从当前观察中读取下一个 k 观察 [英] Reading next k observation from current observation

问题描述

这是一个非常相似的问题

我的问题与上面链接中的问题有点不同.

My question is a bit different from the one in the above link.

背景

我有一个包含每小时数据的数据集.所以每个对象每天有 24 条记录.现在我想创建 K 新列来代表每个对象的下一个 1,2,...K 每小时记录.如果不存在，则用缺失值替换它们.

I have a data set contains hourly data. So each object has 24 records per day. Now I want to create K new columns represents next 1,2,...K hourly records for each object. If not exist, replace them with missing values.

K 是动态的，由用户定义.

K is dynamic and is defined by users.

必须保留原始订单.无论是在数据步骤中保证还是在最后使用排序.

The original order must be preserved. No matter it's guaranteed in the data steps or by using sorting in the end.

我正在寻找一种有效的方法来实现这一目标.

I'm looking for an efficient way to achieve this.

示例

原始数据:

Object Hour Value 
A      1    2.3
A      2    2.3
A      3    4.0
A      4    1.3

给定 K = 2，期望的输出是

Given K = 2, desired output is

Object Hour Value Value1 Value2
A      1    2.3   2.3    4.0
A      2    2.3   4.0    1.3
A      3    4.0   1.3    .
A      4    1.3   .      .

可能的解决方案

1. 逆序排序 -> 获取之前的 k 条记录 -> 将它们重新排序.

当没有.观察量很大，这不应该是一种理想的方式.

When the no. of observation is large, this shouldn't be an ideal way.

1. proc 扩展.我不熟悉它，因为它从未在我的电脑上获得许可.

1. proc expand. I don't familiar with it cause it's never licensed on my pc.

在数据步骤中使用 point.

retain 语句在数据步骤中.我不确定这是如何工作的.

retain statement inside data step. I'm not sure how this works.

推荐答案

假设这是作为宏变量提供的，这很容易通过左右合并提前完成.对于比总记录数大得多的 K，肯定比转置要快，而且可能比循环 POINT 快.

Assuming this is provided as a macro variable, this is pretty easily done with a side to side merge-ahead. Certainly faster than a transpose for K much larger than the total record count, and probably faster than looping POINTs.

基本上，您将原始数据集合并到自身，并使用 FIRSTOBS 将起始点向下推一个以进行每次连续的合并迭代.如果您有需要保护的 BY 组，这需要一些额外的工作，但这通常并不难管理.

Basically you merge the original dataset to itself, and use FIRSTOBS to push the starting point down one for each successive merge iteration. This needs a bit of extra work if you have BY groups that need protecting, but that's usually not too hard to manage.

这是一个使用 SASHELP.CLASS 的示例:

Here's an example using SASHELP.CLASS:

%let K=5;

%macro makemergesets(k=, datain=, varin=, keepin=);
  %do _i = 2 %to &k;
    &datain (firstobs=&_i rename=&varin.=&varin._&_i. keep=&keepin. &varin.)
  %end;
%mend makemregesets;

data class_all;
  merge sashelp.class
    %makemergesets(k=&k,datain=sashelp.class, varin=age,keepin=)
  ;
run;

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