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Titanic Data Analysis using DataFrames.html
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Jessie Wills","female",null,0,0,"248727",33.0,null,"S"],[612,0,3,"Jardin, Mr. Jose Neto","male",null,0,0,"SOTON/O.Q. 3101305",7.05,null,"S"],[634,0,1,"Parr, Mr. William Henry Marsh","male",null,0,0,"112052",0.0,null,"S"],[670,1,1,"Taylor, Mrs. Elmer Zebley (Juliet Cummins Wright)","female",null,1,0,"19996",52.0,"C126","S"],[698,1,3,"\"Mullens, Miss. Katherine \"\"Katie\"\"\"","female",null,0,0,"35852",7.7333,null,"Q"],[728,1,3,"Mannion, Miss. Margareth","female",null,0,0,"36866",7.7375,null,"Q"],[774,0,3,"Elias, Mr. Dibo","male",null,0,0,"2674",7.225,null,"C"],[791,0,3,"\"Keane, Mr. Andrew \"\"Andy\"\"\"","male",null,0,0,"12460",7.75,null,"Q"],[826,0,3,"Flynn, Mr. John","male",null,0,0,"368323",6.95,null,"Q"],[860,0,3,"Razi, Mr. Raihed","male",null,0,0,"2629",7.2292,null,"C"],[889,0,3,"\"Johnston, Miss. Catherine Helen \"\"Carrie\"\"\"","female",null,1,2,"W./C. 6607",23.45,null,"S"]],"arguments":{},"addedWidgets":{},"removedWidgets":[],"schema":[{"name":"PassengerId","type":"\"integer\"","metadata":"{}"},{"name":"Survived","type":"\"integer\"","metadata":"{}"},{"name":"Pclass","type":"\"integer\"","metadata":"{}"},{"name":"Name","type":"\"string\"","metadata":"{}"},{"name":"Sex","type":"\"string\"","metadata":"{}"},{"name":"Age","type":"\"double\"","metadata":"{}"},{"name":"SibSp","type":"\"integer\"","metadata":"{}"},{"name":"Parch","type":"\"integer\"","metadata":"{}"},{"name":"Ticket","type":"\"string\"","metadata":"{}"},{"name":"Fare","type":"\"double\"","metadata":"{}"},{"name":"Cabin","type":"\"string\"","metadata":"{}"},{"name":"Embarked","type":"\"string\"","metadata":"{}"}],"overflow":false,"aggData":[],"aggSchema":[],"aggOverflow":false,"aggSeriesLimitReached":false,"aggError":"","aggType":"","plotOptions":null,"isJsonSchema":true,"dbfsResultPath":null,"datasetInfos":[]},"errorSummary":"<span class=\"ansired\">AttributeError</span>: 'DataFrame' object has no attribute 'age'","error":"<div class=\"ansiout\"><span class=\"ansired\">---------------------------------------------------------------------------</span>\n<span class=\"ansired\">AttributeError</span> Traceback (most recent call last)\n<span class=\"ansigreen\"><ipython-input-22-826c16ca6667></span> in <span class=\"ansicyan\"><module></span><span class=\"ansiblue\">()</span>\n<span class=\"ansigreen\">----> 1</span><span class=\"ansiyellow\"> </span>titanic_data<span class=\"ansiyellow\">.</span>orderBy<span class=\"ansiyellow\">(</span>titanic_data<span class=\"ansiyellow\">.</span>age<span class=\"ansiyellow\">.</span>desc<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/dataframe.py</span> in <span class=\"ansicyan\">__getattr__</span><span class=\"ansiblue\">(self, name)</span>\n<span class=\"ansigreen\"> 856</span> <span class=\"ansigreen\">if</span> name <span class=\"ansigreen\">not</span> <span class=\"ansigreen\">in</span> self<span class=\"ansiyellow\">.</span>columns<span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 857</span> raise AttributeError(\n<span class=\"ansigreen\">--> 858</span><span class=\"ansiyellow\"> "'%s' object has no attribute '%s'" % (self.__class__.__name__, name))\n</span><span class=\"ansigreen\"> 859</span> jc <span class=\"ansiyellow\">=</span> self<span class=\"ansiyellow\">.</span>_jdf<span class=\"ansiyellow\">.</span>apply<span class=\"ansiyellow\">(</span>name<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 860</span> <span class=\"ansigreen\">return</span> Column<span class=\"ansiyellow\">(</span>jc<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n\n<span class=\"ansired\">AttributeError</span>: 'DataFrame' object has no attribute 'age'</div>","workflows":[],"startTime":1512452578624,"submitTime":1512452578615,"finishTime":1512452579508,"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,"streamStates":{},"nuid":"06b35dfb-1a33-454e-a9b8-5ceb057b5b2c"},{"version":"CommandV1","origId":3739718737890563,"guid":"63e1fe1a-3509-4d88-a13b-f3c2ff4a7714","subtype":"command","commandType":"auto","position":9.0,"command":"#Person with longest name\ntitanic_data","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\"></div>","arguments":{},"addedWidgets":{},"removedWidgets":[],"datasetInfos":[]},"errorSummary":null,"error":null,"workflows":[],"startTime":1512452658241,"submitTime":1512452658220,"finishTime":1512452658313,"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,"streamStates":{},"nuid":"5e714330-d723-4d77-9811-396734561917"},{"version":"CommandV1","origId":3739718737890564,"guid":"d2591313-4802-4221-956a-b708e58f8add","subtype":"command","commandType":"auto","position":10.0,"command":"### UDF in dataframes","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\"></div>","arguments":{},"addedWidgets":{},"removedWidgets":[],"datasetInfos":[]},"errorSummary":null,"error":null,"workflows":[],"startTime":1512452973909,"submitTime":1512452973889,"finishTime":1512452973934,"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,"streamStates":{},"nuid":"1b6e4ae3-eadd-4e3b-b2c8-06e0219d5687"},{"version":"CommandV1","origId":3739718737890565,"guid":"79e91190-d069-44c0-b108-19342b7ee15e","subtype":"command","commandType":"auto","position":11.0,"command":"from pyspark.sql.functions import udf","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\"></div>","arguments":{},"addedWidgets":{},"removedWidgets":[],"datasetInfos":[]},"errorSummary":null,"error":null,"workflows":[],"startTime":1512452989021,"submitTime":1512452989001,"finishTime":1512452989065,"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,"streamStates":{},"nuid":"9d49c402-860e-4e4b-94fc-d5ad2b2c2c67"},{"version":"CommandV1","origId":3739718737890566,"guid":"52e2a719-815c-4ac2-ac7c-f1dea9fe763d","subtype":"command","commandType":"auto","position":12.0,"command":"def getLen(word):\n return len(word)","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\"></div>","arguments":{},"addedWidgets":{},"removedWidgets":[],"datasetInfos":[]},"errorSummary":null,"error":null,"workflows":[],"startTime":1512453029186,"submitTime":1512453029166,"finishTime":1512453029257,"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,"streamStates":{},"nuid":"513ad011-e2d1-46fc-ad79-c107a9cef105"},{"version":"CommandV1","origId":3739718737890567,"guid":"35c94339-6a54-4b27-b395-089f74a13de6","subtype":"command","commandType":"auto","position":13.0,"command":"from pyspark.sql.types import IntegerType\nlen_udf = udf(getLen, IntegerType())","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\"></div>","arguments":{},"addedWidgets":{},"removedWidgets":[],"datasetInfos":[]},"errorSummary":"<span class=\"ansired\">NameError</span>: name 'InttegerType' 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-30-4cfe54bd5d86></span> in <span class=\"ansicyan\"><module></span><span class=\"ansiblue\">()</span>\n<span class=\"ansigreen\"> 1</span> <span class=\"ansigreen\">from</span> pyspark<span class=\"ansiyellow\">.</span>sql<span class=\"ansiyellow\">.</span>types <span class=\"ansigreen\">import</span> IntegerType<span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">----> 2</span><span class=\"ansiyellow\"> </span>len_udf <span class=\"ansiyellow\">=</span> udf<span class=\"ansiyellow\">(</span>getLen<span class=\"ansiyellow\">,</span> InttegerType<span class=\"ansiyellow\">(</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n\n<span class=\"ansired\">NameError</span>: name 'InttegerType' is not defined</div>","workflows":[],"startTime":1512453107354,"submitTime":1512453107347,"finishTime":1512453107426,"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,"streamStates":{},"nuid":"2d120643-b2d5-4d5c-a10b-f2d459bcb3e4"},{"version":"CommandV1","origId":3739718737890568,"guid":"ba0f79e7-96fd-41da-8a61-cb4300570712","subtype":"command","commandType":"auto","position":14.0,"command":"titanic_data = titanic_data.select(\"*\", len_udf(\"Name\").alias(\"len_name\"))","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\"></div>","arguments":{},"addedWidgets":{},"removedWidgets":[],"datasetInfos":[]},"errorSummary":null,"error":null,"workflows":[],"startTime":1512453277778,"submitTime":1512453277735,"finishTime":1512453277850,"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,"streamStates":{},"nuid":"c4058468-1ea4-447d-b965-28150db0202b"},{"version":"CommandV1","origId":3739718737890569,"guid":"ae78d351-4bca-49cd-b186-581d08d88d83","subtype":"command","commandType":"auto","position":15.0,"command":"titanic_data.agg({'len_name':'max'}).collect()","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\"><span class=\"ansired\">Out[</span><span class=\"ansired\">40</span><span class=\"ansired\">]: </span>[Row(max(len_name)=82)]\n</div>","arguments":{},"addedWidgets":{},"removedWidgets":[],"datasetInfos":[]},"errorSummary":"<span class=\"ansired\">AnalysisException</span>: u'Cannot resolve column name "leb_name" among (PassengerId, Survived, Pclass, Name, Sex, Age, SibSp, Parch, Ticket, Fare, Cabin, Embarked, len_name);'","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-38-408d457d3d01></span> in <span class=\"ansicyan\"><module></span><span class=\"ansiblue\">()</span>\n<span class=\"ansigreen\">----> 1</span><span class=\"ansiyellow\"> </span>max_len <span class=\"ansiyellow\">=</span> titanic_data<span class=\"ansiyellow\">.</span>agg<span class=\"ansiyellow\">(</span><span class=\"ansiyellow\">{</span><span class=\"ansiblue\">'leb_name'</span><span class=\"ansiyellow\">:</span><span class=\"ansiblue\">'max'</span><span class=\"ansiyellow\">}</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n\n<span class=\"ansigreen\">/databricks/spark/python/pyspark/sql/dataframe.py</span> in <span class=\"ansicyan\">agg</span><span class=\"ansiblue\">(self, *exprs)</span>\n<span class=\"ansigreen\"> 1001</span> <span class=\"ansiyellow\">[</span>Row<span class=\"ansiyellow\">(</span>min<span class=\"ansiyellow\">(</span>age<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">=</span><span class=\"ansicyan\">2</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">]</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 1002</span> """\n<span class=\"ansigreen\">-> 1003</span><span class=\"ansiyellow\"> </span><span class=\"ansigreen\">return</span> self<span class=\"ansiyellow\">.</span>groupBy<span class=\"ansiyellow\">(</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">.</span>agg<span class=\"ansiyellow\">(</span><span class=\"ansiyellow\">*</span>exprs<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 1004</span> <span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 1005</span> <span class=\"ansiyellow\">@</span>since<span class=\"ansiyellow\">(</span><span class=\"ansicyan\">2.0</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n\n<span class=\"ansigreen\">/databricks/spark/python/pyspark/sql/group.py</span> in <span class=\"ansicyan\">agg</span><span class=\"ansiblue\">(self, *exprs)</span>\n<span class=\"ansigreen\"> 84</span> <span class=\"ansigreen\">assert</span> exprs<span class=\"ansiyellow\">,</span> <span class=\"ansiblue\">"exprs should not be empty"</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 85</span> <span class=\"ansigreen\">if</span> len<span class=\"ansiyellow\">(</span>exprs<span class=\"ansiyellow\">)</span> <span class=\"ansiyellow\">==</span> <span class=\"ansicyan\">1</span> <span class=\"ansigreen\">and</span> isinstance<span class=\"ansiyellow\">(</span>exprs<span class=\"ansiyellow\">[</span><span class=\"ansicyan\">0</span><span class=\"ansiyellow\">]</span><span class=\"ansiyellow\">,</span> dict<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">---> 86</span><span class=\"ansiyellow\"> </span>jdf <span class=\"ansiyellow\">=</span> self<span class=\"ansiyellow\">.</span>_jgd<span class=\"ansiyellow\">.</span>agg<span class=\"ansiyellow\">(</span>exprs<span class=\"ansiyellow\">[</span><span class=\"ansicyan\">0</span><span class=\"ansiyellow\">]</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 87</span> <span class=\"ansigreen\">else</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 88</span> <span class=\"ansired\"># Columns</span><span class=\"ansiyellow\"></span><span class=\"ansiyellow\"></span>\n\n<span class=\"ansigreen\">/databricks/spark/python/lib/py4j-0.10.3-src.zip/py4j/java_gateway.py</span> in <span class=\"ansicyan\">__call__</span><span class=\"ansiblue\">(self, *args)</span>\n<span class=\"ansigreen\"> 1131</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\"> 1132</span> return_value = get_return_value(\n<span class=\"ansigreen\">-> 1133</span><span class=\"ansiyellow\"> answer, self.gateway_client, self.target_id, self.name)\n</span><span class=\"ansigreen\"> 1134</span> <span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 1135</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.py</span> in <span class=\"ansicyan\">deco</span><span class=\"ansiblue\">(*a, **kw)</span>\n<span class=\"ansigreen\"> 67</span> e.java_exception.getStackTrace()))\n<span class=\"ansigreen\"> 68</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\">---> 69</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\"> 70</span> <span class=\"ansigreen\">if</span> s<span class=\"ansiyellow\">.</span>startswith<span class=\"ansiyellow\">(</span><span class=\"ansiblue\">'org.apache.spark.sql.catalyst.analysis'</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 71</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\n<span class=\"ansired\">AnalysisException</span>: u'Cannot resolve column name "leb_name" among (PassengerId, Survived, Pclass, Name, Sex, Age, SibSp, Parch, Ticket, Fare, Cabin, Embarked, len_name);'</div>","workflows":[],"startTime":1512453340066,"submitTime":1512453340056,"finishTime":1512453340339,"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,"streamStates":{},"nuid":"71cc63eb-d20d-44d2-889d-3c646b9ba2c4"},{"version":"CommandV1","origId":3739718737890570,"guid":"8c43bf1f-310f-4d05-bc7c-3e7be2d7e255","subtype":"command","commandType":"auto","position":16.0,"command":"display(titanic_data[titanic_data.len_name == 82])","commandVersion":0,"state":"finished","results":{"type":"table","data":[[308,1,1,"Penasco y Castellana, Mrs. Victor de Satode (Maria Josefa Perez de Soto y Vallejo)","female",17.0,1,0,"PC 17758",108.9,"C65","C",82]],"arguments":{},"addedWidgets":{},"removedWidgets":[],"schema":[{"name":"PassengerId","type":"\"integer\"","metadata":"{}"},{"name":"Survived","type":"\"integer\"","metadata":"{}"},{"name":"Pclass","type":"\"integer\"","metadata":"{}"},{"name":"Name","type":"\"string\"","metadata":"{}"},{"name":"Sex","type":"\"string\"","metadata":"{}"},{"name":"Age","type":"\"double\"","metadata":"{}"},{"name":"SibSp","type":"\"integer\"","metadata":"{}"},{"name":"Parch","type":"\"integer\"","metadata":"{}"},{"name":"Ticket","type":"\"string\"","metadata":"{}"},{"name":"Fare","type":"\"double\"","metadata":"{}"},{"name":"Cabin","type":"\"string\"","metadata":"{}"},{"name":"Embarked","type":"\"string\"","metadata":"{}"},{"name":"len_name","type":"\"integer\"","metadata":"{}"}],"overflow":false,"aggData":[],"aggSchema":[],"aggOverflow":false,"aggSeriesLimitReached":false,"aggError":"","aggType":"","plotOptions":null,"isJsonSchema":true,"dbfsResultPath":null,"datasetInfos":[]},"errorSummary":null,"error":null,"workflows":[],"startTime":1512453405254,"submitTime":1512453405247,"finishTime":1512453405566,"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,"streamStates":{},"nuid":"3abde311-cfa0-4ae0-976a-e81a35cb150e"},{"version":"CommandV1","origId":3739718737890571,"guid":"71c3f7d6-1fa9-426b-83df-2b8a0f81cb8f","subtype":"command","commandType":"auto","position":17.0,"command":"\n","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\"></div>","arguments":{},"addedWidgets":{},"removedWidgets":[],"datasetInfos":[]},"errorSummary":"<span class=\"ansired\">AnalysisException</span>: u'resolved attribute(s) len_name#955 missing from Survived#403,Cabin#412,Parch#409,Ticket#410,Name#405,len_name#784,Embarked#413,Fare#411,Sex#406,PassengerId#402,Pclass#404,Age#407,SibSp#408 in operator !Project [PassengerId#402, Survived#403, Pclass#404, Name#405, Sex#406, Age#407, SibSp#408, Parch#409, Ticket#410, Fare#411, Cabin#412, Embarked#413, len_name#784, len_name#955 AS newlen_name#958];;\\n!Project [PassengerId#402, Survived#403, Pclass#404, Name#405, Sex#406, Age#407, SibSp#408, Parch#409, Ticket#410, Fare#411, Cabin#412, Embarked#413, len_name#784, len_name#955 AS newlen_name#958]\\n+- Project [PassengerId#402, Survived#403, Pclass#404, Name#405, Sex#406, Age#407, SibSp#408, Parch#409, Ticket#410, Fare#411, Cabin#412, Embarked#413, getLen(Name#405) AS len_name#784]\\n +- Relation[PassengerId#402,Survived#403,Pclass#404,Name#405,Sex#406,Age#407,SibSp#408,Parch#409,Ticket#410,Fare#411,Cabin#412,Embarked#413] csv\\n'","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-52-80ef041d5a6d></span> in <span class=\"ansicyan\"><module></span><span class=\"ansiblue\">()</span>\n<span class=\"ansigreen\"> 1</span> <span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">----> 2</span><span class=\"ansiyellow\"> </span>titanic_data<span class=\"ansiyellow\">.</span>withColumn<span class=\"ansiyellow\">(</span><span class=\"ansiblue\">"newlen_name"</span><span class=\"ansiyellow\">,</span> titanic_data<span class=\"ansiyellow\">.</span>select<span class=\"ansiyellow\">(</span>len_udf<span class=\"ansiyellow\">(</span><span class=\"ansiblue\">"Name"</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">.</span>alias<span class=\"ansiyellow\">(</span><span class=\"ansiblue\">"len_name"</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">.</span>len_name <span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n\n<span class=\"ansigreen\">/databricks/spark/python/pyspark/sql/dataframe.py</span> in <span class=\"ansicyan\">withColumn</span><span class=\"ansiblue\">(self, colName, col)</span>\n<span class=\"ansigreen\"> 1385</span> """\n<span class=\"ansigreen\"> 1386</span> <span class=\"ansigreen\">assert</span> isinstance<span class=\"ansiyellow\">(</span>col<span class=\"ansiyellow\">,</span> Column<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">,</span> <span class=\"ansiblue\">"col should be Column"</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">-> 1387</span><span class=\"ansiyellow\"> </span><span class=\"ansigreen\">return</span> DataFrame<span class=\"ansiyellow\">(</span>self<span class=\"ansiyellow\">.</span>_jdf<span class=\"ansiyellow\">.</span>withColumn<span class=\"ansiyellow\">(</span>colName<span class=\"ansiyellow\">,</span> col<span class=\"ansiyellow\">.</span>_jc<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">,</span> self<span class=\"ansiyellow\">.</span>sql_ctx<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 1388</span> <span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 1389</span> <span class=\"ansiyellow\">@</span>ignore_unicode_prefix<span class=\"ansiyellow\"></span>\n\n<span class=\"ansigreen\">/databricks/spark/python/lib/py4j-0.10.3-src.zip/py4j/java_gateway.py</span> in <span class=\"ansicyan\">__call__</span><span class=\"ansiblue\">(self, *args)</span>\n<span class=\"ansigreen\"> 1131</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\"> 1132</span> return_value = get_return_value(\n<span class=\"ansigreen\">-> 1133</span><span class=\"ansiyellow\"> answer, self.gateway_client, self.target_id, self.name)\n</span><span class=\"ansigreen\"> 1134</span> <span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 1135</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.py</span> in <span class=\"ansicyan\">deco</span><span class=\"ansiblue\">(*a, **kw)</span>\n<span class=\"ansigreen\"> 67</span> e.java_exception.getStackTrace()))\n<span class=\"ansigreen\"> 68</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\">---> 69</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\"> 70</span> <span class=\"ansigreen\">if</span> s<span class=\"ansiyellow\">.</span>startswith<span class=\"ansiyellow\">(</span><span class=\"ansiblue\">'org.apache.spark.sql.catalyst.analysis'</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 71</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\n<span class=\"ansired\">AnalysisException</span>: u'resolved attribute(s) len_name#955 missing from Survived#403,Cabin#412,Parch#409,Ticket#410,Name#405,len_name#784,Embarked#413,Fare#411,Sex#406,PassengerId#402,Pclass#404,Age#407,SibSp#408 in operator !Project [PassengerId#402, Survived#403, Pclass#404, Name#405, Sex#406, Age#407, SibSp#408, Parch#409, Ticket#410, Fare#411, Cabin#412, Embarked#413, len_name#784, len_name#955 AS newlen_name#958];;\\n!Project [PassengerId#402, Survived#403, Pclass#404, Name#405, Sex#406, Age#407, SibSp#408, Parch#409, Ticket#410, Fare#411, Cabin#412, Embarked#413, len_name#784, len_name#955 AS newlen_name#958]\\n+- Project [PassengerId#402, Survived#403, Pclass#404, Name#405, Sex#406, Age#407, SibSp#408, Parch#409, Ticket#410, Fare#411, Cabin#412, Embarked#413, getLen(Name#405) AS len_name#784]\\n +- Relation[PassengerId#402,Survived#403,Pclass#404,Name#405,Sex#406,Age#407,SibSp#408,Parch#409,Ticket#410,Fare#411,Cabin#412,Embarked#413] csv\\n'</div>","workflows":[],"startTime":1512454151987,"submitTime":1512454151970,"finishTime":1512454152060,"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,"streamStates":{},"nuid":"4bd92935-a122-4dd0-a8e1-5d5e96d30a22"},{"version":"CommandV1","origId":3739718737890572,"guid":"5905e8d0-266a-4b84-a047-38c6d93265bc","subtype":"command","commandType":"auto","position":18.0,"command":"titanic_data.select(len_udf(\"Name\").alias(\"len_name\")).len_name","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\"><span class=\"ansired\">Out[</span><span class=\"ansired\">49</span><span class=\"ansired\">]: </span>Column<len_name>\n</div>","arguments":{},"addedWidgets":{},"removedWidgets":[],"datasetInfos":[]},"errorSummary":null,"error":null,"workflows":[],"startTime":1512453887637,"submitTime":1512453887629,"finishTime":1512453887709,"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,"streamStates":{},"nuid":"5c6a426a-d99e-4224-828f-92edab3c7249"},{"version":"CommandV1","origId":3739718737890573,"guid":"d78f0228-7348-4adb-bc49-8950cffd36a0","subtype":"command","commandType":"auto","position":19.0,"command":"##Remove all the rows in which age is missing","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\"></div>","arguments":{},"addedWidgets":{},"removedWidgets":[],"datasetInfos":[]},"errorSummary":null,"error":null,"workflows":[],"startTime":1512454412910,"submitTime":1512454412888,"finishTime":1512454412982,"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,"streamStates":{},"nuid":"fe68ea17-d996-4a1a-99b8-23bdf6da3163"},{"version":"CommandV1","origId":3739718737890574,"guid":"05ba9f60-93d7-4848-9f14-b16feca811a5","subtype":"command","commandType":"auto","position":20.0,"command":"help(titanic_data.dropna)","commandVersion":0,"state":"finished","results":{"type":"html","data":"<div class=\"ansiout\">Help on method dropna in module pyspark.sql.dataframe:\n\ndropna(self, how='any', thresh=None, subset=None) method of pyspark.sql.dataframe.DataFrame instance\n Returns a new :class:`DataFrame` omitting rows with null values.\n :func:`DataFrame.dropna` and :func:`DataFrameNaFunctions.drop` are aliases of each other.\n \n :param how: 'any' or 'all'.\n If 'any', drop a row if it contains any nulls.\n If 'all', drop a row only if all its values are null.\n :param thresh: int, default None\n If specified, drop rows that have less than `thresh` non-null values.\n This overwrites the `how` parameter.\n :param subset: optional list of column names to consider.\n \n >>> df4.na.drop().show()\n +---+------+-----+\n |age|height| name|\n +---+------+-----+\n | 10| 80|Alice|\n +---+------+-----+\n \n .. versionadded:: 1.3.1\n\n</div>","arguments":{},"addedWidgets":{},"removedWidgets":[],"datasetInfos":[]},"errorSummary":null,"error":null,"workflows":[],"startTime":1512454519357,"submitTime":1512454519335,"finishTime":1512454519428,"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,"streamStates":{},"nuid":"3d258393-ed91-4a10-ae72-3c5ed5e5b12f"},{"version":"CommandV1","origId":3739718737890575,"guid":"91ff559c-638b-48be-935c-774742df4813","subtype":"command","commandType":"auto","position":21.0,"command":"display(titanic_data.dropna(subset=['Age']))","commandVersion":0,"state":"finished","results":{"type":"table","data":[[1,0,3,"Braund, Mr. Owen Harris","male",22.0,1,0,"A/5 21171",7.25,null,"S",23],[2,1,1,"Cumings, Mrs. John Bradley (Florence Briggs Thayer)","female",38.0,1,0,"PC 17599",71.2833,"C85","C",51],[3,1,3,"Heikkinen, Miss. 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