## Question Concerning Consolidating Values for a Variable based on Value of Another Variable

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Occasional Contributor
Posts: 10

# Question Concerning Consolidating Values for a Variable based on Value of Another Variable

Hello SAS Communities.  I have a question regarding consolidating clusters.

Suppose I have the following dataset where LagLatM and LagLongM at the functions lag(LatM) and lag(LongM) and Change is sqrt((LatM - LagLatM)**2 + (LongM - LagLongM)**2):

 ID cluster LatM Long LagLatM LagLongM Change 7729 cluster_5 8000 6000 . . . 7730 cluster_5 8000 6000 8000 6000 0 7731 cluster_5 8000 6000 8000 6000 0 7732 cluster_5 8000 6000 8000 6000 0 7733 cluster_5 8000 6000 8000 6000 0 7734 cluster_5 8000 6000 8000 6000 0 7735 cluster_5 8000 6000 8000 6000 0 7736 cluster_5 8000 6000 8000 6000 0 7737 cluster_5 8000 6000 8000 6000 0 7738 cluster_5 8000 6000 8000 6000 0 7739 cluster_6 8000 6000 8000 6000 0 7740 cluster_6 8000 6000 8000 6000 0 7741 cluster_6 8000 6000 8000 6000 0 7742 cluster_6 8000 6000 8000 6000 0 7743 cluster_6 8000 6000 8000 6000 0 7744 cluster_6 8000 6000 8000 6000 0 7745 cluster_6 8000 6000 8000 6000 0 7746 cluster_6 8000 6000 8000 6000 0 7747 cluster_6 8000 6000 8000 6000 0 7748 cluster_6 8000 6000 8000 6000 0 7749 cluster_7 8000 6000 8000 6000 0 7750 cluster_7 8000 6000 8000 6000 0 7751 cluster_7 8000 6000 8000 6000 0 7752 cluster_7 8000 6000 8000 6000 0 7753 cluster_7 8000 6000 8000 6000 0 7754 cluster_7 8000 6000 8000 6000 0 7755 cluster_7 8000 6000 8000 6000 0 7756 cluster_7 8000 6000 8000 6000 0 7757 cluster_0 7800 5500 8000 6000 538.5164807 7758 cluster_0 7500 5400 7800 5500 316.227766 7759 cluster_0 7000 5000 7500 5400 640.3124237

How could I consolidate clusters 5, 6, and 7 into one cluster base on the Euclidian difference (Change variable) for LatM and LongM? I would be looking for Change < 200 as a cutoff, which is why cluster_0 in points 7757, 7758, and 7759 aren't included.

Accepted Solutions
Solution
‎01-11-2017 03:38 PM
Super User
Posts: 13,583

## Re: Question Concerning Consolidating Values for a Variable based on Value of Another Variable

My goal is to have entries 7729 - 7756 as a uniform cluster, Cluster_5 (or if possible a different name like Cluster_1000).

The result would look like this:

 ID cluster LatM Long LagLatM LagLongM Change 7729 cluster_5 8000 6000 . . . 7730 cluster_5 8000 6000 8000 6000 0 7731 cluster_5 8000 6000 8000 6000 0 7732 cluster_5 8000 6000 8000 6000 0 7733 cluster_5 8000 6000 8000 6000 0 7734 cluster_5 8000 6000 8000 6000 0 7735 cluster_5 8000 6000 8000 6000 0 7736 cluster_5 8000 6000 8000 6000 0 7737 cluster_5 8000 6000 8000 6000 0

Then the approach with:

data want;

set have;

lclus = lag(cluster);

If change < 200 then cluster = lclus;

drop lclus;

run;

Actually this could be in the same data step where you calculate the change value.

would work assuming that your data is sorted as you need.

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PROC Star
Posts: 2,375

## Re: Question Concerning Consolidating Values for a Variable based on Value of Another Variable

Is the CHANGE value really the one you want to use for aggregating?

You could have CHANGE=0 on 2 clusters while having vary different latitudes in these clusters.

Super User
Posts: 13,583

## Re: Question Concerning Consolidating Values for a Variable based on Value of Another Variable

[ Edited ]

Not quite sure what you mean by consolidate. Is your goal to reduce the number of records or to have a single value in a variable to indicate membership?

As an aside instead of LatM - LagLatM, if LagLatM is the Lagged value you might be able to  replace that code with Dif(LatM) or Abs(Dif(LatM)).

If you want to reduce the number records then something like:

If change = 0 then delete.

Grouping perhaps

lclus = lag(cluster);

If change < 200 then cluster = lclus;

If you could show what you think the output for your example data would look like it would help clarify things.

Occasional Contributor
Posts: 10

## Re: Question Concerning Consolidating Values for a Variable based on Value of Another Variable

Hello user ballardw,

My goal is to have entries 7729 - 7756 as a uniform cluster, Cluster_5 (or if possible a different name like Cluster_1000).

The result would look like this:

 ID cluster LatM Long LagLatM LagLongM Change 7729 cluster_5 8000 6000 . . . 7730 cluster_5 8000 6000 8000 6000 0 7731 cluster_5 8000 6000 8000 6000 0 7732 cluster_5 8000 6000 8000 6000 0 7733 cluster_5 8000 6000 8000 6000 0 7734 cluster_5 8000 6000 8000 6000 0 7735 cluster_5 8000 6000 8000 6000 0 7736 cluster_5 8000 6000 8000 6000 0 7737 cluster_5 8000 6000 8000 6000 0 7738 cluster_5 8000 6000 8000 6000 0 7739 cluster_5 8000 6000 8000 6000 0 7740 cluster_5 8000 6000 8000 6000 0 7741 cluster_5 8000 6000 8000 6000 0 7742 cluster_5 8000 6000 8000 6000 0 7743 cluster_5 8000 6000 8000 6000 0 7744 cluster_5 8000 6000 8000 6000 0 7745 cluster_5 8000 6000 8000 6000 0 7746 cluster_5 8000 6000 8000 6000 0 7747 cluster_5 8000 6000 8000 6000 0 7748 cluster_5 8000 6000 8000 6000 0 7749 cluster_5 8000 6000 8000 6000 0 7750 cluster_5 8000 6000 8000 6000 0 7751 cluster_5 8000 6000 8000 6000 0 7752 cluster_5 8000 6000 8000 6000 0 7753 cluster_5 8000 6000 8000 6000 0 7754 cluster_5 8000 6000 8000 6000 0 7755 cluster_5 8000 6000 8000 6000 0 7756 cluster_5 8000 6000 8000 6000 0 7757 cluster_0 7800 5500 8000 6000 538.5164807 7758 cluster_0 7500 5400 7800 5500 316.227766 7759 cluster_0 7000 5000 7500 5400 640.3124237

Or like this:

 ID cluster LatM Long LagLatM LagLongM Change 7729 cluster_1000 8000 6000 . . . 7730 cluster_1000 8000 6000 8000 6000 0 7731 cluster_1000 8000 6000 8000 6000 0 7732 cluster_1000 8000 6000 8000 6000 0 7733 cluster_1000 8000 6000 8000 6000 0 7734 cluster_1000 8000 6000 8000 6000 0 7735 cluster_1000 8000 6000 8000 6000 0 7736 cluster_1000 8000 6000 8000 6000 0 7737 cluster_1000 8000 6000 8000 6000 0 7738 cluster_1000 8000 6000 8000 6000 0 7739 cluster_1000 8000 6000 8000 6000 0 7740 cluster_1000 8000 6000 8000 6000 0 7741 cluster_1000 8000 6000 8000 6000 0 7742 cluster_1000 8000 6000 8000 6000 0 7743 cluster_1000 8000 6000 8000 6000 0 7744 cluster_1000 8000 6000 8000 6000 0 7745 cluster_1000 8000 6000 8000 6000 0 7746 cluster_1000 8000 6000 8000 6000 0 7747 cluster_1000 8000 6000 8000 6000 0 7748 cluster_1000 8000 6000 8000 6000 0 7749 cluster_1000 8000 6000 8000 6000 0 7750 cluster_1000 8000 6000 8000 6000 0 7751 cluster_1000 8000 6000 8000 6000 0 7752 cluster_1000 8000 6000 8000 6000 0 7753 cluster_1000 8000 6000 8000 6000 0 7754 cluster_1000 8000 6000 8000 6000 0 7755 cluster_1000 8000 6000 8000 6000 0 7756 cluster_1000 8000 6000 8000 6000 0 7757 cluster_0 7800 5500 8000 6000 538.5164807 7758 cluster_0 7500 5400 7800 5500 316.227766 7759 cluster_0 7000 5000 7500 5400 640.3124237

Thank you, and I hope this clarifies.

Solution
‎01-11-2017 03:38 PM
Super User
Posts: 13,583

## Re: Question Concerning Consolidating Values for a Variable based on Value of Another Variable

My goal is to have entries 7729 - 7756 as a uniform cluster, Cluster_5 (or if possible a different name like Cluster_1000).

The result would look like this:

 ID cluster LatM Long LagLatM LagLongM Change 7729 cluster_5 8000 6000 . . . 7730 cluster_5 8000 6000 8000 6000 0 7731 cluster_5 8000 6000 8000 6000 0 7732 cluster_5 8000 6000 8000 6000 0 7733 cluster_5 8000 6000 8000 6000 0 7734 cluster_5 8000 6000 8000 6000 0 7735 cluster_5 8000 6000 8000 6000 0 7736 cluster_5 8000 6000 8000 6000 0 7737 cluster_5 8000 6000 8000 6000 0

Then the approach with:

data want;

set have;

lclus = lag(cluster);

If change < 200 then cluster = lclus;

drop lclus;

run;

Actually this could be in the same data step where you calculate the change value.

would work assuming that your data is sorted as you need.

Occasional Contributor
Posts: 10

## Re: Question Concerning Consolidating Values for a Variable based on Value of Another Variable

Thanks, user ballardw! This works well in context of the study.
Occasional Contributor
Posts: 10

## Re: Question Concerning Consolidating Values for a Variable based on Value of Another Variable

Hello, user ChrisNZ.  This is a sample set of data to prevent violation of personal information.  I am looking for consolidation of these clusters when the variable CHANGE is less than 200.

☑ This topic is solved.