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@bsmedberg
Last active August 18, 2017 18:06
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Tab/Pageload Behavior of Firefox Release Users\n",
"\n",
"Author: bsmedberg@mozilla.com\n",
"\n",
"Date: 8-May-2017\n",
"\n",
"Status: Partially-reviewed draft."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import plotly.plotly as py\n",
"from plotly.graph_objs import *\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"import pyspark.sql.functions\n",
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"main_summary = spark.read.option(\"mergeSchema\", \"true\")\\\n",
" .parquet('s3://telemetry-parquet/main_summary/v3/')\\\n",
" .createOrReplaceTempView(\"main_summary\")"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"sample_unfiltered = spark.sql(\"\"\"\n",
" SELECT\n",
" client_id,\n",
" SUM(CASE WHEN app_version < '52' THEN 1 ELSE 0 END) AS bad_version,\n",
" count(1) as subsession_count,\n",
" max(max_concurrent_tab_count) as max_concurrent_tab_count,\n",
" sum(tab_open_event_count) as tab_open_event_count,\n",
" SUM(CASE WHEN subsession_length < 0 OR subsession_length > 172800 THEN 1 ELSE 0 END) AS bad_length,\n",
" sum(subsession_length) as subsession_length_sum,\n",
" sum(total_uri_count) as total_uri_count,\n",
" SUM(CASE WHEN reason = 'aborted-session' THEN 1 ELSE 0 END) AS aborted_sessions,\n",
" SUM(CASE WHEN reason = 'shutdown' THEN 1 ELSE 0 END) AS shutdown_session,\n",
" SUM(CASE WHEN reason = 'environment-change' THEN 1 ELSE 0 END) AS environment_session,\n",
" SUM(CASE WHEN reason = 'daily' THEN 1 ELSE 0 END) AS daily_session\n",
" FROM main_summary\n",
" WHERE\n",
" submission_date_s3 >= '20170415' AND submission_date_s3 <= '20170429'\n",
" AND subsession_start_date >= '2017-04-16' AND subsession_start_date < '2017-04-23'\n",
" GROUP BY 1\n",
" HAVING bad_version = 0 AND bad_length = 0\n",
" \"\"\"\n",
").cache()"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"147499263"
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sample_unfiltered.count()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Discarding severe outliers\n",
"\n",
"When defining heavy users in terms of total pageloads, we can suffer from bots and other unreal situations that inflate pageloads. Discard anyone who loads more than a page every 10 seconds or more than 30000/week (because WTF)."
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"80472094921"
]
},
"execution_count": 39,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"total_uri_count_unfiltered = sample_unfiltered.select(pyspark.sql.functions.sum(sample_unfiltered.total_uri_count)).first()[0]\n",
"total_uri_count_unfiltered"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"total outliers: 1125113\n",
"total URIs loaded by outliers: 1125113 (5%)\n",
"example outliers:\n"
]
},
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>subsession_count</th>\n",
" <th>max_concurrent_tab_count</th>\n",
" <th>tab_open_event_count</th>\n",
" <th>subsession_length_sum</th>\n",
" <th>total_uri_count</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>8</td>\n",
" <td>3</td>\n",
" <td>200.0</td>\n",
" <td>8835</td>\n",
" <td>1804</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>7</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>43</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>71</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>16</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>25</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>10</td>\n",
" <td>83</td>\n",
" <td>391.0</td>\n",
" <td>3204</td>\n",
" <td>405</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>3</td>\n",
" <td>5</td>\n",
" <td>7.0</td>\n",
" <td>200</td>\n",
" <td>39</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1.0</td>\n",
" <td>36</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>12</td>\n",
" <td>3</td>\n",
" <td>36.0</td>\n",
" <td>26032</td>\n",
" <td>3001</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>105</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1.0</td>\n",
" <td>46</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>11</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>2</td>\n",
" <td>9</td>\n",
" <td>22.0</td>\n",
" <td>8274</td>\n",
" <td>2184</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>7</td>\n",
" <td>8</td>\n",
" <td>219.0</td>\n",
" <td>6269</td>\n",
" <td>1334</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>4</td>\n",
" <td>9</td>\n",
" <td>12.0</td>\n",
" <td>330</td>\n",
" <td>47</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>5</td>\n",
" <td>65</td>\n",
" <td>6.0</td>\n",
" <td>159</td>\n",
" <td>29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>63</td>\n",
" <td>12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" <td>2.0</td>\n",
" <td>513</td>\n",
" <td>61</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>19</td>\n",
" <td>58</td>\n",
" <td>960.0</td>\n",
" <td>425283</td>\n",
" <td>53978</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>430</td>\n",
" <td>44</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>5</td>\n",
" <td>61</td>\n",
" <td>154.0</td>\n",
" <td>1976</td>\n",
" <td>547</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>234</td>\n",
" <td>27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>65</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>79</td>\n",
" <td>17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>4</td>\n",
" <td>2</td>\n",
" <td>2.0</td>\n",
" <td>440</td>\n",
" <td>76</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" <td>3.0</td>\n",
" <td>2805</td>\n",
" <td>791</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1060</th>\n",
" <td>9</td>\n",
" <td>10</td>\n",
" <td>45.0</td>\n",
" <td>11043</td>\n",
" <td>1115</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1061</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>41</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1062</th>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" <td>4.0</td>\n",
" <td>450</td>\n",
" <td>60</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1063</th>\n",
" <td>11</td>\n",
" <td>5</td>\n",
" <td>36.0</td>\n",
" <td>1335</td>\n",
" <td>188</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1064</th>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>154</td>\n",
" <td>19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1065</th>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>1.0</td>\n",
" <td>1225</td>\n",
" <td>142</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1066</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1067</th>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>128</td>\n",
" <td>20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1068</th>\n",
" <td>21</td>\n",
" <td>12</td>\n",
" <td>528.0</td>\n",
" <td>100896</td>\n",
" <td>11048</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1069</th>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>16</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1070</th>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>130</td>\n",
" <td>19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1071</th>\n",
" <td>16</td>\n",
" <td>5</td>\n",
" <td>14.0</td>\n",
" <td>1302</td>\n",
" <td>154</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1072</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>18</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1073</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>14</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1074</th>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" <td>12.0</td>\n",
" <td>544</td>\n",
" <td>57</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1075</th>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>2.0</td>\n",
" <td>511</td>\n",
" <td>121</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1076</th>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1.0</td>\n",
" <td>153</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1077</th>\n",
" <td>7</td>\n",
" <td>3</td>\n",
" <td>9.0</td>\n",
" <td>7112</td>\n",
" <td>971</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1078</th>\n",
" <td>3</td>\n",
" <td>5</td>\n",
" <td>7.0</td>\n",
" <td>892</td>\n",
" <td>142</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1079</th>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1.0</td>\n",
" <td>218</td>\n",
" <td>23</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1080</th>\n",
" <td>5</td>\n",
" <td>4</td>\n",
" <td>14.0</td>\n",
" <td>1278</td>\n",
" <td>135</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1081</th>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" <td>1.0</td>\n",
" <td>2363</td>\n",
" <td>242</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1082</th>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>1.0</td>\n",
" <td>38</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1083</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1084</th>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1.0</td>\n",
" <td>94</td>\n",
" <td>17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1085</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>195</td>\n",
" <td>24</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1086</th>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>2.0</td>\n",
" <td>393</td>\n",
" <td>58</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1087</th>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" <td>4.0</td>\n",
" <td>515</td>\n",
" <td>77</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1088</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>30</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1089</th>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>193</td>\n",
" <td>21</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>1090 rows × 5 columns</p>\n",
"</div>"
],
"text/plain": [
" subsession_count max_concurrent_tab_count tab_open_event_count \\\n",
"0 8 3 200.0 \n",
"1 1 1 NaN \n",
"2 2 1 NaN \n",
"3 2 1 NaN \n",
"4 1 1 NaN \n",
"5 1 1 NaN \n",
"6 1 1 NaN \n",
"7 10 83 391.0 \n",
"8 1 1 NaN \n",
"9 3 5 7.0 \n",
"10 1 2 1.0 \n",
"11 12 3 36.0 \n",
"12 3 1 NaN \n",
"13 1 2 1.0 \n",
"14 1 2 NaN \n",
"15 2 9 22.0 \n",
"16 7 8 219.0 \n",
"17 4 9 12.0 \n",
"18 5 65 6.0 \n",
"19 2 2 NaN \n",
"20 1 4 2.0 \n",
"21 1 1 NaN \n",
"22 19 58 960.0 \n",
"23 6 1 NaN \n",
"24 5 61 154.0 \n",
"25 2 1 NaN \n",
"26 4 1 NaN \n",
"27 1 1 NaN \n",
"28 4 2 2.0 \n",
"29 2 3 3.0 \n",
"... ... ... ... \n",
"1060 9 10 45.0 \n",
"1061 1 1 NaN \n",
"1062 1 5 4.0 \n",
"1063 11 5 36.0 \n",
"1064 1 2 NaN \n",
"1065 2 2 1.0 \n",
"1066 1 1 NaN \n",
"1067 2 1 NaN \n",
"1068 21 12 528.0 \n",
"1069 2 1 NaN \n",
"1070 2 1 NaN \n",
"1071 16 5 14.0 \n",
"1072 1 1 NaN \n",
"1073 1 1 NaN \n",
"1074 1 4 12.0 \n",
"1075 1 3 2.0 \n",
"1076 1 2 1.0 \n",
"1077 7 3 9.0 \n",
"1078 3 5 7.0 \n",
"1079 1 2 1.0 \n",
"1080 5 4 14.0 \n",
"1081 3 2 1.0 \n",
"1082 1 3 1.0 \n",
"1083 1 1 NaN \n",
"1084 1 2 1.0 \n",
"1085 1 1 NaN \n",
"1086 1 2 2.0 \n",
"1087 1 5 4.0 \n",
"1088 1 1 NaN \n",
"1089 2 1 NaN \n",
"\n",
" subsession_length_sum total_uri_count \n",
"0 8835 1804 \n",
"1 6 1 \n",
"2 7 2 \n",
"3 43 8 \n",
"4 71 8 \n",
"5 16 2 \n",
"6 25 3 \n",
"7 3204 405 \n",
"8 7 1 \n",
"9 200 39 \n",
"10 36 7 \n",
"11 26032 3001 \n",
"12 105 11 \n",
"13 46 7 \n",
"14 11 4 \n",
"15 8274 2184 \n",
"16 6269 1334 \n",
"17 330 47 \n",
"18 159 29 \n",
"19 63 12 \n",
"20 513 61 \n",
"21 4 1 \n",
"22 425283 53978 \n",
"23 430 44 \n",
"24 1976 547 \n",
"25 234 27 \n",
"26 65 8 \n",
"27 79 17 \n",
"28 440 76 \n",
"29 2805 791 \n",
"... ... ... \n",
"1060 11043 1115 \n",
"1061 41 5 \n",
"1062 450 60 \n",
"1063 1335 188 \n",
"1064 154 19 \n",
"1065 1225 142 \n",
"1066 5 1 \n",
"1067 128 20 \n",
"1068 100896 11048 \n",
"1069 16 2 \n",
"1070 130 19 \n",
"1071 1302 154 \n",
"1072 18 3 \n",
"1073 14 5 \n",
"1074 544 57 \n",
"1075 511 121 \n",
"1076 153 16 \n",
"1077 7112 971 \n",
"1078 892 142 \n",
"1079 218 23 \n",
"1080 1278 135 \n",
"1081 2363 242 \n",
"1082 38 4 \n",
"1083 2 2 \n",
"1084 94 17 \n",
"1085 195 24 \n",
"1086 393 58 \n",
"1087 515 77 \n",
"1088 30 4 \n",
"1089 193 21 \n",
"\n",
"[1090 rows x 5 columns]"
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"outliers = sample_unfiltered.where((sample_unfiltered.total_uri_count > 30000) | (sample_unfiltered.subsession_length_sum / sample_unfiltered.total_uri_count < 10))\n",
"outliers_uri_count = outliers.select(pyspark.sql.functions.sum(outliers.total_uri_count)).first()[0]\n",
"\n",
"print \"total outliers: {}\".format(outliers.count())\n",
"print \"total URIs loaded by outliers: {} ({:.0f}%)\".format(outliers.count(), 100.0 * outliers_uri_count / total_uri_count_unfiltered)\n",
"print \"example outliers:\"\n",
"outliers.select(\"subsession_count\", \"max_concurrent_tab_count\", \"tab_open_event_count\", \"subsession_length_sum\", \"total_uri_count\").sample(False, 0.001).toPandas()"
]
},
{
"cell_type": "code",
"execution_count": 61,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"27134"
]
},
"execution_count": 61,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# how many users just have >30000 uri loads?\n",
"sample_unfiltered.where(sample_unfiltered.total_uri_count > 30000).count()"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"sample = sample_unfiltered.where((sample_unfiltered.total_uri_count <= 30000) & (sample_unfiltered.subsession_length_sum / sample_unfiltered.total_uri_count >= 10))\n",
"sample.createOrReplaceTempView(\"sample\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Heavy users\n",
"\n",
"There are multiple definitions of a heavy user being proposed. We can't calculate heavy users by activeTicks as proposed at https://docs.google.com/a/mozilla.com/document/d/1TJUo1dbTA5mcWg5ZznKqYn3mpSqQeaDlqCRzUsi0_Js/edit?usp=sharing because this dataset doesn't yet have activeTicks.\n",
"\n",
"Instead, this calculates it by pageloads: at what threshold of pageloads (total_uri_count) do we find the users who are responsible for 80% of all pageloads?"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"total_users = sample.count()\n",
"total_uri_count = sample.select(pyspark.sql.functions.sum(sample.total_uri_count)).first()[0]"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"ranked_by_uri = spark.sql(\"\"\"\n",
" SELECT\n",
" total_uri_count,\n",
" RANK() OVER (ORDER BY total_uri_count) AS rank\n",
" FROM sample\n",
" ORDER BY total_uri_count\n",
"\"\"\").cache()"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The top 1% of users accounted for 12% of total URI loads. (cutoff=4423)\n",
"The top 5% of users accounted for 32% of total URI loads. (cutoff=2209)\n",
"The top 10% of users accounted for 48% of total URI loads. (cutoff=1490)\n",
"The top 30% of users accounted for 80% of total URI loads. (cutoff=570)\n"
]
}
],
"source": [
"def top_npct_uris(n):\n",
" topn = ranked_by_uri.where(ranked_by_uri.rank > total_users * (100.0 - n) / 100)\n",
" cutoff = topn.first().total_uri_count\n",
" uri_count = topn.select(pyspark.sql.functions.sum(sample.total_uri_count)).first()[0]\n",
" print \"The top {}% of users accounted for {:.0f}% of total URI loads. (cutoff={})\".format(n, 100.0 * uri_count / total_uri_count, cutoff)\n",
" return cutoff\n",
"top_npct_uris(1)\n",
"top_npct_uris(5)\n",
"heavy_user_cutoff = top_npct_uris(10)\n",
"_ = top_npct_uris(30)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"For the purposes of this analysis and as suggested by bcolloran, we're going to look at the top 10% of users as \"heavy users\"."
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Heavy users are users who loaded more than 1490 pages this week.\n"
]
}
],
"source": [
"print \"Heavy users are users who loaded more than {} pages this week.\".format(heavy_user_cutoff)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Do page loads distribute differently than usage hours\n",
"\n",
"bcolloran did a previous analysis of the distribution of session hours and active ticks. We don't have active ticks yet, but let's calculate the distribution of usage hours to double-check our data and repeat the previous analysis"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"total_session_length = sample.select(pyspark.sql.functions.sum(sample.subsession_length_sum)).first()[0]"
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [],
"source": [
"ranked_by_session_length = spark.sql(\"\"\"\n",
" SELECT\n",
" subsession_length_sum,\n",
" RANK() OVER (ORDER BY subsession_length_sum) AS rank\n",
" FROM sample\n",
" ORDER BY subsession_length_sum\n",
"\"\"\").cache()"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The top 1% of users accounted for 6% of total session hours. (cutoff=168.0 hours)\n",
"The top 5% of users accounted for 27% of total session hours. (cutoff=123.2 hours)\n",
"The top 10% of users accounted for 45% of total session hours. (cutoff=79.7 hours)\n",
"The top 30% of users accounted for 79% of total session hours. (cutoff=30.6 hours)\n"
]
}
],
"source": [
"def top_npct_length(n):\n",
" topn = ranked_by_session_length.where(ranked_by_session_length.rank > total_users * (100.0 - n) / 100)\n",
" cutoff = topn.first().subsession_length_sum\n",
" length_sum = topn.select(pyspark.sql.functions.sum(sample.subsession_length_sum)).first()[0]\n",
" print \"The top {}% of users accounted for {:.0f}% of total session hours. (cutoff={:.1f} hours)\".format(n, 100.0 * length_sum / total_session_length, cutoff / 60.0 / 60.0)\n",
"\n",
"top_npct_length(1)\n",
"top_npct_length(5)\n",
"top_npct_length(10)\n",
"top_npct_length(30)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Comparing light and heavy user behavior\n",
"\n",
"The following charts compare the behavior of heavy users and normal users."
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def iter_with_next(l):\n",
" \"Generate (first, next) pairs for a list (skipping the last item).\"\n",
" i = iter(l)\n",
" prev = i.next()\n",
" for v in i:\n",
" yield (prev, v)\n",
" prev = v"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"def show_histogram(colname, minv, maxv, num_buckets, label):\n",
" buckets = range(minv, maxv, (maxv - minv) / num_buckets) + [maxv]\n",
"\n",
" selected = sample.select(pyspark.sql.functions.expr(colname).alias(\"data\"), \"total_uri_count\")\n",
" \n",
" label_map = {\n",
" -1: \"<{}\".format(minv),\n",
" maxv: \">={}\".format(maxv)\n",
" }\n",
"\n",
" caseExpr = pyspark.sql.functions.when(selected['data'] < minv, -1)\n",
" for start, end in iter_with_next(buckets):\n",
" caseExpr = caseExpr.when(selected['data'] < end, start)\n",
" label_map[start] = start == end - 1 and str(start) or \"{}-{}\".format(start, end - 1)\n",
" \n",
" caseExpr = caseExpr.otherwise(maxv)\n",
"\n",
" def print_chart(data, subgroup):\n",
" bucketed = data.select(caseExpr.alias(\"bucket\"))\n",
"\n",
" counts = bucketed.groupBy(\"bucket\").count().toPandas().set_index(\"bucket\").sort_index()\n",
"\n",
" max_count = counts.max()['count']\n",
" total_count = counts.sum()['count']\n",
"\n",
" counts.plot(kind=\"bar\", legend=None, figsize=((num_buckets + 2) / 3, float(max_count) / total_count * 5))\n",
"\n",
" xticks = [label_map[v] for v in counts.index.values]\n",
" plt.xticks(range(0, num_buckets + 1), xticks)\n",
" plt.xlabel(label)\n",
"\n",
" ytick_ratios = np.arange(0.05, float(max_count) / total_count, 0.05)\n",
" yticks = [\"{:.0f}%\".format(r * 100) for r in ytick_ratios]\n",
" yticks_pos = [r * total_count for r in ytick_ratios]\n",
" plt.yticks(yticks_pos, yticks)\n",
" plt.ylabel(\"% of {} users\".format(subgroup))\n",
" plt.show()\n",
" \n",
" print_chart(selected, \"all\")\n",
" print_chart(selected.where(selected['total_uri_count'] > heavy_user_cutoff), \"heavy\")"
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [
{
"data": {
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R8/Kypw9Iug94FNgN+HPe5hTglNJGkk4CJgNvABOBLYF9gUuA0bUOYMKECQwdOrTbujFj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\nhf0FKM8ZjjSgAIQAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f07a6400e10>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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1SJyPkCde2P2EEguh0CxXVb4coWyXxWc54P6cux/r7isBX2BGrLfywtynuftf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\nkPFh9UnGdOLNcHKh7H9EHK5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"text/plain": [
"<matplotlib.figure.Figure at 0x7f07a3a2f5d0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"show_histogram(\"subsession_length_sum / 60 / 60\", 0, 160, 20, \"usage hours\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Possible conclusions:\n",
" \n",
"1. heavy users tend to use their browser more (let's state the obvious!)\n",
"2. heavy users are more likely to be the kind of user who keeps their browser open overnight."
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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a19L68j4/ADxHmsTql8AP8uuXwOPAs8BWpdZZ5s6G+gt4GtiksLwS6VvQ2/Py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\nQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f07a3880190>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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jYFod7O6BJzSrHB/5CBhNxhAOZaGwKuU7AZdltLcO/iDWiudEWgW4Nv0fzsIH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\n8P8pyoWchkB69gAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f07a61aad90>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"show_histogram(\"subsession_count\", 0, 100, 10, \"# of subsessions\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"No easy conclusions here, although there appear to be a bunch of heavy users who still open and close their browser regularly? Should validate this with the ping reason data."
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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PXuOJvpEgCIIaKGIgDsMz4W2Bx1PYJsDyeCbdLD4zs4llwtcAnkvLdSDp+RT2UtL1QTMb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\nMb8iqBMze6uScUj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/aWC2VXZZOgzvbxvVzjVvwh0XDZU028yuqlbZMBC18xqwh6Rv4+3M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\nCIIgCMoSBiIIgiAoy/8H4sYMlF7i0mEAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f07a3a14cd0>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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AR3bGao6wupqdMQiCoBq1zmLaGBjRE8N2tj8TYhBwXi4t/NEEQdA9qLUH8RQeqOdtSWOA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\nVCUqiCAIgqAq/w+LP2QQAgyb8AAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f07a370cdd0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"show_histogram(\"max_concurrent_tab_count\", 1, 25, 12, \"max # of tabs open any time during the week\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Conclusions: heavy users tend toward a few more tabs in general, and there is a more significant proportion of tab-hoarders who regularly keep >25 tabs open."
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [
{
"data": {
"image/png": 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1Z1Vtbl8jHXVLgauqakNVfQq4B9izrTsVOKuqbp3J8UuSJEm9bMqJQZL+JC/seP/6JH+b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\nRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f07a3726850>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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+lknrLOBhYEdgW+AvwB2F/B2Ap0Or+Vrt2KbQai2tdmxTKusk/KXVKGAD3AgZ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\nTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f07a358e3d0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"show_histogram(\"tab_open_event_count\", 0, 2000, 25, \"# of tabs opened\")"
]
},
{
"cell_type": "code",
"execution_count": 67,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"users with no tab open count: 12,331,737 (9%)\n"
]
}
],
"source": [
"# how many users have a null tab_open_event_count? This could mean they didn't open any tabs... need to check how this behaves more precisely.\n",
"null_tabopen_count = sample.where(pyspark.sql.functions.isnull(sample.tab_open_event_count)).count()\n",
"print \"users with no tab open count: {:,} ({:.0f}%)\".format(null_tabopen_count, 100.0 * null_tabopen_count / total_users)"
]
},
{
"cell_type": "code",
"execution_count": 55,
"metadata": {
"collapsed": false,
"scrolled": false
},
"outputs": [
{
"data": {
"image/png": 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2yMqHkuYvDOmp7ZkzZ9LY2NilLJ/PM3Wql2cwMzMzs8Ft8uTJTJ48uUtZPp+n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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f07a38eec90>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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SMNgbOCgiTiTdptMREZ8n3cazVSOVkLScpE0kbZqtWit7vnpW9lNJW0paQ9KOwGXAv4Fr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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f07a3769a10>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"show_histogram(\"total_uri_count\", 0, 10000, 25, \"Total toplevel URIs loaded\")"
]
},
{
"cell_type": "code",
"execution_count": 56,
"metadata": {
"collapsed": false,
"scrolled": false
},
"outputs": [
{
"data": {
"image/png": 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SM4A30HzDf0+SXdufhW3/Tkk+nGT/JE9N8jLgn4AfAxeOcb4jgXVVNVTn4HLg\npUn2B/qBa6rq7i5cmiRJkjRnzIYnBkfRfIt/yaj2P6bZD/AL4Nk0G4oXAbfRJATvqar7hx+QZBfg\neJq3JAFQVauSnAKcC6xtzyNJkiRpmG1KDJLsDOxPszRn1db2Boylqrb41KKqNgOvnOC51gF7jtH+\nfpoiZ5IkSZLGMOXEIMnrgE/TLOnZHtg7ydFV9ZlOTU6SJElSd0x4j0GSx4xqOhF4XlU9r6r2BQ4B\nPtDJyUmSJEnqjslsPr4iye8P+/wAsMuwz7sC93VkVpIkSZK6ajJLiV4BnJ7kzcDRwLHA37evA30U\n8CDw5k5PUJIkSdL0m3BiUFU3Ar+XpA+4FPgITYGxvWg2H1/bbhSWJEmSNMdMuo5BVQ0AzwWeQ/OK\n0e2q6t9MCiRJkqS5a1JvJUryamAJcGVVvSXJi4HPJTmfpq7Af03HJCVJkiRNr8m8legU4DM0Tws+\nkeTdVXUpsBTYDKxO8qrJTiDJ8Um+l+TuJGuTfCnJM8YYtyLJbUk2Jbk4yV6j+k9NcleSm5IcNqrv\nkCRfnuzcJEmSpEeKyTwxeDPw8qq6IsnjgO8A76uq+4B3JxkAPgGcP8k5vBD4KPD9dj5/AVyUZMnQ\nE4gkxwHH0FQtvpGmWNmF7Zj7khwEHAocCOwNnJnkgqrakKSnHf/SSc5rRt18882sX79+UsfsvPPO\n7L777tM0I0mSJM1nk0kM7gH2AK4AnkLzlOCXquoampv8SamqVw//3L71aB3QC3yrbT6WJgn5Sjvm\ncGAt8BrgHGAxcElVraZ5cnFaO9cNwMnA6VV162TnNlNuvvlm9t57CZs3b5rUcQsX7siPfrTG5ECS\nJEmTNpnE4HjgrCQfAXYE3jQ9U2IRUDQ39STZA3gi8LWhAVV1d5LvAgfQJAZXAkcmWQQ8DVgIXJfk\nBcC+wNunaa7TYv369W1ScDbNlo6JWMPmzW9k/fr1JgaSJEmatMm8rvRzSS4A9gT+vap+1unJJAlw\nGvCt9gkENElB0TwhGG5t20dVXZTkbGAVsIlmydEm4AyaBOboJMcAdwJvG3buWW4JzRYOSZIkaXpN\n6q1EVXUXcNc0zQWaG/lnAr892QOragWwYuhzkhOBi2kqNC8H9gEOBs4C9hvvPP39/fT09IxoW7Zs\n2WSnI0mSJHXdwMAAAwMDI9o2btw4oWMnlRhMpyT/F3g18MKqun1Y1x1AgF0Z+dRgV2D1OOdaDBxG\ns4zoCODq0dBiAAAgAElEQVTSdiPyOTQbk3eqqnvGOnblypUsXTryW/rBwUGWL18+tQuTJEmSuqSv\nr4++vr4RbYODg/T29m712EkXOJsObVLw+8DvVNXNw/uq6gaa5OBlw8Y/Ftgf+PY4p/w40F9Vm2iq\nMm/ftu9AsyxpQUcvQJIkSZrjZvyJQZIzgD6aZT73JNm17do4rJryacAJSa6jeV3p+4BbgIfVJkhy\nJLCuqs5rmy4HTkyyP80TiWuq6u7puh5JkiRpLprxxAA4iuZb/EtGtf8xzX4AqurDSXakqZOwCLgM\neFVbQ+GXkuxC8/akA4baqmpVW5ztXJqlSIdPz2VIkiRJc9eMJwZVNaHlTFV1EnDSVsaso3lr0uj2\n99MUOZMkSZI0hlmxx0CSJEnSzDIxkCRJkmRiIEmSJMnEQJIkSRImBpIkSZIwMZAkSZLELEkMkrww\nyT8nuTXJg0kOHtX/mbZ9+M95o8acmuSuJDclOWxU3yFJHlYMTZIkSVJjxusYtHYC/g34NPCP44w5\nH3gzkPbzvUMdSQ4CDgUOBPYGzkxyQVVtSNJDU8PgpdMzdUmSJGnumxWJQVVdAFwAkCTjDLu3qu4c\np28xcElVrQZWJzkN2APYAJwMnF5Vt3Z42pIkSdK8MSuWEk3QS5KsTXJtkjOSPG5Y35XAfkkWJekF\nFgLXJXkBsC/w0ZmYsCRJkjRXzJXE4HzgcJrlQO8EXgycN/R0oaouAs4GVgFntmM3AWcARwFHtwnF\nZUmeOQPzlyRJkma1WbGUaGuq6pxhH3+Y5CrgeuAlwDfaMSuAFUODkpwIXAw8ACwH9gEOBs4C9uvK\nxCVJkqQ5Yk4kBqNV1Q1J1gN70SYGwyVZDBxGs4zoCODSdiPyOTQbk3eqqnvGOnd/fz89PT0j2pYt\nW9bpS5AkSZI6bmBggIGBgRFtGzdunNCxczIxSPJk4PHA7eMM+TjQX1WbkiwAtm/bdwAKWDDeuVeu\nXMnSpUtHtA0ODrJ8+fJtnrckSZI0nfr6+ujr6xvRNjg4SG9v71aPnRWJQZKdaL79H3oj0Z5JnkPz\nVqENwInAF4E72nEnAz8GLhzjXEcC66pqqM7B5cCJSfYHXg1cU1V3T+PlSJIkSXPOrEgMaNb8f4Pm\n2/wCTmnbPwu8A3g2zYbiRcBtNAnBe6rq/uEnSbILcDxwwFBbVa1KcgpwLrC2PY8kSZKkYWZFYlBV\nl7LlNyS9coLnWQfsOUb7+2mKnEmSJEkaw1x5XakkSZKkaWRiIEmSJMnEQJIkSZKJgSRJkiRMDCRJ\nkiRhYiBJkiQJEwNJkiRJzJLEIMkLk/xzkluTPJjk4DHGrEhyW5JNSS5Osteo/lOT3JXkpiSHjeo7\nJMmXp/s6JEmSpLlqViQGwE7Av9FUOa7RnUmOA44B3go8D7gHuDDJDm3/QcChwIHAccCnkjyu7euh\nKW72jum/DEmSJGlumi2Vjy8ALgBIkjGGHAu8r6q+0o45HFgLvAY4B1gMXFJVq4HVSU4D9gA2ACcD\np1fVrdN+IZIkSdIcNVueGIwryR7AE4GvDbVV1d3Ad4ED2qYrgf2SLErSCywErkvyAmBf4KPdnbUk\nSZI0t8z6xIAmKSiaJwTDrW37qKqLgLOBVcCZwOHAJuAM4Cjg6CTXJrksyTO7NXFJkiRprpgVS4k6\noapWACuGPic5EbgYeABYDuwDHAycBew33nn6+/vp6ekZ0bZs2bJpmLEkSZLUWQMDAwwMDIxo27hx\n44SOnQuJwR1AgF0Z+dRgV2D1WAckWQwcRrOM6Ajg0qrakOQc4MwkO1XVPWMdu3LlSpYuXTqibXBw\nkOXLl2/zhUiSJEnTqa+vj76+vhFtg4OD9Pb2bvXYWZ8YVNUNSe4AXgb8ACDJY4H9gdPHOezjQH9V\nbUqyANi+bd+BZlnSgumd9dxy8803s379+kkft/POO7P77rtPw4wkSZLUbbMiMUiyE7AXzZMBgD2T\nPAfYUFU/BU4DTkhyHXAj8D7gFuBhtQmSHAmsq6rz2qbLgROT7A+8Grim3bwsmqRg772XsHnzpkkf\nu3DhjvzoR2tMDiRJkuaBWZEY0Kz5/wbNt/kFnNK2fxb4H1X14SQ7Ap8AFgGXAa+qqvuGnyTJLsDx\nPPS2IqpqVZJTgHNpliIdPs3XMqesX7++TQrOBpZM4sg1bN78RtavX29iIEmSNA/MisSgqi5lK29I\nqqqTgJO2MmYdsOcY7e+nKXKmcS0Blm51lCRJkuanufC6UkmSJEnTzMRAkiRJkomBJEmSJBMDSZIk\nSZgYSJIkScLEQJIkSRJzJDFIcmKSB0f9XDOs//8kWZvkjiR/OurY/ZOsSjInrlWSJEmaCbOijsEE\nXQ28jIeqIz8AkORZwHtpqhpvB5yb5MKq+mGSBcDHgLdU1YMzMGdJkiRpTphLicEDVXXnGO2LgSvb\nImkk+UHb9kPgncClVTXYvWlKkiRJc89cSgyenuRWYDPwr8DxVfVT4CrgGUmeDCwAng5cleRpwJuA\n3pmasCRJkjRXzJV1998B3gy8AjgK2AO4LMlOVXUt8OfAV4ELgHdV1Y+Bj9M8MXhVkquSXJHkhTMy\ne0mSJGmWmxNPDKrqwmEfr07yPeAm4PXAZ6rqk8AnhwYkeRNwN01C8SOapwa7A19I8htVdX/XJi9J\nkiTNAXMiMRitqjYm+TGw1+i+JDsD7wFeCOwP/KiqfgL8JMn2wDNo9h+Mqb+/n56enhFty5Yt6+Ds\nJUmSpOkxMDDAwMDAiLaNGzdO6Ng5mRgkeQxNUnDWGN2nAqdU1W1JngdsP6zvUTT7EMa1cuVKli5d\nOqJtcHCQ5cuXb9ukBcDNN9/M+vXrJ33czjvvzO677z4NM5IkSZo/+vr66OvrG9E2ODhIb+/Wt93O\nicQgyV8C/0KzfOjXaV5Pej8wMGrc7wJPr6rD26ZVwOIkr6RZSvQAzdIizYCbb76ZvfdewubNmyZ9\n7MKFO/KjH60xOZAkSZomcyIxAJ4MfB54PHAn8C1gWVXdNTQgyULgIzT7DgCoqluT/E/gMzRvMzq8\nqu7t5sT1kPXr17dJwdnAkkkcuYbNm9/I+vXrTQwkSZKmyZxIDKqqbwJjNjPG3WZVnQmcOR3z0lQt\nAZZudZQkSZK6Z668rlSSJEnSNDIxkCRJkmRiIEmSJMnEQJIkSRJzZPOxNFVTqZtgzQRJkvRIZGKg\neWuqdROsmSBJkh6JXErUEQNbHzInY3U7XmdjjaybcMWonw+M0XYFcDabN2+aUnXmLRldmnw6dTNW\nt+PN11jdjjdfY3U73nyN1e148zVWt+PN11jdjjefr20iTAw6Yu7ePM+ueNMVa6huwvCf74zRtpTJ\nFV6bOP9PzVizKd58jdXtePM1VrfjzddY3Y43X2N1O958vraJcCmR1CFb2s+wceNGBgcHx+xzT4Mk\nSZoNTAykDpjIfobe3t4x26eyp8EkRJIkdZqJgdQBI/czjLUcqR9YOUb7GjZvfiPr16+f8A17t5OQ\noZiTTUSmmoSY9EiSNDNMDB6yEGDNmjUP63io7Tzg4f1wC/C5MdpvGHX8xGw5XjdjdTbeI+Pf8YZx\nRvx8jDlMLd6aNWvapOAIYLcxRvw98N/HaL+dzZs/zWWXXcaSJRPfS3H77bfz2tf+Iffdt3ncMWMl\nIjvssJB//Mf/x267jTXHzsaaarw777xz3CTklltu4XOfG+tvpElCnvCEJ0w4zkRsKenptPkaq9vx\n5musbsebr7G6HW++xup2vPl6bcPuMxZuaVyqatonMxckOYyx7xQlSZKk+eANVfX58TpNDFpJHg+8\nArgRGP/rSkmSJGluWQj8BnBhVd013iATA0mSJEnWMZAkSZJkYiBJkiQJEwNJkiRJmBhIkiRJwsRA\nkiRJEhY40xiS7E5TOetB4Cdbeq2VxpdkAbAz8GBV3TlfYs1EPEmSNP18YjAFSfZMcniS45L8WZLX\nJXnsNMXaKcmLkvz3JIck6U2SaYr1jiQ30ZTj/TbwHWBdkm8lGbvcbGfiLkiya5LOlpKdoVhJfi/J\nN4F7gNuAO5L8LMnftUnXnIw1E/HamPPq70OSpNnKxGAS2pv0fwCuA/4W+CDwp8DfA7cmObqDsbZL\n8mFgHfAN4PNtnFXADUkO6lSsNt7/AZYDfwm8DfgRcBLwe8BPgG8m2a/DMefdDXSSPwIGgO8Bf0Xz\n39+HgXcBTwGuSPL0uRZrhuLNu78PSZJmMwucTUKSTwD7AEfRVEf+C5qb5vcChwIfBY7cUqnpScT6\nEHAw8M421ruBc4F/Bg5r2w+uqou2NVYb7wbgHVV1fvv5GTRPDZ5YVQ8k+WtgSVW9vEPx/gg4Hfgk\nzfUdQZNs3UTzb7kP8Pyq+vc5FmsNcFJV/X37eT/gS8DuVVVJvgDsUFWvnUuxuh1vvv59SJI0m5kY\nTEKSO4FXVtUV7edfo/l28fFVtal9YvCWqtq3A7FuA/57VV3Wfv514Fpg56q6N8m7gVdV1fO3NVZ7\n/nuAfarqxvZzgPtobvpuT/Ic4FtV9asdijcvb6CTbAKeOfTv2LbdDzy1qm5L8jyacuS/NpdidTve\nfP37kCRpNnMp0eQ8Crh72Of/bNt2aj9fBCzuUKzHALcO+3w7sBAYuun6IvCcDsUC+DHwu8M+/w5N\nYnBH+3kz0Mks8qnAd4c+VNX3gSfSbHoGOLWdw1yLdSPwyyVXSZbSbOJe2zZtALafg7G6HW++/n1I\nkjRr+VaiyVkFHAsc034+Frhz2FtZHkOTLHTCVUAf8IH28+uB/6yqoRv17YB7OxQLmmVRZyc5kCYJ\neC3wkXrokdJLgKs7GO9GmpvMG6FrN9DdiHU68Kkkz6X5d3wL8HdV9Yu2f3+aJGyuxep2vBuZn38f\nkiTNWiYGk/Mu4OIkr6P5Nv2JwJuG9T8fOK9Dsd4DnJvkYJqbsOcDfzas/5XA6g7FoqrOSfJz4I00\nT0D+tKr+ZtiQ/9f+dMq8vIGuqtOTPEjz7/homrXq7xs25Hs0e0TmVKwZiDcv/z4kSZrN3GMwSUl2\nA/4bzY3R16vqmmmM9RyaJwWPplm7ffF0xZoJSd7OQzeZFwLvq6rNbd/TgQVVde1ci6XO8O9DkqTu\nMjHQhCR5FPCkqrp5pucyF7Wbubcb9i20JEnSrOLm40lKY4/2RpkkO6QpPnZ4kp07GGfaCopN0T40\nhc/mtCS7J9k/yXOTPH4azv+oJO9PcmmS97Ztf0az92RTks8m2aFDsX6e5NNJOvJmqm2V5DlJ5nTi\nM91/H5IkzWYmBpOQZG+am+PrgTVJ9qB51/+ngY+1bZ0q8LQqyXVJ/jzJkzp0zlkjyfOSLBj2+b+1\nN9O3Jvl+ksM7HK9bVZ1PpFmj/n3gD5N8DPifwFuBI4GXAf+rQ7F2oln//q0ka5L878x8xd6OVOWe\nx38fkiTNWi4lmoQk/0Rz43MC8D+AV9BsSjyEJsn6B2BjVf1RB2I9CHwK+H3gcTTrnj8F/Mt0LEdJ\nMriVIb8CPKOqFmxl3ETj/QLYrarWpani/E/A39FsYN0XeDPw+qr6Ugdi/R+gn+bNS5tpqlUP0Lxl\n6jDgdcCL29dUbmus64Fjq+orSfaiqSB92LB35L8eeHdVPasDsR7koddqvoXmWh4DfIXmb+WC6uD/\nwJP841aG9AAv6cTfyHz9+5AkaTYzMZiEJOuAl1fVvyXZCfg58KKq+lbb/3xgoKqe2oFYQzd9G2iS\ng6FEZD3wWeDTVdWxN6Uk2Qx8gfGXC+1GU9W5U4nBgzRVldcluYymeNrxw/r/HDioqg7oQKyuVXVO\n8l80CdRPh33ed2jjavuU6cqqemwHYv3y37D9/Gia18weQfPe/duAz1TVe7Y1Vnv++4GLeeg1nqM9\nDvhvHUoM5uXfhyRJs5mJwSSkqfy6eGgDbvt6z9+qquvbz08B/r2qFnYg1oibvrbt12kShDcDvwFc\nXlUv2tZY7bm/T5NsfGyc/t8CrpimxGAt8OqhitJt/97AdzpURbdrVZ2T3AH8blVd1X6+nOab7Vvb\nz4uB71ZVTwdi/fJb9TH6foMmQXhTVe2+rbHac/4A+Ouq+vQ4/R37G5mvfx+SJM1m7jGYnNuA4TdZ\n7wSG35Q9AfiPDsV6WMZWVbdW1fuq6mnAy4GfdigWwOXA3lvo/znwzQ7GA3hmkmcD/8XYf4udqrPR\nzarO1wBLhz5U1W8PJQWtZwH/3qFY467nr6obq+rdNFV9O+UKhl3bGO4FOvnWqvn49yFJ0qxlgbPJ\n+SqwGPgWwBjfrr8c2Npa/Yna4ibOqvoa8LUOxaKqjt1K//U0N0yd9DUeus7fplnTPWRfOneT2c2q\nzkcB92+hf3vgwx2K9V62Umm7k3sMaK5t3KcBVbUG2KOD8ebj34ckSbOWS4k6qF0/vrmqbu/AuV5M\ns1TogW2f2eyTZPQ32f9ZVXcN6z8coKrO6lC8VzGsgNXwqs5Dr6UcHl8zy78PSZK6z8RgGyV5MnBb\nVT0403OZTu1m696q6vRyIs1xSXYFHm3xO0mS5jb3GGy7a2g2Ak+7JHcn2bMbscawF/CNbgVLUyis\nI5tmux2rfSf+V5Ock+Rlo/p2TvKTORrrV5OcneSmtIXakpwO3A7c0NYZ2Oa3LW1lDrt28e+ia7Ek\nSZoNTAy2XUcKOs3CWDOtm5WWOxYryZ8AfwlcS7MZ97wkxw8bsoAObQjuZqzWB4Fe4K9oNuGfA7wI\neCHN/pOdgeM6EaibSchsSHgkSZoN3HwsAJJs2MqQjrym9BHgbTT1Hj4PkKby8T8l+ZVO1ROYoVjQ\n1NN4U1V9I8kXgVuAg6vq8jb+O4FTgOUdiDU8CXktTRLyNJokZAFNpfHj5mAsSZJmLRODbfdBmiJk\n3XA2cPc0nfvRNDdAV43T/1TgxE4Fy8QqLc+5WDRv5fn20Ieq+naSlwJfTbI9cNocjQWwC3BdG+u2\ntnjb8CJ7VwNP6VCsbiYh3YwlSdKsZWIwSUl2pikydgBNZWKA5yX5NvC3VXXndMWuqrdP17mBfwN+\nWlWfHauzLfLUscQAeCZbr7T8jDkYaz3NzfGNQw1VdXV7w/514EkditPtWAB30dTqGKqf8WXgZ8P6\nH0OzpKkTupmEdDOWJEmzlonBJCR5LnAhsImmpsHQzcOuwJ8A70ryiqr6fofi7QC8hpFJyB003xJ/\nuaru60Sc1rnAoi30bwA68mrI1tU0FYC3VGn5yDkY61s0y1EuG95YVde0m4M7uYG7m7EAfgA8l7ZW\nR1UdNqr/ucCaDsXqZhLSzViSJM1aJgaT81HgH4CjRheOShLg4+2YA7Y1UJK9aJKQJwHfBda2XfvS\nFJq6Jcmrquq6bY0FUFUf3Er/T4E/7kSsVjcrLXcz1odo1qs/TFX9sP02/3VzMBbAG4AtvZZ3LZ1b\nbtPNJKSbsSRJmrWsYzAJ7RKDfavq2nH6FwOrq2qb16wnuRi4Bzi8qu4e1fdYmm/vf6WqXrGtsaTZ\nJsnjgAer6mfj9L8K+K+qumQuxZIkaTbzdaWTcwfwvC30P4+HvtnfVr8NnDA6KQBo295N89aUaTPD\ndRPmjSRXJenKGvVuxprOeFW1Ybwb9bb//E7dqHczliRJs5mJweT8FfDJJH+d5OD8//buPP7u6c7j\n+OttKxpq+hg7SUgjoSSIMlqllqHU0GjVMoMoo0IaE1QZNMYeWyy1FNFay2jttY29jF2YkNgqpIi1\nQeyJfOaPc27y9c1vya+/7+/+7u/m/Xw87iO/7z3nfj/nfu95PHLO93sWaYP82k7SGaShRCdVFOs9\n2t44rS9fHgfdFeq6b0ITN6D7Ags3Yay6xmvi+mFmZtYQPMegAyLibEnvAKOA/Ziztv8XwOPAsIj4\n74rCXQhcIukY4E7mPIlYFtgcOII0n6GZ9KV5G9DWeX1x/TAzM+sy7hh0UERcBVyV14n/x/z2OxEx\no+I4v5L0EfAL0hrqtckgIg1pGhMRVT2daE1X7pswP/kz8EkTxuqOeGZmZtZFPPm4B5C0CnOWK30z\nIl7qzvJ0FUk3A3tFxNRmimXVcP0wMzPrWu4Y9DCSPgcGR0TlyyfWed+EpiZpfea+jg9GxCM9OVZ3\nxDMzM7P6cMegQUk6rZWkA0hDfN4FiIgDK4rX2r4JywIbAK8Cle2bUIjbVA1oScsAfyStKjWFL1/H\n3qQ9FX4UEW/1pFjdES/HbKr6YWZm1sjcMWhQkmYBTzH3ykObAI+R9jiIiNisonh13TehWRvQkv5A\n6lztGRHPldIGABcBr0fEjj0pVr3jNWv9MDMza2TuGDQoSYcC+wB7R8RdhfdnkIYSTaw43sfA+hHx\ndCvpawEPR8TiFcVryga0pOnAxhExvpX0IcA9EbFET4pV73jNWj/MzMwamVclalARcaKkO4HLJN0I\nHFb1ykcltX0TWuwYUP2+CVuRGpnPlRMi4jlJI4F7emCsz4Al20hfIufpabHqHa9Z64eZmVnD8gZn\nDSwiHgWGAEsDj0lakznLllattm/CKEmDJC2bX4MkjQJ+B5xfYbxmbUBfBVwsaWgeggWk4ViShgK/\nBX7fA2PVO16z1g8zM7OG5ScGDS4iPgT2kLQzcAdzNlWrOk69902oNTJHAXfW5jXkBufmwGlU34Cu\nR6wDSR3uK4GF8ipSAIsAM4FxwME9MFa94zVr/TAzM2tYnmPQg0haifQE4Y6I+KgL4xT3TXgjIiZ3\nQYyvAKcDPyV1UFtqZI6KiE7fqa1nrELMJYH1SBNYIXWuHi9P7K4w1hC+vJpOl8SqV7xmrx9mZmaN\nyB0D61b1bNTWuwFtnef6YWZmVj/uGNhskkYA6wM3R8SVknYDDiMNH7kG+FVEzOzOMvYE3b1RnKSX\ngK0i4oUuOPe2pDpyW0Q8IGkz0vChBYBrIqLKeShmZmZWR55jYABIOgI4BLgdGCupD2m+wVhgFjAK\nmAGMrjjuSsB7eS5F8f2FgQ0j4r6KYnwaEe/k4+8C+5LWqH8FODsiHuxsnHzu1jaKWyfHfFVSJRvF\n5dVyWtIb2FPSGwARcWZnY+V4PwN+Tdpf4wBJ+wPnkMbofwGcLmmxiDijing5ZlPVDzMzs0bmJwYG\ngKQXgUMi4hpJg4HHgT0i4vKcPhQ4KSL6VxRveeB60tCNAK4A9qs1ACUtS1o7vtOTrSU9DBwTETdJ\n2p709OMmYBKwGrAtsENE3FRBrLptFJc3wXuNNA6+qA/wOqkjFxGxamdj5XjPAGMj4kJJmwI3AwdF\nxDk5fRipDq1RQaymrB9mZmaNzB0DA2ZvcDYwIqbk48+BdSLimXzcB5gYEV+tKN7FwABgBLAUcCKp\nAbhlREzLDb+pEdHpJXUlfQisFRGTJT0EXBsRYwrpI4CfRsS6FcSq20Zxks4DNgB2jYhJhfe7chO8\nch1Zt/ZdJfUFnqmijjRr/TAzM2tk3sfAat4A1gCQ1J+0LGrxzu83gbcqjLcFMDIiHouIO4DvAFOB\nuyR9Peepqtc6k7QWPcAqwC2l9FtIjdAq1DaKa01fKtooLiL2BY4GbsuN1672LulpBJJWIA1F7F1I\n7wP8raJYzVo/zMzMGpY7BlZzOWmDswtIY+RPAk6RNFzSPsB5wLUVxvsaMK12kJeC3AF4GbgbWKbC\nWPcCu+S/xwPfK6VvShqSU4W6bhQXEdeSJjkPlXSLpOXa+0wnXA+Mk3Q4qS5cApwqaWtJWwJnkeao\nVKFZ64eZmVnD8uRjqxkNfEJqZF5AGrrxFKmDsDhwI3BkhfFeAgYBs1fOiYiZknYEriaN8a7KocCf\n813u+4HjJH2LNIZ8ALATabJpp3XDRnFExGuStiB9z/E5Vlf4JWlt/51JKyz9HBgJXAcsTGpgH1ZR\nrKasH2ZmZo3McwysW0gaA6zd0iRcSQsBfwT+pYox5Pmc/YBjgR8AvfLbM4FHgZMj4roq4pRidvlG\ncS3EHAJsBFwSEdPay19RzEWBhSNieoXnnJf6sW0Vk4/zOfsBxwHbUKf6YWZm1mjcMbBukRt3i7e2\neVROXzEiXqk4rkjDUBYA3omIGVWe36rh+mFmZlZ/nmNg3SIiZrazo+zyVLxnQo4bEfFmREytNfok\nrSzpoqpiSFpM0kaS5lq2U9KiknbvibHqGS9vpLeipD0lDcznHyjp3PxbbVxlp0DS6pL2BFaLiDdJ\ncxzOlHRR3sTNzMys6fmJgTWkvJfCE1UNFalXLEmrkSbg9ibNL7gf2Dkipub0Ktffr1useseT9H3S\nZOcPSXNchpImOz9FuqGxCWnp0rt6UiwzM7NG5o6BdQtJ27WTZVXg1IoamfWMdS1pIu4w0vr7p5OW\nff1eREypuPFct1j1jifpf4G7IuIISTuTdlg+NyIOz+knAEMiYsueFMvMzKyRuWNg3SLv2hu0vYJO\nVNTIrGesN4EtImJCPhapobkNadnLj6iu8Vy3WPWOJ+l9UmP8RUkLAJ+RNo4bn9PXBO6IiE4vz1rP\nWGZmZo3Mcwysu0wFdoiIBVp6AVXuMlvPWIuRVrMBZs9pGE5a7vVeYLUeGqs74kWOMwv4FHi/kDad\nNA+gJ8YyMzNrSO4YWHd5HBjSRnp7d/gbNdazwHpzBYgYQRrHfkNFceodq97xXgb6F443BKYUjnuT\nOnw9LZaZmVnDcsfAusvJpE2yWvMiaXhKT4t1LXN20f2S3ID+PdV1QuoZq97xzgVmD0mKiKfzSkU1\nWwNVTQauZywzM7OG5TkGZmZmZmbmJwZmZmZmZuaOgZmZmZmZ4Y6BmZmZmZnhjoGZmZmZmeGOgZmZ\nmZmZ4Y6BmVnDkDRZ0shmidNTSeojaZakQc0Qx8xsXi3U3QUwMzNrMFOA5YB36hDLa4abWcPwEwMz\nM+t2khrmRlUkb0XErDqEq3ITwnkP2kDX28wahzsGZjZfk3S3pLPy6z1Jb0s6upTn3yQ9KukDSVMl\nXS5p6VKe7SQ9L+ljSbdL2i0PE1mykGcjSfflPK9IOkPS4m2UbWVJ10uaLul9SVdJWqaQvqqk6yS9\nkVLvMukAAAfBSURBVPM8Imnz0jmWlnRjjvkXSbu2EOeoXJ5PJb0q6fQ2yjRa0nhJ+0iaIumjXK4l\nSvn2ljRR0if53+GFtNoQmp9IukfSx8Bc5WqvbJIWkXRKfv9DSQ9K2qSQ3lvSDZL+ltMnSPp+Tlsq\n/45v5WvznKQ9SuUbVDjXJpIezuV4XdIJkhYopN+df88xkt7N9WR0a9expJ+ku/K1fFLSP5WuwY8k\nPZ1jT5Z0YCl9lqTtSu9Nk7R7R6+3mc3f3DEwM4PdgRnAt4CRwIGS9iqkLwQcAQwCtgf6AL+tJUrq\nC1wNXAMMBi4EjqcwTERSP+CWnG9NYCfgO8BZLRVIkoAbgKWA7wJbAKsCVxay9QL+BGwKrJ3Pf4Ok\nlQp5LgZWBDYBfgzsB8zu1Ej6MfAfwL8D3wB+CExo5TrVfAPYEfgBsBWwDnBO4Zz/ChwFHAYMBP4T\nOFrSbqXznACMBVYHbmvhGrRXtrOBDYCfAGuRru0t+VqTy7QIsBHpmv8S+DCnHZvLtlX+dzhfHjpU\n/O1WIF3nh0l1YF9gL1KdKNo9n3994BDgV+WOWiuOBU4i1Z3ngStqnQ5JQ4CrgCvydxgNHFNr9HdQ\nm9fbzIyI8Msvv/yab1/A3cDTpfdOKL9XSl8P+AJYvJD/qVKeY3KeJfPxBcC5pTwbATOBRfLxZGBk\n/vufgc+BFQr5VwdmAUPaKNsEYL/892o5/7qF9AH5vVqcUcAkYMF5vF6jc7mWK7y3Vf4ey+TjF4Cd\nSp87HHgg/90nl2FEO7FaLRuwMqkzt1zp/f8Bjs1/PwUc2cq5rwcubCWtVr5B+fg4YGIpz3Dg/VI9\nureU52Hg+Da+Xy3OsNJv/AWwWj6+DLi19LkxwITC8Sxgu1KeacDuHbnefvnll19+YmBmBg+Vjh8E\n+ue79kgakoekvCLpA+CenK93/ncA8GjpHI+UjgcDw/KQn+mSpgO35rRVWijTQOCvEfF67Y2ImAS8\nR2o8IumreSjNxDx0ZHr+XO/COWZExBOFczyXz1FzNbA4MFnS+ZJ+KGnBFspTNCUi3igcP0h6Aj1A\naWhUP2Bc6bse3sL3fLydOG2VbS1gQeD5UpyNc3yAM4EjJd2fhyStVTj3ucAueVjUGEkbtlGOgfk7\nFj0A9Co9nfm/Up6pwDIAks4tlPODUr4Jpc+o9jnSb/1AC7Fn188OaO96m9l8zh0DM7M25IburaTG\n9K6kpwVDc/IiHThVL+A3pKEog/NrEOmu/l/+zuKdShradCjp6cNg4OmOlCsiXs1lGA58TBqec+88\ndA5a0yv/uzdzvudg0jCYcuP7ow6W7ZxC2XqRnlKsW4qzOnBA/vw4Umfkkhz/UUn757RbSR2o04Dl\ngTslnfR3fueaGeWvwJz/Z48slHHtNj5XG8LUkf+fg7knMS/cQr42r7eZmVclMDNL49SLNgReiIiQ\nNBD4OnBYRLwGIGn9Uv7ngK1L75XzPAGsERGT57FMk4CVJa1YiLsGac7BMznPt4HfRcQNOb0X0Ldw\njmeBhSQNiYjHc54B+RyzRcRnpDH0f5J0Tv7cWsCTrZStt6TlCk8NNiQNf3k2It6W9DrQLyKubOXz\nMI/LdLZRtvGkJwbLRkT5jnrx868B5wPnSzqeNF/h7Jz2LnApcKmk+0nj/A9p4TSTgB1K720ETM+d\nl3n5Hu/Q8vKn7V2HSaS5KOXYz0dE7bNvkzo3AEjqT3rS0pE4ZmbuGJiZkRq6p5AakEOAEaTx7ZDW\ntP8cGCnpPFKjtDzp9DfAKEknAuNIk3H3yGm1BtkY4EFJZ5EmJ38EfBPYIiJ+Xi5QRNwh6Wngckmj\nSHeAzwbujojxOdsLwA6SbsrHR1O4cxwRz0u6jdQoHk5qvI8l3X0HIK/EsyBpPPzHwG7531fauF6f\nARdL+gXwNeAM4KqIeDunjwbOyENmbgW+QnrSslRE1FYVancYTFtli4hpkq4ALpF0MKmjsAywGWm+\nxy2SxpImZD9P6txtCkzM5/4v0tCaZ4BFgW1raS04Bzgg/3a/Jg0tOor0xKaz2rsOpwKPSDqCNAn5\n28D+pAnQNXcBIyQ9RPp//URSne1IHDMzDyUyMyMNNVmMNC/gLGBsRFwIs+/0DiOt6PMM6Y7yQcUP\nR8TLOX0oacLrz0gTViE1oomICaSVgfoD95GeIBwFvFY8Valc25Emkd4L3A68COxcSD8wpz9Amkx7\naz5v0bAc4x7gD6ROzFuF9PdId9Hvz2XfDNg2IqbRuhdIKzDdnGM+SWqskr/rONJQoj1J4+7vIXWU\nik9L5uUOdntlG0b67U4hPUm4htQBmZLTFyQ15Cfmsj5bKOfnpJWjnsrlmwns0lL58jyPbUirVj1J\n6ihcwJzfeF6/T0ta+lwx9njSqks7keYiHAUcERGXFvIfBPyVVK8uA06m0PnrZPnMbD6iOU8izczm\nP5LuBsZHxIHtZu7YeQ8H9omIPlWet7vltfm3j4h1u7ssZmZWLQ8lMjOrQB6q8yjwLmkM+MGkVXHM\nzMx6BHcMzGx+V9Vj0/6kuQf/QBrKcjJprLeZmVmP4KFEZmZmZmbmycdmZmZmZuaOgZmZmZmZ4Y6B\nmZmZmZnhjoGZmZmZmeGOgZmZmZmZ4Y6BmZmZmZnhjoGZmZmZmeGOgZmZmZmZ4Y6BmZmZmZkB/w/u\nFTDBBJi58gAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f07a399b6d0>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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T0FRJO/VNM/kIcDHwIHAJ8DwwPiJeKGnfMFL3pm92lkXEM8B/5XYfCUyIiDf7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\nAACIYAAAAEQwAAAAkvwCzYL+g7mXCVEAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f07a3948890>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"show_histogram(\"total_uri_count / subsession_length_sum * 60 * 60\", 0, 1000, 25, \"pageloads per session-hour\")"
]
},
{
"cell_type": "code",
"execution_count": 57,
"metadata": {
"collapsed": false,
"scrolled": false
},
"outputs": [
{
"data": {
"image/png": 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kST1gqpuP/wL4UpJ7aM4C+HqSH0/UsKqesAFYkiRJ0uI2pcSgqt6d5HM05wh8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\nJWgvAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f07a3ac4290>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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fQJIkSVrg5nwqUZKLgRU003yeSvLytmqkqra0/78AOD3JPcB3gTOB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\nrQAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f07a38d8d10>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"show_histogram(\"total_uri_count / tab_open_event_count\", 0, 500, 25, \"page loads per tab-open-event\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Other checking"
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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wJnCCpMeAJ4FTgWeAZe5dcZpjM7P6dWRwoec0x1+MiNMlrQycR0p1fCuwR0Qs\nLFbiNMdmZo3pyOBSQ5pjIuJk4ORe5nGaYzOzBix351zMzKzvObiYmVnLObiYmVnLObiYmVnLObiY\nmVnLObiYmVnLObiYmVnLObiYmVnLdeRNlL3JIxyfVDb54YjYJJd/HfgG6e7+0yPix4VltwZ+Cmwd\nEYv7qckD3qxZs+jq6qp5/jXXXJMRI0b0YYvMrJ2Wy+CSPUAavLI0/tibAJI2A75DGjdsCPBHSVMi\n4kFJKwA/Aw5xYFlq1qxZjBw5ivnz59W8zNChK/PIIzMcYMw61PIcXN6MiBcrTN8YuDcPIYOk+/K0\nB4FjScPtT++/Zg58XV1dObBcAoyqYYkZzJ9/AF1dXQ4uZh1qeQ4uG0p6FpgP3Al8M4+YfD+wkaR1\nSEPpbwjcL2l94CDACSCqGgWM7nUuM+t8y+sJ/T8BBwO7kdIWrwfcmpN+PQx8C7gOuAY4PiIeJeV0\nORbYQ9L9kqZJ2qEtrTczG+CWyyOXiJhSePqApLuAp4DPARdFxM+Bn5dmkHQQ8AopKD1COnoZAVwh\n6f0R8Ua1dTnNsVn7Oc1x/1sug0u5iHhZ0qOkBGPdSFoTOBHYgZSt8pGIeAJ4QtKKwEak8zEVOc2x\nWfs5zXH/c3ABJK1CCiwXVyj+MfCjiJgtaSuWpjiG9Po5xXE/qfdyZ/Alz2btslwGF0lnAFeTusLe\nS7r0+A3g8rL5PgFsGBGlbJN/ATaWtDupW+xNUjeZ9bFGLncGX/Js1i7LZXAB1gEuA9YAXgRuA7aJ\niJdKM0gaCpxNOg8DQEQ8K+krwEWkq8wOjIgF/dnw5VX9lzuDL3nuXz6ytKLlMrhExLga5plPhW+x\niLgQuLAv2mW18OXOA5GPLK3cchlczHriX+D185GllXNwMSvoz1/gnRnEfGRpiYOLWUF//QJ3ELNO\n5+BiVlHf/gLvxCBmVuTgYtZWnRHEzMo5uJgtF3wuxPrX8jpwpZmZ9SEHlwHn8t5n8Xo6fD2dtC39\nuR4bSBxcBpxO+8B7PQNzHZ24HhtIHFzMzKzlHFzMzKzlfLWYmQ0q9d4U6htC28PBpe8MBZgxY8Yy\nBUunTQLKy58BLq1Q3cyyZXs3cNfT6nV02nqWh32gsfU899xz7LvvZ1m4cH7Ny6y00lCuvPJ/efe7\n391temG9Q2uuzGqmiGh3GzqSpP2p/Ikys4Hl8xFxWbsb0WkcXPqIpDWA3YAnSblfzGxgGQq8H5hS\nzOVkreEbys5pAAATz0lEQVTgYmZmLeerxczMrOUcXMzMrOUcXMzMrOUcXMzMrOUcXMxqJEntboPZ\nYOGbKNtI0prAF4FtgbXz5OeBO4BfRsSL7WqbVbRA0hYRUftdf2bLKV+K3CaSPgJMAeYB1wFzctFa\nwM7AysBuEXF3P7RlXeA7EfHFJut5GzAGmBsRD5WVDQU+FxEXN7OOXNcoYBvgzoh4WNLGwNHAW4FL\nIuKGJuv/cZWio0kpHV8CiIivNrOeKuseBnwO2AB4Dri82XswJI0G/h4RM/PzLwCHASOAp4CfRsQV\nTTU81fsTYGJE3NpsXTb4Obi0iaQ/AfcCh0XZm5C7X/4b2Dwitu2HtmwBTI+IFZqoYyPgWtIXVgC3\nAftFxHO5fC1gdjPryPXsDlwFvEYKwPsAF5NeyyHAjsCuzQQYSYtzff8oK9oRuBt4HYiI2KnRdRTW\n9RCwfUTMzUH+FuAdwKOkAPMGsE0pMDS4jnuBr0XEdZIOAc4GzieN0zISOAQ4OiIubHJbFpPe+8eB\nXwC/iojnm6nTBi8HlzaR9E9gy4h4uEr5xsA9EfG2Fqxrr15m+QDwoyaDy++AFYGDgeHAmcAmwNiI\nmNXC4HIHcENEnCBpP+Bc4GcRMT6Xfx8YExG7NrGO44FDgUOKQUrSG8AW5UdlzchfyGtHxAuSLgHW\nAz4ZES9LWgX4HfBiROzfxDrmAaMi4ilJ00mv1/mF8v2B8RHxwRZsyyeAPYHPA6sBk0mBbFJELG6m\nfhtkIsKPNjxIo/Yd2EP5gcCTLVrXYmBR/lvtsajJdcwBNis8F/AzUrfLB0jdfU2tI9f7MrBB/n8I\n6Zf9loXyTYHnW7CejwCPAD8EVszT3gA2afF+sBh4V/7/ceATZeUfBWY1uY4uUsAtvU9blJWvD8xr\n8basSOreuwZ4E3gW+F7pvfOj8x++Wqx9fgj8XNJZkvaStHV+7CXpLFK32OktWtdzwL4RMaTSAxjd\ngnW8jfQlAqQ+o4g4HLgauBnYqAXrWFJ9Xsdi0rhtLxfKXiX9Ym5uBRF/IZ0/eidwt6RNS+vtA6V6\nh5Leq6JncxuaMRk4PP9/M/DZsvLPAY81uY5uIuKNiJgYEbuTflycTzqaeaSV67GBy1eLtUlEnCOp\nCzgGOAIodRctAqYBB0fExBatbhrpi/Kqas0hHWk042Hgw5SNtx4RR+YreH/fZP0lTwIbkn7lQ7rS\nblahfATLfkE3JCJeAw7K3W/XsfQ9arXrJb0JrEo6B/JAoex95AsImnAccLukm0nnjL4maSxLz7ls\nQzp31SciYhZwsqTvALv01XpsYHFwaaOI+A3wG0krAmvmyV0R8UaLV3UGMKyH8seAjze5jt8B44Bf\nlxfkADOEdIVSs35G4Us+Ih4oK98DaOpqsXIRcYWk20gB+qlW1g18p+z5a2XP9wSauvoqImZL2hI4\nPtcnYCtgXeB2YLtozVWJT5F+HFVrRwBTW7AeGwR8Qt/MzFrO51zMzKzlHFzMzKzlHFzMzKzlHFzM\nzKzlHFzMzKzlWh5cJM2UdFQd8x8kaW7h+UmS7ml1u3ppw46SFklatT/XW6Utp0r67xbXubinIWAk\nvS/Ps3kr19sOktaSNFXSa8X9qmyeiyRd2c/tOqhae1q8nn7//Fj/a+B7tuHPuKQ7JdV9H1RdwSV/\nKE+sdyW9uIJl796u+froHBgaHtQvux14d0S80mQ9Tcnjbx0FfLfFVa9Nuku7J51yTfoxpKFmNqe1\nowI0q9J+3lc65b206j4M/LzOZXrcL/IPoL9XKPoucFqd62p/t1hELIiIrmarabINb0bEC022oRUO\nAW6PiGdaWWlEvFDDjZmdkghrfWBaRDzRgv2qZVq0n/eJfBPvgCZpSKcna6tnGyPipYiYX+8qaiiv\n9F06GXi7pD3qWVlTwUXSOyVdLWmepMfz6Krl8xwj6b7cTTFL0jk5Z0WpvFq0RNIOkhZKelfZ9DPz\nUBa1tLF0OPj/JN0u6Z+S7pf0scI8O+Z5Vi22SdKukh6S9KqkyfnIorTMCpLOzvO9IOl7kn6ZRwcu\nzfPZvO3zJHVJulYp50k1+5HG4iq2X5K+KemJXM89kj5TKHta0n+ULbNl7uZbNz/v1i0maStJ0/Nr\ncRewJWU7laRNJU3K2/68pIslrVEov1FpXLTTJL0k6TlJJ5XVsZqk8/Ly/8yvxScL5dtLuiVv11O5\nvpV7eH2QdLikxyQtkDRD0gGFspnAvqQhWxZJqmkI+Z5e41w+RNIFhfKHVeiSkPSJvH2rltV7lqTr\n8v8HF/dz5e4rSQcodXH8Q9LlZZ+NVSRdqvTZeVrSV/LrXi3fTHHdhyp93l6X9Jti25R6IH4n6VuS\nniUN3YOk4fl9npuXmyRpg8JyL0jat/D8r3n50vPtJc1Xyt2DpJPz+zpf0jOSzizMu5KkH+bpryl1\nvexYKC99BveU9CBpDLl1q2zrjpL+nNczW9L3lUaEKJX3uq9WqFOSTsyv+/z8Xu1WKL9daQTu4jJr\nKn1fbd/MNhben6/l7emS9FNJKxSW7dYtJmmkpNu09PttrCp3h68v6Yb8/v5V0jal1xC4EFgtL7dI\nuZcqj+E3ifT9VLt6RrnMKz+x8HwSMJ00guyWpBwerwFHFeY5ipQHYwQwFniIlJyoVH4QKblU6flJ\npNwipeczSLkoSs/fArxAHlE41/1ED21+H2m01qeAvUljKf2cNNjhOwp1LAJWLbRpASmZ15bAh4AH\ngV8X6h0PvAjsReruOJeU/+PKXL42sDBv/wjgg6ThT1au0s535DZ8pGz6+LzuXYD3k0ZLngfskMtP\nB24uW+aM4rS8/Xvl/4eRRsa9GBgFfJI0/MsiUv4YSAM/zgFOJY3jtQVpdNvrC3XeCPwd+DbpaOEL\nuY6dc7mAO4H7gJ1y23cjJUAjL/Mq8BXSwIbbkMa9+kUP7+U++X35D1Kuk2NIIxXvmMvXIO2Tl5MG\ne3x7lXouKr1PNb7GbyHtl1uS9qdxue2fzeVDgNnAvxXqHEIa4+zgHvbzV4D/ye/DdrmOUwvznA88\nQfrcbAL8lrSP/biH1+ik3LapwGbA9qTcML8u2/5XgF/mdY/K068ijWv20bzs5LzsCrn8f4Gz8//D\nSV+Gc4GN8rRvAbfk/z+b27orsA6pG+ffy7bt1ryu9YCv5td8/bLP4K1539gQGFphe99D+s45m/Q5\n3Iv0/VD8nupxX63yOh6Tl/nXvO4f5PaU2ncEMLNsmSOL0xrcxrfl9+cfwDl5mz6Zt7H4+s0kf8+S\n9rWH8/u1aV7fn/I2lj73pe/BB4HdSZ+fiaT9awhpFOuj8ja/E3gXhe8q0meu6vdsxdewnpnLXsgN\nc2NHF6aNzNOO6mG5zwAvFJ73Fly+ATxQeL4vKTC8rcZ2ll7UrxemrUAa7PDr+Xml4LIIeH9hmcNJ\n+UhKz58Djin7MnmSpcFly1zHujW2c4s8/3sL01bKO9XWZfOeT8q4WFruTWCd/FzA08CXCvMXg8uh\npA/fSmU7TjG4jAcml61znVxPabj7G1k2qP0Z+K/8/66kL/71q2zv+aS8IsVp2+dtWanKMrdVWOY3\nwNWF578DLuzltV4SXGp5javUUcq6WHo+AZhaeL4r6YukuE+V7+ev0v0DfBpwR/5/FdIXzz6F8lVz\nW3sLLgtJOWJK03bL78W7Cts/G3hLYZ4N8vu7dWHa6qTEaJ/Jz48E7sv/70VKx30lcGiedi05OJK+\nnGeQA1NZG9fN7Vm7bPpU4Ltln8FNe3kvvwc8VDbtcODlwvMe99Uq9T4DHFdhmZ/k/9fM7892hfLb\nWbr/j2h0G/P78wR5eK7Cfn5Z4XkxuOye2/LOQvnOdP/cl74HDy7MMyqvf6NCe+ZWeT32BN7o6b0o\nfzTTLTYqr2x6aUJEPEJZ9j5Ju0i6Lh8avkIa2HCN0qFzDX4JbChpq/z8INKH+p91tvdPhXYuIv1K\nHtXD/PMi4snC8+dI0ZzcxbAW8JdCnYtJow+X3AtcDzwgaaKkQyQN72F9pe6yYj/qBqRsi1OVuqde\nlfQq6ZfX+nm995J+tZS6JMeSfnn8b5X1bEz6glhYmHYn3ftjtwB2KlvnDFLX2fqF+e4rq3vJa5Tr\neCYiHqeyLYCDy9ZxTS5br8oyo0hfaEW30/P72JteX2MASV+WdHfuGnqVFKRHFOq5FBgrae38fH/g\nj9HzRSJPRsS8wvPi6/cB0hFTcR97hdqGrJ8V3TNA3kn6QTWyMO3+iHiz8HwU6cvwrsL65ub1lV7f\nm4FNlLpHdwRuyo+xkt5C+sV8U573f0iv60xJP5e0d6FbZ7PcnkfLXvOP0X3/WhjLDkxabuO8fUW3\nA6tIWqcwrad9tRtJbycdEVXd1yKdP5tKSiOApPVII3RfkufdtMltfDDyt3pv7SUd3TwdES8Wpt1V\nZd77y+pUD/UW/RMYIumtNcwL9PGoyJLeRzqHcA7pkHkusANwAekXY68npCLiRUlXA/8m6UnSqLcf\n63mplig/AR7UcdI7B5tdJW1L+hX7FeC7kraOiEoj65ZO9r6DpUOsr5L/fpL0S7NoQeH/S0lfZqfn\nv9dERMXzWDVahTRE/rEsu83F4ewrvUalHyy9Bf9VgPOAsyqsY9ays/eZXl9jpSH3zyD9Gv8T6Yjj\nWNLIwgBExN2SngD2U7qUfB9S91pPenr9+trr9S4QEfcrXU49lhRcvkXqPj2e1DX+FvIXckQ8o5T6\nehdSdspzga/nvv1VSEeoo0m/pouKo0LX+wOyJ33xWl8KnCXpK6TP3X2xNEtps9vYV/tGsd5S8Kql\n3tWB1yNiQa9z1lFpNQ8Db5E0pjRB0khSX2zJGNKh3dcj4q6IeAx4bwPruoB0MulQ4LGI+FMv81ey\nTaGdK+S2NZSuNv+CnEP6QJXqrJh0KyLujIjvkLrJ3qB63ozHSV9amxSmPUT6gntfpKufio9nC/Nd\nBmwqaTSp2/ESqpsBbC5ppcK0bel+Qn866RzRUxXWW+sH/j5gHRVOCJeZTsrqOLPCOt6ssswM0rmJ\nou1o8H3ManmNP0q6iu+8iLg3Ip6g+6/PkkuBA0hdCItI538a9QTpy6m4j61GbZczjygcQUF6fxfR\n81HPDFJw2LqwvjVIRzvF1/c24NOk/fQ20vv8VlLX6t3F/SPSFXJ/jIj/JAWk0rmce0i/6teq8JrX\ne9XmjLx9RdsDr0aDV11GxKukHxq97WtXkRK87UE6D3dpoayV29ibR0gXAhSTym1VYb6oMK1oIdVz\nFm1K2qaaNRxcIuJR0gnvnytdfTSG1E9dPMx/DFhR0lGS1pP0BdJOWK8ppBOQ40kXFTTiy/nQfCTp\nV9RwUt9mSb2XOf4E+JZS5siNSL/Ah5PfwPyafFPSGKWrtj5D6qet+EWYD4GvI30wStNeI2WsnCDp\nQEkfULoS7Mj8Wpbme4rUNfAL0nt6NdVdltt4gaRRSldvfa1snnNIv1SukPThvN7dJF0o1Xyp5C2k\nE5W/zV2j75e0u5ZecXMa8FFJP5G0haQNJH1a0k96qPYMUlfaYXn+r5KC9Rm1tKlKO2t5jf8GfFjp\n6sENJZ1C4Uu/4FLSD4zxwP9GE3l5crt+BfwwX/nzQdKPrEX0/iWxAPiVpM0l7UDaN3/T05da/uH3\ne+B8SdtJ2oL0I+VpuieZu4n0RfrXiJiX99tbSN1DS67gVLoS6ouSPpi7jL5A+m54KiL+RtoPL5a0\nT943tpJ0vOq83JX0WV4370cjJX0aOBn4UZ31lDsDOE7S5yRtJOkHpK7cs0oz5C7Nq0gXvmxMupCk\nVNbKbezNVNKPkYslbSZpO9K9KUH3faW3z+6TpO7EnSStoe5Xtu5AOqdWs2YPsw4mpWG9idTHfx7p\nZDEAEXEf6QqJY0l9feNIh9B1yTvwL0lRdZlkVDU6Pj/+SvoFtWfuU16ymjrrO4208/yK1BXwGunF\nL3X1vULqvvsj6ZfFKcBXI6KnN6h0hLa0URHfJu28x5MC02RSF87MsmUvJd04eGWFQ9cl2xYRr5N+\nWW9KOno4lfT+FNf5HOlX2hBSYL8P+DHw90I/cC2v176kcwaXka5SOS3XSUTcT+pa2ZD05TSd9KXw\nbKWK8jJXAUeTguEDwJdIJyibTabV22t8HunE9RWkbrHVSQG4vJ7HSX3dm9H9V2yjjiHtW1eT9q3b\nSD0GvXUn/y23dxLpPNZfgS/XsL6DSecNryadX1gMfCqfoyy5mfQe3liYdlOedlNh2j9I789tpPOP\nOwH/UuiuPZh0xeIP8zZdSbqirK4u0YiYTXqvPkLaznNJP3K/V5ytnjqzs0n7/A9J+/+upO+M8nOI\npc/dLRWOlA6mBdtYRfEzvZh0NDmMtP/9nBRcRPd9pdLrUKznTlJ69d+Qvse/ASDpvaSjw4sqLF/V\noEkWJukCYM2I2LvO5d5Hiupb5mDXJ/Iv+hmkX4gnNVHPn4AJkbJUmi2hdA/Qs6QfKXV90G35ko9e\nbiFd3Vn+Q7Teun4ADI+IujLJDvg0x0pXZm1OOmH2L41W07oW5QqlEaRfMzeT+l2PJN0jcVmTVR9K\n+uVryzlJHyJ1t9xF6nI9kfRL86qelrPlj6S9Sb0nfyP1BpwJ3NZsYMnm0EA344APLqQP0keAcyOi\n0dzofXF4tph02HsGKXg9QLopq5ZLRavKR1d9doRlg87XSSfxF5K6rLYv6841A3g7qdt5XdKVp1NJ\n+07TImJCI8sNmm4xMzMbPNo+cKWZmXUeBxczM2s5BxczM2s5BxczM2s5BxczM2s5BxczM2s5Bxcz\nM2s5BxczM2u5/w9CFOufiszcOwAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f07a36ea590>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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1Lnpl/C7t9jRLn/TB+FAzG1PfUQFqVWo/7yzN8lmGtm0GXFHhOu3uF+kH0Psl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\nwSWEEELdRXAJIYRQd/8PXfjAEkgMTUsAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f07a3aec450>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"show_histogram(\"daily_session\", 0, 8, 7, \"'daily' pings (evidence of leaving browser on overnight)\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Conclusion: **confirmed** that heavy users are much more likely to leave their browser open overnight."
]
},
{
"cell_type": "code",
"execution_count": 59,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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f+I6kT1bmmUQaNnBn4Ejg3cDEPAawM1HNzKy4bhxDFYsK93uBS/P//w6sM4DlrQD8OSKO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\neLbgKnye5WS0G0mbA8cBnyFdOzlpcNd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LFI9NwHWl75yY+vpfZAKptO+wiCN9PgGfmAuv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\nGgRBEAQ94L8etIIbvdV7vAAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f07a3aec490>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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O9SRgDWAv4IpGt29mZtYMzThC/GTV8zmk3rk/IA39Z2Zm1vKa0Snps41uw8zMrKf15DXU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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f07a34e5350>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"show_histogram(\"aborted_sessions\", 0, 20, 10, \"'aborted-session' ping count (evidence of crash or abrupt logoff)\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"An environment-change ping can be caused by changing some settings, installing/enabling/disabling addons. It probably doesn't mean much."
]
},
{
"cell_type": "code",
"execution_count": 60,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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eAR4HxgBPkn79Vy+rVgby6JyBfDjOQDYzq6ntxYAeMpABIuLcvIvnElIO8mTg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\nMzMD/j8toDeGiVznbgAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f07a38200d0>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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jPmBNYK18+2ClQNJRwOHAl4BtgNeAiZKWz+XF5DZHARdWlrguJLc5rNeeiZlZP9RXgsGb\nEfFcRDybb3MLZUcAJ0XEtRFxH2kW8TrA3rn8reQ2EXEl8DJpGWxwchszsx7pK8GgZnIbSRuQjhT+\nXNkxry10Ox3LTji5jZlZk/pCMKiV3OavObnNWqSVRmdXPWZ2LnNyGzOzEjRyael7IuLxsjrQTXKb\nB3tYh5PbmNlSrdnkNoqIuhqUtAi4BfgF8H95MblS5YBwI3AhaYmLrSJiaqH8ZuDuiFhixnNObnMN\nHcltto+IfSWtBLwKvL1WchtJw4HJkydPrpncJiWImAwMr35oN6YAI6hVr5lZKxWS24yIiCld7dvI\nMNFwYCpp+YlnJJ0vaZsG6qmpkNxmZkRMB54Bdi6UrwKMBG7tpAontzEzq1Mj8wz+GRFHkK7o+QJp\n9vHfJN0n6RuS3llPfV0kt7ky73ImcKykPSVtThrqeZr067+6Lie3MTNrQMMnkCPizYi4CtiHdH3/\nRsBpwFOSfiVp7R5WVUlu8yApADxHTm6T2zmVdEXQ+aSriFYE9oiI14uVFJLbfLXQxzuBSnKbz5BO\nVJuZWZWGF5aT9H7SkcG+pIlgp5HOI6wLjCX9cu92+Kir5DaFfU4ATuhmHye3MTNrUCNXE30DOBgY\nCownXco5vpALebqkg4AnSuqjmZm1WCNHBl8hXc//y4iY1ck+z5Ku5DEzs36gkUxnG/dgn9fxctZm\nZv1G3SeQJT0i6QRJm7SiQ2Zm1vsauZroPFIim2mS7pR0hKS1Su6XmZn1okbmGZwREVsDw0gnkP+X\ndDnpDZIOKLuDZmbWes3MM3g4IsZGxCbADsA7gYub7ZCko3OCm9ML2y6ukQBnfNXjnODGzKxBTSWw\nz8tQ7Af8N7AK8Nsm69ualMTmnhrFE0iTxpTvLyg8rpjgZihwkaTrI2JuIcHNqGb6ZmY2kDVyAnkT\nSd+V9DBpuYdhpBnIa0bEvo12JK9JdClwCPBijV0WVCXAKS7H5wQ3ZmZNaGSY6EFgd+BcYN2I2C0i\nfhURrzbZl3OBP0bEXzop30nS7Jyb4LxKasvMCW7MzJrQyDDR0Ih4pMxOSNoX2IrOcw1MAH4HTAc2\nBH4AjJe0XSQ3SKokuJnH4gluDiQluDmctO7RlyPigTL7b2bW3zUy6azsQLAuaWXSXSLijU7aHFe4\ne7+ke0l5DnYCbsr7lJLgxsltzKw/akdym2VJy0F/FhhCyhPwloh4R63HdVHfJ4CrgIV0nBxelpR7\nYCGwQtTopKRngWMi4oIaZXUnuHFyGzMbaFqd3GYs8A3gN8CqpCQ3VwGL6GZl0U78CdicNEy0Zb7d\nRTqZvGUngWBdYHWgs7WRnODGzKwOjZwz+BzwxYi4TtIJwBUR8ZikqcC2wNn1VJZ/oS82hi/pNeD5\niJgmaTApAP2OlPVsI9IVQg8DE6uq6yzBzdic4OajOMGNmdkSGgkGawH35v+/Sjo6ALgWOKmMTpF+\nvVcsBLYgnRReDZhJCgLHV59jKCS42e6tiiLulFRJcDM712NmZgWNBIOnSakuZ5BO4u5KGhjfmsJE\nsGZExKjC/+eTLmXtyeOc4MbMrAGNnDO4mo4E9ecAJ0l6hHSVzkVldczMzHpPI5eWHl34/28kzSAN\nyzwSEX8ss3NmZtY7mlqbCCAibgNuK6EvZmbWJg2tWirp85L+LmmmpPXztq/nOQNmZtbPNLJQ3VdI\ncwvGk67uqVyz/yLw9fK6ZmZmvaWRI4OvkuYZfJ902WfFXaTJY2Zm1s80Egw2AO6usX0BMLi57piZ\nWTs0Egymk5aOqLY7MK257tTOdJa3n5jPUcyTdKOkjarKnenMzKxBjVxNdDpwrqRBpIXltpE0mjTz\n95BmOtNZpjNJRwGHk2YPP0GaQDZR0rCIeN2ZzszMmlP3kUFEXEjKbPY9YCXgcuArwBE5y1hDusl0\ndgRwUkRcGxH3kYLCOsDeudyZzszMmtDQpaURcVlEbAysDKwVEetGxC+a7EvNTGeSNiCth/TnQvsv\nA7fTsQaRM52ZmTWhqUlneYnoec12optMZ2uRFq6bXbV9di7Dmc7MzJpTdzCQtCZwGml9onfRkZAG\ngIioK1dATzKd9YQznZnZ0qwdmc4mkDKc/YSUXGaxCiKirqt2epDpbFPgUWCriJhaeNzNwN0RMaZG\nnc50ZmZLvXoynTUyTPRBYIeI+Gcjnauhkums6Jeky1RPiYjHJT1DOhKZCiBpFWAk6TxDLW9lOstp\nOp3pzMysC40Eg6eoGhpqRneZzvKmM4FjJT1KurT0JFJehSWOQpzpzMysfo0Eg68Dp0j6ckQ8UXJ/\nKqqHnk7NQzznk9ZDmgTsERGvF/dzpjMzs8b0KBhIeoHFv6AHA49JmgcsdtI3It7RbKeKmc4K204A\nTujmcc50ZmbWgJ4eGXg1UjOzAaxHwSAiLml1R8zMrH0amoFsZmYDi4OBmZk5GJiZWQ+DgaQtJDlw\nmJkNUD39gr8bWANA0uOSVi+rA5IOlXSPpJfy7VZJuxfKL87Jboq38VV1OLGNmVkTenpp6Yuk/ADP\nAu+m3OGlp0j5ER4hzWw+CLhG0laFGcgT8vbKzOcFlQc7sY2ZWfN6Ggx+B9wiqbIw3V2SFtbaMSKW\nmPTVlYi4rmrTsZK+AmxLRxrNBRHxXCdVvJXYBrhb0pmkwDUXJ7YxM+uRns4z+JKkq4CNgLOBC4BX\nyu5MPi/xWVIGtVsLRTtJmg28APwFODYi5uaye4AvSloN2JAlE9t8pex+mpkNND1emygirgfImcTO\niojSgoGk9wK3kb7IXwE+GREP5eIJpCOT6aQv+x8A4yVtF4kT25iZNanuheoi4uDK/3NiGiLi6Sb7\n8SCwJbAq8BngV5I+FBEPRsS4wn73S7oXeAzYCbgpt19KYhtwchsz65+aTW5DRNR1I508Ph54iZR8\nZiHpBPNxwDL11tdJGzcCP+2i/Fngi52UbQo8RBpq+ipwZd6+ErAIGNzJ44YDMXny5Kg2efLkAAIm\nB0Sdt/TYWvWambVSx3cXw6Ob791GlrD+Pil72NGkXAGQEt6cQBrmOaaBOqstA6xQqyAfjaxOyrJW\nixPbmJnVqZFgcCBwSET8obBtqqR/kcbp6woGkk4mnReYAbwd+BywI7CrpMHAWNI5g2dIJ7B/CDwM\nTKxRlxPbmJk1oJFg8A7SGH+1B3NZvd4FXAKsTRp6mgrsGhF/kTQI2IJ0Ung1YCYpCBwfEYvlUXBi\nGzOzxjUSDO4BDge+VrX98FxWl4g4pIuy+cDunZVX7evENmZmDWokGBwJXCdpF9LloJB+ja9HGoox\nM7N+pu5lJSLiFmAT4GrS0M1qwFXA0IiYVG73zMysNzRyZEBEzKScq4bMzKwP8LLUZmbmYGBmZg4G\nZmZGHwgG3SW3yfucKGmmpHmSbpS0UVW5k9uYmTWhqWAgaQ1JH5O0l6S1G6ymktxmODCCtET1NZKG\n5TaOIs1h+BKwDfAaMFHS8rm8mNzmKOBCSe/IZZXkNoc12Dczs6VCw8FA0qeBR0nLRXwXeEzSwV0/\nakkRcV1EXB8Rj0XEoxFxLPAqKbkNwBHASRFxbUTcR5pFvA6wdy5/K7lNRFwJvExKbgNObmNm1iM9\nDgaSVq7aNBbYJiK2iYj3AfuQFrFrmKRlJO1LTm4jaQNgLeDPlX3y2kK307HsxD3A+yWtlnMtVCe3\nOaeZPpmZLQ3qOTKYLOkThftvktYVqlgTeL2RTkh6r6RXSLmNz6Mjuc1apJVGZ1c9ZHYuIyJuACrJ\nbS5i8eQ2h5KS2zwoaZKkzRrpn5nZQFfPpLPdgHMlHQT8L2n45jd5mei3kXIFHNRgP2omt+npg8PJ\nbcxsKddschtFSuzS8wdIo0lfvGcDF5KWlV4WeDAvLNc0STeSzkecSspqtlVETC2U3wzcHRFjajx2\nU+Aa0hDR/wDbR8S+klYinYt4e0S8VuNxw4HJkydPZvjw4YuVTZkyhREjRgCTSee56zEFGEGtes3M\nWqnju4sRETGlq30bWZvoCmBr0i/5m0nZzf5ZViAo9GuFiJhOymOwc6VA0irASODWTh77VnIbUpBy\nchszs27UtTaRpI8Cw4B7IuIQSTsCl0maQMox8O96O9BVcpu8y5nAsZIeBZ4ATgKeJv36r67LyW3M\nzBpQz9VEPwYuJh0VnC/puLyC6XBgPnC3pD0a6EMluc2DwJ9Icw12jYi/AETEqaQrgs4nXUW0IrBH\nRCx2srqQ3OarlW0RcSdQSW7zGRo/p2FmNqDVc2RwEOlLenKe1PUP0vX/rwPHSbqC9IU9oZ4OdJXc\nprDPCaQcy13t4+Q2ZmYNquecwWt0TOZaj3Q08JaIeCAidiirY2Zm1nvqCQbfJl3yORO4BTiuNV0y\nM7Pe1uNhooi4TNL1pKGYRyLixdZ1y8zMelNdVxNFxPPA8y3qi5mZtUnbl7A2M7P2czAwM7P2BwNJ\n35Z0h6SXJc2WdLWkTar2uVjSoqrb+Kp9nODGzKxBdZ0zaJEdSJPK7iL15wfADZKGVc1onkCa66B8\nf0GloCrBzVDgIknXR8TcQoKbUa1+ImZm/VXbg0FEfLR4P6+K+ixpJvLfCkULIuK5Tqp5K8ENaSb0\nmaQ5EXNxghszs261fZiohtVIC8rNrdq+Ux5GelDSeZXUlpkT3JiZNaFPBQNJIi1M97eIeKBQNIGU\ntGYUcCRpIbvxeX8nuDEza1Lbh4mqnAdsBmxf3BgR4wp375d0LynPwU7ATXmfUhLcOLmNmfVHvZ7c\nplUk/QTYE9ghImb0YP9ngWMi4oIaZXUnuHFyGzMbaFqa3KYVciD4BPDhHgaCdYHVgVmd7OIEN2Zm\ndWh7MJB0HimhzX7Aa5LWzLdBuXywpFMljZS0vqSdgd8DDwMTa9RXK8HNqJzgZgxOcGNmtoS+cM7g\nUNKv9Zurth9MGt9fCGxBOim8GjCTFASOj4g3ig8oJLjZrrItIu7MiXmuA2bneszMrKDtwSAiujw6\nybmVd+9hXU5wY2bWgLYPE5mZWfs5GJiZmYOBmZk5GJiZGQ4GZmaGg4GZmdEHgkFPktvk/U6UNFPS\nPEk3StqoqtzJbczMGtT2YEBHcpuRpOQ0y5GS26xY2UHSUcDhwJeAbYDXgImSls/lxeQ2RwEXVpa4\nLiS3Oay3npCZWX/TFyad9SS5zRHASRFxbd7nANJs4r2BcTi5jZlZU/rCkUG1xZLbSNoAWAv4c2WH\nvLbQ7XQsO+HkNmZmTehTwaCT5DZrkYLD7KrdZ+cyJ7cxM2tS24eJqtRMbtMTTm5jZkuzAZ/cJg8T\nPQZsFRFTC9tvBu6OiDE16nJyGzNb6g2o5DYRMR14Bti5sP8qpKuPbu2kSie3MTOrQ9uHiXJym9Gk\nIZzXJK2Zi17Ky1dDOo9wrKRHgSeAk4CnSb/+q+urldxmbE5u81Gc3MbMbAltDwZ0n9yGiDg1D/Gc\nT7raaBKwR0S8XnyAk9uYmTWm7cGgu+Q2hf1OAE7oZh8ntzEza0CfOGdgZmbt5WBgZmYOBmZm5mBg\nZmY4GJiZGQ4GZmZGHwkGknaQ9AdJ/5K0SNJeVeUX5+3F2/iqfZzcxsysQW2fZ5ANBv4J/AK4qpN9\nJgAHAcr3F1QKqpLbDAUuknR9RMwtJLcZ1Zqum5n1f30iGETE9cD18NYy1rUsiIjnOilzchszsyb0\niWGiHtop50h+UNJ5lbSWmZPbmJk1ob8EgwmkNYVGAUcCOwLjK0cRTm5jZtacPjFM1J2IGFe4e7+k\ne0k5DnYCbsr7OLmNmS21BkxymwpJi4C9I+IP3ez3LHBMRFxQo8zJbcxsqdfvktvUS9K6wOrArE52\ncXIbM7M69IlhIkmDgY3ouGz0PZK2JF0NNBcYC/yOlPFsI9IVQg8DE2vU5eQ2ZmZ16hPBgDSGfxPp\nV3sAP87bLwEOA7YgnRReDZhJCgLHR8QbxUoGWnKbGTNmMGfOnLoft8YaazBkyJAW9MjMBqo+EQwi\n4ha6HrLavYf1DJjkNjNmzGDo0GHMnz+v7scOGrQSDz00zQHBzHqsTwQDW9KcOXNyILgUGFbHI6cx\nf/7+zJkzx8HAzHrMwaDPG0b9VzCZmdWnX15NZGZm5XIwMDMzBwMzM3MwMDMz+kgw6C65Td7nREkz\nJc2TdKNVwBqBAAAcBklEQVSkjarKndzGzKxBfSIY0JHc5jDSpLPFSDoKOBz4ErAN8BowUdLyubyY\n3OYo4MLKEteF5DaHtf5pmJn1T33i0tIeJLc5AjgpIq7N+xxAmk28NzAOJ7cxM2tKXzky6JSkDYC1\ngD9XtuW1hW6nY9kJJ7cxM2tCnw8GpEAQpCOBotm5zMltzMya1CeGicrg5DZmtjRrNrlNfwgGz5CW\ntl6TxY8O1gTurvWAnNxmPzqS29wSEXMljQMukjS4OrlNxRlnnFEzuc0xxxzT9BMxM2uV0aNHM3r0\n6MW2FZLbdKvPDxNFxHRSQNi5sk3SKsBI4NZOHubkNmZmdegTRwZdJbeJiKeAM4FjJT0KPAGcBDxN\nSm1ZXZeT25iZ1alPBAO6Tm7zhYg4NecvPp+U4GYSsEdEvF6sZKAltzEz6y19Ihj0ILkNEXECcEI3\n+wyY5DZmZr2pz58zMDOz1nMwMDMzBwMzM3MwMDMzHAzMzAwHAzMzo58EA0ljc9Kb4u2BQvn/kzRb\n0jOSvlH12JGS7pTUL56rmVk79Il5Bj10H2lJisos5TcBJG0OfJc0u3gZ4DpJEyPifknLAj8FDomI\nRW3os5lZv9CfgsGbEfFcje2bAvfkiWtImpq33Q8cSVqkbkrvddPMrP/pT8FgY0n/AuYDtwHfzusW\n3QtsImld0gJ0GwP3StoQOBDo2ZJ9ZmZLsf4yjv4P4CBgN1Kymg2ASXkp6geB7wB/IqXOPDoiHiat\nXHoksIekeyVNlrRDW3pvZtbH9Ysjg4iYWLh7n6Q7gCeBzwIXR8TPgZ9XdpB0IPAyKYg8RDo6GAJc\nKendEfFGZ205uY2Z9UdLQ3KbJUTES5IeJi17vRhJawDHAzuQch48FBGPA49LWg7YhHQ+oSYntzGz\n/mjAJ7epRdLKpEAwq0bx6cCPI2Imiye2gRT8nNjGzKxKvzgykPQj4I+koaH/JF1K+gZwRdV+HwE2\njohKzoI7gU0l7U4aJnqTNGxkZmYF/SIYAOsClwOrA88BfwO2jYjnKztIGgScTTqPAEBE/EvSV4GL\nSVchHRARC3qz42Zm/UG/CAYRMboH+8wHhtXYfhFwUSv6ZWY2UPTLcwZmZlYuBwMzM+sfw0RmZkuD\nGTNmMGfOnLoft8YaazBkyJCm2nYwMDPrA2bMmMHQocOYP39e3Y8dNGglHnpoWlMBwcHAzKwPmDNn\nTg4El1LjWpguTGP+/P2ZM2eOg4GVo52HqGZWMQwY3u1eZfMJ5FJc0f0ufbzNyiHqiBEj6r4NHTqM\nGTNmlNqf6jVWWm2gt9eONt1e6S22tHYHg1L0/2Cw+CHq5Bq3D3Wy/VLmz5/X0BFFVwb6H7aDgdtr\noMWW1u5hIqvS2SHqqp1sb1xXw1IvvfQSU6bUzknkYSmz8jkYWFv05MqJzlZbbPTKid4OPu0Idg6w\n1igHA2uL7q+cGAOcUWN7Y1dO9HbwaVewc4Dt3+21k4NBh0EA06ZNW6KgY9t4YMlyeBq4rJNqp1fV\n0TONt9nf2pveyR6vdNKPxttLX5L/A6xdY4/fAP9dY/ss5s//BZMmTWLYsJ5f7tfb7bWjzVmzZvGp\nT32G11+f3+k+nQWf5ZcfxFVX/R9rr12rn0tne634GyxsG9Rd+4qIHnRz4JO0H51/o5uZ9Wefi4jL\nu9rBwSCTtDopx/ITpOWuzcz6u0HAu4GJxSX/a3EwMDMzzzMwMzMHAzMzw8HAzMxwMDAzMxwMzMwM\nBwMzM8MzkEsl6T+APSPiVyXXK9K1wk9FxJuSlgc+CawAjI+IcpcMXbL9DYCNgFkRcV/JdX8amBAR\n9ad3aq7dUcAHSVN1FwGPA3+IiEd6sx+5L28D1omIctcBX7KdNYEVWt1Oob3lIuKNFtS7Rqs/8120\nPRgYweKfmykxEK7RjwjfSroBWwILS65zKGki3ELgEWAD4C7gVeA14Dlg4xLbOw9YOf9/ReD/ctuL\n8r9/qZSX1N4i4CXg58DIXniP3gXcnp/LG/nfu4BZwJvAqf39cwO8nbTo05PAJcDywLmF9/AWYJUS\n2/sssHzh/uG57YXAHOD4kl+vhcCfgf1Iwa033qNlgFPz39zCwt/Eovz3uWcL2tws/z3enT+fs/L/\nzwM2K7s9DxPVQdIqXd1If4Rl+yFwD7AVcC1wHWmRkv8A3gHcBhxfYntfBlbK/z8OGAnsDKxMSmow\nBDimxPYATgPeD9wm6T5JX88zwlvhbGAm6fVbmfSHdX9ErA3sCnxB0hEtaru3nEz69Xoa6f0aR3rv\ndgA+DKwBHFVie1cAqwFIOhj4EXAxsCdptcEjJR1SYnsCXs9tzJJ0jqStSqy/lpOBj5MWd9oN+Btw\nNOkL+1fAbyXtWlZjkvYgffG/D7gGODHfriH9eJgiabey2gN8ZFBnpK78surstojyjwyeBbbK/x+c\n2/hgofwDwJMlP8d35f/fC4yuKt8LeKhF7Y0gfTm/QFoSZBzwkZJfz5eA/yrcH0z6Ylkl398feLDk\nNqd0c5tW5ucGmAF8OP9/nfwaf7xQ/rEyn2PVe3g78K2q8q+QhlJKbY8U1L4J3J///ibntko76im0\nORPYoXD/P0mrKa6Q7x8H3Fpie/cAJ3ZRfgIwtczn6OUo6iDpJeD7pA98LRsD50fEsiW2OQ/YNPI4\nr6RXSMHhsXx/PeCRiOh2VcIetrcIWDMinpP0HLBTRNxfKF8fmBYRK3VaSf3trRURzxa2DQL2Ab5A\n+kU7IyI2KKm9Z0nP6YF8f0XSkNs7I2KupPcAD5T1euY25gNX0vkSrWsDXyzrc5Pb2zginsr3XwPe\nFxEP5/vrk57j4JLaq/7M7BIR9xTKNwTujohVSmyv+jOzHXAI6XOzLPC7iDigjPZy/S+T/u4ez/eX\nARYA60XEM5I2A+4s8TX9d27voU7KhwL/jIgVy2gPfAK5XlMAIuKWWoWSXiQdwpZpJulQv3LS70jS\n0ULFO0m/pMt0Ug5Ci0i/LO8vlK1OGjctyxK/RiJiPvBr4NeSNgIOLrG9vwEnSjqQdERwMvB4RMzN\n5a14Pe8Dbo+In9YqzEMcXyyxvedJz+OpfP8a4MVC+cqkL7Iy7Z5/LM2nY5ixYhA13ucm1PrM3EYa\nZvwasC/ph0SZ7gVGk34MQjpP8mpEPJPvV4JDWZ4gHcHVDAa57MkS23MwqNPlpJOqnXkG+G7Jbf4J\n2JT0JUaNL5RdyUGqJH8lnbQGeABYv6r8oyweHJrVZfCMiEcp9xzF/wNuIH05Bimw7VMoHwb8ssT2\nAP5Ox2tayyuk170sU4Gt6fjxsl9V+dbUXjC/GZcU/j+KdC6rYlvgsRLb6vQzExGvAb/ItzIdD1wn\naS9SwPsA8K1C+e6kMf4y27tc0k6k74DZefuapHN4u5NOoJfGw0T9XL7sc35EzOql9t4DvB4RT5dU\n3/qkYaBe+yBKWgnYnnRp7j+iTZcptoqkdwCLIuLFTsr3AP4dETf3Un8+DrwRERNLqu9A4MqIKPvo\nprt2tyQdEaxAWhL6xha39wHga8B2wFp58zOkQHtWPhoqrz0Hg+ZIWheYGRGLBmqbbs9s4POlpc17\ngDQhbCC36fZaSNJgSR9ye/2zvXa1WTYHg+aVfcK4L7bp9lprI+Amt9dv22tJm5K2lHSspMMkrVFV\ntoqki8psz8HAzKyPyRPY7iBdGXUU8KCkDxd2WRE4sMw2fTVR804G5na7V/9u82TKv9yyu/Z6+/m1\nrD1J3dVd2rwUt1d+e21q8wTgtIg4Jq9N9i3gD5L2iYjrS24L8AnkuuXDtS+w5Bn+W4FfRsRz7epb\nK0l6HdgyIsq+JHHAy5O+fkq6Vr2W9YGxJU46c3sltteONvOcjeGVyaV5236kNbz2Be4kXfRQ2nP0\nkUEdJG0NTATmka79fTgXrUm6BOxoSbtFxF0lt7siaamGuZWZs4WyQcBno6SVUiWd3knRsqTn9zxA\nRHyjpPaGAy9ExPR8//PAoaSJdk8CP4mIK8toq9Dm4cA2pBVfr8xtfps0bHoVaWG1N0ts8p+kFWcv\nqVWYL1kc6/b6bHvtaHMBeb2nioi4PM++/g1pGY5SORjU5xzgt8Ch1dfF50O5n+V9tiurQUmbkCZJ\nDQFC0t9I6wXNzLusSlqwq6xls79OWhel+hp1kSZkvUa5s0kvJn2wp+fFzM4GLiDNQB4KXCBppYgo\n5WSZpGNJs7hvAM7I8xy+RVpQbREwhrSaaZl/2NdR9YddZS7lvX9ur/z22tHmP0mLCk4ubsw/XsTi\nk/zKUeZCRwP9BvybtE5QZ+WbkibzlNnm1aTVStcgXbFwLWkN9SG5fE3KXeTs6Fz/qKrtb9CCZXNJ\nR1nr5/9PIa3RUyzfj7SqaFntPQp8Kv9/S9Ky1Z8rlH+StNZT2z9vvi29t/w5PKOL8v2Am8ps01cT\n1ecZ0vBCZ7ahY9p4WT4AfDsi5kRammFP0lDVpDwbuFQRcQppmd6fSjpN0nJlt1FlHinQQVoJ8o6q\n8ttJORzKsg4pfwGRFlNbRPoVVjEl72PWNhFxdUSM6aL88oj4cGfljXAwqM9pwM8lnSVpL0kj820v\nSWeRholOLbnNFUm/XgGI5CvAH0lJSjYpuT0i4k7SOYp3AndJei/lDg0VTSAtOwzp+XymqvyzpF/z\nZXmGtAY9kjYmnQvZrFD+Xyy+EGBLSHq5FcHc7fWedrTZSj5nUIeIOFfSHNK48mF0XE5WWUv9oIgY\nV3KzD5ISvyx2FU9EHJ6GDvlDye1V6n8VOFDSvqST5aVfrpcdBfxd0i2kX+zfzItzTSOdM9iWdMhc\nlsuAX0m6hrTg16nAafkqsYXAsaTsbq020CfWDfT2eq1NSdcBh0TErOL/y27HwaBOEfEb4Dd5+KQy\nvDEnWpDrNbuatHTur2v05fC8rvqhLWqbSCes/kY6Uih1ydxc/0xJ7yOdq9iT9Ae2DbAeabXP7aPc\nq7PGks79bEc6UX0K6YT5qaSll/9ISlRi1ld8iI7Vkov/L5XnGZi1gaSfAsdFL62Y6vb6b5tKCa22\njIjHi/8vvR0HAzOzvqu3goGHicx6gaTlgb2pPXP9moh4vQVtrgu8mM//FLcvB2wXEWUm1KnV/uPA\nbhHxSMn1rkvK4TEn39+BxScqnhslr/Wf2/k4aQhzYkT8XdIoUrKkZYCrIuLnZbfZmxwMzFpMKXXn\nRNIlq7fTcfnx+0hfYk9L2iNfOlxGe2uTUl2OIE1UvBw4rBAU3kFaYbOspRO+1knREOBgSc8ARMTZ\nZbQH/A44CbhW0idIs8avJZ1j2gS4RdKnIuLaktpD0peBn5DOLx0h6X+B80izgRcCZ0paMSLOKqvN\n3uZhIrMWk3Qjaeb2ARHxclXZKqSZqytGxG4ltXcJ6Uqsw0mzZk8hXRq8a0S8IGlNYFZElHJpeV4i\n4V8ULoHO1ifl8H6DdFV0KZdhSnoV2Dwipkv6B3B1RPywUH448IWIGF5Ge7nO+0mTwC7Mq4eOB74Z\nEefl8oOAIyNisy6qabRtnzMwGwgkzQO2iYj7OinfHLg9IqoTyTfa3r+AT0bEHfn+CqRlVNYjXU67\nHCUucibpZ8BIYL8oLGQo6Q3SF9cDnT64sfZeBD4UEVMlzQY+EhFTC+UbAlMjYnCJbc4jrT4wI99/\nnbSQ3H35/rtJM+VLa7PQdq8EA086M2u9F+k6k9q7WXItqGasSmHJ8Ui5gj8FPEEaHnpXiW0REYcC\nJwIT86/yVruFdLk1pCT0O1WVf5h0pFKm50lHOkhahzTEPqRQvj6tWwb9SdLRVfX/S+VzBmatdyFp\nottJwJ/pOGewJumX+rGkBQ7L8jiwBfDWiduIeFPSPqQjhNLG0gv1Xy3pDtLz/BhwcNltFBxNWo5l\nHeBvwPfzisKViYr/Tflzb64BfpGH4PYiDe39WFKQzhmcRlr8sHQR8d5a/29FQ7755luLb6SZ1jNJ\nayEtzLdFeduRJbf1Q9IVL7XK3kb6YlvUoucp0nLgs0jnEEpf3DC3syFwBfByfh0XAa+TTiLv3YL2\nBpNyCdwLnA8sT7qSaEFu+ybgXS38/CxDCvBva1UbPmdg1oskbUDh0tLIeRxKbuNtwEpRdbK6qvw/\nI6L0GeWFNkYAHwR+FREty5KXl3N+F+nLspUrAXTW/iBguYh4pcXt7E26iuqAiLisFW34nIFZL4qI\n6RFxW75VEvqspxKTm0fEm50Fgmxtyk/+Ut2HyRFxVqSrl0p9flXtRETMjohZlUDQyvZqtD8/Il7p\nhTYPBJ4DDmpVAz4yMGszpSxZU6LEFIZur/faa3WbeRHFp0mTFv8AvCcini67HZ9ANmsxSXt1s0up\nyyC7vXLba1ebBaOB+yLiekmTgM8DPyi7ER8ZmLVYnpQVdL3kcZT1q9Ltldteu9ostD0ZuCQizpZ0\nMOmCg2Flt+NzBmatN4uUanOZWjegtJmybq8l7bWrTXJiqfcCl+dNvwWGSBpZdlsOBmatN5m0TlBn\nuvvF6fba21672oR04viGyIvyRVpf6ve04ESyzxmYtd6PSNepd+ZR0qxZt9c322tLm5KWBfYHqhcC\nvBS4TNIRUeJqtz5nYGbWB+XVZ78InFL80s/ZDb9DmsMxo7T2HAzMzMznDMzMzMHAzMwcDMzMDAcD\nMzPDwcDMzHAwsB6QdKCkVmVxGnAk3STp9Hb3o7dIWl/SIklbtLsv1jgHg35G0sWSju/lZq8ENunl\nNnvd0vYlDh1f5E1WM4OUo6FmjueBJv8NXtXufpTNM5CtW5Fy6C7orFzScr2dVMRK1dRko0iTlZ4t\nqS/WJj4y6OckLS/pNElPS3pV0m2SdiyUHyjpBUm7SnpA0iuSJkhaM5d/RNK/Ja1SVe9Zkv6U/3+Q\npBcKZWMl3S3pfyQ9Dvy70JezJc3OdU6S9P7C43bMwwmjJN0p6TVJf5e0SY26D5b0ZO7vTyQtI+lI\nSbNy/d+p6u+qki6U9KyklyT9qThsUah3f0nTJb0o6QpJg3P5xcCOwBG5jwslFROeV7/u2+cjidck\nzc2v6aqFXZaR9ENJz+c+j616/BhJU/N7NkPSuZW+9OR9y/ssm1/vF/Lz/r6kX0q6urCPJH1b0uOS\n5uXX4NPVT6ez55nrWCTpUEnjcx2PFeuoHibq4n3euKreY/N7+aKkn0k6WdLd3fRlM0l/zO/xy5Ju\nUcoeV3mux0t6StL8/Fx3Kzy20q9VCtu2zNuG9OR1z+/jgcAnCp+TD3XV536jVfk0fWtZLtSLgOML\n9y8AJgEfADYAvgHMAzbM5QeSftVPBN4HbAXcD/w6ly9DysN7cKHOZUirNB5UqGNuoXws8ApwHbAl\n8N68/SzgKWBXYFPgYuB5YLVcviMpX+ytpJSImwK3AJOq6n4Z+E0u/xgwH5gAnAlsTFqkaxGwdeFx\nNwJX5+e4IXAq6dfqalX1/hYYBmyfn/dJuXwVUv7cnwHvJKVSVCfvwVakAHgOsDkpCfuhwDty+U3A\nC8BxuS+fJ+U83rlQx9fy6zEE2Al4APhJobzL9y3vcwwp+9VepGG884AXgauq9rkf2AV4N3BA/nzs\nkMvXBxZ285lblF/Lg4GNgBOBN4ChxTqALep4nz+X+3FArvO43PcpXfRjHWAOMK7wPu8PbJzLx+TX\nfZ/8OTklv4YbFvq1EFilUOeWeduQHv69DCYNm15X+Jy0LC9xr363tLsDvjXx5sF6+Y9yrartNwLf\ny/8/MH/Y310o/wows3D/DODGwv1d8x/qKoU6qoPBfPKXX962Uv4j+u/CtreRMjR9M9+v/DHuVNhn\nj7xt+ULdr5By+Fb2mQA8VvUcp5ETyecvnBdIuWiL+zwCHNJFvT8Ebi3cvwk4vQev+2XAX7sovwm4\npWrb7cDJXTzm08Czhfs9ed9mAWMK95cBniAHA1LS9leBkVVtXQBcWsfnbBGFQJW33VbZRgoGi1g8\nGHT3Pt8GnFVV5yS6DgYnkxaEW7aT8qeBo2q87udU9au7YNDd634xhYA7UG4+Z9C/bQ4sCzwsqXio\nvzzpF1TFvIh4onB/FukXTcVlwG2S1oqIZ4D9gOui6zy6T0ZE8QqjDUlf/rdWNkTEm5LuIP0SL7q3\nqi/k/lRS+T0REfMK+8wG3qyqY3bhOWwBvB2Yu/jLwKDcr4rqeqtfhyVIuo/0ZQcpAHyM9GtxXFeP\nA6ZW3V+sLUm7AEeTfjWvQnrtVpA0KCLm5906fd/yUMeawJ2VwohYpJQIpfIibEQK0jdWfT6WA7oc\njqnhH1X3byN9kXalq/d5KHBu1f530PXKn1uSji4WVhdIejvpyOHWqqK/kz4f9eju72VAcjDo31Ym\nfUkOJ/0yK3q18P/qk7uLrb0eEXcpjf3vK+lnwCdJh+9dea2hHi/Zn8rJy2U6Ka/sU2tb5TErk4Z8\ndmTJ8e8Xu6m3u/Nme5C+PCGfGyn825VO25K0PvBH0pfhd4C5wA7AhaRAPr+LOupZM3/l/O9HSa9P\nUacXBJSou/e5Xj153btS+RupDozVmn3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"text/plain": [
"<matplotlib.figure.Figure at 0x7f07a3655310>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"show_histogram(\"environment_session\", 0, 20, 10, \"'environment-change' ping count\")"
]
}
],
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "Python [default]",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.12"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
# coding: utf-8
# # Tab/Pageload Behavior of Firefox Release Users
#
# Author: bsmedberg@mozilla.com
#
# Date: 8-May-2017
#
# Status: Partially-reviewed draft.
# In[1]:
import plotly.plotly as py
from plotly.graph_objs import *
import pandas as pd
import matplotlib.pyplot as plt
import pyspark.sql.functions
import numpy as np
# In[2]:
main_summary = spark.read.option("mergeSchema", "true") .parquet('s3://telemetry-parquet/main_summary/v3/') .createOrReplaceTempView("main_summary")
# In[37]:
sample_unfiltered = spark.sql("""
SELECT
client_id,
SUM(CASE WHEN app_version < '52' THEN 1 ELSE 0 END) AS bad_version,
count(1) as subsession_count,
max(max_concurrent_tab_count) as max_concurrent_tab_count,
sum(tab_open_event_count) as tab_open_event_count,
SUM(CASE WHEN subsession_length < 0 OR subsession_length > 172800 THEN 1 ELSE 0 END) AS bad_length,
sum(subsession_length) as subsession_length_sum,
sum(total_uri_count) as total_uri_count,
SUM(CASE WHEN reason = 'aborted-session' THEN 1 ELSE 0 END) AS aborted_sessions,
SUM(CASE WHEN reason = 'shutdown' THEN 1 ELSE 0 END) AS shutdown_session,
SUM(CASE WHEN reason = 'environment-change' THEN 1 ELSE 0 END) AS environment_session,
SUM(CASE WHEN reason = 'daily' THEN 1 ELSE 0 END) AS daily_session
FROM main_summary
WHERE
submission_date_s3 >= '20170415' AND submission_date_s3 <= '20170429'
AND subsession_start_date >= '2017-04-16' AND subsession_start_date < '2017-04-23'
GROUP BY 1
HAVING bad_version = 0 AND bad_length = 0
"""
).cache()
# In[38]:
sample_unfiltered.count()
# # Discarding severe outliers
#
# When defining heavy users in terms of total pageloads, we can suffer from bots and other unreal situations that inflate pageloads. Discard anyone who loads more than a page every 10 seconds or more than 30000/week (because WTF).
# In[39]:
total_uri_count_unfiltered = sample_unfiltered.select(pyspark.sql.functions.sum(sample_unfiltered.total_uri_count)).first()[0]
total_uri_count_unfiltered
# In[40]:
outliers = sample_unfiltered.where((sample_unfiltered.total_uri_count > 30000) | (sample_unfiltered.subsession_length_sum / sample_unfiltered.total_uri_count < 10))
outliers_uri_count = outliers.select(pyspark.sql.functions.sum(outliers.total_uri_count)).first()[0]
print "total outliers: {}".format(outliers.count())
print "total URIs loaded by outliers: {} ({:.0f}%)".format(outliers.count(), 100.0 * outliers_uri_count / total_uri_count_unfiltered)
print "example outliers:"
outliers.select("subsession_count", "max_concurrent_tab_count", "tab_open_event_count", "subsession_length_sum", "total_uri_count").sample(False, 0.001).toPandas()
# In[61]:
# how many users just have >30000 uri loads?
sample_unfiltered.where(sample_unfiltered.total_uri_count > 30000).count()
# In[41]:
sample = sample_unfiltered.where((sample_unfiltered.total_uri_count <= 30000) & (sample_unfiltered.subsession_length_sum / sample_unfiltered.total_uri_count >= 10))
sample.createOrReplaceTempView("sample")
# ## Heavy users
#
# There are multiple definitions of a heavy user being proposed. We can't calculate heavy users by activeTicks as proposed at https://docs.google.com/a/mozilla.com/document/d/1TJUo1dbTA5mcWg5ZznKqYn3mpSqQeaDlqCRzUsi0_Js/edit?usp=sharing because this dataset doesn't yet have activeTicks.
#
# Instead, this calculates it by pageloads: at what threshold of pageloads (total_uri_count) do we find the users who are responsible for 80% of all pageloads?
# In[42]:
total_users = sample.count()
total_uri_count = sample.select(pyspark.sql.functions.sum(sample.total_uri_count)).first()[0]
# In[43]:
ranked_by_uri = spark.sql("""
SELECT
total_uri_count,
RANK() OVER (ORDER BY total_uri_count) AS rank
FROM sample
ORDER BY total_uri_count
""").cache()
# In[44]:
def top_npct_uris(n):
topn = ranked_by_uri.where(ranked_by_uri.rank > total_users * (100.0 - n) / 100)
cutoff = topn.first().total_uri_count
uri_count = topn.select(pyspark.sql.functions.sum(sample.total_uri_count)).first()[0]
print "The top {}% of users accounted for {:.0f}% of total URI loads. (cutoff={})".format(n, 100.0 * uri_count / total_uri_count, cutoff)
return cutoff
top_npct_uris(1)
top_npct_uris(5)
heavy_user_cutoff = top_npct_uris(10)
_ = top_npct_uris(30)
# For the purposes of this analysis and as suggested by bcolloran, we're going to look at the top 10% of users as "heavy users".
# In[45]:
print "Heavy users are users who loaded more than {} pages this week.".format(heavy_user_cutoff)
# ## Do page loads distribute differently than usage hours
#
# bcolloran did a previous analysis of the distribution of session hours and active ticks. We don't have active ticks yet, but let's calculate the distribution of usage hours to double-check our data and repeat the previous analysis
# In[46]:
total_session_length = sample.select(pyspark.sql.functions.sum(sample.subsession_length_sum)).first()[0]
# In[47]:
ranked_by_session_length = spark.sql("""
SELECT
subsession_length_sum,
RANK() OVER (ORDER BY subsession_length_sum) AS rank
FROM sample
ORDER BY subsession_length_sum
""").cache()
# In[48]:
def top_npct_length(n):
topn = ranked_by_session_length.where(ranked_by_session_length.rank > total_users * (100.0 - n) / 100)
cutoff = topn.first().subsession_length_sum
length_sum = topn.select(pyspark.sql.functions.sum(sample.subsession_length_sum)).first()[0]
print "The top {}% of users accounted for {:.0f}% of total session hours. (cutoff={:.1f} hours)".format(n, 100.0 * length_sum / total_session_length, cutoff / 60.0 / 60.0)
top_npct_length(1)
top_npct_length(5)
top_npct_length(10)
top_npct_length(30)
# ## Comparing light and heavy user behavior
#
# The following charts compare the behavior of heavy users and normal users.
# In[49]:
def iter_with_next(l):
"Generate (first, next) pairs for a list (skipping the last item)."
i = iter(l)
prev = i.next()
for v in i:
yield (prev, v)
prev = v
# In[50]:
def show_histogram(colname, minv, maxv, num_buckets, label):
buckets = range(minv, maxv, (maxv - minv) / num_buckets) + [maxv]
selected = sample.select(pyspark.sql.functions.expr(colname).alias("data"), "total_uri_count")
label_map = {
-1: "<{}".format(minv),
maxv: ">={}".format(maxv)
}
caseExpr = pyspark.sql.functions.when(selected['data'] < minv, -1)
for start, end in iter_with_next(buckets):
caseExpr = caseExpr.when(selected['data'] < end, start)
label_map[start] = start == end - 1 and str(start) or "{}-{}".format(start, end - 1)
caseExpr = caseExpr.otherwise(maxv)
def print_chart(data, subgroup):
bucketed = data.select(caseExpr.alias("bucket"))
counts = bucketed.groupBy("bucket").count().toPandas().set_index("bucket").sort_index()
max_count = counts.max()['count']
total_count = counts.sum()['count']
counts.plot(kind="bar", legend=None, figsize=((num_buckets + 2) / 3, float(max_count) / total_count * 5))
xticks = [label_map[v] for v in counts.index.values]
plt.xticks(range(0, num_buckets + 1), xticks)
plt.xlabel(label)
ytick_ratios = np.arange(0.05, float(max_count) / total_count, 0.05)
yticks = ["{:.0f}%".format(r * 100) for r in ytick_ratios]
yticks_pos = [r * total_count for r in ytick_ratios]
plt.yticks(yticks_pos, yticks)
plt.ylabel("% of {} users".format(subgroup))
plt.show()
print_chart(selected, "all")
print_chart(selected.where(selected['total_uri_count'] > heavy_user_cutoff), "heavy")
# In[51]:
show_histogram("subsession_length_sum / 60 / 60", 0, 160, 20, "usage hours")
# Possible conclusions:
#
# 1. heavy users tend to use their browser more (let's state the obvious!)
# 2. heavy users are more likely to be the kind of user who keeps their browser open overnight.
# In[52]:
show_histogram("subsession_count", 0, 100, 10, "# of subsessions")
# No easy conclusions here, although there appear to be a bunch of heavy users who still open and close their browser regularly? Should validate this with the ping reason data.
# In[53]:
show_histogram("max_concurrent_tab_count", 1, 25, 12, "max # of tabs open any time during the week")
# Conclusions: heavy users tend toward a few more tabs in general, and there is a more significant proportion of tab-hoarders who regularly keep >25 tabs open.
# In[54]:
show_histogram("tab_open_event_count", 0, 2000, 25, "# of tabs opened")
# In[67]:
# how many users have a null tab_open_event_count? This could mean they didn't open any tabs... need to check how this behaves more precisely.
null_tabopen_count = sample.where(pyspark.sql.functions.isnull(sample.tab_open_event_count)).count()
print "users with no tab open count: {:,} ({:.0f}%)".format(null_tabopen_count, 100.0 * null_tabopen_count / total_users)
# In[55]:
show_histogram("total_uri_count", 0, 10000, 25, "Total toplevel URIs loaded")
# In[56]:
show_histogram("total_uri_count / subsession_length_sum * 60 * 60", 0, 1000, 25, "pageloads per session-hour")
# In[57]:
show_histogram("total_uri_count / tab_open_event_count", 0, 500, 25, "page loads per tab-open-event")
# ## Other checking
# In[58]:
show_histogram("daily_session", 0, 8, 7, "'daily' pings (evidence of leaving browser on overnight)")
# Conclusion: **confirmed** that heavy users are much more likely to leave their browser open overnight.
# In[59]:
show_histogram("aborted_sessions", 0, 20, 10, "'aborted-session' ping count (evidence of crash or abrupt logoff)")
# An environment-change ping can be caused by changing some settings, installing/enabling/disabling addons. It probably doesn't mean much.
# In[60]:
show_histogram("environment_session", 0, 20, 10, "'environment-change' ping count")
@bcolloran
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(copying from email thread per request from rweiss)

"""
Hi Benjamin, this looks great. I did notice one thing that I think bears looking into "Users with more than 3741 page loads per week account for 80% of all page loads. This is 1.4% of all users." -- In terms of session hours, the top 10% of users accounted for only about 58% of of all session hours recorded; the top 1% for only about 10% of session hours (see https://docs.google.com/document/d/1cctqvm7fbaPemb1C900KGQJsO6GsBsgUIGJLVJV9jKo/edit# ; unfortunately I don't have similar breakdowns for activeTicks or URI loads). The relationship may well be different for URI loads, but the top 1.4% of users accounting for 80% of URI loads is so sharply different that it raises a red flag and should be investigated further. I wonder if there might be an outlier in your sample that is singlehandedly accounting for some crazily large proportion of URI loads or something like that? FWIW, I think you would be justified in throwing away or truncating stratospherically high page load counts -- it seems fine to impose some king of physically realistic limit on what a human can do in a day (something like: 16hrs/day * 3600secs/hr * .1 clicks/sec = 5760 clicks/day -- this is totally made up, but I think it's acceptable to make stuff like this up if you call out your assumptions).

FWIW, using URI loads rather than activeTicks is fine, that is the direction we want to head eventually. We were waiting for the URI measure to reach a 'big enough' (whatever that means) share of the population, but since you are focusing on clients with sufficiently new versions, URI loads and activeTicks are strongly enough correlated that either will work fine.

For most of the heavy user stuff, we've been aiming for the top 10% of the population. So you should be able to skip the cumulative sum of total_uri_count step -- just sort users by total URI loads and mark the top 10% as the heavy users. Does that make sense?

Interesting stuff, please keep me posted!
"""

@bsmedberg
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To close the loop on this, there was an error in the first version of this sheet which @bcolloran detected and has since been fixed. This has been rereviewed and this statement is perhaps the key takeaway: "The top 10% of users accounted for 48% of total URI loads. (cutoff=1490)"

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