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{"name":"C4","type":"\"integer\""},{"name":"T8","type":"\"integer\""},{"name":"TP9","type":"\"integer\""},{"name":"CP5","type":"\"integer\""},{"name":"CP1","type":"\"integer\""},{"name":"CP2","type":"\"integer\""},{"name":"CP6","type":"\"integer\""},{"name":"TP10","type":"\"integer\""},{"name":"P7","type":"\"integer\""},{"name":"P3","type":"\"integer\""},{"name":"Pz","type":"\"integer\""},{"name":"P4","type":"\"integer\""},{"name":"P8","type":"\"integer\""},{"name":"PO9","type":"\"integer\""},{"name":"O1","type":"\"integer\""},{"name":"Oz","type":"\"integer\""},{"name":"O2","type":"\"integer\""},{"name":"PO10","type":"\"integer\""}],"overflow":true,"aggData":[],"aggSchema":[],"aggOverflow":false,"aggSeriesLimitReached":false,"aggError":"","aggType":"","plotOptions":null,"isJsonSchema":true,"dbfsResultPath":null},"errorSummary":null,"error":null,"startTime":1.464215084131E12,"submitTime":1.464215050512E12,"finishTime":1.464215084553E12,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"1280","height":"408","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"a user","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"c6a9ce43-37ef-441b-a9fb-c578b06038cd"},{"version":"CommandV1","origId":123743,"guid":"8ab59645-27d8-42d1-8a82-d51435b073f4","subtype":"command","commandType":"auto","position":8.25,"command":"%md create DF from RDD","commandVersion":0,"state":"finished","results":null,"errorSummary":null,"error":null,"startTime":0.0,"submitTime":0.0,"finishTime":0.0,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"a user","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"e513aa96-e21d-4d5f-9ab0-361c34ffda41"},{"version":"CommandV1","origId":123744,"guid":"1a9b82a8-f28f-48dd-b837-82952579b361","subtype":"command","commandType":"auto","position":8.5,"command":"subj3_series4_Raw_DF = subj3_series4_data.map(lambda x: (x, )).toDF()","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\"></div>","arguments":{},"addedWidgets":{},"removedWidgets":[]},"errorSummary":"<span class=\"ansired\">TypeError</span>: Can not infer schema for type: <type 'unicode'>","error":"<div class=\"ansiout\"><span class=\"ansired\">---------------------------------------------------------------------------</span>\n<span class=\"ansired\">TypeError</span> Traceback (most recent call last)\n<span class=\"ansigreen\"><ipython-input-14-ddbcc4dc852b></span> in <span class=\"ansicyan\"><module></span><span class=\"ansiblue\">()</span>\n<span class=\"ansigreen\">----> 1</span><span class=\"ansiyellow\"> </span>subj3_series4_Raw_DF <span class=\"ansiyellow\">=</span> subj3_series4_data<span class=\"ansiyellow\">.</span>toDF<span class=\"ansiyellow\">(</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n\n<span class=\"ansigreen\">/databricks/spark/python/pyspark/sql/context.pyc</span> in <span class=\"ansicyan\">toDF</span><span class=\"ansiblue\">(self, schema, sampleRatio)</span>\n<span class=\"ansigreen\"> 62</span> <span class=\"ansiyellow\">[</span>Row<span class=\"ansiyellow\">(</span>name<span class=\"ansiyellow\">=</span><span class=\"ansiblue\">u'Alice'</span><span class=\"ansiyellow\">,</span> age<span class=\"ansiyellow\">=</span><span class=\"ansicyan\">1</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">]</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 63</span> """\n<span class=\"ansigreen\">---> 64</span><span class=\"ansiyellow\"> </span><span class=\"ansigreen\">return</span> sqlContext<span class=\"ansiyellow\">.</span>createDataFrame<span class=\"ansiyellow\">(</span>self<span class=\"ansiyellow\">,</span> schema<span class=\"ansiyellow\">,</span> sampleRatio<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 65</span> <span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 66</span> RDD<span class=\"ansiyellow\">.</span>toDF <span class=\"ansiyellow\">=</span> toDF<span class=\"ansiyellow\"></span>\n\n<span class=\"ansigreen\">/databricks/spark/python/pyspark/sql/context.pyc</span> in <span class=\"ansicyan\">createDataFrame</span><span class=\"ansiblue\">(self, data, schema, samplingRatio)</span>\n<span class=\"ansigreen\"> 421</span> <span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 422</span> <span class=\"ansigreen\">if</span> isinstance<span class=\"ansiyellow\">(</span>data<span class=\"ansiyellow\">,</span> RDD<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">--> 423</span><span class=\"ansiyellow\"> </span>rdd<span class=\"ansiyellow\">,</span> schema <span class=\"ansiyellow\">=</span> self<span class=\"ansiyellow\">.</span>_createFromRDD<span class=\"ansiyellow\">(</span>data<span class=\"ansiyellow\">,</span> schema<span class=\"ansiyellow\">,</span> samplingRatio<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 424</span> <span class=\"ansigreen\">else</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 425</span> rdd<span class=\"ansiyellow\">,</span> schema <span class=\"ansiyellow\">=</span> self<span class=\"ansiyellow\">.</span>_createFromLocal<span class=\"ansiyellow\">(</span>data<span class=\"ansiyellow\">,</span> schema<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n\n<span class=\"ansigreen\">/databricks/spark/python/pyspark/sql/context.pyc</span> in <span class=\"ansicyan\">_createFromRDD</span><span class=\"ansiblue\">(self, rdd, schema, samplingRatio)</span>\n<span class=\"ansigreen\"> 308</span> """\n<span class=\"ansigreen\"> 309</span> <span class=\"ansigreen\">if</span> schema <span class=\"ansigreen\">is</span> None <span class=\"ansigreen\">or</span> isinstance<span class=\"ansiyellow\">(</span>schema<span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">(</span>list<span class=\"ansiyellow\">,</span> tuple<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">--> 310</span><span class=\"ansiyellow\"> </span>struct <span class=\"ansiyellow\">=</span> self<span class=\"ansiyellow\">.</span>_inferSchema<span class=\"ansiyellow\">(</span>rdd<span class=\"ansiyellow\">,</span> samplingRatio<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 311</span> converter <span class=\"ansiyellow\">=</span> _create_converter<span class=\"ansiyellow\">(</span>struct<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 312</span> rdd <span class=\"ansiyellow\">=</span> rdd<span class=\"ansiyellow\">.</span>map<span class=\"ansiyellow\">(</span>converter<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n\n<span class=\"ansigreen\">/databricks/spark/python/pyspark/sql/context.pyc</span> in <span class=\"ansicyan\">_inferSchema</span><span class=\"ansiblue\">(self, rdd, samplingRatio)</span>\n<span class=\"ansigreen\"> 261</span> <span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 262</span> <span class=\"ansigreen\">if</span> samplingRatio <span class=\"ansigreen\">is</span> None<span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">--> 263</span><span class=\"ansiyellow\"> </span>schema <span class=\"ansiyellow\">=</span> _infer_schema<span class=\"ansiyellow\">(</span>first<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 264</span> <span class=\"ansigreen\">if</span> _has_nulltype<span class=\"ansiyellow\">(</span>schema<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 265</span> <span class=\"ansigreen\">for</span> row <span class=\"ansigreen\">in</span> rdd<span class=\"ansiyellow\">.</span>take<span class=\"ansiyellow\">(</span><span class=\"ansicyan\">100</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">[</span><span class=\"ansicyan\">1</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\">]</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n\n<span class=\"ansigreen\">/databricks/spark/python/pyspark/sql/types.pyc</span> in <span class=\"ansicyan\">_infer_schema</span><span class=\"ansiblue\">(row)</span>\n<span class=\"ansigreen\"> 829</span> <span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 830</span> <span class=\"ansigreen\">else</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">--> 831</span><span class=\"ansiyellow\"> </span><span class=\"ansigreen\">raise</span> TypeError<span class=\"ansiyellow\">(</span><span class=\"ansiblue\">"Can not infer schema for type: %s"</span> <span class=\"ansiyellow\">%</span> type<span class=\"ansiyellow\">(</span>row<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 832</span> <span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 833</span> fields <span class=\"ansiyellow\">=</span> <span class=\"ansiyellow\">[</span>StructField<span class=\"ansiyellow\">(</span>k<span class=\"ansiyellow\">,</span> _infer_type<span class=\"ansiyellow\">(</span>v<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">,</span> True<span class=\"ansiyellow\">)</span> <span class=\"ansigreen\">for</span> k<span class=\"ansiyellow\">,</span> v <span class=\"ansigreen\">in</span> items<span class=\"ansiyellow\">]</span><span class=\"ansiyellow\"></span>\n\n<span class=\"ansired\">TypeError</span>: Can not infer schema for type: <type 'unicode'>\n</div>","startTime":1.464046270393E12,"submitTime":1.464046246266E12,"finishTime":1.464046270716E12,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"a 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These oscillations appear naturally in ongoing EEG activity, can be induced by a specific task, for example a hand movement, or mental calculus. \n* For each subject, we should see a spot over the electrode C3 (Left motor cortex,corresponding to a right hand movement), and a decrease of the signal power in \n10 and 20 Hz during the movement (by reference to after the movement).\n","commandVersion":0,"state":"finished","results":null,"errorSummary":null,"error":null,"startTime":0.0,"submitTime":0.0,"finishTime":0.0,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"a user","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"84904883-287a-43d3-ac8b-39731a6f3773"},{"version":"CommandV1","origId":123748,"guid":"4e0587c6-f464-496d-b19d-99d82f245d12","subtype":"command","commandType":"auto","position":10.0,"command":"subj3_series3_events_DF.filter(\"HandStart = 1\").count()","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\"><span class=\"ansired\">Out[</span><span class=\"ansired\">50</span><span class=\"ansired\">]: </span>5100\n</div>","arguments":{},"addedWidgets":{},"removedWidgets":[]},"errorSummary":null,"error":null,"startTime":1.464050133548E12,"submitTime":1.464050109199E12,"finishTime":1.464050134857E12,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"a user","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"aba1feba-cbf0-4f02-a1e0-d19c1711e6a8"},{"version":"CommandV1","origId":123749,"guid":"50e68953-457d-495e-9ad8-5f4235898668","subtype":"command","commandType":"auto","position":10.375,"command":"subj3_series34.map(lambda x: (x, )).toDF().filter(\"HandStart = 1\").count()","commandVersion":0,"state":"error","results":null,"errorSummary":"<span class=\"ansired\">AnalysisException</span>: u"cannot resolve 'HandStart' given input columns: [_1];"","error":"<div class=\"ansiout\"><span class=\"ansired\">---------------------------------------------------------------------------</span>\n<span class=\"ansired\">AnalysisException</span> Traceback (most recent call last)\n<span class=\"ansigreen\"><ipython-input-80-56a54e909317></span> in <span class=\"ansicyan\"><module></span><span class=\"ansiblue\">()</span>\n<span class=\"ansigreen\">----> 1</span><span class=\"ansiyellow\"> </span>subj3_series34<span class=\"ansiyellow\">.</span>map<span class=\"ansiyellow\">(</span><span class=\"ansigreen\">lambda</span> x<span class=\"ansiyellow\">:</span> <span class=\"ansiyellow\">(</span>x<span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">.</span>toDF<span class=\"ansiyellow\">(</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">.</span>filter<span class=\"ansiyellow\">(</span><span class=\"ansiblue\">"HandStart = 1"</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">.</span>count<span class=\"ansiyellow\">(</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n\n<span class=\"ansigreen\">/databricks/spark/python/pyspark/sql/dataframe.pyc</span> in <span class=\"ansicyan\">filter</span><span class=\"ansiblue\">(self, condition)</span>\n<span class=\"ansigreen\"> 898</span> """\n<span class=\"ansigreen\"> 899</span> <span class=\"ansigreen\">if</span> isinstance<span class=\"ansiyellow\">(</span>condition<span class=\"ansiyellow\">,</span> basestring<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">--> 900</span><span class=\"ansiyellow\"> </span>jdf <span class=\"ansiyellow\">=</span> self<span class=\"ansiyellow\">.</span>_jdf<span class=\"ansiyellow\">.</span>filter<span class=\"ansiyellow\">(</span>condition<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 901</span> <span class=\"ansigreen\">elif</span> isinstance<span class=\"ansiyellow\">(</span>condition<span class=\"ansiyellow\">,</span> Column<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 902</span> jdf <span class=\"ansiyellow\">=</span> self<span class=\"ansiyellow\">.</span>_jdf<span class=\"ansiyellow\">.</span>filter<span class=\"ansiyellow\">(</span>condition<span class=\"ansiyellow\">.</span>_jc<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n\n<span class=\"ansigreen\">/databricks/python/local/lib/python2.7/site-packages/py4j/java_gateway.pyc</span> in <span class=\"ansicyan\">__call__</span><span class=\"ansiblue\">(self, *args)</span>\n<span class=\"ansigreen\"> 536</span> answer <span class=\"ansiyellow\">=</span> self<span class=\"ansiyellow\">.</span>gateway_client<span class=\"ansiyellow\">.</span>send_command<span class=\"ansiyellow\">(</span>command<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 537</span> return_value = get_return_value(answer, self.gateway_client,\n<span class=\"ansigreen\">--> 538</span><span class=\"ansiyellow\"> self.target_id, self.name)\n</span><span class=\"ansigreen\"> 539</span> <span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 540</span> <span class=\"ansigreen\">for</span> temp_arg <span class=\"ansigreen\">in</span> temp_args<span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n\n<span class=\"ansigreen\">/databricks/spark/python/pyspark/sql/utils.pyc</span> in <span class=\"ansicyan\">deco</span><span class=\"ansiblue\">(*a, **kw)</span>\n<span class=\"ansigreen\"> 49</span> e.java_exception.getStackTrace()))\n<span class=\"ansigreen\"> 50</span> <span class=\"ansigreen\">if</span> s<span class=\"ansiyellow\">.</span>startswith<span class=\"ansiyellow\">(</span><span class=\"ansiblue\">'org.apache.spark.sql.AnalysisException: '</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">---> 51</span><span class=\"ansiyellow\"> </span><span class=\"ansigreen\">raise</span> AnalysisException<span class=\"ansiyellow\">(</span>s<span class=\"ansiyellow\">.</span>split<span class=\"ansiyellow\">(</span><span class=\"ansiblue\">': '</span><span class=\"ansiyellow\">,</span> <span class=\"ansicyan\">1</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">[</span><span class=\"ansicyan\">1</span><span class=\"ansiyellow\">]</span><span class=\"ansiyellow\">,</span> stackTrace<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 52</span> <span class=\"ansigreen\">if</span> s<span class=\"ansiyellow\">.</span>startswith<span class=\"ansiyellow\">(</span><span class=\"ansiblue\">'java.lang.IllegalArgumentException: '</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 53</span> <span class=\"ansigreen\">raise</span> IllegalArgumentException<span class=\"ansiyellow\">(</span>s<span class=\"ansiyellow\">.</span>split<span class=\"ansiyellow\">(</span><span class=\"ansiblue\">': '</span><span class=\"ansiyellow\">,</span> <span class=\"ansicyan\">1</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">[</span><span class=\"ansicyan\">1</span><span class=\"ansiyellow\">]</span><span class=\"ansiyellow\">,</span> stackTrace<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n\n<span class=\"ansired\">AnalysisException</span>: u"cannot resolve 'HandStart' given input columns: [_1];"\n</div>","startTime":1.464235451645E12,"submitTime":1.464235451645E12,"finishTime":1.464235452022E12,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"a user","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"e8022c7c-3a9f-424c-8641-54a7ee075bb4"},{"version":"CommandV1","origId":123750,"guid":"ab77a3b2-7fb8-4d22-95d5-c64278e1b301","subtype":"command","commandType":"auto","position":10.75,"command":"raw = creat_mne_raw_object(subj3_series3_DF)","commandVersion":0,"state":"error","results":null,"errorSummary":"<span class=\"ansired\">NameError</span>: name 'creat_mne_raw_object' is not defined","error":"<div class=\"ansiout\"><span class=\"ansired\">---------------------------------------------------------------------------</span>\n<span class=\"ansired\">NameError</span> Traceback (most recent call last)\n<span class=\"ansigreen\"><ipython-input-74-690aa8929e68></span> in <span class=\"ansicyan\"><module></span><span class=\"ansiblue\">()</span>\n<span class=\"ansigreen\">----> 1</span><span class=\"ansiyellow\"> </span>raw <span class=\"ansiyellow\">=</span> creat_mne_raw_object<span class=\"ansiyellow\">(</span>subj3_series3_DF<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n\n<span class=\"ansired\">NameError</span>: name 'creat_mne_raw_object' is not defined\n</div>","startTime":1.464234754353E12,"submitTime":1.464234754353E12,"finishTime":1.464234754611E12,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"a user","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"501a3e55-9500-4162-935e-5427ed407c61"},{"version":"CommandV1","origId":123751,"guid":"05752436-698d-4cc6-8674-62ef8e5d9828","subtype":"command","commandType":"auto","position":11.5,"command":"# get chanel names\nch_names = list(subj3_series3_DF)\n \nch_names","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\"><span class=\"ansired\">Out[</span><span class=\"ansired\">71</span><span class=\"ansired\">]: </span>\n[Column<Fp1>,\n Column<Fp2>,\n Column<F7>,\n Column<F3>,\n Column<Fz>,\n Column<F4>,\n Column<F8>,\n Column<FC5>,\n Column<FC1>,\n Column<FC2>,\n Column<FC6>,\n Column<T7>,\n Column<C3>,\n Column<Cz>,\n Column<C4>,\n Column<T8>,\n Column<TP9>,\n Column<CP5>,\n Column<CP1>,\n Column<CP2>,\n Column<CP6>,\n Column<TP10>,\n Column<P7>,\n Column<P3>,\n Column<Pz>,\n Column<P4>,\n Column<P8>,\n Column<PO9>,\n Column<O1>,\n Column<Oz>,\n Column<O2>,\n Column<PO10>]\n</div>","arguments":{},"addedWidgets":{},"removedWidgets":[]},"errorSummary":"<span class=\"ansired\">NameError</span>: name 'fname' is not defined","error":"<div class=\"ansiout\"><span class=\"ansired\">---------------------------------------------------------------------------</span>\n<span class=\"ansired\">NameError</span> Traceback (most recent call last)\n<span class=\"ansigreen\"><ipython-input-70-8ebcfb92bb53></span> in <span class=\"ansicyan\"><module></span><span class=\"ansiblue\">()</span>\n<span class=\"ansigreen\">----> 1</span><span class=\"ansiyellow\"> </span>data <span class=\"ansiyellow\">=</span> pd<span class=\"ansiyellow\">.</span>read_csv<span class=\"ansiyellow\">(</span>fname<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n\n<span class=\"ansired\">NameError</span>: name 'fname' is not defined\n</div>","startTime":1.464227791262E12,"submitTime":1.464227756923E12,"finishTime":1.464227791332E12,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"a user","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"b4068aec-fef4-49a5-adbf-28ee1840f77d"},{"version":"CommandV1","origId":123752,"guid":"8094bc49-0d39-487c-a86a-385f24f0531e","subtype":"command","commandType":"auto","position":14.0,"command":"%md\n### To get data to dbfs let's download and save.","commandVersion":0,"state":"finished","results":null,"errorSummary":null,"error":null,"startTime":0.0,"submitTime":0.0,"finishTime":0.0,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"a user","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"f739744b-e466-4b3e-b274-bc24d3b5751d"},{"version":"CommandV1","origId":123819,"guid":"8179217f-b1e9-4630-aad2-47f6263ad2f4","subtype":"command","commandType":"auto","position":14.5,"command":"%sh\npwd","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\">/databricks/driver\n</div>","arguments":{},"addedWidgets":{},"removedWidgets":[]},"errorSummary":null,"error":null,"startTime":1.464931383424E12,"submitTime":1.464931173922E12,"finishTime":1.46493138398E12,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"r.sainudiin@math.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"a0b91939-d86e-47e4-81c5-740cfa093e14"},{"version":"CommandV1","origId":123820,"guid":"1f7ed98f-296c-4089-9e91-b37e2179100c","subtype":"command","commandType":"auto","position":14.75,"command":"%sh \ndf -h /databricks/driver\n","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\">Filesystem Size Used Avail Use% Mounted on\n/var/lib/lxc/d984c3c2b0ef8e179895fbe5e1d84779a3f7b1ed/rootfs 296G 30G 254G 11% /\n</div>","arguments":{},"addedWidgets":{},"removedWidgets":[]},"errorSummary":null,"error":null,"startTime":1.464931445336E12,"submitTime":1.464931238608E12,"finishTime":1.46493144539E12,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"r.sainudiin@math.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"f1d22ff3-d3dd-414d-84f8-f96a03385705"},{"version":"CommandV1","origId":135887,"guid":"e414a7d5-6bb2-4146-a30c-da922bde4b5c","subtype":"command","commandType":"auto","position":14.8125,"command":"%md\nThis data in `http://www.math.canterbury.ac.nz/~r.sainudiin/tmp/` may be deleted in the future.","commandVersion":0,"state":"error","results":null,"errorSummary":null,"error":null,"startTime":0.0,"submitTime":0.0,"finishTime":0.0,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"81ebd8ed-5e09-457d-945a-0fa872d35334"},{"version":"CommandV1","origId":123821,"guid":"df37384d-2153-41ef-8657-cef4d9a89072","subtype":"command","commandType":"auto","position":14.875,"command":"%sh\nwget http://www.math.canterbury.ac.nz/~r.sainudiin/tmp/test.zip","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\">--2016-06-03 05:25:27-- http://www.math.canterbury.ac.nz/~r.sainudiin/tmp/test.zip\nResolving www.math.canterbury.ac.nz (www.math.canterbury.ac.nz)... 132.181.26.35\nConnecting to www.math.canterbury.ac.nz (www.math.canterbury.ac.nz)|132.181.26.35|:80... connected.\nHTTP request sent, awaiting response... 200 OK\nLength: 160156951 (153M) [application/zip]\nSaving to: 'test.zip'\n\n 0K .......... .......... .......... .......... .......... 0% 339K 7m41s\n 50K .......... .......... .......... .......... .......... 0% 1.32M 4m48s\n 100K .......... .......... .......... .......... .......... 0% 1.34M 3m50s\n 150K .......... .......... .......... .......... .......... 0% 35.8M 2m53s\n 200K .......... .......... .......... .......... .......... 0% 1.35M 2m41s\n 250K .......... .......... .......... .......... .......... 0% 30.9M 2m15s\n 300K .......... .......... .......... .......... .......... 0% 1.41M 2m11s\n 350K .......... .......... .......... .......... .......... 0% 22.6M 1m56s\n 400K .......... .......... .......... .......... .......... 0% 23.5M 1m44s\n 450K .......... .......... .......... .......... .......... 0% 1.50M 1m43s\n 500K .......... .......... .......... .......... .......... 0% 13.6M 95s\n 550K .......... .......... .......... .......... .......... 0% 36.9M 87s\n 600K .......... .......... .......... .......... .......... 0% 1.53M 88s\n 650K .......... .......... .......... .......... .......... 0% 13.8M 83s\n 700K .......... .......... .......... .......... .......... 0% 34.5M 77s\n 750K .......... .......... .......... .......... .......... 0% 1.54M 79s\n 800K .......... .......... .......... .......... .......... 0% 14.0M 75s\n 850K .......... .......... .......... .......... .......... 0% 35.0M 71s\n 900K .......... .......... .......... .......... .......... 0% 56.0M 67s\n 950K .......... .......... .......... .......... .......... 0% 1.56M 69s\n 1000K .......... .......... .......... .......... .......... 0% 13.1M 66s\n 1050K .......... .......... .......... .......... .......... 0% 21.2M 63s\n 1100K .......... .......... .......... .......... .......... 0% 1.64M 64s\n 1150K .......... .......... .......... .......... .......... 0% 56.8M 62s\n 1200K .......... .......... .......... .......... .......... 0% 12.7M 60s\n 1250K .......... .......... .......... .......... .......... 0% 20.6M 58s\n 1300K .......... .......... .......... .......... .......... 0% 1.66M 59s\n 1350K .......... .......... .......... .......... .......... 0% 12.5M 57s\n 1400K .......... .......... .......... .......... .......... 0% 44.8M 55s\n 1450K .......... .......... .......... .......... .......... 0% 16.5M 54s\n 1500K .......... .......... .......... .......... .......... 0% 29.5M 52s\n 1550K .......... .......... .......... .......... .......... 1% 1.77M 53s\n 1600K .......... .......... .......... .......... .......... 1% 50.6M 52s\n 1650K .......... .......... .......... .......... .......... 1% 7.26M 51s\n 1700K .......... .......... .......... .......... .......... 1% 40.5M 50s\n 1750K .......... .......... .......... .......... .......... 1% 37.2M 48s\n 1800K .......... .......... .......... .......... .......... 1% 1.82M 49s\n 1850K .......... .......... .......... .......... .......... 1% 50.5M 48s\n 1900K .......... .......... .......... .......... .......... 1% 7.83M 47s\n 1950K .......... .......... .......... .......... .......... 1% 48.1M 46s\n 2000K .......... .......... .......... .......... .......... 1% 30.4M 45s\n 2050K .......... .......... .......... .......... .......... 1% 1.81M 46s\n 2100K .......... .......... .......... .......... .......... 1% 51.0M 45s\n 2150K .......... .......... .......... .......... .......... 1% 8.48M 44s\n 2200K .......... .......... .......... .......... .......... 1% 21.2M 43s\n 2250K .......... .......... .......... .......... .......... 1% 44.6M 43s\n 2300K .......... .......... .......... .......... .......... 1% 71.1M 42s\n 2350K .......... .......... .......... .......... .......... 1% 78.9M 41s\n 2400K .......... .......... .......... .......... .......... 1% 1.82M 42s\n 2450K .......... .......... .......... .......... .......... 1% 7.89M 41s\n 2500K .......... .......... .......... .......... .......... 1% 25.4M 41s\n 2550K .......... .......... .......... .......... .......... 1% 49.4M 40s\n 2600K .......... .......... .......... .......... .......... 1% 33.1M 39s\n 2650K .......... .......... .......... .......... .......... 1% 88.2M 38s\n 2700K .......... .......... .......... .......... .......... 1% 1.92M 39s\n 2750K .......... .......... .......... .......... .......... 1% 7.71M 39s\n 2800K .......... .......... .......... .......... .......... 1% 99.2M 38s\n 2850K .......... .......... .......... .......... .......... 1% 19.9M 38s\n 2900K .......... .......... .......... .......... .......... 1% 22.1M 37s\n 2950K .......... .......... .......... .......... .......... 1% 34.5M 36s\n 3000K .......... .......... .......... .......... .......... 1% 19.2M 36s\n 3050K .......... .......... .......... .......... .......... 1% 2.21M 36s\n 3100K .......... .......... .......... .......... .......... 2% 8.34M 36s\n 3150K .......... .......... .......... .......... .......... 2% 25.7M 36s\n 3200K .......... .......... .......... .......... .......... 2% 17.5M 35s\n 3250K .......... .......... .......... .......... .......... 2% 54.3M 35s\n 3300K .......... .......... .......... .......... .......... 2% 21.3M 34s\n 3350K .......... .......... .......... .......... .......... 2% 2.18M 35s\n 3400K .......... .......... .......... .......... .......... 2% 8.37M 35s\n 3450K .......... .......... .......... .......... .......... 2% 28.3M 34s\n 3500K .......... .......... .......... .......... .......... 2% 47.3M 34s\n 3550K .......... .......... .......... .......... .......... 2% 22.3M 33s\n 3600K .......... .......... .......... .......... .......... 2% 29.4M 33s\n 3650K .......... .......... .......... .......... .......... 2% 22.0M 33s\n 3700K .......... .......... .......... .......... .......... 2% 36.9M 32s\n 3750K .......... .......... .......... .......... .......... 2% 2.26M 33s\n 3800K .......... .......... .......... .......... .......... 2% 7.82M 32s\n 3850K .......... .......... .......... .......... .......... 2% 30.3M 32s\n 3900K .......... .......... .......... .......... .......... 2% 20.8M 32s\n 3950K .......... .......... .......... .......... .......... 2% 55.3M 31s\n 4000K .......... .......... .......... .......... .......... 2% 25.9M 31s\n 4050K .......... .......... .......... .......... .......... 2% 22.7M 31s\n 4100K .......... .......... .......... .......... .......... 2% 2.23M 31s\n 4150K .......... .......... .......... .......... .......... 2% 6.94M 31s\n 4200K .......... .......... .......... .......... .......... 2% 49.9M 31s\n 4250K .......... .......... .......... .......... .......... 2% 33.2M 30s\n 4300K .......... .......... .......... .......... .......... 2% 33.8M 30s\n 4350K .......... .......... .......... .......... .......... 2% 23.7M 30s\n 4400K .......... .......... .......... .......... .......... 2% 53.1M 29s\n 4450K .......... .......... .......... .......... .......... 2% 22.9M 29s\n 4500K .......... .......... .......... .......... .......... 2% 2.24M 30s\n 4550K .......... .......... .......... .......... .......... 2% 5.43M 30s\n 4600K .......... .......... .......... .......... .......... 2% 28.4M 29s\n 4650K .......... .......... .......... .......... .......... 3% 27.1M 29s\n 4700K .......... .......... .......... .......... .......... 3% 21.8M 29s\n 4750K .......... .......... .......... .......... .......... 3% 30.2M 29s\n 4800K .......... .......... .......... .......... .......... 3% 18.4M 28s\n 4850K .......... .......... .......... .......... .......... 3% 2.65M 29s\n 4900K .......... .......... .......... .......... .......... 3% 51.5M 28s\n 4950K .......... .......... .......... .......... .......... 3% 5.85M 28s\n 5000K .......... .......... .......... .......... .......... 3% 17.5M 28s\n 5050K .......... .......... .......... .......... .......... 3% 18.0M 28s\n 5100K .......... .......... .......... .......... .......... 3% 39.0M 28s\n 5150K .......... .......... .......... .......... .......... 3% 31.5M 27s\n 5200K .......... .......... .......... .......... .......... 3% 20.2M 27s\n 5250K .......... .......... .......... .......... .......... 3% 2.77M 27s\n 5300K .......... .......... .......... .......... .......... 3% 5.33M 27s\n 5350K .......... .......... .......... .......... .......... 3% 70.4M 27s\n 5400K .......... .......... .......... .......... .......... 3% 21.7M 27s\n 5450K .......... .......... .......... .......... .......... 3% 15.5M 27s\n 5500K .......... .......... .......... .......... .......... 3% 27.9M 27s\n 5550K .......... .......... .......... .......... .......... 3% 11.3M 26s\n 5600K .......... .......... .......... .......... .......... 3% 52.2M 26s\n 5650K .......... .......... .......... 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11% 45.9M 17s\n 17400K .......... .......... .......... .......... .......... 11% 19.3M 17s\n 17450K .......... .......... .......... .......... .......... 11% 10.2M 17s\n 17500K .......... .......... .......... .......... .......... 11% 67.3M 17s\n 17550K .......... .......... .......... .......... .......... 11% 2.73M 17s\n 17600K .......... .......... .......... .......... .......... 11% 5.67M 17s\n 17650K .......... .......... .......... .......... .......... 11% 47.4M 17s\n 17700K .......... .......... .......... .......... .......... 11% 87.0M 17s\n 17750K .......... .......... .......... .......... .......... 11% 25.1M 17s\n 17800K .......... .......... .......... .......... .......... 11% 13.5M 17s\n 17850K .......... .......... .......... .......... .......... 11% 16.2M 17s\n 17900K .......... .......... .......... .......... .......... 11% 2.72M 17s\n 17950K .......... .......... .......... .......... .......... 11% 94.0M 17s\n 18000K .......... .......... .......... 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.......... .......... .......... .......... 11% 51.5M 17s\n 18700K .......... .......... .......... .......... .......... 11% 2.75M 17s\n 18750K .......... .......... .......... .......... .......... 12% 5.85M 17s\n 18800K .......... .......... .......... .......... .......... 12% 30.2M 17s\n 18850K .......... .......... .......... .......... .......... 12% 39.3M 17s\n 18900K .......... .......... .......... .......... .......... 12% 88.7M 17s\n 18950K .......... .......... .......... .......... .......... 12% 9.23M 17s\n 19000K .......... .......... .......... .......... .......... 12% 17.1M 17s\n 19050K .......... .......... .......... .......... .......... 12% 2.97M 17s\n 19100K .......... .......... .......... .......... .......... 12% 41.8M 17s\n 19150K .......... .......... .......... .......... .......... 12% 5.81M 17s\n 19200K .......... .......... .......... .......... .......... 12% 34.3M 17s\n 19250K .......... .......... .......... .......... .......... 12% 23.4M 17s\n 19300K .......... .......... .......... .......... .......... 12% 11.7M 17s\n 19350K .......... .......... .......... .......... .......... 12% 62.2M 17s\n 19400K .......... .......... .......... .......... .......... 12% 16.0M 16s\n 19450K .......... .......... .......... .......... .......... 12% 3.01M 17s\n 19500K .......... .......... .......... .......... .......... 12% 5.82M 17s\n 19550K .......... .......... .......... .......... .......... 12% 25.7M 17s\n 19600K .......... .......... .......... .......... .......... 12% 80.0M 16s\n 19650K .......... .......... .......... .......... .......... 12% 34.7M 16s\n 19700K .......... .......... .......... .......... .......... 12% 8.85M 16s\n 19750K .......... .......... .......... .......... .......... 12% 22.4M 16s\n 19800K .......... .......... .......... .......... .......... 12% 48.7M 16s\n 19850K .......... .......... .......... .......... .......... 12% 2.91M 16s\n 19900K .......... .......... .......... .......... .......... 12% 5.52M 16s\n 19950K .......... .......... .......... .......... .......... 12% 36.6M 16s\n 20000K .......... .......... .......... .......... .......... 12% 39.1M 16s\n 20050K .......... .......... .......... .......... .......... 12% 40.1M 16s\n 20100K .......... .......... .......... .......... .......... 12% 9.93M 16s\n 20150K .......... .......... .......... .......... .......... 12% 22.3M 16s\n 20200K .......... .......... .......... .......... .......... 12% 2.70M 16s\n 20250K .......... .......... .......... .......... .......... 12% 6.49M 16s\n 20300K .......... .......... .......... .......... .......... 13% 55.0M 16s\n 20350K .......... .......... .......... .......... .......... 13% 32.0M 16s\n 20400K .......... .......... .......... .......... .......... 13% 31.3M 16s\n 20450K .......... .......... .......... .......... .......... 13% 8.57M 16s\n 20500K .......... .......... .......... .......... .......... 13% 61.1M 16s\n 20550K .......... .......... .......... .......... .......... 13% 20.2M 16s\n 20600K .......... .......... .......... .......... .......... 13% 2.18M 16s\n 20650K .......... .......... .......... .......... .......... 13% 12.7M 16s\n 20700K .......... .......... .......... .......... .......... 13% 37.6M 16s\n 20750K .......... .......... .......... .......... .......... 13% 28.5M 16s\n 20800K .......... .......... .......... .......... .......... 13% 120M 16s\n 20850K .......... .......... .......... .......... .......... 13% 10.7M 16s\n 20900K .......... .......... .......... .......... .......... 13% 18.9M 16s\n 20950K .......... .......... .......... .......... .......... 13% 2.14M 16s\n 21000K .......... .......... .......... .......... .......... 13% 44.6M 16s\n 21050K .......... .......... .......... .......... .......... 13% 12.8M 16s\n 21100K .......... .......... .......... .......... .......... 13% 13.2M 16s\n 21150K .......... .......... .......... .......... .......... 13% 84.8M 16s\n 21200K .......... .......... .......... .......... .......... 13% 140M 16s\n 21250K .......... .......... .......... .......... .......... 13% 8.93M 16s\n 21300K .......... .......... .......... .......... .......... 13% 11.3M 16s\n 21350K .......... .......... .......... .......... .......... 13% 2.63M 16s\n 21400K .......... .......... .......... .......... .......... 13% 5.08M 16s\n 21450K .......... .......... .......... .......... .......... 13% 51.9M 16s\n 21500K .......... .......... .......... .......... .......... 13% 24.1M 16s\n 21550K .......... .......... .......... .......... .......... 13% 46.2M 16s\n 21600K .......... .......... .......... .......... .......... 13% 6.47M 16s\n 21650K .......... .......... .......... .......... .......... 13% 15.5M 16s\n 21700K .......... .......... .......... .......... .......... 13% 36.5M 16s\n 21750K .......... .......... .......... .......... .......... 13% 3.39M 16s\n 21800K .......... .......... .......... .......... .......... 13% 6.59M 16s\n 21850K .......... .......... .......... .......... .......... 14% 21.5M 16s\n 21900K .......... .......... .......... .......... .......... 14% 22.5M 16s\n 21950K .......... .......... .......... .......... .......... 14% 109M 16s\n 22000K .......... .......... .......... ........ 14% 3.51M=2.6s\n\n\nCannot write to 'test.zip' (Cannot allocate memory).\n</div>","arguments":{},"addedWidgets":{},"removedWidgets":[]},"errorSummary":null,"error":null,"startTime":1.464931527858E12,"submitTime":1.464931321021E12,"finishTime":1.464931531132E12,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"r.sainudiin@math.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"a4b6e4a4-419c-4115-9f70-1c0323e27b27"},{"version":"CommandV1","origId":123828,"guid":"02b001d3-90ba-4715-8338-32959a9f7ff0","subtype":"command","commandType":"auto","position":14.8828125,"command":"%sh\nwget http://www.math.canterbury.ac.nz/~r.sainudiin/tmp/train.zip","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\">--2016-06-03 06:02:18-- http://www.math.canterbury.ac.nz/~r.sainudiin/tmp/train.zip\nResolving www.math.canterbury.ac.nz (www.math.canterbury.ac.nz)... 132.181.26.35\nConnecting to www.math.canterbury.ac.nz (www.math.canterbury.ac.nz)|132.181.26.35|:80... connected.\nHTTP request sent, awaiting response... 200 OK\nLength: 959247528 (915M) [application/zip]\nSaving to: 'train.zip'\n\n 0K .......... .......... .......... .......... .......... 0% 342K 45m39s\n 50K .......... .......... .......... .......... .......... 0% 1.20M 29m12s\n 100K .......... .......... .......... .......... .......... 0% 1.36M 23m12s\n 150K .......... .......... .......... .......... .......... 0% 17.9M 17m37s\n 200K .......... .......... .......... .......... .......... 0% 1.49M 16m9s\n 250K .......... .......... .......... .......... .......... 0% 14.8M 13m38s\n 300K .......... .......... .......... .......... .......... 0% 1.49M 13m8s\n 350K .......... .......... .......... .......... .......... 0% 19.7M 11m36s\n 400K .......... .......... .......... .......... .......... 0% 29.0M 10m22s\n 450K .......... .......... .......... .......... .......... 0% 1.42M 10m24s\n 500K .......... .......... .......... .......... .......... 0% 15.5M 9m33s\n 550K .......... .......... .......... .......... .......... 0% 45.1M 8m46s\n 600K .......... .......... .......... .......... .......... 0% 1.42M 8m55s\n 650K .......... .......... .......... .......... .......... 0% 16.7M 8m21s\n 700K .......... .......... .......... .......... .......... 0% 24.8M 7m50s\n 750K .......... .......... .......... .......... .......... 0% 1.48M 7m59s\n 800K .......... .......... .......... .......... .......... 0% 21.6M 7m33s\n 850K .......... .......... .......... .......... .......... 0% 26.5M 7m10s\n 900K .......... .......... .......... .......... .......... 0% 20.9M 6m50s\n 950K .......... .......... .......... .......... .......... 0% 1.22M 7m7s\n 1000K .......... .......... .......... .......... .......... 0% 22.8M 6m48s\n 1050K .......... .......... .......... .......... .......... 0% 40.8M 6m31s\n 1100K .......... .......... .......... .......... .......... 0% 46.7M 6m15s\n 1150K .......... .......... .......... .......... .......... 0% 1.48M 6m25s\n 1200K .......... .......... .......... .......... .......... 0% 21.2M 6m11s\n 1250K .......... .......... .......... .......... .......... 0% 35.9M 5m58s\n 1300K .......... .......... .......... .......... .......... 0% 1.54M 6m6s\n 1350K .......... .......... .......... .......... .......... 0% 58.2M 5m54s\n 1400K .......... .......... .......... .......... .......... 0% 20.9M 5m43s\n 1450K .......... .......... .......... .......... .......... 0% 21.0M 5m33s\n 1500K .......... .......... .......... .......... .......... 0% 19.5M 5m24s\n 1550K .......... .......... .......... .......... .......... 0% 1.67M 5m31s\n 1600K .......... .......... .......... .......... .......... 0% 57.5M 5m21s\n 1650K .......... .......... .......... .......... .......... 0% 18.2M 5m13s\n 1700K .......... .......... .......... .......... .......... 0% 27.4M 5m5s\n 1750K .......... .......... .......... .......... .......... 0% 22.8M 4m58s\n 1800K .......... .......... .......... .......... .......... 0% 83.3M 4m50s\n 1850K .......... .......... .......... .......... .......... 0% 1.66M 4m57s\n 1900K .......... .......... .......... .......... .......... 0% 16.6M 4m51s\n 1950K .......... .......... .......... .......... .......... 0% 32.1M 4m44s\n 2000K .......... .......... .......... .......... .......... 0% 25.8M 4m38s\n 2050K .......... .......... .......... .......... .......... 0% 82.8M 4m32s\n 2100K .......... .......... .......... .......... .......... 0% 1.63M 4m38s\n 2150K .......... .......... .......... .......... .......... 0% 20.1M 4m33s\n 2200K .......... .......... .......... .......... .......... 0% 21.3M 4m28s\n 2250K .......... .......... .......... .......... .......... 0% 20.6M 4m23s\n 2300K .......... .......... .......... .......... .......... 0% 69.3M 4m18s\n 2350K .......... .......... .......... .......... .......... 0% 64.4M 4m13s\n 2400K .......... .......... .......... .......... .......... 0% 1.67M 4m19s\n 2450K .......... .......... .......... .......... .......... 0% 28.6M 4m14s\n 2500K .......... .......... .......... .......... .......... 0% 35.6M 4m10s\n 2550K .......... .......... .......... .......... .......... 0% 23.3M 4m5s\n 2600K .......... .......... .......... .......... .......... 0% 27.5M 4m1s\n 2650K .......... .......... .......... .......... .......... 0% 37.5M 3m57s\n 2700K .......... .......... .......... .......... .......... 0% 1.69M 4m3s\n 2750K .......... .......... .......... .......... .......... 0% 62.8M 3m59s\n 2800K .......... .......... .......... .......... .......... 0% 22.0M 3m55s\n 2850K .......... .......... .......... .......... .......... 0% 30.3M 3m52s\n 2900K .......... .......... .......... .......... .......... 0% 26.3M 3m48s\n 2950K .......... .......... .......... .......... .......... 0% 37.7M 3m45s\n 3000K .......... .......... .......... .......... .......... 0% 48.1M 3m42s\n 3050K .......... .......... .......... .......... .......... 0% 1.64M 3m47s\n 3100K .......... .......... .......... .......... .......... 0% 30.5M 3m44s\n 3150K .......... .......... .......... .......... .......... 0% 33.0M 3m41s\n 3200K .......... .......... .......... .......... .......... 0% 69.9M 3m38s\n 3250K .......... .......... .......... .......... .......... 0% 37.2M 3m35s\n 3300K .......... .......... .......... .......... .......... 0% 42.9M 3m32s\n 3350K .......... .......... .......... .......... .......... 0% 1.54M 3m37s\n 3400K .......... .......... .......... .......... .......... 0% 51.8M 3m34s\n 3450K .......... .......... .......... .......... .......... 0% 54.1M 3m32s\n 3500K .......... .......... .......... .......... .......... 0% 25.2M 3m29s\n 3550K .......... .......... .......... .......... .......... 0% 41.0M 3m27s\n 3600K .......... .......... .......... .......... .......... 0% 41.3M 3m24s\n 3650K .......... .......... .......... .......... .......... 0% 43.5M 3m21s\n 3700K .......... .......... .......... .......... .......... 0% 56.3M 3m19s\n 3750K .......... .......... .......... .......... .......... 0% 1.57M 3m24s\n 3800K .......... .......... .......... .......... .......... 0% 50.7M 3m22s\n 3850K .......... .......... .......... .......... .......... 0% 22.9M 3m20s\n 3900K .......... .......... .......... .......... .......... 0% 40.3M 3m17s\n 3950K .......... .......... .......... .......... .......... 0% 58.9M 3m15s\n 4000K .......... .......... .......... .......... .......... 0% 17.1M 3m13s\n 4050K .......... .......... .......... .......... .......... 0% 30.8M 3m11s\n 4100K .......... .......... .......... .......... .......... 0% 1.78M 3m15s\n 4150K .......... .......... .......... .......... .......... 0% 49.9M 3m13s\n 4200K .......... .......... .......... .......... .......... 0% 35.9M 3m11s\n 4250K .......... .......... .......... .......... .......... 0% 26.4M 3m9s\n 4300K .......... .......... .......... .......... .......... 0% 23.8M 3m7s\n 4350K .......... .......... .......... .......... .......... 0% 19.4M 3m6s\n 4400K .......... .......... .......... .......... .......... 0% 28.8M 3m4s\n 4450K .......... .......... .......... .......... .......... 0% 17.1M 3m3s\n 4500K .......... .......... .......... .......... .......... 0% 1.90M 3m6s\n 4550K .......... .......... .......... .......... .......... 0% 40.0M 3m4s\n 4600K .......... .......... .......... .......... .......... 0% 49.4M 3m2s\n 4650K .......... .......... .......... .......... .......... 0% 42.5M 3m1s\n 4700K .......... .......... .......... .......... .......... 0% 28.3M 2m59s\n 4750K .......... .......... .......... .......... .......... 0% 14.0M 2m58s\n 4800K .......... .......... .......... .......... .......... 0% 13.5M 2m57s\n 4850K .......... .......... .......... .......... .......... 0% 47.3M 2m55s\n 4900K .......... .......... .......... .......... .......... 0% 1.82M 2m58s\n 4950K .......... .......... .......... .......... .......... 0% 26.2M 2m57s\n 5000K .......... .......... .......... .......... .......... 0% 42.5M 2m55s\n 5050K .......... .......... .......... .......... .......... 0% 44.0M 2m54s\n 5100K .......... .......... .......... .......... .......... 0% 48.5M 2m52s\n 5150K .......... .......... .......... .......... .......... 0% 17.7M 2m51s\n 5200K .......... .......... .......... .......... .......... 0% 15.1M 2m50s\n 5250K .......... .......... .......... .......... .......... 0% 1.85M 2m53s\n 5300K .......... .......... .......... .......... .......... 0% 40.7M 2m52s\n 5350K .......... .......... .......... .......... .......... 0% 16.9M 2m51s\n 5400K .......... .......... .......... .......... .......... 0% 38.4M 2m49s\n 5450K .......... .......... .......... .......... .......... 0% 24.6M 2m48s\n 5500K .......... .......... .......... .......... .......... 0% 28.6M 2m47s\n 5550K .......... .......... .......... .......... .......... 0% 51.2M 2m45s\n 5600K .......... .......... .......... .......... .......... 0% 27.1M 2m44s\n 5650K .......... .......... .......... .......... .......... 0% 1.84M 2m47s\n 5700K .......... .......... .......... .......... .......... 0% 8.76M 2m47s\n 5750K .......... .......... .......... .......... .......... 0% 43.8M 2m45s\n 5800K .......... .......... .......... .......... .......... 0% 47.3M 2m44s\n 5850K .......... .......... .......... .......... .......... 0% 15.3M 2m43s\n 5900K .......... .......... .......... .......... .......... 0% 38.6M 2m42s\n 5950K .......... .......... .......... .......... .......... 0% 18.8M 2m41s\n 6000K .......... .......... .......... .......... .......... 0% 46.6M 2m40s\n 6050K .......... .......... .......... .......... .......... 0% 2.19M 2m42s\n 6100K .......... .......... .......... .......... .......... 0% 7.76M 2m42s\n 6150K .......... .......... .......... .......... .......... 0% 24.2M 2m41s\n 6200K .......... .......... .......... .......... .......... 0% 34.1M 2m39s\n 6250K .......... .......... .......... .......... .......... 0% 31.1M 2m38s\n 6300K .......... .......... .......... .......... .......... 0% 25.4M 2m37s\n 6350K .......... .......... .......... .......... .......... 0% 23.7M 2m36s\n 6400K .......... .......... .......... .......... .......... 0% 2.27M 2m38s\n 6450K .......... .......... .......... .......... .......... 0% 7.66M 2m38s\n 6500K .......... .......... .......... .......... .......... 0% 42.4M 2m37s\n 6550K .......... .......... .......... .......... .......... 0% 20.4M 2m36s\n 6600K .......... .......... .......... .......... .......... 0% 15.8M 2m35s\n 6650K .......... .......... .......... .......... .......... 0% 21.4M 2m35s\n 6700K .......... .......... .......... .......... .......... 0% 50.2M 2m34s\n 6750K .......... .......... .......... .......... .......... 0% 26.9M 2m33s\n 6800K .......... .......... .......... .......... .......... 0% 2.50M 2m34s\n 6850K .......... .......... .......... .......... .......... 0% 6.79M 2m34s\n 6900K .......... .......... .......... .......... .......... 0% 13.1M 2m33s\n 6950K .......... .......... .......... .......... .......... 0% 32.8M 2m32s\n 7000K .......... .......... .......... .......... .......... 0% 14.5M 2m32s\n 7050K .......... .......... .......... .......... .......... 0% 48.6M 2m31s\n 7100K .......... .......... .......... .......... .......... 0% 28.9M 2m30s\n 7150K .......... .......... .......... .......... .......... 0% 2.68M 2m31s\n 7200K .......... .......... .......... .......... .......... 0% 54.2M 2m30s\n 7250K .......... .......... .......... .......... .......... 0% 6.29M 2m30s\n 7300K .......... .......... .......... .......... 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.......... .......... 98% 4.24M 1s\n926250K .......... .......... .......... .......... .......... 98% 54.0M 1s\n926300K .......... .......... .......... .......... .......... 98% 7.09M 1s\n926350K .......... .......... .......... .......... .......... 98% 12.8M 1s\n926400K .......... .......... .......... .......... .......... 98% 5.83M 1s\n926450K .......... .......... .......... .......... .......... 98% 56.5M 1s\n926500K .......... .......... .......... .......... .......... 98% 8.50M 1s\n926550K .......... .......... .......... .......... .......... 98% 28.3M 1s\n926600K .......... .......... .......... .......... .......... 98% 5.23M 1s\n926650K .......... .......... .......... .......... .......... 98% 6.91M 1s\n926700K .......... .......... .......... .......... .......... 98% 73.2M 1s\n926750K .......... .......... .......... .......... .......... 98% 8.74M 1s\n926800K .......... .......... .......... .......... .......... 98% 7.59M 1s\n926850K .......... .......... .......... 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.......... .......... 99% 38.7M 0s\n932100K .......... .......... .......... .......... .......... 99% 4.14M 0s\n932150K .......... .......... .......... .......... .......... 99% 2.68M 0s\n932200K .......... .......... .......... .......... .......... 99% 12.3M 0s\n932250K .......... .......... .......... .......... .......... 99% 21.2M 0s\n932300K .......... .......... .......... .......... .......... 99% 26.3M 0s\n932350K .......... .......... .......... .......... .......... 99% 17.3M 0s\n932400K .......... .......... .......... .......... .......... 99% 45.8M 0s\n932450K .......... .......... .......... .......... .......... 99% 6.46M 0s\n932500K .......... .......... .......... .......... .......... 99% 2.72M 0s\n932550K .......... .......... .......... .......... .......... 99% 37.4M 0s\n932600K .......... .......... .......... .......... .......... 99% 15.7M 0s\n932650K .......... .......... .......... .......... .......... 99% 15.4M 0s\n932700K .......... .......... .......... .......... .......... 99% 15.3M 0s\n932750K .......... .......... .......... .......... .......... 99% 32.5M 0s\n932800K .......... .......... .......... .......... .......... 99% 28.1M 0s\n932850K .......... .......... .......... .......... .......... 99% 4.14M 0s\n932900K .......... .......... .......... .......... .......... 99% 2.58M 0s\n932950K .......... .......... .......... .......... .......... 99% 32.5M 0s\n933000K .......... .......... .......... .......... .......... 99% 52.7M 0s\n933050K .......... .......... .......... .......... .......... 99% 19.9M 0s\n933100K .......... .......... .......... .......... .......... 99% 13.9M 0s\n933150K .......... .......... .......... .......... .......... 99% 47.3M 0s\n933200K .......... .......... .......... .......... .......... 99% 5.66M 0s\n933250K .......... .......... .......... .......... .......... 99% 65.0M 0s\n933300K .......... .......... .......... .......... .......... 99% 2.56M 0s\n933350K .......... .......... .......... 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.......... .......... 99% 2.59M 0s\n936000K .......... .......... .......... .......... .......... 99% 12.2M 0s\n936050K .......... .......... .......... .......... .......... 99% 39.7M 0s\n936100K .......... .......... .......... .......... .......... 99% 9.80M 0s\n936150K .......... .......... .......... .......... .......... 99% 26.9M 0s\n936200K .......... .......... .......... .......... .......... 99% 27.5M 0s\n936250K .......... .......... .......... .......... .......... 99% 50.0M 0s\n936300K .......... .......... .......... .......... .......... 99% 9.09M 0s\n936350K .......... .......... .......... .......... .......... 99% 2.65M 0s\n936400K .......... .......... .......... .......... .......... 99% 7.92M 0s\n936450K .......... .......... .......... .......... .......... 99% 20.2M 0s\n936500K .......... .......... .......... .......... .......... 99% 56.6M 0s\n936550K .......... .......... .......... .......... .......... 99% 16.7M 0s\n936600K .......... .......... .......... .......... .......... 99% 39.9M 0s\n936650K .......... .......... .......... .......... .......... 99% 10.6M 0s\n936700K .......... .......... .......... .......... .......... 99% 2.50M 0s\n936750K .......... ..... 100% 45.8M=1m40s\n\n2016-06-03 06:03:58 (9.12 MB/s) - 'train.zip' saved [959247528/959247528]\n\n</div>","arguments":{},"addedWidgets":{},"removedWidgets":[]},"errorSummary":null,"error":null,"startTime":1.46493373801E12,"submitTime":1.464933531173E12,"finishTime":1.464933838543E12,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"r.sainudiin@math.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"9175899a-1394-4361-b2b4-6581b0819316"},{"version":"CommandV1","origId":123824,"guid":"4858215c-9156-488e-a1ad-9015694cbc10","subtype":"command","commandType":"auto","position":14.890625,"command":"dbutils.fs.mkdirs(\"dbfs:/datasets/eeg\")","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\"><span class=\"ansired\">Out[</span><span class=\"ansired\">12</span><span class=\"ansired\">]: </span>True\n</div>","arguments":{},"addedWidgets":{},"removedWidgets":[]},"errorSummary":null,"error":null,"startTime":1.464931730661E12,"submitTime":1.46493152391E12,"finishTime":1.464931730992E12,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"r.sainudiin@math.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"5859c006-1380-4a65-bd13-58919d2b190a"},{"version":"CommandV1","origId":123825,"guid":"1f266fb6-d6f0-42f2-8a78-184a243a6ae7","subtype":"command","commandType":"auto","position":14.8984375,"command":"dbutils.fs.cp(\"file:/databricks/driver/train.zip\",\"dbfs:/datasets/eeg/\")","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\"><span class=\"ansired\">Out[</span><span class=\"ansired\">23</span><span class=\"ansired\">]: </span>True\n</div>","arguments":{},"addedWidgets":{},"removedWidgets":[]},"errorSummary":null,"error":null,"startTime":1.464933874859E12,"submitTime":1.464933668036E12,"finishTime":1.464933952179E12,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"r.sainudiin@math.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"305753ac-46ac-4947-b31e-8484d04fa65e"},{"version":"CommandV1","origId":123823,"guid":"00c998a9-2d8e-47b7-a9ed-34e07b95adb0","subtype":"command","commandType":"auto","position":14.90625,"command":"display(dbutils.fs.ls(\"dbfs:/datasets/eeg/\"))","commandVersion":0,"state":"finished","results":{"type":"table","data":[["dbfs:/datasets/eeg/test.zip","test.zip",2.256896E7],["dbfs:/datasets/eeg/train.zip","train.zip",9.59247528E8]],"arguments":{},"addedWidgets":{},"removedWidgets":[],"schema":[{"name":"path","type":"\"string\""},{"name":"name","type":"\"string\""},{"name":"size","type":"\"long\""}],"overflow":false,"aggData":[],"aggSchema":[],"aggOverflow":false,"aggSeriesLimitReached":false,"aggError":"","aggType":"","plotOptions":null,"isJsonSchema":true,"dbfsResultPath":null},"errorSummary":"java.net.URISyntaxException: Expected authority at index 7: dbfs://","error":"<div class=\"ansiout\"><span class=\"ansired\">---------------------------------------------------------------------------</span>\n<span class=\"ansired\">ExecutionError</span> Traceback (most recent call last)\n<span class=\"ansigreen\"><ipython-input-9-f832d9235848></span> in <span class=\"ansicyan\"><module></span><span class=\"ansiblue\">()</span>\n<span class=\"ansigreen\">----> 1</span><span class=\"ansiyellow\"> </span>display<span class=\"ansiyellow\">(</span>dbutils<span class=\"ansiyellow\">.</span>fs<span class=\"ansiyellow\">.</span>ls<span class=\"ansiyellow\">(</span><span class=\"ansiblue\">"dbfs://"</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n\n<span class=\"ansigreen\">/tmp/1464828131988-0/dbutils.pyc</span> in <span class=\"ansicyan\">f_with_exception_handling</span><span class=\"ansiblue\">(*args, **kwargs)</span>\n<span class=\"ansigreen\"> 116</span> <span class=\"ansigreen\">class</span> ExecutionError<span class=\"ansiyellow\">(</span>BaseException<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 117</span> <span class=\"ansigreen\">pass</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">--> 118</span><span class=\"ansiyellow\"> </span><span class=\"ansigreen\">raise</span> ExecutionError<span class=\"ansiyellow\">(</span>str<span class=\"ansiyellow\">(</span>e<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 119</span> <span class=\"ansigreen\">return</span> f_with_exception_handling<span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 120</span> <span class=\"ansiyellow\"></span>\n\n<span class=\"ansired\">ExecutionError</span>: An error occurred while calling z:com.databricks.backend.daemon.dbutils.FSUtils.ls.\n: java.net.URISyntaxException: Expected authority at index 7: dbfs://\n\tat java.net.URI$Parser.fail(URI.java:2848)\n\tat java.net.URI$Parser.failExpecting(URI.java:2854)\n\tat java.net.URI$Parser.parseHierarchical(URI.java:3102)\n\tat java.net.URI$Parser.parse(URI.java:3053)\n\tat java.net.URI.<init>(URI.java:820)\n\tat com.databricks.util.URIHelper$.createURI(URIHelper.scala:24)\n\tat com.databricks.backend.daemon.dbutils.FSUtils$.getPath(DBUtilsCore.scala:157)\n\tat com.databricks.backend.daemon.dbutils.FSUtils$.getFS(DBUtilsCore.scala:168)\n\tat com.databricks.backend.daemon.dbutils.FSUtils$.ls(DBUtilsCore.scala:60)\n\tat com.databricks.backend.daemon.dbutils.FSUtils.ls(DBUtilsCore.scala)\n\tat sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)\n\tat sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)\n\tat sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)\n\tat java.lang.reflect.Method.invoke(Method.java:497)\n\tat py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)\n\tat py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381)\n\tat py4j.Gateway.invoke(Gateway.java:259)\n\tat py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)\n\tat py4j.commands.CallCommand.execute(CallCommand.java:79)\n\tat py4j.GatewayConnection.run(GatewayConnection.java:209)\n\tat java.lang.Thread.run(Thread.java:745)\n\n</div>","startTime":1.464934193085E12,"submitTime":1.464933986198E12,"finishTime":1.464934194052E12,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"r.sainudiin@math.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"221728dc-3f95-4ac4-84bf-5380752b53d2"},{"version":"CommandV1","origId":123826,"guid":"cc8dd18c-2868-4a41-8c91-24bf028d54e9","subtype":"command","commandType":"auto","position":14.921875,"command":"testRdd = sc.textFile('dbfs:/datasets/eeg/test.zip')\ntrainRdd = sc.textFile('dbfs:/datasets/eeg/train.zip')","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\"></div>","arguments":{},"addedWidgets":{},"removedWidgets":[]},"errorSummary":null,"error":null,"startTime":1.464934216538E12,"submitTime":1.464934009702E12,"finishTime":1.464934216619E12,"collapsed":false,"bindings":{},"inputWidgets":{},"displayType":"table","width":"auto","height":"auto","xColumns":null,"yColumns":null,"pivotColumns":null,"pivotAggregation":null,"customPlotOptions":{},"commentThread":[],"commentsVisible":false,"parentHierarchy":[],"diffInserts":[],"diffDeletes":[],"globalVars":{},"latestUser":"r.sainudiin@math.canterbury.ac.nz","commandTitle":"","showCommandTitle":false,"hideCommandCode":false,"hideCommandResult":false,"iPythonMetadata":null,"nuid":"702d136e-5fd9-4e85-ba4b-c141fbc5f497"},{"version":"CommandV1","origId":123827,"guid":"90e829be-063c-44fe-bd42-4a92bf8dad20","subtype":"command","commandType":"auto","position":14.9296875,"command":"testRdd.take(5)","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\"><span class=\"ansired\">Out[</span><span class=\"ansired\">21</span><span class=\"ansired\">]: </span>\n[u'PK\\x03\\x04\\x14\\x03\\x00\\x00\\x00\\x009H\\ufffdF\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x05\\x00\\x00\\x00test/PK\\x03\\x04\\x14\\x03\\x00\\x00\\x08\\x00zl\\ufffdF\\ufffd',\n u'\\ufffdj\\ufffd\\ufffdb\\x00\\x1c\\ufffd"\\x01\\x1d\\x00\\x00\\x00test/subj10_series10_data.csvd\\ufffd\\ufffd\\ufffd\\x141\\x10Es\\ufffd\\ufffd\\ufffd\\ufffd\\ufffd\\ufffd&\\ufffd\\t6GB\\x10@\\ufffdX\\ufffd\\ufffd\\ufffd\\ufffd\\ufffd!\\x1b\\ufffdO\\ufffd}\\x03\\ufffd)\\ufffd?\\ufffds\\ufffdm\\x1bqo\\ufffd\\ufffd\\ufffd\\ufffd{p\\ufffd\\ufffdo\\ufffd\\ufffd\\ufffd6\\ufffd{ssn\\ufffd\\u0702\\ufffd\\ufffd\\ufffdcq{\\ufffd\\ufffd6\\ufffd\\ufffd\\ufffdl\\ufffdh\\x1e\\ufffd\\ufffdG\\ufffd<\\ufffd\\x16o\\ufffd\\ufffd\\'o\\ufffd\\x0b\\x1b_>\\ufffd~\\ufffde\\ufffd\\ufffd\\u01cf??\\x7f|\\ufffd\\ufffd\\ufffd\\ufffdv\\ufffd\\u01229\\ufffdF;\\x1e\\ufffd\\ufffdPjgBj\\ufffd\\ufffd\\u0296\\ufffd\\x07V\\ufffd\\\\xO\\u05a2\\ufffd\\ufffd\\ufffd\\ufffdEY\\ufffd\\ufffd"\\ufffd\\ufffdG\\x131\\ufffdj|\\x05r\\ufffd\\x08l\\ufffd\\ufffd\\ufffdq\\ufffd\\x07\\ufffd\\ufffd\\ufffd\\ufffd\\x1cR\\u04c5k\\ufffd\\ufffdQ\\x14\\ufffd%\\ufffd {\\ufffd]\\ufffdN\\x0c\\ufffd\\'\\ufffd"\\ufffd\\ufffdI\\x15\\ufffd\\ufffdA\\ufffd\\ufffd',\n u'\\ufffd0\\x17\\ufffd$V\\ufffd\\u02c81Q\\x08w4_OG\\x1c\\ufffd\\ufffd\\ufffdz!\\ufffdS\\ufffdY\\ufffd\\ufffd F?\\'\\u0478\\ufffdf\\x0b\\ufffd\\ufffd\\x13)\\ufffdU\\ufffd\\x07\\ufffd\\ufffd\\ufffd\\ufffd\\x06\\u04ba\\ufffdk\\x06\\ufffd\\x15X&\\x1e"\\ufffd\\t\\ufffd\\ufffdD=)C\\ufffd\\ufffdx\\ufffdn\\ufffd\\ufffdU\\ufffdN\\ufffd`%n\\ufffd}\\x14;K\\ufffd\\ufffd\\x11c\\x18\\u04d0%\\ufffd\\x1a\\ufffd\\x11%LI;\\ufffd\\ufffdXO\\ufffd8S\\ufffd,<\\ufffdL\\x11',\n u'"\\x1a-\\u0467\\ufffd|\\ufffd\\ufffda\\ufffd\\ufffd:\\ufffd[\\ufffdY\\ufffd>\\ufffdn\\ufffd\\ufffd\\ufffdW\\ufffd\\ufffd\\ufffd\\x19\\ufffdp\\ufffd\\x1b3\\ufffdN\\ufffd\\u0132X\\x0b\\ufffd@\\ufffdv\\ufffd31\\t\\ufffd\\ufffdE\\ufffdZ\\ufffd&Bh.\\ufffd\\ufffdn/B\\ufffdas\\ufffd2\\x06^\\ufffd\\x14Z\\ufffdH\\ufffd\\ufffd\\ufffd\\ufffd\\x7f\\ufffdq\\ufffd\\x11K\\ufffd\\ufffdJ\\x14B)<\\ufffd4am\\ufffd9\\ufffdE\\x05\\u0767Qa!l\\x161Dy\\x13fD',\n u'\\x1f\\ufffd\\ufffd\\ufffd^\\ufffd\\ufffdT\\ufffd.\\ufffd\\ufffd$\\ufffdT,\\ufffdmW+yr\\ufffdBe\\ufffdg\\ufffd\\ufffd']\n</div>","arguments":{},"addedWidgets":{},"removedWidgets":[]},"errorSummary":"org.apache.hadoop.mapred.InvalidInputException: Input path does not exist: dbfs:/databricks/driver/test.zip","error":"<div class=\"ansiout\"><span class=\"ansired\">---------------------------------------------------------------------------</span>\n<span class=\"ansired\">Py4JJavaError</span> Traceback (most recent call last)\n<span class=\"ansigreen\"><ipython-input-19-ebf95bc3bdb8></span> in <span class=\"ansicyan\"><module></span><span class=\"ansiblue\">()</span>\n<span class=\"ansigreen\">----> 1</span><span class=\"ansiyellow\"> </span>testRdd<span class=\"ansiyellow\">.</span>take<span class=\"ansiyellow\">(</span><span class=\"ansicyan\">5</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n\n<span class=\"ansigreen\">/databricks/spark/python/pyspark/rdd.pyc</span> in <span class=\"ansicyan\">take</span><span class=\"ansiblue\">(self, num)</span>\n<span class=\"ansigreen\"> 1265</span> """\n<span class=\"ansigreen\"> 1266</span> items <span class=\"ansiyellow\">=</span> <span class=\"ansiyellow\">[</span><span class=\"ansiyellow\">]</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">-> 1267</span><span class=\"ansiyellow\"> </span>totalParts <span class=\"ansiyellow\">=</span> self<span class=\"ansiyellow\">.</span>getNumPartitions<span class=\"ansiyellow\">(</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 1268</span> partsScanned <span class=\"ansiyellow\">=</span> <span class=\"ansicyan\">0</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 1269</span> <span class=\"ansiyellow\"></span>\n\n<span class=\"ansigreen\">/databricks/spark/python/pyspark/rdd.pyc</span> in <span class=\"ansicyan\">getNumPartitions</span><span class=\"ansiblue\">(self)</span>\n<span class=\"ansigreen\"> 354</span> <span class=\"ansicyan\">2</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 355</span> """\n<span class=\"ansigreen\">--> 356</span><span class=\"ansiyellow\"> </span><span class=\"ansigreen\">return</span> self<span class=\"ansiyellow\">.</span>_jrdd<span class=\"ansiyellow\">.</span>partitions<span class=\"ansiyellow\">(</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">.</span>size<span class=\"ansiyellow\">(</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 357</span> <span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 358</span> <span class=\"ansigreen\">def</span> filter<span class=\"ansiyellow\">(</span>self<span class=\"ansiyellow\">,</span> f<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n\n<span class=\"ansigreen\">/databricks/python/local/lib/python2.7/site-packages/py4j/java_gateway.pyc</span> in <span class=\"ansicyan\">__call__</span><span class=\"ansiblue\">(self, *args)</span>\n<span class=\"ansigreen\"> 536</span> answer <span class=\"ansiyellow\">=</span> self<span class=\"ansiyellow\">.</span>gateway_client<span class=\"ansiyellow\">.</span>send_command<span class=\"ansiyellow\">(</span>command<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 537</span> return_value = get_return_value(answer, self.gateway_client,\n<span class=\"ansigreen\">--> 538</span><span class=\"ansiyellow\"> self.target_id, self.name)\n</span><span class=\"ansigreen\"> 539</span> <span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 540</span> <span class=\"ansigreen\">for</span> temp_arg <span class=\"ansigreen\">in</span> temp_args<span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n\n<span class=\"ansigreen\">/databricks/spark/python/pyspark/sql/utils.pyc</span> in <span class=\"ansicyan\">deco</span><span class=\"ansiblue\">(*a, **kw)</span>\n<span class=\"ansigreen\"> 43</span> <span class=\"ansigreen\">def</span> deco<span class=\"ansiyellow\">(</span><span class=\"ansiyellow\">*</span>a<span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">**</span>kw<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 44</span> <span class=\"ansigreen\">try</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">---> 45</span><span class=\"ansiyellow\"> </span><span class=\"ansigreen\">return</span> f<span class=\"ansiyellow\">(</span><span class=\"ansiyellow\">*</span>a<span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">**</span>kw<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 46</span> <span class=\"ansigreen\">except</span> py4j<span class=\"ansiyellow\">.</span>protocol<span class=\"ansiyellow\">.</span>Py4JJavaError <span class=\"ansigreen\">as</span> e<span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 47</span> s <span class=\"ansiyellow\">=</span> e<span class=\"ansiyellow\">.</span>java_exception<span class=\"ansiyellow\">.</span>toString<span class=\"ansiyellow\">(</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n\n<span class=\"ansigreen\">/databricks/python/local/lib/python2.7/site-packages/py4j/protocol.pyc</span> in <span class=\"ansicyan\">get_return_value</span><span class=\"ansiblue\">(answer, gateway_client, target_id, name)</span>\n<span class=\"ansigreen\"> 298</span> raise Py4JJavaError(\n<span class=\"ansigreen\"> 299</span> <span class=\"ansiblue\">'An error occurred while calling {0}{1}{2}.\\n'</span><span class=\"ansiyellow\">.</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">--> 300</span><span class=\"ansiyellow\"> format(target_id, '.', name), value)\n</span><span class=\"ansigreen\"> 301</span> <span class=\"ansigreen\">else</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 302</span> raise Py4JError(\n\n<span class=\"ansired\">Py4JJavaError</span>: An error occurred while calling o723.partitions.\n: org.apache.hadoop.mapred.InvalidInputException: Input path does not exist: dbfs:/databricks/driver/test.zip\n\tat org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:197)\n\tat org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:208)\n\tat org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:199)\n\tat org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)\n\tat org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)\n\tat scala.Option.getOrElse(Option.scala:120)\n\tat org.apache.spark.rdd.RDD.partitions(RDD.scala:237)\n\tat org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)\n\tat org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)\n\tat org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)\n\tat scala.Option.getOrElse(Option.scala:120)\n\tat org.apache.spark.rdd.RDD.partitions(RDD.scala:237)\n\tat org.apache.spark.api.java.JavaRDDLike$class.partitions(JavaRDDLike.scala:64)\n\tat org.apache.spark.api.java.AbstractJavaRDDLike.partitions(JavaRDDLike.scala:46)\n\tat sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)\n\tat sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)\n\tat sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)\n\tat java.lang.reflect.Method.invoke(Method.java:497)\n\tat py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)\n\tat py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381)\n\tat py4j.Gateway.invoke(Gateway.java:259)\n\tat py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)\n\tat py4j.commands.CallCommand.execute(CallCommand.java:79)\n\tat py4j.GatewayConnection.run(GatewayConnection.java:209)\n\tat 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