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June 3, 2015 23:37
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| {"nbformat_minor": 0, "cells": [{"execution_count": 97, "cell_type": "code", "source": "import ujson as json\nimport matplotlib.pyplot as plt\nimport pandas as pd\nimport numpy as np\nimport plotly.plotly as py\nimport networkx as nx\nimport collections\nimport datetime\n\nfrom moztelemetry import get_pings, get_pings_properties, get_one_ping_per_client\n\n# %pylab inline\n\n", "outputs": [{"output_type": "stream", "name": "stdout", "text": "Populating the interactive namespace from numpy and matplotlib\n"}, {"output_type": "stream", "name": "stderr", "text": "WARNING: pylab import has clobbered these variables: ['info']\n`%matplotlib` prevents importing * from pylab and numpy\n"}], "metadata": {"collapsed": false, "trusted": true}}, {"execution_count": 2, "cell_type": "code", "source": "sc.defaultParallelism", "outputs": [{"execution_count": 2, "output_type": "execute_result", "data": {"text/plain": "64"}, "metadata": {}}], "metadata": {"collapsed": false, "trusted": true}}, {"source": "#Get pings, filter them, and do some basic checks", "cell_type": "markdown", "metadata": {}}, {"execution_count": 3, "cell_type": "code", "source": "pings = get_pings(sc, app=\"Firefox\",\n channel=\"nightly\",\n submission_date=(\"20150520\",\"20150530\"),\n fraction=1,\n schema=\"v4\")\n\n", "outputs": [], "metadata": {"collapsed": true, "trusted": true}}, {"execution_count": 4, "cell_type": "code", "source": "p = pings.first()", "outputs": [], "metadata": {"collapsed": false, "trusted": true}}, {"execution_count": 5, "cell_type": "code", "source": "# p[\"payload\"][\"info\"]\np.keys()\n# p.get(\"payload\",{}).get(\"info\",{}).get(\"subsessionId\",False)\n# {k:p[k] for k in p.keys() if k!=\"main\"} ", "outputs": [{"execution_count": 5, "output_type": "execute_result", "data": {"text/plain": "[u'clientId',\n u'id',\n u'environment',\n u'application',\n u'version',\n 'meta',\n u'creationDate',\n u'type',\n u'payload']"}, "metadata": {}}], "metadata": {"collapsed": false, "trusted": true}}, {"execution_count": 11, "cell_type": "code", "source": "#note that we have to filter out the 'meta' entry, b/c this can contain things like intake timestamps,\n#which should be expected to change if the same ping is sent twice\n\npingsByPingId = pings \\\n .map(lambda p: (p.get(\"id\",\"MISSING\"),\n [{k:p[k] for k in p.keys() if k!=\"meta\"}]) ) \\\n .reduceByKey(lambda l1,l2: l1+l2)\npingsByPingId.cache()", "outputs": [], "metadata": {"collapsed": true, "trusted": true}}, {"source": "# Group pings by clientId \nGet the \"payload/info\" section recent pings from builds newer than 20150507000000, and which are not idle-daily pings, and group by clientId", "cell_type": "markdown", "metadata": {}}, {"execution_count": 6, "cell_type": "code", "source": "info = get_pings_properties(pings, [\"id\",\n \"clientId\",\n \"type\",\n \"payload/info\",\n \"environment/build/buildId\"])\n\nsubsess = info.filter(\n lambda p: ((p[\"payload/info\"].get(\"reason\", \"idle-daily\") != \"idle-daily\") and\n (p[\"type\"] == \"main\") and\n (p[\"environment/build/buildId\"]>\"20150507000000\")) )\n\n# subsess.cache()\n# numPings = subsess.count()\n\n# numPings", "outputs": [], "metadata": {"collapsed": true, "trusted": true}}, {"execution_count": 7, "cell_type": "code", "source": "clients = subsess.map(lambda p: (p.get(\"clientId\",\"noId\"),\n [p[\"payload/info\"]]) ) \\\n .reduceByKey(lambda l1,l2: l1+l2)", "outputs": [{"execution_count": 7, "output_type": "execute_result", "data": {"text/plain": "PythonRDD[11] at RDD at PythonRDD.scala:43"}, "metadata": {}}], "metadata": {"collapsed": false, "trusted": true}}, {"source": "### Remove duplicate subsessions for each client", "cell_type": "markdown", "metadata": {}}, {"execution_count": 42, "cell_type": "code", "source": "def dropDupeSubsessions(subsessList):\n subsessIdsAdded = []\n subsessListOut = []\n for s in subsessList:\n if s['subsessionId'] not in subsessIdsAdded:\n subsessIdsAdded.append(s['subsessionId'])\n subsessListOut.append(s)\n return subsessListOut\n \n", "outputs": [], "metadata": {"collapsed": true, "trusted": true}}, {"execution_count": 43, "cell_type": "code", "source": "cleanedClients = clients \\\n .map(lambda id_sesslist: (id_sesslist[0],dropDupeSubsessions(id_sesslist[1])) )\n\n# cleanedClients.cache()\n# numClients = cleanedClients.count()\n# numClients", "outputs": [], "metadata": {"collapsed": false, "trusted": true}}, {"execution_count": 44, "cell_type": "code", "source": "# cc = cleanedClients.first()", "outputs": [], "metadata": {"collapsed": true, "trusted": true}}, {"source": "##Construct session graphs and compute degree distributions over graphs\n\nOnce we've grouped by clientId, we can use the subSessionIds and previousSubsessionId pointer to construct a graph of the session, and then look at the degree of each node in the graph to see whether the graph looks the way we expect. Ideally, we should have a graph that has *zero* nodes with degree greater than 1 (no subsession should be pointed at by two or more sessions) and only *one* node with degree zero (the first subsession in the chain won't point to any prior subsession). Additionally, any given value of 'profileSubsessionCounter' should appear only once.\n", "cell_type": "markdown", "metadata": {}}, {"execution_count": 34, "cell_type": "code", "source": "def sessGraphFromList(sessInfoList):\n g = nx.DiGraph()\n for s in sessInfoList:\n # each s is a separate subsession submission \"info\" section\n \n # have to clear these vars to prevent spillover from previous iter\n subsessId = None \n prevSubSess = None\n \n try:\n subsessId = s['subsessionId']\n except KeyError:\n continue\n\n N = s.get(\"profileSubsessionCounter\",\"NA\")\n g.add_node(subsessId,subSessNum=N)\n\n prevSubSess = s.get('previousSubsessionId',None)\n if prevSubSess:\n g.add_node(prevSubSess)\n g.add_edge(subsessId,prevSubSess)\n return g\n\n\ndef degreeDistrib(g):\n return collections.Counter(g.out_degree().values())\n\ndef subsessSummary(sessInfoList):\n g = sessGraphFromList(sessInfoList)\n d = degreeDistrib(g)\n subSessCounterMult = collections.Counter(map(lambda x:x[\"profileSubsessionCounter\"], sessInfoList))\n return {\"info\":sorted(sessInfoList, key=lambda x:x[\"profileSubsessionCounter\"]),\n \"graph\":g,\n \"degDist\":d,\n \"subSessCounterMult\":subSessCounterMult}\n", "outputs": [], "metadata": {"collapsed": true, "trusted": true}}, {"execution_count": 45, "cell_type": "code", "source": "# cc", "outputs": [{"execution_count": 45, "output_type": "execute_result", "data": {"text/plain": "(u'fe976713-23da-425e-a3b7-f2eda532f22c',\n [{u'addons': u'%7B972ce4c6-7e08-4474-a285-3208198ce6fd%7D:41.0a1',\n u'asyncPluginInit': False,\n u'flashVersion': u'17.0.0.169',\n u'previousSubsessionId': u'5e62b0fe-2b6e-41f0-9caa-cd7fe00b7905',\n u'profileSubsessionCounter': 26,\n u'reason': u'daily',\n u'revision': u'https://hg.mozilla.org/mozilla-central/rev/b9424d63fe35',\n u'sessionId': u'751eae58-97e0-48b6-927e-630e19ea6067',\n u'sessionStartDate': u'2015-05-29T00:00:00.0+02:00',\n u'subsessionCounter': 1,\n u'subsessionId': u'b9ec15b9-053f-4a6a-a358-5c7371620558',\n u'subsessionLength': 11785,\n u'subsessionStartDate': u'2015-05-29T00:00:00.0+02:00',\n u'timezoneOffset': 120},\n {u'addons': u'%7B972ce4c6-7e08-4474-a285-3208198ce6fd%7D:41.0a1',\n u'asyncPluginInit': False,\n u'flashVersion': u'17.0.0.169',\n u'previousBuildId': u'20150520030205',\n u'previousSubsessionId': u'99c616b4-6965-44d4-8a7e-d3fe44317371',\n u'profileSubsessionCounter': 25,\n u'reason': u'shutdown',\n u'revision': u'https://hg.mozilla.org/mozilla-central/rev/b9424d63fe35',\n u'sessionId': u'8f60bec5-1115-491d-b285-34d076c0285f',\n u'sessionStartDate': u'2015-05-29T00:00:00.0+02:00',\n u'subsessionCounter': 1,\n u'subsessionId': u'5e62b0fe-2b6e-41f0-9caa-cd7fe00b7905',\n u'subsessionLength': 3910,\n u'subsessionStartDate': u'2015-05-29T00:00:00.0+02:00',\n u'timezoneOffset': 120},\n {u'addons': u'%7B972ce4c6-7e08-4474-a285-3208198ce6fd%7D:41.0a1',\n u'asyncPluginInit': False,\n u'flashVersion': u'17.0.0.169',\n u'previousSubsessionId': u'cc99753e-311e-483e-8465-8c52ff11ebc8',\n u'profileSubsessionCounter': 20,\n u'reason': u'shutdown',\n u'revision': u'https://hg.mozilla.org/mozilla-central/rev/62d9b117c688',\n u'sessionId': u'66e93273-7b07-44c8-85e3-fa7c36ceaa9c',\n u'sessionStartDate': u'2015-05-18T00:00:00.0+02:00',\n u'subsessionCounter': 2,\n u'subsessionId': u'fdad78f2-6fe9-43f3-9e47-bb147afebd99',\n u'subsessionLength': 33290,\n u'subsessionStartDate': u'2015-05-18T00:00:00.0+02:00',\n u'timezoneOffset': 120},\n {u'addons': u'%7B972ce4c6-7e08-4474-a285-3208198ce6fd%7D:41.0a1',\n u'asyncPluginInit': False,\n u'flashVersion': u'17.0.0.169',\n u'previousSubsessionId': u'fdad78f2-6fe9-43f3-9e47-bb147afebd99',\n u'profileSubsessionCounter': 21,\n u'reason': u'shutdown',\n u'revision': u'https://hg.mozilla.org/mozilla-central/rev/62d9b117c688',\n u'sessionId': u'15c3b65e-00f2-44c9-8946-79187522eb5f',\n u'sessionStartDate': u'2015-05-19T00:00:00.0+02:00',\n u'subsessionCounter': 1,\n u'subsessionId': u'1e994161-c014-4ae0-b410-57e1cda231cc',\n u'subsessionLength': 844,\n u'subsessionStartDate': u'2015-05-19T00:00:00.0+02:00',\n u'timezoneOffset': 120},\n {u'addons': u'%7B972ce4c6-7e08-4474-a285-3208198ce6fd%7D:41.0a1',\n u'asyncPluginInit': False,\n u'flashVersion': u'17.0.0.169',\n u'previousBuildId': u'20150513030209',\n u'previousSubsessionId': u'1e994161-c014-4ae0-b410-57e1cda231cc',\n u'profileSubsessionCounter': 22,\n u'reason': u'shutdown',\n u'revision': u'https://hg.mozilla.org/mozilla-central/rev/2f6ea66057fe',\n u'sessionId': u'77d37251-6b7d-4418-ae33-2222c0008cbf',\n u'sessionStartDate': u'2015-05-20T00:00:00.0+02:00',\n u'subsessionCounter': 1,\n u'subsessionId': u'3a09aae1-c443-4194-adb4-bf7cc44e58c5',\n u'subsessionLength': 33,\n u'subsessionStartDate': u'2015-05-20T00:00:00.0+02:00',\n u'timezoneOffset': 120},\n {u'addons': u'%7B972ce4c6-7e08-4474-a285-3208198ce6fd%7D:41.0a1',\n u'asyncPluginInit': False,\n u'flashVersion': u'17.0.0.169',\n u'previousBuildId': u'20150519030202',\n u'previousSubsessionId': u'b4245d65-ca11-4843-a037-db1e3e0e8021',\n u'profileSubsessionCounter': 24,\n u'reason': u'shutdown',\n u'revision': u'https://hg.mozilla.org/mozilla-central/rev/ac277e615f8f',\n u'sessionId': u'5dbb8ee9-2a6e-4c63-805f-7a6181dae5fd',\n u'sessionStartDate': u'2015-05-21T00:00:00.0+02:00',\n u'subsessionCounter': 1,\n u'subsessionId': u'99c616b4-6965-44d4-8a7e-d3fe44317371',\n u'subsessionLength': 501,\n u'subsessionStartDate': u'2015-05-21T00:00:00.0+02:00',\n u'timezoneOffset': 120},\n {u'addons': u'%7B972ce4c6-7e08-4474-a285-3208198ce6fd%7D:41.0a1',\n u'asyncPluginInit': False,\n u'flashVersion': u'17.0.0.169',\n u'previousBuildId': u'20150517030204',\n u'previousSubsessionId': u'3a09aae1-c443-4194-adb4-bf7cc44e58c5',\n u'profileSubsessionCounter': 23,\n u'reason': u'shutdown',\n u'revision': u'https://hg.mozilla.org/mozilla-central/rev/4fb7ff694bf5',\n u'sessionId': u'e49e3cbf-5184-46bf-ba7b-e8fa7935e2fc',\n u'sessionStartDate': u'2015-05-20T00:00:00.0+02:00',\n u'subsessionCounter': 1,\n u'subsessionId': u'b4245d65-ca11-4843-a037-db1e3e0e8021',\n u'subsessionLength': 19947,\n u'subsessionStartDate': u'2015-05-20T00:00:00.0+02:00',\n u'timezoneOffset': 120}])"}, "metadata": {}}], "metadata": {"collapsed": true, "trusted": true}}, {"execution_count": 46, "cell_type": "code", "source": "subsessSummaries = cleanedClients.map(lambda c: (c[0],subsessSummary(c[1])))\n# subsessSummaries.cache()", "outputs": [], "metadata": {"collapsed": false, "trusted": true}}, {"execution_count": 38, "cell_type": "code", "source": "# sss = subsessSummaries.take(1)", "outputs": [{"ename": "Py4JJavaError", "evalue": "An error occurred while calling z:org.apache.spark.api.python.PythonRDD.runJob.\n: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 10.3 failed 4 times, most recent failure: Lost task 0.3 in stage 10.3 (TID 223299, ip-10-228-135-214.us-west-2.compute.internal): org.apache.spark.api.python.PythonException: Traceback (most recent call last):\n File \"/mnt/var/lib/hadoop/tmp/nm-local-dir/usercache/hadoop/filecache/10/spark-assembly-1.2.1-hadoop2.4.0.jar/pyspark/worker.py\", line 107, in main\n process()\n File \"/mnt/var/lib/hadoop/tmp/nm-local-dir/usercache/hadoop/filecache/10/spark-assembly-1.2.1-hadoop2.4.0.jar/pyspark/worker.py\", line 98, in process\n serializer.dump_stream(func(split_index, iterator), outfile)\n File \"/mnt/var/lib/hadoop/tmp/nm-local-dir/usercache/hadoop/filecache/10/spark-assembly-1.2.1-hadoop2.4.0.jar/pyspark/serializers.py\", line 231, in dump_stream\n vs = list(itertools.islice(iterator, batch))\n File \"/home/hadoop/spark/python/pyspark/rdd.py\", line 1117, in takeUpToNumLeft\n yield next(iterator)\n File \"<ipython-input-35-8cf34cf6d752>\", line 1, in <lambda>\n File \"<ipython-input-34-97af35f3d138>\", line 29, in subsessSummary\n File \"<ipython-input-34-97af35f3d138>\", line 11, in sessGraphFromList\nTypeError: list indices must be integers, not str\n\n\tat org.apache.spark.api.python.PythonRDD$$anon$1.read(PythonRDD.scala:137)\n\tat org.apache.spark.api.python.PythonRDD$$anon$1.<init>(PythonRDD.scala:174)\n\tat org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:96)\n\tat org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:280)\n\tat org.apache.spark.rdd.RDD.iterator(RDD.scala:247)\n\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)\n\tat org.apache.spark.scheduler.Task.run(Task.scala:56)\n\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:200)\n\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)\n\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)\n\tat java.lang.Thread.run(Thread.java:745)\n\nDriver stacktrace:\n\tat org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1214)\n\tat org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1203)\n\tat org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1202)\n\tat scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)\n\tat scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)\n\tat org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1202)\n\tat org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:696)\n\tat org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:696)\n\tat scala.Option.foreach(Option.scala:236)\n\tat org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:696)\n\tat org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1420)\n\tat akka.actor.Actor$class.aroundReceive(Actor.scala:465)\n\tat org.apache.spark.scheduler.DAGSchedulerEventProcessActor.aroundReceive(DAGScheduler.scala:1375)\n\tat akka.actor.ActorCell.receiveMessage(ActorCell.scala:516)\n\tat akka.actor.ActorCell.invoke(ActorCell.scala:487)\n\tat akka.dispatch.Mailbox.processMailbox(Mailbox.scala:238)\n\tat akka.dispatch.Mailbox.run(Mailbox.scala:220)\n\tat akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:393)\n\tat scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)\n\tat scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)\n\tat scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)\n\tat scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)\n", "traceback": ["\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[1;31mPy4JJavaError\u001b[0m Traceback (most recent call last)", "\u001b[1;32m<ipython-input-38-35e49ca3c093>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0msss\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0msubsessSummaries\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtake\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[1;32m/home/hadoop/spark/python/pyspark/rdd.py\u001b[0m in \u001b[0;36mtake\u001b[1;34m(self, num)\u001b[0m\n\u001b[0;32m 1119\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1120\u001b[0m \u001b[0mp\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mrange\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpartsScanned\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmin\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpartsScanned\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mnumPartsToTry\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtotalParts\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1121\u001b[1;33m \u001b[0mres\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcontext\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrunJob\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtakeUpToNumLeft\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mp\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 1122\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1123\u001b[0m \u001b[0mitems\u001b[0m \u001b[1;33m+=\u001b[0m \u001b[0mres\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;32m/home/hadoop/spark/python/pyspark/context.py\u001b[0m in \u001b[0;36mrunJob\u001b[1;34m(self, rdd, partitionFunc, partitions, allowLocal)\u001b[0m\n\u001b[0;32m 825\u001b[0m \u001b[1;31m# SparkContext#runJob.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 826\u001b[0m \u001b[0mmappedRDD\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mrdd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmapPartitions\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpartitionFunc\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 827\u001b[1;33m \u001b[0mit\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_jvm\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPythonRDD\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrunJob\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_jsc\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmappedRDD\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_jrdd\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mjavaPartitions\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mallowLocal\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 828\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mlist\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmappedRDD\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_collect_iterator_through_file\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mit\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 829\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;32m/home/hadoop/anaconda/lib/python2.7/site-packages/py4j/java_gateway.pyc\u001b[0m in \u001b[0;36m__call__\u001b[1;34m(self, *args)\u001b[0m\n\u001b[0;32m 536\u001b[0m \u001b[0manswer\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mgateway_client\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msend_command\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcommand\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 537\u001b[0m return_value = get_return_value(answer, self.gateway_client,\n\u001b[1;32m--> 538\u001b[1;33m self.target_id, self.name)\n\u001b[0m\u001b[0;32m 539\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 540\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mtemp_arg\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mtemp_args\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;32m/home/hadoop/anaconda/lib/python2.7/site-packages/py4j/protocol.pyc\u001b[0m in \u001b[0;36mget_return_value\u001b[1;34m(answer, gateway_client, target_id, name)\u001b[0m\n\u001b[0;32m 298\u001b[0m raise Py4JJavaError(\n\u001b[0;32m 299\u001b[0m \u001b[1;34m'An error occurred while calling {0}{1}{2}.\\n'\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 300\u001b[1;33m format(target_id, '.', name), value)\n\u001b[0m\u001b[0;32m 301\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 302\u001b[0m raise Py4JError(\n", "\u001b[1;31mPy4JJavaError\u001b[0m: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.runJob.\n: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 10.3 failed 4 times, most recent failure: Lost task 0.3 in stage 10.3 (TID 223299, ip-10-228-135-214.us-west-2.compute.internal): org.apache.spark.api.python.PythonException: Traceback (most recent call last):\n File \"/mnt/var/lib/hadoop/tmp/nm-local-dir/usercache/hadoop/filecache/10/spark-assembly-1.2.1-hadoop2.4.0.jar/pyspark/worker.py\", line 107, in main\n process()\n File \"/mnt/var/lib/hadoop/tmp/nm-local-dir/usercache/hadoop/filecache/10/spark-assembly-1.2.1-hadoop2.4.0.jar/pyspark/worker.py\", line 98, in process\n serializer.dump_stream(func(split_index, iterator), outfile)\n File \"/mnt/var/lib/hadoop/tmp/nm-local-dir/usercache/hadoop/filecache/10/spark-assembly-1.2.1-hadoop2.4.0.jar/pyspark/serializers.py\", line 231, in dump_stream\n vs = list(itertools.islice(iterator, batch))\n File \"/home/hadoop/spark/python/pyspark/rdd.py\", line 1117, in takeUpToNumLeft\n yield next(iterator)\n File \"<ipython-input-35-8cf34cf6d752>\", line 1, in <lambda>\n File \"<ipython-input-34-97af35f3d138>\", line 29, in subsessSummary\n File \"<ipython-input-34-97af35f3d138>\", line 11, in sessGraphFromList\nTypeError: list indices must be integers, not str\n\n\tat org.apache.spark.api.python.PythonRDD$$anon$1.read(PythonRDD.scala:137)\n\tat org.apache.spark.api.python.PythonRDD$$anon$1.<init>(PythonRDD.scala:174)\n\tat org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:96)\n\tat org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:280)\n\tat org.apache.spark.rdd.RDD.iterator(RDD.scala:247)\n\tat org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)\n\tat org.apache.spark.scheduler.Task.run(Task.scala:56)\n\tat org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:200)\n\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)\n\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)\n\tat java.lang.Thread.run(Thread.java:745)\n\nDriver stacktrace:\n\tat org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1214)\n\tat org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1203)\n\tat org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1202)\n\tat scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)\n\tat scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)\n\tat org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1202)\n\tat org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:696)\n\tat org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:696)\n\tat scala.Option.foreach(Option.scala:236)\n\tat org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:696)\n\tat org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1420)\n\tat akka.actor.Actor$class.aroundReceive(Actor.scala:465)\n\tat org.apache.spark.scheduler.DAGSchedulerEventProcessActor.aroundReceive(DAGScheduler.scala:1375)\n\tat akka.actor.ActorCell.receiveMessage(ActorCell.scala:516)\n\tat akka.actor.ActorCell.invoke(ActorCell.scala:487)\n\tat akka.dispatch.Mailbox.processMailbox(Mailbox.scala:238)\n\tat akka.dispatch.Mailbox.run(Mailbox.scala:220)\n\tat akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:393)\n\tat scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)\n\tat scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)\n\tat scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)\n\tat scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)\n"], "output_type": "error"}], "metadata": {"collapsed": true, "trusted": true}}, {"execution_count": 47, "cell_type": "code", "source": "badGraphSummaries = subsessSummaries.filter(\n lambda id_summary: any([k>1 for k in id_summary[1][\"degDist\"].keys()]) \\\n or any([v>1 for k,v in id_summary[1][\"degDist\"].iteritems() if k!=1]) \\\n or any([v>1 for v in id_summary[1][\"subSessCounterMult\"].values()]) )\nbadGraphSummaries.cache()\nnumBadGraphs = badGraphSummaries.count()\nnumBadGraphs", "outputs": [{"execution_count": 47, "output_type": "execute_result", "data": {"text/plain": "32547"}, "metadata": {}}], "metadata": {"scrolled": true, "collapsed": false, "trusted": true}}, {"source": "#Percentage of clients with bad session graphs", "cell_type": "markdown", "metadata": {}}, {"execution_count": 48, "cell_type": "code", "source": "numBadGraphs/float(numClients)", "outputs": [{"execution_count": 48, "output_type": "execute_result", "data": {"text/plain": "0.33243450283438025"}, "metadata": {}}], "metadata": {"collapsed": false, "trusted": true}}, {"source": "##Grab a few examples of graphs with imperfect session chains and plot them", "cell_type": "markdown", "metadata": {}}, {"execution_count": 163, "cell_type": "code", "source": "bg = badGraphSummaries.take(100)", "outputs": [], "metadata": {"collapsed": false, "trusted": true}}, {"execution_count": 106, "cell_type": "code", "source": "def sessGraphFromList2(sessInfoList,byDate=True):\n g = nx.DiGraph()\n subSessIds = [s['subsessionId'] for s in sessInfoList]\n numInferred = 0\n nodePositions = []\n \n for s in sessInfoList:\n # each s is a separate subsession submission \"info\" section\n \n # have to clear these vars to prevent spillover from previous iter\n subsessId = None \n prevSubSess = None\n \n try:\n subsessId = s['subsessionId']\n except KeyError:\n continue\n\n N = s.get(\"profileSubsessionCounter\",-1)\n subSessCounter = s.get(\"subsessionCounter\",-1)\n #if a node has already been added with this (x,y) position, bump up the y position\n if byDate:\n dateStr = s.get(\"sessionStartDate\",\"2015-01-01\")[0:10]\n dateNum = datetime.datetime.strptime(dateStr,\"%Y-%m-%d\").toordinal()\n thisPosition = [dateNum,subSessCounter]\n else:\n thisPosition = [N,subSessCounter]\n while thisPosition in nodePositions:\n thisPosition[1]+=1\n g.add_node(subsessId,subSessNum=N,x=thisPosition[0], y=thisPosition[1])\n nodePositions.append(thisPosition)\n \n prevSubSess = s.get('previousSubsessionId',None)\n# if prevSubSess:\n# #NB: adding these nodes allows us to infer the existence\n# #of some sessions that have not actually been submitted.\n# # Nodes added this way will not have any data attached to them.\n# g.add_node(prevSubSess)\n# g.add_edge(subsessId,prevSubSess)\n if prevSubSess in subSessIds:\n #NB: adding these nodes allows us to infer the existence\n #of some sessions that have not actually been submitted.\n # Nodes added this way will not have any data attached to them.\n g.add_node(prevSubSess)\n g.add_edge(subsessId,prevSubSess) \n \n \n #add placement details for inferred nodes\n for nodeId,nodeData in (tup for tup in g.nodes(data=True) if not tup[1]):\n pred = g.predecessors(nodeId)[0]\n nodeData[\"x\"] = g.node[pred][\"x\"]-random.random()/3 +.1/.6\n nodeData[\"y\"] = g.node[pred][\"y\"]-1-random.random()\n \n return g\n", "outputs": [], "metadata": {"collapsed": false, "trusted": true}}, {"execution_count": 118, "cell_type": "code", "source": "def plotSessGraph(g):\n pos = {n:[d['x'],d[\"y\"]] for n,d in g.nodes(data=True)}\n fig, ax = plt.subplots(1,figsize=(18,3), dpi=100)\n G = nx.draw(g,pos=pos,ax=ax,node_size=300, node_color=\"w\")\n for sessId,nodeData in [(n,d) for n,d in g.nodes(data=True) if d]:\n x,y = nodeData[\"x\"],nodeData[\"y\"]\n subSessNum = nodeData.get(\"subSessNum\",\"NA\")\n plt.text(x,y-.1,s=subSessNum\n ,horizontalalignment='center')\n plt.show()\n\n", "outputs": [], "metadata": {"collapsed": false, "trusted": true}}, {"execution_count": 152, "cell_type": "code", "source": "def plotSessGraphAndInfo(i_x):\n i,x = i_x\n sessInfoList = x[1][\"info\"]\n g = sessGraphFromList2(sessInfoList)\n dg = degreeDistrib(g)\n print \"############################################\"\n print \"session graph index:\", i\n \n if any([k>1 for k in dg.keys()]) \\\n or any([v>1 for k,v in dg.iteritems() if k!=1]):\n print \"bad degree distribution: \",dg\n \n \n subSessCounterMult = collections.Counter(map(lambda x:x[\"profileSubsessionCounter\"], sessInfoList))\n if any([v>1 for v in subSessCounterMult.values()]):\n print \"repeated profileSubsessionCounter(s): \", {c:m for c,m in subSessCounterMult.iteritems() if m>1}\n \n# print \n# print collections.Counter(map(lambda x:x[\"profileSubsessionCounter\"], sessInfoList))\n print \"subsessions by date\"\n plotSessGraph(g)\n \n print \"subsessions by profileSubsessionCounter (x-axis)\"\n g = sessGraphFromList2(sessInfoList,byDate=False)\n plotSessGraph(g)\n", "outputs": [], "metadata": {"collapsed": true, "trusted": true}}, {"source": "##Explanation of the plots used below\n\nIn what follows, two plots are drawn for depicting the subsession histories of a sample of clients. For each client, we draw:\n1. The subsession graph organized by date the x-axis. In these plots, all the subsession that occured on one day are stacked in vertical column coresponding to the integer day number. These plots help to show cases in which \"profileSubsessionCounter\" is reset to 1.\n2. The subsession graph organized by subsessionId. In these plots, the x-axis position of each subsession is given by its subsession number. These plots help to show cases in which there are big gaps between recorded subsession.\n\n", "cell_type": "markdown", "metadata": {}}, {"execution_count": 153, "cell_type": "code", "source": "i=0\nplotSessGraphAndInfo((i,bg[i]))\n# bg[i]", "outputs": [{"output_type": "stream", "name": "stdout", "text": "############################################\nsession graph index: 0\nbad degree distribution: Counter({1: 36, 0: 2})\nsubsessions by date\n"}, {"output_type": "display_data", "data": {"image/png": 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ix2frsaeiokJiY2NlyZIljd6GLdk6H3N988034u3tLfn5+VbfV3N25coVWb9+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\nebz44osYPny40s2hZoBFAiIFeHl54fr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"text/plain": "<matplotlib.figure.Figure at 0x7f560c65c1d0>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "subsessions by profileSubsessionCounter (x-axis)\n"}, {"output_type": "display_data", "data": {"image/png": 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"text/plain": "<matplotlib.figure.Figure at 0x7f560c29c3d0>"}, "metadata": {}}], "metadata": {"scrolled": true, "collapsed": false, "trusted": true}}, {"source": "##Clients with profileSubsessionCounter reset to 1\n\nThe following clients have had their profileSubsessionCounter reset at some point. Some of these also have missing subsessions.", "cell_type": "markdown", "metadata": {}}, {"execution_count": 171, "cell_type": "code", "source": "resetClients = []\nfor i,clientData in enumerate(bg):\n clientDates = [ss.get('sessionStartDate',0) for ss in clientData[1][\"info\"]]\n \n if any([ (ss.get('profileSubsessionCounter',0)==1\n and any(ss.get('sessionStartDate',None)>d for d in clientDates))\n for ss in clientData[1][\"info\"]]):\n print i\n plotSessGraphAndInfo((i,clientData))\n resetClients.append(i)", "outputs": [{"output_type": "stream", "name": "stdout", "text": "0\n############################################\nsession graph index: 0\nbad degree distribution: Counter({1: 36, 0: 2})\nsubsessions by date\n"}, {"output_type": "display_data", "data": {"image/png": 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ix2frsaeiokJiY2NlyZIljd6GLdk6H3N988034u3tLfn5+VbfV3N25coVWb9+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\nebz44osYPny40s2hZoBFAiIFeHl54fr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"text/plain": "<matplotlib.figure.Figure at 0x7f55cc60bc50>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "subsessions by profileSubsessionCounter (x-axis)\n"}, {"output_type": "display_data", "data": {"image/png": 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"text/plain": "<matplotlib.figure.Figure at 0x7f564c2836d0>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "1\n############################################\nsession graph index: 1\nbad degree distribution: Counter({1: 11, 0: 2})\nsubsessions by date\n"}, {"output_type": "display_data", "data": {"image/png": 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Gw3RCKF+fAOBvTC3A7qjrAHyhkeBAob6hB/q8hGDkGcrTCaF+fQJAV2NqAXZC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\n", "text/plain": "<matplotlib.figure.Figure at 0x7f560c474690>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "subsessions by profileSubsessionCounter (x-axis)\n"}, {"output_type": "display_data", "data": {"image/png": 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fP39Mzy8qKlJZWZmMMRYnG91Ybsu43rJlyybtffHUYgi1gJfRTAAAAICnBCZgY11pkJSU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\nd99996bf2/FciR9t3L179+o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"text/plain": "<matplotlib.figure.Figure at 0x7f564c5305d0>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "2\n############################################\nsession graph index: 2\nbad degree distribution: Counter({1: 36, 0: 2})\nsubsessions by date\n"}, {"output_type": "display_data", "data": {"image/png": 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+/v5X3RYuXyAiT8dlC0RERETklKqqqhAYGGjeVSE0NBShoaFITEwEAKSmpqKkpASFhYVI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\nEg8AAACASDwAAAAAIvEAAAAAiMQDAAAAIBIPAAA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"text/plain": "<matplotlib.figure.Figure at 0x7f564c6d7c90>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "subsessions by profileSubsessionCounter (x-axis)\n"}, {"output_type": "display_data", "data": {"image/png": 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PfiJvvPFG1GKIF75jetVVV8lLL70kubm5sm/fPtm8ebMhfbjdbunq6pLMzEy55JJL5IUX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\nrCGX19bWakpKiubm5vr14Xm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"text/plain": "<matplotlib.figure.Figure at 0x7f55ec370bd0>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "4\n############################################\nsession graph index: 4\nbad degree distribution: Counter({1: 12, 0: 2})\nrepeated profileSubsessionCounter(s): {1: 2, 2: 2, 3: 2, 4: 2, 5: 2}\nsubsessions by date\n"}, {"output_type": "display_data", "data": {"image/png": 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"text/plain": "<matplotlib.figure.Figure at 0x7f564c1c9990>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "subsessions by profileSubsessionCounter (x-axis)\n"}, {"output_type": "display_data", "data": {"image/png": 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QUBDS09NRXV3dvJ6VlYVhw4bh8ccfl5hOWXbs2IG//vWv+Oyzz/DAAw8Y7Hkef/xx2Nvb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\nLzR/bcWKFWLGjBm8RkwQGwkWQK1Wi71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"text/plain": "<matplotlib.figure.Figure at 0x7f562c70e550>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "6\n############################################\nsession graph index: 6\nbad degree distribution: Counter({1: 14, 0: 2})\nsubsessions by date\n"}, {"output_type": "display_data", "data": {"image/png": 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"text/plain": "<matplotlib.figure.Figure at 0x7f564c6d7d90>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "subsessions by profileSubsessionCounter (x-axis)\n"}, {"output_type": "display_data", "data": {"image/png": 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/aOfOnQ3XshMnTigjI8PHqT3j5MmTiouLc3ldz8rK0hNPPKGKioqLCigBWMdbGwAErKKi\nIo0ePVplZWXq1KmTJKmmpkZVVVWSpM6dOys8PFzjxo3TqlWrGvbr1KmTdu/erW7duvkkNwAAPzp2\n7JhiYmK0evVqDRkyRJLza9mSJUv09NNPO+y7adMmDRs2zNuRPaaqqkqxsbFav369EhISJDlfCwCt\nxyABQECqr6/XkCFDNHnyZE2aNKnRbQ8ePKi+ffvqhx9+aHjsscce09KlSz0dEwCARmVkZKiqqkq5\nubmNbnfu3DkNGjRIpaWlDY/FxsaqtLRUISEhno7pFenp6QoODtarr77q6yiA3+OtDQACUm5urtq1\na6eJEyc2uW1kZKReeuklh8eWLVumzz77zFPxAABo0o4dO/Tmm28qMzOzyW3btWunJUuWODy2a9cu\nLV682FPxvKq4uFgFBQWaOXOmr6MAAYE7EgAEnKqqKsXExGjDhg0Ntz42pba2VvHx8fryyy8bHktM\nTNTWrVvVrl07T0UFAMApY4yGDx+u+++/X+np6Zb3mzRpkt54442GP3fo0EG7d+/W1Vdf7YGU3lFf\nX69bbrlFkydP1iOPPOLrOEBA4I4EAAHnxRdf1H333Wd5iCBJoaGhDrdKhoaGasqUKQoKCvJERAAA\nGpWXl6djx47pySefbNZ+c+fOdegJ+PWvf60rrrjC3fG86vXXX1dwcLAmTJjg6yhAwGjv6wAA4E1F\nRUUqKChQWVlZs/dNSUnR+PHjFRYWpo0bN+qaa65RcDDzWACAdx07dkwZGRlavXp1s++K6969u2bN\nmqWCggK1a9dOV1xxhTp06OChpJ5XVVWlF198UevXr+eaDHgRb20AEDCaU7DY2GsEBwfrvffe04wZ\nM/TFF18oNDTUzUkBAHDNasGiK/X19QoKCtLBgweVkJCgrVu36tprr3VzSu+gYBHwDQYJAALG0qVL\nlZubqy1btrT6txbGGI0aNUrDhw/XCy+84KaEAAA0bseOHbrtttu0Y8cOde/evdWvl5mZqU8//VSF\nhYVuSOddxcXFGj16tHbt2tXwMc4AvINBAoCA0JKCxaZ89dVXuvnmm1VaWqrIyEi3vCYAAK60tGCx\nMbW1tRowYIAWLFig0aNHu+U1vYGCRcC3eCMRgIDQkoLFplx//fWaMmWKMjIy3PaaAAC40tKCxcaE\nhoZq8eLFeuaZZ3Tq1Cm3va6nUbAI+BZ3JADwe0VFRRo9erTKysrcfuvjyZMnFRcXp6VLlyolJcWt\nrw0AwI+OHTummJgYrV69WkOGDHH76993333q16+fXnrpJbe/trtVVVUpNjZW69evd+svCABYxyAB\ngF9zR8FiUyheBAB4WmsLFpty4MCBNlO8SMEi4HsMEgD4NXcWLLpC8SIAwJPcXbDoSlsoXqRgEbAH\nBgkA/JYnChZdoXgRAOAJnihYdMXuxYsULAL2QdkiAL/liYJFVyheBAB4gicKFl2xe/EiBYuAfXBH\nAgC/5MmCRVcoXgQAuJOnCxZdsWPxIgWLgL0wSADgd7xRsOgKxYsAAHfxdMGiK3YsXqRgEbAXBgkA\n/I43ChZdoXgRAOAO3ipYdMVOxYsULAL2wyABgF/xZsGiKxQvAgBaw5sFi67YpXiRgkXAnihbBOBX\nvFmw6ArFiwCA1vBmwaIrdilepGARsCfuSADgN3xRsOgKxYsAgJbwVcGiK74sXqRgEbAvBgkA/IIv\nCxZdoXgRANBcvipYdMWXxYsULAL2xSABgF/wZcGiKxQvAgCaw9cFi674oniRgkXA3hgkAGjz7FCw\n6ArFiwAAK+xQsOiKt4sXKVgE7M8ev7YDgFawQ8GiKxQvAgCssEPBoiveLl6kYBGwP+5IANCm2alg\n0RWKFwEAjbFbwaIr3ihepGARaBsYJABos+xYsOgKxYsAAFfsVrDoijeKFylYBNoGBgkA2iw7Fiy6\nQvEiAMAZuxYsuuLJ4kUKFoG2g0ECgDbJzgWLrlC8CAD4OTsXLLriqeJFChaBtsXev8IDABfsXLDo\nCsWLAICfs3PBoiueKl6kYBFoW7gjAUCb0xYKFl2heBEAILWdgkVX3Fm8SMEi0PYwSADQZtTX10tS\nmylYdIXiRQAIXPX19QoODm4zBYuuuKN48ce1oGARaHva/fGPf/yjr0MAQFN27dqloUOHas+ePTp8\n+LCys7MVFBTk61gt0qdPH61bt07fffedfvGLX/g6DgDAS06dOqXBgwfrm2++0fLly1VQUKCwsDBf\nx2qR8PBw1dfX67XXXtP48eObvf/x48eVlJSkffv2aeXKlVqzZo0uu+wyDyQF4Al0JACwPWOMfvOb\n32jv3r1asmSJ2rdvr/Lycl/HarGgoCBlZ2dr7ty5OnjwoK/jAAC8ZO7cudq+fbsWLFig9u3ba9eu\nXb6O1CrTpk3Tnj179P777zd735kzZ2rXrl1asGCBQkND2/xaAIGGQQIA21u1apU++uijhj9v2bJF\nJSUlPkzUehQvAkBg+frrr5WZmdnw58OHD6ugoMCHiVqvpcWLu3bt0qJFixr+fODAgRYNIwD4Dh0J\nAGzt+PHj6tu3rw4dOtTw2MiRI7Vx48Y2+9aGH1G8CACB41e/+pXD/yxHREToyy+/1JVXXunDVO7R\nnOJFY4xGjBjh8AuCqKgolZWVtdm3eQCBiDsSANjazJkzHYYIISEhWrx4cZsfIkjS5ZdfrldeeUVP\nP/20amtrfR0HAOAha9euveg37vPmzfOLIYIkLVy4UIsXL9Y333zT5LYX3mX44/4MEYC2hTsSAB+r\nqalRZWWlJKlLly4KDw8PyAzOcnz77beKj4/X2bNnG7aZMWOG5syZ45N8nmCM0ahRozR8+HC98MIL\nDY/b4XtihwyAM3Y5Nu2Qww4Z7JLDDhmc5QgNDVVcXJxDt8/QoUP1ySef+MVQ/EeZmZn69NNPVVhY\n2PDYhWsRHBzst3cZAgHHAPC606dPm7ffftsMHTrUhIWFmd69e5vevXubsLAwM3ToUPP222+bM2fO\n+H2GpnL06NHDSGr4Jyoqypw4ccLjmbxt7969pkuXLuarr77y+ffELscFcCG7HJt2yGGHDHbJYYcM\nTeW4/vrrHa5lwcHBprS01OOZvO3MmTOmT58+Jj8/3+VaXHvttQ5rERISYr788ktfRwfQAgwSAC/L\ny8szERERZsSIESY/P9/U1dU1PFdbW2vWrFljUlJSTEREhMnLy/PbDFZz3Hjjjeayyy4zksw777zj\nsSy+lpqaaq644gqOC8AJuxybdshhhwx2yWGHDFZz/PxaNnXqVI9l8bXf/e53JiwszKSkpFhaixkz\nZvgwLYDWYJAAeFFWVpaJiooyRUVFTW5bVFRkoqKiTFZWlt9laEmO7t27m1deecXtOezADt8TO2QA\nnLHLsWmHHHbIYJccdsjQkhxdu3Y1mZmZbs9hBy1Zi3nz5nkhGQBPYJAAeEleXp6Jiooy+/fvt7zP\n/v37TVRUlNt+k2KHDHbKYQd2WAs7ZACcscuxaYccdshglxx2yGCnHHbAWgCBh0EC4AWnT582ERER\npri4uNn7FhUVmYiIiFa/x9MOGeyUww7ssBZ2yAA4Y5dj0w457JDBLjnskMFOOeyAtQACEx//CHhB\nfn6++vXrp8TExGbvm5SUpLi4OOXn57f5DHbKYQd2WAs7ZACcscuxaYccdshglxx2yGCnHHbAWgAB\nyteTDCAQDB061KxZs6bF+69evdokJye3+Qx2ymEHdlgLO2QAnLHLsWmHHHbIYJccdshgpxx2wFoA\ngYlBAuBh1dXVJiwszKG5+EeTJk0y3bt3N/369Wv0NWpra01YWJiprq52ewZjjKmoqDDDhg0zsbGx\nJi4uzmkhVWszNJXj1KlT5sYbbzTx8fEmJibGZZOzO3LYQVPfk+joaNO/f38zcOBAM3jwYKfbePq4\nOHr0qElLSzN9+/Y1MTEx5l//+pfbMwDOODs2nZ0vV61aZWJjY01wcPBFt1XX1taa0NBQt5+znOXI\nyMgwffv2NQMGDDCpqakOX9MTP6fOMvz+9783AwYMMPHx8ea2224zFRUVDhncvRaNXb8WLFhggoKC\nTGVlpcPj3lqLl156yfTs2dMMHDjQDBw40Kxfv94hg7fWIjs72/Tt29fExcWZ6dOnOzznL+dOK2vx\n73//2wwePNgMHDjQDBo0yGzdutXhNfxlLYBAw1sbAA+rrKxUt27d1L59+4uemzRpkjZs2NDka4SE\nhKhr166qqqpye4YfX3/RokXauXOnPvvsMy1ZskRlZWVuzdBUjksvvVSbNm1SaWmptm/frk2bNmnL\nli1Os7Y2hx009T0JCgrSxx9/rJKSEm3dutXpNp4+Lp555hndddddKisr0/bt2xUTE+P2DIAzzo5N\nZ+fL/v37q6CgQLfeeutFrxESEqKOHTu6/ZzlLMftt9+unTt36osvvtANN9ygOXPmOORw98+pswzT\np0/XF198odLSUo0ZM0Z/+tOfHDK4ey1cXb8OHDigDz74QNHR0Rc95621CAoK0rRp01RSUqKSkhLd\neeedDhm8sRabNm1SYWGhtm/frh07digjI8PheX85d1pZi+nTp2vmzJkqKSnRn//8Z02fPt3heX9Z\nCyDQOP/bIwCvSE5O1r59+yxte+LECV177bUt/lpdu3Z1+dxVV12lq666SpLUoUMHxcTE6NChQxf9\nj2NrMzSV4/LLL5ck1dbW6ty5c+rcuXOrvlZbZ4xpchtPHRc1NTXavHmzli9fLklq3769wsPDW/x1\ngNZydr7s27dvk/u5+5zlLMfIkSMb/v2mm27SmjVrHJ5398+pswwdO3Z0+HrOfrbduRaurl/Tpk3T\nvHnzdM899zh9DW+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"text/plain": "<matplotlib.figure.Figure at 0x7f562c70e310>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "7\n############################################\nsession graph index: 7\nbad degree distribution: Counter({1: 34, 0: 3})\nsubsessions by date\n"}, {"output_type": "display_data", "data": {"image/png": 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KbNmypdk7b0dERKB3797Vbo8lam3ffPMNtm/fDi8vLzz11FPYs2cPJk6cCCcn\nJ+UX59jYWGU/gDuNi4sLAMDR0RGRkZHIyMiAs7Mz/vjjDwDAxYsX4eTk1CqxzJ49G4mJibh69Wqr\nXK+tcnV1haurKwYNGgQAiI6ORnZ2Nn7//Xf4+vrCy8sL586dQ2BgIC5dumTiaInI1Dh5QERECnt7\ne+Tl5UGv1wMA8vPzlVu0r127ht27d8Pf3x8AkJ6ejn79+uHee+81qEOv1yM/P99gb4S63LolXK1W\nK09wIGoNVfv722+/jbNnz0Kr1WLDhg0YMWIE1q5di4sXLyrnbNmyBT4+PsrrxvZ3c1E196tXr6Kk\npAQAUFpail27dsHHxwdjx47FmjVrAABr1qxBRESEUkdL5t6/f3/cf//9+Pjjj41ed1tVtc0BoHv3\n7nBzc1M+e9PT0xEYGIg//vgDWq0WWq0Wrq6uyMrKgpOTk8X2dyIyDk4eEBGRws7ODv7+/vjiiy8A\n3PxL44gRI+Dn54chQ4bgkUceQWhoKICbzwq/faPEW7Zv346AgABl062GcHd3x7x58zBt2rRaN6Yj\nMraq/f12IqLcoj979mwMHDgQvr6+2L9/P959912lXFP6uzmomntubi5CQkKUsT5mzBiMGjUKc+fO\nxe7du9G7d2/s2bMHc+fOVepo6dznzJmDpUuXGvyyS01XW39PSkrC+PHj4evri2PHjuGVV14xOH77\nUhVL7e9EZBwq4bc0IiK6zfr167Fq1Sqkp6c36fzQ0FBMnToVTz75ZKPOq6iowODBgzFz5kxMmDCh\nSdcmaixT9XdzYAm5P/jgg4iNjcX48eNb7BptiSW0ORGZL04eEBGRgbKyMnh4eCAtLc3gWeANodFo\nEB4ejpycHLRv377R187MzMSYMWPw008/wd7evtHnEzVWc/v7X//6V5w9e7ZJ/d3UTDnWG+rrr79G\nQkICjh07ZvAXcGoaS2hzIjJfXLZAREQGOnToALVajYiICOTk5DT4vJycHERGRkKtVjf5i2VQUBBi\nYmIwe/bsJp1P1FjN6e+jR49Gp06dcO3atRaMsOWYcqw31KhRo2BtbY20tLQWvU5bYQltTkTmy2r+\n/PnzTR0EERGZlwEDBsDKygqxsbF44IEHqm2KWJVGo8Ho0aORkJCAKVOmNOvaf/nLX/DSSy8hMDAQ\nnp6ezaqLqCGa0t9DQkKg0+lQVFSEw4cPIyYmBjY2Nq0UsfGYcqw3hEqlQteuXfHOO+9g8uTJLX69\ntsDc25wolqeXAAAgAElEQVSIzJgQERHVYsOGDeLs7CyhoaGyefNm0ev1yrHy8nLZtGmTjBgxQpyd\nnWXDhg1Gu25qaqr07dtXrl+/brQ6ierT0P7euXNnAWDw7+GHH5aysjITRt88phrrDaHX66Vnz55y\n8ODBVrmeTqeT06dPy+nTp0Wn07XKNU3BnNuciMwT9zwgIqI6lZSU4JVXXsGmTZtQWFgIOzs7iAgu\nX76Mbt26ITo6GosWLULnzp2Ndk0RQUREBIKCgvDaa68ZrV6i+jSkv8+bNw+RkZH47rvvDM6NiYnB\nunXrYGVlZaLom8cUY72hPvzwQ3z55Zc1PhnDGMrKypCamork5GRkZ2fD0dERAJCXlwd/f3/ExcUh\nKirqjrtl35zbnIjMD/c8ICKiWqWkpOC+++7DiRMnkJycjAsXLuD7779HRkYGzp8/jxUrVuDnn39G\nr169kJKSYrTrqlQqJCUlQa1WK88fJ2ppDe3vfn5+iI2NhY+PT7XzLfVxo6Ya6w319NNPQ6PR4Mcf\nfzR63SkpKfDw8MDq1asRHx8PnU4HrVYLrVaLoqIizJw5E6tWrYK7u7tJcm8p5t7mRGSGTHfTAxER\nmTO1Wi1ubm6SmZlZb9nMzExxc3MTtVpt1BjeeecdGTFihFRWVhq1XqKqmtLfFy5cKL169aq2hCEh\nIcGi+qw5jPWGWLx4sfztb38zap2WkruxtdW8iah5OHlARETVbNiwQdzc3OTkyZMyePBg8fX1lX79\n+sncuXOVMomJidK3b1/x9vaW2bNny5kzZ8TNzc2oa2P1er34+/vL2rVrjVYnUVW3+vuZM2dERKSi\nokL8/PxkzJgxBuWWLVsmKpVKCgoKlP6elJQkrq6u1SYQ3nrrLVOk0mj15X706FEZOnSo+Pj4yCOP\nPCKXL19ukbHeEDqdTuzt7UWr1Rqlvttz9/DwEB8fH/Hz85NBgwaJiMj3338vgwYNEj8/PwkKCpKM\njAyT5W5MVdu8qKhIoqKipG/fvtKvXz/59ttv5bXXXpOBAweKr6+vjBgxQr799luLz5uImo+TB0RE\nZOD69evi7OwsGo1GRERKS0tF5OYv8kOGDJGDBw/Knj17JCwsTMrLy0VE5NKlSyJy8y9Uzs7ORt04\n7siRI+Ls7Cz5+flGq5Polqr9XURk+fLlMm7cOHnkkUeU93JycmT06NHi6ekpBQUFIvK//v7DDz+I\no6NjtQmE9957r9XzaYyG5B4UFCQHDhwQEZHVq1fLa6+9JiItM9YbYu7cufLCCy80u56qud/errcM\nGzZMvvrqKxERSUtLk+HDh4uI6XI3hprafOLEibJq1SoRufk5r9Pp5PLly8rxxMREmTJlikXnTUTG\nwT0PiIjIQGpqKgYMGICAgAAAQKdOnQAA5eXluHHjBrp27YoPPvgAL7/8svJoulubiwUGBsLb2xup\nqalGiycoKAgxMTGYPXu20eokuqVqfz937hzS0tIQGxtrsHdBfHw8lixZYnDurf5+/PhxfP3117jn\nnnsMjr/wwgv49NNPWz6JJmpI7r/++itCQkIAAGFhYdi8eTOAlhnrDTFjxgysW7cOly5dalY9VXMH\nUG2vChcXFxQXFwMAdDodevToAcB0uRtD1byLi4tx8OBB5TGY1tbWsLOzw913362cc+XKFTg4OFh0\n3kRkHJw8ICIiA8nJyYiLi1NeV1ZWws/PD87OznjwwQfh7e2NX375BQcOHMDQoUMxfPhwZGZmKuXj\n4uKQnJxs1JgWLlyIXbt2Yf/+/Uatl6hqf585cyaWLl2Kdu3+9xVp27ZtcHV1xcCBA6udf6u/+/v7\nY8eOHbjrrrsMjk+aNAnbtm1ruQSaoSG5e3t7K/F//vnnOHv2rHKsJcZ6fbp3746YmBgkJSU1q56q\nuatUKoSFhSEoKAgfffQRAGDx4sV46aWX4O7ujlmzZmHRokVKeVPkbgxV89ZqtXB0dMQzzzyDgIAA\nTJ06FVevXgUAzJs3D+7u7lizZg3mzp0LwHLzJiIjMfGdD0REZEZ0Op3Y2toaPO/79mNDhgyRvXv3\nyoABA2T69OkiIpKRkSFeXl5KufLycrG1tTX689FTU1Olb9++cv36daPWS21X1f7+xRdfSFxcnIiI\n7N27V8aMGSOlpaUyePBgKS4uFpGbt7ffvoSman/fuXOn2NjYGCxfcHJykitXrrRydnVrSO4iIidO\nnJBRo0ZJYGCgLFiwQOzt7ZU6Wmqs1+fUqVPi4OBgcGt9Y9T0OXfhwgURubkEy9fXVw4cOCChoaGS\nmpoqIiIbN26UsLAwpbypcm+OmvI+cuSIWFtbS0ZGhoiIzJgxQ1macsuiRYtk0qRJImKZeROR8fDO\nAyIiUhQUFMDR0RHW1tbVjtnZ2SE8PByZmZlwdXXFY489BgAYNGgQ2rVrh4KCAgCAjY0NHBwcUFhY\naNTYIiIi0Lt372q3jhM1VdX+/s0332D79u3w8vLCU089hT179mDixIn4/fff4evrCy8vL5w7dw6B\ngYHKbfNV+/tDDz2EdevWKX+9V6lUSExMhK2trWmSrEVDc+/Tpw++/vprZGZm4sknn0TPnj2VOlpq\nrNenZ8+eCAsLw8qVK5t0fk2fcy4uLgBuLsGKjIxERkYGMjIyEBkZCQCIjo5GRkaGUt5UuTdHTXm7\nurrC1dUVgwYNAnAzz6ysLIPzxo0bhyNHjgCwzLyJyHg4eUBERLXKz8+HTqcDAFy7dg27d++Gv78/\nIiIisGfPHgDAL7/8gvLyctjb27doLCqVCklJSVCr1fjll19a9FrUNr399ts4e/YstFotNmzYgBEj\nRmDTpk3Izc2FVquFVquFq6srsrKy4OTkVGs9jz/+OD766CO4ubnhnXfeQXx8PH799ddWzKTxasp9\n7dq1yMvLA3Bz+dKbb76JadOmmTjSm+bMmYN33nkHZWVlza7r6tWrKCkpAQCUlpZi165dGDBgAHr1\n6qUsldqzZw969+7d7GuZm+7du8PNzU35TE1PT4e3tzdOnTqllNm2bRv8/f1NFSIRmZHqf1oiIqI2\ny97eHnl5edDr9bCxscHFixfx9NNPo7KyEpWVlZgwYQJCQ0PxwAMPYPLkyfDx8UH79u2xdu1apQ69\nXo/8/Hx069bN6PG5u7tj3rx5mDZtGtLT06FSqYx+DWo7qvb3qmrqX1Xfq62/T548GTExMbC1tUXn\nzp0xcuRIHDx4EG5ubsZNookamvtnn32mrHGPiorCpEmTlDItOdbr4+fnh4EDB+LTTz/FlClTGnVu\n1dxzc3OVOwwqKiowfvx4jB49Gvb29vj73/+OsrIy3HXXXQZ3Opgy96aqrc2TkpIwfvx4lJeXo2fP\nnli9ejViY2Nx8uRJWFlZoWfPnnj//fcBWGbeRGREpl43QURE5iU4OFg2b97c5PM3bdokISEhRozI\nkF6vF39/f1m7dm2LXYPajtbq78uWLZM+ffoojzU1B+Y+1uuzb98+6d27t1RUVDT6XEvPvanaat5E\nZBxctkBERAaau5t21d28jc3a2horV67ErFmzlH0WiJqqtfr7Sy+9hMcffxyjR49WHv9nauY+1uvz\nwAMPoFu3bti6dWujz21u7mq12qS5N5WltzkRmZZKpMpDbYmIqE0rKyuDh4cH0tLSDJ6B3hAajQbh\n4eHIyclB+/btWyjCm2bMmIErV65g1apVLXodurO1Zn8XEUyfPh1Hjx7F119/jU6dOjU1bKOwlLFe\nl23btuHNN99ERkZGo5YxNTf3kJAQPPXUU0hOTkaHDh0aG7bJ3AltTkSmwzsPiIjIQIcOHaBWqxER\nEYGcnJwGn5eTk4PIyEio1epW+WK5cOFC7Nq1S9nQjKgpWrO/q1QqqNVqeHl5ISoqCuXl5U0N2ygs\nZazX5ZFHHkFpaamygWtDNSf30aNH49q1a1i9ejWGDx+OCxcuNDZsk7kT2pyITMjEyyaIiMhMqdVq\ncXNzk8zMzHrLZmZmipubm6jV6laI7H9SU1Olb9++cv369Va9Lt15WrO/6/V6iYiIkMcff7xJ6/WN\nzRLGel0++eQTCQsLa9K5jc3dwcFBrKysBIDyr3v37nL48OEmXd9ULL3Nicg0OHlARES12rBhgzg7\nO0toaKhs3rxZ9Hq9cqy8vFw2bdokI0aMEGdnZ9mwYUOrx1dZWSljx46VN954o9WvTXeeqv09Pz9f\nTp8+LadPn5a8vDyj9vdr165JaGioTJkyRSorK42UQdO1Zu7GVlZWJm5ubnLkyJEmnd+Yz7mlS5dK\nz549DSYPAIiNjY188MEHxkqpVVhymxubTqdTctfpdKYOh8hscfKAiIjqdPnyZXnhhReke/fu0r59\ne3F0dBQHBwdp3769dO/eXV544QUpKSkxWXxnzpwRe3t7OXnypMlioDtH1f7u5OQkjo6OLdLfS0pK\nZMiQIRIfH28WEwitmbux/fOf/5To6Ogmn9+Yz7nCwkIZPXp0tQkEADJ16lSLuhOqpjZ3cnKyiDZv\nruvXr8tnn30mwcHBYmtrK56enuLp6Sm2trYSHBwsn332mZSVlZk6TCKzwj0PiIioVikpKbjvvvtw\n4sQJJCcn48KFC/j++++RkZGB8+fPY8WKFfj555/Rq1cvpKSkmCRGd3d3zJs3D9OmTYNwD2Bqhqr9\nvbS0FLm5ubh06RKuXLli9P7euXNnpKWlYffu3XjrrbeMkEHTtXbuxhYbG4v9+/fjl19+afS5jf2c\n69q1K3bs2IGXX365Wl0fffSRxeyDUFub5+bmWkSbN0dKSgo8PDywevVqxMfHQ6fTQavVQqvVoqio\nCDNnzsSqVavg7u5+x+VO1Cymnr0gIiLzZElrYvV6vfj7+8vatWtNcn2yfKbs7xcvXpRevXpJYmKi\nUeprLEsa63WZP3++xMbGNuqc5ub++eefi62tbbU7ELp3796gOk3lTmnzpmjLuRM1FycPiIiomg0b\nNoibm5ucPHlSBg8eLL6+vtKvXz+ZO3euiIi8/vrr0qNHD/Hz8xM/Pz/ZuXOnnDlzRtzc3Ey2NvbI\nkSPi7Ows+fn5Jrk+Wa5b/f3MmTMiIlJRUSF+fn4yZswYERF59dVXZeDAgeLr6ysjRoyQnJwco/d3\nrVYrbm5usmbNGqPU11D15f7999/LoEGDxM/PT4KCgiQjI8PkY702+fn50rVrVzl37lyDyt+eu4eH\nh/j4+Iifn58MGjRIRESeeOIJ5TPO09NT/Pz8asz9xx9/rLYPgqOjY4PjaG1V27yoqEiioqKkb9++\n0q9fP/n2229l48aN0r9/f2nXrp1oNBqzbfPGqpr7LdeuXavxZ52I3DG5ExkDJw+IiMjA9evXxdnZ\nWTQajYiIlJaWisjNv+4PGTJEDh48KPPnz5fly5dXOzczM1OcnZ1Ntk50+vTpMnnyZJNcmyxT1f4u\nIrJ8+XIZN26cPPLIIyJyc134LYmJiTJlyhQRMX5/P378uHTv3l1SU1ONUl99GpL7sGHD5KuvvhIR\nkbS0NBk+fLiImH6s1+bFF1+UhISEestVzd3T01MKCgpqLf/SSy/JwoULRaTm3G/fB6Fdu3bSpUsX\n+fLLL5uZjfHV1OYTJ06UVatWicjNz3mdTic///yznDx5UoYPH66UNdc2b6iacr9dTT/rbrH03ImM\nhXseEBGRgdTUVAwYMAABAQEAgE6dOgEAysvLcePGDXTt2hUAatxfIDAwEN7e3khNTW29gG+zcOFC\n7Nq1C/v37zfJ9cnyVO3v586dQ1paGmJjY5U+fvfddyvlr1y5AgcHBwDG7+/9+vXDjh078NxzzyE9\nPd0oddalIbm7uLiguLgYAKDT6dCjRw8Aph/rtYmPj8fq1atRVFRUZ7mquQM1f6bden/jxo146qmn\nANSc++37ILz33nvYsWMHnn32Wbz55puorKw0QmbGUTXv4uJiHDx4EJMnTwYAWFtbw87ODn379kXv\n3r0NzjXXNm+omtr8dlV/1nXr1k05Zum5ExmNSacuiIjI7AQHB8vmzZuV1zdu3BBfX1/p3LmzzJo1\nS0Ruri328PCQgQMHyuTJk6WoqEgpv2nTJgkJCWn1uG9JTU2Vvn37WtSO52Q6Vft7dHS0ZGVlyb59\n+5Rb90VEXnnlFXFzc5M+ffq0eH8/cOCAODg4yDfffGPUeqtqSO6///67uLq6ipubm/To0UNycnKU\n8qYe67WZNGmSvPnmm3WWqZq7l5eX+Pn5SWBgoKxcudKg7P79+yUoKMjgvYbkfv78eRk6dKhERkYa\n3L1iSlXzzs7OlsGDB8ukSZPE399fYmNjlb/Ai4jBnQci5tvmDVE196pq+ll3O0vOnchYOHlAREQK\nnU4ntra2Bs85v/3YkCFDZO/evZKbmyuVlZVSWVkp8+bNM1gqUF5eLra2tiZ7VnZlZaWMHTtW3njj\nDZNcnyxH1f7+xRdfSFxcnIiI7N2712Dy4JZFixbJpEmTlNct1d/T0tLEyclJfvjhB6PWe0tDcw8N\nDVWWUWzcuFHCwsKUOkw91mtz/PhxcXJyMvgl+HY1fc5duHBBREQuXbokvr6+cuDAAeXY888/L++8\n845BHQ3N/fr16zJ16lTp16+fyR8nW1PeR44cEWtra8nIyBARkRkzZshrr72mHK86eWCubV6fun62\n1VT21s+621lq7kTGxGULRESkKCgogKOjI6ytrasds7OzQ3h4ODIzM+Hk5ASVSgWVSoXY2FhkZGQo\n5WxsbODg4IDCwsLWDF2hUqmQlJQEtVrdpMe2UdtRtb9/88032L59O7y8vPDUU09hz549mDhxosE5\n48aNw5EjR5TXLdXfH374YSQlJeHhhx/Gr7/+atS6gYblPmHCBGRkZCAyMhIAEB0dbVZjvTb9+vXD\n/fffj48//rjG4zV9zrm4uAAAHB0dERkZqeRZUVGBLVu2ICYmxqCOhubeoUMHrFy5Ei+++CKCg4Ox\nY8eO5qTWLDXl7erqCldXVwwaNAjAzTbOysqqtQ5zbfP61PWzrarbf9bdzlJzJzImTh4QEVGt8vPz\nodPpAADXrl3D7t274e/vjz/++EMps2XLFvj4+JgqxBq5u7tj3rx5mDZtWq3rmImqevvtt3H27Flo\ntVps2LABI0aMwNq1aw1+ed+2bRv8/f1bJZ4nnngCCxYswMiRI3H27NkWvVZNuf/73/9Gr169lD1E\n9uzZU20dvLmaM2cOli5dCr1eX2/Zq1evoqSkBABQWlqKXbt2KZ9p6enp6NevH+69995mxfPss89i\n69atZrcPQvfu3eHm5qZMtKanp8Pb29ugTFv4DK3tZx0RGap/+o2IiNoMe3t75OXlQa/Xw8bGBhcv\nXsTTTz+NyspKVFZWYsKECQgNDcXEiRNx9OhRqFQqeHl54cMPP1Tq0Ov1yM/PN9hsyhT+3//7f/j3\nv/+NTz/9FBMmTDBpLGSeqvb324kIVCoVAODll1/GyZMnYWVlhZ49e+L9999XyrV0f4+NjUVxcTFG\njhyJgwcPwtHR0Sj11pU7ACX3lStX4u9//zvKyspw1113YeXKlUoZcxnrNRk6dCi8vLywceNGjB8/\n3uBY1dxzc3OVuysqKiowfvx4jBo1CgCQkpKibJR4u6bkfv/99+PIkSOIiopCVlYW1qxZY7AZZ0ur\nrc2TkpIwfvx4lJeXo2fPnvj444+xZcsWTJ8+Hfn5+QgPD4e/vz927txp1m1el/r6e20/625nqbkT\nGZWJl00QEZGZqW9TqfqY06ZSR44cEWdnZ8nPzzd1KGSmLKW/v/rqq+Lv72/U9daWkntTffXVVzJg\nwACprKysdsyUuZtyH4Q7vc3r0pZzJzIWLlsgIiIDcXFxSE5ObvL5ycnJiIuLM2JETRcUFISYmBjM\nnj3b1KGQmbKU/v7GG2/gL3/5C8aMGYOrV68apU5Lyb2pRo0aBWtra6SlpVU7ZsrcTbkPwp3e5nVp\ny7kTGY2pZy+IiMi8XL9+XZydnQ122G6ozMxMcXZ2lrKyshaIrGmKi4vF1dVV9u3bZ+pQyAxZUn+/\nceOGTJgwQR566CGjXNOScm+qDRs2SHBwcLX3zSX3w4cPy7333isLFy6UGzduNLu++phL3qbQlnMn\nMhbeeUBERAY6dOgAtVqNiIgI5OTkNPi8nJwcREZGQq1Wo3379i0YYePcc889SExMxPPPP4+ysjJT\nh0NmxpL6e7t27bB69Wp07NgRf/vb33Djxo1m1WdJuTdVVFQULl68iEOHDhm8by6539oHYceOHYiO\njlY2bmwp5pK3KbTl3ImMxtSzF0SWTKfTyenTp+X06dN87m8b0lbaXa1Wi5ubm2RmZirv1ZZ7Zmam\nuLm5iVqtNkWo9aqsrJSxY8fKG2+8YepQyEzV1N9rY+r+fu3aNQkNDZUpU6bUuJ6/sSwp96b44IMP\nZMyYMTUeM5fcW3sfBHPJ2xTupJ9tRK2NkwdEjXT9+nX57LPPJDg4WGxtbcXT01M8PT3F1tZWgoOD\n5bPPPuNtbXegttruGzZsECcnJ/H29hYfH59qufv4+Ej//v3FyclJNmzYYOpw63TmzBmxt7dv9Q3K\nyHJs2LBBnJ2d5YEHHpDNmzeLXq9XjpWXlysbpjk7O5u8v5eUlMiQIUMkPj7eKBMIlpR7Y127dk1c\nXFzk2LFjNR43p9w//PBDcXR0lC+//LJFryNiXnm3tjvpZxtRa+KyBaJGSElJgYeHB1avXo34+Hjo\ndDpotVpotVoUFRVh5syZWLVqFdzd3ZGSkmLqcMlI2nq7q1QqODg4YMGCBdVynz9/PhwcHJTHupkz\nd3d3zJs3D9OmTWsTzy2nphERFBYWYsGCBejSpQs8PT3h6emJrl27YsGCBSgsLDSL/tO5c2ekpaVh\n9+7deOutt4xSp6Xk3lgdO3bEjBkzsGTJklrLmEvuzz77LLZu3Ypnn30Wb775JiorK1v0euaStync\nKT/biFqVyaYtiCxMW77Fry1ry+1+J+au1+vF399f1q5da+pQyMzUdivzb7/9Jr/99pvZ3sp88eJF\n6dWrlyQmJja5DkvNvTF0Op3Y29uLVqs1eN9ccz9//rwMHTpUIiMj5fLly0av31zzbg134s82otbC\nyQOiBtiwYYO4ubnJmTNnGnzOmTNnxM3Njbe7WbC23O53cu5HjhwRZ2dnyc/PN3UoZCYsvb9rtVpx\nc3OTNWvWNPpcS8+9MebOnSsvvPCC8trcc2+pfRDMPe+W1JZzJzIGTh4Q1aPqo32uXbsmgwcPFl9f\nX+nXr5/MnTtXREQKCgokLCxM7rvvPhk5cqQUFRXx0T4W7PZ2r63NExISpG/fvjJw4ECJjIxU/lJj\n6e3ekNxvWbZsmahUKikoKBARy8l9+vTpMnnyZFOHQWagpse3VVRUiJ+fn7LJniWM9ePHj0v37t0l\nNTW1wec0JPcnnnhC/Pz8xM/PTzw9PcXPz09EzCv3hrp48aJ07dpVcnNzq+Xu4eEhPj4+4ufnJ4MG\nDVLOSUxMlL59+4q3t7fMnj1bRFo/d2Pug1BTmxcVFUlUVJT07dtX+vXrJ999990d+Z2mrkc15uTk\nyPDhw6V///7i7e1d7U4DS8+dyFg4eUBUj88++0xCQ0MN3istLRWRm7dADxkyRA4ePCizZs2Sf/zj\nHyIisnjxYpkzZ46IiIwYMULWr1/fukFTs1Vt95rafNeuXcpzuefMmaO0uYhlt3tDche5+WVr9OjR\n4unpqUweiFhG7sXFxeLq6ir79u0zdShkYjV9xi9fvlzGjRsnjzzyiIiIxYx1jUYjjo6Osnv37gaV\nb0jut3vppZdk4cKFymtzyr2hnn/+eXn11Ver5V71c0xEZM+ePRIWFibl5eUiInLp0iXlWGvnfvjw\nYbn33ntl4cKFSl9siprafOLEibJq1SoRufk5r9Pp7sjvNDXlfsvFixclOztbRG5uRtq7d285fvy4\nQRlLzp3IWDh5QFSP4OBg2bx5c43HSktLJSgoSP773/9Knz595I8//hCRmz+E+vTpIyKi7FZMlqW2\ndr/V5j/99JPB+6mpqTJ+/HjltSW3e0Nzj46Olh9++KHal25LyT01NVX69u0r169fN3UoZEJV+/vZ\ns2clNDRU9uzZU+Pj/cx9rB84cEAcHBzkm2++qbdsY3KvrKwUNzc3OXXqlPKeueXeEKdOnRIHBwf5\n85//bJC7p6dntaVMjz/+uPznP/+psR5T5G6MfRCqtrlOpxMvL69q5e7E7zR1fZ+r6tFHH5X09HSD\n9yw5dyJj4eQBUR10Op3Y2toaPL5IROTGjRvi6+srnTt3llmzZomISJcuXZTjlZWVyuvy8nKxtbU1\n2HyIzFtN7V5Tm99uzJgxsm7dOuW1pbZ7Q3PfunWrvPjiiyJS/S92lpJ7ZWWljB07Vt544w1Th0Im\nUlN/j46OlqysLNm3b1+NkweWMNbT0tLEyclJfvjhh1rLNDb3/fv3S1BQkMF75ph7Qzz22GNy1113\nGeTu5eUlfn5+EhgYKCtXrhQRET8/P3n99ddlyJAhMmzYMDly5IhS3lS5N2cfhJraPDs7WwYPHiyT\nJk0Sf39/iY2NlStXrtxx32lq+z5XE61WK+7u7lJSUmLwvqXmTmRMfFQjUR0KCgrg6OgIa2trg/fb\ntWuHo0eP4ty5czhw4AD27t1rcFylUimP97GxscHdd9+NBQsWYN26dfjuu+9w6dKlO/bRR3eCmtq9\napvv27dPOfbWW2+hffv2GDdunPKejY0NHBwcUFhY2JqhN1tDck9LS8OiRYuwYMECpczt/dlSclep\nVEhKSoJarcYvv/xi6nDIBKr29y+//BJOTk7w9/ev8TPaUsb6ww8/jKSkJDz88MP49ddfayzT2NzX\nr19vkDdgnrk3xDPPPIPOnTsbfM4dPnwY2dnZ2LlzJ1asWIGDBw+ioqICRUVF+O6777B06VI88cQT\nSnlT5d6hQwesXLkSL774IoKDg7Fjx44Gn1vT53tFRQWysrIQFxeHrKws2NraYvHixQbnVf1OY4lt\nXvgSAykAABR5SURBVNv3uaquXLmC6OhoqNVqdO7c2eCYpeZOZEx1jyAiqpOdnR3Cw8Oh0Wjg7OyM\nP/74A927d8fFixfh5OSklNPr9Xj33XcNzrW1tcWf/vQn5V/Pnj2V//b09ESHDh1aOx1qgFttnpmZ\nieHDh+OTTz5BWloa/vOf/1Qrq9frcezYMbi7u8PKysoE0RrXrdyzsrKg1Wrh6+sLADh37hwCAwOR\nkZFh0O8tgbu7O+bNm4dp06YhPT2dz/Ru47755hts374daWlpuH79Oi5fvoyJEydi7dq1dY51c/TE\nE0/g8uXLGDlyJA4ePAg3N7c6y9eVe0VFBbZs2YKsrKxWir5l9e/fv9pnsouLCwDA0dERkZGRyMjI\ngKurKx577DEAwKBBg9CuXTsUFBTA3t6+1WOu6tlnn8WAAQPw+OOPY9q0aXjllVfQrl3j/ybo6uoK\nV1dXDBo0CAAQHR2NRYsWoXv37rV+p7lT6fV6REVF4W9/+xsiIiJMHQ6ReTLtjQ9E5u3WbW63NksS\nEcnLy5OioiIREbl69aqEhIRIenq6zJo1SxYvXiwiIosWLVI2FyovL5f27dsLgAb/U6lU4urqKg88\n8IBMmjRJFi5cKOvWrZNvv/1WcnNzpbKysvX/Z7QhVdu9tjbfuXOn9O/fX/Ly8qrVcXu7d+3aVaKi\nouT999+XU6dOmXX7NTT321nqsoVb9Hq9+Pv7y9q1a00dCrWymj7jb7n91v36xro59/dly5ZJnz59\nDDb7E2l47iI38x8+fHi1cuaee210Op106tRJyb20tFTZQ+DKlSty//33y9dffy0ffPCB/N///Z+I\niJw8eVLc3NyUOswl98bsg1Bbm4eEhChLIF5//XWZNWtWnd9pzCHvxqqrv4vcXJoxYcIEZTleTSw1\ndyJj4uQBUT2qbrBz7Ngx8ff3F19fX/Hx8ZElS5aIyM1HNYaGhho81kjk5gY7d999d6MmD+r7Z2tr\nKz4+PhIRESHx8fFSUVFhkv83d7Lb2722Nu/Vq5e4u7srjzGbNm2acn5d7e7p6SmxsbHV1lOai4bk\nfjsvLy+L3DDxdkeOHBFnZ+dqG6bRna+2TdT27t2rPHGgvrFu7v391VdfFX9//2q/9NSW+759+wye\ntjBp0iT58MMPq5WzhNxrc3vuv/32m/j6+orv/2/v7mOqrP8/jr9xijZgOLk5eXOGzq+hInITSjFN\n42BlqENLUzPz7h+dtaXTmGlaK6upOVyx2Uozy84a4E0mSw0VpnOKyrTWdAmKNC1uRIFQEN6/P/xx\nJni8POjh5pzr+djO5oHrOnxevj8Hznlf1/lcUVEaERGha9euVdW7bxZnzZqlw4YN09jYWD106JBj\n/86UvTXrIDireUFBgcbFxTW7FKnRa5rOkru1jBZMzMvLUx8fH42KinI8z7Ozs5tt48nZAXeheQA8\nhNGlfVzx3HPP6dy5c3Xp0qWakpKiw4cPV39/f7c1EoKCgtyYFk0et+4jRowwrFtISEinPQPhcbN7\n6uWs3n77bZ03b15HDwPtzAzzvbGxURcvXqyjRo1yXHpV1RzZH2THjh06ZsyYR96/M2bfvHmzhoSE\n6N69ex+4jdlrbtbsgLv4qLJqG2Dk9u3bEhYWJvv27ZPY2NhW7Xvq1ClJTk6W4uJi8fX1dXxdVaWs\nrEwKCwulsLBQLl686Ph3YWGhlJSUuLygoo+Pj4SGhjZbP+HeNRR69+79SJ+DNLvHrfu4cePk+eef\nl0OHDsn169fv26Zr164SGxsrSUlJkpSUJAkJCZ1mnYu2mPOe4ObNmxIRESHff/+9jBkzpqOHg3Zi\nlvne2Ngoc+bMkdLSUtm9e7f4+vqaJrsz3pr92LFjhusgeGtuV5g5O+A2Hdu7ADyD3W5Xq9Wqly9f\ndnmfy5cvq9VqVbvd3uqfd+vWLT1//rxmZ2frF198oUuWLHGcteDn59fsCPZrr72mJSUlmpubq99+\n+62+//77OmvWLE1ISNAnn3xSe/TooYMHD9aXX35ZFy9erJ9//rnu2rVLz507p9XV1a0em5m4o+53\n7tzRkydP6ieffKI2m027d++uIqKbN2/WQ4cO6XvvvacjR45Uf39/ffHFF3XdunV65swZbWhoaKtY\nLmnvOd9ZZGVl6eDBg/XWrVsdPRS0I7PM9/r6ek1JSdGpU6c6Pu5mluzO2O127dOnj9dlf9g6CGav\nuVmzA+5A8wBwUVpamlqtVs3Pz3/otvn5+Wq1WjUtLc3t42hsbNR///1Xjx8/rj/88IPm5OQYbl9d\nXa3nzp3T3bt368aNG/Wtt97S5ORkHTJkiPbo0UMtFos+++yz+vrrr+uqVat069ateuTIES0pKenw\nN7CdgbvrXlNTo/v3779v8bKKigrNysrShQsX6qB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"text/plain": "<matplotlib.figure.Figure at 0x7f564c34b410>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "subsessions by profileSubsessionCounter (x-axis)\n"}, {"output_type": "display_data", "data": {"image/png": 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AgCTQ0pfi4d4cQIRmQrKhFsrosW6ylvforRbxLCVRurxHFjQTACKhmQAAAJAE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\naf/5+fmKHxo3mpoJzKz5C+i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"text/plain": "<matplotlib.figure.Figure at 0x7f560c479850>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "8\n############################################\nsession graph index: 8\nbad degree distribution: Counter({0: 2})\nsubsessions by date\n"}, {"output_type": "display_data", "data": {"image/png": 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"text/plain": "<matplotlib.figure.Figure at 0x7f562c68c990>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "subsessions by profileSubsessionCounter (x-axis)\n"}, {"output_type": "display_data", "data": {"image/png": 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"text/plain": "<matplotlib.figure.Figure at 0x7f564c6de710>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "9\n############################################\nsession graph index: 9\nbad degree distribution: Counter({1: 44, 0: 2})\nsubsessions by date\n"}, {"output_type": "display_data", "data": {"image/png": 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Li6FWq/HZZ5/hu+++Q8uWLWFmZobc3FwEBgbCysoKL774IiZOnAig8a7OUBeu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\n8fHByJEjlc80Tz31FHbt2qW8xtKlS+Hj46Pp7H25WxNBi+c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"text/plain": "<matplotlib.figure.Figure at 0x7f55ec24cfd0>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "subsessions by profileSubsessionCounter (x-axis)\n"}, {"output_type": "display_data", "data": {"image/png": 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"text/plain": "<matplotlib.figure.Figure at 0x7f55cc6162d0>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "16\n############################################\nsession graph index: 16\nbad degree distribution: Counter({1: 71, 0: 3})\nsubsessions by date\n"}, {"output_type": "display_data", "data": {"image/png": 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Qfn5+yMrKwt69e+Hg4IADBw5g0KBBKCkpQV5eXovXEUJg5MiRCA4OxvTp0zsoOiIiIqJ7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\n", "text/plain": "<matplotlib.figure.Figure at 0x7f55cc6167d0>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "subsessions by profileSubsessionCounter (x-axis)\n"}, {"output_type": "display_data", "data": {"image/png": 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BHBwccPr0aURGRuK7776T9vfbb79BpVLBxcUF4eHhWLNmDYArtwts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\nfffdp9TPX95+/foFlHfBggXUaDS0WCxK3rNmzVJuGzcajdy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"text/plain": "<matplotlib.figure.Figure at 0x7f55cc62eb90>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "17\n############################################\nsession graph index: 17\nbad degree distribution: Counter({1: 5, 0: 2})\nsubsessions by date\n"}, {"output_type": "display_data", "data": {"image/png": 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"text/plain": "<matplotlib.figure.Figure at 0x7f564c667750>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "subsessions by profileSubsessionCounter (x-axis)\n"}, {"output_type": "display_data", "data": {"image/png": 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"text/plain": "<matplotlib.figure.Figure at 0x7f560c0c6190>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "18\n############################################\nsession graph index: 18\nbad degree distribution: Counter({1: 66, 0: 3})\nrepeated profileSubsessionCounter(s): {1: 2}\nsubsessions by date\n"}, {"output_type": "display_data", "data": {"image/png": 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Cv/zlL9Dr9bCwsMBLL72ERYsWYc6cOYiLizN30omIiIhaDDsRiIxUUVEBZ2dndOzYEd99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\nERERERERyfJ/dwjhKBqgxyUAAAAASUVORK5CYII=\n", "text/plain": "<matplotlib.figure.Figure at 0x7f564c6f6fd0>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "subsessions by profileSubsessionCounter (x-axis)\n"}, {"output_type": "display_data", "data": {"image/png": 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YQERERERENID27t2LwsJChISEDFibI0eOREdHBzo7OwesTaL+4GICERERERHRACorKxvQ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\nVWLVaqgVKyLyv//7vxIWFqa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"text/plain": "<matplotlib.figure.Figure at 0x7f562c670d10>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "19\n############################################\nsession graph index: 19\nbad degree distribution: Counter({1: 18, 0: 2})\nsubsessions by date\n"}, {"output_type": "display_data", "data": {"image/png": 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"text/plain": "<matplotlib.figure.Figure at 0x7f564c676750>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "subsessions by profileSubsessionCounter (x-axis)\n"}, {"output_type": "display_data", "data": {"image/png": 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"text/plain": "<matplotlib.figure.Figure at 0x7f55ec27fd50>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "21\n############################################\nsession graph index: 21\nbad degree distribution: Counter({1: 23, 0: 2})\nsubsessions by date\n"}, {"output_type": "display_data", "data": {"image/png": 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LX88eza91AJFDMQEhU1dXp8zMTPl8Pl111VVKT0/XgQMH5PP5JEk+n08HDhxw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\nhewAEEoUE+CqWLjwBrJ+Qiz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"text/plain": "<matplotlib.figure.Figure at 0x7f564c293810>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "subsessions by profileSubsessionCounter (x-axis)\n"}, {"output_type": "display_data", "data": {"image/png": 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"text/plain": "<matplotlib.figure.Figure at 0x7f55ec713e10>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "22\n############################################\nsession graph index: 22\nbad degree distribution: Counter({1: 23, 0: 2})\nsubsessions by date\n"}, {"output_type": "display_data", "data": {"image/png": 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"text/plain": "<matplotlib.figure.Figure at 0x7f562c5ba0d0>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "subsessions by profileSubsessionCounter (x-axis)\n"}, {"output_type": "display_data", "data": {"image/png": 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0AZHkPUURTVa32y0tLS3i9/vjlAoAEArNBAAAAIOiaSa4XC45fvy4+Hy+OKUKLZqsRUVF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\nRU5ErkJggg==\n", "text/plain": "<matplotlib.figure.Figure at 0x7f564c50be10>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "24\n############################################\nsession graph index: 24\nbad degree distribution: Counter({1: 87, 0: 2})\nsubsessions by date\n"}, {"output_type": "display_data", "data": {"image/png": 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CsHDhQvj7+2P06NE6EUhaO3bsQFJSEjZu3KiznYhgYWEBHx8fHDt2rLOazBhjjDHWSGBg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\n/w/qk8M9zkmkHgAAAABJRU5ErkJggg==\n", "text/plain": "<matplotlib.figure.Figure at 0x7f560c0c8750>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "subsessions by profileSubsessionCounter (x-axis)\n"}, {"output_type": "display_data", "data": {"image/png": 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GRERERET9wGAwICkpCZs2beqyv6SkRPp9/fr1SEpK6nJcCCH9vmHDBiQnJ8Pb25tJAyLq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\nqKqqgkwmk47r9Xr4+vpi9OjR2L9/P9z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"text/plain": "<matplotlib.figure.Figure at 0x7f55ec1f83d0>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "25\n############################################\nsession graph index: 25\nbad degree distribution: Counter({1: 51, 0: 3})\nsubsessions by date\n"}, {"output_type": "display_data", "data": {"image/png": 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ixYvw8vKq9/345AUiIiJqSTjygIiICEB+fj78/f1NnqowY8YMZGdnY+/evfD29ka3bt0Q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\nAyIiIiIiIiJyioMHREREREREROTU/wF9rxkR4GIzzQAAAABJRU5ErkJggg==\n", "text/plain": "<matplotlib.figure.Figure at 0x7f562c308850>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "subsessions by profileSubsessionCounter (x-axis)\n"}, {"output_type": "display_data", "data": {"image/png": 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VM1D7e7hz506l572hoUGKiopkyZIl3dbr+Ph4MRgMcvr06bDcw/4S41//+lfA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\n", "text/plain": "<matplotlib.figure.Figure at 0x7f562c308910>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "26\n############################################\nsession graph index: 26\nbad degree distribution: Counter({1: 112, 0: 3})\nsubsessions by date\n"}, {"output_type": "display_data", "data": {"image/png": 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3oGpG3d/fH4sXL8bw4cORnJyMnJwcbN68GXq9HlOnTsWCBQsQGhqKAQMG4O67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"text/plain": "<matplotlib.figure.Figure at 0x7f562c784c10>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "subsessions by profileSubsessionCounter (x-axis)\n"}, {"output_type": "display_data", "data": {"image/png": 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+n5qamvSDH/xAX3zxhYwxWrRokYYMGSJJKi4ult/vt8OEv/iLv7BP1BYvXixJ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\nHnjgAbu+9vZ23X777SotLdU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"text/plain": "<matplotlib.figure.Figure at 0x7f562c784350>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "27\n############################################\nsession graph index: 27\nbad degree distribution: Counter({1: 40, 0: 2})\nsubsessions by date\n"}, {"output_type": "display_data", "data": {"image/png": 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lafbr16/Xmb0+MaTNTSGTybB+/Xq8/fbbePjwoWjvY4iG2uYAZzdHn58/fz7+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\nKmvJLuSE6FPWkl0M9SE7r0/AxCYjqnYDZMZYrWQ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"text/plain": "<matplotlib.figure.Figure at 0x7f55cc612c10>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "subsessions by profileSubsessionCounter (x-axis)\n"}, {"output_type": "display_data", "data": {"image/png": 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MAAAQmdUW/VaOYQSr5GmVPMYSS7FovFdWDAwMSEdHh7hcroj7jvbIVQoLEweF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\nD31IzzvvPFVV3bt3r1533XXBvqmq+t3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"text/plain": "<matplotlib.figure.Figure at 0x7f55ec65dd10>"}, "metadata": {}}, {"output_type": "stream", "name": "stdout", "text": "30\n############################################\nsession graph index: 30\nbad degree distribution: Counter({1: 67, 0: 2})\nsubsessions by date\n"}, {"output_type": "display_data", "data": {"image/png": 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NDcWGDRtw7NgxXL9+HUuXLsXQoUPRqVMnWFpa4sknn8TZs2eVbq3r1q3DihUr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