aggregate

Querying for a unique value based on the aggregate of another value while grouping on a third value entirely

家住魔仙堡 提交于 2020-01-14 02:16:06
问题 So I know this problem isn't a new one, but I'm trying to wrap my head around it and understand the best way to deal with scenarios like this. Say I have a hypothetical table 'X' that looks like this: GroupID ID (identity) SomeDateTime -------------------------------------------- 1 1000 1/1/01 1 1001 2/2/02 1 1002 3/3/03 2 1003 4/4/04 2 1004 5/5/05 I want to query it so the result set looks like this: ---------------------------------------- 1 1002 3/3/03 2 1004 5/5/05 Basically what I want

Unexpected KeyError Pandas while trying to aggregate multiple functions into new column

社会主义新天地 提交于 2020-01-13 11:04:56
问题 I've looked at the following question: Apply multiple functions to multiple groupby columns and I have data along the lines of p.date p.instrument p.sector \ 11372 2013-02-15 00:00:00 A Health Care 11373 2013-02-15 00:00:00 AA Materials 11374 2013-02-15 00:00:00 AAPL Information Technology 11375 2013-02-15 00:00:00 ABBV Health Care 11376 2013-02-15 00:00:00 ABC Health Care p.industry p.retn p.pfwt b.bwt 11372 Health Care Equipment & Services -5.232929 NaN 0.000832 11373 Aluminum 0.328947 NaN

Unexpected KeyError Pandas while trying to aggregate multiple functions into new column

时光怂恿深爱的人放手 提交于 2020-01-13 11:04:39
问题 I've looked at the following question: Apply multiple functions to multiple groupby columns and I have data along the lines of p.date p.instrument p.sector \ 11372 2013-02-15 00:00:00 A Health Care 11373 2013-02-15 00:00:00 AA Materials 11374 2013-02-15 00:00:00 AAPL Information Technology 11375 2013-02-15 00:00:00 ABBV Health Care 11376 2013-02-15 00:00:00 ABC Health Care p.industry p.retn p.pfwt b.bwt 11372 Health Care Equipment & Services -5.232929 NaN 0.000832 11373 Aluminum 0.328947 NaN

Apache Shiro 学习记录1

泪湿孤枕 提交于 2020-01-13 09:00:58
  最近几天在学习Apache Shiro......看了一些大神们的教程.....感觉收获不少.....但是毕竟教程也只是指引一下方向....即使是精品教程,仍然有很多东西都没有说明....所以自己也稍微研究了一下...记录了一下我的研究发现.... 教程点这里   这篇教程的最后提到了strategy.....然后给出了4个方法.....但是并没有怎么详细说明.....我想说说我的理解.....(我的理解可能会有很多错误)   我想先说说登陆验证的大致流程....大致...... Subject 从用户那里收集完用户名密码以后我们会调用subject.login(token)这个方法去登陆.....Subject是一个接口,没有定义login的具体实现.....Shiro里只有一个类实现了这个接口,是DelegatingSubject这个类.这个类里的方法login方法如下: 1 public void login(AuthenticationToken token) throws AuthenticationException { 2 clearRunAsIdentitiesInternal(); 3 Subject subject = securityManager.login(this, token); 4 5 PrincipalCollection principals

Aggregating daily content

早过忘川 提交于 2020-01-13 05:05:09
问题 I've been attempting to aggregate (some what erratic) daily data. I'm actually working with csv data, but if i recreate it - it would look something like this: library(zoo) dates <- c("20100505", "20100505", "20100506", "20100507") val1 <- c("10", "11", "1", "6") val2 <- c("5", "31", "2", "7") x <- data.frame(dates = dates, val1=val1, val2=val2) z <- read.zoo(x, format = "%Y%m%d") Now i'd like to aggregate this on a daily basis (notice that some times there are >1 datapoint for a day, and

mongodb aggregate 分组统计group count

我们两清 提交于 2020-01-13 01:44:52
1. collection 名称mycol, 数据初始化 //1 { "_id" : ObjectId ( "5e05fe4a32780f42806a80c5" ) , "author" : "tom" , "books" : [ { "type" : "IT类" , "name" : "mongodb" , "price" : NumberInt ( "100" ) } , { "type" : "IT类" , "name" : "java" , "price" : NumberInt ( "50" ) } , { "type" : "文学类" , "name" : "红楼梦" , "price" : NumberInt ( "20" ) } ] , "year" : NumberInt ( "2018" ) } //2 { "_id" : ObjectId ( "5e05fe6032780f42806a80c7" ) , "author" : "tom" , "books" : [ { "type" : "IT类" , "name" : "程序员的修养" , "price" : NumberInt ( "30" ) } , { "type" : "文学类" , "name" : "简爱" , "price" : NumberInt ( "50" ) } , { "type" :

python-迭代器模式

风流意气都作罢 提交于 2020-01-12 09:09:53
源码地址: https://github.com/weilanhanf/PythonDesignPatterns 说明: 集合是用来管理和组织数据对象的数据结构的。集合有两项基本职能:一、批量的存储数据对象,二、在不暴露集合内部结构的条件下向外界提供访问内部元素的接口(可能存在的遍历方式:顺序、逆序遍历,二叉树的广度优先,先序后序中序遍历等)。要使得集合保持整洁和优雅,而不是说令集合内部包含着各种遍历的方法。因此要求将遍历的方法从集合的指责中分离出来,按照不同的遍历需求分别封装成一个个专门遍历集合内部数据的迭代器。这种思想可以最大限度的减少彼此之间的耦合程度,从而建立一个松散耦合的对象网络。职责分离的要点就是要对分离的职责进行封装,并以抽象对象的方式建立彼此之间的关系。 迭代器模式:提供一种方法顺序访问一个聚合对象中各个元素,且不用暴露该对象的内部表示 聚合对象的两个职责: 存储数据,聚合对象的基本职责 遍历数据,既是可变化的,又是可分离的。将遍历数据的行为从聚合对象中分离出来,封装在迭代器对象中。由迭代器来提供遍历聚合对象内部数据的行为,简化聚合对象的设计,更符合单一职责原则。 迭代器模式包含以下4个角色: Iterator(抽象迭代器) ConcreteIterator(具体迭代器) Aggregate(抽象聚合类) ConcreteAggregate(具体聚合类) 实例:

Counting multiple rows in MySQL in one query

倖福魔咒の 提交于 2020-01-12 03:49:26
问题 I currently have a table which stores a load of statistics such as views, downloads, purchases etc. for a multiple number of items. To get a single operation count on each item I can use the following query: SELECT *, COUNT(*) FROM stats WHERE operation = 'view' GROUP BY item_id This gives me all the items and a count of their views. I can then change 'view' to 'purchase' or 'download' for the other variables. However this means three separate calls to the database. Is it possible to get all

Repository Pattern: how to Lazy Load? or, Should I split this Aggregate?

老子叫甜甜 提交于 2020-01-11 14:49:06
问题 I have a domain model that has the concept of an Editor and a Project. An Editor owns a number of Projects, and a Project has not only an Editor owner, but also a number of Editor members. Therefore, an Editor also has a number of "joined" Projects. I am taking a DDD approach to modelling this and using the Repository pattern for persistence. However, I don't grok the pattern well enough yet to determine how I should do this. I'm working on the assumption that Editor and Project are

Moving window method to aggregate data

流过昼夜 提交于 2020-01-11 13:42:12
问题 I have the matrix below: mat<- matrix(c(1,0,0,0,0,0,1,0,0,0,0,0,0,0,2,0, 2,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0, 0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0, 0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0, 0,0,0,0,1,0,0,1,0,1,1,0,0,1,0,1, 1,1,0,0,0,0,0,0,1,0,1,2,1,0,0,0), nrow=16, ncol=6) dimnames(mat)<- list(c("a", "c", "f", "h", "i", "j", "l", "m", "p", "q", "s", "t", "u", "v","x", "z"), c("1", "2", "3", "4", "5", "6")) I need to aggregate columns using a moving window method. First, the window size will be 2, such that the