statistical analysis book

',' earned '), 1,0) over (partition by sname order by Earnmonth) last month, /c6> Lead (Decode (NVL (personincome,0), 0,' not earned ',' earned '), 1,0) over (partition by sname ORDER by Earnmonth) Next month From earnings; Note: The lag and lead functions can take the first n rows of a field and the last n rows of data in a single query (which can be data from other fields, such as the word Jianyi of the previous row or the next two lines based on the field a), originally

second type: fragment+activity fragmentactivitypublic void Onresume () { super.onresume (); Mobclickagent.onresume (this); Statistical duration}public void OnPause () { super.onpause (); Mobclickagent.onpause (this);} fragmentpublic void Onresume () { super.onresume (); Mobclickagent.onpagestart ("Mainscreen"); Statistics page}public void OnPause () { super.onpause (); Mobclickagent.onpageend ("Mainscreen"); }6. Send Pol

Original address: http://javaz.cn/site/javaz/site_study/info/2015/23900.htmlProject Address:http://www.freeteam.cn/Statistical analysisSite-level statistical analysis for the statistics of current site data.Workload statisticsStatistics the workload of users under the current site. From the left admin menu click on Workload statistics to enter.You can filter by a

The construction process of the statistical analysis system, which is completely independently completed, is mainly used in the Php+hadoop+hive+thrift+mysql realization Installation Hadoop Installation: http://www.powerxing.com/install-hadoop/Hadoop cluster configuration: http://www.powerxing.com/install-hadoop-cluster/Hive Installation: https://chu888chu888.gitbooks.io/hadoopstudy/content/Conte

Http://itindex.net/blog/2015/01/09/1420751820000.htmlWeka:weka is a collection of machine learning algorithms that can be used for data mining tasks. The algorithm can be applied directly to a dataset or called from its own Java code. Weka contains data preprocessing, classification, regression, clustering, association rules, and visualization tools. It is also ideal for developing new machine learning scenarios.Jmotif: Time series, classification, data Mining Development LibraryJava-ml:java Mac

In daily work, after getting a batch of data, the first thing to do is basic statistical analysis, that is, the descriptive statistics commonly described. Descriptive statistics can help us to further grasp the basic characteristics and laws of data distribution, which is mainly measured and described from three aspects: first, the concentration trend of data distribution, reflecting the degree of convergen

This article mainly on the use of visual charts on the compilation and packaging of Webpack 2 for statistical analysis of the detailed explanation, for you to more intuitive reference.In a total of 17 chapters previously updated, we explained in detail the Webpack 2 from configuration to packaging, compression optimization to debug state, and in this section, we have a more profound understanding of the pac

To view the statistical data steps:(1) Links: http://dev.xiaomi.com/Document dev.xiaomi.com/doc/p=3995/index.html(2) Login--Statistics Service--Your app--View Statistics report--The left menu bar "Integration test"--test equipmentTo see statistics for existing test devices(3) New test equipment method:In activity, after initialization, add:String Deiviceid =. Getdeviceid (this);if (deiviceid!=null) {LOG.D ("Test", "deviceId =" +deviceid);}Get the Devi

###########################begin Hadoop Stat#echo "Begin Hadoop stat Requesttimecount" >>/u1/hadoop-stat/stat.log#/u1/hadoop-1.0.1/bin/hadoop Jar/u1/hadoop-stat/stat.jar Gy.log.mr.requestTime.RequestTimeCount $day#echo "Begin Hadoop stat RequestCount" >>/u1/hadoop-stat/stat.log#/u1/hadoop-1.0.1/bin/hadoop Jar/u1/hadoop-stat/stat.jar Gy.log.mr.request.RequestCount $dayecho "Begin Hadoop stat Nginxcount" >>/u1/hadoop-stat/stat.log/u1/hadoop-1.0.1/bin/hadoop Jar/u1/hadoop-stat/stat.jar Gy.log.mr.ng

=-0.10993962467082698 View the statistical distribution of data Val Colarray = Array ("Age", "yearsmarried", "religiousness", "Education", "occupation", "rating")//view the statistical distribution of the data Val DESCRDF = Data.describe ("Age", "yearsmarried", "religiousness", "Education", "occupation", "rating") DESCRDF: Org.apache.spark.sql.DataFrame = [Summary:string, age:string ... 5 more

sharing link. After the user installs the app via the share link, the app developer can accurately restore the dynamic parameters in each of the shared links via the Android/ios Client API provided by Shareinstall, which we call app sharing source tracking. With this basic technology, app developers and product designers can make the most of their imaginations, presenting amazing promotions in the details of the experience, leaving the user with the best first impression of a personalized insta

observation data distribution characteristicSingle-Variable value grouping: Applies to discrete variables with less variable values.Group distance Grouping: Applies to continuous variables with more variable values.Ex: grouping methods and their watchmaking processesStep1: Determines the number of groups. The determination of group number is mainly used for the observation of data characteristics, so it depends on its data characteristics.Step2: Determines the group spacing for each group. Grou

, but definitely not exceeding (n + 1), then the number of times each I appears, that is, the remainder of a [I] pair (n + 1. There is also a method of traversing twice, which is also the above idea: consider a [I], the current position is I, if you use a to count, its position should be a [I] % (n + 1). How can I handle this position when finding the counting position? Add 1? Obviously not. Here is a trick, that is, adding (n + 1) for two reasons. Adding N ensures that a [I] % (n + 1) remains

extracting the characteristic parameters of this time series, and as the input of the clustering algorithm, realize the classification of this set of data.4. Finding eigenvalues and eigenvectors of matricesThe function Eigen (SM) is used to calculate the eigenvalues and eigenvectors of the matrix SM. The return value of this function is aContains a list of values and vectors two components. Command> EV This list will be assigned to EV. Ev$val represents the eigenvalue vector of SM, and Ev$vec i

.6. View MySQL database table dataMysql> select * from jtxx2; Empty Set (0.00 sec) mysql> Select * from jtxx2;+----------------------------------+-----------+| CLLXBH | hphm |+----------------------------------+-----------+| 32100017000000000220140317000015 | Lu Q58182 | | 32100017000000000220140317000016 | lu QV4662 | | 32100017000000000220140317000019 | su LL8128 | | 32100017000000000220140317000020 | Su CAH367 | | 32100017000000000220140317000023 | LU q7899w

. Item ($col) = $event. $col}$dt. Rows.Add ($row)}# Write to the database!$bulkCopy. WriteToServer ($DT)The above paragraph:Filter current log taken from forwarded eventXML contentAfter execution can go to SQL to check whether the log has been written into SQLSELECT * FROM GeneraleventsYou can see that the log was successfully written to SQL.Finally, it's a Windows scheduled task that automatically executes the PowerShell scripts above every 1 hours.Save the successfully executed script above to

(MyTable, 2, 1)#可以用gmodels的CrossTable生成二维列联表Library (Gmodels)CrossTable (Arthritis$treatment, arthritis$improved)#独立性检验Library (VCD)MyTable Chisq.test (MyTable)#以上代码结果p值为0.001, there is some kind of relationshipMyTable Chisq.test (MyTable)#以上代码结果p值为0.08, it's okay.#以下代码结果p值为0.001, it's related.MyTable Fisher.test (MyTable)#以下代码p值为0.0006, assuming there is no third-order interactionMyTable Mantelhaen.test (MyTable)#以下为相关性度量, the greater the value, the stronger the correlationLibrary (VCD)MyTable

Http://stackoverflow.com/questions/185697/the-most-efficient-way-to-find-top-k-frequent-words-in-a-big-word-sequencehttp://www.geeksforgeeks.org/find-the-k-most-frequent-words-from-a-file/Http://cs.stackexchange.com/questions/26427/word-frequency-with-ordering-in-on-complexityThe idea is roughly as follows:(1) Hash table statistics Word occurrences, and then look for top K appears, wherein the top K can use N*log (k) heap ideas, or quick-line ideas, or bucket sequencing ideas (previously in FBT