3NzeKX/7Vr1/L444/j5uZGmTJlaNq0KevXrzcfv379OnFxcdStWxdnZ2eqVKnC6NGjLXqzTEM633//fSZOnIi3tzeenp5069bNondNKQXA66+/bn7PYmJizPedc5hoXnbu3Em7du1wd3endOnShIaGcuTIkQLPO3fuHNu2beOZZ56xKLfn887LmTNnSEhIICIiwqL82WefJSsri02bNpnL3n33XUJCQiwSwaLk5eVFaGgoCxYsKOqm3BJ7ewYzgFJ5HPMGLt6Z5gghhBBC3P+2jhzJ+VxzlO6k7OxsHBwc8o2p1LAhHWfOvOlrOzg44OTkZFXu7OxskUwkJibSoEEDq7iAgAA+/PBDLl++TJcuXZgwYQKxsbGsWrWKqlWrAuDt7W2OX7ZsGXXq1GHWrFlkZmYSFRVFWFgYP/30k0VCakt6ejpPPfUUY8eOpVatWixfvpwRI0bg7u7OgAEDAEMi8thjj1GxYkXeeecdKlSowIoVKwgPD2fdunVWPU5hYWEMGjSIsWPHUqKEoV9lzpw5jBgxgh49erBkyRLc3Nw4ePCgRVIbERHBhg0bGDt2LM2bN+fYsWO8+uqrJCUlsWbNGos64uLiaN68OQsXLiQlJYXRo0cTERHBjh07ANi3bx/BwcEMGDCAIUOGAJjfO3ts3LiRsLAwunTpwrJlywCYPn06LVu25PDhw1SrVi3Pc7dt20Z2djYtW7a0KLfn83ZzcwMM8/H8/PzM92NK7nOf7+/vT6lSpTh69CgAWVlZHDhwgCFDhjBmzBgWLlzIxYsXadSoEXFxcbRt29Z87o4dO2jTpg2LFi0yf9Ym//nPf5gxYwYODg40a9aMyZMnW90PwIYNGyhVqhTZ2dkEBQUxbtw4evToYRXXqlUrXnnlFTIyMnBxccnzvSuO7E0G9wAjlVI503pTD+EgwHrAshBCCCGEuO/UqVOH/fv3W5SdPn2a3377DUdHR3PZhQsXbPZQlS1bFjAsNlKtWjXzsMaGDRtSq1Ytq3hHR0fi4+Mtrt27d2+++eYbmjdvnm9bL126xPz58+nbty8AnTp1Ijk5mUmTJtG/f39zj5rWmp07d1KuXDnAMFfszJkzTJw40SoZHDFiBJGRkebX6enpREdH07NnTz799FNzeWhoqPnn3bt3s2LFCpYsWcJzzxlmV7Vv356yZcsSERFBQkICDRs2NMf7+fnx8ccfm1//8ccfREVFce7cOapUqWIeumjvcMfcIiMjCQkJseixa9OmDTVq1OCtt95iZj5/JNi/fz/e3t6UL1/eotyez9uUDJYsWdLijxWm+aJeXl5W53t5eZmP//XXX2RmZrJ48WJq1KjBBx98gLOzMzNmzKBTp07s3buXxo0bA4beUwcHB3PCbhIREUHXrl2pUqUKp0+fZsaMGbRt25Zt27bRunVrc1y3bt1o0qQJ/v7+nD9/nrlz59KzZ0+WLl1q1YMZFBREZmYmBw8eLPA7WdzYmwy+CnyNYdP51RgSwf5KqbeBR4EmhdM8IYQQQoj7z630yN2MS5cu4e7uXijXjoyMJCIiggkTJjBixAguXLjA888/T4kSJax+8b4TOnToYJEIPvzwwwD8+uuvBf7i7eDgQHh4uEVZ3759GTx4MMnJyVStWpXNmzfTuXNnPDw8uH79ujkuNDSUqKgo0tPTKVOmjLm8Z8+eFtfbu3cvly9f5vnnn8+zHZs3b8bJyYlevXpZ1NGxY0cAdu3aZZEMdu7c2eL8nPdcpUqVfO+5ID///DO//PIL0dHRFm0pVaoUwcHB7Nq1K9/zz507Z5UI3qwTJ07c0nk3btwADD2En3/+ufm9aNWqFTVq1GDGjBmsWLECgJCQEIv7M1m6dKn555YtWxIWFkaDBg2YMGECe/bsMR/LPZy4Z8+eNGvWjPHjx1slgxUqGGbMnTt37pbuqyjZ9S9Wa/0D0Ao4D7wCKP5ZRCZEa328cJonhBBCCCGKk379+jFhwgTeeustKlWqRP369fHx8aFz584Wwzu9vLxITU21Oj+/XiBbTD1LJqYFW+xZOdLLy8sikQSoVKkSAMnJyQCkpKTw4Ycf4ujoaPGIiooCDL1ROeW8x5zH8xummZKSQmZmJqVLl7aoo2LFijbruJ17LkhKSgoAgwYNsrrn+Ph4q7bklpGRYXOY8O183qZjts5PTU01vx9eXl4opahfv75FUuzm5kZwcDCHDh3Kt+22uLu706VLF7799tt84xwcHOjduzdnz5612sLC1dUVMGw1ca+5mU3nDwLtlFIuQFkgTWt9pdBaJoQQQgghiqUpU6Ywbtw4Tp48ScWKFalUqRL16tWjRYsW5piAgAC2bt1qde7Ro0fx9fU1DxksTKmpqWRlZVkkhKb9EE0rYZYrV46WLVsyduxYm9fI3RNnWrzFxNRLlpycbHPOnKkOFxcXdu/ebVcdhck0FDYuLo727dtbHbeV6OU+/5dffrEqv53POyAgADDMHQwODjaXJyUlceXKFerXrw8Ykq4aNWrkeZ3b6ZnO/bneTKwp4b3dHtOicNPvmNY6Q2t9DnBRSj2qlCpe6+kKIYQQQohCV7p0aR5++GEqVarE5s2b+emnn3jhhX+2nu7evTvJycns3LnTXJaens6GDRss5uGZer0Ko1clOzvbanGW5cuX4+vra04GO3XqxOHDhwkICKBx48ZWj4K2jmjevDlubm7mLRFs6dSpExkZGVy8eNFmHbeSDDo5Od3Se1anTh38/PxITEy02ZZHHnkk3/Pr1q1LcnKy1RBMez9vW3x9fQkMDOSjjz6yKF+2bBmOjo488cQT5rKePXuSmJho7tkFw7Bo06qxNys9PZ34+HiaNm2ab9z169dZsWIFvr6+5m0uTE6dOgUY3tt7jV09g0qpCUBprfV44+tWQDxQGkhWSrXTWv9ceM0UQoii4TduY1E3QQghipVDhw6xadMmGjVqBMCePXuYMWMGY8aMsZjD1717d4KDg4mIiGDGjBl4eXkRFxeH1poxY8aY40y9PvPmzaN///44OjryyCOPFNhDZQ93d3fGjBnDn3/+yUMPPcQnn3zCF198weLFi829O6+99hpNmzalVatWDBs2DD8/P1JTUzly5AgnT55k4cKFBdYRFxfH8OHDCQ8Pp1+/fri7u5OQkICLiwvDhw+ndevWPP300/Tq1YtRo0bRtGlTSpQoQVJSEp9//jnTp0+3uel5furXr8/GjRvp1KkTXl5eVKlSxa6kUinFvHnzCAsLIzMzkz59+lC+fHnOnz/P3r178fX1ZdSoUXme36pVKyZNmsThw4fN3wGw//MGqFWrFtWrV+fLL780l02dOpWuXbsyZMgQnn76aQ4dOkRsbCyRkZEWyde///1vli5dyhNPPMHEiRNxcnLizTff5MqVK4wbN84cZ9o6Y+HCheZFe958802OHz9OmzZtzAvIvPnmm/z+++8Wiegnn3zCZ599RufOnalWrRrnz59n3rx5HDx4kE8++cTqPTlw4AA+Pj759loWV/b2DEYAJ3O8no5hMZkeGOYRTrnD7RJCCCGEEMWQk5MTn3/+OX379qVnz558/vnnvPfee0yfPt0irkSJEsTHx9OhQwdeeuklevbsiYODA9u3b7fYuiAwMJCYmBg2bNhAixYtaNKkyR1biKNMmTIsX76cJUuWEBYWxvbt25k1axb9+/c3x/j6+vLdd98RGBhIdHQ0HTp04MUXX2Tnzp0WWxXkZ9iwYaxatYqzZ8/Sr18/wsPDWb16Nf7+/uaYZcuWERMTw+rVqwkLC6NXr17MnTuXhx56yDyP8WbMnTuX0qVLm1e9zK9nMrfOnTuza9cu/v77bwYPHkxoaChjxozh999/tximaUvLli3x9vZmw4YNFuX2ft5g6GXLzs62atPq1avZv38/oaGhvPPOO0RHRzNt2jSLuEqVKrFr1y6qV6/OwIEDefrpp3FycmLnzp3m4aYAWmuys7PNi86Aoefu6NGjjBgxgg4dOjBq1Cj8/f3Zs2ePxdYS/v7+pKSkEBUVRceOHXnhhRdwdnZm8+bN5pVpc4qPj7dZfi9Qhn3kCwhS6hLQTWu9QylVAfgdaGd8HQ7M1lr7FHJb71l16tTRx4/LGjviAbckgbS0NDwjWxfK5aUHr3ia+7Hhr7TDnplWQKR9kqZ1yfPYjh07LJYFF6KoLDV+D5817qF27Ngx6tWrd1fbUJirid4rBgwYwBdffGGxWbu4M8aPH8/q1av53//+d1Nz7e5HBw4cMO8bmV/v7qVLlzh79my+/y1QSn2vtW5cGO3Mi70LyGQDpr76Vhg2of/a+PoPDAvKCCGEEIUqv6R/9MPXGXCTfxTIL7kUQghh29ChQ1mwYAFr1qyhV69eRd2cIjVt2jT69+9/08N8iwt7h4kmAhFKKTfg/4CdWuss47FqQEphNE4IIYQQQghRvHh4eLB06VIyMzOLuilF6urVqzRs2JDXX3+9qJtyy+ztGXwN+AzoB2QBoTmOdQYO3uF2CSGEEEIIccsWL15c1E24r3Xq1Kmom1DkXF1dmTRpUlE347bYlQxqrbcopeoBjYAErXXOzUV2YVhMRgghhBBCCCHEPeJmNp0/BZyyUf7+HW2REEIIIcR9Rmv9wC+0IcSDzJ5FO4vCTW86L4QQQggh7Ofo6FgoG6oLIe4dmZmZODo6FnUzrEgyKIQQQghRiCpWrEhycjJXrlwptr0DQojCobXmypUrJCcnU7FixaJujhW7h4kKIYQQQoibV6ZMGQDOnTtHVlZWAdF3RkZGBi4uLnelLvHgke/XzXF0dCQ9Pd3834LiRJJBIYQQQohCVqZMmbv6i+COHTsICgq6a/WJB4t8v27e2bNni7oJNtk1TOHgZOAAACAASURBVFQp1cq4x6CtY25KqVZ2XqeXUmqNUuq0UuqqUuq4UipOKeWeI8ZPKaXzeHjaUUcJpdR4pVSSUipDKfWDUio8j9h/KaV+UkpdM7blhTzieiilDhmvd1opNUEp5WDPPQshhBBCCCFEcWTvnMHtQP08jtUxHrfHv4FsIBroBPwHeBHYppTK3ZY4IDjX45IddUwBYoC5wBPAfmCVUqpzziCl1L+A94E1xrasAt5VSr2YKy7UGPOt8XqzgAnAVHtuWAghhBBCCCGKI3uHiea3FrIzhgTPHt201n/keL1TKXUBWAK0Br7Kceyk1nq/ndc1NFKpihgSzmla6zeNxduVUrWAacDnxriSwOvAUq31KzniqgBTlFILtNamQf3TgD1a6+dzxLkBE5RS72itf7+ZNgohhBBCCCFEcZBnz6BxuGZbpVRbY1Fj0+scjy7AaOBXeyrLlQiafGt89rmpltsWCjgBy3KVLwMeVkr5G18HAxVsxC0FygEtAJRS1YCGecQ5YugpFEIIIYQQQoh7Tn49g/2BSYA2PuZg2UOoja+vA0Nvow0hxuf/Z+/ewyQpq8OPfw+3BRYU0BV/cnFBIgZcxUQMJEQWNCKiiBHxgpEVhWjEaFyNICh3XKIS0YguIoLgjVtUBFQIzCIKKkERUECEBUFAYFlkuewFzu+PqglN0z3zzk5Xz+37eZ56evqtU1Wne6q650xVve9v29o/GRFfAh4CFgAHZ+Y1w6xra2ApcFNb+3X141bALXUcwLVDxF3SLS4zb4mIh+l+6awkSZIkjWtDFYOnAANUBd/FVAXfb9pilgI3Zuaildl4RGwEHAFclJlXtqxzPvAj4B7gBVT3GP40Il6Wme1FY6sNgMX51EF8FrXMb328fyXjBts26NAOQETsD+wPMGPGDAYGBoZIW5r8tlkMy5Y/xue//t1G1j93ViOr1ShtMr36OJ47a0Xj29pwrZFvx89mNWHx4sXA2O5fS5Yscf9WY9y/Rm68vmddi8HMvBW4FSAidgKuysySDlyK1PfdfZfqzOI7W7Z7J9Daq+ePI+IHVGftDgbe3qscmpSZJwInAmy55ZY5e/bssU1IGmu3/orb776Pz1zjiDZTyWYPVReU9OP3PnfWihFvZ+Hes5tJRlPaH9arOj8fy+/+gYGBMd2+Jjf3r5Ebr+9ZUW+imbmgx4XgWsC5wObALpk55MAbmfkH4DJg22FWfT+wXkS0d3gzeAZvUUscwPorGTfYtlJnRCVJkiRprHX9F2pE3Ay8ITOvjohbqO4R7CYz83klG4yI1YGzgJcC/1BwH+CTtjPM/Ouoejd9Hk++b3Dw3r7ftMRBdU/gnYVxlw8GRcRMYG2eetmsJEmSJE0IQ11PswD4c8vPwxViw6rHEvw6sDPw2tKhIyJiU6oePr8zTOgPgOXA3sDhLe1vB67NzFvq55cD99ZxF7XFLQJ+ApCZt0XE1XXcSW1xy4ELSvKXJEmSpPFmqHsGW+/jm9Oj7X0BeBPVGH8PRcR2LfNuz8zbI+IzVJevXk7VgcyWwEHA4/Vy/yciFgILM3N2neefIuI44KCIeBC4CngzVfG5e8vrWR4RH6caZP4OqoJwZ2Bf4P2ZuaxlMx8Dvh8R84FvAi+hGnT+eMcYlCRJkjRR9bsnh8Fx+Q6up1aHA4dRXZr5XmAOsA5wH1Vvpodn5g1ty0wH2guyg4ElwAeAZwM3AHtl5vdbgzLzSxGRVOMkfoRqrMQDMvOEtrjzI2JPqmE25gB3A8fQVphKkiRJ0kQy1D2D7xjJijLzawUxMwtiTgZOHi4uIp4PPBM4rm35x4Cj6mm4bc2nGsZiuLhzgHOGi5MkSZKkiWK4cQZbDd4z2D7w/KBhi8Ee2xG4MDN/3uftSpIkSdKEN1QxuFnLzxsD3wDOA75FdankhsBbqS79fGtTCXaTmV8Gvtzv7UqSJEnSZDDcoPMARMTxwLcy86MtITcAl0bEfwD/DryhsSwlSZIkST1VNOg88Argwi7zflTPlyRJkiRNEKXF4FKqQeI72RZY1mWeJEmSJGkcKh1a4gzgsIh4DDiTJ+4Z3ItqyIWvNJOeJEmSJKkJpcXgXGBd4JPAvJb2pOpYZm6P85IkSZIkNaioGMzMR4B/iogjge2oBnO/E/hZZt7YYH6SJEmSpAaUnhkEoC78LP4kSZIkaYIr7UCGiJgeEf8aEWdFxMUR8Rd1+1si4gXNpShJkiRJ6rWiM4MRsQkwQDX4/PXAC6nuIQTYCXgl8O4G8pMkSZIkNaD0zOBnqIaXeD7w10C0zFsA/H2P85IkSZIkNaj0nsF/APbPzFsjYtW2eXcAG/U2LUmSJElSk0rPDK4BPNhl3tOBFb1JR5IkSZLUD6XF4K+BN3aZtyvwv71JR5IkSZLUD6WXiX4KOCsioBpkHmCriHg98C5g9wZykyRJkiQ1pHTQ+XMi4l+AecC+dfPXqC4dPSAzf9BQfpIkSZKkBhQPOp+ZX4qI04DtgWcB9wE/zcxu9xJKkiRJksap4mIQIDMfAi5qKBdJkvpq5oHn9XR9C+ft1tP1SZLUpNIOZCRJkiRJk4jFoCRJkiRNQRaDkiRJkjQFWQxKkiRJ0hRkMShJkiRJU1DX3kQjYtORrCgzbxt9OpIkSZKkfhhqaImFQI5gXauOLhVJkiRJUr8MVQzuyxPF4DTgEODPwBnA3cCzgb2AdYEjG8xRkiRJktRjXYvBzDxl8OeI+CxwFfCGzMyW9iOA7wBbNZijJEmSJKnHSjuQeSswv7UQBKiffwl4W68TkyRJkiQ1p7QYXAeY0WXes4DpvUlHkiRJktQPQ90z2GoAOCYifpuZvxhsjIiXAUfX8yVJmtJmHnheT9e3cN5uPV2fJEmtSs8MHgAsBa6IiIUR8bOIWAhcDjxaz5ckSZIkTRBFZwYz85aIeAEwB9gO+H/AtVTF4KmZubyxDCVJkiRJPVd6mSh1wfflepIkSZIkTWDFxSBARLwIeDnwDKreRe+KiC2AuzPzwSYSlCRJkiT1XlExGBHTgNOBfwSCajD6c4G7gP8AbgQObChHSZIkSVKPlXYgczTwSuCfgA2pCsJBFwC79DgvSZIkSVKDSi8TfStwSGZ+IyJWbZt3CzCzp1lJkiRJkhpVembwGcBvh1jHtN6kI0mSJEnqh9Ji8BZg+y7zXgbc0Jt0JEmSJEn9UFoMfg04MCL2Blav2zIidgL+DTi5ieQkSZIkSc0oLQb/AzgPOA24v267DLgI+EFmfr6B3CRJkiRJDSnqQCYzHwPeEhFfoOo59FnAfVSF4IIG85MkSZIkNaB0nMFNgTsz88fAj9vmrQY8JzNvayA/SZIkSVIDRtKBzEu6zHtxPV+SJEmSNEGUFoMxxLzVgceLVhKxZ0ScHRG3RsQjEXFDRHwyItZti1s/Ik6KiHsj4qGIuCgiZhVuY5WIOCgiFkbEoxFxdUS8sUvsfhFxfUQsrXN5T5e4PSLil/X6bo2IQzqMtyhJkiRJE0bXYjAi1ouIzSNi87ppo8HnLdPWwD7AXYXb+zDwGPAx4NXAF4H3AhdGxCr1dgM4t57/fuCNVAXnJRGxccE2jgQOA/4L2BW4AjgzIl7T9vr2A+YDZ9fbOhM4ISLe2xa3Sx3zi3p9xwOHAMcUvmZJkiRJGneGumfwA8ChQNbTWV3ioo4r8brMvKfl+YKIWAScCswGLgZ2B/4O2DkzLwGIiMupLkX9d+Bfu608Ip5FVXDOy8xP182XRMQWwDzg/DpuNeBo4LTMPLgl7jnAkRFxUmYur9vnAZdl5v4tcesAh0TEf2ZmaSEsSZIkSePGUMXgd4CFVMXeycBRwO/bYpYCv8nMX5dsrK0QHPSL+nGj+nF34I+DhWC93AMRcS7weoYoBql6Ol0DOL2t/XTg5IjYLDNvAbYHZnSIOw14J7ADVdG3CbANsH+HuMOpzhR+dYh8JEmSJGlc6loMZubVwNUAEZHAeZl5bwM57Fg//rZ+3Bq4tkPcdcA7ImKdzFzSZV1bUxWoN3VYFmArqjOMW9fP27fTGndJt7jMvCUiHq7jJEmSJGnCKR1n8FSAiHgmsB3wDODczFwUEWsCyzKzqBOZVhGxEXAEcFFmXlk3b0B1RrLdovpxfaBbMbgBsDgzs8uyG7Q93r+ScYNtG3RoByAi9qc+ozhjxgwGBga6hUpTwjaLYY1VYO6sFWOdivpok+nVx3E/fu8brjX59i+/OyamxYsXA2P7+1uyZIn7jxrj/jVy4/U9KyoGASLiU1QduqxBdQ/htlTF03eBy6g6bilW33f3XWAF1aWZk0pmngicCLDlllvm7NmzxzYhaazd+ituv/s+PnNN8ceOJoHNHqo6o+7H733urBWTbv9auPfssU5BK+EP660HwFh+9w8MDIzp9jW5uX+N3Hh9z4qGloiIjwEHUJ3F+xuePNTEucBrR7LRiFirXm5zYJfMvL1l9v1UZ//aDXWWrnXZ9eoeSTstu6gljg7bKY0bbFvUoV2SJEmSxr3ScQbfDRyRmccAV7XNuwl4XukGI2J1qp5JXwq8JjOvaQu5jifu1Wu1FXDbEPcLDi47rUM+g/f2/aYljg7bKYqLiJnA2i1xkiRJkjShlBaDG1GN19fJMmB6yUrqsQS/DuwM7JGZndb5PaoxDXdsWe5pwOvqeUP5AbAc2Lut/e3AtXVPogCXA/d2iVsE/AQgM2+j6kSnU9xy4IJh8pEkSZKkcan05oo7gBdS9bDZ7sVUPXSW+ALwJqox/h6KiO1a5t1eXy76Papi7fSI+AjVpZoHUV2a+h+tK4uIhcDCzJwNkJl/iojjgIMi4kGqs5hvpio+dx9cLjOXR8THqQaZvwO4qI7ZF3h/Zi5r2czHgO9HxHzgm8BLqAadP94xBiVJkiRNVKXF4JnAJyLiKp44Q5gR8XxgLnVHKQV2rR8PrqdWhwOHZebjEfFa4NPACcCaVMXhTpn5h7ZlpgPtBdnBVL2NfgB4NnADsFdmfr81KDO/VA+ZMRf4CHAbcEBmntAWd35E7AkcCswB7gaOoSpoJUmSJGlCKi0GDwP+FrgUuLVuOxPYBPgpMK9kJZk5szBuEdVZun27xdSF6DOB49qWfQw4qp6G2858YH5B3DnAOcPFSZIkSdJEUTrO4CMRMRt4G7ALVacx91ENJ/H1zByLgZ12BC7MzJ+PwbYlSZIkaUIrHpCpPuN2Wj2Nucz8MvDlsc5DkiRJkiaiyTU6ryRJk8jMA8/r6foWztutp+uTJE1sXYvBiLgFyML1ZGYWjzUoSZIkSRpbQ50ZXEB5MShJkiRJmkC6FoOZOaePeUiSJEmS+miVsU5AkiRJktR/xcVgRPxFRJwaETdGxEP14ykRsUWTCUqSJEmSeq+oN9F6jMHzgUeA84C7gQ2B1wFvjohXZ+aCppKUJEmSJPVW6dASnwF+CeySmUsGGyNiXeBH9fyX9j49SZIkSVITSi8T3Qo4trUQBMjMB4Fjga17nZgkSZIkqTmlxeDtwBpd5q0B3NGbdCRJkiRJ/VBaDB4LHB4Rz2ltjIiNgEOBY3qdmCRJkiSpOaX3DO4IPA24OSKu4IkOZLarf55ddzIDkJm5T68TlSRJkiT1TmkxuAOwArgTeG49UT8H+PuW2OxNapIkSZKkphQVg5m5WdOJSJIkSZL6p3jQeUmSJEnS5FF6mSgAEbEJsAmwZvu8zLy4V0lJkiRJkppVVAxGxObA14GXDTbVj1n/nMCqPc9OkiRJktSI0jODJwGbAh8ErgeWNZaRJEmSJKlxpcXgtsCczDy7yWQkSZIkSf1R2oHM7Xg2UJIkSZImjdJi8BjgoxExvclkJEmSJEn9UTrO4GkR8QJgYURcAdz/1JDcp+fZSZIkSZIaUdqb6BzgIOAx4K946iWj2du0JEmSJElNKu1A5nDgv4F3ZebiBvORJEmSJPVB6T2DzwBOsBCUJEmSpMmhtBi8DPjLJhORJEmSJPVP6WWiHwDOiIj7gR/w1A5kyMzHe5mYJEmSJKk5pcXgb+vHr3WZnyNYlyRJkiRpjJUWcEdgj6GSJE1oMw88r+frXDhvt56vU5LUH6XjDB7WcB6SJEmSpD4q7UDm/0TEOhGxSUSs00RCkiRJkqTmFReDEbFLRFwJLAYWAosj4ucR8Q9NJSdJkiRJakbRZaIRsQtwHnATcCRwF/D/gDcD50fEazLzwsaylCRJkiT1VGkHMocBPwJe2zqEREQcAXwfOBywGJQkSZKkCaL0MtEXA19oH0uwfn4CsE2vE5MkSZIkNae0GFwKPK3LvHXr+ZIkSZKkCaK0GBwAjoyIzVobI2JTqktIL+ltWpIkSZKkJpXeM/hR4CfADRFxBXAn8GxgO6reRT/aTHqSJEmSpCYUnRnMzBuBFwGfA6YBfwWsCRwPbJOZv2ssQ0mSJElSz5WeGSQz7wQ+3GAuksahmQee15P1fGvaWmw8vSerkiRJUg8UnRmMiOdHxI5d5r08Iv6it2lJkiRJkppU2oHMZ4HXdZn3WuA/e5OOJEmSJKkfSovBlwKXdpl3KbBtb9KRJEmSJPVDaTG4LvBol3nLgaf3Jh1JkiRJUj+UFoM3A6/oMm9nYGHpBiNi44j4fERcHhEPR0RGxMwOcdll2qZwO/tFxPURsTQiboiI93SJ2yMifhkRj0bErRFxSESs2iFuh4j4aUQ8EhF3RcRxEbFW6euWJEmSpPGktBj8GvBvEfG+iJgGEBHTIuJ9wAeBU0ewzS2AvYD7gR8PE3sKsH3bdONwG4iI/YD5wNnAq4EzgRMi4r1tcbvUMb8AdqUaKuMQ4Ji2uBcBFwJ/orpH8hDgnXV+kiRJkjThlA4t8Wmq+wI/DxwfEYuADaiKybOBY0ewzUszc0OAiHg38KohYu/IzCtGsG4iYjXgaOC0zDy4br4kIp4DHBkRJ2Xm8rp9HnBZZu7fErcOcEhE/Gdm3lW3Hw7cDrxpcNmIWAacGhHHZuZVI8lRkiRJksZa6aDzj2XmnsArgU8B3wH+A9g5M9+UmY+XbnAksStpe2AGcHpb+2nAM4AdACJiE2CbLnGrU50pJCJWpzq7eEZLEQlwBrAMeH2P85ckSZKkxhUPOg+QmRcDFzeUSyfvjYiPAI8BVwCHZuZwl5ZuXT9e29Z+Xf24FXBJt7jMvCUiHq7jAJ4HrNkh7tGI+H1LnCRJkiRNGCMqBvvsdOD7wB+B5wIfAS6OiH/IzIEhltugfry/rX1R2/xucYNtJXGLWuY/SUTsD+wPMGPGDAYGhkpZGr/mzlrRk/VsfEeyxiq9W58mhk2mJ9Cf3/uGa7l/jQW/355q8eLFwNi+N0uWLPF3o8a4f43ceH3Pxm0xmJn/1PL0xxHxXaqzc0dRX+o5nmXmicCJAFtuuWXOnj17bBOSVtKcA8/ryXq2nRZsPD35zDXj9mNHDdjsoQDoy+997qwV7l9jYOHes8c6hXHnD+utB8BYfvcPDAyM6fY1ubl/jdx4fc9KexMdc5n5IHAeww9wP3gGb/229sEzeIuGiRtsK4nboCVOkiRJkiaMCVMMtshh5g/eG7h1W/vgvX2/GSquHvNw7Za43wNLO8StCWzeEidJkiRJE8aEuZ4mIp5GNcbfz4cJvRy4F9gbuKil/e1UZ/F+ApCZt0XE1XXcSW1xy4EL6rhlEfEDYK+IOCwzB29I2ROYBnxvNK9LkqSJbGaPLiUftHDebj1dnySpuzEpBiNiz/rHv64fd42Ie4B7MnNBRHwY2JKq18/BDmQ+DDybqnhrXdcAMDMzZwJk5vKI+DjVIPN3UBWEOwP7Au/PzGUti38M+H5EzAe+CbyEakD541vGGAQ4jKo30zMi4gvATKohNs7KzP8d3bshSZIkSf036mIwIi4G7gSOG0FhdGbb8xPqxwXAbOAG4A319HTgz1Rn9N6Vme1nBqcDrYUbmfmliEhgLlUvpLcBB2TmCW1x59eF6aHAHOBu4BiqQetb434VEa8CjqW6b/EB4GtUxaQkSZIkTTi9ODO4OfBC4K0R8aPMfPVwC2RmDDP/XODc4dYTEdOpBo7fu31eZs4H5hfkcg5wTkHcpVQD2kuSJEnShDfqYnDw8syIeD7w8tGub4T+FrgJOKvP25UkSZKkCa1n9wxm5o3Ajb1aX+E2LwT+sp/blCRJkqTJYCIOLSFJkiRJGqWuZwbrjmFKZWa+ogf5SJIkSZL6YKjLRFfhyQO8b0k1tMNCql43N6QaYuFOqt4/JUmSJEkTRNdiMDNnD/4cEXsAxwPbZ+bPWtr/Bvh2PU+SJEmSNEGU3jN4JPDx1kIQoH5+GHBUj/OSJEmSJDWotBj8C+CeLvP+BGzRm3QkSZIkSf1QWgzeAvxzl3n/THUfoSRJkiRpgigdZ/Bw4OsRcS3VAO+DHcjsCbwA2LuZ9CRJkiRJTSgqBjPzWxFxL1VReBCwOrAc+AWwS2b+T3MpSpIkSZJ6rfTMIJl5EXBRRKwCPBO4NzMfbywzSZIkSVJjSu8ZbLU2sBawao9zkSRJkiT1SXExGBGvjYirgAeAm4FZdftJEfG2hvKTJEmSJDWgqBisB53/LnAv8FEgWmbfAuzT+9QkSZIkSU0pPTN4KPDVzHwV8Nm2edcCL+xpVpIkSZKkRpUWg38JfLv+Odvm3Q88o2cZSZIkSZIaV1oM/pmqB9FOZgL39CQbSZIkSVJflA4tcSFwUERcADxYt2VETAMOAC5oIjlJkjS1zDzwvJ6ub+G83Xq6PkmaTEqLwYOBnwM3AOdTXSp6IPAi4OnAHo1kJ0mSJElqRFExmJkLI+KvgMOBXYDHgJcDPwA+kZl/bC5FSUPp9X/RJUmSNDWUnhkkM28H3tVgLpIkSZKkPikedF6SJEmSNHl0PTMYESePYD2ZmZ41lCRJkqQJYqjLRHfmqWMKdlMaJ0mSJEkaB7oWg5k5s495SJIkSZL6yHsGJUmSJGkKKu5NNCJWBd4BbA9sBNwB/BQ4LTMfayY9SZIkSVITis4MRsRzgeuArwCvBp5VP54MXFvPlyRJkiRNEKWXif4X8DRgh8zcNDO3zcxNgb8Hng58vqkEJUmSJEm9V1oM7gwclJk/bW3MzJ8AH6vnS5IkSZImiNJicAnwpy7z/gQ83Jt0JEmSJEn9UFoMng68p8u8fwa+1pt0JEmSJEn9UNqb6E3AmyLiGuBs4G5gQ2BPYF3ggojYdzA4M0/udaKSJEmSpN4pLQa/UD9uDGzdYf4JLT8nVS+jkiRJkqRxqrQY3KzRLCRJkiRJfVVUDGbmrU0nIkmSJEnqn9Izg08SEU/peCYzHx99OpIkSb0z88Dzerq+hfN26+n6JGksFfUmGhFrRcS8iPh9RCwFlrdNyxrMUZIkSZLUY6VnBk8A9gbOBb6FxZ8kSZIkTWilxeDuwIcz83NNJiNJkiRJ6o/SQeeXAr9tMhFJkiRJUv+UFoOnAG9pMA9JkiRJUh+VXib6ceCLEfEj4IfA/e0BmelA85IkSZI0QZQWg39Ndd/gs4BXdpifgMWgJEmSJE0QpZeJfgm4D3g9sCWwWdu0eekGI2LjiPh8RFweEQ9HREbEzA5xa0bEpyLizoh4pI5/+Qi2s19EXB8RSyPihoh4T5e4PSLilxHxaETcGhGHRMSqHeJ2iIif1rncFRHHRcRapflIkiRJ0nhSembwBcCemXl+D7a5BbAX8L/Aj4FXdYn7CrAb8BHgZuB9wA8jYvvM/NVQG4iI/YD5wCeBi4BXACdERGTmF1vidgHOrrf1IeAlwDHAusBHW+JeBFxIdYnsa6kK4E8BGwFvHsFrlyRJkqRxobQYvAGY3qNtXpqZGwJExLvpUAxGxIuBtwH7ZuZX67YFwHXAEVSXrHYUEasBRwOnZebBdfMlEfEc4MiIOCkzl9ft84DLMnP/lrh1gEMi4j8z8666/XDgduBNg8tGxDLg1Ig4NjOvWrm3QpIkSZLGRullogdSFUjPHe0GM/PxgrDdgeXAt1uWW0E14P0uETFtiGW3B2YAp7e1nwY8A9gBICI2AbbpErc6sGsdtzrwauCMliIS4AxgGdWls5IkSZI0oZSeGTyEqvOYGyPiRp7am2hm5o49zGtr4JbMfLit/TpgDapLTa8bYlmAazssC7AVcEm3uMy8JSIeruMAnges2SHu0Yj4fUucJEmSJE0YpcXgY8D1TSbSZgM6DF8BLGqZP9SydFi+fdlucYNtJXGLuuUSEfsD+wPMmDGDgYGBIVKWVt7cWSvGOoUiG9+RrLHKxMlXvbHJ9AT683vfcC33LzWv5Pt88eLFxbFNWbJkiX97qDHuXyM3Xt+zomIwM2c3nMekk5knAicCbLnlljl79uyxTUiT1pwDzxvrFIpsOy3YeHrymWtK/welyWCzhwKgL7/3ubNWuH+pcQv3nj1szB/WWw+AsfzuHxgYGNPta3Jz/xq58fqeld4z2G/3A+t3aB88C7eow7zWZemwfPuy3eIG20riNhgmF0mSJEkal0b0L9SIWB/4C6p76J4kMy/tVVJU9/e9ISLWbrtvcCuqTltuGmZZqO4JvLNtWYDfdIi7fDCoHvNw7Za43wNLeeIew8G4NanGVzxz2FcjSZIkSeNM0ZnBegD4bwD3UBVOl3SYeulcqh4939SSw2pUY/r9KDOXDrHs5cC9wN5t7W+nOov3E4DMvA24ukvccuCCOm4Z8ANgrzqHQXsC04DvjeSFSZIkSdJ4UHpm8OPAbGAfqqEX3gc8CswB/h/wgZFsNCL2rH/86/px14i4B7gnMxdk5i8j4tvAZ+uhHW4B3ks12PvebesaAGZm5kyAzFweER+nGmT+DqpB53cG9gXeXxd3gz4GfD8i5gPfpBp0/hDg+JYxBgEOA64AzoiILwAzqQadPysz/3ckr12SJEmSxoPSYvCNVIO9f4uqGPxZPdD6VyPiTKpx+C4YwXbbL608oX5cQFV0AryTavD4o4D1qM7ivbrDAO/TgdbCZqAOIwAAIABJREFUjcz8UkQkMBf4CHAbcEBmntAWd35dmB5KVdjeDRxTb7c17lcR8SrgWOA84AHga1TFpCRJmiJmFnTatdvN9wHw8YLYhfN2G3VOkrSySovBTYHrMvOxiFhOVYANOhn4KiM4O5iZURDzCPCheuooIqZTDRzffqknmTkfmF+wnXOAcwriLqUa0F6SJEmSJrzS3kTvA9apf/4D8OKWec8E1uplUiPwt1SdyZw1RtuXJEmSpAmp9MzgFVT3010AnA0cGRHrAiuoLsW8rJn0hpaZFwJ/ORbbliRJkqSJrLQYPJbqUlGo7uHbguoewlWpCsX39j41SZIkSVJTiorBzLwSuLL++UHgjRExDZiWmX9uMD9JkiRJUgNK7xl8inqsv9V7mIskSZIkqU9KB53fLyI+0vJ8VkTcDvwpIq6MiGc3lqEkSZIkqedKzwy+H3ik5flxwGLgg8DTqe4flCRJkiRNEKUdyDwXuB4gIp4O7AjsUQ/afh/wyYbykyRJkiQ1oPTM4CrA4/XPOwAJDNTP/wA8q7dpSZIkSZKaVFoM/g7Yrf75LcBPM/Ph+vlzgEW9TkySJEmS1JzSy0Q/DZwWEfsA6wNvapm3E/DrXicmSZIkSWpO6TiD34iI24C/AX6RmZe2zL4b+F4TyUmSJEmSmlF6ZpDMvAy4rEP7oT3NSJIkSZLUuJUedF6SJEmSNHFZDEqSJEnSFGQxKEmSJElTkMWgJEmSJE1BXTuQiYirgH/KzOsi4hPASZn5x/6lJkmSNLnNPPC8nq5v4bzdhg+SpNpQZwZnAevUPx8KbNx8OpIkSZKkfhhqaIk/AntExN1AAM+OiE27BWfmbb1OTpIkSZLUjKGKwfnAUcC/Awn89zDrWrVXSUmSJEmSmtW1GMzMYyLiQmAr4KvAJ4Gb+5WYJEmSJKk5Q50ZJDN/AfwiIuYAp2Xm9X3JSpIkSZLUqCGLwUGZuVPTiUiSJEmS+qd4nMGImBURZ0XEPRGxon48IyJmNZmgJEmSJKn3is4MRsS2wALgEeB7wF3As4HXAbtFxMsz838by1KSJEmS1FNFxSBV5zHXAq/IzAcHGyNiXeCiev6rep+eJEmSJKkJpZeJbgd8srUQBKifHwts3+vEJEmSJEnNKS0Gc5TzJUmSJEnjSGkx+DPgY/Vlof8nIqYDHwWu6HVikiRJkqTmlN4z+DFgALg1Ir4P3EnVgcxrgLWB2U0kJ0mSJElqRuk4gz+PiO2ATwC7ABsAi4BLgCMz85rmUpQkSZIk9VrpmUEy89fAng3mIkmSJEnqk+JiUJIkSePbzAPPA2DurBXMqX8ejYXzdhv1OiSNX6UdyEiSJEmSJhGLQUmSJEmagiwGJUmSJGkKshiUJEmSpClo2GIwItaIiEURsXs/EpIkSZIkNW/YYjAzlwErgEebT0eSJEmS1A+ll4l+B8cYlCRJkqRJo3ScwQuAz0XEWVSF4Z1AtgZk5sU9zk2SJEmS1JDSYvDs+vEf62lQAlE/rtrDvCRJkiRJDSotBndqNAtJkiRJUl8VFYOZuaDpRCRJkiRJ/TOicQYj4pkR8dqI2CciNqjb1oyIno9XGBGzIyI7TIsLll0zIj4VEXdGxCMRcXlEvLxD3CoRcVBELIyIRyPi6oh4Y5d17hcR10fE0oi4ISLe04vXKUmSJEljoaiIi8qngNuB7wEnAzPr2d8FDm4ku8q/Atu3TK8sWOYrwH7AJ4DXUnV488OI2KYt7kjgMOC/gF2BK4AzI+I1rUERsR8wn+reyVcDZwInRMR7V+4lSZIkSdLYKr1n8CDgAOAI4ELgZy3zzgX+iaqwasJvM/OK0uCIeDHwNmDfzPxq3bYAuI4q/93rtmcBHwbmZean68UviYgtgHnA+XXcasDRwGmZeXBL3HOAIyPipMxcPtoXKUmSNN7MPPC8nq5v4bzdero+SaNTennnu4EjMvMY4Kq2eTcBz+tpVqOzO7Ac+PZgQ2auAL4F7BIR0+rmXYA1gNPblj8dmBURm9XPtwdmdIg7DXgGsENPs5ckSZKkPigtBjeiuoSyk2XA9N6k09HXI+KxiLgvIr4REZsOE781cEtmPtzWfh1V8bdFS9xSqmK2PQ5gq5Y4gGuHiZMkSZKkCaP0MtE7gBcCl3SY92Lglp5l9IQHgM8AC4A/Ay8BPgZcHhEvycw/dVluA+D+Du2LWuYPPi7OzCyIo8M62+OeJCL2B/YHmDFjBgMDA13SlUZn7qwVY51CkY3vSNZYZeLkq97YZHr1EduP3/uGa7l/aXx4qI/7fTfj9Xjw76HJYcmSJf4uR2i8vmelxeCZwCci4iqeOEOYEfF8YC5wYq8Ty8xfAr9saVoQEZcCP6fqVOaQXm+zlzLzROr3Zcstt8zZs2ePbUKatOb0+H6Opmw7Ldh4evKZa0o/djQZbPZQAPTl9z531gr3L40Lu9X7/XljuD+O1+Nh4d6zxzoF9cDAwAD+bTsy4/U9K71M9DDgeuBS4Hd125nANfXzeT3PrIPMvAq4Edh2iLD7gfU7tA+ewVvUErdeRERBHB3W2R4nSZIkSRNG6aDzj0TEbKpeOnehus/uPqoeRL9ed9DST+2Xdra6DnhDRKzddt/gVlT3N97UEjeNqvObm9riAH7TEgfVvYN3DhEnrbRe99YmSZIkDad4sPjMfCwzT8vMt2fmqzLzrZl5aj8LwYh4KbAl1aWi3ZwLrA68qWW51YA3Az/KzKV18w+oeh3du235twPXZubgfZCXA/d2iVsE/GTkr0SSJEmSxtaILiavx+B7GVXvorcDP8/M3zeRWER8napjmquAxVQdyBxE1ZnN51riEjg1M+dAda9hRHwb+GxErF6v473AZrQUdJn5p4g4DjgoIh6st/NmYGfqsQjruOUR8XGqQebvAC6qY/YF3p+Zy5p4/ZIkSZLUpKJiMCLWBE6gGlx+1ZZZj0XEqcD7Ws649cq1wFuB9wNrA3cB5wCHZua9dV6DQ1rc1bbsO6kGij8KWA+4Gnh1fc9hq4OBJcAHgGcDNwB7Zeb3W4My80t10TkX+AhwG3BAZp7Qg9cpSZIkSX1Xembw01Rn1Q6lGrz9bmBDqmLtE8DDVD189kxmfhL45DBhf0d1H+B/tS37CPChehpqG49RFYxHFeQzH5g/XJwkSZIkTQSlxeBbgMMz85iWtpuBo+vOOP+NHheDhXakukT09jHYtiRJkkag1x2mLZy3W0/XJ001pcXgNLp32vIzYI3epDMymXnwWGxXkiRJkia60mLwIuBV9WO7VwEX9ywjaYJwOAhJkiRNZF2LwYjYvOXpccBpdYctZ/LEPYN7Aa+hGmZBkiRJkjRBDHVm8CaePLh7UA3R8J62NoAFPLmXUUmSJEnSODZUMfjOvmUhSZIkSeqrrsVgZp7az0SkXvJ+PkmSJGloq4x1ApIkSZKk/ivtTZSIeDXwJmATYM222ZmZO/YyMUmSJElSc4qKwYj4d2AecA9VxzLLmkxKkiRJGo6D2EujU3pm8ABgPnBAZj7WYD6SJEmSpD4ovWfwacCZFoKSJEmSNDmUFoM/BLZrMhFJkiRJUv+M5DLR/46IBH4E3N8ekJk39zIxSZIkSVJzSovBBB4EjgaO6hKzak8ykiRJkiQ1rrQYPAX4W+A/geuxN1FJkiRJmtBKi8GdgPdl5ikN5iJJkiRJ6pPSYvAe4O4mE5EkSZLGkuMWaqop7U30c8C/RERpvCRJkiRpHCs9M7g+8ELgNxFxIU/tTTQz89CeZiZJkiRJakxpMXhwy8/P7zA/AYtBSZIkSZogiorBzPTyUEmSJEmaRCzyJEmSJGkKKr1MVJIkSdII2DupxruiYjAiHqe6L7CrzFy1JxlJkiRJkhpXembwCJ5aDD4DeBUwDTilhzlJkiRJkhpW2oHMYZ3aI2JV4FzggR7mJEmSJElq2Kg6kMnMx4ATgA/2Jh1JkiRJUj/0ogOZacAGPViPJoFe3ygtSZIkqRmlHchs2qF5DeCFwDzgyl4mJUmSJElqVumZwYV07k00gN8D7+tVQpIkSZKeyqEq1GulxeC+PLUYfBS4FfhFfe+gJEmSJGmCKO1N9JSG85AkSZIk9dGoehOVJEmSJE1Mxb2JRsQ+wFuBTYE122ZnZj6vl4lJkiRJkppT2pvox4HDgWuBXwFLm0xKkiRJUrNWtkOaubNWMKfDsnZIM/GUnhl8F3B8Zv5bk8lIkiRJkvqj9J7BZwDnNpmIJEmSJKl/SovBBcCLm0xEkiRJktQ/pZeJfhA4JyLuA84HFrUHZObjvUxMkiRJ0sSxsvcgduM9iM0rLQZvrB+/2mV+jmBdkiRJkqQxVlrAHUFV8EmSJEmSJoGiYjAzD2s4D0mSJEn6P1522rzSDmQkSZIkSZOIxaAkSZIkTUF2+tIHjyx/rOenuSVJkiSV87LTp/LMYKGI2CQizoqIByLizxFxTkRsOtZ5SZIkSdLK8MxggYhYG7gYWArsQ9Wz6lHAJRHxosx8aCzzkyRJktRfIznTOHfWCuaMwysFLQbL7AdsDmyZmTcBRMSvgd8B/wwcN4a5SZIkSdKIeZlomd2BKwYLQYDMvAX4CfD6MctKkiRJklaSxWCZrYFrO7RfB2zV51wkSZIkadQiM8c6h3EvIpYBx2XmgW3tRwEHZuZTLreNiP2B/eunL6RzMTkZPR14YKyToD959HIbo1nXyiw7kmVKY0vingncW7jdiW68HAvQfC7j5VjYFLit4e318niYKsbTezFVjgVo/njwWFg54+X9GG0eJd/nvXqto13PePk7qeSYfG5mzijcbm9kptMwE7AMmNeh/ShgRcHyV471a+jje3XiWOfQrzx6uY3RrGtllh3JMqWxJXEeC5Mzl3F0LNzT9PZ6eTxMlWk8vRdT5Viol2/0ePBYGPt9ZCzzKPk+79Vr7UGu4+XvpBEfk/2YvEy0zP3A+h3aN6jn6QnnjnUCtX7k0cttjGZdK7PsSJYpjR0vv/vxYjy9H03nMl6OhcV92J7Hw8iNp/diqhwL0Pzx4LGwcsbL+zGR/k4a7XrGy99JK3NMNs7LRAtExMXAGpm5Q1v7ANV7uOMwy1+ZmS9tMEVpQvBYUJPcv6QneDyoSe5fIzde3zPPDJb5HrBdRGw+2BARM4G/q+cN58Rm0pImHI8FNcn9S3qCx4Oa5P41cuPyPfPMYIGImA5cDTwCHEI16PyRwLrAizJzyRimJ0mSJEkj5pnBApn5ELAzcCNwGvB14BZgZwtBSZIkSRORZwYlSZIkaQqacmcGI2KTiDgrIh6IiD9HxDkRsekIlt8vIq6PiKURcUNEvKdL3B4R8cuIeDQibo2IQyJi1cJtrB8RJ0XEvRHxUERcFBGzOsQdExE/ioj7IiIjYk7p65Bg/B8PEbFuRHw6Igbq/DIiZneJXSUiDoqIhfV2ro6IN5a+FvVeP/aviHhdRHwjIm6MiMfrjr1GkuOaEfGpiLgzIh6JiMsj4uUd4ty/tNJGcyxExD4RcXb92ZkRccoQsTtExE/rffmuiDguItYq3I7HwgQVERtHxOfr39nD9X4ycwTLF31HT6b9KyL2bDmuHqm/Yz4ZEesWLPvViPhtfSwvqXN8f5f3rOjvpC7bKfrciMK6oauxHtuinxOwNvA7qgHg9wBeD1wD/B6YXrD8fsDjwNHATlTjDD4OvLctbhfgMaobRXcCPgQ8ChxbsI0ALgNuB94KvBpYQDWw58ZtsQ8CPwZOpbqPcc5Yv8dOE2eaIMfDTGARcBFwdr2fz+4SezSwFPhwvZ35dT6vGev3eipOfdy/vgL8Bvga1WC+AyPM8+tU3X3vB7wCOIfq/vBt3L+cejH14Fi4EPgVcBLVwNandIl7Ub3vfqfel99NNfzVtwvz9FiYoBMwG7gbOB/4Yf1dObNw2aLv6Mm2fwFXAGcAewM7Ah+s87sCWGWYZb8F/Ev93r0K+Eyd4/FtcUXfY122UfS5wQjqhq7bGusduJ8T8IF6h9+ipW0zYAXwoWGWXQ34E3BqW/vJ9Ru+ekvbL4EFbXGfoBq8/tnDbOf19UG8U0vb06n+IP5cW+wq9eMWWAw6jXCaIMdDtPz8SroUg8Cz6i+Pw9va/wf49Vi/11Nx6uP+tUrLz5cxgmIQeHG9T72zbds3AN9z/3LqxTSaY6GObd3Hb6d7MfjfVH88th4f76j38b8aZhseCxN4attH3s3IisGi7+jJtn8BMzq0Db6enVdifd8EHmx7fUXfY13WV/S5wQjqhm7TVLtMdHfgisy8abAhM28BfkL1Zg5le2AGcHpb+2nAM4AdoDqlC2zTJW51YNeCHP+YmZe05PgA1YCWT8oxMx8fZl3SUMb98ZD1p1qBXYA1OmzndGBWRGxWuB71TuP7V73O0XwO7g4sB77dsr4VVP/13SUiptXN7l8ajdEcC0X7eESsTnVG4IzMXN4y6wyqP+qH247HwgS2sp+Dpd/Rk3H/ysx7OjT/on7caCVWeR9VoTao+Husi9LPjeK6oZupVgxuTXW6td11wFatDR2uy9+6fmxf/rr6cauh4upf4MOt24mIOfHUe6CGynHTiFinwzxpZUyE46HU1lT/Tbyprb09H/VPP/avYhExO556b/XWwC2Z+XCH7axBddXFYJz7l1bWaI6FUs8D1mzfTmY+SnVZWetnrcfCFFXfhzfQ0lT6HT1V9q8d68ffDjZ0OyajslpErFff07gPcFxLSPH3WEQc1uE+z9LPjVHXDVOtGNyA6vrmdouA9dvaHqun1mXpsPyitvnd4gbbNmh5/ni9jdazH0PlSIc8pZU1EY6HUhsAizucSWzPR/3Tj/1rJLLeRut/0If7vG3dj92/tLJGcyyMZBsMsZ3WfdRjYepaQdln7WBbyXf5pNi/ImIj4Ajgosy8smVWt2NyN6qznfcDZwKfz8wjW+aP5HtspPXA+oVxUFA3rDZcwFSVmY2/N5n5NapOD6RxzeNBTerT/rUAv/M0znksqEmZucXwUaPexoTbv+qzZ9+lKpbf2TpviGPyx8C2VPfnvQL4cERkZh480u1n5hFUheiYmGpnBu+nc4XcrapuX5YOyw9W9ouGiRtsW9ShvTTH1vVLozURjodS9wPrRUQMk4/6px/712gN93nbuh+7f2lljeZYGMk2GGI7o/3bw2Nhcir9jp60+1c9NMa5wObALpl5e8lymflAZl6Zmf+TmR8DjgEOrM8wwui/x0o/N0ZdN0y1YvA6nriGt9VWVF2TD7csHZYfvG73N0PF1dcBr124nW453paZS4ZZXio1EY6HUtcB06juaxgqH/VPP/av0boO2Cwi1u6wnWU8cd+K+5dGYzTHQqnfU91r1f5ZuybVH7klx5zHwtRT+h09KfevumOcs4CXUg1dcc0oVnclVV012MnNaL/HSj83Rl03TLVi8HvAdhGx+WBDvcP/XT1vKJdTdQW7d1v726mq+58AZOZtwNVd4pYDFxTkuFFEDN7ESkQ8DXhdQY7SSEyE46HUD+r1ddrOtfXN8OqvxvevHjiXqse8N7XkuBrwZuBHmbm0bnb/0miM5lgokpnLqPbTvep9eNCeVH9cD7cdj4UpqPQ7ejLuXxGxCtXYhzsDe2TmFaNc5Y5U9/zdXD8f7fdY6efG6OuGkY6jMZEnYDrVfx+uoepudXeqg+BmYJ222BXAV9ra3kN1k+dRVAN8HlE/f19b3Gvq9vl13L9RDeD5qba4d9Tb2bGlbRXgp8AfgLdQdbM7QLXjbNK2/I5UB+IBVDvgf9XP9xzr99pp/E8T4Xio23et9+vD6/380Pr5rm1x8+r1fqjezhfr7b52rN/rqTj1cf967uDnHlUPcNe1PH9uS9yO9Xbe0bb8t6guo3k31X0fZ9X70V+1xbl/Oa3U1INjYauWffo+4JKW5zNa4rap99Fz6n35XVR/O5zZtj6PhUk4tewTX6y/K99bP9+xJeYm4H/aliv9jp5U+1fL+3QUsF3btHFL3JOOSaqOY86i6j10p/p4/iJVBzBfbNtG6ffYJ+rtPLelrehzgxHUDV3fi7HeecfgYNkUOBv4M/Ag8B06DMxZ7yCndGj/Z+BGqtPlvwP+pct2/rH+pS0Fbqt/0au2xcyhwyDaVNf5nlz/Ih+mGmzzxR22MVAv/5RprN9np4kxTZDjYWGX/XxhW9yqwCHArfV2fo3/GJn0+1fLftNpmtMSN7u9rW5fi6o78Luo/gD5Wfs+6P7lNNppNMcCcNgQ+/jsttiXU52ReBS4G/gssHZbjMfCJJyG2EcGWmIWtj5vaR/2O3qy7V90/9sigcPa3tdTWp6/gKog/kOd393AZVRnAFfpsJ2S77HBY3xmW3vp50ZR3dBtinolkiRJkqQpZKrdMyhJkiRJwmJQkiRJkqYki0FJkiRJmoIsBiVJkiRpCrIYlCRJkqQpyGJQkiRJkqYgi0FJahMRe0TEhzq0z46IjIjZY5BWey4zI+KwiNh8rHOZbCJi1Yg4NiL+FBF/iIgPdojZKyL+GBFP6zBvICIu67Lud9f70MxhcnhmRJwTEQ9ExLURsXOHmBMi4rwuy2c9HdNhXkTEzfX804fKo45/W0T8PiIWRcSXI2KttvkzI+LBiPibDsuuEhHvjIifR8T9EfFQva5vRcTLhtt2vY4PRcSvIyJatpcRMadk+YkoIk6JiIUrsdxLIuLhiNi0gbQkTUIWg5L0VHsATykGgauA7evHsTYTOBSwGOy9fagGCv5X4Gjg063/AIiIdagGT56bmX9uKIfjgOcBewGXAGdFxPotOfw18A7g/UOs40Fg78EiqsXfU+0/Dw2XREQ8HzgVOAmYA+wKfLQt7HjgG5n5sw6r+DTwZeBSqkGZ96hf2zOBpxSPHba/HnAwcEQ6MPKwMvOXwIXAkWOdi6SJYbWxTkCSJor6D/8rxjoPNW5XquLmWwAR8fq6baCefxhwfWZ+s+Ec3peZP4yI/6EqxLYDLoiIVYAvAsdm5s1DrOM7wNuBHXkid6iKyAXAZgV5/APwu8z8JEBE/CXwj1TvARHxWuBvgS3bF6zPIL4P/n97Zx5sRXHF4e8XFXGLCkpUtMTdsohoxaBRo8RdQwgkGldwi1tFNATcNaLiGvcFxaiFgAsuMSaBICCKcYmKBuMGROWB4goSFREEPfnj9PDmzbt37n3gQorzVU3dNz3dPadneub1mXP6NNeZWb/coTHADakdtTga+Bx4oI68gTMIeFDSGWb29rctTBAESzdhGQyCIMghaTBuGWqfc7VrSMeauYlmLoGS9pE0UdJnkv4laXtJy0u6SNI7ycVusKRVCudbObkkTpX0efo9q2ygnM7/SNodk5OzSzq+gqQBkhpSnQ1pf4U62n+ypFdTO2ZLmiCpR+74XpJGpjbNTS6MfSUtl8szQlIz66mkdSUtlNQnl7aRpDskfSBpfrqGPYplK9S1tqRBkqYkOd6UdKek9oV8m0t6QO7yOU/SdEn3Sir7GNoK+Cy3PxdonerrCByPKzlfJ4tkMLOFuELUOh07FlgduKxGHdNxJbBnliCpNbA/MKSlciTy12Il4FrgFDP7sELZVVL5dytVbGZf1nH+XwP3mNkXtTJKOkzSC+k+z5Q0VNK6hTwrS7pR0ixJc1Lf2LEet9N6+lLqlwNTf5yffodKWjEd3zTtT03P2BtJnjWrn7mJ7PW8K0YDH+MfEIIgCEoJZTAIgqApFwAjgQ9wl9AfAbWUk02BPwCXAAcAKwJ/wa036+KDsvNxN7lzs0JpEPkQPuC9BrcG3QKck+qrxvM0KiMn5eTMFLDbgdPxAX9XYDDu2nd7WSMkHQpcAdwF7JfkvQ9ok8u2MfAwcBTw01Rnf9ydMmMosK2krQqnOCT93pnOtwHwNNAJ6AN0S224X1K3MlmTTPOAM4B9gFOAzYAnksKTMQJoD5wA7I1fl/mU//97GvhlGrj/ANiLRovwQOBqM5tcQz7Sx4AmW6XzSjpCzeeiPg0cJ6mtpKOB1YDnJK2NX+vfmNn8WjLgfWD/3DXpDqyA39dKMjdIerQgRydJe0paDziSxmtxJjCDKv3KzGYCU4F+ko5XC+exSdoQ2BL4Rx15j8X73au45fJ0/H6Pl7v1ZtyM993L8ed6MnBHnSKV9qWk0D0JHIi7wu4HnIpf71apjvWAN4HfpjrOB3bH3zll7av7XZE+HjyFPxdBEATlmFlsscUWW2y5DVee3qqQ3gUwoEsu7VFgAbBxLq1byje2UP5PwNTcfs+Ub5dCvrNwS1C7EhkzWfYopHdM6f0L6Wen9K1L6rweeL4F10n4dIOzgNnAd1L6SsBHwMWF/BOBkbn9W3Glu20h3xhgYgvv2XLABqmNPVLaWmm/WwvrWi3dV0vbXfiAvxfwBrBSjfL5stW2Drn8vYCFwK6F+zgt5V0AnJTSbwPurqMNBgwAVsXnBh6U0kcCd6S/G4BhhXKvAQ8X0q7IyT0R/8CxGTAH6FhDjh3SebLyM9J971xHGw5MZTYrpHdI6Ufk7v17wCOFfDunfNm12wL4Eji1kO/afH1VZKnZl3DF7gtg2xb0teVzcm6bSx8MNOT2W/SuwD9qzSM9k7HFFlts1bawDAZBECw5U6zp3K1J6fehQr5JwPrSooAe++AD/icL1qPRuDVhh8WQZZf0W4wSme3vWlL2WWAbSddJ2kPSysUMydVzkKRp+CB0Aa50rAG0AzCzz3DL06LgJZK+j1sAh+aq2wdXTj4qtP8h3BrVLFJnQZYTklvgHFyZmp4OZfPXZuHK2yWSjpG0WVl9GWb2iZl1wZWO9czsYOC7uAWmNzBf0oWS3pI0I/1d/H/6AvDDCtuACucbYmbLm9n4XNpLeACZLXBl+VpJO+FWrz7yaKPDk7vjJEkHVGnLHHy+XU9J6+BWzqouoma2qZntXkjrC6yNW8C3NbN38A8HN5rZS5IOlLsWz0oytcmV/Wdqw764UtmAu2E/JalXNTkS66VSlc0fAAAHKUlEQVTfD2rk2wLve00sfGb2OP58ZX1+e/wDxr2F8hWtpAXq6Ut7Ac+aB3GpiKRWks5M9+wz/PnJLJ/N5l3maOm74gPcQ6ENQRAEJYQyGARBsOTMLux/XpK+PG7JAB/AbogPCPPbM+l428WQJRv8vVNIf7dwvBJDcBe47XGF7EP58gYdwJcJwN1fu+JKzW64gpO5iObdM4filrouab8nHt3yz7k87XCrWLH9mdtb1fZL6o27bI7FFaTONA6IWwOYmeEBUCYAFwNT0hytE0quwSLMbFpSfEhtfNLMRuBBTQ7Do3LunNp2ZKH4HDObUNzwAX1dmNlCM5tiZh/L52QOBM5NMl2DW/02whXUoZKqKRNDcEWlD/A+fs1ahJnNNLPXzcyS4rkVcJ48oMyQJEMHXGm+plB2vpmNMrN+ZrZTKvsu7kpZRtafarnDVuvzpPNkx7P5g+8X8rxXo/56+1Jb4K0aVV2Mu1UPw92sO+P9F5o+P0Va+q7I5nmuRBAEQQkRTTQIguDbYxY+p+pXVY43LEadWSCPdYDXc+nrFI43Iw14BwGD0vynvXBrznBcQdwE2A7oaWaLLI+SflahuvG4pe4wSePx+YL3JathxizcKnJpFZHKIiEehLsz9s3J0Sw6ZrLY9koWyk7AicBASQ1m9veS+heR5g32xF03wa0095nZ1HT83pR2az31LSa9cRfH63MyHGEe4XaMpJeBPfA5cEXG4gpQP+BKqyMYSzXS/LurgJPNbI6kPYCXzGxsOj4Qd2WtiplNkTQct3C2M7OicpYxK/2uSdMgNkXyfb7IOsBz6e9MWWyHP3cZ3yuTN6OOvjQTn1NYxkHAEDNbZCEuzGmsRkvfFZkCPLOOuoMgWIYJy2AQBEFz5vPNfFEfhVvPKlqRzANwlMkIzeV8LP0eVEg/NP0+Wo9gZjbbzIYD99CoBGVuowuyfPIIpYcWimeK5TA8cuV++CB5aCHbKGBr4OUq7S+zCK2clyNRtM41kcfMJtK4fmTHannzJGvoQGCAmU3PHcpHhV0Vdz/8WpBHxOwPnFBQ5OqSwTxq5wXAX6mhqNVBf+DfZnZ/LTnkUW2rWXe3xBW8j0rOlblb11pLczJu3WvS5yXtiFvTHk1Jz+Dz7ooutRVdbKtR0pdGA50ldSop3qJ+m6Ol74qNgDcLH1+CIAiaEZbBIAiC5rwCtEkuYBOAeWb24tdwnjvwgeDDkq7A55m1wi1w3YDuZja3Stkp+Dy5oyR9iCuHk9McrruA/mlO0ZN4pNFzgLvK2iHpZtyV8ynckrQ5bhEbnbK8irs5XijpC3xQ26dCVRlD8YiTN9G4zEGe3+MD9MckXY9bN9bEB9cbm9lRJXWPAk6TdGaqYzdc8cy3Z2vcZXE4HhhlOTyy60JgXEndeY7BlZ2rcmljgUslZXO9DgH6FgvWS5o7dxuwe37eYI4r8eUV8mtcjgXOlvQR7mq4CSVtMrOb8PtQS5bXgGnFeYPpWEd8WYttcsnjgKslZffybBr7y+pAQ7ICjsVdKNviStu+wGU1FP5n8H7dGXi8pG1fpPMPkjQM/wjRHnft/Q9JATazSZLuBC5ISv5zeL/JLNtVl7qosy9dhfeFsZIGAC/igWd+DhxvZp/g/fZwSS+men6Br9NYi5a+K7an8cNQEARBVUIZDIIgaM4t+Pyzi/DAKNPw+VBfKWa2QFIWov5Y/Gv+p7h75wga5x5WKjtL0on4khHj8cHpT3CF6wg82MVR+OD8bdwV87waIj2BDzh74gP5t/GB9bnpnJ9L6o67Kg7B3fNuwxW9P1aQcZKkCbhr6cXJWpg/Pl3Sdri16SI8SMks4CVqLIOBR25cA1dGW6drsHdqd8a7SbbfAevj0RVfBLqa2XPUQNJaSa4eZpa35tyMD8KvxK1gN7FkLqLfwe9fM8uepN1w98/ifMCT0nnvxq/Z4Wb2yhLIkJGf01rkBuDyfLAkM3tZvj5ff9wN9WHg5HT4Y7zP7YnPA22H34OXgeOo0GfymNk8SQ/iylrp/EIzu1nSXHyJkQfxSKcj8cihn+ayHot/8DgVV6bG4cu0/I1yK2XNvmRm/01Bfgbgz3Rb3GI5jsZnuTd+n7N5tiOBg2mc+1etfXW/K+RLtnTCPwAFQRCUosL/5iAIgiAIgqUC+dqL4/ClOKbXyL645+gHXPZ1nuObRNJpeCCoTZZkfmgQBMsGoQwGQRAEQbDUImkM7gJ94ldQV1fcDXki7hb6Y9yi+aCZFefZ/t8hqTVuHT/dzKouIRIEQZARbqJBEARBECzN9Aa6S1LR1Xgx+ATojrtbrgLMwBedP3cJ611a6IDPbSwGawqCIKhIWAaDIAiCIAiCIAiWQWJpiSAIgiAIgiAIgmWQUAaDIAiCIAiCIAiWQUIZDIIgCIIgCIIgWAYJZTAIgiAIgiAIgmAZJJTBIAiCIAiCIAiCZZD/AQNvECysUVh5AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1008x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.set_title(\"Time to save\")\n",
    "duration_hist(ax, completed[\"duration\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 359,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x1008 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "full_desktop = completed.query(\"platform == 'desktop'\")\n",
    "full_phone = completed.query(\"platform == 'phone'\")\n",
    "\n",
    "fig, ax = plt.subplots(2, 1, figsize=(14, 14))\n",
    "\n",
    "fig.suptitle(\"Time to save by platform\")\n",
    "desktop_ax = ax[0]\n",
    "phone_ax = ax[1]\n",
    "\n",
    "duration_hist(desktop_ax, full_desktop[\"duration\"])\n",
    "desktop_ax.set_title(\"Desktops\")\n",
    "\n",
    "duration_hist(phone_ax, full_phone[\"duration\"])\n",
    "phone_ax.set_title(\"Phones\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 360,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x1008 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "full_desktop_ve = completed.query(\"platform == 'desktop' & editor == 'visualeditor'\")\n",
    "full_desktop_wte = completed.query(\"platform == 'desktop' & editor == 'wikitext'\")\n",
    "\n",
    "fig, ax = plt.subplots(2, 1, figsize=(14, 14))\n",
    "\n",
    "fig.suptitle(\"Desktop time to save duration by editing interface\")\n",
    "ve_ax = ax[0]\n",
    "wte_ax = ax[1]\n",
    "\n",
    "duration_hist(ve_ax, full_desktop_ve[\"duration\"])\n",
    "ve_ax.set_title(\"Visual editor\")\n",
    "\n",
    "duration_hist(wte_ax, full_desktop_wte[\"duration\"])\n",
    "wte_ax.set_title(\"2010 wikitext editor\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}